@misc{kolli_modeling_of_2024, 
author={Kolli, V., Scheider, I., Ovri, H., Giuntini, D., Cyron, C.},
title={Modeling of time-dependent mechanical behavior of oleic acid nanocomposites using nanoindentation},
year={2024},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.mtcomm.2024.108892},
abstract = {Supercrystalline nanocomposites are a burgeoning class of hybrid inorganic–organic materials. Studies showed that self-assembly of iron oxide particles surface-functionalized with organic (e.g. oleic acid) ligands produces a supercrystalline nanocomposite with exceptional mechanical properties. Consequently, significant research has been conducted on these materials to experimentally characterize the mechanical properties of such materials. However, so far all modeling studies used time and rate independent elastoplastic material models. In the light of new experimental results, we propose to extent this view and use time-dependent models to capture viscoelastic behavior. To this end, we quantified this behavior using nanoindentation creep experiments and modeled it using a rheological network model with several parallel Maxwell branches and an additional elasto-plastic branch. We demonstrate how the parameters of such a model can be found using inverse analysis. With the calibrated material model, a good agreement of the time dependent behavior between simulation and experimental results is achieved. Thus, a method is provided to model time dependent behavior using complex non-classical experiments like nanoindentation.},
note = {Online available at: \url{https://doi.org/10.1016/j.mtcomm.2024.108892} (DOI). Kolli, V.; Scheider, I.; Ovri, H.; Giuntini, D.; Cyron, C.: Modeling of time-dependent mechanical behavior of oleic acid nanocomposites using nanoindentation. Materials Today : Communications. 2024. vol. 39, 108892. DOI: 10.1016/j.mtcomm.2024.108892}}
@misc{nourisa_gene_regulatory_2024, 
author={Nourisa, J., Passemiers, A., Shakeri, F., Omidi, M., Helmholz, H., Raimondi, D., Moreau, Y., Tomforde, S., Schlüter, H., Luthringer-Feyerabend, B., Cyron, C.J., Aydin, R.C., Willumeit-Römer, R., Zeller-Plumhoff, B.},
title={Gene regulatory network analysis identifies MYL1, MDH2, GLS, and TRIM28 as the principal proteins in the response of mesenchymal stem cells to Mg2+ ions},
year={2024},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.csbj.2024.04.033},
abstract = {Magnesium (Mg)-based implants have emerged as a promising alternative for orthopedic applications, owing to their bioactive properties and biodegradability. As the implants degrade, Mg2+ ions are released, influencing all surrounding cell types, especially mesenchymal stem cells (MSCs). MSCs are vital for bone tissue regeneration, therefore, it is essential to understand their molecular response to Mg2+ ions in order to maximize the potential of Mg-based biomaterials. In this study, we conducted a gene regulatory network (GRN) analysis to examine the molecular responses of MSCs to Mg2+ ions. We used time-series proteomics data collected at 11 time points across a 21-day period for the GRN construction. We studied the impact of Mg2+ ions on the resulting networks and identified the key proteins and protein interactions affected by the application of Mg2+ ions. Our analysis highlights MYL1, MDH2, GLS, and TRIM28 as the primary targets of Mg2+ ions in the response of MSCs during 1–21 days phase. Our results also identify MDH2-MYL1, MDH2-RPS26, TRIM28-AK1, TRIM28-SOD2, and GLS-AK1 as the critical protein relationships affected by Mg2+ ions. By offering a comprehensive understanding of the regulatory role of Mg2+ ions on MSCs, our study contributes valuable insights into the molecular response of MSCs to Mg-based materials, thereby facilitating the development of innovative therapeutic strategies for orthopedic applications.},
note = {Online available at: \url{https://doi.org/10.1016/j.csbj.2024.04.033} (DOI). Nourisa, J.; Passemiers, A.; Shakeri, F.; Omidi, M.; Helmholz, H.; Raimondi, D.; Moreau, Y.; Tomforde, S.; Schlüter, H.; Luthringer-Feyerabend, B.; Cyron, C.; Aydin, R.; Willumeit-Römer, R.; Zeller-Plumhoff, B.: Gene regulatory network analysis identifies MYL1, MDH2, GLS, and TRIM28 as the principal proteins in the response of mesenchymal stem cells to Mg2+ ions. Computational and Structural Biotechnology Journal. 2024. vol. 23, 1773-1785. DOI: 10.1016/j.csbj.2024.04.033}}
@misc{sardhara_role_of_2024, 
author={Sardhara, T., Shkurmanov, A., Li, Y., Shi, S., Cyron, C.J., Aydin, R.C., Ritter, M.},
title={Role of slice thickness quantification in the 3D reconstruction of FIB tomography data of nanoporous materials},
year={2024},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.ultramic.2023.113878},
abstract = {In focused ion beam (FIB) tomography, a combination of FIB with a scanning electron microscope (SEM) is used for collecting a series of planar images of the microstructure of nanoporous materials. These planar images serve as the basis for reconstructing the three-dimensional microstructure through segmentation algorithms. However, the assumption of a constant distance between consecutively imaged sections is generally invalid due to random variations in the FIB milling process. This variation complicates the accurate reconstruction of the three-dimensional microstructure. Using synthetic FIB tomography data, we present an algorithm that repositions slices according to their actual thickness and interpolates the results using machine learning-based methods. We applied our algorithm to real datasets, comparing two standard approaches of microstructure reconstruction: on-the-fly via image processing and ruler-based via sample structuring. Our findings indicate that the ruler-based method, combined with our novel slice repositioning and interpolation algorithm, exhibits superior performance in reconstructing the microstructure.},
note = {Online available at: \url{https://doi.org/10.1016/j.ultramic.2023.113878} (DOI). Sardhara, T.; Shkurmanov, A.; Li, Y.; Shi, S.; Cyron, C.; Aydin, R.; Ritter, M.: Role of slice thickness quantification in the 3D reconstruction of FIB tomography data of nanoporous materials. Ultramicroscopy. 2024. vol. 256, 113878. DOI: 10.1016/j.ultramic.2023.113878}}
@misc{chandran_studying_the_2024, 
author={Chandran, A., Ganesan, H., Cyron, C.J.},
title={Studying the effects of Nb on high-temperature deformation in TiAl alloys using atomistic simulations},
year={2024},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.matdes.2023.112596},
abstract = {Intermetallic γ(TiAl)-based alloys find their application as high-temperature materials for aero engine and automotive components. Microstructure optimization and microalloying play key roles in optimizing these alloys. Several pioneering experimental works showed improved mechanical properties of γ(TiAl)-based alloys containing Niobium (Nb). Despite Nb being a key alloying element, its contribution remains debated, if not least understood, due to the TiAl microstructure's complexity with hierarchical interfaces. This work examines the effects of Nb on the high-temperature deformation behavior of TiAl alloys using atomistic simulations. These revealed that Nb alloying retarded the stress-induced phase transformation of γ → , favoring a refined microstructure with the dislocation sources from microstructure boundaries and interfaces at high temperature and improving thus the ductility. Our microstructure-informed atomistic models reveal a comprehensive picture of the underlying nanomechanical events.},
note = {Online available at: \url{https://doi.org/10.1016/j.matdes.2023.112596} (DOI). Chandran, A.; Ganesan, H.; Cyron, C.: Studying the effects of Nb on high-temperature deformation in TiAl alloys using atomistic simulations. Materials & Design. 2024. vol. 237, 112569. DOI: 10.1016/j.matdes.2023.112596}}
@misc{munch_on_the_2024, 
author={Munch, P., Ivannikov, V., Cyron, C., Kronbichler, M.},
title={On the construction of an efficient finite-element solver for phase-field simulations of many-particle solid-state-sintering processes},
year={2024},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.commatsci.2023.112589},
abstract = {We present an efficient solver for the simulation of many-particle solid-state-sintering processes. The microstructure evolution is described by a system of equations consisting of one Cahn–Hilliard equation and a set of Allen-Cahn equations to distinguish neighboring particles. The particle packing is discretized in space via multicomponent linear adaptive finite elements and implicitly in time with variable time-step sizes, resulting in a large nonlinear system of equations with strong coupling between all components to be solved. Since on average 10k degrees of freedom per particle are necessary to accurately capture the interface dynamics in 3D, we propose strategies to solve the resulting large and challenging systems. This includes the efficient evaluation of the Jacobian matrix as well as the implementation of Jacobian-free methods by applying state-of-the-art matrix-free algorithms for high and dynamic numbers of components, advances regarding preconditioning, and a fully distributed grain-tracking algorithm. We validate the obtained results, examine in detail the node-level performance and demonstrate the scalability up to 10k particles on modern supercomputers. Such numbers of particles are sufficient to simulate the sintering process in (statistically meaningful) representative volume elements. Our framework thus forms a valuable tool for the virtual design of solid-state-sintering processes for pure metals and their alloys.},
note = {Online available at: \url{https://doi.org/10.1016/j.commatsci.2023.112589} (DOI). Munch, P.; Ivannikov, V.; Cyron, C.; Kronbichler, M.: On the construction of an efficient finite-element solver for phase-field simulations of many-particle solid-state-sintering processes. Computational Materials Science. 2024. DOI: 10.1016/j.commatsci.2023.112589}}
@misc{steglich_strength_and_2023, 
author={Steglich, D., Besson, J., Reinke, I., Helmholz, H., Luczak, M., Garamus, V.M., Wiese, B., Höche, D., Cyron, C.J., Willumeit-Römer, R.},
title={Strength and Ductility Loss of Magnesium-Gadolinium due to Corrosion in Physiological Environment: Experiments and Modeling},
year={2023},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.jmbbm.2023.105939},
abstract = {We propose a computational framework to study the effect of corrosion on the mechanical strength of magnesium (Mg) samples. Our work is motivated by the need to predict the residual strength of biomedical Mg implants after a given period of degradation in a physiological environment. To model corrosion, a mass-diffusion type model is used that accounts for localised corrosion using Weibull statistics. The overall mass loss is prescribed (e.g., based on experimental data). The mechanical behaviour of the Mg samples is modeled by a state-of-the-art Cazacu–Plunkett–Barlat plasticity model with a coupled damage model. This allowed us to study how Mg degradation in immersed samples reduces the mechanical strength over time. We performed a large number of in vitro corrosion experiments and mechanical tests to validate our computational framework. Our framework could predict both the experimentally observed loss of mechanical strength and the ductility due to corrosion for both tension and compression tests.},
note = {Online available at: \url{https://doi.org/10.1016/j.jmbbm.2023.105939} (DOI). Steglich, D.; Besson, J.; Reinke, I.; Helmholz, H.; Luczak, M.; Garamus, V.; Wiese, B.; Höche, D.; Cyron, C.; Willumeit-Römer, R.: Strength and Ductility Loss of Magnesium-Gadolinium due to Corrosion in Physiological Environment: Experiments and Modeling. Journal of the Mechanical Behavior of Biomedical Materials. 2023. vol. 144, 105939. DOI: 10.1016/j.jmbbm.2023.105939}}
@misc{kronbichler_enhancing_data_2023, 
author={Kronbichler, M., Sashko, D., Munch, P.},
title={Enhancing data locality of the conjugate gradient method for high-order matrix-free finite-element implementations},
year={2023},
howpublished = {journal article},
doi = {https://doi.org/10.1177/10943420221107880},
abstract = {This work investigates a variant of the conjugate gradient (CG) method and embeds it into the context of high-order finite-element schemes with fast matrix-free operator evaluation and cheap preconditioners like the matrix diagonal. Relying on a data-dependency analysis and appropriate enumeration of degrees of freedom, we interleave the vector updates and inner products in a CG iteration with the matrix-vector product with only minor organizational overhead. As a result, around 90% of the vector entries of the three active vectors of the CG method are transferred from slow RAM memory exactly once per iteration, with all additional access hitting fast cache memory. Node-level performance analyses and scaling studies on up to 147k cores show that the CG method with the proposed performance optimizations is around two times faster than a standard CG solver as well as optimized pipelined CG and s-step CG methods for large sizes that exceed processor caches, and provides similar performance near the strong scaling limit.},
note = {Online available at: \url{https://doi.org/10.1177/10943420221107880} (DOI). Kronbichler, M.; Sashko, D.; Munch, P.: Enhancing data locality of the conjugate gradient method for high-order matrix-free finite-element implementations. The International Journal of High Performance Computing Applications. 2023. vol. 37, no. 2, 61-81. DOI: 10.1177/10943420221107880}}
@misc{shojaei_peridynamic_elastic_2023, 
author={Shojaei, A., Hermann, A., Seleson, P., Silling, S., Rabczuk, T., Cyron, C.},
title={Peridynamic elastic waves in two-dimensional unbounded domains: Construction of nonlocal Dirichlet-type absorbing boundary conditions},
year={2023},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.cma.2023.115948},
abstract = {The focus of this paper is on application of peridynamics (PD) to propagation of elastic waves in unbounded domains. We construct absorbing boundary conditions (ABCs) derived from a semi-analytical solution of the PD governing equation at the exterior region. This solution is made up of a finite series of plane waves, as fundamental solutions (modes), which satisfy the PD dispersion relations. The modes are adjusted to transmit the energy from the interior region (near field) to the exterior region (far field). The corresponding unknown coefficients of the series are found in terms of the displacement field at a layer of points adjacent to the absorbing boundary. This is accomplished through a collocation procedure at subregions (clouds) around each absorbing point. The proposed ABCs offer appealing advantages, which facilitate their application to PD. They are of Dirichlet-type, hence their implementation is relatively simple as no derivatives of the field variables are required. They are constructed in the time and space domains and thus application of Fourier and Laplace transforms, cumbersome for nonlocal models, is not required. At the discrete level, the modes satisfy the same numerical dispersion relations of the near field, which makes the far-field solution compatible with that of the near field. We scrutinize the performance of the proposed ABCs through several examples. Our investigation shows that the proposed ABCs perform stably in time with an appropriate level of accuracy even in problems characterized by highly-dispersive propagating waves, including crack propagation in semi-unbounded brittle solids.},
note = {Online available at: \url{https://doi.org/10.1016/j.cma.2023.115948} (DOI). Shojaei, A.; Hermann, A.; Seleson, P.; Silling, S.; Rabczuk, T.; Cyron, C.: Peridynamic elastic waves in two-dimensional unbounded domains: Construction of nonlocal Dirichlet-type absorbing boundary conditions. Computer Methods in Applied Mechanics and Engineering. 2023. vol. 407, 115948. DOI: 10.1016/j.cma.2023.115948}}
@misc{munch_efficient_distributed_2023, 
author={Munch, P., Heister, T., Prieto Saavedra, L., Kronbichler, M.},
title={Efficient distributed matrix-free multigrid methods on locally refined meshes for FEM computations},
year={2023},
howpublished = {journal article},
doi = {https://doi.org/10.1145/3580314},
abstract = {This work studies three multigrid variants for matrix-free finite-element computations on locally refined meshes: geometric local smoothing, geometric global coarsening (both h-multigrid), and polynomial global coarsening (a variant of p-multigrid). We have integrated the algorithms into the same framework—the open source finite-element library deal.II—, which allows us to make fair comparisons regarding their implementation complexity, computational efficiency, and parallel scalability as well as to compare the measurements with theoretically derived performance metrics. Serial simulations and parallel weak and strong scaling on up to 147,456 CPU cores on 3,072 compute nodes are presented. The results obtained indicate that global-coarsening algorithms show a better parallel behavior for comparable smoothers due to the better load balance, particularly on the expensive fine levels. In the serial case, the costs of applying hanging-node constraints might be significant, leading to advantages of local smoothing, even though the number of solver iterations needed is slightly higher. When using p- and h-multigrid in sequence (hp-multigrid), the results indicate that it makes sense to decrease the degree of the elements first from a performance point of view due to the cheaper transfer.},
note = {Online available at: \url{https://doi.org/10.1145/3580314} (DOI). Munch, P.; Heister, T.; Prieto Saavedra, L.; Kronbichler, M.: Efficient distributed matrix-free multigrid methods on locally refined meshes for FEM computations. ACM Transactions on Parallel Computing. 2023. vol. 10, no. 1, 3. DOI: 10.1145/3580314}}
@misc{sheikhbahaei_an_efficient_2023, 
author={Sheikhbahaei, P., Mossaiby, F., Shojaei, A.},
title={An efficient peridynamic framework based on the arc-length method for fracture modeling of brittle and quasi-brittle problems with snapping instabilities},
year={2023},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.camwa.2023.02.020},
abstract = {In this paper an implicit peridynamic (PD) framework is devised for the solution of quasi-static problems involving brittle and quasi-brittle fracture. A common way to deal with such problems, in explicit frameworks, is to incorporate artificial damping into the PD equation of motion. This may contribute to non-physical behavior of the system. Also, implicit frameworks, based on the Newton-Raphson method, fail to trace the snap-back behavior. To this end, we develop an implicit peridynamic framework to deal with quasi-static problems involving snap-back/snap-through instabilities. This is achieved through two different approaches. The first approach is based on the global arc-length method applicable to problems with zero displacement constraints. The second one is based on a displacement-controlled arc-length method, suitable for problems with non-zero prescribed displacements. The framework is developed for linear elastic as well as softening (degrading) material damage models, respectively appropriate for brittle and quasi-brittle fracture modeling. The robust performance of the proposed framework, within various loading scenarios and damage models, is demonstrated. To boost the numerical performance of the proposed PD framework, a hybrid integration scheme is employed. We demonstrate the advantages of this scheme over the conventional (standard) one in terms of efficiency for quasi-static problems.},
note = {Online available at: \url{https://doi.org/10.1016/j.camwa.2023.02.020} (DOI). Sheikhbahaei, P.; Mossaiby, F.; Shojaei, A.: An efficient peridynamic framework based on the arc-length method for fracture modeling of brittle and quasi-brittle problems with snapping instabilities. Computers & Mathematics with Applications. 2023. vol. 136, 165-190. DOI: 10.1016/j.camwa.2023.02.020}}
@misc{albaraghtheh_utilizing_computational_2023, 
author={Albaraghtheh, T., Hermann, A., Shojaei, A., Willumeit-Römer, R., Cyron, C.J., Zeller-Plumhoff, B.},
title={Utilizing computational modelling to bridge the gap between in vivo and in vitro degradation rates for Mg-xGd implants},
year={2023},
howpublished = {journal article},
doi = {https://doi.org/10.3390/cmd4020014},
abstract = {Magnesium (Mg) and its alloys are promising materials for temporary bone implants due to their mechanical properties and biocompatibility. The most challenging aspect of Mg-based implants involves adapting the degradation rate to the human body, which requires extensive in vitro and in vivo testing. Given that in vivo tests are significantly more labour-intensive than in vitro and ethics prohibit direct experiments on animals or humans, attempts are commonly undertaken to infer conclusions on in vivo degradation behavior from in vitro experiments. However, there is a wide gap between these tests, and in vitro testing is often a poor predictor of in vivo outcomes. In the development of biodegradable Mg-based implants, considerable efforts are being made to reduce the overall time and cost of in vitro and in vivo testing. Finding a suitable alternative to predict the degradation of Mg alloys, however, remains challenging. We present computational modelling as a possible alternative to bridge the gap between in vitro and in vivo testing, thus reducing overall cost, duration and number of experiments. However, traditional modelling approaches for complex biodegradable systems are still rather time-consuming and require a clear definition of the relations between input parameters and the model result. In this study, Kriging surrogate models based on the peridynamic in vitro degradation model were developed to simulate the degradation behavior for two main alloys, Mg-5Gd and Mg-10Gd, for both in vitro and in vivo cases. Using Kriging surrogate models, the simulation parameters were calibrated to the volume loss data from in vitro and in vivo experiments. In vivo degradation of magnesium has one order of magnitude higher apparent diffusion coefficients than in vitro degradation, thus yielding the higher volume loss observed in vivo than in vitro. On the basis of the diffusivity of the Mg2+ ions modeled under in vitro degradation, Kriging surrogate models were able to simulate the in vivo degradation behavior of Mg-xGd with a ratio between 0.46 and 0.5, indicating that the surrogate-modelling approach is able to bridge the gap between in vitro and in vivo degradation rates for Mg-xGd implants.},
note = {Online available at: \url{https://doi.org/10.3390/cmd4020014} (DOI). Albaraghtheh, T.; Hermann, A.; Shojaei, A.; Willumeit-Römer, R.; Cyron, C.; Zeller-Plumhoff, B.: Utilizing computational modelling to bridge the gap between in vivo and in vitro degradation rates for Mg-xGd implants. Corrosion and Materials Degradation. 2023. vol. 4, no. 2, 274-283. DOI: 10.3390/cmd4020014}}
@misc{hermann_dirichlettype_absorbing_2023, 
author={Hermann, A., Shojaei, A., Seleson, P., Cyron, C.J., Silling, S.A.},
title={Dirichlet-type absorbing boundary conditions for peridynamic scalar waves in two-dimensional viscous media},
year={2023},
howpublished = {journal article},
doi = {https://doi.org/10.1002/nme.7260},
abstract = {Construction of absorbing boundary conditions (ABCs) for nonlocal models is generally challenging, primarily due to the fact that nonlocal operators are commonly associated with volume constrained boundary conditions. Moreover, application of Fourier and Laplace transforms, which are essential for the majority of available methods for ABCs, to nonlocal models is complicated. In this paper, we propose a simple method to construct accurate ABCs for peridynamic scalar wave-type problems in viscous media. The proposed ABCs are constructed in the time and space domains and are of Dirichlet type. Consequently, their implementation is relatively simple, since no derivatives of the wave field are required. The proposed ABCs are derived at the continuum level, from a semi-analytical solution of the exterior domain using harmonic exponential basis functions in space and time (plane-wave modes). The numerical implementation is done using a meshfree collocation approach employed within a boundary layer adjacent to the interior domain boundary. The modes satisfy the peridynamic numerical dispersion relation, resulting in a compatible solution of the interior region (near-field) with that of the exterior region (far-field). The accuracy and stability of the proposed ABCs are demonstrated with several numerical examples in two-dimensional unbounded domains.},
note = {Online available at: \url{https://doi.org/10.1002/nme.7260} (DOI). Hermann, A.; Shojaei, A.; Seleson, P.; Cyron, C.; Silling, S.: Dirichlet-type absorbing boundary conditions for peridynamic scalar waves in two-dimensional viscous media. International Journal for Numerical Methods in Engineering. 2023. vol. 124, no. 16, 3524-3553. DOI: 10.1002/nme.7260}}
@misc{ongaro_multiadaptive_spatial_2023, 
author={Ongaro, G., Shojaei, A., Mossaiby, F., Hermann, A., Cyron, C.J., Trovalusci, P.},
title={Multi-adaptive spatial discretization of bond-based peridynamics},
year={2023},
howpublished = {journal article},
doi = {https://doi.org/10.1007/s10704-023-00709-8},
abstract = {Peridynamic (PD) models are commonly implemented by exploiting a particle-based method referred to as standard scheme. Compared to numerical methods based on classical theories (e.g., the finite element method), PD models using the meshfree standard scheme are typically computationally more expensive mainly for two reasons. First, the nonlocal nature of PD requires advanced quadrature schemes. Second, non-uniform discretizations of the standard scheme are inaccurate and thus typically avoided. Hence, very fine uniform discretizations are applied in the whole domain even in cases where a fine resolution is per se required only in a small part of it (e.g., close to discontinuities and interfaces). In the present study, a new framework is devised to enhance the computational performance of PD models substantially. It applies the standard scheme only to localized regions where discontinuities and interfaces emerge, and a less demanding quadrature scheme to the rest of the domain. Moreover, it uses a multi-grid approach with a fine grid spacing only in critical regions. Because these regions are identified dynamically over time, our framework is referred to as multi-adaptive. The performance of the proposed approach is examined by means of two real-world problems, the Kalthoff–Winkler experiment and the bio-degradation of a magnesium-based bone implant screw. It is demonstrated that our novel framework can vastly reduce the computational cost (for given accuracy requirements) compared to a simple application of the standard scheme.},
note = {Online available at: \url{https://doi.org/10.1007/s10704-023-00709-8} (DOI). Ongaro, G.; Shojaei, A.; Mossaiby, F.; Hermann, A.; Cyron, C.; Trovalusci, P.: Multi-adaptive spatial discretization of bond-based peridynamics. International Journal of Fracture. 2023. vol. 244, 1-24. DOI: 10.1007/s10704-023-00709-8}}
@misc{mossaiby_multiadaptive_coupling_2023, 
author={Mossaiby, F., Sheikhbahaei, P., Shojaei, A.},
title={Multi-adaptive coupling of finite element meshes with peridynamic grids: robust implementation and potential applications},
year={2023},
howpublished = {journal article},
doi = {https://doi.org/10.1007/s00366-022-01656-z},
abstract = {Coupling of methods based on the classical continuum mechanics (CCM), with peridynamic (PD) models is a recent hot topic in the realm of computational mechanics. In the coupled models, to optimize the usage of computational resources, usually the application of PD (the more demanding procedure) is restricted to critical areas of the domain affected by discontinuities such as propagating cracks. The remaining parts of the domain are described by a more efficient CCM-based model such as the finite element method (FEM). Here, we develop a coupled FEM/PD model for dynamic fracture modeling. The proposed method simultaneously features the following: (1) it can adaptively change the coupling configuration throughout the simulation such that only critical zones, on the verge of crack nucleation/propagation, are tackled by the PD procedure, and (2) it appropriately supports different grid spacing of PD and FEM parts. We refer to a model possessing both the features as multi-adaptive. This is crucial for a highly efficient coupling scheme. The performance of the proposed method is analyzed in terms of accuracy and computational efficiency through different numerical examples. The results show that the proposed method is superior to using a refined PD model, since it provides the same level of accuracy at a much lower computational cost. As a novel application, we present the promising results of a crack propagation problem in an unbounded domain, solved using classical artificial boundary conditions on an outer FEM layer.},
note = {Online available at: \url{https://doi.org/10.1007/s00366-022-01656-z} (DOI). Mossaiby, F.; Sheikhbahaei, P.; Shojaei, A.: Multi-adaptive coupling of finite element meshes with peridynamic grids: robust implementation and potential applications. Engineering with Computers. 2023. vol. 39, 2807-2828. DOI: 10.1007/s00366-022-01656-z}}
@misc{munch_stageparallel_fully_2023, 
author={Munch, P., Dravins, I., Kronbichler, M., Neytcheva, M.},
title={Stage-parallel fully implicit Runge-Kutta implementations with optimal multilevel preconditioners at the scaling limit},
year={2023},
howpublished = {journal article},
doi = {https://doi.org/10.1137/22M1503270},
abstract = {We present an implementation of a stage-parallel preconditioner for Radau IIA type fully implicit Runge–Kutta methods, which approximates the inverse of the Runge–Kutta matrix AQ from the Butcher tableau by the lower triangular matrix resulting from an LU decomposition and diagonalizes the system with as many blocks as stages. For the transformed system, we employ a block preconditioner where each block is distributed and solved by a subgroup of processes in parallel. For combination of partial results, we use either a communication pattern resembling Cannon’s algorithm or shared memory. A performance model and a large set of performance studies (including strong-scaling runs with up to 150k processes on 3k compute nodes) conducted for a time-dependent heat problem, using matrix-free finite element methods, indicate that the stage-parallel implementation can reach higher throughputs near the scaling limit. The achievable speedup increases linearly with the number of stages and is bounded by the number of stages. Furthermore, we show that the presented stage-parallel concepts are also applicable to the case that AQ is directly diagonalized, which requires either complex arithmetic or solutions of two-by-two blocks, both exposing about half the parallelism. Alternatively to distributing stages and assigning them to distinct processes, we discuss the possibility of batching operations from different stages together.},
note = {Online available at: \url{https://doi.org/10.1137/22M1503270} (DOI). Munch, P.; Dravins, I.; Kronbichler, M.; Neytcheva, M.: Stage-parallel fully implicit Runge-Kutta implementations with optimal multilevel preconditioners at the scaling limit. SIAM Journal on Scientific Computing. 2023. S71-S96. DOI: 10.1137/22M1503270}}
@misc{schiessler_searching_the_2023, 
author={Schiessler, E.J., Würger, T., Vaghefinazari, B., Lamaka, S.V., Meißner, R.H., Cyron, C.J., Zheludkevich, M.L., Feiler, C., Aydin, R.C.},
title={Searching the Chemical Space for Effective Magnesium Dissolution Modulators: A Deep Learning Approach using Sparse Features},
year={2023},
howpublished = {journal article},
doi = {https://doi.org/10.1038/s41529-023-00391-0},
abstract = {Small organic molecules can alter the degradation rates of the magnesium alloy ZE41. However, identifying suitable candidate compounds from the vast chemical space requires sophisticated tools. The information contained in only a few molecular descriptors derived from recursive feature elimination was previously shown to hold the potential for determining such candidates using deep neural networks. We evaluate the capability of these networks to generalise by blind testing them on 15 randomly selected, completely unseen compounds. We find that their generalisation ability is still somewhat limited, most likely due to the relatively small amount of available training data. However, we demonstrate that our approach is scalable; meaning deficiencies caused by data limitations can presumably be overcome as the data availability increases. Finally, we illustrate the influence and importance of well-chosen descriptors towards the predictive power of deep neural networks.},
note = {Online available at: \url{https://doi.org/10.1038/s41529-023-00391-0} (DOI). Schiessler, E.; Würger, T.; Vaghefinazari, B.; Lamaka, S.; Meißner, R.; Cyron, C.; Zheludkevich, M.; Feiler, C.; Aydin, R.: Searching the Chemical Space for Effective Magnesium Dissolution Modulators: A Deep Learning Approach using Sparse Features. npj Materials Degradation. 2023. vol. 7, 74. DOI: 10.1038/s41529-023-00391-0}}
@misc{sheikhbahaei_analyzing_cyclic_2023, 
author={Sheikhbahaei, P., Mossaiby, F., Shojaei, A.},
title={Analyzing cyclic loading behavior of concrete structures: A peridynamic approach with softening models and validation},
year={2023},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.tafmec.2023.104165},
abstract = {This study introduces a bond-based peridynamic (BB-PD) approach for analyzing concrete structures under cyclic loading, with the aim of comprehensively addressing crack propagation and concrete crushing phenomena. The model’s generality is enhanced by eliminating the need for calibration. Additionally, a practical method is proposed to incorporate the hardening effect of steel bars, making it applicable to reinforced concrete structures. The accuracy of the approach is evaluated through numerical examples under various loading conditions, and the results are validated by comparing them with standard experiments using an implicit arc-length method. By eliminating the use of constant or adaptive parameters typically found in explicit methods, the arc-length method, combined with the proposed material model, effectively captures the behavior of both ordinary and reinforced concretes subjected to cyclic loading.},
note = {Online available at: \url{https://doi.org/10.1016/j.tafmec.2023.104165} (DOI). Sheikhbahaei, P.; Mossaiby, F.; Shojaei, A.: Analyzing cyclic loading behavior of concrete structures: A peridynamic approach with softening models and validation. Theoretical and Applied Fracture Mechanics. 2023. vol. 128, 104165. DOI: 10.1016/j.tafmec.2023.104165}}
@misc{arndt_the_dealii_2023, 
author={Arndt, D., Bangerth, W., Bergbauer, M., Feder, M., Fehling, M., Heinz, J., Heister, T., Heltai, L., Kronbichler, M., Maier, M., Munch, P., Pelteret, J.P., Turcksin, B., Wells, D., Zampini, S.},
title={The deal.II Library, Version 9.5},
year={2023},
howpublished = {journal article},
doi = {https://doi.org/10.1515/jnma-2023-0089},
abstract = {This paper provides an overview of the new features of the finite element library deal.II, version 9.5.},
note = {Online available at: \url{https://doi.org/10.1515/jnma-2023-0089} (DOI). Arndt, D.; Bangerth, W.; Bergbauer, M.; Feder, M.; Fehling, M.; Heinz, J.; Heister, T.; Heltai, L.; Kronbichler, M.; Maier, M.; Munch, P.; Pelteret, J.; Turcksin, B.; Wells, D.; Zampini, S.: The deal.II Library, Version 9.5. Journal of Numerical Mathematics. 2023. vol. 31, no. 3, 231. DOI: 10.1515/jnma-2023-0089}}
@misc{paukner_what_are_2023, 
author={Paukner, D., Eichinger, J., Cyron, C.J.},
title={What are the key mechanical mechanisms governing integrin mediated cell migration in three dimensional fiber networks?},
year={2023},
howpublished = {journal article},
doi = {https://doi.org/https://doi.org/10.1007/s10237-023-01709-2},
abstract = {Cell migration plays a vital role in numerous processes such as development, wound healing, or cancer. It is well known that numerous complex mechanisms are involved in cell migration. However, so far it remains poorly understood what are the key mechanisms required to produce the main characteristics of this behavior. The reason is a methodological one. In experimental studies, specific factors and mechanisms can be promoted or inhibited. However, while doing so, there can always be others in the background which play key roles but which have simply remained unattended so far. This makes it very difficult to validate any hypothesis about a minimal set of factors and mechanisms required to produce cell migration. To overcome this natural limitation of experimental studies, we developed a computational model where cells and extracellular matrix fibers are represented by discrete mechanical objects on the micrometer scale. In this model, we had exact control of the mechanisms by which cells and matrix fibers interacted with each other. This enabled us to identify the key mechanisms required to produce physiologically realistic cell migration (including advanced phenomena such as durotaxis and a biphasic relation between migration efficiency and matrix stiffness). We found that two main mechanisms are required to this end: a catch-slip bond of individual integrins and cytoskeletal actin-myosin contraction. Notably, more advanced phenomena such as cell polarization or details of mechanosensing were not necessary to qualitatively reproduce the main characteristics of cell migration observed in experiments.},
note = {Online available at: \url{https://doi.org/https://doi.org/10.1007/s10237-023-01709-2} (DOI). Paukner, D.; Eichinger, J.; Cyron, C.: What are the key mechanical mechanisms governing integrin mediated cell migration in three dimensional fiber networks?. Biomechanics and Modeling in Mechanobiology. 2023. vol. 22, 1177-1192. DOI: https://doi.org/10.1007/s10237-023-01709-2}}
@misc{gebauer_a_homogenized_2023, 
author={Gebauer, A.M., Pfaller, M.R., Braeu, F.A., Cyron, C.J., Wall, W.A.},
title={A homogenized constrained mixture model of cardiac growth and remodeling: analyzing mechanobiological stability and reversal},
year={2023},
howpublished = {journal article},
doi = {https://doi.org/10.1007/s10237-023-01747-w},
abstract = {Cardiac growth and remodeling (G&R) patterns change ventricular size, shape, and function both globally and locally. Biomechanical, neurohormonal, and genetic stimuli drive these patterns through changes in myocyte dimension and fibrosis. We propose a novel microstructure-motivated model that predicts organ-scale G&R in the heart based on the homogenized constrained mixture theory. Previous models, based on the kinematic growth theory, reproduced consequences of G&R in bulk myocardial tissue by prescribing the direction and extent of growth but neglected underlying cellular mechanisms. In our model, the direction and extent of G&R emerge naturally from intra- and extracellular turnover processes in myocardial tissue constituents and their preferred homeostatic stretch state. We additionally propose a method to obtain a mechanobiologically equilibrated reference configuration. We test our model on an idealized 3D left ventricular geometry and demonstrate that our model aims to maintain tensional homeostasis in hypertension conditions. In a stability map, we identify regions of stable and unstable G&R from an identical parameter set with varying systolic pressures and growth factors. Furthermore, we show the extent of G&R reversal after returning the systolic pressure to baseline following stage 1 and 2 hypertension. A realistic model of organ-scale cardiac G&R has the potential to identify patients at risk of heart failure, enable personalized cardiac therapies, and facilitate the optimal design of medical devices.},
note = {Online available at: \url{https://doi.org/10.1007/s10237-023-01747-w} (DOI). Gebauer, A.; Pfaller, M.; Braeu, F.; Cyron, C.; Wall, W.: A homogenized constrained mixture model of cardiac growth and remodeling: analyzing mechanobiological stability and reversal. Biomechanics and Modeling in Mechanobiology. 2023. vol. 22, 1983-2002. DOI: 10.1007/s10237-023-01747-w}}
@misc{davoodikermani_simulated_annealing_2023, 
author={Davoodi Kermani, I., Dyckhoff, L., Aydin, R.C., Huber, N., Cyron, C.J.},
title={Simulated annealing framework for generating representative volume elements of materials with complex ligamentous microstructures},
year={2023},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.commatsci.2023.112302},
abstract = {At the microscale, various materials from biological tissues to nanoporous metals are formed by networks of ligaments. Here we propose a highly efficient simulated annealing (SA) framework for generating synthetic representative volume elements (RVE) of such materials. It can produce RVE where the microstructural characteristics both on the network level (e.g., node valency and ligament length) and on the level of individual ligaments (e.g., curvature) can be predefined by the user via probability distributions. As an application example of our framework, we generate a large variety of RVEs, analyze their mechanical properties by the finite element method, and establish through this approach links between microstructural descriptors and macromechanical properties of materials with ligamentous microstructures.},
note = {Online available at: \url{https://doi.org/10.1016/j.commatsci.2023.112302} (DOI). Davoodi Kermani, I.; Dyckhoff, L.; Aydin, R.; Huber, N.; Cyron, C.: Simulated annealing framework for generating representative volume elements of materials with complex ligamentous microstructures. Computational Materials Science. 2023. vol. 228, 112302. DOI: 10.1016/j.commatsci.2023.112302}}
@misc{golshan_lethedem_an_2023, 
author={Golshan, S., Munch, P., Gassmöller, R., Kronbichler, M., Blais, B.},
title={Lethe-DEM: an open-source parallel discrete element solver with load balancing},
year={2023},
howpublished = {journal article},
doi = {https://doi.org/10.1007/s40571-022-00478-6},
abstract = {Approximately 75% of the raw material and 50% of the products in the chemical industry are granular materials. The discrete element method (DEM) provides detailed insights of phenomena at particle scale, and it is therefore often used for modeling granular materials. However, because DEM tracks the motion and contact of individual particles separately, its computational cost increases nonlinearly O(nplog(np)) – O(n2p) (depending on the algorithm) with the number of particles (np). In this article, we introduce a new open-source parallel DEM software with load balancing: Lethe-DEM. Lethe-DEM, a module of Lethe, consists of solvers for two-dimensional and three-dimensional DEM simulations. Load balancing allows Lethe-DEM to significantly increase the parallel efficiency by ≈25–70% depending on the granular simulation. We explain the fundamental modules of Lethe-DEM, its software architecture, and the governing equations. Furthermore, we verify Lethe-DEM with several tests including analytical solutions and comparison with other software. Comparisons with experiments in a flat-bottomed silo, wedge-shaped silo, and rotating drum validate Lethe-DEM. We investigate the strong and weak scaling of Lethe-DEM with 1≤nc≤192 and 32≤nc≤320 processes, respectively, with and without load balancing. The strong-scaling analysis is performed on the wedge-shaped silo and rotating drum simulations, while for the weak-scaling analysis, we use a dam-break simulation. The best scalability of Lethe-DEM is obtained in the range of 5000≤np/nc≤15,000. Finally, we demonstrate that large-scale simulations can be carried out with Lethe-DEM using the simulation of a three-dimensional cylindrical silo with np=4.3×106 on 320 cores.},
note = {Online available at: \url{https://doi.org/10.1007/s40571-022-00478-6} (DOI). Golshan, S.; Munch, P.; Gassmöller, R.; Kronbichler, M.; Blais, B.: Lethe-DEM: an open-source parallel discrete element solver with load balancing. Computational Particle Mechanics. 2023. vol. 10, no. 1, 77-96. DOI: 10.1007/s40571-022-00478-6}}
@misc{dipasquale_a_stress_2022, 
author={Dipasquale, D., Sarego, G., Prapamonthon, P., Yooyen, S., Shojaei, A.},
title={A Stress Tensor-based Failure Criterion for Ordinary State-based ‎Peridynamic Models‎},
year={2022},
howpublished = {journal article},
doi = {https://doi.org/10.22055/JACM.2021.38664.3264},
abstract = {Peridynamics is a recent nonlocal theory of continuum mechanics that is suitable to describe fracture problems in solid mechanics. In this paper, a new failure criterion based on the stress field is developed by adopting the damage correspondence model in the ordinary state-based peridynamic theory. The proposed stress tensor-based failure criterion is capable of predicting more accurately crack propagation in the mixed mode I-II fracture problems different from other failure criteria in peridynamics. The effectiveness of the proposed model is demonstrated by performing several examples of mixed-mode dynamic fracture in brittle materials.},
note = {Online available at: \url{https://doi.org/10.22055/JACM.2021.38664.3264} (DOI). Dipasquale, D.; Sarego, G.; Prapamonthon, P.; Yooyen, S.; Shojaei, A.: A Stress Tensor-based Failure Criterion for Ordinary State-based ‎Peridynamic Models‎. Journal of Applied and Computational Mechanics. 2022. vol. 8, no. 2, 617-628. DOI: 10.22055/JACM.2021.38664.3264}}
@misc{fehn_numerical_evidence_2022, 
author={Fehn, N., Kronbichler, M., Munch, P., Wall, W.},
title={Numerical evidence of anomalous energy dissipation in incompressible Euler flows: towards grid-converged results for the inviscid Taylor-Green problem},
year={2022},
howpublished = {journal article},
doi = {https://doi.org/10.1017/jfm.2021.1003},
abstract = {The well-known energy dissipation anomaly in the inviscid limit, related to velocity singularities according to Onsager, still needs to be demonstrated by numerical experiments. The present work contributes to this topic through high-resolution numerical simulations of the inviscid three-dimensional Taylor–Green vortex problem using a novel high-order discontinuous Galerkin discretisation approach for the incompressible Euler equations. The main methodological ingredient is the use of a discretisation scheme with inbuilt dissipation mechanisms, as opposed to discretely energy-conserving schemes, which – by construction – rule out the occurrence of anomalous dissipation. We investigate effective spatial resolution up to 81923 (defined based on the 2π-periodic box) and make the interesting phenomenological observation that the kinetic energy evolution does not tend towards exact energy conservation for increasing spatial resolution of the numerical scheme, but that the sequence of discrete solutions seemingly converges to a solution with non-zero kinetic energy dissipation rate. Taking the fine-resolution simulation as a reference, we measure grid-convergence with a relative L2-error of 0.27% for the temporal evolution of the kinetic energy and 3.52% for the kinetic energy dissipation rate against the dissipative fine-resolution simulation. The present work raises the question of whether such results can be seen as a numerical confirmation of the famous energy dissipation anomaly. Due to the relation between anomalous energy dissipation and the occurrence of singularities for the incompressible Euler equations according to Onsager's conjecture, we elaborate on an indirect approach for the identification of finite-time singularities that relies on energy arguments.},
note = {Online available at: \url{https://doi.org/10.1017/jfm.2021.1003} (DOI). Fehn, N.; Kronbichler, M.; Munch, P.; Wall, W.: Numerical evidence of anomalous energy dissipation in incompressible Euler flows: towards grid-converged results for the inviscid Taylor-Green problem. Journal of Fluid Mechanics. 2022. vol. 932, A40. DOI: 10.1017/jfm.2021.1003}}
@misc{shojaei_a_hybrid_2022, 
author={Shojaei, A., Hermann, A., Cyron, C., Seleson, P., Silling, S.},
title={A hybrid meshfree discretization to improve the numerical performance of peridynamic models},
year={2022},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.cma.2021.114544},
abstract = {Efficient and accurate calculation of spatial integrals is of major interest in the numerical implementation of peridynamics (PD). The standard way to perform this calculation is a particle-based approach that discretizes the strong form of the PD governing equation. This approach has rapidly been adopted by the PD community since it offers some advantages. It is computationally cheaper than other available schemes, can conveniently handle material separation, and effectively deals with nonlinear PD models. Nevertheless, PD models are still computationally very expensive compared with those based on the classical continuum mechanics theory, particularly for large-scale problems in three dimensions. This results from the nonlocal nature of the PD theory which leads to interactions of each node of a discretized body with multiple surrounding nodes. Here, we propose a new approach to significantly boost the numerical efficiency of PD models. We propose a discretization scheme that employs a simple collocation procedure and is truly meshfree; i.e., it does not depend on any background integration cells. In contrast to the standard scheme, the proposed scheme requires a much smaller set of neighboring nodes (keeping the same physical length scale) to achieve a specific accuracy and is thus computationally more efficient. Our new scheme is applicable to the case of linear PD models and within neighborhoods where the solution can be approximated by smooth basis functions. Therefore, to fully exploit the advantages of both the standard and the proposed schemes, a hybrid discretization is presented that combines both approaches within an adaptive framework. The high performance of the developed framework is illustrated by several numerical examples, including brittle fracture and corrosion problems in two and three dimensions.},
note = {Online available at: \url{https://doi.org/10.1016/j.cma.2021.114544} (DOI). Shojaei, A.; Hermann, A.; Cyron, C.; Seleson, P.; Silling, S.: A hybrid meshfree discretization to improve the numerical performance of peridynamic models. Computer Methods in Applied Mechanics and Engineering. 2022. vol. 391, 114544. DOI: 10.1016/j.cma.2021.114544}}
@misc{hermann_combining_peridynamic_2022, 
author={Hermann, A., Shojaei, A., Steglich, D., Höche, D., Zeller-Plumhof, B., Cyron, C.},
title={Combining peridynamic and finite element simulations to capture the corrosion of degradable bone implants and to predict their residual strength},
year={2022},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.ijmecsci.2022.107143},
abstract = {This paper proposes a computational framework to describe the biodegradation of magnesium (Mg)-based bone implants. It is based on a sequential combination of two models: an electrochemical corrosion model to compute the mass loss of the implant over several weeks combined with a mechanical model to assess its residual mechanical strength. The first model uses a peridynamic (PD) corrosion model to tackle the complex moving boundary of the corroding material in an efficient manner. The results of this corrosion simulation are mapped to a finite element (FE) model by way of a damage variable. Subsequently, the FE model is used for mechanical analysis. To use PD for such a complex problem, we proposed three innovative improvements compared to state-of-the-art PD models: (1) application of an adaptive multi-grid discretization in space and an implicit time-stepping algorithm enabling an efficient simulation of the complex implant geometry over prolonged periods, (2) novel non-local Dirichlet absorbing boundary conditions to truncate the simulation domain in the close neighborhood of the implant of interest without prohibitive losses of accuracy, and (3) selection of suitable non-local kernel functions and parameter calibration on the basis of experimental data by an evolutionary algorithm. We demonstrate that this framework can capture the loss of implant mass due to corrosion for typical alloys such as Mg-5Gd and Mg-10Gd. Moreover, we point out how this framework can be used in the future to predict the declining mechanical strength of bone screws subject to biocorrosion over several weeks.},
note = {Online available at: \url{https://doi.org/10.1016/j.ijmecsci.2022.107143} (DOI). Hermann, A.; Shojaei, A.; Steglich, D.; Höche, D.; Zeller-Plumhof, B.; Cyron, C.: Combining peridynamic and finite element simulations to capture the corrosion of degradable bone implants and to predict their residual strength. International Journal of Mechanical Sciences. 2022. vol. 220, 107143. DOI: 10.1016/j.ijmecsci.2022.107143}}
@misc{sardhara_training_deep_2022, 
author={Sardhara, T., Aydin, R.C., Li, Y., Piché, N., Gauvin, R., Cyron, C.J., Ritter, M.},
title={Training Deep Neural Networks to Reconstruct Nanoporous Structures From FIB Tomography Images Using Synthetic Training Data},
year={2022},
howpublished = {journal article},
doi = {https://doi.org/10.3389/fmats.2022.837006},
abstract = {Focused ion beam (FIB) tomography is a destructive technique used to collect three-dimensional (3D) structural information at a resolution of a few nanometers. For FIB tomography, a material sample is degraded by layer-wise milling. After each layer, the current surface is imaged by a scanning electron microscope (SEM), providing a consecutive series of cross-sections of the three-dimensional material sample. Especially for nanoporous materials, the reconstruction of the 3D microstructure of the material, from the information collected during FIB tomography, is impaired by the so-called shine-through effect. This effect prevents a unique mapping between voxel intensity values and material phase (e.g., solid or void). It often substantially reduces the accuracy of conventional methods for image segmentation. Here we demonstrate how machine learning can be used to tackle this problem. A bottleneck in doing so is the availability of sufficient training data. To overcome this problem, we present a novel approach to generate synthetic training data in the form of FIB-SEM images generated by Monte Carlo simulations. Based on this approach, we compare the performance of different machine learning architectures for segmenting FIB tomography data of nanoporous materials. We demonstrate that two-dimensional (2D) convolutional neural network (CNN) architectures processing a group of adjacent slices as input data as well as 3D CNN perform best and can enhance the segmentation performance significantly.},
note = {Online available at: \url{https://doi.org/10.3389/fmats.2022.837006} (DOI). Sardhara, T.; Aydin, R.; Li, Y.; Piché, N.; Gauvin, R.; Cyron, C.; Ritter, M.: Training Deep Neural Networks to Reconstruct Nanoporous Structures From FIB Tomography Images Using Synthetic Training Data. Frontiers in Materials. 2022. vol. 9, 837006. DOI: 10.3389/fmats.2022.837006}}
@misc{fuchs_a_versatile_2022, 
author={Fuchs, S.L., Praegla, P.M., Cyron, C.J., Wall, W.A., Meier, C.},
title={A versatile SPH modeling framework for coupled microfluid-powder dynamics in additive manufacturing: binder jetting, material jetting, directed energy deposition and powder bed fusion},
year={2022},
howpublished = {journal article},
doi = {https://doi.org/10.1007/s00366-022-01724-4},
abstract = {Many additive manufacturing (AM) technologies rely on powder feedstock, which is fused to form the final part either by melting or by chemical binding with subsequent sintering. In both cases, process stability and resulting part quality depend on dynamic interactions between powder particles and a fluid phase, i.e., molten metal or liquid binder. The present work proposes a versatile computational modeling framework for simulating such coupled microfluid-powder dynamics problems involving thermo-capillary flow and reversible phase transitions. In particular, a liquid and a gas phase are interacting with a solid phase that consists of a substrate and mobile powder particles while simultaneously considering temperature-dependent surface tension and wetting effects. In case of laser–metal interactions, the effect of rapid evaporation is incorporated through additional mechanical and thermal interface fluxes. All phase domains are spatially discretized using smoothed particle hydrodynamics. The method’s Lagrangian nature is beneficial in the context of dynamically changing interface topologies due to phase transitions and coupled microfluid-powder dynamics. Special care is taken in the formulation of phase transitions, which is crucial for the robustness of the computational scheme. While the underlying model equations are of a very general nature, the proposed framework is especially suitable for the mesoscale modeling of various AM processes. To this end, the generality and robustness of the computational modeling framework is demonstrated by several application-motivated examples representing the specific AM processes binder jetting, material jetting, directed energy deposition, and powder bed fusion. Among others, it is shown how the dynamic impact of droplets in binder jetting or the evaporation-induced recoil pressure in powder bed fusion leads to powder motion, distortion of the powder packing structure, and powder particle ejection.},
note = {Online available at: \url{https://doi.org/10.1007/s00366-022-01724-4} (DOI). Fuchs, S.; Praegla, P.; Cyron, C.; Wall, W.; Meier, C.: A versatile SPH modeling framework for coupled microfluid-powder dynamics in additive manufacturing: binder jetting, material jetting, directed energy deposition and powder bed fusion. Engineering with Computers. 2022. vol. 38, no. 6, 4853-4877. DOI: 10.1007/s00366-022-01724-4}}
@misc{linka_predicting_and_2022, 
author={Linka, K., Cavinato, C., Humphrey, J.D., Cyron, C.J.},
title={Predicting and understanding arterial elasticity from key microstructural features by bidirectional deep learning},
year={2022},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.actbio.2022.05.039},
abstract = {Microstructural features and mechanical properties are closely related in all soft biological tissues. Both yet exhibit considerable inter-individual differences and are affected by factors such as aging and disease and its progression. Histological analysis, modern in situ imaging, and biomechanical testing have deepened our understanding of these complex interrelations, yet two key questions remain: (1) Given the specific microstructure, can one predict the macroscopic mechanical properties without mechanical testing? (2) Can one quantify individual contributions of the different microstructural features to the macroscopic mechanical properties in an automated, systematic and largely unbiased way? Here we propose a bidirectional deep learning architecture to address these two questions. Our architecture uses data from standard histological analyses, two-photon microscopy and biaxial biomechanical testing. Its capabilities are demonstrated by predicting with high accuracy () the evolving mechanical properties of the murine aorta during maturation and aging. Moreover, our architecture reveals that the extracellular matrix composition and organization are the most prominent factors governing the macroscopic mechanical properties of the tissues studied herein.},
note = {Online available at: \url{https://doi.org/10.1016/j.actbio.2022.05.039} (DOI). Linka, K.; Cavinato, C.; Humphrey, J.; Cyron, C.: Predicting and understanding arterial elasticity from key microstructural features by bidirectional deep learning. Acta Biomaterialia. 2022. vol. 147, 63-72. DOI: 10.1016/j.actbio.2022.05.039}}
@misc{arndt_the_dealii_2022, 
author={Arndt, D., Bangerth, W., Feder, M., Fehling, M., Gassmöller, R., Heister, T., Heltai, L., Kronbichler, M., Maier, M., Munch, P., Pelteret, J.-P., Sticko, S., Turcksin, B., Wells, D.},
title={The deal.II Library, Version 9.4},
year={2022},
howpublished = {journal article},
doi = {https://doi.org/10.1515/jnma-2022-0054},
abstract = {This paper provides an overview of the new features of the finite element library deal.II, version 9.4.},
note = {Online available at: \url{https://doi.org/10.1515/jnma-2022-0054} (DOI). Arndt, D.; Bangerth, W.; Feder, M.; Fehling, M.; Gassmöller, R.; Heister, T.; Heltai, L.; Kronbichler, M.; Maier, M.; Munch, P.; Pelteret, J.; Sticko, S.; Turcksin, B.; Wells, D.: The deal.II Library, Version 9.4. Journal of Numerical Mathematics. 2022. vol. 30, no. 3, 231-246. DOI: 10.1515/jnma-2022-0054}}
@misc{fuchs_an_sph_2021, 
author={Fuchs, S., Meier, C., Wall, W., Cyron, C.},
title={An SPH framework for fluid–solid and contact interaction problems including thermo-mechanical coupling and reversible phase transitions},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.1186/s40323-021-00200-w},
abstract = {The present work proposes an approach for fluid–solid and contact interaction problems including thermo-mechanical coupling and reversible phase transitions. The solid field is assumed to consist of several arbitrarily-shaped, undeformable but mobile rigid bodies, that are evolved in time individually and allowed to get into mechanical contact with each other. The fluid field generally consists of multiple liquid or gas phases. All fields are spatially discretized using the method of smoothed particle hydrodynamics (SPH). This approach is especially suitable in the context of continually changing interface topologies and dynamic phase transitions without the need for additional methodological and computational effort for interface tracking as compared to mesh- or grid-based methods. Proposing a concept for the parallelization of the computational framework, in particular concerning a computationally efficient evaluation of rigid body motion, is an essential part of this work. Finally, the accuracy and robustness of the proposed framework is demonstrated by several numerical examples in two and three dimensions, involving multiple rigid bodies, two-phase flow, and reversible phase transitions, with a focus on two potential application scenarios in the fields of engineering and biomechanics: powder bed fusion additive manufacturing (PBFAM) and disintegration of food boluses in the human stomach. The efficiency of the parallel computational framework is demonstrated by a strong scaling analysis.},
note = {Online available at: \url{https://doi.org/10.1186/s40323-021-00200-w} (DOI). Fuchs, S.; Meier, C.; Wall, W.; Cyron, C.: An SPH framework for fluid–solid and contact interaction problems including thermo-mechanical coupling and reversible phase transitions. Advanced Modeling and Simulation in Engineering Sciences. 2021. vol. 8, no. 1, 15. DOI: 10.1186/s40323-021-00200-w}}
@misc{linka_constitutive_artificial_2021, 
author={Linka, K., Hillgärtner, M., Abdolazizi, K., Aydin, R., Itskov, M., Cyron, C.},
title={Constitutive artificial neural networks: A fast and general approach to predictive data-driven constitutive modeling by deep learning},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.jcp.2020.110010},
abstract = {In this paper we introduce constitutive artificial neural networks (CANNs), a novel machine learning architecture for data-driven modeling of the mechanical constitutive behavior of materials. CANNs are able to incorporate by their very design information from three different sources, namely stress-strain data, theoretical knowledge from materials theory, and diverse additional information (e.g., about microstructure or materials processing). CANNs can easily and efficiently be implemented in standard computational software. They require only a low-to-moderate amount of training data and training time to learn without human guidance the constitutive behavior also of complex nonlinear and anisotropic materials. Moreover, in a simple academic example we demonstrate how the input of microstructural data can endow CANNs with the ability to describe not only the behavior of known materials but to predict also the properties of new materials where no stress-strain data are available yet. This ability may be particularly useful for the future in-silico design of new materials. The developed source code of the CANN architecture and accompanying example data sets are available at https://github.com/ConstitutiveANN/CANN.},
note = {Online available at: \url{https://doi.org/10.1016/j.jcp.2020.110010} (DOI). Linka, K.; Hillgärtner, M.; Abdolazizi, K.; Aydin, R.; Itskov, M.; Cyron, C.: Constitutive artificial neural networks: A fast and general approach to predictive data-driven constitutive modeling by deep learning. Journal of Computational Physics. 2021. vol. 429, 110010. DOI: 10.1016/j.jcp.2020.110010}}
@misc{ganesan_quantifying_the_2021, 
author={Ganesan, H., Scheider, I., Cyron, C.},
title={Quantifying the High-Temperature Separation Behavior of Lamellar Interfaces in γ-Titanium Aluminide Under Tensile Loading by Molecular Dynamics},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.3389/fmats.2020.602567},
abstract = {γ-titanium aluminide (TiAl) alloys with fully lamellar microstructure possess excellent properties for high-temperature applications. Such fully lamellar microstructure has interfaces at different length scales. The separation behavior of the lamellae at these interfaces is crucial for the mechanical properties of the whole material. Unfortunately, quantifying it by experiments is difficult. Therefore, we use molecular dynamics (MD) simulations to this end. Specifically, we study the high-temperature separation behavior under tensile loading of the four different kinds of lamellar interfaces appearing in TiAl, namely, the γ/α2, γ/γPT, γ/γTT, and γ/γRB interfaces. In our simulations, we use two different atomistic interface models, a defect-free (Type-1) model and a model with preexisting voids (Type-2). Clearly, the latter is more physical but studying the former also helps to understand the role of defects. Our simulation results show that among the four interfaces studied, the γ/α2 interface possesses the highest yield strength, followed by the γ/γPT, γ/γTT, and γ/γRB interfaces. For Type-1 models, our simulations reveal failure at the interface for all γ/γ interfaces but not for the γ/α2 interface. By contrast, for Type-2 models, we observe for all the four interfaces failure at the interface. Our atomistic simulations provide important data to define the parameters of traction–separation laws and cohesive zone models, which can be used in the framework of continuum mechanical modeling of TiAl. Temperature-dependent model parameters were identified, and the complete traction–separation behavior was established, in which interface elasticity, interface plasticity, and interface damage could be distinguished. By carefully eliminating the contribution of bulk deformation from the interface behavior, we were able to quantify the contribution of interface plasticity and interface damage, which can also be related to the dislocation evolution and void nucleation in the atomistic simulations.},
note = {Online available at: \url{https://doi.org/10.3389/fmats.2020.602567} (DOI). Ganesan, H.; Scheider, I.; Cyron, C.: Quantifying the High-Temperature Separation Behavior of Lamellar Interfaces in γ-Titanium Aluminide Under Tensile Loading by Molecular Dynamics. Frontiers in Materials. 2021. vol. 7, 602567. DOI: 10.3389/fmats.2020.602567}}
@misc{schnabel_crystal_plasticity_2021, 
author={Schnabel, J., Scheider, I.},
title={Crystal Plasticity Modeling of Creep in Alloys with Lamellar Microstructures at the Example of Fully Lamellar TiAl},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.3389/fmats.2020.581187},
abstract = {A crystal plasticity model of the creep behavior of alloys with lamellar microstructures is presented. The model is based on the additive decomposition of the plastic strain into a part that describes the instantaneous (i.e., high strain rate) plastic response due to loading above the yield point, and a part that captures the viscoplastic deformation at elevated temperatures. In order to reproduce the transition from the primary to the secondary creep stage in a physically meaningful way, the competition between work hardening and recovery is modeled in terms of the evolving dislocation density. The evolution model for the dislocation density is designed to account for the significantly different free path lengths of slip systems in lamellar microstructures depending on their orientation with respect to the lamella interface. The established model is applied to reproduce and critically discuss experimental findings on the creep behavior of polysynthetically twinned TiAl crystals. Although the presented crystal plasticity model is designed with the creep behavior of fully lamellar TiAl in mind, it is by no means limited to these specific alloys. The constitutive model and many of the discussed assumptions also apply to the creep behavior of other crystalline materials with lamellar microstructures.},
note = {Online available at: \url{https://doi.org/10.3389/fmats.2020.581187} (DOI). Schnabel, J.; Scheider, I.: Crystal Plasticity Modeling of Creep in Alloys with Lamellar Microstructures at the Example of Fully Lamellar TiAl. Frontiers in Materials. 2021. vol. 7, 581187. DOI: 10.3389/fmats.2020.581187}}
@misc{eichinger_mechanical_homeostasis_2021, 
author={Eichinger, J., Haeusel, L., Paukner, D., Aydin, R., Humphrey, J., Cyron, C.},
title={Mechanical homeostasis in tissue equivalents: a review},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.1007/s10237-021-01433-9},
abstract = {There is substantial evidence that growth and remodeling of load bearing soft biological tissues is to a large extent controlled by mechanical factors. Mechanical homeostasis, which describes the natural tendency of such tissues to establish, maintain, or restore a preferred mechanical state, is thought to be one mechanism by which such control is achieved across multiple scales. Yet, many questions remain regarding what promotes or prevents homeostasis. Tissue equivalents, such as collagen gels seeded with living cells, have become an important tool to address these open questions under well-defined, though limited, conditions. This article briefly reviews the current state of research in this area. It summarizes, categorizes, and compares experimental observations from the literature that focus on the development of tension in tissue equivalents. It focuses primarily on uniaxial and biaxial experimental studies, which are well-suited for quantifying interactions between mechanics and biology. The article concludes with a brief discussion of key questions for future research in this field.},
note = {Online available at: \url{https://doi.org/10.1007/s10237-021-01433-9} (DOI). Eichinger, J.; Haeusel, L.; Paukner, D.; Aydin, R.; Humphrey, J.; Cyron, C.: Mechanical homeostasis in tissue equivalents: a review. Biomechanics and Modeling in Mechanobiology. 2021. vol. 20, no. 3, 833-850. DOI: 10.1007/s10237-021-01433-9}}
@misc{giuntini_deformation_behavior_2021, 
author={Giuntini, D., Davydok, A., Blankenburg, M., Domènech, B., Bor, B., Li, M., Scheider, I., Krywka, C., Müller, M., Schneider, G.},
title={Deformation Behavior of Cross-Linked Supercrystalline Nanocomposites: An in Situ SAXS/WAXS Study during Uniaxial Compression},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.1021/acs.nanolett.0c05041},
abstract = {With the ever-expanding functional applications of supercrystalline nanocomposites (a relatively new category of materials consisting of organically functionalized nanoparticles arranged into periodic structures), it becomes necessary to ensure their structural stability and understand their deformation and failure mechanisms. Inducing the cross-linking of the functionalizing organic ligands, for instance, leads to a remarkable enhancement of the nanocomposites’ mechanical properties. It is however still unknown how the cross-linked organic phase redistributes applied loads, how the supercrystalline lattice accommodates the imposed deformations, and thus in general what phenomena govern the overall material’s mechanical response. This work elucidates these aspects for cross-linked supercrystalline nanocomposites through an in situ small- and wide-angle X-ray scattering study combined with uniaxial pressing. Because of this loading condition, it emerges that the cross-linked ligands effectively carry and distribute loads homogeneously throughout the nanocomposites, while the superlattice deforms via rotation, slip, and local defects generation.},
note = {Online available at: \url{https://doi.org/10.1021/acs.nanolett.0c05041} (DOI). Giuntini, D.; Davydok, A.; Blankenburg, M.; Domènech, B.; Bor, B.; Li, M.; Scheider, I.; Krywka, C.; Müller, M.; Schneider, G.: Deformation Behavior of Cross-Linked Supercrystalline Nanocomposites: An in Situ SAXS/WAXS Study during Uniaxial Compression. Nano Letters. 2021. vol. 21, no. 7, 2891-2897. DOI: 10.1021/acs.nanolett.0c05041}}
@misc{zellerplumhoff_evaluating_the_2021, 
author={Zeller-Plumhoff, B., Laipple, D., Slominska, H., Iskhakova, K., Longo, E., Hermann, A., Flenner, S., Greving, I., Storm, M., Willumeit-Römer, R.},
title={Evaluating the morphology of the degradation layer of pure magnesium via 3D imaging at resolutions below 40 nm},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.bioactmat.2021.04.009},
abstract = {Magnesium is attractive for the application as a temporary bone implant due to its inherent biodegradability, non-toxicity and suitable mechanical properties. The degradation process of magnesium in physiological environments is complex and is thought to be a diffusion-limited transport problem. We use a multi-scale imaging approach using micro computed tomography and transmission X-ray microscopy (TXM) at resolutions below 40 nm. Thus, we are able to evaluate the nanoporosity of the degradation layer and infer its impact on the degradation process of pure magnesium in two physiological solutions. Magnesium samples were degraded in simulated body fluid (SBF) or Dulbecco's modified Eagle's medium (DMEM) with 10% fetal bovine serum (FBS) for one to four weeks. TXM reveals the three-dimensional interconnected pore network within the degradation layer for both solutions. The pore network morphology and degradation layer composition are similar for all samples. By contrast, the degradation layer thickness in samples degraded in SBF was significantly higher and more inhomogeneous than in DMEM+10%FBS. Distinct features could be observed within the degradation layer of samples degraded in SBF, suggesting the formation of microgalvanic cells, which are not present in samples degraded in DMEM+10%FBS. The results suggest that the nanoporosity of the degradation layer and the resulting ion diffusion processes therein have a limited influence on the overall degradation process. This indicates that the influence of organic components on the dampening of the degradation rate by the suppression of microgalvanic degradation is much greater in the present study.},
note = {Online available at: \url{https://doi.org/10.1016/j.bioactmat.2021.04.009} (DOI). Zeller-Plumhoff, B.; Laipple, D.; Slominska, H.; Iskhakova, K.; Longo, E.; Hermann, A.; Flenner, S.; Greving, I.; Storm, M.; Willumeit-Römer, R.: Evaluating the morphology of the degradation layer of pure magnesium via 3D imaging at resolutions below 40 nm. Bioactive Materials. 2021. vol. 6, no. 12, 4368-4376. DOI: 10.1016/j.bioactmat.2021.04.009}}
@misc{linka_machine_learningaugmented_2021, 
author={Linka, K., Thüring, J., Rieppo, L., Aydin, R., Cyron, C., Kuhl, C., Merhof, D., Truhn, D., Nebelung, S.},
title={Machine learning-augmented and microspectroscopy-informed multiparametric MRI for the non-invasive prediction of articular cartilage composition},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.joca.2020.12.022},
abstract = {Once trained for the clinical setting, advanced machine learning techniques, in particular ANNs, may be used to non-invasively determine compositional features of cartilage based on quantitative MRI parameters with potential implications for the diagnosis of (early) degeneration and for the monitoring of therapeutic outcomes.},
note = {Online available at: \url{https://doi.org/10.1016/j.joca.2020.12.022} (DOI). Linka, K.; Thüring, J.; Rieppo, L.; Aydin, R.; Cyron, C.; Kuhl, C.; Merhof, D.; Truhn, D.; Nebelung, S.: Machine learning-augmented and microspectroscopy-informed multiparametric MRI for the non-invasive prediction of articular cartilage composition. Osteoarthritis and Cartilage. 2021. vol. 29, no. 4, 592-602. DOI: 10.1016/j.joca.2020.12.022}}
@misc{brandstaeter_global_sensitivity_2021, 
author={Brandstaeter, S., Fuchs, S., Biehler, J., Aydin, R., Wall, W., Cyron, C.},
title={Global Sensitivity Analysis of a Homogenized Constrained Mixture Model of Arterial Growth and Remodeling},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.1007/s10659-021-09833-9},
abstract = {Growth and remodeling in arterial tissue have attracted considerable attention over the last decade. Mathematical models have been proposed, and computational studies with these have helped to understand the role of the different model parameters. So far it remains, however, poorly understood how much of the model output variability can be attributed to the individual input parameters and their interactions. To clarify this, we propose herein a global sensitivity analysis, based on Sobol indices, for a homogenized constrained mixture model of aortic growth and remodeling. In two representative examples, we found that 54–80% of the long term output variability resulted from only three model parameters. In our study, the two most influential parameters were the one characterizing the ability of the tissue to increase collagen production under increased stress and the one characterizing the collagen half-life time. The third most influential parameter was the one characterizing the strain-stiffening of collagen under large deformation. Our results suggest that in future computational studies it may - at least in scenarios similar to the ones studied herein - suffice to use population average values for the other parameters. Moreover, our results suggest that developing methods to measure the said three most influential parameters may be an important step towards reliable patient-specific predictions of the enlargement of abdominal aortic aneurysms in clinical practice.},
note = {Online available at: \url{https://doi.org/10.1007/s10659-021-09833-9} (DOI). Brandstaeter, S.; Fuchs, S.; Biehler, J.; Aydin, R.; Wall, W.; Cyron, C.: Global Sensitivity Analysis of a Homogenized Constrained Mixture Model of Arterial Growth and Remodeling. Journal of Elasticity. 2021. vol. 145, no. 1-2, 191-221. DOI: 10.1007/s10659-021-09833-9}}
@misc{eichinger_a_computational_2021, 
author={Eichinger, J.F., Grill, M.J., Kermani, I.D., Aydin, R.C., Wall, W.A., Humphrey, J.D., Cyron, C.J.},
title={A computational framework for modeling cell–matrix interactions in soft biological tissues},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.1007/s10237-021-01480-2},
abstract = {Living soft tissues appear to promote the development and maintenance of a preferred mechanical state within a defined tolerance around a so-called set point. This phenomenon is often referred to as mechanical homeostasis. In contradiction to the prominent role of mechanical homeostasis in various (patho)physiological processes, its underlying micromechanical mechanisms acting on the level of individual cells and fibers remain poorly understood, especially how these mechanisms on the microscale lead to what we macroscopically call mechanical homeostasis. Here, we present a novel computational framework based on the finite element method that is constructed bottom up, that is, it models key mechanobiological mechanisms such as actin cytoskeleton contraction and molecular clutch behavior of individual cells interacting with a reconstructed three-dimensional extracellular fiber matrix. The framework reproduces many experimental observations regarding mechanical homeostasis on short time scales (hours), in which the deposition and degradation of extracellular matrix can largely be neglected. This model can serve as a systematic tool for future in silico studies of the origin of the numerous still unexplained experimental observations about mechanical homeostasis.},
note = {Online available at: \url{https://doi.org/10.1007/s10237-021-01480-2} (DOI). Eichinger, J.; Grill, M.; Kermani, I.; Aydin, R.; Wall, W.; Humphrey, J.; Cyron, C.: A computational framework for modeling cell–matrix interactions in soft biological tissues. Biomechanics and Modeling in Mechanobiology. 2021. vol. 20, 1851-1870. DOI: 10.1007/s10237-021-01480-2}}
@misc{fuchs_a_novel_2021, 
author={Fuchs, S., Meier, C., Wall, W., Cyron, C.},
title={A novel smoothed particle hydrodynamics and finite element coupling scheme for fluid–structure interaction: The sliding boundary particle approach},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.cma.2021.113922},
abstract = {A novel numerical formulation for solving fluid–structure interaction (FSI) problems is proposed where the fluid field is spatially discretized using smoothed particle hydrodynamics (SPH) and the structural field using the finite element method (FEM). As compared to fully mesh- or grid-based FSI frameworks, due to the Lagrangian nature of SPH this framework can be easily extended to account for more complex fluids consisting of multiple phases and dynamic phase transitions. Moreover, this approach facilitates the handling of large deformations of the fluid domain respectively the fluid–structure interface without additional methodological and computational efforts. In particular, to achieve an accurate representation of interaction forces between fluid particles and structural elements also for strongly curved interface geometries, the novel sliding boundary particle approach is proposed to ensure full support of SPH particles close to the interface. The coupling of the fluid and the structural field is based on a Dirichlet–Neumann partitioned approach, where the fluid field is the Dirichlet partition with prescribed interface displacements and the structural field is the Neumann partition subject to interface forces. To overcome instabilities inherent to weakly coupled schemes an iterative fixed-point coupling scheme is employed. Several numerical examples in form of well-known benchmark tests are considered to validate the accuracy, stability, and robustness of the proposed formulation. Finally, the filling process of a highly flexible thin-walled balloon-like container is studied, representing a model problem close to potential application scenarios of the proposed scheme in the field of biomechanics.},
note = {Online available at: \url{https://doi.org/10.1016/j.cma.2021.113922} (DOI). Fuchs, S.; Meier, C.; Wall, W.; Cyron, C.: A novel smoothed particle hydrodynamics and finite element coupling scheme for fluid–structure interaction: The sliding boundary particle approach. Computer Methods in Applied Mechanics and Engineering. 2021. vol. 383, 113922. DOI: 10.1016/j.cma.2021.113922}}
@misc{steglich_prediction_of_2021, 
author={Steglich, D., Besson, J.},
title={Prediction of deformation and failure anisotropy for thin magnesium sheets under mixed-mode loading},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.mechmat.2021.104064},
abstract = {The plastic deformation and the failure behavior of a third generation magnesium AZ31 sheet is studied under quasi-static tensile, compressive, and mixed mode loading conditions at room temperature. While the deformation anisotropy is found to be less pronounced compared to previously investigated rolled sheets of this alloy, a strong dependence of the failure strain on the sheets orientation is experienced. This failure anisotropy is further studied and quantified using mixed-mode tests realized using a modified Arcan fixture. The irreversible deformation is modeled in the framework of finite elements using two coupled anisotropic plastic potentials. The model parameters are calibrated using the global force-elongation record of the tested samples. For the prediction of failure, an uncoupled damage model based on transformation of strain rates is developed and applied. It is shown that this model is able to predict the observed edge failure of notched specimens with good accuracy. The model predictions for the smooth tensile tests are analyzed in detail by full-field FE analyses to understand the interaction between strain localization and predicted damage evolution.},
note = {Online available at: \url{https://doi.org/10.1016/j.mechmat.2021.104064} (DOI). Steglich, D.; Besson, J.: Prediction of deformation and failure anisotropy for thin magnesium sheets under mixed-mode loading. Mechanics of Materials. 2021. vol. 163, 104064. DOI: 10.1016/j.mechmat.2021.104064}}
@misc{munch_hyperdeal_an_2021, 
author={Munch, P., Kormann, K., Kronbichler, M.},
title={hyper.deal: An Efficient, Matrix-free Finite-element Library for High-dimensional Partial Differential Equations},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.1145/3469720},
abstract = {This work presents the efficient, matrix-free finite-element library hyper.deal for solving partial differential equations in two up to six dimensions with high-order discontinuous Galerkin methods. It builds upon the low-dimensional finite-element library deal.II to create complex low-dimensional meshes and to operate on them individually. These meshes are combined via a tensor product on the fly, and the library provides new special-purpose highly optimized matrix-free functions exploiting domain decomposition as well as shared memory via MPI-3.0 features. Both node-level performance analyses and strong/weak-scaling studies on up to 147,456 CPU cores confirm the efficiency of the implementation. Results obtained with the library hyper.deal are reported for high-dimensional advection problems and for the solution of the Vlasov–Poisson equation in up to six-dimensional phase space.},
note = {Online available at: \url{https://doi.org/10.1145/3469720} (DOI). Munch, P.; Kormann, K.; Kronbichler, M.: hyper.deal: An Efficient, Matrix-free Finite-element Library for High-dimensional Partial Differential Equations. ACM Transactions on Mathematical Software. 2021. vol. 47, no. 4, 33. DOI: 10.1145/3469720}}
@misc{arndt_the_dealii_2021, 
author={Arndt, D., Bangerth, W., Blais, B., Fehling, M., Gassmöller, R., Heister, T., Heltai, L., Kronbichler, M., Köcher, U., Maier, M., Munch, P., Pelteret, J., Proell, S., Simon, K., Turcksin, B., Wells, D., Zhang, J.},
title={The deal.II library, Version 9.3},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.1515/jnma-2021-0081},
abstract = {This paper provides an overview of the new features of the finite element library deal.II, version 9.3.},
note = {Online available at: \url{https://doi.org/10.1515/jnma-2021-0081} (DOI). Arndt, D.; Bangerth, W.; Blais, B.; Fehling, M.; Gassmöller, R.; Heister, T.; Heltai, L.; Kronbichler, M.; Köcher, U.; Maier, M.; Munch, P.; Pelteret, J.; Proell, S.; Simon, K.; Turcksin, B.; Wells, D.; Zhang, J.: The deal.II library, Version 9.3. Journal of Numerical Mathematics. 2021. vol. 29, no. 3, 171-186. DOI: 10.1515/jnma-2021-0081}}
@misc{bor_constitutive_and_2021, 
author={Bor, B., Giuntini, D., Domènech, B., Plunkett, A., Kampferbeck, M., Vossmeyer, T., Weller, H., Scheider, I., Schneider, G.},
title={Constitutive and fracture behavior of ultra-strong supercrystalline nanocomposites},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.1063/5.0056616},
abstract = {Supercrystalline nanocomposites are a new class of hybrid and nanostructured materials that can reach exceptional mechanical strength and can be fabricated at low temperatures. Hierarchically arranged, they bridge the gap from the nano- to the macro-scale. Even though their mechanical properties are starting to be characterized, their constitutive behavior is still largely unexplored. Here, the mechanical behavior of supercrystalline nanocomposites of iron oxide nanoparticles, surface-functionalized with oleic acid and oleyl phosphate ligands, is investigated in both bending and compression, with loading–unloading tests. A new bar geometry is implemented to better detect deformation prior to unstable crack propagation, and notched bending bars are tested to evaluate fracture toughness. Micro-mechanical tests result in the values of strength and elastic modulus that are extremely high for supercrystals, reaching record-high numbers in the oleic acid-based nanocomposites, which also show a significant tension–compression asymmetry. The constitutive behavior of both materials is predominantly linear elastic, with some more marked nonlinearities arising in the oleyl phosphate-based nanocomposites. The fracture toughness of both types of nanocomposites, ∼0.3 MPa√m, suggests that extrinsic toughening, associated with both material composition and nanostructure, plays an important role. Fractographic observations reveal analogies with shear and cleavage in atomic crystals. The influence of material composition, nanostructure, and processing method on the mechanical behavior of the nanocomposites is analyzed.},
note = {Online available at: \url{https://doi.org/10.1063/5.0056616} (DOI). Bor, B.; Giuntini, D.; Domènech, B.; Plunkett, A.; Kampferbeck, M.; Vossmeyer, T.; Weller, H.; Scheider, I.; Schneider, G.: Constitutive and fracture behavior of ultra-strong supercrystalline nanocomposites. Applied Physics Reviews. 2021. vol. 8, no. 3, 031414. DOI: 10.1063/5.0056616}}
@misc{linka_unraveling_the_2021, 
author={Linka, K., Reiter, N., Würges, J., Schicht, M., Bräuer, L., Cyron, C., Paulsen, F., Budday, S.},
title={Unraveling the Local Relation Between Tissue Composition and Human Brain Mechanics Through Machine Learning},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.3389/fbioe.2021.704738},
abstract = {The regional mechanical properties of brain tissue are not only key in the context of brain injury and its vulnerability towards mechanical loads, but also affect the behavior and functionality of brain cells. Due to the extremely soft nature of brain tissue, its mechanical characterization is challenging. The response to loading depends on length and time scales and is characterized by nonlinearity, compression-tension asymmetry, conditioning, and stress relaxation. In addition, the regional heterogeneity–both in mechanics and microstructure–complicates the comprehensive understanding of local tissue properties and its relation to the underlying microstructure. Here, we combine large-strain biomechanical tests with enzyme-linked immunosorbent assays (ELISA) and develop an extended type of constitutive artificial neural networks (CANNs) that can account for viscoelastic effects. We show that our viscoelastic constitutive artificial neural network is able to describe the tissue response in different brain regions and quantify the relevance of different cellular and extracellular components for time-independent (nonlinearity, compression-tension-asymmetry) and time-dependent (hysteresis, conditioning, stress relaxation) tissue mechanics, respectively. Our results suggest that the content of the extracellular matrix protein fibronectin is highly relevant for both the quasi-elastic behavior and viscoelastic effects of brain tissue. While the quasi-elastic response seems to be largely controlled by extracellular matrix proteins from the basement membrane, cellular components have a higher relevance for the viscoelastic response. Our findings advance our understanding of microstructure - mechanics relations in human brain tissue and are valuable to further advance predictive material models for finite element simulations or to design biomaterials for tissue engineering and 3D printing applications.},
note = {Online available at: \url{https://doi.org/10.3389/fbioe.2021.704738} (DOI). Linka, K.; Reiter, N.; Würges, J.; Schicht, M.; Bräuer, L.; Cyron, C.; Paulsen, F.; Budday, S.: Unraveling the Local Relation Between Tissue Composition and Human Brain Mechanics Through Machine Learning. Frontiers in Bioengineering and Biotechnology. 2021. vol. 9, 704738. DOI: 10.3389/fbioe.2021.704738}}
@misc{holzapfel_predictive_constitutive_2021, 
author={Holzapfel, G., Linka, K., Sherifova, S., Cyron, C.},
title={Predictive constitutive modelling of arteries by deep learning},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.1098/rsif.2021.0411},
abstract = {The constitutive modelling of soft biological tissues has rapidly gained attention over the last 20 years. Current constitutive models can describe the mechanical properties of arterial tissue. Predicting these properties from microstructural information, however, remains an elusive goal. To address this challenge, we are introducing a novel hybrid modelling framework that combines advanced theoretical concepts with deep learning. It uses data from mechanical tests, histological analysis and images from second-harmonic generation. In this first proof of concept study, our hybrid modelling framework is trained with data from 27 tissue samples only. Even such a small amount of data is sufficient to be able to predict the stress–stretch curves of tissue samples with a median coefficient of determination of R2 = 0.97 from microstructural information, as long as one limits the scope to tissue samples whose mechanical properties remain in the range commonly encountered. This finding suggests that deep learning could have a transformative impact on the way we model the constitutive properties of soft biological tissues.},
note = {Online available at: \url{https://doi.org/10.1098/rsif.2021.0411} (DOI). Holzapfel, G.; Linka, K.; Sherifova, S.; Cyron, C.: Predictive constitutive modelling of arteries by deep learning. Journal of the Royal Society Interface. 2021. vol. 18, no. 182, 20210411. DOI: 10.1098/rsif.2021.0411}}
@misc{abdolazizi_concentrationspecific_constitutive_2021, 
author={Abdolazizi, K., Linka, K., Sprenger, J., Neidhardt, M., Schlaefer, A., Cyron, C.},
title={Concentration-Specific Constitutive Modeling of Gelatin Based on Artificial Neural Networks},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.1002/pamm.202000284},
abstract = {Gelatin phantoms are frequently used in the development of surgical devices and medical imaging techniques. They exhibit mechanical properties similar to soft biological tissues [1] but can be handled at a much lower cost. Moreover, they enable a better reproducibility of experiments. Accurate constitutive models for gelatin are therefore of great interest for biomedical engineering. In particular it is important to capture the dependence of mechanical properties of gelatin on its concentration. Herein we propose a simple machine learning approach to this end. It uses artificial neural networks (ANN) for learning from indentation data the relation between the concentration of ballistic gelatin and the resulting mechanical properties.},
note = {Online available at: \url{https://doi.org/10.1002/pamm.202000284} (DOI). Abdolazizi, K.; Linka, K.; Sprenger, J.; Neidhardt, M.; Schlaefer, A.; Cyron, C.: Concentration-Specific Constitutive Modeling of Gelatin Based on Artificial Neural Networks. PAMM: Proceedings in Applied Mathematics and Mechanics. 2021. vol. 20, no. 1, e202000284. DOI: 10.1002/pamm.202000284}}
@misc{eichinger_what_do_2021, 
author={Eichinger, J.F., Paukner, D., Aydin, R.C., Wall, W.A., Humphrey, J.D., Cyron, C.J.},
title={What do cells regulate in soft tissues on short time scales?},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.actbio.2021.07.054},
abstract = {Cells within living soft biological tissues seem to promote the maintenance of a mechanical state within a defined range near a so-called set-point. This mechanobiological process is often referred to as mechanical homeostasis. During this process, cells interact with the fibers of the surrounding extracellular matrix (ECM). It remains poorly understood, however, what individual cells actually regulate during these interactions, and how these micromechanical regulations are translated to the tissue-level to lead to what we observe as biomaterial properties. Herein, we examine this question by a combination of experiments, theoretical analysis, and computational modeling. We demonstrate that on short time scales (hours) - during which deposition and degradation of ECM fibers can largely be neglected - cells appear to not regulate the stress / strain in the ECM or their own shape, but rather only the contractile forces that they exert on the surrounding ECM.},
note = {Online available at: \url{https://doi.org/10.1016/j.actbio.2021.07.054} (DOI). Eichinger, J.; Paukner, D.; Aydin, R.; Wall, W.; Humphrey, J.; Cyron, C.: What do cells regulate in soft tissues on short time scales?. Acta Biomaterialia. 2021. vol. 134, 348-356. DOI: 10.1016/j.actbio.2021.07.054}}
@misc{schiessler_neural_network_2021, 
author={Schiessler, E., Aydin, R., Linka, K., Cyron, C.},
title={Neural network surgery: Combining training with topology optimization},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.neunet.2021.08.034},
abstract = {With ever increasing computational capacities, neural networks become more and more proficient at solving complex tasks. However, picking a sufficiently good network topology usually relies on expert human knowledge. Neural architecture search aims to reduce the extent of expertise that is needed. Modern architecture search techniques often rely on immense computational power, or apply trained meta-controllers for decision making. We develop a framework for a genetic algorithm that is both computationally cheap and makes decisions based on mathematical criteria rather than trained parameters. It is a hybrid approach that fuses training and topology optimization together into one process. Structural modifications that are performed include adding or removing layers of neurons, with some re-training applied to make up for any incurred change in input–output behaviour. Our ansatz is tested on several benchmark datasets with limited computational overhead compared to training only the baseline. This algorithm can achieve a significant increase in accuracy (as compared to a fully trained baseline), rescue insufficient topologies that in their current state are only able to learn to a limited extent, and dynamically reduce network size without loss in achieved accuracy. On standard ML datasets, accuracy improvements compared to baseline performance can range from 20% for well performing starting topologies to more than 40% in case of insufficient baselines, or reduce network size by almost 15%.},
note = {Online available at: \url{https://doi.org/10.1016/j.neunet.2021.08.034} (DOI). Schiessler, E.; Aydin, R.; Linka, K.; Cyron, C.: Neural network surgery: Combining training with topology optimization. Neural networks. 2021. vol. 144, 384-393. DOI: 10.1016/j.neunet.2021.08.034}}
@misc{schiessler_predicting_the_2021, 
author={Schiessler, E., Würger, T., Lamaka, S., Meißner, R., Cyron, C., Zheludkevich, M., Feiler, C., Aydin, R.},
title={Predicting the inhibition efficiencies of magnesium dissolution modulators using sparse machine learning models},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.1038/s41524-021-00658-7},
abstract = {The degradation behaviour of magnesium and its alloys can be tuned by small organic molecules. However, an automatic identification of effective organic additives within the vast chemical space of potential compounds needs sophisticated tools. Herein, we propose two systematic approaches of sparse feature selection for identifying molecular descriptors that are most relevant for the corrosion inhibition efficiency of chemical compounds. One is based on the classical statistical tool of analysis of variance, the other one based on random forests. We demonstrate how both can—when combined with deep neural networks—help to predict the corrosion inhibition efficiencies of chemical compounds for the magnesium alloy ZE41. In particular, we demonstrate that this framework outperforms predictions relying on a random selection of molecular descriptors. Finally, we point out how autoencoders could be used in the future to enable even more accurate automated predictions of corrosion inhibition efficiencies.},
note = {Online available at: \url{https://doi.org/10.1038/s41524-021-00658-7} (DOI). Schiessler, E.; Würger, T.; Lamaka, S.; Meißner, R.; Cyron, C.; Zheludkevich, M.; Feiler, C.; Aydin, R.: Predicting the inhibition efficiencies of magnesium dissolution modulators using sparse machine learning models. npj Computational Materials. 2021. vol. 7, no. 1, 193. DOI: 10.1038/s41524-021-00658-7}}
@misc{davoodikermani_computational_study_2021, 
author={Davoodi Kermani, I., Schmitter, M., Eichinger, J.F., Aydin, R.C., Cyron, C.J.},
title={Computational study of the geometric properties governing the linear mechanical behavior of fiber networks},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.commatsci.2021.110711},
abstract = {Materials whose microstructure is formed by random fiber networks play an important role both in biology and engineering. So far, it still remains unclear which geometric properties of the fiber network determine the macroscopic mechanical properties of such materials. This paper presents a computational study based on a large number of representative volume elements of random fiber networks. Our study reveals that the linear mechanical properties of fiber networks (i.e., Young’s modulus and Poisson’s ratio) are largely determined by only four scalar key descriptors. These are the number of fibers per volume, the mean node valency, the mean fiber length, and the mean direction cosine between fibers adjacent to the same node. Number of fibers per volume and node valency were found to be responsible for around 80% of the variance of the mechanical properties, making them the two by far dominant microstructural descriptors. In the part of the configuration space covered by our study, we observed a linear or quadratic relationship between the above four scalar microstructural descriptors and the Young’s modulus. For the number of fibers per unit volume we propose a theoretical explanation for this simple relation.},
note = {Online available at: \url{https://doi.org/10.1016/j.commatsci.2021.110711} (DOI). Davoodi Kermani, I.; Schmitter, M.; Eichinger, J.; Aydin, R.; Cyron, C.: Computational study of the geometric properties governing the linear mechanical behavior of fiber networks. Computational Materials Science. 2021. vol. 199, 110711. DOI: 10.1016/j.commatsci.2021.110711}}
@misc{ganesan_understanding_creep_2021, 
author={Ganesan, H., Scheider, I., Cyron, C.},
title={Understanding creep in TiAl alloys on the nanosecond scale by molecular dynamics simulations},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.matdes.2021.110282},
abstract = {Molecular dynamics (MD) simulations of creep generally face the problem that the creep most often evolves on time scales hard to capture with MD due to their typically short time step size. Consequently, MD studies of creep often use unrealistically high temperatures and stresses and simplified atomistic models to make creep-like processes happen on computationally accessible time scales. Apparently, this compromises the physical reliability of such studies. To alleviate this problem, we designed an MD model of titanium aluminide (TiAl) with a microstructure matching at least many of the key parameters of experimentally observed microstructures. We applied this MD model with stresses much lower than the ones used in most previous creep studies (well below yield stress) and in the temperature range , with melting temperature . Compared to typical previous MD studies, this much more realistic setup produces creep rates more than three orders of magnitude smaller and thus much closer to reality. We identified the driving mechanisms of primary creep on the nanosecond scale that agree very well with recent experimental observations, thus contributing towards the overarching goal of bridging the gap between atomistic creep simulations and continuum-scale creep simulations for engineering applications.},
note = {Online available at: \url{https://doi.org/10.1016/j.matdes.2021.110282} (DOI). Ganesan, H.; Scheider, I.; Cyron, C.: Understanding creep in TiAl alloys on the nanosecond scale by molecular dynamics simulations. Materials & Design. 2021. vol. 212, 110282. DOI: 10.1016/j.matdes.2021.110282}}
@misc{giuntini_defects_and_2021, 
author={Giuntini, D., Zhao, S., Krekeler, T., Li, M., Blankenburg, M., Bor, B., Schaan, G., Domènech, B., Müller, M., Scheider, I., Ritter, M., Schneider, G.A.},
title={Defects and plasticity in ultrastrong supercrystalline nanocomposites},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.1126/sciadv.abb6063},
abstract = {Supercrystalline nanocomposites are nanoarchitected materials with a growing range of applications but unexplored in their structural behavior. They typically consist of organically functionalized inorganic nanoparticles arranged into periodic structures analogous to crystalline lattices, including superlattice imperfections induced by processing or mechanical loading. Although featuring a variety of promising functional properties, their lack of mechanical robustness and unknown deformation mechanisms hamper their implementation into devices. We show that supercrystalline materials react to indentation with the same deformation patterns encountered in single crystals. Supercrystals accommodate plastic deformation in the form of pile-ups, dislocations, and slip bands. These phenomena occur, at least partially, also after cross-linking of the organic ligands, which leads to a multifold strengthening of the nanocomposites. The classic shear theories of crystalline materials are found to describe well the behavior of supercrystalline nanocomposites, which result to feature an elastoplastic behavior, accompanied by compaction.},
note = {Online available at: \url{https://doi.org/10.1126/sciadv.abb6063} (DOI). Giuntini, D.; Zhao, S.; Krekeler, T.; Li, M.; Blankenburg, M.; Bor, B.; Schaan, G.; Domènech, B.; Müller, M.; Scheider, I.; Ritter, M.; Schneider, G.: Defects and plasticity in ultrastrong supercrystalline nanocomposites. Science Advances. 2021. vol. 7, no. 2, eabb6063. DOI: 10.1126/sciadv.abb6063}}
@misc{tang_unloading_behaviors_2021, 
author={Tang, W., Lee, J., Wang, H., Steglich, D., Li, D., Peng, Y., Wu, P.},
title={Unloading behaviors of the rare-earth magnesium alloy ZE10 sheet},
year={2021},
howpublished = {journal article},
doi = {https://doi.org/10.1016/j.jma.2020.02.023},
abstract = {Due to their low symmetry in crystal structure, low elastic modulus (∼45 GPa) and low yielding stress, magnesium (Mg) alloys exhibit strong inelastic behaviors during unloading. As more and more Mg alloys are developed, their unloading behaviors were less investigated, especially for rare-earth (RE) Mg alloys. In the current work, the unloading behaviors of the RE Mg alloy ZE10 sheet is carefully studied by both mechanical tests and crystal plasticity modeling. In terms of the stress–strain curves, the inelastic strain, the chord modulus, and the active deformation mechanisms, the substantial anisotropy and the loading path dependency of the unloading behaviors of ZE10 sheets are characterized. The inelastic strains are generally larger under compressive Loading–UnLoading (L–UL) than under tensile L–UL, along the transverse direction (TD) than along the rolling direction (RD) under tensile L–UL, and along RD than along TD under compressive L–UL. The basal slip, twinning and de-twinning are found to be responsible for the unloading behaviors of ZE10 sheets.},
note = {Online available at: \url{https://doi.org/10.1016/j.jma.2020.02.023} (DOI). Tang, W.; Lee, J.; Wang, H.; Steglich, D.; Li, D.; Peng, Y.; Wu, P.: Unloading behaviors of the rare-earth magnesium alloy ZE10 sheet. Journal of Magnesium and Alloys. 2021. vol. 9, no. 3, 927-936. DOI: 10.1016/j.jma.2020.02.023}}