Related references
Note: Only part of the references are listed.Bayesian estimation of single ply anisotropic elastic constants from spherical indentations on multi-laminate polymer-matrix fiber-reinforced composite samples
Andrew R. Castillo et al.
MECCANICA (2021)
A digital workflow for learning the reduced-order structure-property linkages for permeability of porous membranes
Yuksel C. Yabansu et al.
ACTA MATERIALIA (2020)
Materials informatics
Seeram Ramakrishna et al.
JOURNAL OF INTELLIGENT MANUFACTURING (2019)
Reduced-order microstructure-sensitive protocols to rank-order the transition fatigue resistance of polycrystalline microstructures
Noah H. Paulson et al.
INTERNATIONAL JOURNAL OF FATIGUE (2019)
Materials knowledge system for nonlinear composites
Marat I. Latypov et al.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2019)
A Bayesian framework for materials knowledge systems
Surya R. Kalidindi
MRS COMMUNICATIONS (2019)
Convolutional Neural Networks for Crystal Material Property Prediction Using Hybrid Orbital-Field Matrix and Magpie Descriptors
Zhuo Cao et al.
CRYSTALS (2019)
Application of Gaussian process regression models for capturing the evolution of microstructure statistics in aging of nickel-based superalloys
Yuksel C. Yabansu et al.
ACTA MATERIALIA (2019)
Transfer learning of deep material network for seamless structure-property predictions
Zeliang Liu et al.
COMPUTATIONAL MECHANICS (2019)
Bayesian Sequential Design of Experiments for Extraction of Single-Crystal Material Properties from Spherical Indentation Measurements on Polycrystalline Samples
Andrew R. Castillo et al.
JOM (2019)
A Bayesian Framework for the Estimation of the Single Crystal Elastic Parameters From Spherical Indentation Stress-Strain Measurements
Andrew Castillo et al.
FRONTIERS IN MATERIALS (2019)
Application of Gaussian process autoregressive models for capturing the time evolution of microstructure statistics from phase-field simulations for sintering of polycrystalline ceramics
Yuksel C. Yabansu et al.
MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING (2019)
An efficient machine learning approach to establish structure-property linkages
Jaimyun Jung et al.
COMPUTATIONAL MATERIALS SCIENCE (2019)
Bayesian approach in predicting mechanical properties of materials: Application to dual phase steels
Jaimyun Jung et al.
MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING (2019)
A Comparative Study of the Efficacy of Local/Global and Parametric/Nonparametric Machine Learning Methods for Establishing Structure-Property Linkages in High-Contrast 3D Elastic Composites
Patxi Fernandez-Zelaia et al.
INTEGRATING MATERIALS AND MANUFACTURING INNOVATION (2019)
Data Infrastructure Elements in Support of Accelerated Materials Innovation: ELA, PyMKS, and MATIN
Surya R. Kalidindi et al.
INTEGRATING MATERIALS AND MANUFACTURING INNOVATION (2019)
Process-Structure-Property Modeling for Severe Plastic Deformation Processes Using Orientation Imaging Microscopy and Data-Driven Techniques
Patxi Fernandez-Zelaia et al.
INTEGRATING MATERIALS AND MANUFACTURING INNOVATION (2019)
Material structure-property linkages using three-dimensional convolutional neural networks
Ahmet Cecen et al.
ACTA MATERIALIA (2018)
Application of spherical indentation and the materials knowledge system framework to establishing microstructure-yield strength linkages from carbon steel scoops excised from high-temperature exposed components
Almambet Iskakov et al.
ACTA MATERIALIA (2018)
Deep learning approaches for mining structure-property linkages in high contrast composites from simulation datasets
Zijiang Yang et al.
COMPUTATIONAL MATERIALS SCIENCE (2018)
A tutorial on Gaussian process regression: Modelling, exploring, and exploiting functions
Eric Schulz et al.
JOURNAL OF MATHEMATICAL PSYCHOLOGY (2018)
Computational microstructure characterization and reconstruction: Review of the state-of-the-art techniques
Ramin Bostanabad et al.
PROGRESS IN MATERIALS SCIENCE (2018)
Data-driven reduced-order models for rank-ordering the high cycle fatigue performance of polycrystalline microstructures
Noah H. Paulson et al.
MATERIALS & DESIGN (2018)
Estimating mechanical properties from spherical indentation using Bayesian approaches
Patxi Fernandez-Zelaia et al.
MATERIALS & DESIGN (2018)
Adaptive Gaussian Process Approximation for Bayesian Inference with Expensive Likelihood Functions
Hongqiao Wang et al.
NEURAL COMPUTATION (2018)
Crystal Plasticity Model Calibration for Ti-7Al Alloy with a Multi-fidelity Computational Scheme
Pinar Acar
INTEGRATING MATERIALS AND MANUFACTURING INNOVATION (2018)
Strategies for rapid parametric assessment of microstructure-sensitive fatigue for HCP polycrystals
Matthew W. Priddy et al.
INTERNATIONAL JOURNAL OF FATIGUE (2017)
Data-driven reduced order models for effective yield strength and partitioning of strain in multiphase materials
Marat I. Latypov et al.
JOURNAL OF COMPUTATIONAL PHYSICS (2017)
Data Descriptor: Machine-learned and codified synthesis parameters of oxide materials
Edward Kim et al.
SCIENTIFIC DATA (2017)
Machine learning in materials informatics: recent applications and prospects
Rampi Ramprasad et al.
NPJ COMPUTATIONAL MATERIALS (2017)
Extracting knowledge from molecular mechanics simulations of grain boundaries using machine learning
Joshua A. Gomberg et al.
ACTA MATERIALIA (2017)
Materials discovery and design using machine learning
Yue Liu et al.
JOURNAL OF MATERIOMICS (2017)
Strain fields induced by kink band propagation in Cu-Nb nanolaminate composites
T. J. Nizolek et al.
ACTA MATERIALIA (2017)
Reduced-order structure-property linkages for polycrystalline microstructures based on 2-point statistics
Noah H. Paulson et al.
ACTA MATERIALIA (2017)
Process-Structure Linkages Using a Data Science Approach: Application to Simulated Additive Manufacturing Data
Evdokia Popova et al.
INTEGRATING MATERIALS AND MANUFACTURING INNOVATION (2017)
Extraction of reduced-order process-structure linkages from phase-field simulations
Yuksel C. Yabansu et al.
ACTA MATERIALIA (2017)
Statistical construction of 3-D microstructures from 2-D exemplars collected on oblique sections
David M. Turner et al.
ACTA MATERIALIA (2016)
Image driven machine learning methods for microstructure recognition
Aritra Chowdhury et al.
COMPUTATIONAL MATERIALS SCIENCE (2016)
The Materials Data Facility: Data Services to Advance Materials Science Research
B. Blaiszik et al.
JOM (2016)
Vision for Data and Informatics in the Future Materials Innovation Ecosystem
Surya R. Kalidindi et al.
JOM (2016)
Polycrystal plasticity modeling of nickel-based superalloy IN 617 subjected to cyclic loading at high temperature
Xiang Zhang et al.
MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING (2016)
The materials innovation ecosystem: A key enabler for the Materials Genome Initiative
David L. McDowell et al.
MRS BULLETIN (2016)
Machine-learning-assisted materials discovery using failed experiments
Paul Raccuglia et al.
NATURE (2016)
Machine learning bandgaps of double perovskites
G. Pilania et al.
SCIENTIFIC REPORTS (2016)
Versatile algorithms for the computation of 2-point spatial correlations in quantifying material structure
Ahmet Cecen et al.
INTEGRATING MATERIALS AND MANUFACTURING INNOVATION (2016)
Experiment-based validation and uncertainty quantification of coupled multi-scale plasticity models
Garrison Stevens et al.
MULTIDISCIPLINE MODELING IN MATERIALS AND STRUCTURES (2016)
Representation and calibration of elastic localization kernels for a broad class of cubic polycrystals
Yuksel C. Yabansu et al.
ACTA MATERIALIA (2015)
Materials Data Science: Current Status and Future Outlook
Surya R. Kalidindi et al.
ANNUAL REVIEW OF MATERIALS RESEARCH, VOL 45 (2015)
X-TMCMC: Adaptive kriging for Bayesian inverse modeling
Panagiotis Angelikopoulos et al.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2015)
Local Gaussian Process Approximation for Large Computer Experiments
Robert B. Gramacy et al.
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS (2015)
Effect of martensite volume fraction on low cycle fatigue behaviour of dual phase steels: Experimental and microstructural investigation
Surajit Kumar Paul et al.
MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING (2015)
Application of data science tools to quantify and distinguish between structures and models in molecular dynamics datasets
Surya R. Kalidindi et al.
NANOTECHNOLOGY (2015)
Data science and cyberinfrastructure: critical enablers for accelerated development of hierarchical materials
Surya R. Kalidindi
INTERNATIONAL MATERIALS REVIEWS (2015)
High-throughput experimental tools for the materials genome initiative
Ji-Cheng Zhao
CHINESE SCIENCE BULLETIN (2014)
Materials Genome Initiative: Advances and Initiatives
JOM (2014)
A data-driven approach to establishing microstructure-property relationships in porous transport layers of polymer electrolyte fuel cells
A. Cecen et al.
JOURNAL OF POWER SOURCES (2014)
Four-Dimensional Morphological Evolution of an Aluminum Silicon Alloy Using Propagation-Based Phase Contrast X-ray Tomographic Microscopy
Emine Begum Gulsoy et al.
MATERIALS TRANSACTIONS (2014)
Combinatorial screening for new materials in unconstrained composition space with machine learning
B. Meredig et al.
PHYSICAL REVIEW B (2014)
Materials genomics: From CALPHAD to flight
G. B. Olson et al.
SCRIPTA MATERIALIA (2014)
Reconstruction of three-dimensional anisotropic microstructures from two-dimensional micrographs imaged on orthogonal planes
Veera Sundararaghavan
INTEGRATING MATERIALS AND MANUFACTURING INNOVATION (2014)
ICMEg - the Integrated Computational Materials Engineering expert group - a new European coordination action
Georg J. Schmitz et al.
INTEGRATING MATERIALS AND MANUFACTURING INNOVATION (2014)
Stalking the Materials Genome: A Data-Driven Approach to the Virtual Design of Nanostructured Polymers
Curt M. Breneman et al.
ADVANCED FUNCTIONAL MATERIALS (2013)
Simulation-based optimal Bayesian experimental design for nonlinear systems
Xun Huan et al.
JOURNAL OF COMPUTATIONAL PHYSICS (2013)
Effects of volume fraction on the microstructure and tensile properties of in situ TiBw/Ti6Al4V composites with novel network microstructure
L. J. Huang et al.
MATERIALS & DESIGN (2013)
Machine Learning of Hierarchical Clustering to Segment 2D and 3D Images
Juan Nunez-Iglesias et al.
PLOS ONE (2013)
X-Ray Tomography of Porous, Transition Metal Oxide Based Lithium Ion Battery Electrodes
Martin Ebner et al.
ADVANCED ENERGY MATERIALS (2013)
Accelerating materials property predictions using machine learning
Ghanshyam Pilania et al.
SCIENTIFIC REPORTS (2013)
Commentary: The Materials Project: A materials genome approach to accelerating materials innovation
Anubhav Jain et al.
APL MATERIALS (2013)
Novel microstructure quantification framework for databasing, visualization, and analysis of microstructure data
Stephen R. Niezgoda et al.
INTEGRATING MATERIALS AND MANUFACTURING INNOVATION (2013)
Influence of martensite volume fraction and cooling rate on the properties of thermomechanically processed dual phase steel
Mehdi Asadi et al.
MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING (2012)
Understanding and visualizing microstructure and microstructure variance as a stochastic process
Stephen R. Niezgoda et al.
ACTA MATERIALIA (2011)
Automated serial sectioning methods for rapid collection of 3-D microstructure data
Michael D. Uchic et al.
JOM (2011)
High-energy diffraction microscopy at the advanced photon source
U. Lienert et al.
JOM (2011)
Optimized structure based representative volume element sets reflecting the ensemble-averaged 2-point statistics
Stephen R. Niezgoda et al.
ACTA MATERIALIA (2010)
Microstructure sensitive design for performance optimization
David T. Fullwood et al.
PROGRESS IN MATERIALS SCIENCE (2010)
Atom probe tomography
M. K. Miller et al.
MATERIALS CHARACTERIZATION (2009)
Neural Networks and Information in Materials Science
H. K. D. H. Bhadeshia
Statistical Analysis and Data Mining (2009)
A new spectral framework for establishing localization relationships for elastic behavior of composites and their calibration to finite-element models
Massimiliano Binci et al.
ACTA MATERIALIA (2008)
Delineation of the space of 2-point correlations in a composite material system
S. R. Niezgoda et al.
ACTA MATERIALIA (2008)
Microstructure reconstructions from 2-point statistics using phase-recovery algorithms
David T. Fullwood et al.
ACTA MATERIALIA (2008)
Concurrent design of hierarchical materials and structures
D. L. McDowell et al.
SCIENTIFIC MODELING AND SIMULATIONS (2008)
Gaussian process regression for multivariate spectroscopic calibration
Tao Chen et al.
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS (2007)
Three-dimensional microstructural characterization using focused ion beam tomography
Michael D. Uchic et al.
MRS BULLETIN (2007)
Three-dimensional study of a fretting crack using synchrotron X-ray micro-tomography
H. Proudhon et al.
ENGINEERING FRACTURE MECHANICS (2007)
Elastic properties closures using second-order homogenization theories: Case studies in composites of two isotropic constituents
Surya R. Kalidindi et al.
ACTA MATERIALIA (2006)
Finite approximations to the second-order properties closure in single phase polycrystals
BL Adams et al.
ACTA MATERIALIA (2005)
Regularization and variable selection via the elastic net
H Zou et al.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY (2005)
Principal manifolds and nonlinear dimensionality reduction via tangent space alignment
ZY Zhang et al.
SIAM JOURNAL ON SCIENTIFIC COMPUTING (2004)
Amazon.com recommendation - Item-to-item collaborative filtering
G Linden et al.
IEEE INTERNET COMPUTING (2003)
Statistical continuum theory for large plastic deformation of polycrystalline materials
H Garmestani et al.
JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS (2001)
Nonlinear dimensionality reduction by locally linear embedding
ST Roweis et al.
SCIENCE (2000)
Share Paper
