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Interpretable machine learning for knowledge generation in heterogeneous catalysis

Journal Article · · Nature Catalysis
Not provided.
Research Organization:
Univ. of Michigan, Ann Arbor, MI (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
DOE Contract Number:
SC0021008
OSTI ID:
1978727
Journal Information:
Nature Catalysis, Journal Name: Nature Catalysis Journal Issue: 3 Vol. 5; ISSN 2520-1158
Publisher:
Springer Nature
Country of Publication:
United States
Language:
English

References (75)

Machine-Learning-Augmented Chemisorption Model for CO 2 Electroreduction Catalyst Screening journal August 2015
Computational catalyst discovery: Active classification through myopic multiscale sampling journal March 2021
Chemical Pressure-Driven Enhancement of the Hydrogen Evolving Activity of Ni 2 P from Nonmetal Surface Doping Interpreted via Machine Learning journal March 2018
Intelligible Models for HealthCare: Predicting Pneumonia Risk and Hospital 30-day Readmission conference January 2015
Predicting reaction performance in C–N cross-coupling using machine learning journal February 2018
Automatic Prediction of Surface Phase Diagrams Using Ab Initio Grand Canonical Monte Carlo journal January 2019
Adsorption Enthalpies for Catalysis Modeling through Machine-Learned Descriptors journal June 2021
Communications: Exceptions to the d-band model of chemisorption on metal surfaces: The dominant role of repulsion between adsorbate states and metal d-states journal June 2010
High-throughput screening of bimetallic catalysts enabled by machine learning journal January 2017
Identifying domains of applicability of machine learning models for materials science journal September 2020
Materials Synthesis Insights from Scientific Literature via Text Extraction and Machine Learning journal October 2017
Machine Learning for Computational Heterogeneous Catalysis journal June 2019
Symbolic regression in materials science journal June 2019
Beyond Scaling Relations for the Description of Catalytic Materials journal February 2019
A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting journal August 1997
Intelligible models for classification and regression conference January 2012
Frontier Molecular Orbital Based Analysis of Solid–Adsorbate Interactions over Group 13 Metal Oxide Surfaces journal June 2020
A Review of Multiscale Analysis: Examples from Systems Biology, Materials Engineering, and Other Fluid-Surface Interacting Systems book January 2005
Automated Discovery and Construction of Surface Phase Diagrams Using Machine Learning journal September 2016
Neural-network-enhanced evolutionary algorithm applied to supported metal nanoparticles journal May 2018
Interpretable machine learning as a tool for scientific discovery in chemistry journal January 2020
Commentary: The Materials Project: A materials genome approach to accelerating materials innovation journal July 2013
Machine learning for heterogeneous catalyst design and discovery journal May 2018
Theory-Guided Machine Learning Finds Geometric Structure-Property Relationships for Chemisorption on Subsurface Alloys journal November 2020
Role of Strain and Ligand Effects in the Modification of the Electronic and Chemical Properties of Bimetallic Surfaces journal October 2004
Resolving Transition Metal Chemical Space: Feature Selection for Machine Learning and Structure–Property Relationships journal November 2017
Gaussian Processes in Machine Learning book January 2004
Acceleration of saddle-point searches with machine learning journal August 2016
Uncovering electronic and geometric descriptors of chemical activity for metal alloys and oxides using unsupervised machine learning journal September 2021
Machine Learning for Catalysis Informatics: Recent Applications and Prospects journal December 2019
Subgroup Discovery Points to the Prominent Role of Charge Transfer in Breaking Nitrogen Scaling Relations at Single-Atom Catalysts on VS2 journal June 2021
Using statistical learning to predict interactions between single metal atoms and modified MgO(100) supports journal July 2020
Autonomous intelligent agents for accelerated materials discovery journal January 2020
Open Catalyst 2020 (OC20) Dataset and Community Challenges journal May 2021
Modeling confounding by half-sibling regression journal July 2016
Machine learning in catalysis journal April 2018
Bayesian learning of chemisorption for bridging the complexity of electronic descriptors journal November 2020
Analysis of Updated Literature Data up to 2019 on the Oxidative Coupling of Methane Using an Extrapolative Machine‐Learning Method to Identify Novel Catalysts journal June 2021
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead journal May 2019
Causal inference in statistics: An overview journal January 2009
Visualizing the effects of predictor variables in black box supervised learning models journal June 2020
New tolerance factor to predict the stability of perovskite oxides and halides journal February 2019
CO Chemisorption at Metal Surfaces and Overlayers journal March 1996
Accelerated discovery of CO2 electrocatalysts using active machine learning journal May 2020
Identifying Outstanding Transition-Metal-Alloy Heterogeneous Catalysts for the Oxygen Reduction and Evolution Reactions via Subgroup Discovery journal September 2021
machine. journal October 2001
Data-science driven autonomous process optimization journal August 2021
Opening the Black Box: Interpretable Machine Learning for Geneticists journal June 2020
SISSO: A compressed-sensing method for identifying the best low-dimensional descriptor in an immensity of offered candidates journal August 2018
Reaction-based machine learning representations for predicting the enantioselectivity of organocatalysts journal January 2021
Active Learning Accelerated Discovery of Stable Iridium Oxide Polymorphs for the Oxygen Evolution Reaction journal June 2020
Understanding the Composition and Activity of Electrocatalytic Nanoalloys in Aqueous Solvents: A Combination of DFT and Accurate Neural Network Potentials journal April 2014
The Elements of Statistical Learning book January 2001
Machine Learning-Guided Discovery of Underlying Decisive Factors and New Mechanisms for the Design of Nonprecious Metal Electrocatalysts journal July 2021
Discovery of complex oxides via automated experiments and data science journal September 2021
Factorial Sampling Plans for Preliminary Computational Experiments journal May 1991
Subgroup discovery journal January 2015
Discovery of Descriptors for Stable Monolayer Oxide Coatings through Machine Learning journal October 2018
Infusing theory into deep learning for interpretable reactivity prediction journal September 2021
Interaction trends between single metal atoms and oxide supports identified with density functional theory and statistical learning journal July 2018
Quantum-mechanical transition-state model combined with machine learning provides catalyst design features for selective Cr olefin oligomerization journal January 2020
To address surface reaction network complexity using scaling relations machine learning and DFT calculations journal March 2017
Modeling Segregation on AuPd(111) Surfaces with Density Functional Theory and Monte Carlo Simulations journal February 2017
Distill-and-Compare conference December 2018
Data mining in catalysis: Separating knowledge from garbage journal August 2008
Genetic algorithms for computational materials discovery accelerated by machine learning journal April 2019
Active learning across intermetallics to guide discovery of electrocatalysts for CO2 reduction and H2 evolution journal September 2018
An overview on subgroup discovery: foundations and applications journal November 2010
Effect of Strain on the Reactivity of Metal Surfaces journal September 1998
Definitions, methods, and applications in interpretable machine learning journal October 2019
Uncovering structure-property relationships of materials by subgroup discovery journal January 2017
Holistic prediction of enantioselectivity in asymmetric catalysis journal July 2019
Simple descriptor derived from symbolic regression accelerating the discovery of new perovskite catalysts journal July 2020
Convolutional Neural Network of Atomic Surface Structures To Predict Binding Energies for High-Throughput Screening of Catalysts journal July 2019
Explainable and trustworthy artificial intelligence for correctable modeling in chemical sciences journal October 2020

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