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Exploration of data science techniques to predict fatigue strength of steel from composition and processing parameters

Integrating materials and manufacturing innovation, 2014-12, Vol.3 (1), p.90-108

2014

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Novel microstructure quantification framework for databasing, visualization, and analysis of microstructure data

Integrating materials and manufacturing innovation, 2013-12, Vol.2 (1), p.54-80

2013

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Extracting single-crystal elastic constants from polycrystalline samples using spherical nanoindentation and orientation measurements

Acta materialia, 2014-10, Vol.79, p.108-116

2014

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Role of materials data science and informatics in accelerated materials innovation

MRS bulletin, 2016-08, Vol.41 (8), p.596-602

2016

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Data science and cyberinfrastructure: critical enablers for accelerated development of hierarchical materials

International materials reviews, 2015-04, Vol.60 (3), p.150-168

Kalidindi, Surya R.

2015

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Viscoelasticity and high buckling stress of dense carbon nanotube brushes

Carbon (New York), 2009-07, Vol.47 (8), p.1969-1976

2009

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Strain hardening of titanium: role of deformation twinning

Acta materialia, 2003-08, Vol.51 (14), p.4225-4237

2003

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Building texture evolution networks for deformation processing of polycrystalline fcc metals using spectral approaches: Applications to process design for targeted performance

International journal of plasticity, 2010-08, Vol.26 (8), p.1183-1194

2010

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A Generalized and Modular Framework for Digital Generation of Composite Microstructures

Journal of composites science, 2021-08, Vol.5 (8), p.211

2021

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Correlation of spherical nanoindentation stress-strain curves to simple compression stress-strain curves for elastic-plastic isotropic materials using finite element models

Acta materialia, 2016-06, Vol.112 (C), p.295-302

2016

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Material structure-property linkages using three-dimensional convolutional neural networks

Acta materialia, 2018-03, Vol.146, p.76-84

2018

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Importance of surface preparation on the nano-indentation stress-strain curves measured in metals

Journal of materials research, 2009-03, Vol.24 (3), p.1142-1155

2009

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Microstructure Sensitive Design for Performance Optimization

1, 2012

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An approach towards plastic scintillators from thermally activated delayed fluorescent dyes and cross-linkable bismuth compounds

Journal of materials chemistry. C, Materials for optical and electronic devices, 2022-12, Vol.1 (46), p.17481-17488

2022

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Structure–property linkages using a data science approach: Application to a non-metallic inclusion/steel composite system

Acta materialia, 2015-06, Vol.91, p.239-254

2015

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Autonomous Development of a Machine-Learning Model for the Plastic Response of Two-Phase Composites from Micromechanical Finite Element Models

JOM (1989), 2021-07, Vol.73 (7), p.2085-2095

2021

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Bayesian analysis of parametric uncertainties and model form probabilities for two different crystal plasticity models of lamellar grains in α+β Titanium alloys

International journal of plasticity, 2022-07, Vol.154, p.103289, Article 103289

2022

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Quantification and classification of microstructures in ternary eutectic alloys using 2-point spatial correlations and principal component analyses

Acta materialia, 2016-05, Vol.110, p.131-141

2016

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Critical Comparison of Spherical Microindentation, Small Punch Test, and Uniaxial Tensile Testing for Selective Laser Melted Inconel 718

Applied sciences, 2021-01, Vol.11 (3), p.1061

2021

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Deep learning approaches for mining structure-property linkages in high contrast composites from simulation datasets

Computational materials science, 2018-08, Vol.151 (C), p.278-287

2018

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Establishing structure-property localization linkages for elastic deformation of three-dimensional high contrast composites using deep learning approaches

Acta materialia, 2019-03, Vol.166 (C), p.335-345

2019

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Hierarchical Materials Informatics: Novel Analytics for Materials Data

Kalidindi, Surya R

1, 2015

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A hybrid approach for the efficient computation of polycrystalline yield loci with the accuracy of the crystal plasticity finite element method

Modelling and simulation in materials science and engineering, 2022-03, Vol.30 (2), p.25015

2022

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Addressing biases in spectral databases for increasing accuracy and computational efficiency of crystal plasticity computations

International journal of plasticity, 2021-03, Vol.138, p.102945, Article 102945

2021

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Decoding defect statistics from diffractograms via machine learning

npj computational materials, 2021-05, Vol.7 (1), p.1-9, Article 67

2021

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Exploration of data science techniques to predict fatigue strength of steel from composition and processing parameters

Novel microstructure quantification framework for databasing, visualization, and analysis of microstructure data

Extracting single-crystal elastic constants from polycrystalline samples using spherical nanoindentation and orientation measurements

Role of materials data science and informatics in accelerated materials innovation

Data science and cyberinfrastructure: critical enablers for accelerated development of hierarchical materials

Viscoelasticity and high buckling stress of dense carbon nanotube brushes

Strain hardening of titanium: role of deformation twinning

Building texture evolution networks for deformation processing of polycrystalline fcc metals using spectral approaches: Applications to process design for targeted performance

A Generalized and Modular Framework for Digital Generation of Composite Microstructures

Correlation of spherical nanoindentation stress-strain curves to simple compression stress-strain curves for elastic-plastic isotropic materials using finite element models

Material structure-property linkages using three-dimensional convolutional neural networks

Importance of surface preparation on the nano-indentation stress-strain curves measured in metals

Microstructure Sensitive Design for Performance Optimization

An approach towards plastic scintillators from thermally activated delayed fluorescent dyes and cross-linkable bismuth compounds

Structure–property linkages using a data science approach: Application to a non-metallic inclusion/steel composite system

Autonomous Development of a Machine-Learning Model for the Plastic Response of Two-Phase Composites from Micromechanical Finite Element Models

Bayesian analysis of parametric uncertainties and model form probabilities for two different crystal plasticity models of lamellar grains in α+β Titanium alloys

Quantification and classification of microstructures in ternary eutectic alloys using 2-point spatial correlations and principal component analyses

Critical Comparison of Spherical Microindentation, Small Punch Test, and Uniaxial Tensile Testing for Selective Laser Melted Inconel 718

Deep learning approaches for mining structure-property linkages in high contrast composites from simulation datasets

Establishing structure-property localization linkages for elastic deformation of three-dimensional high contrast composites using deep learning approaches

Hierarchical Materials Informatics: Novel Analytics for Materials Data

A hybrid approach for the efficient computation of polycrystalline yield loci with the accuracy of the crystal plasticity finite element method

Addressing biases in spectral databases for increasing accuracy and computational efficiency of crystal plasticity computations

Decoding defect statistics from diffractograms via machine learning

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