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Materials Data Science: Current Status and Future Outlook

Annual review of materials research, 2015-07, Vol.45 (1), p.171-193

2015

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Key computational modeling issues in Integrated Computational Materials Engineering

Computer aided design, 2013-01, Vol.45 (1), p.4-25

2013

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Biomaterialomics: Data science-driven pathways to develop fourth-generation biomaterials

Acta biomaterialia, 2022-04, Vol.143, p.1-25

2022

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Estimating the slip resistance from spherical nanoindentation and orientation measurements in polycrystalline samples of cubic metals

International journal of plasticity, 2017-05, Vol.92 (C), p.19-30

2017

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Feature engineering of material structure for AI-based materials knowledge systems

Journal of applied physics, 2020-07, Vol.128 (4)

Kalidindi, Surya R.

2020

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Sequential Designs for Filling Output Spaces

Technometrics, 2024-01, Vol.66 (1), p.65-76

2024

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Mechanical characterization of grain boundaries using nanoindentation

Current opinion in solid state & materials science, 2014-08, Vol.18 (4), p.196-204

2014

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Bayesian estimation of single ply anisotropic elastic constants from spherical indentations on multi-laminate polymer-matrix fiber-reinforced composite samples

Meccanica (Milan), 2021-06, Vol.56 (6), p.1575-1586

2021

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Microstructure informatics using higher-order statistics and efficient data-mining protocols

JOM (1989), 2011-04, Vol.63 (4), p.34-41

2011

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Spherical nanoindentation stress–strain curves

Materials science & engineering. R, Reports : a review journal, 2015-05, Vol.91 (C), p.1-36

2015

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Evaluation of Ti–Mn Alloys for Additive Manufacturing Using High-Throughput Experimental Assays and Gaussian Process Regression

Materials, 2020-10, Vol.13 (20), p.4641

2020

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Understanding pop-ins in spherical nanoindentation

Applied physics letters, 2014-10, Vol.105 (16)

2014

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Studying grain boundary regions in polycrystalline materials using spherical nano-indentation and orientation imaging microscopy

Journal of materials science, 2012-01, Vol.47 (2), p.815-823

2012

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Study of a Bimodal α–β Ti Alloy Microstructure Using Multi-Resolution Spherical Indentation Stress-Strain Protocols

Journal of composites science, 2022-06, Vol.6 (6), p.162

2022

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Application of Gaussian process autoregressive models for capturing the time evolution of microstructure statistics from phase-field simulations for sintering of polycrystalline ceramics

Modelling and simulation in materials science and engineering, 2019-09, Vol.27 (8), p.84006

2019

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Probing nanoscale damage gradients in ion-irradiated metals using spherical nanoindentation

Scientific reports, 2017-09, Vol.7 (1), p.11918-12, Article 11918

2017

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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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Modeling anisotropic strain hardening and deformation textures in low stacking fault energy fcc metals

International journal of plasticity, 2001-01, Vol.17 (6), p.837-860

Kalidindi, S R

2001

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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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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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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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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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Materials Data Science: Current Status and Future Outlook

Key computational modeling issues in Integrated Computational Materials Engineering

Biomaterialomics: Data science-driven pathways to develop fourth-generation biomaterials

Estimating the slip resistance from spherical nanoindentation and orientation measurements in polycrystalline samples of cubic metals

Feature engineering of material structure for AI-based materials knowledge systems

Sequential Designs for Filling Output Spaces

Mechanical characterization of grain boundaries using nanoindentation

Bayesian estimation of single ply anisotropic elastic constants from spherical indentations on multi-laminate polymer-matrix fiber-reinforced composite samples

Microstructure informatics using higher-order statistics and efficient data-mining protocols

Spherical nanoindentation stress–strain curves

Evaluation of Ti–Mn Alloys for Additive Manufacturing Using High-Throughput Experimental Assays and Gaussian Process Regression

Understanding pop-ins in spherical nanoindentation

Studying grain boundary regions in polycrystalline materials using spherical nano-indentation and orientation imaging microscopy

Study of a Bimodal α–β Ti Alloy Microstructure Using Multi-Resolution Spherical Indentation Stress-Strain Protocols

Application of Gaussian process autoregressive models for capturing the time evolution of microstructure statistics from phase-field simulations for sintering of polycrystalline ceramics

Probing nanoscale damage gradients in ion-irradiated metals using spherical nanoindentation

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

Modeling anisotropic strain hardening and deformation textures in low stacking fault energy fcc metals

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

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

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

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

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