Random forest machine learning models for interpretable X-ray absorption near-edge structure spectrum-property relationships
出版年份 2020 全文链接
标题
Random forest machine learning models for interpretable X-ray absorption near-edge structure spectrum-property relationships
作者
关键词
-
出版物
npj Computational Materials
Volume 6, Issue 1, Pages -
出版商
Springer Science and Business Media LLC
发表日期
2020-07-29
DOI
10.1038/s41524-020-00376-6
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。- SciPy 1.0: fundamental algorithms for scientific computing in Python
- (2020) Pauli Virtanen et al. NATURE METHODS
- Analyzing machine learning models to accelerate generation of fundamental materials insights
- (2019) Mitsutaro Umehara et al. npj Computational Materials
- Machine Learning Prediction of H Adsorption Energies on Ag Alloys
- (2019) Robert A. Hoyt et al. Journal of Chemical Information and Modeling
- Prediction of Synthesis of 2D Metal Carbides and Nitrides (MXenes) and Their Precursors with Positive and Unlabeled Machine Learning
- (2019) Nathan C. Frey et al. ACS Nano
- Classification of local chemical environments from x-ray absorption spectra using supervised machine learning
- (2019) Matthew R. Carbone et al. PHYSICAL REVIEW MATERIALS
- CRYSTAL: a multi-agent AI system for automated mapping of materials' crystal structures
- (2019) Carla P. Gomes et al. MRS Communications
- The Electronic Structure of the Metal Active Site Determines the Geometric Structure and Function of the Metalloregulator NikR
- (2019) Yang Ha et al. BIOCHEMISTRY
- Experiment Specification, Capture and Laboratory Automation Technology (ESCALATE): a software pipeline for automated chemical experimentation and data management
- (2019) Ian M. Pendleton et al. MRS Communications
- Revealing Electronic Signatures of Lattice Oxygen Redox in Lithium Ruthenates and Implications for High-Energy Li-Ion Battery Material Designs
- (2019) Yang Yu et al. CHEMISTRY OF MATERIALS
- Inverting” X-ray Absorption Spectra of Catalysts by Machine Learning in Search for Activity Descriptors
- (2019) Janis Timoshenko et al. ACS Catalysis
- 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
- PyFitit: The software for quantitative analysis of XANES spectra using machine-learning algorithms
- (2019) A. Martini et al. COMPUTER PHYSICS COMMUNICATIONS
- Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization
- (2019) Ramprasaath R. Selvaraju et al. INTERNATIONAL JOURNAL OF COMPUTER VISION
- Adventures in DFT by a wavefunction theorist
- (2019) Rodney J. Bartlett JOURNAL OF CHEMICAL PHYSICS
- Matminer: An open source toolkit for materials data mining
- (2018) Logan Ward et al. COMPUTATIONAL MATERIALS SCIENCE
- α-Fe2O3 Nanoparticles as Oxygen Carriers for Chemical Looping Combustion: An Integrated Materials Characterization Approach to Understanding Oxygen Carrier Performance, Reduction Mechanism, and Particle Size Effects
- (2018) Hayder A. Alalwan et al. ENERGY & FUELS
- Neural Network Approach for Characterizing Structural Transformations by X-Ray Absorption Fine Structure Spectroscopy
- (2018) Janis Timoshenko et al. PHYSICAL REVIEW LETTERS
- Accelerating the discovery of materials for clean energy in the era of smart automation
- (2018) Daniel P. Tabor et al. Nature Reviews Materials
- Automated generation and ensemble-learned matching of X-ray absorption spectra
- (2018) Chen Zheng et al. npj Computational Materials
- 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
- Quantitative structural determination of active sites from in situ and operando XANES spectra: From standard ab initio simulations to chemometric and machine learning approaches
- (2018) Alexander A. Guda et al. CATALYSIS TODAY
- Probing Atomic Distributions in Mono- and Bimetallic Nanoparticles by Supervised Machine Learning
- (2018) Janis Timoshenko et al. NANO LETTERS
- Catalyst discovery through megalibraries of nanomaterials
- (2018) Edward J. Kluender et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Supervised Machine-Learning-Based Determination of Three-Dimensional Structure of Metallic Nanoparticles
- (2017) Janis Timoshenko et al. Journal of Physical Chemistry Letters
- Automated Phase Mapping with AgileFD and its Application to Light Absorber Discovery in the V–Mn–Nb Oxide System
- (2016) Santosh K. Suram et al. ACS Combinatorial Science
- Efficient implementation of core-excitation Bethe–Salpeter equation calculations
- (2015) K. Gilmore et al. COMPUTER PHYSICS COMMUNICATIONS
- Redox activity of surface oxygen anions in oxygen-deficient perovskite oxides during electrochemical reactions
- (2015) David N. Mueller et al. Nature Communications
- The Open Quantum Materials Database (OQMD): assessing the accuracy of DFT formation energies
- (2015) Scott Kirklin et al. npj Computational Materials
- Discovering Ce-rich oxygen evolution catalysts, from high throughput screening to water electrolysis
- (2014) Joel A. Haber et al. Energy & Environmental Science
- 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
- XAS study of Mn, Fe and Cu as indicators of historical glass decay
- (2013) M. Abuín et al. JOURNAL OF ANALYTICAL ATOMIC SPECTROMETRY
- 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
- Hubbard model corrections in real-space x-ray spectroscopy theory
- (2012) Towfiq Ahmed et al. PHYSICAL REVIEW B
- The NumPy Array: A Structure for Efficient Numerical Computation
- (2011) Stéfan van der Walt et al. COMPUTING IN SCIENCE & ENGINEERING
- Bethe-Salpeter equation calculations of core excitation spectra
- (2011) J. Vinson et al. PHYSICAL REVIEW B
- Chemical imaging of catalytic solids with synchrotron radiation
- (2010) Andrew M. Beale et al. CHEMICAL SOCIETY REVIEWS
- Parameter-free calculations of X-ray spectra with FEFF9
- (2010) John J. Rehr et al. PHYSICAL CHEMISTRY CHEMICAL PHYSICS
- Chemical Imaging of Spatial Heterogeneities in Catalytic Solids at Different Length and Time Scales
- (2009) Bert M. Weckhuysen ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
- The oxidation state of iron determined by Fe K-edge XANES—application to iron gall ink in historical manuscripts
- (2009) Max Wilke et al. JOURNAL OF ANALYTICAL ATOMIC SPECTROMETRY
- X-ray absorption spectroscopy
- (2009) Junko Yano et al. PHOTOSYNTHESIS RESEARCH
- Ab initio theory and calculations of X-ray spectra
- (2008) John J. Rehr et al. COMPTES RENDUS PHYSIQUE
- Assignment of pre-edge peaks in K-edge x-ray absorption spectra of 3d transition metal compounds: electric dipole or quadrupole?
- (2008) Takashi Yamamoto X-RAY SPECTROMETRY
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreFind the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
Search