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Title: What Are the Best Materials To Separate a Xenon/Krypton Mixture?

Abstract

Accelerating progress in the discovery and deployment of advanced nanoporous materials relies on chemical insight and structure property relationships for rational design. Because of the complexity of this problem, trial-and-error is heavily involved in the laboratory today. A cost-effective route to aid experimental materials discovery is to construct structure models of nanoporous materials in silico and use molecular simulations to rapidly test them and elucidate data-driven guidelines for rational design. For example, highly-tunable nanoporous materials have shown promise as adsorbents for separating an industrially relevant gaseous mixture of xenon and krypton. Here in this work, we characterize, screen, and analyze the Nanoporous Materials Genome, a database of ca. 670,000 porous material structures, for candidate adsorbents for xenon/krypton separations. For over half a million structures, the computational resources required for a brute-force screening using grand-canonical Monte Carlo simulations of Xe/Kr adsorption are prohibitive. To overcome the computational cost, we used a hybrid approach combining machine learning algorithms (random forests) with molecular simulations. We compared the results from our large-scale screening with simple pore models to rationalize the strong link between pore size and selectivity. With this insight, we then analyzed the anatomy of the binding sites of the most selective materials.more » These binding sites can be constructed from tubes, pockets, rings, or cages and are often composed of non-discrete chemical fragments. The complexity of these binding sites emphasizes the importance of high-throughput computational screenings to discover new materials. Interestingly, our screening study predicts that the two most selective materials in the database are an aluminophosphate zeolite analogue and a calcium based coordination network, both of which have already been synthesized but not yet tested for Xe/Kr separations.« less

Authors:
 [1];  [2];  [3];  [1];  [4]
+ Show Author Affiliations
  1. Univ. of California, Berkeley, CA (United States). Dept. of Chemical and Biomolecular Engineering
  2. Univ. of California, Berkeley, CA (United States). Dept. of Chemistry
  3. Univ. of California, Berkeley, CA (United States). Dept. of Chemical and Biomolecular Engineering; Norwegian Univ. of Science and Technology, Trondheim (Norway)
  4. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Scientific Computing Group
Publication Date:
Research Org.:
Univ. of Minnesota, Minneapolis, MN (United States). Nanoporous Materials Genome Center; Energy Frontier Research Centers (EFRC) (United States). Center for Gas Separations Relevant to Clean Energy Technologies (CGS)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES)
Contributing Org.:
National Energy Research Scientific Computing Center
OSTI Identifier:
1474401
Grant/Contract Number:  
FG02-12ER16362; SC0008688
Resource Type:
Accepted Manuscript
Journal Name:
Chemistry of Materials
Additional Journal Information:
Journal Volume: 27; Journal Issue: 12; Journal ID: ISSN 0897-4756
Publisher:
American Chemical Society (ACS)
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY

Citation Formats

Simon, Cory M., Mercado, Rocio, Schnell, Sondre K., Smit, Berend, and Haranczyk, Maciej. What Are the Best Materials To Separate a Xenon/Krypton Mixture?. United States: N. p., 2015. Web. doi:10.1021/acs.chemmater.5b01475.
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Simon, Cory M., Mercado, Rocio, Schnell, Sondre K., Smit, Berend, & Haranczyk, Maciej. What Are the Best Materials To Separate a Xenon/Krypton Mixture?. United States. https://doi.org/10.1021/acs.chemmater.5b01475
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Simon, Cory M., Mercado, Rocio, Schnell, Sondre K., Smit, Berend, and Haranczyk, Maciej. Tue . "What Are the Best Materials To Separate a Xenon/Krypton Mixture?". United States. https://doi.org/10.1021/acs.chemmater.5b01475. https://www.osti.gov/servlets/purl/1474401.
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@article{osti_1474401,
title = {What Are the Best Materials To Separate a Xenon/Krypton Mixture?},
author = {Simon, Cory M. and Mercado, Rocio and Schnell, Sondre K. and Smit, Berend and Haranczyk, Maciej},
abstractNote = {Accelerating progress in the discovery and deployment of advanced nanoporous materials relies on chemical insight and structure property relationships for rational design. Because of the complexity of this problem, trial-and-error is heavily involved in the laboratory today. A cost-effective route to aid experimental materials discovery is to construct structure models of nanoporous materials in silico and use molecular simulations to rapidly test them and elucidate data-driven guidelines for rational design. For example, highly-tunable nanoporous materials have shown promise as adsorbents for separating an industrially relevant gaseous mixture of xenon and krypton. Here in this work, we characterize, screen, and analyze the Nanoporous Materials Genome, a database of ca. 670,000 porous material structures, for candidate adsorbents for xenon/krypton separations. For over half a million structures, the computational resources required for a brute-force screening using grand-canonical Monte Carlo simulations of Xe/Kr adsorption are prohibitive. To overcome the computational cost, we used a hybrid approach combining machine learning algorithms (random forests) with molecular simulations. We compared the results from our large-scale screening with simple pore models to rationalize the strong link between pore size and selectivity. With this insight, we then analyzed the anatomy of the binding sites of the most selective materials. These binding sites can be constructed from tubes, pockets, rings, or cages and are often composed of non-discrete chemical fragments. The complexity of these binding sites emphasizes the importance of high-throughput computational screenings to discover new materials. Interestingly, our screening study predicts that the two most selective materials in the database are an aluminophosphate zeolite analogue and a calcium based coordination network, both of which have already been synthesized but not yet tested for Xe/Kr separations.},
doi = {10.1021/acs.chemmater.5b01475},
journal = {Chemistry of Materials},
number = 12,
volume = 27,
place = {United States},
year = {Tue Jun 09 00:00:00 EDT 2015},
month = {Tue Jun 09 00:00:00 EDT 2015}
}
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    Metal–organic framework derived nanoporous carbons with highly selective adsorption and separation of xenon
    journal, January 2018

    • Gong, Youjin; Tang, Yuanming; Mao, Zhenghao
    • Journal of Materials Chemistry A, Vol. 6, Issue 28
    • DOI: 10.1039/c8ta02091d

    In silico discovery of metal-organic frameworks for precombustion CO 2 capture using a genetic algorithm
    journal, October 2016

    • Chung, Yongchul G.; Gómez-Gualdrón, Diego A.; Li, Peng
    • Science Advances, Vol. 2, Issue 10
    • DOI: 10.1126/sciadv.1600909

    Porous organic materials with ultra-small pores and sulfonic functionality for xenon capture with exceptional selectivity
    journal, January 2018

    • Li, Jialu; Huang, Ling; Zou, Xiaoqin
    • Journal of Materials Chemistry A, Vol. 6, Issue 24
    • DOI: 10.1039/c8ta03991g

    Fast screening of porous materials for noble gas adsorption and separation: a classical density functional approach
    journal, January 2018

    • Guo, Fangyuan; Liu, Yu; Hu, Jun
    • Physical Chemistry Chemical Physics, Vol. 20, Issue 44
    • DOI: 10.1039/c8cp03777a

    Neon-Bearing Ammonium Metal Formates: Formation and Behaviour under Pressure
    journal, September 2016

    Cutting the cost of carbon capture: a case for carbon capture and utilization
    journal, January 2016

    • Joos, Lennart; Huck, Johanna M.; Van Speybroeck, Veronique
    • Faraday Discuss., Vol. 192
    • DOI: 10.1039/c6fd00031b

    Hybrid Ultra-Microporous Materials for Selective Xenon Adsorption and Separation
    journal, May 2016

    • Mohamed, Mona H.; Elsaidi, Sameh K.; Pham, Tony
    • Angewandte Chemie, Vol. 128, Issue 29
    • DOI: 10.1002/ange.201602287

    Hybrid Ultra-Microporous Materials for Selective Xenon Adsorption and Separation
    journal, May 2016

    • Mohamed, Mona H.; Elsaidi, Sameh K.; Pham, Tony
    • Angewandte Chemie International Edition, Vol. 55, Issue 29
    • DOI: 10.1002/anie.201602287

    A new approach for the prediction of partition functions using machine learning techniques
    journal, July 2018

    • Desgranges, Caroline; Delhommelle, Jerome
    • The Journal of Chemical Physics, Vol. 149, Issue 4
    • DOI: 10.1063/1.5037098

    Predicting defect behavior in B2 intermetallics by merging ab initio modeling and machine learning
    journal, December 2016

    A nanosized metal–organic framework with small pores for kinetic xenon separation
    journal, January 2018

    • Yu, Guangli; Liu, Yueqiao; Zou, Xiaoqin
    • Journal of Materials Chemistry A, Vol. 6, Issue 25
    • DOI: 10.1039/c8ta03509a

    A microporous metal–organic framework with commensurate adsorption and highly selective separation of xenon
    journal, January 2018

    • Xiong, Shunshun; Gong, Youjin; Hu, Shuanglin
    • Journal of Materials Chemistry A, Vol. 6, Issue 11
    • DOI: 10.1039/c7ta11321h

    Metal–organic framework with optimally selective xenon adsorption and separation
    journal, June 2016

    • Banerjee, Debasis; Simon, Cory M.; Plonka, Anna M.
    • Nature Communications, Vol. 7, Issue 1
    • DOI: 10.1038/ncomms11831

    Deep neural network learning of complex binary sorption equilibria from molecular simulation data
    journal, January 2019

    • Sun, Yangzesheng; DeJaco, Robert F.; Siepmann, J. Ilja
    • Chemical Science, Vol. 10, Issue 16
    • DOI: 10.1039/c8sc05340e

    XRD-DSC: a screening tool for identifying effective MOFs for selective gas sorption from humid gas streams
    journal, February 2019

    An In-Situ Neutron Diffraction and DFT Study of Hydrogen Adsorption in a Sodalite-Type Metal-Organic Framework, Cu-BTTri : An
    journal, January 2019

    • Asgari, Mehrdad; Semino, Rocio; Schouwink, Pascal
    • European Journal of Inorganic Chemistry, Vol. 2019, Issue 8
    • DOI: 10.1002/ejic.201801253

    Molecular modelling and machine learning for high-throughput screening of metal-organic frameworks for hydrogen storage
    journal, April 2019

    High-throughput computational screening of nanoporous adsorbents for CO 2 capture from natural gas
    journal, January 2016

    • Braun, Efrem; Zurhelle, Alexander F.; Thijssen, Wouter
    • Molecular Systems Design & Engineering, Vol. 1, Issue 2
    • DOI: 10.1039/c6me00043f

    Distinguishing Metal–Organic Frameworks
    journal, January 2018

    • Barthel, Senja; Alexandrov, Eugeny V.; Proserpio, Davide M.
    • Crystal Growth & Design, Vol. 18, Issue 3
    • DOI: 10.1021/acs.cgd.7b01663

    High-Throughput Screening Approach for Nanoporous Materials Genome Using Topological Data Analysis: Application to Zeolites
    journal, June 2018

    • Lee, Yongjin; Barthel, Senja D.; Dłotko, Paweł
    • Journal of Chemical Theory and Computation, Vol. 14, Issue 8
    • DOI: 10.1021/acs.jctc.8b00253

    Eigencages: Learning a Latent Space of Porous Cage Molecules
    journal, December 2018

    The Influence of Intrinsic Framework Flexibility on Adsorption in Nanoporous Materials
    journal, April 2017

    • Witman, Matthew; Ling, Sanliang; Jawahery, Sudi
    • Journal of the American Chemical Society, Vol. 139, Issue 15
    • DOI: 10.1021/jacs.7b01688

    Metal Substitution as the Method of Modifying Electronic Structure of Metal–Organic Frameworks
    journal, March 2019

    • Syzgantseva, Maria A.; Ireland, Christopher Patrick; Ebrahim, Fatmah Mish
    • Journal of the American Chemical Society, Vol. 141, Issue 15
    • DOI: 10.1021/jacs.8b13667

    Excavating hidden adsorption sites in metal-organic frameworks using rational defect engineering
    journal, November 2017

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