From DFT to machine learning: recent approaches to materials science–a review
Recent advances in experimental and computational methods are increasing the quantity
and complexity of generated data. This massive amount of raw data needs to be stored and …
and complexity of generated data. This massive amount of raw data needs to be stored and …
[HTML][HTML] Computational discovery of energy materials in the era of big data and machine learning: a critical review
Z Lu - Materials Reports: Energy, 2021 - Elsevier
The discovery of novel materials with desired properties is essential to the advancements of
energy-related technologies. Despite the rapid development of computational infrastructures …
energy-related technologies. Despite the rapid development of computational infrastructures …
Generative adversarial networks for crystal structure prediction
The constant demand for novel functional materials calls for efficient strategies to accelerate
the materials discovery, and crystal structure prediction is one of the most fundamental tasks …
the materials discovery, and crystal structure prediction is one of the most fundamental tasks …
High throughput screening of M 3 C 2 MXenes for efficient CO 2 reduction conversion into hydrocarbon fuels
The electrocatalytic reduction conversion of CO2 to produce methane (CH4) as a fuel has
attracted intensive attention for renewable energy. Density functional theory (DFT) …
attracted intensive attention for renewable energy. Density functional theory (DFT) …
3D Carbon Allotropes: Topological Quantum Materials with Obstructed Atomic Insulating Phases, Multiple Bulk‐Boundary Correspondences, and Real Topology
J Wang, TT Zhang, Q Zhang, X Cheng… - Advanced Functional …, 2024 - Wiley Online Library
The study of topological phases with unconventional bulk‐boundary correspondences and
nontrivial real Chern number has garnered significant attention in the topological states of …
nontrivial real Chern number has garnered significant attention in the topological states of …
MagneticTB: A package for tight-binding model of magnetic and non-magnetic materials
We present a Mathematica program package MagneticTB, which can generate the tight-
binding model for arbitrary magnetic space group. The only input parameters in MagneticTB …
binding model for arbitrary magnetic space group. The only input parameters in MagneticTB …
Relative Abundance of Topological Order in Exfoliable Two-Dimensional Insulators
Quantum spin Hall insulators make up a class of two-dimensional materials with a finite
electronic band gap in the bulk and gapless helical edge states. In the presence of time …
electronic band gap in the bulk and gapless helical edge states. In the presence of time …
Quantum spin Hall effect in Ta 2 M 3 Te 5 (M= Pd, Ni)
Quantum spin Hall (QSH) effect with great promise for the potential application in spintronics
and quantum computing has attracted extensive research interest from both theoretical and …
and quantum computing has attracted extensive research interest from both theoretical and …
Magnetic i-MXenes: a new class of multifunctional two-dimensional materials
Based on density functional theory calculations, we investigated two-dimensional in-plane
ordered MXenes (i-MXenes), focusing particularly on their magnetic properties. It has been …
ordered MXenes (i-MXenes), focusing particularly on their magnetic properties. It has been …
Two-dimensional topological materials discovery by symmetry-indicator method
Two-dimensional (2D) topological materials (TMs) have attracted tremendous attention due
to the promise of revolutionary devices with nondissipative electric or spin currents …
to the promise of revolutionary devices with nondissipative electric or spin currents …