  Citation: Li, L.; Shi, Z.; Liang, H.; Liu, J.; Qiao, Z. Machine Learning- Assisted Computational Screening of Metal-Organic Frameworks for Atmospheric Water Harvesting. Nanomaterials 2022, 12, 159. https://doi.org/10.3390/ nano12010159 Academic Editors: Filipe Figueiredo and Jorge Pasán Received: 7 November 2021 Accepted: 31 December 2021 Published: 3 January 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). nanomaterials Article Machine Learning-Assisted Computational Screening of Metal-Organic Frameworks for Atmospheric Water Harvesting Lifeng Li 1,† , Zenan Shi 1,† , Hong Liang 1, *, Jie Liu 2, * and Zhiwei Qiao 1, * 1 Guangzhou Key Laboratory for New Energy and Green Catalysis, School of Chemistry and Chemical Engineering, Guangzhou University, Guangzhou 510006, China; lilifeng@e.gzhu.edu.cn (L.L.); zenanshi@126.com (Z.S.) 2 Key Laboratory for Green Chemical Process of Ministry of Education, School of Chemical Engineering and Pharmacy, Wuhan Institute of Technology, Wuhan 430073, China * Correspondence: lhong@gzhu.edu.cn (H.L.); ljie@wit.edu.cn (J.L.); zqiao@gzhu.edu.cn (Z.Q.); Tel.: +86-135-6015-8624 (Z.Q.) † These authors contributed equally to this work. Abstract: Atmospheric water harvesting by strong adsorbents is a feasible method of solving the shortage of water resources, especially for arid regions. In this study, a machine learning (ML)- assisted high-throughput computational screening is employed to calculate the capture of H 2 O from N 2 and O 2 for 6013 computation-ready, experimental metal-organic frameworks (CoRE-MOFs) and 137,953 hypothetical MOFs (hMOFs). Through the univariate analysis of MOF structure-performance relationships, Q st is shown to be a key descriptor. Moreover, three ML algorithms (random forest, gradient boosted regression trees, and neighbor component analysis (NCA)) are applied to hunt for the complicated interrelation between six descriptors and performance. After the optimizing strategy of grid search and five-fold cross-validation is performed, three ML can effectively build the predictive model for CoRE-MOFs, and the accuracy R 2 of NCA can reach 0.97. In addition, based on the relative importance of the descriptors by ML, it can be quantitatively concluded that the Q st is dominant in governing the capture of H 2 O. Besides, the NCA model trained by 6013 CoRE-MOFs can predict the selectivity of hMOFs with a R 2 of 0.86, which is more universal than other models. Finally, 10 CoRE-MOFs and 10 hMOFs with high performance are identified. The computational screening and prediction of ML could provide guidance and inspiration for the development of materials for water harvesting in the atmosphere. Keywords: metal-organic frameworks; water harvesting; molecular simulation; algorithm; absorption 1. Induction As we all know, 71% of the earth’s surface is covered by water, and the remaining 29% is land. At first glance, we have a lot of water resources; in fact, the water we use is mainly fresh water, and fresh water only accounts for 2.5% of all water resources on the earth [1]. Among them, approximately 69% of the fresh water is enclosed in the ice layer of Antarctica and Greenland, and the remaining 30% is stored in the ground, so the fresh water (such as river water and fresh water lakes) that humans can directly use accounts for only 0.4% of all water resources [1]. As population growth and living standards improve, water resources are becoming increasingly scarce, especially daily water for residents of arid regions. Currently, one third of the world’s population live in regions with medium and high water shortages. It is estimated that two thirds of the world will face water shortages by 2050 [2]. Therefore, the lack of fresh water has become one of the major crises to be resolved. At present, several technologies are being used to address this issue. Desalination is one of the main ways to develop new fresh water resources, but the construction of this infrastructure requires a lot of money and the production process is highly energy intensive [3]. In addition, since the main arid and water-scarce areas are far inland, there Nanomaterials 2022, 12, 159. https://doi.org/10.3390/nano12010159 https://www.mdpi.com/journal/nanomaterials