Machine Learning versus Human Learning in Predicting Glass-Forming Ability of Metallic Glasses

Predicting elastic properties of hard-coating alloys using ab-initio and machine learning methods

(2022) H. Levämäki et al.   npj Computational Materials

Accelerated identification of equilibrium structures of multicomponent inorganic crystals using machine learning potentials

(2022) Sungwoo Kang et al.   npj Computational Materials

Machine learning sparse tight-binding parameters for defects

(2022) Christoph Schattauer et al.   npj Computational Materials

Compositional dependence of the fragility in metallic glass forming liquids

(2022) Sebastian A. Kube et al.   Nature Communications

Machine learning prediction of glass-forming ability in bulk metallic glasses

(2021) Jie Xiong et al.   COMPUTATIONAL MATERIALS SCIENCE

Machine learning for alloys

(2021) Gus L. W. Hart et al.   Nature Reviews Materials

Catalytic materials and chemistry development using a synergistic combination of machine learning and ab initio methods

(2020) Nilesh Varadan Orupattur et al.   COMPUTATIONAL MATERIALS SCIENCE

Opportunities and Challenges for Machine Learning in Materials Science

(2020) Dane Morgan et al.   Annual Review of Materials Research

Phase Selection Motifs in High Entropy Alloys Revealed Through Combinatorial Methods: Large Atomic Size Difference Favors BCC over FCC

(2019) Sebastian Alexander Kube et al.   ACTA MATERIALIA

Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals

(2019) Chi Chen et al.   CHEMISTRY OF MATERIALS

High-temperature bulk metallic glasses developed by combinatorial methods

(2019) Ming-Xing Li et al.   NATURE

Recent advances and applications of machine learning in solid-state materials science

(2019) Jonathan Schmidt et al.   npj Computational Materials

Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties

(2018) Tian Xie et al.   PHYSICAL REVIEW LETTERS

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

(2018) Fang Ren et al.   Science Advances

A machine learning approach for engineering bulk metallic glass alloys

(2018) Logan Ward et al.   ACTA MATERIALIA

Metallic Metal–Organic Frameworks Predicted by the Combination of Machine Learning Methods and Ab Initio Calculations

(2018) Yuping He et al.   Journal of Physical Chemistry Letters

Deep neural networks for accurate predictions of crystal stability

(2018) Weike Ye et al.   Nature Communications

How Many Bulk Metallic Glasses Are There?

(2017) Yanglin Li et al.   ACS Combinatorial Science

Machine Learning Energies of 2 Million Elpasolite(ABC2D6)Crystals

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

Quantifying the origin of metallic glass formation

(2016) W. L. Johnson et al.   Nature Communications

The thermodynamic scale of inorganic crystalline metastability

(2016) W. Sun et al.   Science Advances

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

(2016) Logan Ward et al.   npj Computational Materials

On the origin of multi-component bulk metallic glasses: Atomic size mismatches and de-mixing

(2015) Kai Zhang et al.   JOURNAL OF CHEMICAL PHYSICS

New horizons for glass formation and stability

(2015) A. Lindsay Greer   NATURE MATERIALS

A combinatorial strategy for metallic glass design via laser deposition

(2014) Peter Tsai et al.   INTERMETALLICS

Fast and slow crystal growth kinetics in glass-forming melts

(2014) J. Orava et al.   JOURNAL OF CHEMICAL PHYSICS

Combinatorial development of bulk metallic glasses

(2014) Shiyan Ding et al.   NATURE MATERIALS

Connection between the packing efficiency of binary hard spheres and the glass-forming ability of bulk metallic glasses

(2014) Kai Zhang et al.   PHYSICAL REVIEW E

Compositional landscape for glass formation in metal alloys

(2014) J. H. Na et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

A survey on feature selection methods

(2013) Girish Chandrashekar et al.   COMPUTERS & ELECTRICAL ENGINEERING

Bulk Metallic Glasses

(2013) Jan Schroers   PHYSICS TODAY

Pd20Pt20Cu20Ni20P20 high-entropy alloy as a bulk metallic glass in the centimeter

(2011) A. Takeuchi et al.   INTERMETALLICS

Beating Crystallization in Glass-Forming Metals by Millisecond Heating and Processing

(2011) W. L. Johnson et al.   SCIENCE

Combining combinatorial nanocalorimetry and X-ray diffraction techniques to study the effects of composition and quench rate on Au–Cu–Si metallic glasses

(2011) John M. Gregoire et al.   SCRIPTA MATERIALIA

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

(2010) Geoffroy Hautier et al.   CHEMISTRY OF MATERIALS

An assessment of binary metallic glasses: correlations between structure, glass forming ability and stability

(2010) D B Miracle et al.   INTERNATIONAL MATERIALS REVIEWS

Metallic Liquids and Glasses: Atomic Order and Global Packing

(2010) X. J. Liu et al.   PHYSICAL REVIEW LETTERS

Injection molding metallic glass

(2008) A WIEST et al.   SCRIPTA MATERIALIA