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

Combinatorial screening for new materials in unconstrained composition space with machine learning

(2014) B. Meredig et al.   PHYSICAL REVIEW B

Combinatorial exploration of rare-earth-free permanent magnets: Magnetic and microstructural properties of Fe-Co-W thin films

(2013) T. R. Gao et al.   APPLIED PHYSICS LETTERS

Assessment and Validation of Machine Learning Methods for Predicting Molecular Atomization Energies

(2013) Katja Hansen et al.   Journal of Chemical Theory and Computation

The high-throughput highway to computational materials design

(2013) Stefano Curtarolo et al.   NATURE MATERIALS

Machine learning of molecular electronic properties in chemical compound space

(2013) Grégoire Montavon et al.   NEW JOURNAL OF PHYSICS

Effects of alloying and strain on the magnetic properties of Fe16N2

(2013) Liqin Ke et al.   PHYSICAL REVIEW B

Accelerating materials property predictions using machine learning

(2013) Ghanshyam Pilania et al.   Scientific Reports

AFLOWLIB.ORG: A distributed materials properties repository from high-throughput ab initio calculations

(2012) Stefano Curtarolo et al.   COMPUTATIONAL MATERIALS SCIENCE

The Computational Materials Repository

(2012) David D. Landis et al.   COMPUTING IN SCIENCE & ENGINEERING

Prospects for Non-Rare Earth Permanent Magnets for Traction Motors and Generators

(2012) M. J. Kramer et al.   JOM

Combinatorial search of structural transitions: Systematic investigation of morphotropic phase boundaries in chemically substituted BiFeO3

(2012) Daisuke Kan et al.   JOURNAL OF MATERIALS RESEARCH

Data mining for materials: Computational experiments withABcompounds

(2012) Yousef Saad et al.   PHYSICAL REVIEW B

Finding Density Functionals with Machine Learning

(2012) John C. Snyder et al.   PHYSICAL REVIEW LETTERS

Genetic-Algorithm Discovery of a Direct-Gap and Optically Allowed Superstructure from Indirect-Gap Si and Ge Semiconductors

(2012) Mayeul d’Avezac et al.   PHYSICAL REVIEW LETTERS

Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning

(2012) Matthias Rupp et al.   PHYSICAL REVIEW LETTERS

Understanding and visualizing microstructure and microstructure variance as a stochastic process

(2011) Stephen R. Niezgoda et al.   ACTA MATERIALIA

A high-throughput infrastructure for density functional theory calculations

(2011) Anubhav Jain et al.   COMPUTATIONAL MATERIALS SCIENCE

Bayesian methods for image segmentation

(2011) Mary Comer et al.   JOM

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

(2011) Surya R. Kalidindi et al.   JOM

Neural network potential-energy surfaces in chemistry: a tool for large-scale simulations

(2011) Jörg Behler   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Giant magnetostriction in annealed Co1−xFex thin-films

(2011) Dwight Hunter et al.   Nature Communications

Finding Nature’s Missing Ternary Oxide Compounds Using Machine Learning and Density Functional Theory

(2010) Geoffroy Hautier et al.   CHEMISTRY OF MATERIALS

Comparing efficiencies of genetic and minima hopping algorithms for crystal structure prediction

(2010) Min Ji et al.   PHYSICAL CHEMISTRY CHEMICAL PHYSICS

Neural network approach to quantum-chemistry data: Accurate prediction of density functional theory energies

(2009) Roman M. Balabin et al.   JOURNAL OF CHEMICAL PHYSICS

Strong perpendicular anisotropy inFe1−xCoxalloy films epitaxially grown on mismatching Pd(001), Ir(001), and Rh(001) substrates

(2009) F. Yildiz et al.   PHYSICAL REVIEW B

Rapid identification of structural phases in combinatorial thin-film libraries using x-ray diffraction and non-negative matrix factorization

(2009) C. J. Long et al.   REVIEW OF SCIENTIFIC INSTRUMENTS

A reliable methodology for high throughput identification of a mixture of crystallographic phases from powder X-ray diffraction data

(2008) Laurent Allan Baumes et al.   CRYSTENGCOMM

Application and further development of advanced image processing algorithms for automated analysis of serial section image data

(2008) J P Simmons et al.   MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING

Application of joint histogram and mutual information to registration and data fusion problems in serial sectioning microstructure studies

(2008) E GULSOY et al.   SCRIPTA MATERIALIA

On the use of 2-D moment invariants for the automated classification of particle shapes

(2007) J.P. MacSleyne et al.   ACTA MATERIALIA