Combined deep-learning optimization predictive models for determining carbon dioxide solubility in ionic liquids-Reference-Cited by-同舟云学术

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Combined deep-learning optimization predictive models for determining carbon dioxide solubility in ionic liquids

Published:2024-09 Issue: Volume:41 Page:100662
ISSN:2452-414X
Container-title:Journal of Industrial Information Integration
language:en
Short-container-title:Journal of Industrial Information Integration

Author:

Davoodi Shadfar^ORCID,Thanh Hung Vo,Wood David A.,Mehrad Mohammad,Hajsaeedi Mohammad Reza^ORCID,Rukavishnikov Valeriy S.

Funder

Tomsk Polytechnic University

Publisher

Elsevier BV

Reference70 articles.

1. Mapping global carbon footprint in China;Yang;Nat. Commun.,2020

2. Natural gas: A transition fuel for sustainable energy system transformation?;Safari;Energy Sci. Eng.,2019

3. Wind Power Forecasting Using Optimized Dendritic Neural Model Based on Seagull Optimization Algorithm and Aquila Optimizer;Al-qaness;Energies,2022

4. The case for estimating carbon return on investment (CROI) for CCUS platforms;Singh;Appl. Energy.,2021

5. Integrated CO2 capture-fixation chemistry via interfacial ionic liquid catalyst in laminar gas/liquid flow;Vishwakarma;Nat. Commun.,2017

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. Carbon capture using ionic liquids: An explicit data driven model for carbon (IV) Oxide solubility estimation;Journal of Cleaner Production;2024-09

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