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The mechanical properties are essential for structural materials. The analyzed 360 data on four mechanical properties of steels, viz. fatigue strength, tensile strength, fracture strength, and hardness, are selected from the NIMS database,…

应用物理 · 物理学 2021-01-05 Jie Xiong , Tong-Yi Zhang , San-Qiang Shi

This chapter presents an innovative framework for the application of machine learning and data analytics for the identification of alloys or composites exhibiting certain desired properties of interest. The main focus is on alloys and…

材料科学 · 物理学 2020-12-15 Baldur Steingrimsson , Xuesong Fan , Anand Kulkarni , Michael C. Gao , Peter K. Liaw

Austenitic stainless steels with low carbon have exceptional mechanical properties and are capable to reduce embrittlement, due to high chromium and nickel alloying, thus they are very attractive for efficient energy production in extreme…

High-temperature alloy design requires a concurrent consideration of multiple mechanisms at different length scales. We propose a workflow that couples highly relevant physics into machine learning (ML) to predict properties of complex…

材料科学 · 物理学 2020-09-04 Jian Peng , Yukinori Yamamoto , Jeffrey A. Hawk , Edgar Lara-Curzio , Dongwon Shin

Machine learning (ML) is shown to predict new alloys and their performances in a high dimensional, multiple-target-property design space that considers chemistry, multi-step processing routes, and characterization methodology variations. A…

Designing alloys for additive manufacturing (AM) presents significant opportunities. Still, the chemical composition and processing conditions required for printability (ie., their suitability for fabrication via AM) are challenging to…

High-entropy alloys (HEAs) stand out between multi-component alloys due to their attractive microstructures and mechanical properties. In this investigation, molecular dynamics (MD) simulation and machine learning were used to ascertain the…

材料科学 · 物理学 2024-02-05 Hoang-Giang Nguyen , Thanh-Dung Le

Residual stress engineering is very widely used in the design of new advanced lightweight materials. For metallic glasses the attention has been on structural changes and rejuvenation processes. High energy scanning X-ray diffraction strain…

材料科学 · 物理学 2022-10-12 D. Şopu , F. Spieckermann , X. L. Bian , S. Fellner , J. Wright , M. Cordill , C. Gammer , G. Wang , M. Stoica , J. Eckert

Accelerating the design of materials with targeted properties is one of the key materials informatics tasks. The most common approach takes a data-driven motivation, where the underlying knowledge is incorporated in the form of…

材料科学 · 物理学 2022-09-28 Shunshun Liu , Kyungtae Lee , Prasanna V. Balachandran

A Twinning Induced Plasticity (TWIP) steel with a nominal composition of Fe-16.4Mn-0.9C-0.5Si-0.05Nb-0.05V was deformed to an engineering strain of 6\%. The strain around the deformation twins were mapped using the 4D-STEM technique. Strain…

材料科学 · 物理学 2022-10-03 T W J Kwok , T P McAuliffe , A K Ackerman , B H Savitzky , M Danaie , C Ophus , D Dye

My scientific activities aim at understand and predict the mechanical behaviour of steels, from fundamental mechanisms to macroscopic deformation. This manuscript is dedicated to the TWIP effect (TWinning Induced Plasticity) of high…

材料科学 · 物理学 2014-01-10 Sebastien Allain

Gradient structured (GS) metals processed by severe plastic deformation techniques can be designed to achieve simultaneously high strength and high ductility. Significant kinematic hardening is key to their excellent strain hardening…

材料科学 · 物理学 2020-02-11 Jianfeng Zhao , Xiaochong Lu , Jinling Liu , Chen Bao , Guozheng Kang , Michael Zaiser , Xu Zhang

Strain engineering has been used to modify materials properties in ferroelectric, superconducting, and ferromagnetic thin films. The advantage of strain engineering is that it can achieve unexpected enhancement in certain properties, such…

超导电性 · 物理学 2008-08-11 R. Zeng S. X. Dou , L. Lu , W. X. Li , J. H. Kim , P. Munroe , R. K. Zheng , S. P. Ringer

Nowadays high speed machining (HSM) machine tool combines productivity and part quality. So mould and die maker invested in HSM. Die and mould features are more and more complex shaped. Thus, it is difficult to choose the best machining…

机器人学 · 计算机科学 2009-10-12 Laurent Tapie , Kwamiwi Mawussi , Bernard Anselmetti

High-manganese twinning-induced plasticity (TWIP) steels exhibit high strain hardening, high tensile strength, and high ductility, which make them attractive for structural applications. At low tensile strain rates, TWIP steels are prone to…

材料科学 · 物理学 2023-04-27 Heena Khanchandani , Dirk Ponge , Stefan Zaefferer , Baptiste Gault

High speed machining has been improved thanks to considerable advancement on the tools (optimum geometry, harder materials), on machined materials (increased workability and machining capacity for harder workpieces) and finally on the…

经典物理 · 物理学 2009-09-29 Olivier Cahuc , Alain Gérard

Steels, and in particular stainless steels, play a crucial role in the construction of large particle accelerators and high-energy physics experiments, of fusion reactors and their superconducting magnet structures. Such projects face…

加速器物理 · 物理学 2025-09-04 Stefano Sgobba

Elastic constants and mechanical properties play a pivotal role across multiple disciplines and engineering applications. We introduced the optimized high-efficient strain-matrix set (OHESS) that determines the second-order elastic…

材料科学 · 物理学 2023-08-29 Zhong-Li Liu , Ya-Dong Wei , Xiao-Dong Xu , Wei-Qi Li , Gang Lv , Jian-Qun Yang , Xing-Ji Li , Chinedu E. Ekuma

This work presents a three-dimensional constitutive model for shape memory alloys considering the TRansformation-Induced Plasticity (TRIP) as well as the Two-Way Shape Memory Effect (TWSME) through a large deformation framework. The…

材料科学 · 物理学 2020-01-15 Lei Xu , Alexandros Solomou , Theocharis Baxevanis , Dimitris Lagoudas

The understanding of the material properties of the layered transition metal dichalcogenides (TMDs) is critical for their applications in structural composites. The data-driven machine learning (ML) based approaches are being developed in…

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