| 학회 |
한국화학공학회 |
| 학술대회 |
2019년 가을 (10/23 ~ 10/25, 대전컨벤션센터) |
| 권호 |
25권 2호, p.2190 |
| 발표분야 |
Application Studies of Multiscale Molecular Modeling and Simulation in Sustainable Chemistry and Eng |
| 제목 |
Computational screening of metal-organic frameworks for adsorption heat pumps |
| 초록 |
Adsorption heat pumps(AHPs) driven by low-grade heat sources including waste heat and solar energy is promising for heating and cooling. However, the coefficient of performance (COP) of AHP is unsatisfactory due to the low uptake and high regeneration cost of conventional adsorbents. Metal-organic frameworks (MOFs) were recognized as potential adsorbents due to their outstanding properties. However,it is a challenging task to quickly find out the potential candidates from a huge number of MOFs. In this work, high-throughput computational screening[1,2] was employed for evaluating the heating/cooling efficiency of a large number of MOFs [3]. Structure-property relationship highlighted the importance of pore size, shape of adsorption isotherms and Henry’s constant towards working fluids in determining COP. Machine learning algorithm was successfully carried out to predict the COP of MOFs. This work provided useful insights into the exploration of high efficient AHPs based on MOFs. |
| 저자 |
Song Li, Wei Li, Xiaoxiao Xia
|
| 소속 |
Huazhong Univ. of Science and Technology |
| 키워드 |
adsorbents; molecular simulations; coefficient of performance; machine learning
|
| E-Mail |
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| 원문파일 |
초록 보기 |
