BisQue for 3D Materials Science in the Cloud: Microstructure–Property Linkages View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-03

AUTHORS

Marat I. Latypov, Amil Khan, Christian A. Lang, Kris Kvilekval, Andrew T. Polonsky, McLean P. Echlin, Irene J. Beyerlein, B. S. Manjunath, Tresa M. Pollock

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. More... »

PAGES

52-65

References to SciGraph publications

  • 2014-12. Three-dimensional sampling of material structure for property modeling and design in INTEGRATING MATERIALS AND MANUFACTURING INNOVATION
  • 2017-03. Materials Knowledge Systems in Python—a Data Science Framework for Accelerated Development of Hierarchical Materials in INTEGRATING MATERIALS AND MANUFACTURING INNOVATION
  • 2014-04. Microstructure and Mechanical Properties of Copper Processed by Twist Extrusion with a Reduced Twist-Line Slope in METALLURGICAL AND MATERIALS TRANSACTIONS A
  • 2015-01. Plastic Deformation Behavior and Microstructural Evolution of Al-Core/Cu-Sheath Composites in Multi-pass Caliber Rolling in METALLURGICAL AND MATERIALS TRANSACTIONS A
  • 2013-12. Experimental measurement of surface strains and local lattice rotations combined with 3D microstructure reconstruction from deformed polycrystalline ensembles at the micro-scale in INTEGRATING MATERIALS AND MANUFACTURING INNOVATION
  • 2018-09. Reduced-Order Microstructure-Sensitive Models for Damage Initiation in Two-Phase Composites in INTEGRATING MATERIALS AND MANUFACTURING INNOVATION
  • 2016-08. Materials Data Infrastructure: A Case Study of the Citrination Platform to Examine Data Import, Storage, and Access in JOM
  • 2016-08. The Materials Commons: A Collaboration Platform and Information Repository for the Global Materials Community in JOM
  • 2016-12. Creating an integrated collaborative environment for materials research in INTEGRATING MATERIALS AND MANUFACTURING INNOVATION
  • 2009. Electron Backscatter Diffraction in Materials Science in NONE
  • 2014-12. DREAM.3D: A Digital Representation Environment for the Analysis of Microstructure in 3D in INTEGRATING MATERIALS AND MANUFACTURING INNOVATION
  • 2014-12. h5ebsd: an archival data format for electron back-scatter diffraction data sets in INTEGRATING MATERIALS AND MANUFACTURING INNOVATION
  • 2017-03. Microstructure-Informed Cloud Computing for Interoperability of Materials Databases and Computational Models: Microtextured Regions in Ti Alloys in INTEGRATING MATERIALS AND MANUFACTURING INNOVATION
  • 2016-03. Modeling and Characterization of Texture Evolution in Twist Extrusion in METALLURGICAL AND MATERIALS TRANSACTIONS A
  • 2017-03. Process-Structure Linkages Using a Data Science Approach: Application to Simulated Additive Manufacturing Data in INTEGRATING MATERIALS AND MANUFACTURING INNOVATION
  • 2016-12. Versatile algorithms for the computation of 2-point spatial correlations in quantifying material structure in INTEGRATING MATERIALS AND MANUFACTURING INNOVATION
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s40192-019-00128-5

    DOI

    http://dx.doi.org/10.1007/s40192-019-00128-5

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1112896310


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0801", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Artificial Intelligence and Image Processing", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/08", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Information and Computing Sciences", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "University of California, Santa Barbara", 
              "id": "https://www.grid.ac/institutes/grid.133342.4", 
              "name": [
                "Materials Department, University of California Santa Barbara, 93106, Santa Barbara, CA, USA", 
                "Mechanical Engineering Department, University of California Santa Barbara, 93106, Santa Barbara, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Latypov", 
            "givenName": "Marat I.", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of California, Santa Barbara", 
              "id": "https://www.grid.ac/institutes/grid.133342.4", 
              "name": [
                "Electrical and Computer Engineering Department, University of California Santa Barbara, 93106, Santa Barbara, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Khan", 
            "givenName": "Amil", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of California, Santa Barbara", 
              "id": "https://www.grid.ac/institutes/grid.133342.4", 
              "name": [
                "Electrical and Computer Engineering Department, University of California Santa Barbara, 93106, Santa Barbara, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Lang", 
            "givenName": "Christian A.", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of California, Santa Barbara", 
              "id": "https://www.grid.ac/institutes/grid.133342.4", 
              "name": [
                "Electrical and Computer Engineering Department, University of California Santa Barbara, 93106, Santa Barbara, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Kvilekval", 
            "givenName": "Kris", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of California, Santa Barbara", 
              "id": "https://www.grid.ac/institutes/grid.133342.4", 
              "name": [
                "Materials Department, University of California Santa Barbara, 93106, Santa Barbara, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Polonsky", 
            "givenName": "Andrew T.", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of California, Santa Barbara", 
              "id": "https://www.grid.ac/institutes/grid.133342.4", 
              "name": [
                "Materials Department, University of California Santa Barbara, 93106, Santa Barbara, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Echlin", 
            "givenName": "McLean P.", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of California, Santa Barbara", 
              "id": "https://www.grid.ac/institutes/grid.133342.4", 
              "name": [
                "Materials Department, University of California Santa Barbara, 93106, Santa Barbara, CA, USA", 
                "Mechanical Engineering Department, University of California Santa Barbara, 93106, Santa Barbara, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Beyerlein", 
            "givenName": "Irene J.", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of California, Santa Barbara", 
              "id": "https://www.grid.ac/institutes/grid.133342.4", 
              "name": [
                "Electrical and Computer Engineering Department, University of California Santa Barbara, 93106, Santa Barbara, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Manjunath", 
            "givenName": "B. S.", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of California, Santa Barbara", 
              "id": "https://www.grid.ac/institutes/grid.133342.4", 
              "name": [
                "Materials Department, University of California Santa Barbara, 93106, Santa Barbara, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Pollock", 
            "givenName": "Tresa M.", 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1016/j.commatsci.2014.10.020", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000880736"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.1319436111", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005026064"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.scriptamat.2005.06.013", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1005140219"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0022-5096(97)00019-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1006706651"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0749-6419(91)90043-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007989349"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0749-6419(91)90043-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007989349"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ijfatigue.2010.01.003", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008860307"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.actamat.2011.04.005", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009416387"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1002/zamm.19290090104", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010507429"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11661-013-2165-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010659351", 
              "https://doi.org/10.1007/s11661-013-2165-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.actamat.2005.03.052", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014155991"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s40192-014-0021-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014824955", 
              "https://doi.org/10.1186/s40192-014-0021-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s40192-014-0021-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014824955", 
              "https://doi.org/10.1186/s40192-014-0021-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s40192-014-0021-9", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1014824955", 
              "https://doi.org/10.1186/s40192-014-0021-9"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.actamat.2015.02.045", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015211689"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-0-387-88136-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016945857", 
              "https://doi.org/10.1007/978-0-387-88136-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/978-0-387-88136-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1016945857", 
              "https://doi.org/10.1007/978-0-387-88136-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.actamat.2016.02.001", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017010889"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.actamat.2014.07.071", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1017819783"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0001-6160(61)90060-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023496312"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0001-6160(61)90060-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023496312"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1063/1.4943679", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023524157"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.actamat.2007.11.040", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024130474"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/2193-9772-2-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024595919", 
              "https://doi.org/10.1186/2193-9772-2-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11837-016-1998-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024870190", 
              "https://doi.org/10.1007/s11837-016-1998-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11837-016-1998-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024870190", 
              "https://doi.org/10.1007/s11837-016-1998-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0022-5096(02)00021-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028305988"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.actamat.2013.10.043", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028616294"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.actamat.2010.04.041", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031320327"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0022-5096(63)90060-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031920985"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0022-5096(63)90060-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1031920985"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.pmatsci.2009.08.002", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033045094"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0020-7683(87)90045-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035119054"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s40192-016-0055-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035478491", 
              "https://doi.org/10.1186/s40192-016-0055-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s40192-016-0055-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035478491", 
              "https://doi.org/10.1186/s40192-016-0055-2"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/bioinformatics/btp699", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036191837"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11661-014-2608-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038544558", 
              "https://doi.org/10.1007/s11661-014-2608-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0022-5096(65)90010-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041039986"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0022-5096(65)90010-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041039986"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.actamat.2014.08.022", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1041863078"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s40192-015-0044-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042237011", 
              "https://doi.org/10.1186/s40192-015-0044-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s40192-015-0044-x", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042237011", 
              "https://doi.org/10.1186/s40192-015-0044-x"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0001-6160(73)90064-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042745661"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/0001-6160(73)90064-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042745661"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.actamat.2004.02.032", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042883854"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.actamat.2007.11.041", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043021048"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.matdes.2015.05.025", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1045701255"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/2193-9772-3-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046188731", 
              "https://doi.org/10.1186/2193-9772-3-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/2193-9772-3-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046188731", 
              "https://doi.org/10.1186/2193-9772-3-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11837-016-1984-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046594386", 
              "https://doi.org/10.1007/s11837-016-1984-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11837-016-1984-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046594386", 
              "https://doi.org/10.1007/s11837-016-1984-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0955-7997(99)00013-2", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047608754"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s11661-015-3298-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049993195", 
              "https://doi.org/10.1007/s11661-015-3298-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0045-7825(98)00227-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051897672"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/2193-9772-3-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052006640", 
              "https://doi.org/10.1186/2193-9772-3-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1063/1.3680111", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1057999402"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevb.82.125416", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060633812"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1103/physrevb.82.125416", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1060633812"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1115/1.3119494", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1062101709"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1557/mrs.2016.164", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1067967397"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1557/mrs.2016.93", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1067967460"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.commatsci.2017.01.026", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1083905309"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s40192-017-0088-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1084038374", 
              "https://doi.org/10.1007/s40192-017-0088-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s40192-017-0089-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1084038375", 
              "https://doi.org/10.1007/s40192-017-0089-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s40192-017-0090-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1084038376", 
              "https://doi.org/10.1007/s40192-017-0090-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.actamat.2017.03.009", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1084055680"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.actamat.2017.03.009", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1084055680"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.actamat.2017.03.009", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1084055680"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.compstruct.2017.03.029", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1084067745"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.jcp.2017.06.013", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1086024729"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.actamat.2017.09.016", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1091515999"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.matchar.2018.02.020", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1101095083"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ijfatigue.2018.04.017", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1103656340"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s40192-018-0112-0", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1105177953", 
              "https://doi.org/10.1007/s40192-018-0112-0"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.actamat.2018.07.011", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1105413892"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.commatsci.2018.09.034", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1107146162"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cma.2018.11.034", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1110481552"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.cma.2018.11.034", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1110481552"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2019-03", 
        "datePublishedReg": "2019-03-01", 
        "description": "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\u2013structure\u2013property 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\u2013structure\u2013property 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.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1007/s40192-019-00128-5", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": false, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.7824181", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.3660390", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.5542542", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.7058070", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": [
          {
            "id": "sg:journal.1136615", 
            "issn": [
              "2193-9764", 
              "2193-9772"
            ], 
            "name": "Integrating Materials and Manufacturing Innovation", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "1", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "8"
          }
        ], 
        "name": "BisQue for 3D Materials Science in the Cloud: Microstructure\u2013Property Linkages", 
        "pagination": "52-65", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "23733710de7d3df16af4c9f8a7a1ae40076bbbacb394a8375af661e34e999490"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1007/s40192-019-00128-5"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1112896310"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1007/s40192-019-00128-5", 
          "https://app.dimensions.ai/details/publication/pub.1112896310"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-11T13:18", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000368_0000000368/records_78938_00000001.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://link.springer.com/10.1007%2Fs40192-019-00128-5"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s40192-019-00128-5'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s40192-019-00128-5'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s40192-019-00128-5'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s40192-019-00128-5'


     

    This table displays all metadata directly associated to this object as RDF triples.

    317 TRIPLES      21 PREDICATES      88 URIs      19 LITERALS      7 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1007/s40192-019-00128-5 schema:about anzsrc-for:08
    2 anzsrc-for:0801
    3 schema:author N6af34171eb80412e9197ca818b4d3814
    4 schema:citation sg:pub.10.1007/978-0-387-88136-2
    5 sg:pub.10.1007/s11661-013-2165-1
    6 sg:pub.10.1007/s11661-014-2608-3
    7 sg:pub.10.1007/s11661-015-3298-1
    8 sg:pub.10.1007/s11837-016-1984-0
    9 sg:pub.10.1007/s11837-016-1998-7
    10 sg:pub.10.1007/s40192-017-0088-1
    11 sg:pub.10.1007/s40192-017-0089-0
    12 sg:pub.10.1007/s40192-017-0090-7
    13 sg:pub.10.1007/s40192-018-0112-0
    14 sg:pub.10.1186/2193-9772-2-5
    15 sg:pub.10.1186/2193-9772-3-4
    16 sg:pub.10.1186/2193-9772-3-5
    17 sg:pub.10.1186/s40192-014-0021-9
    18 sg:pub.10.1186/s40192-015-0044-x
    19 sg:pub.10.1186/s40192-016-0055-2
    20 https://doi.org/10.1002/zamm.19290090104
    21 https://doi.org/10.1016/0001-6160(61)90060-8
    22 https://doi.org/10.1016/0001-6160(73)90064-3
    23 https://doi.org/10.1016/0020-7683(87)90045-x
    24 https://doi.org/10.1016/0022-5096(63)90060-7
    25 https://doi.org/10.1016/0022-5096(65)90010-4
    26 https://doi.org/10.1016/0749-6419(91)90043-x
    27 https://doi.org/10.1016/j.actamat.2004.02.032
    28 https://doi.org/10.1016/j.actamat.2005.03.052
    29 https://doi.org/10.1016/j.actamat.2007.11.040
    30 https://doi.org/10.1016/j.actamat.2007.11.041
    31 https://doi.org/10.1016/j.actamat.2010.04.041
    32 https://doi.org/10.1016/j.actamat.2011.04.005
    33 https://doi.org/10.1016/j.actamat.2013.10.043
    34 https://doi.org/10.1016/j.actamat.2014.07.071
    35 https://doi.org/10.1016/j.actamat.2014.08.022
    36 https://doi.org/10.1016/j.actamat.2015.02.045
    37 https://doi.org/10.1016/j.actamat.2016.02.001
    38 https://doi.org/10.1016/j.actamat.2017.03.009
    39 https://doi.org/10.1016/j.actamat.2017.09.016
    40 https://doi.org/10.1016/j.actamat.2018.07.011
    41 https://doi.org/10.1016/j.cma.2018.11.034
    42 https://doi.org/10.1016/j.commatsci.2014.10.020
    43 https://doi.org/10.1016/j.commatsci.2017.01.026
    44 https://doi.org/10.1016/j.commatsci.2018.09.034
    45 https://doi.org/10.1016/j.compstruct.2017.03.029
    46 https://doi.org/10.1016/j.ijfatigue.2010.01.003
    47 https://doi.org/10.1016/j.ijfatigue.2018.04.017
    48 https://doi.org/10.1016/j.jcp.2017.06.013
    49 https://doi.org/10.1016/j.matchar.2018.02.020
    50 https://doi.org/10.1016/j.matdes.2015.05.025
    51 https://doi.org/10.1016/j.pmatsci.2009.08.002
    52 https://doi.org/10.1016/j.scriptamat.2005.06.013
    53 https://doi.org/10.1016/s0022-5096(02)00021-2
    54 https://doi.org/10.1016/s0022-5096(97)00019-7
    55 https://doi.org/10.1016/s0045-7825(98)00227-8
    56 https://doi.org/10.1016/s0955-7997(99)00013-2
    57 https://doi.org/10.1063/1.3680111
    58 https://doi.org/10.1063/1.4943679
    59 https://doi.org/10.1073/pnas.1319436111
    60 https://doi.org/10.1093/bioinformatics/btp699
    61 https://doi.org/10.1103/physrevb.82.125416
    62 https://doi.org/10.1115/1.3119494
    63 https://doi.org/10.1557/mrs.2016.164
    64 https://doi.org/10.1557/mrs.2016.93
    65 schema:datePublished 2019-03
    66 schema:datePublishedReg 2019-03-01
    67 schema:description 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.
    68 schema:genre research_article
    69 schema:inLanguage en
    70 schema:isAccessibleForFree false
    71 schema:isPartOf N1bec3171ea7c48fdb711de258da5f167
    72 Nd9833dd35c0b47ca960d13212e08a9f2
    73 sg:journal.1136615
    74 schema:name BisQue for 3D Materials Science in the Cloud: Microstructure–Property Linkages
    75 schema:pagination 52-65
    76 schema:productId N2491be80f917483d9cd2284d942176a7
    77 N46ce369b34424442bab9b031986fc7f7
    78 N7d452bcd658a4ae5a89d296c10d20521
    79 schema:sameAs https://app.dimensions.ai/details/publication/pub.1112896310
    80 https://doi.org/10.1007/s40192-019-00128-5
    81 schema:sdDatePublished 2019-04-11T13:18
    82 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    83 schema:sdPublisher N8af6cc0d5bc74b0da4e0e439c069840b
    84 schema:url https://link.springer.com/10.1007%2Fs40192-019-00128-5
    85 sgo:license sg:explorer/license/
    86 sgo:sdDataset articles
    87 rdf:type schema:ScholarlyArticle
    88 N032600e0b00c41c6b1fa41076a54254b schema:affiliation https://www.grid.ac/institutes/grid.133342.4
    89 schema:familyName Kvilekval
    90 schema:givenName Kris
    91 rdf:type schema:Person
    92 N046ea6f636b54fb992b34ecd08bc455f rdf:first Nb06ba58224024bb997eff6cc2068f74d
    93 rdf:rest rdf:nil
    94 N19a31c9e9205404e91ca74e3693a3720 schema:affiliation https://www.grid.ac/institutes/grid.133342.4
    95 schema:familyName Polonsky
    96 schema:givenName Andrew T.
    97 rdf:type schema:Person
    98 N1bec3171ea7c48fdb711de258da5f167 schema:volumeNumber 8
    99 rdf:type schema:PublicationVolume
    100 N2491be80f917483d9cd2284d942176a7 schema:name readcube_id
    101 schema:value 23733710de7d3df16af4c9f8a7a1ae40076bbbacb394a8375af661e34e999490
    102 rdf:type schema:PropertyValue
    103 N25a3fb72b43442899df53b7c35804195 rdf:first Na8f9a603aa4d4fef8063c78deb3b04a7
    104 rdf:rest Nb6e430bc5858496eb5f5f5b97325d520
    105 N3333b2522f474c31bc29d6ef7eaf676f schema:affiliation https://www.grid.ac/institutes/grid.133342.4
    106 schema:familyName Beyerlein
    107 schema:givenName Irene J.
    108 rdf:type schema:Person
    109 N436adf216af14d07980f6eab7d019642 rdf:first N3333b2522f474c31bc29d6ef7eaf676f
    110 rdf:rest N6e8d5b3ea90f4c718f19996f447e8251
    111 N46ce369b34424442bab9b031986fc7f7 schema:name dimensions_id
    112 schema:value pub.1112896310
    113 rdf:type schema:PropertyValue
    114 N6af34171eb80412e9197ca818b4d3814 rdf:first Naf1e6aed8d0c45cfa2b2ce32063115bc
    115 rdf:rest N25a3fb72b43442899df53b7c35804195
    116 N6e8d5b3ea90f4c718f19996f447e8251 rdf:first Na91e3d7306c44ed89f89944776199f1e
    117 rdf:rest N046ea6f636b54fb992b34ecd08bc455f
    118 N7d452bcd658a4ae5a89d296c10d20521 schema:name doi
    119 schema:value 10.1007/s40192-019-00128-5
    120 rdf:type schema:PropertyValue
    121 N841c0ec12ea74aaa8e542c2339033ad2 rdf:first Ne8c4b099b7aa46b5a1a5acee8c31ec91
    122 rdf:rest N436adf216af14d07980f6eab7d019642
    123 N8af6cc0d5bc74b0da4e0e439c069840b schema:name Springer Nature - SN SciGraph project
    124 rdf:type schema:Organization
    125 N994096e795ed41589950d74a4f80093e rdf:first N032600e0b00c41c6b1fa41076a54254b
    126 rdf:rest Nec5e705809fe4200b0bdca34657384a3
    127 Na8f9a603aa4d4fef8063c78deb3b04a7 schema:affiliation https://www.grid.ac/institutes/grid.133342.4
    128 schema:familyName Khan
    129 schema:givenName Amil
    130 rdf:type schema:Person
    131 Na91e3d7306c44ed89f89944776199f1e schema:affiliation https://www.grid.ac/institutes/grid.133342.4
    132 schema:familyName Manjunath
    133 schema:givenName B. S.
    134 rdf:type schema:Person
    135 Naf1e6aed8d0c45cfa2b2ce32063115bc schema:affiliation https://www.grid.ac/institutes/grid.133342.4
    136 schema:familyName Latypov
    137 schema:givenName Marat I.
    138 rdf:type schema:Person
    139 Nb06ba58224024bb997eff6cc2068f74d schema:affiliation https://www.grid.ac/institutes/grid.133342.4
    140 schema:familyName Pollock
    141 schema:givenName Tresa M.
    142 rdf:type schema:Person
    143 Nb6e430bc5858496eb5f5f5b97325d520 rdf:first Nb927e66e820f405cbebe00773bb6b726
    144 rdf:rest N994096e795ed41589950d74a4f80093e
    145 Nb927e66e820f405cbebe00773bb6b726 schema:affiliation https://www.grid.ac/institutes/grid.133342.4
    146 schema:familyName Lang
    147 schema:givenName Christian A.
    148 rdf:type schema:Person
    149 Nd9833dd35c0b47ca960d13212e08a9f2 schema:issueNumber 1
    150 rdf:type schema:PublicationIssue
    151 Ne8c4b099b7aa46b5a1a5acee8c31ec91 schema:affiliation https://www.grid.ac/institutes/grid.133342.4
    152 schema:familyName Echlin
    153 schema:givenName McLean P.
    154 rdf:type schema:Person
    155 Nec5e705809fe4200b0bdca34657384a3 rdf:first N19a31c9e9205404e91ca74e3693a3720
    156 rdf:rest N841c0ec12ea74aaa8e542c2339033ad2
    157 anzsrc-for:08 schema:inDefinedTermSet anzsrc-for:
    158 schema:name Information and Computing Sciences
    159 rdf:type schema:DefinedTerm
    160 anzsrc-for:0801 schema:inDefinedTermSet anzsrc-for:
    161 schema:name Artificial Intelligence and Image Processing
    162 rdf:type schema:DefinedTerm
    163 sg:grant.3660390 http://pending.schema.org/fundedItem sg:pub.10.1007/s40192-019-00128-5
    164 rdf:type schema:MonetaryGrant
    165 sg:grant.5542542 http://pending.schema.org/fundedItem sg:pub.10.1007/s40192-019-00128-5
    166 rdf:type schema:MonetaryGrant
    167 sg:grant.7058070 http://pending.schema.org/fundedItem sg:pub.10.1007/s40192-019-00128-5
    168 rdf:type schema:MonetaryGrant
    169 sg:grant.7824181 http://pending.schema.org/fundedItem sg:pub.10.1007/s40192-019-00128-5
    170 rdf:type schema:MonetaryGrant
    171 sg:journal.1136615 schema:issn 2193-9764
    172 2193-9772
    173 schema:name Integrating Materials and Manufacturing Innovation
    174 rdf:type schema:Periodical
    175 sg:pub.10.1007/978-0-387-88136-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1016945857
    176 https://doi.org/10.1007/978-0-387-88136-2
    177 rdf:type schema:CreativeWork
    178 sg:pub.10.1007/s11661-013-2165-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010659351
    179 https://doi.org/10.1007/s11661-013-2165-1
    180 rdf:type schema:CreativeWork
    181 sg:pub.10.1007/s11661-014-2608-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038544558
    182 https://doi.org/10.1007/s11661-014-2608-3
    183 rdf:type schema:CreativeWork
    184 sg:pub.10.1007/s11661-015-3298-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049993195
    185 https://doi.org/10.1007/s11661-015-3298-1
    186 rdf:type schema:CreativeWork
    187 sg:pub.10.1007/s11837-016-1984-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046594386
    188 https://doi.org/10.1007/s11837-016-1984-0
    189 rdf:type schema:CreativeWork
    190 sg:pub.10.1007/s11837-016-1998-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024870190
    191 https://doi.org/10.1007/s11837-016-1998-7
    192 rdf:type schema:CreativeWork
    193 sg:pub.10.1007/s40192-017-0088-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084038374
    194 https://doi.org/10.1007/s40192-017-0088-1
    195 rdf:type schema:CreativeWork
    196 sg:pub.10.1007/s40192-017-0089-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084038375
    197 https://doi.org/10.1007/s40192-017-0089-0
    198 rdf:type schema:CreativeWork
    199 sg:pub.10.1007/s40192-017-0090-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084038376
    200 https://doi.org/10.1007/s40192-017-0090-7
    201 rdf:type schema:CreativeWork
    202 sg:pub.10.1007/s40192-018-0112-0 schema:sameAs https://app.dimensions.ai/details/publication/pub.1105177953
    203 https://doi.org/10.1007/s40192-018-0112-0
    204 rdf:type schema:CreativeWork
    205 sg:pub.10.1186/2193-9772-2-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024595919
    206 https://doi.org/10.1186/2193-9772-2-5
    207 rdf:type schema:CreativeWork
    208 sg:pub.10.1186/2193-9772-3-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046188731
    209 https://doi.org/10.1186/2193-9772-3-4
    210 rdf:type schema:CreativeWork
    211 sg:pub.10.1186/2193-9772-3-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052006640
    212 https://doi.org/10.1186/2193-9772-3-5
    213 rdf:type schema:CreativeWork
    214 sg:pub.10.1186/s40192-014-0021-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014824955
    215 https://doi.org/10.1186/s40192-014-0021-9
    216 rdf:type schema:CreativeWork
    217 sg:pub.10.1186/s40192-015-0044-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1042237011
    218 https://doi.org/10.1186/s40192-015-0044-x
    219 rdf:type schema:CreativeWork
    220 sg:pub.10.1186/s40192-016-0055-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035478491
    221 https://doi.org/10.1186/s40192-016-0055-2
    222 rdf:type schema:CreativeWork
    223 https://doi.org/10.1002/zamm.19290090104 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010507429
    224 rdf:type schema:CreativeWork
    225 https://doi.org/10.1016/0001-6160(61)90060-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023496312
    226 rdf:type schema:CreativeWork
    227 https://doi.org/10.1016/0001-6160(73)90064-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042745661
    228 rdf:type schema:CreativeWork
    229 https://doi.org/10.1016/0020-7683(87)90045-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1035119054
    230 rdf:type schema:CreativeWork
    231 https://doi.org/10.1016/0022-5096(63)90060-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031920985
    232 rdf:type schema:CreativeWork
    233 https://doi.org/10.1016/0022-5096(65)90010-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041039986
    234 rdf:type schema:CreativeWork
    235 https://doi.org/10.1016/0749-6419(91)90043-x schema:sameAs https://app.dimensions.ai/details/publication/pub.1007989349
    236 rdf:type schema:CreativeWork
    237 https://doi.org/10.1016/j.actamat.2004.02.032 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042883854
    238 rdf:type schema:CreativeWork
    239 https://doi.org/10.1016/j.actamat.2005.03.052 schema:sameAs https://app.dimensions.ai/details/publication/pub.1014155991
    240 rdf:type schema:CreativeWork
    241 https://doi.org/10.1016/j.actamat.2007.11.040 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024130474
    242 rdf:type schema:CreativeWork
    243 https://doi.org/10.1016/j.actamat.2007.11.041 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043021048
    244 rdf:type schema:CreativeWork
    245 https://doi.org/10.1016/j.actamat.2010.04.041 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031320327
    246 rdf:type schema:CreativeWork
    247 https://doi.org/10.1016/j.actamat.2011.04.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009416387
    248 rdf:type schema:CreativeWork
    249 https://doi.org/10.1016/j.actamat.2013.10.043 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028616294
    250 rdf:type schema:CreativeWork
    251 https://doi.org/10.1016/j.actamat.2014.07.071 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017819783
    252 rdf:type schema:CreativeWork
    253 https://doi.org/10.1016/j.actamat.2014.08.022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1041863078
    254 rdf:type schema:CreativeWork
    255 https://doi.org/10.1016/j.actamat.2015.02.045 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015211689
    256 rdf:type schema:CreativeWork
    257 https://doi.org/10.1016/j.actamat.2016.02.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1017010889
    258 rdf:type schema:CreativeWork
    259 https://doi.org/10.1016/j.actamat.2017.03.009 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084055680
    260 rdf:type schema:CreativeWork
    261 https://doi.org/10.1016/j.actamat.2017.09.016 schema:sameAs https://app.dimensions.ai/details/publication/pub.1091515999
    262 rdf:type schema:CreativeWork
    263 https://doi.org/10.1016/j.actamat.2018.07.011 schema:sameAs https://app.dimensions.ai/details/publication/pub.1105413892
    264 rdf:type schema:CreativeWork
    265 https://doi.org/10.1016/j.cma.2018.11.034 schema:sameAs https://app.dimensions.ai/details/publication/pub.1110481552
    266 rdf:type schema:CreativeWork
    267 https://doi.org/10.1016/j.commatsci.2014.10.020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000880736
    268 rdf:type schema:CreativeWork
    269 https://doi.org/10.1016/j.commatsci.2017.01.026 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083905309
    270 rdf:type schema:CreativeWork
    271 https://doi.org/10.1016/j.commatsci.2018.09.034 schema:sameAs https://app.dimensions.ai/details/publication/pub.1107146162
    272 rdf:type schema:CreativeWork
    273 https://doi.org/10.1016/j.compstruct.2017.03.029 schema:sameAs https://app.dimensions.ai/details/publication/pub.1084067745
    274 rdf:type schema:CreativeWork
    275 https://doi.org/10.1016/j.ijfatigue.2010.01.003 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008860307
    276 rdf:type schema:CreativeWork
    277 https://doi.org/10.1016/j.ijfatigue.2018.04.017 schema:sameAs https://app.dimensions.ai/details/publication/pub.1103656340
    278 rdf:type schema:CreativeWork
    279 https://doi.org/10.1016/j.jcp.2017.06.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1086024729
    280 rdf:type schema:CreativeWork
    281 https://doi.org/10.1016/j.matchar.2018.02.020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1101095083
    282 rdf:type schema:CreativeWork
    283 https://doi.org/10.1016/j.matdes.2015.05.025 schema:sameAs https://app.dimensions.ai/details/publication/pub.1045701255
    284 rdf:type schema:CreativeWork
    285 https://doi.org/10.1016/j.pmatsci.2009.08.002 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033045094
    286 rdf:type schema:CreativeWork
    287 https://doi.org/10.1016/j.scriptamat.2005.06.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005140219
    288 rdf:type schema:CreativeWork
    289 https://doi.org/10.1016/s0022-5096(02)00021-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028305988
    290 rdf:type schema:CreativeWork
    291 https://doi.org/10.1016/s0022-5096(97)00019-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006706651
    292 rdf:type schema:CreativeWork
    293 https://doi.org/10.1016/s0045-7825(98)00227-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051897672
    294 rdf:type schema:CreativeWork
    295 https://doi.org/10.1016/s0955-7997(99)00013-2 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047608754
    296 rdf:type schema:CreativeWork
    297 https://doi.org/10.1063/1.3680111 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057999402
    298 rdf:type schema:CreativeWork
    299 https://doi.org/10.1063/1.4943679 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023524157
    300 rdf:type schema:CreativeWork
    301 https://doi.org/10.1073/pnas.1319436111 schema:sameAs https://app.dimensions.ai/details/publication/pub.1005026064
    302 rdf:type schema:CreativeWork
    303 https://doi.org/10.1093/bioinformatics/btp699 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036191837
    304 rdf:type schema:CreativeWork
    305 https://doi.org/10.1103/physrevb.82.125416 schema:sameAs https://app.dimensions.ai/details/publication/pub.1060633812
    306 rdf:type schema:CreativeWork
    307 https://doi.org/10.1115/1.3119494 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062101709
    308 rdf:type schema:CreativeWork
    309 https://doi.org/10.1557/mrs.2016.164 schema:sameAs https://app.dimensions.ai/details/publication/pub.1067967397
    310 rdf:type schema:CreativeWork
    311 https://doi.org/10.1557/mrs.2016.93 schema:sameAs https://app.dimensions.ai/details/publication/pub.1067967460
    312 rdf:type schema:CreativeWork
    313 https://www.grid.ac/institutes/grid.133342.4 schema:alternateName University of California, Santa Barbara
    314 schema:name Electrical and Computer Engineering Department, University of California Santa Barbara, 93106, Santa Barbara, CA, USA
    315 Materials Department, University of California Santa Barbara, 93106, Santa Barbara, CA, USA
    316 Mechanical Engineering Department, University of California Santa Barbara, 93106, Santa Barbara, CA, USA
    317 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...