Mapping the Flammability Space of Sustainable Refrigerant Mixtures through an Artificial Neural Network Based on Molecular Descriptors-Reference-Cited by-同舟云学术

Mapping the Flammability Space of Sustainable Refrigerant Mixtures through an Artificial Neural Network Based on Molecular Descriptors

Published:2024-07-23 Issue:31 Volume:12 Page:11561-11577
ISSN:2168-0485
Container-title:ACS Sustainable Chemistry & Engineering
language:en
Short-container-title:ACS Sustainable Chem. Eng.

Author:

Albà Carlos G.¹,Alkhatib Ismail I. I.²^ORCID,Vega Lourdes F.²^ORCID,Llovell Fèlix¹^ORCID

Affiliation:

1. Department of Chemical Engineering, ETSEQ, Universitat Rovira i Virgili (URV), Campus Sescelades, Av. Països Catalans 26, 43007 Tarragona, Spain

2. Research and Innovation Center on CO2 and Hydrogen (RICH Center) and Department of Chemical and Petroleum Engineering, Khalifa University, PO Box 127788 Abu Dhabi, United Arab Emirates

Funder

European Commission

Khalifa University of Science, Technology and Research

Ministerio de Ciencia e Innovaci?n

Ag?ncia de Gesti? d'Ajuts Universitaris i de Recerca

Generalitat de Catalunya

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acssuschemeng.4c01961

Reference110 articles.

1. Meeting the environmental challenge: a case of win–win or lose–win? A study of the UK baking and refrigeration industries

2. Trade-offs in refrigerant selections: past, present, and future

3. The next generation of refrigerants – Historical review, considerations, and outlook

4. Electricity sector transformation in New Zealand: A sustainability assessment approach

5. Analysis based on EU Regulation No 517/2014 of new HFC/HFO mixtures as alternatives of high GWP refrigerants in refrigeration and HVAC systems

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. High-temperature heat pump working fluid development based on molecular design and the group contribution method;Applied Thermal Engineering;2024-12