Expanding the horizons of machine learning in nanomaterials to chiral nanostructures
V Kuznetsova, Á Coogan, D Botov… - Advanced …, 2024 - Wiley Online Library
Abstract Machine learning holds significant research potential in the field of nanotechnology,
enabling nanomaterial structure and property predictions, facilitating materials design and …
enabling nanomaterial structure and property predictions, facilitating materials design and …
Recent progress in high-entropy alloys for laser powder bed fusion: Design, processing, microstructure, and performance
Laser powder bed fusion (LPBF), as the most commercialized metal additive manufacturing
technique, is tantalizing the metallurgical community owing to its capabilities of directly …
technique, is tantalizing the metallurgical community owing to its capabilities of directly …
铌酸锂基光量子器件与集成技术: 机遇与挑战
田晓慧， 尚鸣昊， 祝世宁， 谢臻达 - 物理, 2023 - wuli.iphy.ac.cn
铌酸锂材料具有宽的透光范围和高的非线性光学, 电光, 声光, 热光系数, 且化学性能稳定,
是理想的光子集成芯片的衬底材料. 在量子光学领域, 人们已经发展出一系列铌酸锂基集成器件 …
是理想的光子集成芯片的衬底材料. 在量子光学领域, 人们已经发展出一系列铌酸锂基集成器件 …
Synergistic strength-ductility enhancement of CoCrFeNi high-entropy alloys with regulated Co/Cr atomic ratios
Z Shi, Y Liu, H Zhang, C Li, S Chen, Y Yang… - Materials Science and …, 2024 - Elsevier
In this paper, the mechanical properties and deformation mechanisms of the non-equimolar
high-entropy alloy Co 35 Cr 25 Fe 20 Ni 20 (Co35) are investigated. Compared with the …
high-entropy alloy Co 35 Cr 25 Fe 20 Ni 20 (Co35) are investigated. Compared with the …
Surface effects on the crystallization kinetics of amorphous antimony
Elemental antimony (Sb) is regarded as a promising candidate to improve the programming
consistency and cycling endurance of phase-change memory and neuro-inspired computing …
consistency and cycling endurance of phase-change memory and neuro-inspired computing …
Atomistic investigation of effect of alloying on mechanical properties and microstructural evolution of ternary FeCo-X (X= V, Nb, Mo, W)
M Muralles, JT Oh, Z Chen - Computational Materials Science, 2024 - Elsevier
This atomistic simulation study delves into the impact of V, Nb, Mo, and W on the mechanical
properties of equiatomic FeCo, employing the modified embedded atom method (MEAM) …
properties of equiatomic FeCo, employing the modified embedded atom method (MEAM) …
High-throughput and data-driven machine learning techniques for discovering high-entropy alloys
L Zhichao, M Dong, L Xiongjun, Z Lu - Communications Materials, 2024 - nature.com
High-entropy alloys (HEAs) have attracted extensive attention in recent decades due to their
unique chemical, physical, and mechanical properties. An in-depth understanding of the …
unique chemical, physical, and mechanical properties. An in-depth understanding of the …
Machine learning design for high-entropy alloys: models and algorithms
S Liu, C Yang - Metals, 2024 - mdpi.com
High-entropy alloys (HEAs) have attracted worldwide interest due to their excellent
properties and vast compositional space for design. However, obtaining HEAs with low …
properties and vast compositional space for design. However, obtaining HEAs with low …
A comparative study of predicting high entropy alloy phase fractions with traditional machine learning and deep neural networks
Predicting phase stability in high entropy alloys (HEAs), such as phase fractions as functions
of composition and temperature, is essential for understanding alloy properties and …
of composition and temperature, is essential for understanding alloy properties and …
Multiscale plastic deformation in additively manufactured FeCoCrNiMox high-entropy alloys to achieve strength–ductility synergy at elevated temperatures
The application of structural metals in extreme environments necessitates materials with
superior mechanical properties. Mo-doped FeCoCrNi high-entropy alloys (HEAs) have …
superior mechanical properties. Mo-doped FeCoCrNi high-entropy alloys (HEAs) have …