Correlative study between elastic modulus and glass formation in ZrCuAl(X) amorphous system using a machine learning approach

Identification of rejuvenation and relaxation regions in a Zr-based metallic glass induced by laser shock peening

(2021) Zaid Hamid Mahmoud et al.   Journal of Materials Research and Technology-JMR&T

Engineering of new Mg-based glassy compositions by a computational intelligence model

(2021) Tzu-Chia Chen et al.   MATERIALS LETTERS

Inverse Design of Fe-Based Bulk Metallic Glasses Using Machine Learning

(2021) Junhyub Jeon et al.   Metals

Determination of glass forming ability of bulk metallic glasses based on machine learning

(2021) Li Peng et al.   COMPUTATIONAL MATERIALS SCIENCE

A two-step fused machine learning approach for the prediction of glass-forming ability of metallic glasses

(2021) Y.X. Zhang et al.   JOURNAL OF ALLOYS AND COMPOUNDS

Developing a multilateral-based neural network model for engineering of high entropy amorphous alloys

(2021) Tzu-Chia Chen et al.   MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING

Machine learning enabled autonomous microstructural characterization in 3D samples

(2020) Henry Chan et al.   npj Computational Materials

Revisiting the breakdown of Stokes-Einstein relation in glass-forming liquids with machine learning

(2020) ZhenWei Wu et al.   Science China-Physics Mechanics & Astronomy

Machine learning bridges local static structure with multiple properties in metallic glasses

(2020) Zhao Fan et al.   Materials Today

A High-Throughput Structural and Electrochemical Study of Metallic Glass Formation in Ni–Ti–Al

(2020) Howie Joress et al.   ACS Combinatorial Science

Tailored hardening of ZrCuAl bulk metallic glass induced by 2D gradient rejuvenation

(2020) Wookha Ryu et al.   NPG Asia Materials

Identifying flow defects in amorphous alloys using machine learning outlier detection methods

(2020) Liang Tian et al.   SCRIPTA MATERIALIA

Machine learning-based glass formation prediction in multicomponent alloys

(2020) Xiaodi Liu et al.   ACTA MATERIALIA

Discovery of novel quaternary bulk metallic glasses using a developed correlation-based neural network approach

(2020) Majid Samavatian et al.   COMPUTATIONAL MATERIALS SCIENCE

Predicting the propensity for thermally activated β events in metallic glasses via interpretable machine learning

(2020) Qi Wang et al.   npj Computational Materials

Design of Fe-based bulk metallic glasses for maximum amorphous diameter (Dmax) using machine learning models

(2020) Daniel G. Mastropietro et al.   COMPUTATIONAL MATERIALS SCIENCE

The effect of oxygen on phase formation in an industrial Zr based bulk metallic glass

(2020) Weihua Zhou et al.   INTERMETALLICS

Characterization, mechanical properties and dimensional accuracy of a Zr-based bulk metallic glass manufactured via laser powder-bed fusion

(2020) Navid Sohrabi et al.   MATERIALS & DESIGN

Probabilistic Assessment of Glass Forming Ability Rules for Metallic Glasses Aided by Automated Analysis of Phase Diagrams

(2019) Aparajita Dasgupta et al.   Scientific Reports

Effects of Nb minor addition on atomic structure and glass forming ability of Zr55Cu30Ni5Al10 bulk metallic glass

(2019) Majid Samavatian et al.   Materials Research Express

Role of tensile elastostatic loading on atomic structure and mechanical properties of Zr55Cu30Ni5Al10 bulk metallic glass

(2019) Majid Samavatian et al.   MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING

Dynamic Relaxations and Relaxation-Property Relationships in Metallic Glasses

(2019) Wei Hua Wang   PROGRESS IN MATERIALS SCIENCE

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

(2019) Jie Xiong et al.   MRS Communications

A transferable machine-learning framework linking interstice distribution and plastic heterogeneity in metallic glasses

(2019) Qi Wang et al.   Nature Communications

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

(2019) Jie Xiong et al.   MATERIALS & DESIGN

Residual modulus degradation model for woven fabric composite determined by impulse excitation technique

(2019) Maísa Milanez Ávila Dias Maciel et al.   INTERNATIONAL JOURNAL OF FATIGUE

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

Porous Ti-based bulk metallic glass with excellent mechanical properties and good biocompatibility

(2018) Guoqiang Xie et al.   INTERMETALLICS

A predictable glass forming ability expression by statistical learning and evolutionary intelligence

(2017) Manwendra K. Tripathi et al.   INTERMETALLICS

Structural mechanism of the enhanced glass-forming ability in multicomponent alloys with positive heat of mixing

(2016) S. Y. Wu et al.   Scientific Reports

Enhance the thermal stability and glass forming ability of Al-based metallic glass by Ca minor-alloying

(2012) J.Q. Wang et al.   INTERMETALLICS

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

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