Machine learning and in silico discovery of metal-organic frameworks: Methanol as a working fluid in adsorption-driven heat pumps and chillers

2020 ◽  
Vol 214 ◽  
pp. 115430 ◽  
Author(s):  
Zenan Shi ◽  
Hong Liang ◽  
Wenyuan Yang ◽  
Jie Liu ◽  
Zili Liu ◽  
...  
Keyword(s):  
Machine Learning ◽  
In Silico ◽  
Metal Organic Frameworks ◽  
Heat Pumps ◽  
Working Fluid ◽  
Metal Organic

scholarly journals In Silico Screening of Metal–Organic Frameworks for Adsorption-Driven Heat Pumps and Chillers

2018 ◽  
Vol 10 (32) ◽  
pp. 27074-27087 ◽  
Author(s):  
Máté Erdős ◽  
Martijn F. de Lange ◽  
Freek Kapteijn ◽  
Othonas A. Moultos ◽  
Thijs J. H. Vlugt
Keyword(s):  
In Silico ◽  
Metal Organic Frameworks ◽  
Heat Pumps ◽  
In Silico Screening ◽  
Metal Organic

Techno-Economic Analysis of Metal–Organic Frameworks for Adsorption Heat Pumps/Chillers: From Directional Computational Screening, Machine Learning to Experiment

2021 ◽  
Author(s):  
Zenan Shi ◽  
Xueying Yuan ◽  
Yaling Yan ◽  
Yuanlin Tang ◽  
Junjie Li ◽  
...  
Keyword(s):  
Machine Learning ◽  
Economic Analysis ◽  
High Performance ◽  
Metal Organic Frameworks ◽  
Heat Pumps ◽  
Adsorption Heat ◽  
Organic P ◽  
Computational Screening ◽  
Metal Organic ◽  
Low Costs

The key to achieving high efficiencies, high performance, and low costs of adsorption heat pumps/chillers (AHPs/ACs) is to choose a suitable adsorbent. A computational screening of 6,013 computation-ready experimental metal–organic...

scholarly journals Machine learning the quantum-chemical properties of metal–organic frameworks for accelerated materials discovery

Matter ◽  
2021 ◽  
Author(s):  
Andrew S. Rosen ◽  
Shaelyn M. Iyer ◽  
Debmalya Ray ◽  
Zhenpeng Yao ◽  
Alán Aspuru-Guzik ◽  
...  
Keyword(s):  
Machine Learning ◽  
Quantum Chemical ◽  
Metal Organic Frameworks ◽  
Chemical Properties ◽  
Metal Organic

An Automated Machine Learning architecture for the accelerated prediction of Metal-Organic Frameworks performance in energy and environmental applications

2020 ◽  
Vol 300 ◽  
pp. 110160 ◽  
Author(s):  
Ioannis Tsamardinos ◽  
George S. Fanourgakis ◽  
Elissavet Greasidou ◽  
Emmanuel Klontzas ◽  
Konstantinos Gkagkas ◽  
...  
Keyword(s):  
Machine Learning ◽  
Metal Organic Frameworks ◽  
Environmental Applications ◽  
Metal Organic ◽  
Automated Machine Learning
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