@article {1676, title = {Insight into microstructure-sensitive elastic strain concentrations from integrated computational modeling and digital image correlation}, journal = {Scripta Materialia}, volume = {192}, year = {2021}, pages = {78{\textendash}82}, abstract = {

The microstructural origins of highly localized elastic strain concentrations in polycrystalline microstructures under monotonic loading are studied using grain-scale, in situ digital image correlation and crystal plasticity finite element method. It is shown that the locations of exceptionally high elastic strain concentrations in the microstructure depend on particular crystallographic and morphological orientations of grains and less so on crystalline details of their local neighborhood. Based on these results, we discuss how topological and crystallographic features of annealing twin boundaries can increase the likelihood of slip band initiation throughout the microstructure of polycrystalline Ni-base superalloys.

}, keywords = {Elasticity, Micromechanics, Microstructure, Superalloys}, issn = {13596462}, doi = {10.1016/j.scriptamat.2020.10.001}, url = {https://doi.org/10.1016/j.scriptamat.2020.10.001}, author = {Latypov, Marat I. and Stinville, Jean Charles and Mayeur, Jason R. and Hestroffer, Jonathan M. and Pollock, Tresa M. and Beyerlein, Irene J.} } @article {1691, title = {Multiplicity of dislocation pathways in a refractory multiprincipal element alloy}, journal = {Science}, volume = {370}, year = {2020}, pages = {95{\textendash}101}, abstract = {

Refractory multiprincipal element alloys (MPEAs) are promising materials to meet the demands of aggressive structural applications, yet require fundamentally different avenues for accommodating plastic deformation in the body-centered cubic (bcc) variants of these alloys. We show a desirable combination of homogeneous plastic deformability and strength in the bcc MPEA MoNbTi, enabled by the rugged atomic environment through which dislocations must navigate. Our observations of dislocation motion and atomistic calculations unveil the unexpected dominance of nonscrew character dislocations and numerous slip planes for dislocation glide. This behavior lends credence to theories that explain the exceptional high temperature strength of similar alloys. Our results advance a defect-aware perspective to alloy design strategies for materials capable of performance across the temperature spectrum.

}, issn = {10959203}, doi = {10.1126/science.aba3722}, author = {Wang, Fulin and Balbus, Glenn H. and Xu, Shuozhi and Su, Yanqing and Shin, Jungho and Rottmann, Paul F. and Knipling, Keith E. and Stinville, Jean Charles and Mills, Leah H. and Senkov, Oleg N. and Beyerlein, Irene J. and Pollock, Tresa M. and Gianola, Daniel S.} } @article {1401, title = {Three-dimensional maps of geometrically necessary dislocation densities in additively manufactured Ni-based superalloy IN718}, journal = {International Journal of Plasticity}, year = {2020}, pages = {102709}, keywords = {Dislocations, Metallic material, Microstructures, Polycrystalline material, Three-dimensional electron backscatter diffraction}, issn = {0749-6419}, doi = {10.1016/j.ijplas.2020.102709}, url = {https://doi.org/10.1016/j.ijplas.2020.102709}, author = {Witzen, Wyatt A. and Polonsky, Andrew T. and Pollock, Tresa M. and Beyerlein, Irene J.} } @article {1351, title = {BisQue for 3D Materials Science in the Cloud: Microstructure{\textendash}Property Linkages}, journal = {Integrating Materials and Manufacturing Innovation}, volume = {8}, year = {2019}, pages = {52{\textendash}65}, abstract = {

Accelerating the design and development of new advanced materials is one of the priorities in modern materials science. These efforts are critically dependent on the development of comprehensive materials cyberinfrastructures which enable efficient data storage, management, sharing, and collaboration as well as integration of computational tools that help establish processing\–structure\–property relationships. In this contribution, we present implementation of such computational tools into a cloud-based platform called BisQue (Kvilekval et al., Bioinformatics 26(4):554, 2010). We first describe the current state of BisQue as an open-source platform for multidisciplinary research in the cloud and its potential for 3D materials science. We then demonstrate how new computational tools, primarily aimed at processing\–structure\–property relationships, can be implemented into the system. Specifically, in this work, we develop a module for BisQue that enables microstructure-sensitive predictions of effective yield strength of two-phase materials. Towards this end, we present an implementation of a computationally efficient data-driven model into the BisQue platform. The new module is made available online (web address: https://bisque.ece.ucsb.edu/module_service/Composite_Strength/) and can be used from a web browser without any special software and with minimal computational requirements on the user end. The capabilities of the module for rapid property screening are demonstrated in case studies with two different methodologies based on datasets containing 3D microstructure information from (i) synthetic generation and (ii) sampling large 3D volumes obtained in experiments.

}, keywords = {Cloud-based computing, Homogenization, Materials cyberinfrastructure, Reduced order models}, isbn = {4019201900}, issn = {21939772}, doi = {10.1007/s40192-019-00128-5}, author = {Latypov, Marat I. and Khan, Amil and Lang, Christian A. and Kvilekval, Kris and Polonsky, Andrew T. and Echlin, McLean L.P. and Beyerlein, Irene J. and Manjunath, B. S. and Pollock, Tresa M.} } @article {1386, title = {Computational homogenization for multiscale forward modeling of resonant ultrasound spectroscopy of heterogeneous materials}, journal = {Materials Characterization}, volume = {158}, year = {2019}, pages = {109945}, abstract = {

We present a computational framework for multiscale forward modeling of ultrasound resonance in heterogeneous materials that accounts for microstructure. The approach includes two steps. The first step is the accurate determination of the elastic properties of heterogeneous materials with finite element simulations on a representative volume element of the microstructure at the mesoscopic length scale. The second step is modeling resonance frequencies of a macroscopic component made of an effective homogeneous medium having the same elastic properties as the actual material with microstructure. The approach is validated in a case study on a Cu\–W two-phase composite, for which resonance frequencies predicted with the proposed framework are compared against the experimental measurements. The present multiscale modeling approach, involving computational homogenization and leveraging 3D microstructure data, showed better accuracy compared to classical Voigt/Reuss bounds often used for forward modeling of resonant ultrasound spectroscopy.

}, keywords = {Computational homogenization, Finite elements, Forward modeling, Non-destructive evaluation, Resonant ultrasound spectroscopy}, issn = {10445803}, doi = {10.1016/j.matchar.2019.109945}, url = {https://doi.org/10.1016/j.matchar.2019.109945}, author = {Latypov, Marat I. and Charpagne, Marie Agathe and Souther, Mason and Goodlet, Brent R. and Echlin, Mclean P. and Beyerlein, Irene J. and Pollock, Tresa M.} } @article {1471, title = {Application of chord length distributions and principal component analysis for quantification and representation of diverse polycrystalline microstructures}, journal = {Materials Characterization}, volume = {145}, year = {2018}, pages = {671{\textendash}685}, abstract = {

Quantification of mesoscale microstructures of polycrystalline materials is important for a range of practical tasks of materials design and development. The current protocols of quantifying grain size and morphology often rely on microstructure metrics (e.g., mean grain diameter) that overlook important details of the mesostructure. In this work, we present a quantification framework based on directionally resolved chord length distribution and principal component analysis as a means of extracting additional information from 2-D microstructural maps. Towards this end, we first present in detail a method for calculating chord length distribution based on boundary segments available in modern digital datasets (e.g., from microscopy post-processing) and their low-rank representations by principal component analysis. The utility of the proposed framework for capturing grain size, morphology, and their anisotropy for efficient visualization, representation, and specification of polycrystalline microstructures is then demonstrated in case studies on datasets from synthetic generation, experiments (on Ni-base superalloys), and simulations (on steel during recrystallization).

}, keywords = {Chord length distribution, EBSD, Grain size, Microstructure, Principal component analysis}, issn = {10445803}, doi = {10.1016/j.matchar.2018.09.020}, url = {https://doi.org/10.1016/j.matchar.2018.09.020}, author = {Latypov, Marat I. and K{\"u}hbach, Markus and Beyerlein, Irene J. and Stinville, Jean Charles and Toth, Laszlo S. and Pollock, Tresa M. and Kalidindi, Surya R.} }