Accuracy and transferability of Gaussian approximation potential models for tungsten

Article Properties
Refrences
Title Journal Journal Categories Citations Publication Date
10.1007/978-3-540-28650-9_4 2006
Advances in Neural Information Processing Systems 2006
Information Theory, Inference and Learning Algorithms 2003
10.1103/PhysRevB.64.184102
Effective interatomic potential for body-centered-cubic metals

Journal of Applied Physics
  • Science: Chemistry: Physical and theoretical chemistry
  • Science: Physics
  • Technology: Chemical technology
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Materials of engineering and construction. Mechanics of materials
  • Science: Physics
20 1995
Citations
Title Journal Journal Categories Citations Publication Date
Many-body interactions and deep neural network potentials for water

The Journal of Chemical Physics
  • Science: Chemistry: Physical and theoretical chemistry
  • Science: Physics: Atomic physics. Constitution and properties of matter
  • Science: Chemistry: Physical and theoretical chemistry
  • Science: Chemistry
2024
ænet-PyTorch: A GPU-supported implementation for machine learning atomic potentials training

The Journal of Chemical Physics
  • Science: Chemistry: Physical and theoretical chemistry
  • Science: Physics: Atomic physics. Constitution and properties of matter
  • Science: Chemistry: Physical and theoretical chemistry
  • Science: Chemistry
7 2023
Machine-learned acceleration for molecular dynamics in CASTEP

The Journal of Chemical Physics
  • Science: Chemistry: Physical and theoretical chemistry
  • Science: Physics: Atomic physics. Constitution and properties of matter
  • Science: Chemistry: Physical and theoretical chemistry
  • Science: Chemistry
3 2023
ACEpotentials.jl: A Julia implementation of the atomic cluster expansion

The Journal of Chemical Physics
  • Science: Chemistry: Physical and theoretical chemistry
  • Science: Physics: Atomic physics. Constitution and properties of matter
  • Science: Chemistry: Physical and theoretical chemistry
  • Science: Chemistry
3 2023
Persistent homology-based descriptor for machine-learning potential of amorphous structures

The Journal of Chemical Physics
  • Science: Chemistry: Physical and theoretical chemistry
  • Science: Physics: Atomic physics. Constitution and properties of matter
  • Science: Chemistry: Physical and theoretical chemistry
  • Science: Chemistry
2023
Citations Analysis
The category Science: Chemistry 29 is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled A neural-network potential through charge equilibration for WS2: From clusters to sheets and was published in 2017. The most recent citation comes from a 2024 study titled Many-body interactions and deep neural network potentials for water. This article reached its peak citation in 2020, with 8 citations. It has been cited in 6 different journals, 33% of which are open access. Among related journals, the The Journal of Chemical Physics cited this research the most, with 25 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year