标题
Machine-Learning X-Ray Absorption Spectra to Quantitative Accuracy
作者
关键词
-
出版物
PHYSICAL REVIEW LETTERS
Volume 124, Issue 15, Pages -
出版商
American Physical Society (APS)
发表日期
2020-04-17
DOI
10.1103/physrevlett.124.156401
参考文献
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。- Classification of local chemical environments from x-ray absorption spectra using supervised machine learning
- (2019) Matthew R. Carbone et al. PHYSICAL REVIEW MATERIALS
- Ultrathin Amorphous Titania on Nanowires: Optimization of Conformal Growth and Elucidation of Atomic-Scale Motifs
- (2019) Danhua Yan et al. NANO LETTERS
- Identifying topological order through unsupervised machine learning
- (2019) Joaquin F. Rodriguez-Nieva et al. Nature Physics
- The machine learning revolution in materials?
- (2019) Kristofer G. Reyes et al. MRS BULLETIN
- A neural network protocol for electronic excitations of N-methylacetamide
- (2019) Sheng Ye et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Recent advances and applications of machine learning in solid-state materials science
- (2019) Jonathan Schmidt et al. npj Computational Materials
- Elucidating the Evolving Atomic Structure in Atomic Layer Deposition Reactions with in Situ XANES and Machine Learning
- (2019) Orlando Trejo et al. CHEMISTRY OF MATERIALS
- Neural Network Approach for Characterizing Structural Transformations by X-Ray Absorption Fine Structure Spectroscopy
- (2018) Janis Timoshenko et al. PHYSICAL REVIEW LETTERS
- Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties
- (2018) Tian Xie et al. PHYSICAL REVIEW LETTERS
- Deep Potential Molecular Dynamics: A Scalable Model with the Accuracy of Quantum Mechanics
- (2018) Linfeng Zhang et al. PHYSICAL REVIEW LETTERS
- Learning atoms for materials discovery
- (2018) Quan Zhou et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Inverse molecular design using machine learning: Generative models for matter engineering
- (2018) Benjamin Sanchez-Lengeling et al. SCIENCE
- High-throughput computational X-ray absorption spectroscopy
- (2018) Kiran Mathew et al. Scientific Data
- Spatial and temporal exploration of heterogeneous catalysts with synchrotron radiation
- (2018) Florian Meirer et al. Nature Reviews Materials
- Extrapolating Quantum Observables with Machine Learning: Inferring Multiple Phase Transitions from Properties of a Single Phase
- (2018) Rodrigo A. Vargas-Hernández et al. PHYSICAL REVIEW LETTERS
- Supervised Machine-Learning-Based Determination of Three-Dimensional Structure of Metallic Nanoparticles
- (2017) Janis Timoshenko et al. Journal of Physical Chemistry Letters
- Machine learning molecular dynamics for the simulation of infrared spectra
- (2017) Michael Gastegger et al. Chemical Science
- The Materials Application Programming Interface (API): A simple, flexible and efficient API for materials data based on REpresentational State Transfer (REST) principles
- (2015) Shyue Ping Ong et al. COMPUTATIONAL MATERIALS SCIENCE
- Machine Learning for Quantum Mechanical Properties of Atoms in Molecules
- (2015) Matthias Rupp et al. Journal of Physical Chemistry Letters
- Deep learning
- (2015) Yann LeCun et al. NATURE
- exciting: a full-potential all-electron package implementing density-functional theory and many-body perturbation theory
- (2014) Andris Gulans et al. JOURNAL OF PHYSICS-CONDENSED MATTER
- EXAFS and XANES analysis of oxides at the nanoscale
- (2014) Alexei Kuzmin et al. IUCrJ
- Quantum chemistry structures and properties of 134 kilo molecules
- (2014) Raghunathan Ramakrishnan et al. Scientific Data
- Commentary: The Materials Project: A materials genome approach to accelerating materials innovation
- (2013) Anubhav Jain et al. APL Materials
- Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis
- (2012) Shyue Ping Ong et al. COMPUTATIONAL MATERIALS SCIENCE
- Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning
- (2012) Matthias Rupp et al. PHYSICAL REVIEW LETTERS
- Bethe-Salpeter equation calculations of core excitation spectra
- (2011) J. Vinson et al. PHYSICAL REVIEW B
- Characterization of oxygen containing functional groups on carbon materials with oxygen K-edge X-ray absorption near edge structure spectroscopy
- (2010) Kyungsoo Kim et al. CARBON
- Parameter-free calculations of X-ray spectra with FEFF9
- (2010) John J. Rehr et al. PHYSICAL CHEMISTRY CHEMICAL PHYSICS
- X-Ray Absorption Signatures of the Molecular Environment in Water and Ice
- (2010) Wei Chen et al. PHYSICAL REVIEW LETTERS
- Ab initio theory and calculations of X-ray spectra
- (2008) John J. Rehr et al. COMPTES RENDUS PHYSIQUE
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now