Machine learning in materials design and discovery: Examples from the present and suggestions for the future

Accelerated Discovery of Large Electrostrains in BaTiO3 -Based Piezoelectrics Using Active Learning

(2018) Ruihao Yuan et al.   ADVANCED MATERIALS

Identifying interphase properties in polymer nanocomposites using adaptive optimization

(2018) Yixing Wang et al.   COMPOSITES SCIENCE AND TECHNOLOGY

Multi-objective Optimization for Materials Discovery via Adaptive Design

(2018) Abhijith M. Gopakumar et al.   Scientific Reports

Multifunctional structural design of graphene thermoelectrics by Bayesian optimization

(2018) Masaki Yamawaki et al.   Science Advances

Predictions of new ABO3 perovskite compounds by combining machine learning and density functional theory

(2018) Prasanna V. Balachandran et al.   PHYSICAL REVIEW MATERIALS

Machine learning for molecular and materials science

(2018) Keith T. Butler et al.   NATURE

Efficient search of compositional space for hybrid organic–inorganic perovskites via Bayesian optimization

(2018) Henry C. Herbol et al.   npj Computational Materials

Extracting Grain Orientations from EBSD Patterns of Polycrystalline Materials Using Convolutional Neural Networks

(2018) Dipendra Jha et al.   MICROSCOPY AND MICROANALYSIS

Materials Screening for the Discovery of New Half-Heuslers: Machine Learning versus ab Initio Methods

(2017) Fleur Legrain et al.   JOURNAL OF PHYSICAL CHEMISTRY B

Why Does Deep and Cheap Learning Work So Well?

(2017) Henry W. Lin et al.   JOURNAL OF STATISTICAL PHYSICS

Selecting the selector: Comparison of update rules for discrete global optimization

(2017) James Theiler et al.   Statistical Analysis and Data Mining

Wave Functions, Density Functionals, and Artificial Intelligence for Materials and Energy Research: Future Prospects and Challenges

(2017) Martín A. Mosquera et al.   ACS Energy Letters

Multi-objective optimization techniques to design the Pareto front of organic dielectric polymers

(2016) Arun Mannodi-Kanakkithodi et al.   COMPUTATIONAL MATERIALS SCIENCE

Multiobjective optimization of expensive-to-evaluate deterministic computer simulator models

(2016) Joshua Svenson et al.   COMPUTATIONAL STATISTICS & DATA ANALYSIS

Materials informatics: a journey towards material design and synthesis

(2016) Keisuke Takahashi et al.   DALTON TRANSACTIONS

Acceleration of stable interface structure searching using a kriging approach

(2016) Shin Kiyohara et al.   JAPANESE JOURNAL OF APPLIED PHYSICS

New opportunities for materials informatics: Resources and data mining techniques for uncovering hidden relationships

(2016) Anubhav Jain et al.   JOURNAL OF MATERIALS RESEARCH

The optimal one dimensional periodic table: a modified Pettifor chemical scale from data mining

(2016) Henning Glawe et al.   NEW JOURNAL OF PHYSICS

Accelerated search for materials with targeted properties by adaptive design

(2016) Dezhen Xue et al.   Nature Communications

Optimisation of GaN LEDs and the reduction of efficiency droop using active machine learning

(2016) Bertrand Rouet-Leduc et al.   Scientific Reports

The thermodynamic scale of inorganic crystalline metastability

(2016) W. Sun et al.   Science Advances

Machine Learning Strategy for Accelerated Design of Polymer Dielectrics

(2016) Arun Mannodi-Kanakkithodi et al.   Scientific Reports

Adaptive Strategies for Materials Design using Uncertainties

(2016) Prasanna V. Balachandran et al.   Scientific Reports

Optimal Experimental Design for Gene Regulatory Networks in the Presence of Uncertainty

(2015) Roozbeh Dehghannasiri et al.   IEEE-ACM Transactions on Computational Biology and Bioinformatics

A Review of Modern Computational Algorithms for Bayesian Optimal Design

(2015) Elizabeth G. Ryan et al.   INTERNATIONAL STATISTICAL REVIEW

On using the hypervolume indicator to compare Pareto fronts: Applications to multi-criteria optimal experimental design

(2015) Yongtao Cao et al.   JOURNAL OF STATISTICAL PLANNING AND INFERENCE

Structure classification and melting temperature prediction in octet AB solids via machine learning

(2015) G. Pilania et al.   PHYSICAL REVIEW B

Prediction of Low-Thermal-Conductivity Compounds with First-Principles Anharmonic Lattice-Dynamics Calculations and Bayesian Optimization

(2015) Atsuto Seko et al.   PHYSICAL REVIEW LETTERS

Classification ofABO3perovskite solids: a machine learning study

(2015) G. Pilania et al.   Acta Crystallographica Section B-Structural Science Crystal Engineering and Materials

Optimal Learning in Experimental Design Using the Knowledge Gradient Policy with Application to Characterizing Nanoemulsion Stability

(2015) Si Chen et al.   SIAM-ASA Journal on Uncertainty Quantification

Machine learning with systematic density-functional theory calculations: Application to melting temperatures of single- and binary-component solids

(2014) Atsuto Seko et al.   PHYSICAL REVIEW B

On-the-fly machine-learning for high-throughput experiments: search for rare-earth-free permanent magnets

(2014) Aaron Gilad Kusne et al.   Scientific Reports

RECURSIVE CO-KRIGING MODEL FOR DESIGN OF COMPUTER EXPERIMENTS WITH MULTIPLE LEVELS OF FIDELITY

(2014) Loic Le Gratiet et al.   International Journal for Uncertainty Quantification

Quantifying the Objective Cost of Uncertainty in Complex Dynamical Systems

(2013) Byung-Jun Yoon et al.   IEEE TRANSACTIONS ON SIGNAL PROCESSING

Materials Design and Discovery with High-Throughput Density Functional Theory: The Open Quantum Materials Database (OQMD)

(2013) James E. Saal et al.   JOM

Adaptive reconstruction method for three-dimensional orientation imaging

(2013) S. F. Li et al.   JOURNAL OF APPLIED CRYSTALLOGRAPHY

The high-throughput highway to computational materials design

(2013) Stefano Curtarolo et al.   NATURE MATERIALS

Adapting the Hypervolume Quality Indicator to Quantify Trade-offs and Search Efficiency for Multiple Criteria Decision Making Using Pareto Fronts

(2013) Lu Lu et al.   QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL

Commentary: The Materials Project: A materials genome approach to accelerating materials innovation

(2013) Anubhav Jain et al.   APL Materials

Bayesian Analysis of Hierarchical Multifidelity Codes

(2013) Loic Le Gratiet   SIAM-ASA Journal on Uncertainty Quantification

Crystallography Open Database (COD): an open-access collection of crystal structures and platform for world-wide collaboration

(2011) Saulius Gražulis et al.   NUCLEIC ACIDS RESEARCH

Hypervolume-based multiobjective optimization: Theoretical foundations and practical implications

(2011) Anne Auger et al.   THEORETICAL COMPUTER SCIENCE

Data Mined Ionic Substitutions for the Discovery of New Compounds

(2010) Geoffroy Hautier et al.   INORGANIC CHEMISTRY

Recent Developments in the Methods and Applications of the Bond Valence Model

(2009) Ian David Brown   CHEMICAL REVIEWS

The Value of Information in Spatial Decision Making

(2009) Debarun Bhattacharjya et al.   Mathematical Geosciences

Tensor Decompositions and Applications

(2009) Tamara G. Kolda et al.   SIAM REVIEW

A Knowledge-Gradient Policy for Sequential Information Collection

(2008) Peter I. Frazier et al.   SIAM JOURNAL ON CONTROL AND OPTIMIZATION