Data-centric science for materials innovation

Compositional descriptor-based recommender system for the materials discovery

(2018) Atsuto Seko et al.   JOURNAL OF CHEMICAL PHYSICS

Predicting the stability of ternary intermetallics with density functional theory and machine learning

(2018) Jonathan Schmidt et al.   JOURNAL OF CHEMICAL PHYSICS

An open experimental database for exploring inorganic materials

(2018) Andriy Zakutayev et al.   Scientific Data

Accelerated discovery of metallic glasses through iteration of machine learning and high-throughput experiments

(2018) Fang Ren et al.   Science Advances

Matrix- and tensor-based recommender systems for the discovery of currently unknown inorganic compounds

(2018) Atsuto Seko et al.   PHYSICAL REVIEW MATERIALS

Harnessing the Materials Project for machine-learning and accelerated discovery

(2018) Weike Ye et al.   MRS BULLETIN

Strategies for accelerating the adoption of materials informatics

(2018) Logan Ward et al.   MRS BULLETIN

Provenance, workflows, and crystallographic tools in materials science: AiiDA, spglib, and seekpath

(2018) Giovanni Pizzi et al.   MRS BULLETIN

Prediction Errors of Molecular Machine Learning Models Lower than Hybrid DFT Error

(2017) Felix A. Faber et al.   Journal of Chemical Theory and Computation

Quantum-chemical insights from deep tensor neural networks

(2017) Kristof T. Schütt et al.   Nature Communications

Universal fragment descriptors for predicting properties of inorganic crystals

(2017) Olexandr Isayev et al.   Nature Communications

Machine learning of accurate energy-conserving molecular force fields

(2017) Stefan Chmiela et al.   Science Advances

Machine learning in materials informatics: recent applications and prospects

(2017) Rampi Ramprasad et al.   npj Computational Materials

Automated crystal structure solution from powder diffraction data: Validation of the first-principles-assisted structure solution method

(2017) Logan Ward et al.   PHYSICAL REVIEW MATERIALS

Machine Learning Energies of 2 Million Elpasolite(ABC2D6)Crystals

(2016) Felix A. Faber et al.   PHYSICAL REVIEW LETTERS

A general-purpose machine learning framework for predicting properties of inorganic materials

(2016) Logan Ward et al.   npj Computational Materials

The materials genome in action: identifying the performance limits for methane storage

(2015) Cory M. Simon et al.   Energy & Environmental Science

Special quasirandom structure in heterovalent ionic systems

(2015) Atsuto Seko et al.   PHYSICAL REVIEW B

Informatics derived materials databases for multifunctional properties

(2015) Scott Broderick et al.   SCIENCE AND TECHNOLOGY OF ADVANCED MATERIALS

The Open Quantum Materials Database (OQMD): assessing the accuracy of DFT formation energies

(2015) Scott Kirklin et al.   npj Computational Materials

Dissolving the Periodic Table in Cubic Zirconia: Data Mining to Discover Chemical Trends

(2014) Bryce Meredig et al.   CHEMISTRY OF MATERIALS

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

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

The high-throughput highway to computational materials design

(2013) Stefano Curtarolo et al.   NATURE MATERIALS

A hybrid computational–experimental approach for automated crystal structure solution

(2012) Bryce Meredig et al.   NATURE MATERIALS

Ab initiorandom structure searching

(2011) Chris J Pickard et al.   JOURNAL OF PHYSICS-CONDENSED MATTER

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

(2010) Geoffroy Hautier et al.   CHEMISTRY OF MATERIALS

Crystal structure prediction using the minima hopping method

(2010) Maximilian Amsler et al.   JOURNAL OF CHEMICAL PHYSICS

Crystal structure prediction via particle-swarm optimization

(2010) Yanchao Wang et al.   PHYSICAL REVIEW B

Combinatorial Materials Sciences: Experimental Strategies for Accelerated Knowledge Discovery

(2008) Krishna Rajan   Annual Review of Materials Research