Machine learning-based glass formation prediction in multicomponent alloys

Explainable Machine Learning Algorithms For Predicting Glass Transition Temperatures

(2020) Edesio Alcobaça et al.   ACTA MATERIALIA

Machine learning assisted design of high entropy alloys with desired property

(2019) Cheng Wen et al.   ACTA MATERIALIA

Theoretical prediction and experimental evaluation of glass forming ability, density and equilibrium point of Ta based bulk metallic glass alloys

(2019) K. Bharath et al.   JOURNAL OF NON-CRYSTALLINE SOLIDS

Machine learning prediction of elastic properties and glass-forming ability of bulk metallic glasses

(2019) Jie Xiong et al.   MRS Communications

First-principles and Machine Learning Predictions of Elasticity in Severely Lattice-distorted High-Entropy Alloys with Experimental Validation

(2019) George Kim et al.   ACTA MATERIALIA

A machine-learning approach to predicting and understanding the properties of amorphous metallic alloys

(2019) Jie Xiong et al.   MATERIALS & DESIGN

Machine learning guided appraisal and exploration of phase design for high entropy alloys

(2019) Ziqing Zhou et al.   npj Computational Materials

Crystal Structure Prediction via Deep Learning

(2018) Kevin Ryan et al.   JOURNAL OF THE AMERICAN CHEMICAL SOCIETY

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

Predicting glass transition temperatures using neural networks

(2018) Daniel R. Cassar et al.   ACTA MATERIALIA

Computational Platform for Manufacturing Bulk Metallic Glasses Based on GFA Parameters

(2018) Sudhanshu Kuthe et al.   TRANSACTIONS OF THE INDIAN INSTITUTE OF METALS

The glassy state of matter: Its definition and ultimate fate

(2017) Edgar D. Zanotto et al.   JOURNAL OF NON-CRYSTALLINE SOLIDS

Machine Learning Approach for Prediction and Understanding of Glass-Forming Ability

(2017) Y. T. Sun et al.   Journal of Physical Chemistry Letters

Machine learning in materials informatics: recent applications and prospects

(2017) Rampi Ramprasad et al.   npj Computational Materials

Critical evaluation of glass forming ability criteria

(2016) C. Chattopadhyay et al.   MATERIALS SCIENCE AND TECHNOLOGY

Quantifying the origin of metallic glass formation

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

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

(2016) Logan Ward et al.   npj Computational Materials

A geometric model for intrinsic residual strain and phase stability in high entropy alloys

(2015) Y.F. Ye et al.   ACTA MATERIALIA

Hidden topological order and its correlation with glass-forming ability in metallic glasses

(2015) Z. W. Wu et al.   Nature Communications

Precisely predicting and designing the elasticity of metallic glasses

(2014) Z. Q. Liu et al.   JOURNAL OF APPLIED PHYSICS

Prediction of critical cooling rate for glass forming alloys by artificial neural network

(2013) A.H. Cai et al.   MATERIALS & DESIGN

Hume-Rothery rules for structurally complex alloy phases

(2012) Uichiro Mizutani   MRS BULLETIN

Phase stability in high entropy alloys: Formation of solid-solution phase or amorphous phase

(2012) Sheng GUO et al.   Progress in Natural Science-Materials International

Prediction of Glass Forming Ability Using Thermodynamic Parameters

(2012) B. Ramakrishna Rao et al.   TRANSACTIONS OF THE INDIAN INSTITUTE OF METALS

The elastic properties, elastic models and elastic perspectives of metallic glasses

(2011) Wei Hua Wang   PROGRESS IN MATERIALS SCIENCE

Dependence of glass forming ability on liquid fragility: Thermodynamics versus kinetics

(2010) Li-Min Wang et al.   APPLIED PHYSICS LETTERS

Artificial neural network modeling for undercooled liquid region of glass forming alloys

(2010) An-hui Cai et al.   COMPUTATIONAL MATERIALS SCIENCE

Critical-like behaviour of glass-forming liquids

(2010) Hajime Tanaka et al.   NATURE MATERIALS

Metallic Liquids and Glasses: Atomic Order and Global Packing

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

On the new criterion to assess the glass-forming ability of metallic alloys

(2009) Zhilin Long et al.   MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING

Artificial neural network modeling of reduced glass transition temperature of glass forming alloys

(2008) An-hui Cai et al.   APPLIED PHYSICS LETTERS

New criterion in predicting glass forming ability of various glass-forming systems

(2008) X. H Du et al.   Chinese Physics B

Electronegativity difference as a factor for evaluating the thermal stability of Al-rich metallic glasses

(2008) C.S. Ma et al.   PHILOSOPHICAL MAGAZINE LETTERS