Machine learning-assisted discovery of strong and conductive Cu alloys: Data mining from discarded experiments and physical features

Accelerated design of novel W-free high-strength Co-base superalloys with extremely wide γ/γʹ region by machine learning and CALPHAD methods

(2020) Jingjing Ruan et al.   ACTA MATERIALIA

Prediction of composite microstructure stress-strain curves using convolutional neural networks

(2020) Charles Yang et al.   MATERIALS & DESIGN

Machine learning as a contributor to physics: Understanding Mg alloys

(2019) Zongrui Pei et al.   MATERIALS & DESIGN

Machine learning assisted design of high entropy alloys with desired property

(2019) Cheng Wen et al.   ACTA MATERIALIA

Machine-learning phase prediction of high-entropy alloys

(2019) Wenjiang Huang et al.   ACTA MATERIALIA

Modulating the prestrain history to optimize strength and ductility in CoCrFeMnNi high-entropy alloy

(2019) S.J. Sun et al.   SCRIPTA MATERIALIA

Machine learning for hierarchical prediction of elastic properties in Fe-Cr-Al system

(2019) Ruirui Wang et al.   COMPUTATIONAL MATERIALS SCIENCE

Effect of cold rolling reduction rate on mechanical properties and electrical conductivity of Cu–Ni–Si alloy prepared by temperature controlled mold continuous casting

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

A property-oriented design strategy for high performance copper alloys via machine learning

(2019) Changsheng Wang et al.   npj Computational Materials

Physical metallurgy-guided machine learning and artificial intelligent design of ultrahigh-strength stainless steel

(2019) Chunguang Shen et al.   ACTA MATERIALIA

Tuning element distribution, structure and properties by composition in high-entropy alloys

(2019) Qingqing Ding et al.   NATURE

Phase prediction in high entropy alloys with a rational selection of materials descriptors and machine learning models

(2019) Yan Zhang et al.   ACTA MATERIALIA

Effective design space exploration of gradient nanostructured materials using active learning based surrogate models

(2019) Xin Chen et al.   MATERIALS & DESIGN

Machine learning for phase selection in multi-principal element alloys

(2018) Nusrat Islam et al.   COMPUTATIONAL MATERIALS SCIENCE

Machine learning properties of binary wurtzite superlattices

(2018) G. Pilania et al.   JOURNAL OF MATERIALS SCIENCE

Effect of lattice distortion on solid solution strengthening of BCC high-entropy alloys

(2018) Zhipeng Wang et al.   JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY

Three-Dimensional High-Entropy Alloy–Polymer Composite Nanolattices That Overcome the Strength–Recoverability Trade-off

(2018) Xuan Zhang et al.   NANO LETTERS

Parameter free quantitative analysis of atom probe data by correlation functions: Application to the precipitation in Al-Zn-Mg-Cu

(2018) Huan Zhao et al.   SCRIPTA MATERIALIA

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

Machine leaning aided study of sintered density in Cu-Al alloy

(2018) Zhenghua Deng et al.   COMPUTATIONAL MATERIALS SCIENCE

Predicting the effective thermal conductivities of composite materials and porous media by machine learning methods

(2018) Han Wei et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

Microstructure and Properties of a Novel Cu–Ni–Co–Si–Mg Alloy with Super-high Strength and Conductivity

(2018) Jiazhen Huang et al.   MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING

Extra strengthening and work hardening in gradient nanotwinned metals

(2018) Zhao Cheng et al.   SCIENCE

Precipitation behavior of Cu-3.0Ni-0.72Si alloy

(2018) Jiang Yi et al.   ACTA MATERIALIA

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

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

A high strength and high electrical conductivity Cu-Cr-Zr alloy fabricated by cryorolling and intermediate aging treatment

(2017) Shaojian Zhang et al.   MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING

Ultrastrong steel via minimal lattice misfit and high-density nanoprecipitation

(2017) Suihe Jiang et al.   NATURE

Additively manufactured hierarchical stainless steels with high strength and ductility

(2017) Y. Morris Wang et al.   NATURE MATERIALS

Points of Significance: Principal component analysis

(2017) Jake Lever et al.   NATURE METHODS

Effect of Boron and Cerium on Corrosion Resistance of Cu-Fe-P Alloy

(2016) Jin Zou et al.   JOURNAL OF MATERIALS ENGINEERING AND PERFORMANCE

Modelling solid solution hardening in high entropy alloys

(2015) Isaac Toda-Caraballo et al.   ACTA MATERIALIA

Microstructure evolution of Cu–0.2Mg alloy during continuous extrusion process

(2015) Yuan Yuan et al.   JOURNAL OF MATERIALS RESEARCH

Microstructure evolution and quench sensitivity of Cu–10Ni–3Al–0.8Si alloy during isothermal treatment

(2015) Leinuo Shen et al.   JOURNAL OF MATERIALS RESEARCH

Microstructure and properties of Cu–2.3Fe–0.03P alloy during thermomechanical treatments

(2015) Qi-yi DONG et al.   TRANSACTIONS OF NONFERROUS METALS SOCIETY OF CHINA

How to represent crystal structures for machine learning: Towards fast prediction of electronic properties

(2014) K. T. Schütt et al.   PHYSICAL REVIEW B

Effects of Al addition on structural evolution and tensile properties of the FeCoNiCrMn high-entropy alloy system

(2013) J.Y. He et al.   ACTA MATERIALIA

Studies of electrical resistivity of an annealed Cu-Fe composite

(2013) Lei Qu et al.   JOURNAL OF APPLIED PHYSICS

Ultrafine grained copper alloy sheets having both high strength and high electric conductivity

(2009) Naoki Takata et al.   MATERIALS LETTERS