A high-throughput computational screening of potential adsorbents for a thermal compression CO2 Brayton cycle-Reference-Cited by-同舟云学术

A high-throughput computational screening of potential adsorbents for a thermal compression CO2 Brayton cycle

Published:2021 Issue:5 Volume:5 Page:1415-1428
ISSN:2398-4902
Container-title:Sustainable Energy & Fuels
language:en
Short-container-title:Sustainable Energy Fuels

Author:

Du Zhenyu¹²³⁴⁵,Deng Shuai¹²³⁴⁵^ORCID,Zhao Li¹²³⁴⁵^ORCID,Ma Zhiwei⁶⁷⁸⁹,Bao Huashan⁶⁷⁸⁹,Zhao Jie¹²³⁴⁵

Affiliation:

1. Key Laboratory of Efficient Utilization of Low and Medium Grade Energy

2. MOE

3. Tianjin University

4. Tianjin 300072

5. China

6. Department of Engineering

7. Durham University

8. Durham

9. UK

Abstract

The efficient utilization of thermal energy through MOF-based thermal compression CO₂ Brayton cycle.

Funder

National Basic Research Program of China

Natural Science Foundation of Tianjin City

Tianjin Science and Technology Committee

Tianjin Research Program of Application Foundation and Advanced Technology of China

Publisher

Royal Society of Chemistry (RSC)

Subject

Energy Engineering and Power Technology,Fuel Technology,Renewable Energy, Sustainability and the Environment

Link

http://pubs.rsc.org/en/content/articlepdf/2021/SE/D0SE01538E

Reference32 articles.

1. BP , BP Statistical Review of World Energy , https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html , 2020

2. Organic Brayton Cycles with solid sorption thermal compression for low grade heat utilization

3. Adsorption refrigeration—An efficient way to make good use of waste heat and solar energy☆

4. Carbon dioxide based power generation in renewable energy systems

5. Solar driven carbon dioxide Brayton cycle power generation with thermal compression

Cited by 4 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. Computational and Machine Learning Methods for CO₂ Capture Using Metal–Organic Frameworks;ACS Nano;2024-08-22

2. Study on operation performance and application potential of the piston-type thermally-driven pump;Energy Conversion and Management;2024-01

3. Advances in data‐assisted high‐throughput computations for material design;Materials Genome Engineering Advances;2023-09

4. Minimal crystallographic descriptors of sorption properties in hypothetical MOFs and role in sequential learning optimization;npj Computational Materials;2022-06-03