High-throughput virtual screening of metal–organic frameworks for xenon recovery from exhaled anesthetic gas mixture

Cheng, Min; Wang, Shihui; Zhang, Zhiyuan; Ji, Xu; Liu, Chong; Dai, Yiyang; Dang, Yagu; Zhou, Li

doi:10.1016/j.cej.2022.138218

Cited by 19 publications

(5 citation statements)

References 46 publications

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“…By the end of 2023, it is projected that there will have been about 300 papers on photocatalytic MOF. Additionally, MOF-based materials have been used for the removal of heavy metals [ 44 , 45 ], the recovery of precious metals [ 46 , 47 ], the capture of CO 2 and other toxic gases [ 48 , 49 ], water splitting [ 35 , 36 ], production of solar fuel [ 50 – 52 ], and photocatalytic degradation of various organic and inorganic pollutants [ 38 – 42 ] ( Figure 1b ).…”

Section: Metal-organic Framework (Mofs)mentioning

confidence: 99%

Metal-organic frameworks as photocatalysts in energetic and environmental applications

ÖZCAN,

MERMER,

ZORLU

2023

Turkish Journal of Chemistry

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Metal-organic frameworks (MOFs) are an exciting new class of porous materials with great potential for photocatalytic applications in the environmental and energy sectors. MOFs provide significant advantages over more traditional materials when used as photocatalysts due to their high surface area, adaptable topologies, and functional ability. In this article, we summarize current developments in the use of MOFs as photocatalysts for a variety of applications, such as CO 2 reduction, water splitting, pollutant degradation, and hydrogen production. We discuss the fundamental properties of MOFs that make them ideal for photocatalytic applications, as well as strategies for improving their performance. The opportunities and challenges presented by this rapidly expanding field are also highlighted.

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Section: Metal-organic Framework (Mofs)mentioning

confidence: 99%

Metal-organic frameworks as photocatalysts in energetic and environmental applications

ÖZCAN,

MERMER,

ZORLU

2023

Turkish Journal of Chemistry

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“…High-throughput computational screening of MOFs using molecular simulations can provide information that can be acquired much faster than experiments to determine the gas separation performance of MOFs. There are a growing number of studies in the literature on the large-scale screening of MOFs for gas separations. − However, very few studies have focused on the separation of CF 4 from CH 4 and/or N 2 . One of the first studies on CF 4 /CH 4 separation was conducted by Buss and Heuchel where the CF 4 /CH 4 (50/50) selectivity in silicalite at 298.15 K and 17 bar was estimated to be about 2.5 using ideal adsorbed solution theory (IAST).…”

Section: Introductionmentioning

confidence: 99%

Simulation and Machine Learning-Integrated Investigation of Double-Linker MOFs for the Separation of CF₄ from CH₄ and N₂

Demir,

Erucar

2024

Ind. Eng. Chem. Res.

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One of the most crucial problems of the modern world is to combat the emission of greenhouse gases as these lead to extreme weather conditions, droughts, etc., and endanger the global ecosystem. Among the various greenhouse gases, the removal of carbon tetrafluoride, CF 4 , from the atmosphere is of particular interest as its global warming potential is several orders of magnitude higher than that of many other greenhouse gases, including carbon dioxide, CO 2 . The separation of CF 4 from methane, CH 4 , and nitrogen, N 2 , which are present in the atmosphere alongside CF 4 , can be efficiently accomplished by adsorption-or membrane-based processes. Metal−organic frameworks (MOFs) offer a variety of possibilities for gas separation due to their large surface areas and tailored chemical and physical structures. In this work, the separation of CF 4 /CH 4 , CF 4 /N 2 , and CF 4 / CH 4 /N 2 in a subset of MOFs, double-linker MOFs (DL-MOFs), is investigated by using molecular simulations and machine learning (ML) methods. Among ∼500 MOFs, the best MOFs for adsorption-based CF 4 /CH 4 , CF 4 /N 2 , and CF 4 /CH 4 /N 2 separation are determined by considering the adsorption selectivity, working capacity, and regenerability. The ML models developed for adsorption-based CF 4 /CH 4 , CF 4 /N 2 , and CF 4 /CH 4 /N 2 separation have revealed that only one or two features (Henry's constant and/or surface area) are sufficient to establish models that can make accurate predictions of gas uptake. The membrane-based CF 4 /CH 4 and CF 4 /N 2 separation performances of DL-MOFs have also been studied, and it was found that inverse selective MOFs preferring CH 4 or N 2 over CF 4 can exist. Overall, this study will open avenues for the design and development of novel MOF adsorbents and membranes for the separation of CF 4 from CH 4 and N 2 by providing atomistic insights into the adsorption and diffusion properties of DL-MOFs.

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“…MOFs, in particular, are highly versatile materials with well-defined structures, uniform pore sizes, and tunability, making them suitable for gas separation and capture. − However, the rapid and precise discovery of a specific functional MOF, particularly for Rn capture, from the vast pool of millions of candidates remains a formidable challenge. Very recently, high-throughput screening has emerged as a powerful strategy to tackle this. − Within this framework, researchers employ grand-canonical Monte Carlo (GCMC) simulations , or data mining approaches that leverage GCMC-generated data in conjunction with machine learning algorithms to explore the vast realm of big data . Subsequently, candidates identified through theoretical screening undergo further optimization and rigorous experimental validation to confirm their performance. , However, despite these efforts, many virtual screening results often fall short when faced with real-world application scenarios, primarily due to the excessively idealized modeling processes employed during screening.…”

Section: Introductionmentioning

confidence: 99%

Water Unexpectedly Impacts Both Thermodynamics and Kinetics of Rn Removal in HKUST-1

Geng,

Mao,

et al. 2023

J. Phys. Chem. C

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Excessive radon (Rn) exposure remains a significant risk factor for lung cancer in the general population. Metal–organic frameworks (MOFs) have emerged as promising materials for Rn radiation protection due to their unique characteristics, including large surface areas and customizable porous structures. However, the presence of water molecules, both during the synthesis process and in humid air, has often been overlooked but can significantly impact the Rn adsorption performance of MOFs in practical applications. In this study, we conducted a comprehensive investigation into the influence of varying water contents on the Rn selectivity and Rn adsorption capacity of HKUST-1, a prospective candidate. Our findings revealed that the primary Rn capture site within HKUST-1 is a tetrahedral cage (SCage) with a diameter of approximately 5.4 Å, which is ideally suited for accommodating Rn. Interestingly, increasing water content enhances the Rn adsorption capacity and selectivity of HKUST-1, primarily due to thermodynamic advantages. However, fully coordinated water molecules can give rise to additional narrow pore apertures (∼3.7 Å), resulting in a high kinetic barrier (∼16.8 kcal/mol) that hampers Rn adsorption by SCage. Consequently, water molecules play a crucial role in regulating the delicate balance between thermodynamics and kinetics in Rn adsorption by modifying the pore aperture morphology of the adsorption site within HKUST-1. Our theoretical calculations predict the optimal range of water content in HKUST-1 for efficient Rn removal, spanning from 0 wt % (fully dehydrated) to 8 wt % (fully coordinated). These findings not only provide theoretical explanations and guidance for future experimental endeavors but also offer valuable insights and references into the role of water molecules in modulating gas separation within MOFs containing open metal sites under different humidity or activation levels.

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High-throughput virtual screening of metal–organic frameworks for xenon recovery from exhaled anesthetic gas mixture

Cited by 19 publications

References 46 publications

Metal-organic frameworks as photocatalysts in energetic and environmental applications

Metal-organic frameworks as photocatalysts in energetic and environmental applications

Simulation and Machine Learning-Integrated Investigation of Double-Linker MOFs for the Separation of CF₄ from CH₄ and N₂

Water Unexpectedly Impacts Both Thermodynamics and Kinetics of Rn Removal in HKUST-1

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High-throughput virtual screening of metal–organic frameworks for xenon recovery from exhaled anesthetic gas mixture

Cited by 19 publications

References 46 publications

Metal-organic frameworks as photocatalysts in energetic and environmental applications

Metal-organic frameworks as photocatalysts in energetic and environmental applications

Simulation and Machine Learning-Integrated Investigation of Double-Linker MOFs for the Separation of CF4 from CH4 and N2

Water Unexpectedly Impacts Both Thermodynamics and Kinetics of Rn Removal in HKUST-1

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Simulation and Machine Learning-Integrated Investigation of Double-Linker MOFs for the Separation of CF₄ from CH₄ and N₂