Machine Learning for Computational Heterogeneous Catalysis
Abstract
Abstract Big data and artificial intelligence has revolutionized science in almost every field – from economics to physics. In the area of materials science and computational heterogeneous catalysis, this revolution has led to the development of scientific data repositories, as well as data mining and machine learning tools to investigate the vast materials space. The goal of using these tools is to establish a deeper understanding of the relations between materials properties and activity, selectivity and stability – the important figures of merit in catalysis. Based on these insights, catalyst design principles can be established, which hopefully lead us to discover highly efficient catalysts to solve pressing issues for a sustainable future and the synthesis of highly functional materials, chemicals and pharmaceuticals. The inherent complexity of catalytic reactions quests for machine learning methods to efficiently navigate through the high‐dimensional hyper‐surfaces in structure optimization problems to determine relevant chemical structures and transition states. In this review, we show how cutting edge data infrastructures and machine learning methods are being used to address problems in computational heterogeneous catalysis.
- Authors:
-
- SUNCAT Center for Interface Science and Catalysis, SLAC National Accelerator Laboratory 2575 Sand Hill Road, Menlo Park California 94025 United States, Department of Chemical Engineering Stanford University 443 Via Ortega Stanford CA 94305 United States
- Publication Date:
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1561362
- Resource Type:
- Publisher's Accepted Manuscript
- Journal Name:
- ChemCatChem
- Additional Journal Information:
- Journal Name: ChemCatChem Journal Volume: 11 Journal Issue: 16; Journal ID: ISSN 1867-3880
- Publisher:
- Wiley Blackwell (John Wiley & Sons)
- Country of Publication:
- Germany
- Language:
- English
Citation Formats
Schlexer Lamoureux, Philomena, Winther, Kirsten T., Garrido Torres, Jose Antonio, Streibel, Verena, Zhao, Meng, Bajdich, Michal, Abild‐Pedersen, Frank, and Bligaard, Thomas. Machine Learning for Computational Heterogeneous Catalysis. Germany: N. p., 2019.
Web. doi:10.1002/cctc.201900595.
Schlexer Lamoureux, Philomena, Winther, Kirsten T., Garrido Torres, Jose Antonio, Streibel, Verena, Zhao, Meng, Bajdich, Michal, Abild‐Pedersen, Frank, & Bligaard, Thomas. Machine Learning for Computational Heterogeneous Catalysis. Germany. https://doi.org/10.1002/cctc.201900595
Schlexer Lamoureux, Philomena, Winther, Kirsten T., Garrido Torres, Jose Antonio, Streibel, Verena, Zhao, Meng, Bajdich, Michal, Abild‐Pedersen, Frank, and Bligaard, Thomas. Tue .
"Machine Learning for Computational Heterogeneous Catalysis". Germany. https://doi.org/10.1002/cctc.201900595.
@article{osti_1561362,
title = {Machine Learning for Computational Heterogeneous Catalysis},
author = {Schlexer Lamoureux, Philomena and Winther, Kirsten T. and Garrido Torres, Jose Antonio and Streibel, Verena and Zhao, Meng and Bajdich, Michal and Abild‐Pedersen, Frank and Bligaard, Thomas},
abstractNote = {Abstract Big data and artificial intelligence has revolutionized science in almost every field – from economics to physics. In the area of materials science and computational heterogeneous catalysis, this revolution has led to the development of scientific data repositories, as well as data mining and machine learning tools to investigate the vast materials space. The goal of using these tools is to establish a deeper understanding of the relations between materials properties and activity, selectivity and stability – the important figures of merit in catalysis. Based on these insights, catalyst design principles can be established, which hopefully lead us to discover highly efficient catalysts to solve pressing issues for a sustainable future and the synthesis of highly functional materials, chemicals and pharmaceuticals. The inherent complexity of catalytic reactions quests for machine learning methods to efficiently navigate through the high‐dimensional hyper‐surfaces in structure optimization problems to determine relevant chemical structures and transition states. In this review, we show how cutting edge data infrastructures and machine learning methods are being used to address problems in computational heterogeneous catalysis.},
doi = {10.1002/cctc.201900595},
journal = {ChemCatChem},
number = 16,
volume = 11,
place = {Germany},
year = {Tue Jun 18 00:00:00 EDT 2019},
month = {Tue Jun 18 00:00:00 EDT 2019}
}
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1002/cctc.201900595
https://doi.org/10.1002/cctc.201900595
Other availability
Search WorldCat to find libraries that may hold this journal
Cited by: 182 works
Citation information provided by
Web of Science
Web of Science
Save to My Library
You must Sign In or Create an Account in order to save documents to your library.
Works referenced in this record:
Fast Prediction of Adsorption Properties for Platinum Nanocatalysts with Generalized Coordination Numbers
journal, June 2014
- Calle-Vallejo, Federico; Martínez, José I.; García-Lastra, Juan M.
- Angewandte Chemie, Vol. 126, Issue 32
Descriptors of Oxygen-Evolution Activity for Oxides: A Statistical Evaluation
journal, December 2015
- Hong, Wesley T.; Welsch, Roy E.; Shao-Horn, Yang
- The Journal of Physical Chemistry C, Vol. 120, Issue 1
Beyond Scaling Relations for the Description of Catalytic Materials
journal, February 2019
- Andersen, Mie; Levchenko, Sergey V.; Scheffler, Matthias
- ACS Catalysis, Vol. 9, Issue 4
The nature of the active site in heterogeneous metal catalysis
journal, January 2008
- Nørskov, Jens K.; Bligaard, Thomas; Hvolbæk, Britt
- Chemical Society Reviews, Vol. 37, Issue 10
Computational high-throughput screening of electrocatalytic materials for hydrogen evolution
journal, October 2006
- Greeley, Jeff; Jaramillo, Thomas F.; Bonde, Jacob
- Nature Materials, Vol. 5, Issue 11, p. 909-913
Linear Inversion of Band-Limited Reflection Seismograms
journal, October 1986
- Santosa, Fadil; Symes, William W.
- SIAM Journal on Scientific and Statistical Computing, Vol. 7, Issue 4
New opportunities for materials informatics: Resources and data mining techniques for uncovering hidden relationships
journal, April 2016
- Jain, Anubhav; Hautier, Geoffroy; Ong, Shyue Ping
- Journal of Materials Research, Vol. 31, Issue 8
CatApp: A Web Application for Surface Chemistry and Heterogeneous Catalysis
journal, December 2011
- Hummelshøj, Jens S.; Abild-Pedersen, Frank; Studt, Felix
- Angewandte Chemie, Vol. 124, Issue 1
Integrating high-throughput characterization into combinatorial heterogeneous catalysis: unsupervised construction of quantitative structure/property relationship models
journal, June 2005
- Corma, A.; Serra, J.; Serna, P.
- Journal of Catalysis, Vol. 232, Issue 2
A genetic algorithm for generating initial parameter estimations for kinetic models of catalytic processes
journal, October 1996
- Moros, R.; Kalies, H.; Rex, H. G.
- Computers & Chemical Engineering, Vol. 20, Issue 10
Electronic factors determining the reactivity of metal surfaces
journal, December 1995
- Hammer, B.; Nørskov, J. K.
- Surface Science, Vol. 343, Issue 3
Machine-learning prediction of the d-band center for metals and bimetals
journal, January 2016
- Takigawa, Ichigaku; Shimizu, Ken-ichi; Tsuda, Koji
- RSC Advances, Vol. 6, Issue 58
Theoretical Heterogeneous Catalysis: Scaling Relationships and Computational Catalyst Design
journal, June 2016
- Greeley, Jeffrey
- Annual Review of Chemical and Biomolecular Engineering, Vol. 7, Issue 1
Including crystal structure attributes in machine learning models of formation energies via Voronoi tessellations
journal, July 2017
- Ward, Logan; Liu, Ruoqian; Krishna, Amar
- Physical Review B, Vol. 96, Issue 2
Scaling Relations for Adsorption Energies on Doped Molybdenum Phosphide Surfaces
journal, March 2017
- Fields, Meredith; Tsai, Charlie; Chen, Leanne D.
- ACS Catalysis, Vol. 7, Issue 4
Prediction of Organic Reaction Outcomes Using Machine Learning
journal, April 2017
- Coley, Connor W.; Barzilay, Regina; Jaakkola, Tommi S.
- ACS Central Science, Vol. 3, Issue 5
Structural optimization of Lennard-Jones clusters by a genetic algorithm
journal, June 1996
- Daven, D. M.; Tit, N.; Morris, J. R.
- Chemical Physics Letters, Vol. 256, Issue 1-2
Nudged elastic band calculations accelerated with Gaussian process regression
journal, October 2017
- Koistinen, Olli-Pekka; Dagbjartsdóttir, Freyja B.; Ásgeirsson, Vilhjálmur
- The Journal of Chemical Physics, Vol. 147, Issue 15
The Rise of Catalyst Informatics: Towards Catalyst Genomics
journal, January 2019
- Takahashi, Keisuke; Takahashi, Lauren; Miyazato, Itsuki
- ChemCatChem, Vol. 11, Issue 4
Machine learning for heterogeneous catalyst design and discovery
journal, May 2018
- Goldsmith, Bryan R.; Esterhuizen, Jacques; Liu, Jin-Xun
- AIChE Journal, Vol. 64, Issue 7
NOMAD: The FAIR concept for big data-driven materials science
journal, September 2018
- Draxl, Claudia; Scheffler, Matthias
- MRS Bulletin, Vol. 43, Issue 9
Toward Effective Utilization of Methane: Machine Learning Prediction of Adsorption Energies on Metal Alloys
journal, March 2018
- Toyao, Takashi; Suzuki, Keisuke; Kikuchi, Shoma
- The Journal of Physical Chemistry C, Vol. 122, Issue 15
On representing chemical environments
journal, May 2013
- Bartók, Albert P.; Kondor, Risi; Csányi, Gábor
- Physical Review B, Vol. 87, Issue 18
Predicting Catalytic Activity of Nanoparticles by a DFT-Aided Machine-Learning Algorithm
journal, August 2017
- Jinnouchi, Ryosuke; Asahi, Ryoji
- The Journal of Physical Chemistry Letters, Vol. 8, Issue 17
Regularization and variable selection via the elastic net
journal, April 2005
- Zou, Hui; Hastie, Trevor
- Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 67, Issue 2
The Computational 2D Materials Database: high-throughput modeling and discovery of atomically thin crystals
journal, September 2018
- Haastrup, Sten; Strange, Mikkel; Pandey, Mohnish
- 2D Materials, Vol. 5, Issue 4
A high-throughput framework for determining adsorption energies on solid surfaces
journal, March 2017
- Montoya, Joseph H.; Persson, Kristin A.
- npj Computational Materials, Vol. 3, Issue 1
Graph Theory Approach to High-Throughput Surface Adsorption Structure Generation
journal, February 2019
- Boes, Jacob R.; Mamun, Osman; Winther, Kirsten
- The Journal of Physical Chemistry A, Vol. 123, Issue 11
Machine-Learning-Augmented Chemisorption Model for CO 2 Electroreduction Catalyst Screening
journal, August 2015
- Ma, Xianfeng; Li, Zheng; Achenie, Luke E. K.
- The Journal of Physical Chemistry Letters, Vol. 6, Issue 18
Thermal Analysis of Heat-Assisted Magnetic Recording Optical Head with Laser Diode on Slider
journal, September 2011
- Xu, Baoxi; Chia, Cheow Wee; Zhang, Qide
- Japanese Journal of Applied Physics, Vol. 50, Issue 9S1
Combinatorial Density Functional Theory-Based Screening of Surface Alloys for the Oxygen Reduction Reaction
journal, March 2009
- Greeley, Jeff; Nørskov, Jens K.
- The Journal of Physical Chemistry C, Vol. 113, Issue 12
Extrapolating Energetics on Clusters and Single-Crystal Surfaces to Nanoparticles by Machine-Learning Scheme
journal, November 2017
- Jinnouchi, Ryosuke; Hirata, Hirohito; Asahi, Ryoji
- The Journal of Physical Chemistry C, Vol. 121, Issue 47
New developments in the Inorganic Crystal Structure Database (ICSD): accessibility in support of materials research and design
journal, May 2002
- Belsky, Alec; Hellenbrandt, Mariette; Karen, Vicky Lynn
- Acta Crystallographica Section B Structural Science, Vol. 58, Issue 3
SchNet – A deep learning architecture for molecules and materials
journal, June 2018
- Schütt, K. T.; Sauceda, H. E.; Kindermans, P. -J.
- The Journal of Chemical Physics, Vol. 148, Issue 24
Adaptive machine learning framework to accelerate ab initio molecular dynamics
journal, December 2014
- Botu, Venkatesh; Ramprasad, Rampi
- International Journal of Quantum Chemistry, Vol. 115, Issue 16
Crystallography Open Database (COD): an open-access collection of crystal structures and platform for world-wide collaboration
journal, November 2011
- Gražulis, Saulius; Daškevič, Adriana; Merkys, Andrius
- Nucleic Acids Research, Vol. 40, Issue D1
New design paradigm for heterogeneous catalysts
journal, April 2015
- Vojvodic, Aleksandra; Nørskov, Jens K.
- National Science Review, Vol. 2, Issue 2
A climbing image nudged elastic band method for finding saddle points and minimum energy paths
journal, December 2000
- Henkelman, Graeme; Uberuaga, Blas P.; Jónsson, Hannes
- The Journal of Chemical Physics, Vol. 113, Issue 22, p. 9901-9904
Predicting Adsorption Properties of Catalytic Descriptors on Bimetallic Nanoalloys with Site-Specific Precision
journal, March 2019
- Choksi, Tej S.; Roling, Luke T.; Streibel, Verena
- The Journal of Physical Chemistry Letters, Vol. 10, Issue 8
Conditioning of quasi-Newton methods for function minimization
journal, September 1970
- Shanno, D. F.
- Mathematics of Computation, Vol. 24, Issue 111
Catalysis-Hub.org, an open electronic structure database for surface reactions
journal, May 2019
- Winther, Kirsten T.; Hoffmann, Max J.; Boes, Jacob R.
- Scientific Data, Vol. 6, Issue 1
A Perovskite Oxide Optimized for Oxygen Evolution Catalysis from Molecular Orbital Principles
journal, October 2011
- Suntivich, J.; May, K. J.; Gasteiger, H. A.
- Science, Vol. 334, Issue 6061
Examining the Linearity of Transition State Scaling Relations
journal, May 2015
- Plessow, Philipp N.; Abild-Pedersen, Frank
- The Journal of Physical Chemistry C, Vol. 119, Issue 19
A general representation scheme for crystalline solids based on Voronoi-tessellation real feature values and atomic property data
journal, March 2018
- Jalem, Randy; Nakayama, Masanobu; Noda, Yusuke
- Science and Technology of Advanced Materials, Vol. 19, Issue 1
Thermo-Calc & DICTRA, computational tools for materials science
journal, June 2002
- Andersson, J-O; Helander, Thomas; Höglund, Lars
- Calphad, Vol. 26, Issue 2
A new approach to variable metric algorithms
journal, March 1970
- Fletcher, R.
- The Computer Journal, Vol. 13, Issue 3
Resolving Transition Metal Chemical Space: Feature Selection for Machine Learning and Structure–Property Relationships
journal, November 2017
- Janet, Jon Paul; Kulik, Heather J.
- The Journal of Physical Chemistry A, Vol. 121, Issue 46
Machine learning model for non-equilibrium structures and energies of simple molecules
journal, January 2019
- Iype, E.; Urolagin, S.
- The Journal of Chemical Physics, Vol. 150, Issue 2
Low-Scaling Algorithm for Nudged Elastic Band Calculations Using a Surrogate Machine Learning Model
journal, April 2019
- Garrido Torres, José A.; Jennings, Paul C.; Hansen, Martin H.
- Physical Review Letters, Vol. 122, Issue 15
Alchemical Predictions for Computational Catalysis: Potential and Limitations
journal, September 2017
- Saravanan, Karthikeyan; Kitchin, John R.; von Lilienfeld, O. Anatole
- The Journal of Physical Chemistry Letters, Vol. 8, Issue 20
Exploration versus Exploitation in Global Atomistic Structure Optimization
journal, January 2018
- Jørgensen, Mathias S.; Larsen, Uffe F.; Jacobsen, Karsten W.
- The Journal of Physical Chemistry A, Vol. 122, Issue 5
Lost in chemical space? Maps to support organometallic catalysis
journal, June 2015
- Fey, Natalie
- Chemistry Central Journal, Vol. 9, Issue 1
Chemometrics: Views and Propositions
journal, November 1975
- Kowalski, B. R.
- Journal of Chemical Information and Modeling, Vol. 15, Issue 4
Modeling the Electrochemical Hydrogen Oxidation and Evolution Reactions on the Basis of Density Functional Theory Calculations
journal, October 2010
- Skúlason, Egill; Tripkovic, Vladimir; Björketun, Mårten E.
- The Journal of Physical Chemistry C, Vol. 114, Issue 42
Matminer: An open source toolkit for materials data mining
journal, September 2018
- Ward, Logan; Dunn, Alexander; Faghaninia, Alireza
- Computational Materials Science, Vol. 152
Predictive Structure–Reactivity Models for Rapid Screening of Pt-Based Multimetallic Electrocatalysts for the Oxygen Reduction Reaction
journal, November 2011
- Xin, Hongliang; Holewinski, Adam; Linic, Suljo
- ACS Catalysis, Vol. 2, Issue 1
The Computational Materials Repository
journal, November 2012
- Landis, David D.; Hummelshoj, Jens S.; Nestorov, Svetlozar
- Computing in Science & Engineering, Vol. 14, Issue 6
The Development of Descriptors for Solids: Teaching“Catalytic Intuition” to a Computer
journal, October 2004
- Klanner, Catharina; Farrusseng, David; Baumes, Laurent
- Angewandte Chemie International Edition, Vol. 43, Issue 40
Configurational Energies of Nanoparticles Based on Metal–Metal Coordination
journal, October 2017
- Roling, Luke T.; Li, Lin; Abild-Pedersen, Frank
- The Journal of Physical Chemistry C, Vol. 121, Issue 41
The FAIR Guiding Principles for scientific data management and stewardship
journal, March 2016
- Wilkinson, Mark D.; Dumontier, Michel; Aalbersberg, IJsbrand Jan
- Scientific Data, Vol. 3, Issue 1
Metadynamics for training neural network model chemistries: A competitive assessment
journal, June 2018
- Herr, John E.; Yao, Kun; McIntyre, Ryker
- The Journal of Chemical Physics, Vol. 148, Issue 24
Research Update: The materials genome initiative: Data sharing and the impact of collaborative ab initio databases
journal, March 2016
- Jain, Anubhav; Persson, Kristin A.; Ceder, Gerbrand
- APL Materials, Vol. 4, Issue 5
Neural network potential-energy surfaces in chemistry: a tool for large-scale simulations
journal, January 2011
- Behler, Jörg
- Physical Chemistry Chemical Physics, Vol. 13, Issue 40
FactSage thermochemical software and databases, 2010–2016
journal, September 2016
- Bale, C. W.; Bélisle, E.; Chartrand, P.
- Calphad, Vol. 54
Design of a Surface Alloy Catalyst for Steam Reforming
journal, March 1998
- Besenbacher, F.
- Science, Vol. 279, Issue 5358
Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons
journal, April 2010
- Bartók, Albert P.; Payne, Mike C.; Kondor, Risi
- Physical Review Letters, Vol. 104, Issue 13
Die katalytische Zersetzung des Nitramids und ihre physikalisch-chemische Bedeutung
journal, January 1924
- Brönsted, J. N.; Pedersen, Kai
- Zeitschrift für Physikalische Chemie, Vol. 108U, Issue 1
Feature engineering of machine-learning chemisorption models for catalyst design
journal, February 2017
- Li, Zheng; Ma, Xianfeng; Xin, Hongliang
- Catalysis Today, Vol. 280
Quantum-chemical insights from deep tensor neural networks
journal, January 2017
- Schütt, Kristof T.; Arbabzadah, Farhad; Chmiela, Stefan
- Nature Communications, Vol. 8, Issue 1
The Development of Descriptors for Solids: Teaching“Catalytic Intuition” to a Computer
journal, October 2004
- Klanner, Catharina; Farrusseng, David; Baumes, Laurent
- Angewandte Chemie, Vol. 116, Issue 40
Machine Learning Force Fields: Construction, Validation, and Outlook
journal, December 2016
- Botu, V.; Batra, R.; Chapman, J.
- The Journal of Physical Chemistry C, Vol. 121, Issue 1
Extracting Knowledge from Data through Catalysis Informatics
journal, June 2018
- Medford, Andrew J.; Kunz, M. Ross; Ewing, Sarah M.
- ACS Catalysis, Vol. 8, Issue 8
Neural network as a tool for catalyst development
journal, April 1995
- Hattori, Tadashi; Kito, Shigeharu
- Catalysis Today, Vol. 23, Issue 4
To address surface reaction network complexity using scaling relations machine learning and DFT calculations
journal, March 2017
- Ulissi, Zachary W.; Medford, Andrew J.; Bligaard, Thomas
- Nature Communications, Vol. 8, Issue 1
Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties
journal, April 2018
- Xie, Tian; Grossman, Jeffrey C.
- Physical Review Letters, Vol. 120, Issue 14
Strongly Modified Scaling of CO Hydrogenation in Metal Supported TiO Nanostripes
journal, September 2018
- Sandberg, Robert B.; Hansen, Martin H.; Nørskov, Jens K.
- ACS Catalysis, Vol. 8, Issue 11
Machine learning for molecular and materials science
journal, July 2018
- Butler, Keith T.; Davies, Daniel W.; Cartwright, Hugh
- Nature, Vol. 559, Issue 7715
Artificial neural network analysis of the catalytic efficiency of platinum nanoparticles
journal, January 2017
- Fernandez, Michael; Barron, Hector; Barnard, Amanda S.
- RSC Adv., Vol. 7, Issue 77
Automated Discovery of Elementary Chemical Reaction Steps Using Freezing String and Berny Optimization Methods
journal, August 2015
- Suleimanov, Yury V.; Green, William H.
- Journal of Chemical Theory and Computation, Vol. 11, Issue 9
MTDATA - thermodynamic and phase equilibrium software from the national physical laboratory
journal, June 2002
- Davies, Rh; Dinsdale, At; Gisby, Ja
- Calphad, Vol. 26, Issue 2
The Convergence of a Class of Double-rank Minimization Algorithms 1. General Considerations
journal, January 1970
- Broyden, C. G.
- IMA Journal of Applied Mathematics, Vol. 6, Issue 1
A coordination-based model for transition metal alloy nanoparticles
journal, January 2019
- Roling, Luke T.; Choksi, Tej S.; Abild-Pedersen, Frank
- Nanoscale, Vol. 11, Issue 10
Chemical Pressure-Driven Enhancement of the Hydrogen Evolving Activity of Ni 2 P from Nonmetal Surface Doping Interpreted via Machine Learning
journal, March 2018
- Wexler, Robert B.; Martirez, John Mark P.; Rappe, Andrew M.
- Journal of the American Chemical Society, Vol. 140, Issue 13
Prediction of solid-aqueous equilibria: Scheme to combine first-principles calculations of solids with experimental aqueous states
journal, June 2012
- Persson, Kristin A.; Waldwick, Bryn; Lazic, Predrag
- Physical Review B, Vol. 85, Issue 23
A family of variable-metric methods derived by variational means
journal, January 1970
- Goldfarb, Donald
- Mathematics of Computation, Vol. 24, Issue 109
Machine-learning models for combinatorial catalyst discovery
journal, December 2004
- Landrum, Gregory A.; Penzotti, Julie E.; Putta, Santosh
- Measurement Science and Technology, Vol. 16, Issue 1
Optimizing Perovskites for the Water-Splitting Reaction
journal, December 2011
- Vojvodic, A.; Norskov, J. K.
- Science, Vol. 334, Issue 6061
An open experimental database for exploring inorganic materials
journal, April 2018
- Zakutayev, Andriy; Wunder, Nick; Schwarting, Marcus
- Scientific Data, Vol. 5, Issue 1
Single-ended transition state finding with the growing string method
journal, January 2015
- Zimmerman, Paul M.
- Journal of Computational Chemistry, Vol. 36, Issue 9
From the Sabatier principle to a predictive theory of transition-metal heterogeneous catalysis
journal, August 2015
- Medford, Andrew J.; Vojvodic, Aleksandra; Hummelshøj, Jens S.
- Journal of Catalysis, Vol. 328
The small sample size problem of ICA: A comparative study and analysis
journal, December 2012
- Deng, Weihong; Liu, Yebin; Hu, Jiani
- Pattern Recognition, Vol. 45, Issue 12
Vision for Data and Informatics in the Future Materials Innovation Ecosystem
journal, August 2016
- Kalidindi, Surya R.; Medford, Andrew J.; McDowell, David L.
- JOM, Vol. 68, Issue 8
Charting the complete elastic properties of inorganic crystalline compounds
journal, March 2015
- de Jong, Maarten; Chen, Wei; Angsten, Thomas
- Scientific Data, Vol. 2, Issue 1
Redesigning the Materials and Catalysts Database Construction Process Using Ontologies
journal, August 2018
- Takahashi, Lauren; Miyazato, Itsuki; Takahashi, Keisuke
- Journal of Chemical Information and Modeling, Vol. 58, Issue 9
Active learning with non- ab initio input features toward efficient CO 2 reduction catalysts
journal, January 2018
- Noh, Juhwan; Back, Seoin; Kim, Jaehoon
- Chemical Science, Vol. 9, Issue 23
High-throughput screening of bimetallic catalysts enabled by machine learning
journal, January 2017
- Li, Zheng; Wang, Siwen; Chin, Wei Shan
- Journal of Materials Chemistry A, Vol. 5, Issue 46
Self-organized formation of topologically correct feature maps
journal, January 1982
- Kohonen, Teuvo
- Biological Cybernetics, Vol. 43, Issue 1
Finding optimal surface sites on heterogeneous catalysts by counting nearest neighbors
journal, October 2015
- Calle-Vallejo, F.; Tymoczko, J.; Colic, V.
- Science, Vol. 350, Issue 6257
Statistical Inference for Probabilistic Functions of Finite State Markov Chains
journal, December 1966
- Baum, Leonard E.; Petrie, Ted
- The Annals of Mathematical Statistics, Vol. 37, Issue 6
PANDAT software with PanEngine, PanOptimizer and PanPrecipitation for multi-component phase diagram calculation and materials property simulation
journal, June 2009
- Cao, W.; Chen, S. -L.; Zhang, F.
- Calphad, Vol. 33, Issue 2
The rate of electrolytic hydrogen evolution and the heat of adsorption of hydrogen
journal, January 1958
- Parsons, Roger
- Transactions of the Faraday Society, Vol. 54, p. 1053-1063
Further considerations on the thermodynamics of chemical equilibria and reaction rates
journal, January 1936
- Evans, M. G.; Polanyi, M.
- Transactions of the Faraday Society, Vol. 32
AiiDA: automated interactive infrastructure and database for computational science
journal, January 2016
- Pizzi, Giovanni; Cepellotti, Andrea; Sabatini, Riccardo
- Computational Materials Science, Vol. 111
Why Is Bulk Thermochemistry a Good Descriptor for the Electrocatalytic Activity of Transition Metal Oxides?
journal, January 2015
- Calle-Vallejo, Federico; Díaz-Morales, Oscar A.; Kolb, Manuel J.
- ACS Catalysis, Vol. 5, Issue 2
Orbitalwise Coordination Number for Predicting Adsorption Properties of Metal Nanocatalysts
journal, January 2017
- Ma, Xianfeng; Xin, Hongliang
- Physical Review Letters, Vol. 118, Issue 3
Comparing partitions
journal, December 1985
- Hubert, Lawrence; Arabie, Phipps
- Journal of Classification, Vol. 2, Issue 1
Atomic-position independent descriptor for machine learning of material properties
journal, December 2018
- Jain, Ankit; Bligaard, Thomas
- Physical Review B, Vol. 98, Issue 21
Selective methanation of CO over supported Ru catalysts
journal, May 2009
- Panagiotopoulou, Paraskevi; Kondarides, Dimitris I.; Verykios, Xenophon. E.
- Applied Catalysis B: Environmental, Vol. 88, Issue 3-4
Materials Data Science: Current Status and Future Outlook
journal, July 2015
- Kalidindi, Surya R.; De Graef, Marc
- Annual Review of Materials Research, Vol. 45, Issue 1
International chemical identifier for reactions (RInChI)
journal, May 2018
- Grethe, Guenter; Blanke, Gerd; Kraut, Hans
- Journal of Cheminformatics, Vol. 10, Issue 1
How Many Clusters? Which Clustering Method? Answers Via Model-Based Cluster Analysis
journal, August 1998
- Fraley, C.
- The Computer Journal, Vol. 41, Issue 8
CatApp: A Web Application for Surface Chemistry and Heterogeneous Catalysis
journal, December 2011
- Hummelshøj, Jens S.; Abild-Pedersen, Frank; Studt, Felix
- Angewandte Chemie International Edition, Vol. 51, Issue 1
Prediction of Adsorption Energies for Chemical Species on Metal Catalyst Surfaces Using Machine Learning
journal, November 2018
- Chowdhury, Asif J.; Yang, Wenqiang; Walker, Eric
- The Journal of Physical Chemistry C, Vol. 122, Issue 49
Predicting the Thermodynamic Stability of Solids Combining Density Functional Theory and Machine Learning
journal, May 2017
- Schmidt, Jonathan; Shi, Jingming; Borlido, Pedro
- Chemistry of Materials, Vol. 29, Issue 12
Computational Design Principles of Two-Center First-Row Transition Metal Oxide Oxygen Evolution Catalysts
journal, July 2017
- Mavros, Michael G.; Shepherd, James J.; Tsuchimochi, Takashi
- The Journal of Physical Chemistry C, Vol. 121, Issue 29
Fundamental Concepts in Heterogeneous Catalysis
book, January 2014
- Nørskov, Jens K.; Studt, Felix; Abild-Pedersen, Frank
- John Wiley & Sons, Inc.
Identifying optimal active sites for heterogeneous catalysis by metal alloys based on molecular descriptors and electronic structure engineering
journal, August 2013
- Holewinski, Adam; Xin, Hongliang; Nikolla, Eranda
- Current Opinion in Chemical Engineering, Vol. 2, Issue 3
On-the-Fly Machine Learning of Atomic Potential in Density Functional Theory Structure Optimization
journal, January 2018
- Jacobsen, T. L.; Jørgensen, M. S.; Hammer, B.
- Physical Review Letters, Vol. 120, Issue 2
Machine learning bandgaps of double perovskites
journal, January 2016
- Pilania, G.; Mannodi-Kanakkithodi, A.; Uberuaga, B. P.
- Scientific Reports, Vol. 6, Issue 1
Structural Relaxation Made Simple
journal, October 2006
- Bitzek, Erik; Koskinen, Pekka; Gähler, Franz
- Physical Review Letters, Vol. 97, Issue 17
Electrostatic Origins of Linear Scaling Relationships at Bifunctional Metal/Oxide Interfaces: A Case Study of Au Nanoparticles on Doped MgO Substrates
journal, October 2018
- Choksi, Tej; Majumdar, Paulami; Greeley, Jeffrey P.
- Angewandte Chemie International Edition, Vol. 57, Issue 47
Knowledge extraction for water gas shift reaction over noble metal catalysts from publications in the literature between 2002 and 2012
journal, April 2014
- Odabaşı, Çağla; Günay, M. Erdem; Yıldırım, Ramazan
- International Journal of Hydrogen Energy, Vol. 39, Issue 11
Physical descriptor for the Gibbs energy of inorganic crystalline solids and temperature-dependent materials chemistry
journal, October 2018
- Bartel, Christopher J.; Millican, Samantha L.; Deml, Ann M.
- Nature Communications, Vol. 9, Issue 1
Machine-Learning Methods Enable Exhaustive Searches for Active Bimetallic Facets and Reveal Active Site Motifs for CO 2 Reduction
journal, August 2017
- Ulissi, Zachary W.; Tang, Michael T.; Xiao, Jianping
- ACS Catalysis, Vol. 7, Issue 10
Creating Machine Learning-Driven Material Recipes Based on Crystal Structure
journal, January 2019
- Takahashi, Keisuke; Takahashi, Lauren
- The Journal of Physical Chemistry Letters, Vol. 10, Issue 2
MatCALO: Knowledge-enabled machine learning in materials science
journal, June 2019
- Picklum, Mareike; Beetz, Michael
- Computational Materials Science, Vol. 163
Commentary: The Materials Project: A materials genome approach to accelerating materials innovation
journal, July 2013
- Jain, Anubhav; Ong, Shyue Ping; Hautier, Geoffroy
- APL Materials, Vol. 1, Issue 1
Structure-Sensitive Scaling Relations: Adsorption Energies from Surface Site Stability
journal, March 2018
- Roling, Luke T.; Abild-Pedersen, Frank
- ChemCatChem, Vol. 10, Issue 7
Scaling Properties of Adsorption Energies for Hydrogen-Containing Molecules on Transition-Metal Surfaces
journal, July 2007
- Abild-Pedersen, F.; Greeley, J.; Studt, F.
- Physical Review Letters, Vol. 99, Issue 1
Global Optimization by Basin-Hopping and the Lowest Energy Structures of Lennard-Jones Clusters Containing up to 110 Atoms
journal, July 1997
- Wales, David J.; Doye, Jonathan P. K.
- The Journal of Physical Chemistry A, Vol. 101, Issue 28
Materials Design and Discovery with High-Throughput Density Functional Theory: The Open Quantum Materials Database (OQMD)
journal, September 2013
- Saal, James E.; Kirklin, Scott; Aykol, Muratahan
- JOM, Vol. 65, Issue 11
Automated Discovery and Construction of Surface Phase Diagrams Using Machine Learning
journal, September 2016
- Ulissi, Zachary W.; Singh, Aayush R.; Tsai, Charlie
- The Journal of Physical Chemistry Letters, Vol. 7, Issue 19
Molecular Geometry Optimization with a Genetic Algorithm
journal, July 1995
- Deaven, D. M.; Ho, K. M.
- Physical Review Letters, Vol. 75, Issue 2
Chemisorption phenomena: Analytic modeling based on perturbation theory and bond-order conservation
journal, July 1986
- Shustorovich, Evgeny
- Surface Science Reports, Vol. 6, Issue 1
Machine learning hydrogen adsorption on nanoclusters through structural descriptors
journal, July 2018
- Jäger, Marc O. J.; Morooka, Eiaki V.; Federici Canova, Filippo
- npj Computational Materials, Vol. 4, Issue 1
Active Learning
journal, June 2012
- Settles, Burr
- Synthesis Lectures on Artificial Intelligence and Machine Learning, Vol. 6, Issue 1
AFLOWLIB.ORG: A distributed materials properties repository from high-throughput ab initio calculations
journal, June 2012
- Curtarolo, Stefano; Setyawan, Wahyu; Wang, Shidong
- Computational Materials Science, Vol. 58
Fast Prediction of Adsorption Properties for Platinum Nanocatalysts with Generalized Coordination Numbers
journal, June 2014
- Calle-Vallejo, Federico; Martínez, José I.; García-Lastra, Juan M.
- Angewandte Chemie International Edition, Vol. 53, Issue 32
Acceleration of saddle-point searches with machine learning
journal, August 2016
- Peterson, Andrew A.
- The Journal of Chemical Physics, Vol. 145, Issue 7
Optimal design of an ammonia synthesis reactor using genetic algorithms
journal, September 1997
- Upreti, Simant R.; Deb, Kalyanmoy
- Computers & Chemical Engineering, Vol. 21, Issue 1
Impact of nanoparticle size and lattice oxygen on water oxidation on NiFeOxHy
journal, November 2018
- Roy, C.; Sebok, B.; Scott, S. B.
- Nature Catalysis, Vol. 1, Issue 11
AFLOW-ML: A RESTful API for machine-learning predictions of materials properties
journal, September 2018
- Gossett, Eric; Toher, Cormac; Oses, Corey
- Computational Materials Science, Vol. 152
Phase diagram calculation: past, present and future
journal, January 2004
- Chang, Y. Austin; Chen, Shuanglin; Zhang, Fan
- Progress in Materials Science, Vol. 49, Issue 3-4
The Cambridge Structural Database: a quarter of a million crystal structures and rising
journal, May 2002
- Allen, Frank H.
- Acta Crystallographica Section B Structural Science, Vol. 58, Issue 3
Active learning across intermetallics to guide discovery of electrocatalysts for CO2 reduction and H2 evolution
journal, September 2018
- Tran, Kevin; Ulissi, Zachary W.
- Nature Catalysis, Vol. 1, Issue 9
Combining theory and experiment in electrocatalysis: Insights into materials design
journal, January 2017
- Seh, Zhi Wei; Kibsgaard, Jakob; Dickens, Colin F.
- Science, Vol. 355, Issue 6321
Combinatorial screening for new materials in unconstrained composition space with machine learning
journal, March 2014
- Meredig, B.; Agrawal, A.; Kirklin, S.
- Physical Review B, Vol. 89, Issue 9
An electronic structure descriptor for oxygen reactivity at metal and metal-oxide surfaces
journal, March 2019
- Dickens, Colin F.; Montoya, Joseph H.; Kulkarni, Ambarish R.
- Surface Science, Vol. 681
On Benchmarking of Automated Methods for Performing Exhaustive Reaction Path Search
journal, March 2019
- Maeda, Satoshi; Harabuchi, Yu
- Journal of Chemical Theory and Computation, Vol. 15, Issue 4