Zobrazeno 1 - 10
of 1 133
pro vyhledávání: '"Volker L"'
Autor:
Jieling Tan, Jiang‐Jing Wang, Hang‐Ming Zhang, Han‐Yi Zhang, Heming Li, Yu Wang, Yuxing Zhou, Volker L. Deringer, Wei Zhang
Publikováno v:
Small Science, Vol 4, Iss 9, Pp n/a-n/a (2024)
Main‐group layered binary semiconductors, in particular, the III–VI alloys in the binary Ga–Te system are attracting increasing interest for a range of practical applications. The III–VI semiconductor, monoclinic gallium monotelluride (m‐Ga
Externí odkaz:
https://doaj.org/article/9f59ee6f08484070a464d4f247f23629
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-12 (2024)
Abstract Silicon–oxygen compounds are among the most important ones in the natural sciences, occurring as building blocks in minerals and being used in semiconductors and catalysis. Beyond the well-known silicon dioxide, there are phases with diffe
Externí odkaz:
https://doaj.org/article/319c8b89b64f48269bb58ddc2cafc7f7
Autor:
Xiaozhe Wang, Suyang Sun, Jiang‐Jing Wang, Shuang Li, Jian Zhou, Oktay Aktas, Ming Xu, Volker L. Deringer, Riccardo Mazzarello, En Ma, Wei Zhang
Publikováno v:
Advanced Science, Vol 10, Iss 23, Pp n/a-n/a (2023)
Abstract The layered crystal structure of Cr2Ge2Te6 shows ferromagnetic ordering at the two‐dimensional limit, which holds promise for spintronic applications. However, external voltage pulses can trigger amorphization of the material in nanoscale
Externí odkaz:
https://doaj.org/article/ebcb4332717a4378a0aaff745538295d
Publikováno v:
Machine Learning: Science and Technology, Vol 5, Iss 1, p 015003 (2024)
Machine learning (ML) based interatomic potentials have transformed the field of atomistic materials modelling. However, ML potentials depend critically on the quality and quantity of quantum-mechanical reference data with which they are trained, and
Externí odkaz:
https://doaj.org/article/365cc2c702354ec79bf6d23c3fe4a19b
Publikováno v:
npj Computational Materials, Vol 8, Iss 1, Pp 1-12 (2022)
Abstract Silica (SiO2) is an abundant material with a wide range of applications. Despite much progress, the atomistic modelling of the different forms of silica has remained a challenge. Here we show that by combining density-functional theory at th
Externí odkaz:
https://doaj.org/article/ec693eb8d378400bbd5a8252cf450cd0
Training interatomic potentials for spin-polarized systems continues to be a difficult task for the molecular modeling community. In this note, a proof-of-concept, random initial spin committee approach is proposed for obtaining the ground state of s
Externí odkaz:
http://arxiv.org/abs/2410.16252
Autor:
Xu‐Dong Wang, Jieling Tan, Jian Ouyang, Hang‐Ming Zhang, Jiang‐Jing Wang, Yuecun Wang, Volker L. Deringer, Jian Zhou, Wei Zhang, En Ma
Publikováno v:
Advanced Science, Vol 9, Iss 30, Pp n/a-n/a (2022)
Abstract While metals can be readily processed and reshaped by cold rolling, most bulk inorganic semiconductors are brittle materials that tend to fracture when plastically deformed. Manufacturing thin sheets and foils of inorganic semiconductors is
Externí odkaz:
https://doaj.org/article/37d6a200dc5141d495eb01ea56f61126
Autor:
Liang Sun, Yu-Xing Zhou, Xu-Dong Wang, Yu-Han Chen, Volker L. Deringer, Riccardo Mazzarello, Wei Zhang
Publikováno v:
npj Computational Materials, Vol 7, Iss 1, Pp 1-8 (2021)
Abstract The Ge2Sb2Te5 alloy has served as the core material in phase-change memories with high switching speed and persistent storage capability at room temperature. However widely used, this composition is not suitable for embedded memories—for e
Externí odkaz:
https://doaj.org/article/0c4bf7f112fe4a9e9266f799a978f41e
Autor:
Zhou, Yuxing, Elliott, Stephen R., Toit, Daniel F. Thomas du, Zhang, Wei, Deringer, Volker L.
Chiral crystals, like chiral molecules, cannot be superimposed onto their mirror images -- a fundamental property that has been linked to interesting physical behavior and exploited in functional devices. Among the simplest inorganic systems with cry
Externí odkaz:
http://arxiv.org/abs/2409.03860
Machine-learning-based interatomic potentials enable accurate materials simulations on extended time- and lengthscales. ML potentials based on the Atomic Cluster Expansion (ACE) framework have recently shown promising performance for this purpose. He
Externí odkaz:
http://arxiv.org/abs/2408.00656