Title: Evaluating generalized feature importance via performance assessment of machine learning models for predicting elastic properties of materials

Journal Article · · Computational Materials Science
ORCiD logo; ; ORCiD logo; ;

Not Available

Sponsoring Organization:
USDOE
OSTI ID:
2369659
Journal Information:
Computational Materials Science, Journal Name: Computational Materials Science Journal Issue: C Vol. 236; ISSN 0927-0256
Publisher:
ElsevierCopyright Statement
Country of Publication:
Netherlands
Language:
English

References (50)

Two Dimensional Materials Beyond MoS 2 : Noble-Transition-Metal Dichalcogenides journal February 2014
Fast Parallel Algorithms for Short-Range Molecular Dynamics journal March 1995
Kernel Ridge Regression book January 2013
A Review on Die Attach Materials for SiC-Based High-Temperature Power Devices journal April 2010
Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set journal July 1996
Ductility improvement of amorphous steels: Roles of shear modulus and electronic structure journal January 2008
Valence electron concentration as an indicator for mechanical properties in rocksalt structure nitrides, carbides and carbonitrides journal June 2018
Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis journal February 2013
Matminer: An open source toolkit for materials data mining journal September 2018
Machine learning for hierarchical prediction of elastic properties in Fe-Cr-Al system journal August 2019
Machine learning elastic constants of multi-component alloys journal October 2021
USPEX—Evolutionary crystal structure prediction journal December 2006
The elastic properties, elastic models and elastic perspectives of metallic glasses journal April 2012
Industrial applications of superhard nanocomposite coatings journal July 2008
Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals journal April 2019
The XtalOpt Evolutionary Algorithm for Crystal Structure Prediction journal December 2020
Machine Learning-Aided Design of Materials with Target Elastic Properties journal February 2019
Predicting the Band Gaps of Inorganic Solids by Machine Learning journal March 2018
Learning with Delayed Rewards—A Case Study on Inverse Defect Design in 2D Materials journal July 2021
Unusual High Hardness and Load-Dependent Mechanical Characteristics of Hydrogenated Carbon–Nitrogen Hybrid Films journal April 2022
Machine Learning Directed Search for Ultraincompressible, Superhard Materials journal July 2018
A tutorial on support vector regression journal August 2004
Electronic mechanism of hardness enhancement in transition-metal carbonitrides journal May 1999
Universal fragment descriptors for predicting properties of inorganic crystals journal June 2017
A general-purpose machine learning framework for predicting properties of inorganic materials journal August 2016
Learning in continuous action space for developing high dimensional potential energy models journal January 2022
Explaining a series of models by propagating Shapley values journal August 2022
Benchmarking materials property prediction methods: the Matbench test set and Automatminer reference algorithm journal September 2020
Benchmarking graph neural networks for materials chemistry journal June 2021
Atomistic Line Graph Neural Network for improved materials property predictions journal November 2021
Predicting elastic properties of hard-coating alloys using ab-initio and machine learning methods journal January 2022
CEGANN: Crystal Edge Graph Attention Neural Network for multiscale classification of materials environment journal February 2023
A Continuous Action Space Tree search for INverse desiGn (CASTING) framework for materials discovery journal September 2023
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead journal May 2019
A Statistical Learning Framework for Materials Science: Application to Elastic Moduli of k-nary Inorganic Polycrystalline Compounds journal October 2016
Comparing molecules and solids across structural and alchemical space journal January 2016
Artificial intelligence and machine learning in design of mechanical materials journal January 2021
The Voigt‐Reuss‐Hill Approximation and Elastic Moduli of Polycrystalline MgO, CaF 2 , β‐ZnS, ZnSe, and CdTe journal May 1967
Commentary: The Materials Project: A materials genome approach to accelerating materials innovation journal July 2013
Application of machine learning methods for predicting new superhard materials journal August 2020
Reinforcement learning in discrete action space applied to inverse defect design journal March 2021
Ab initiomolecular dynamics for liquid metals journal January 1993
On representing chemical environments journal May 2013
Vacancy-induced mechanical stabilization of cubic tungsten nitride journal November 2016
Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties journal April 2018
Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy journal August 2005
The search for novel, superhard materials journal September 1999
Elementary Solid State Physics: A Short Course journal August 1963
Reconfigurable perovskite nickelate electronics for artificial intelligence journal February 2022
Minimum redundancy maximum relevance feature selection approach for temporal gene expression data journal January 2017

Similar Records

Related Subjects