相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。Nonrelativistic Spin-Momentum Coupling in Antiferromagnetic Twisted Bilayers
Ran He et al.
PHYSICAL REVIEW LETTERS (2023)
The rise of halide perovskite semiconductors
Chenlu He et al.
LIGHT-SCIENCE & APPLICATIONS (2023)
Trustworthy Federated Learning via Blockchain
Zhanpeng Yang et al.
IEEE INTERNET OF THINGS JOURNAL (2023)
Curvature effect on graphene-based Co/Ni single-atom catalysts
Shuaihao Tang et al.
APPLIED SURFACE SCIENCE (2023)
Preparation of corn stover hydrothermal carbon sphere-CdS/g-C3N4 composite and evaluation of its performance in the photocatalytic co- reduction of CO2 and decomposition of water for hydrogen production
Meng Sun et al.
JOURNAL OF ALLOYS AND COMPOUNDS (2023)
Photocatalytic Decomposition of Water on Semiconductor Materials
T. S. Dzhabiev et al.
RUSSIAN JOURNAL OF PHYSICAL CHEMISTRY A (2022)
Density-functional theory vs density-functional fits
Axel D. Becke
JOURNAL OF CHEMICAL PHYSICS (2022)
Defects in semiconductors
L. Vines et al.
JOURNAL OF APPLIED PHYSICS (2022)
Machine learning of materials design and state prediction for lithium ion batteries
Jiale Mao et al.
CHINESE JOURNAL OF CHEMICAL ENGINEERING (2021)
Recent advances in photocatalytic decomposition of water and pollutants for sustainable application
Yujie Zhao et al.
CHEMOSPHERE (2021)
Accelerating materials discovery using machine learning
Yongfei Juan et al.
JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY (2021)
Machine learning aided design of perovskite oxide materials for photocatalytic water splitting
Qiuling Tao et al.
JOURNAL OF ENERGY CHEMISTRY (2021)
Machine Learning for Predicting the Band Gaps of ABX3 Perovskites from Elemental Properties
Vladislav Gladkikh et al.
JOURNAL OF PHYSICAL CHEMISTRY C (2020)
Discovery of Novel Two-Dimensional Photovoltaic Materials Accelerated by Machine Learning
Hao Jin et al.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS (2020)
A band-gap database for semiconducting inorganic materials calculated with hybrid functional
Sangtae Kim et al.
SCIENTIFIC DATA (2020)
Recent developments in the Inorganic Crystal Structure Database: theoretical crystal structure data and related features
D. Zagorac et al.
JOURNAL OF APPLIED CRYSTALLOGRAPHY (2019)
Comparison and Modelling of Country-level Microblog User and Activity in Cyber-physical-social Systems Using Weibo and Twitter Data
Po Yang et al.
ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY (2019)
Predicting the Band Gaps of Inorganic Solids by Machine Learning
Ya Zhuo et al.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS (2018)
A general-purpose machine learning framework for predicting properties of inorganic materials
Logan Ward et al.
NPJ COMPUTATIONAL MATERIALS (2016)
Commentary: The Materials Project: A materials genome approach to accelerating materials innovation
Anubhav Jain et al.
APL MATERIALS (2013)
Screened hybrid density functionals applied to solids -: art. no. 154709
J Paier et al.
JOURNAL OF CHEMICAL PHYSICS (2006)