Výsledky vyhledávání - "Randall Q, Snurr"

Akademický článek

Rapid design of top-performing metal-organic frameworks with qualitative representations of building blocks

Autor: Yigitcan Comlek, Thang Duc Pham, Randall Q. Snurr, Wei Chen

Publikováno v: npj Computational Materials, Vol 9, Iss 1, Pp 1-14 (2023)

Abstract Data-driven materials design often encounters challenges where systems possess qualitative (categorical) information. Specifically, representing Metal-organic frameworks (MOFs) through different building blocks poses a challenge for designer

Externí odkaz: https://doaj.org/article/8b1ab520a4d3453a8775fcacaba5f94c

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Akademický článek

Regulating adsorption performance of zeolites by pre-activation in electric fields

Autor: Kaifei Chen, Zhi Yu, Seyed Hesam Mousavi, Ranjeet Singh, Qinfen Gu, Randall Q. Snurr, Paul A. Webley, Gang Kevin Li

Publikováno v: Nature Communications, Vol 14, Iss 1, Pp 1-11 (2023)

Abstract While multiple external stimuli (e.g., temperature, light, pressure) have been reported to regulate gas adsorption, limited studies have been conducted on controlling molecular admission in nanopores through the application of electric field

Externí odkaz: https://doaj.org/article/b8b02e875ce542dca4b3b114807a5b66

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Akademický článek

Computational investigation of hysteresis and phase equilibria of n-alkanes in a metal-organic framework with both micropores and mesopores

Autor: Zhao Li, Jake Turner, Randall Q. Snurr

Publikováno v: Communications Chemistry, Vol 6, Iss 1, Pp 1-12 (2023)

Abstract Adsorption hysteresis is a phenomenon related to phase transitions that can impact applications such as gas storage and separations in porous materials. Computational approaches can greatly facilitate the understanding of phase transitions a

Externí odkaz: https://doaj.org/article/3bb2b3cabcba43ca93e7aa26c0e43016

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Akademický článek

High-throughput predictions of metal–organic framework electronic properties: theoretical challenges, graph neural networks, and data exploration

Autor: Andrew S. Rosen, Victor Fung, Patrick Huck, Cody T. O’Donnell, Matthew K. Horton, Donald G. Truhlar, Kristin A. Persson, Justin M. Notestein, Randall Q. Snurr

Publikováno v: npj Computational Materials, Vol 8, Iss 1, Pp 1-10 (2022)

Abstract With the goal of accelerating the design and discovery of metal–organic frameworks (MOFs) for electronic, optoelectronic, and energy storage applications, we present a dataset of predicted electronic structure properties for thousands of M

Externí odkaz: https://doaj.org/article/e0c539f7b8f34ab1bf3579bc903a0157

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