Article detail · 2021
Recent advances in knowledge discovery for heterogeneous catalysis using machine learning
Journal
CATALYSIS REVIEWS-SCIENCE AND ENGINEERINGISSN 0161-4940
The ISSN points to another catalog journal; the name is from the YÖKSİS record.
- Year
- 2021
- Type
- article
Data source split
- YÖKSİS YÖKSİS article record
- YÖKSİS venue CATALYSIS REVIEWS-SCIENCE AND ENGINEERING
- Catalog match (ISSN) Catalysis Reviews - Science and Engineering
- OpenAlex OpenAlex enrichment (abstract, citations, topics)
Abstract
OpenAlex · English
The use of machine learning (ML) in catalysis has been significantly increased in recent years due to the astonishing developments in data processing technologies and the accumulation of a large amount of data in published literature and databases. The data generated in house or extracted from external sources have been analyzed using various ML techniques to see patterns, develop models for prediction and deduce heuristic rules for the future. This communication aims to review the works involving knowledge discovery in catalysis using ML techniques; the basic principles, common tools and implementation of ML in catalysis are also summarized.Abbreviations: ANN: Artificial neural network; ASLA: Atomistic structure learning algorithm; CatApp: A web application heterogeneous catalysis; CSD: Cambridge Structural Database; co-pre: Co-precipitation; Cx: Fraction of curvature; DFT: Density functional theory; DT: Decision tree; ∆ECO: CO adsorption energy; Fx: Fraction of facets; MBTR: Many-body tensor representation; ML: Machine learning; MOF: Metal-organic framework; Nx: Number of atoms; PC: Polymerized complex; Rx: Radius; R2: Coefficient of determination; RMSE: Root mean square error; RSM: Response surface methodology; SG: Sol-gel; SISSO: Sure independence screening and sparsifying operator; SIMELS: Simplified molecular-input line-entry system; SOAP: Smooth overlap of atomic positions; SSR: Solid-state reaction; T: Temperature; t: Time; τ: Atomic deposition rate; WIPO: World Intellectual Property Organization; WOS: Web of Science; XANES: X-ray absorption near-edge structure
Topics
Citations
OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.
129 citations
OpenAlex cited_by_count (cache / database)
31 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).
- Machine Learning Meets with Metal Organic Frameworks for Gas Storage and Separation 2021
- Machine Learning Meets with Metal Organic Frameworks for Gas Storage and Separation 2021
- Machine Learning Meets with Metal Organic Frameworks for Gas Storage and Separation 2021
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