A Generic Machine Learning Algorithm for the Prediction of Gas Adsorption in Nanoporous Materials
| Autor: | George S. Fanourgakis, George E. Froudakis, Konstantinos Gkagkas, Emmanuel Tylianakis |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer science
Nanoporous business.industry 02 engineering and technology 010402 general chemistry 021001 nanoscience & nanotechnology Machine learning computer.software_genre 01 natural sciences 0104 chemical sciences Surfaces Coatings and Films Electronic Optical and Magnetic Materials Set (abstract data type) General Energy Adsorption Artificial intelligence Physical and Theoretical Chemistry 0210 nano-technology business computer |
| Zdroj: | The Journal of Physical Chemistry C. 124:7117-7126 |
| ISSN: | 1932-7455 1932-7447 |
| DOI: | 10.1021/acs.jpcc.9b10766 |
| Popis: | In the present study, we propose a new set of descriptors, appropriate for machine learning (ML) methods, aiming to predict accurately the gas adsorption capacities of nanoporous materials. The pre... |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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