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Metal-organic frameworks (MOFs) are of immense interest in applications such as gas storage and carbon capture due to their exceptional porosity and tunable chemistry.
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The chemistry of metal–organic frameworks for co2 capture, regeneration and conversion
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Markus J Kalmutzki, Nikita Hanikel, and Omar M Yaghi · 2018
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Recent advances in gas storage and separation using metal–organic frameworks
Hao Li, Kecheng Wang, Yujia Sun, Christina T Lollar, Jialuo Li, and Hong-Cai Zhou · 2018
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Crystal graph convolutional neural networks for an accurate and interpretable prediction of material properties
Tian Xie and Jeffrey C Grossman · 2018
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Data-driven design of metal–organic frameworks for wet flue gas co2 capture
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Graph networks as a universal machine learning framework for molecules and crystals
Chi Chen, Weike Ye, Yunxing Zuo, Chen Zheng, and Shyue Ping Ong · 2019
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Advances, updates, and analytics for the computation-ready, experimental metal–organic framework database: Core mof 2019
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Mofsimplify, machine learning models with extracted stability data of three thousand metal–organic frameworks
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Crystal diffusion variational autoencoder for periodic material generation
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Review on metal–organic framework classification, synthetic approaches, and influencing factors: Applications in energy, drug delivery, and wastewater treatment
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