Classical density functional theory as a fast and accurate method for adsorption property prediction of porous materials

IF 3.5 3区 工程技术 Q2 ENGINEERING, CHEMICAL AIChE Journal Pub Date : 2025-02-21 DOI:10.1002/aic.18779
Vincent Dufour-Décieux, Philipp Rehner, Johannes Schilling, Elias Moubarak, Joachim Gross, André Bardow
{"title":"Classical density functional theory as a fast and accurate method for adsorption property prediction of porous materials","authors":"Vincent Dufour-Décieux, Philipp Rehner, Johannes Schilling, Elias Moubarak, Joachim Gross, André Bardow","doi":"10.1002/aic.18779","DOIUrl":null,"url":null,"abstract":"Physical adsorption is crucial in many industrial processes, prompting researchers to develop new materials for energy-efficient processes. Porous adsorbents are particularly promising due to their design flexibility, and computational screening has accelerated the search for optimal materials. Recently, classical density functional theory (cDFT) has emerged as a faster screening alternative to state-of-the-art computational methods. However, its predictions have not been extensively validated, especially for materials involving strong Coulombic interactions. This article validates cDFT by calculating adsorption properties for over 500 Metal-Organic Frameworks with three adsorbates <span data-altimg=\"/cms/asset/2b4ac214-7081-4b58-89b7-95daa2eeb1ba/aic18779-math-0001.png\"></span><mjx-container ctxtmenu_counter=\"24\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"><mjx-math aria-hidden=\"true\" location=\"graphic/aic18779-math-0001.png\"><mjx-semantics><mjx-mrow data-semantic-children=\"0,3\" data-semantic-content=\"0\" data-semantic- data-semantic-role=\"startpunct\" data-semantic-speech=\"left parenthesis CH Subscript 4 Baseline\" data-semantic-type=\"punctuated\"><mjx-mo data-semantic- data-semantic-operator=\"punctuated\" data-semantic-parent=\"4\" data-semantic-role=\"openfence\" data-semantic-type=\"punctuation\" style=\"margin-left: 0.056em; margin-right: 0.056em;\"><mjx-c></mjx-c></mjx-mo><mjx-msub data-semantic-children=\"1,2\" data-semantic- data-semantic-parent=\"4\" data-semantic-role=\"unknown\" data-semantic-type=\"subscript\"><mjx-mrow><mjx-mtext data-semantic-annotation=\"clearspeak:unit\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"3\" data-semantic-role=\"unknown\" data-semantic-type=\"text\"><mjx-c></mjx-c><mjx-c></mjx-c></mjx-mtext></mjx-mrow><mjx-script style=\"vertical-align: -0.15em;\"><mjx-mrow size=\"s\"><mjx-mn data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"3\" data-semantic-role=\"integer\" data-semantic-type=\"number\"><mjx-c></mjx-c></mjx-mn></mjx-mrow></mjx-script></mjx-msub></mjx-mrow></mjx-semantics></mjx-math><mjx-assistive-mml display=\"inline\" unselectable=\"on\"><math altimg=\"urn:x-wiley:00011541:media:aic18779:aic18779-math-0001\" display=\"inline\" location=\"graphic/aic18779-math-0001.png\" overflow=\"scroll\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><semantics><mrow data-semantic-=\"\" data-semantic-children=\"0,3\" data-semantic-content=\"0\" data-semantic-role=\"startpunct\" data-semantic-speech=\"left parenthesis CH Subscript 4 Baseline\" data-semantic-type=\"punctuated\"><mo data-semantic-=\"\" data-semantic-operator=\"punctuated\" data-semantic-parent=\"4\" data-semantic-role=\"openfence\" data-semantic-type=\"punctuation\" stretchy=\"false\">(</mo><msub data-semantic-=\"\" data-semantic-children=\"1,2\" data-semantic-parent=\"4\" data-semantic-role=\"unknown\" data-semantic-type=\"subscript\"><mrow><mtext data-semantic-=\"\" data-semantic-annotation=\"clearspeak:unit\" data-semantic-font=\"normal\" data-semantic-parent=\"3\" data-semantic-role=\"unknown\" data-semantic-type=\"text\">CH</mtext></mrow><mrow><mn data-semantic-=\"\" data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic-parent=\"3\" data-semantic-role=\"integer\" data-semantic-type=\"number\">4</mn></mrow></msub></mrow>$$ \\Big({\\mathrm{CH}}_4 $$</annotation></semantics></math></mjx-assistive-mml></mjx-container>, <span data-altimg=\"/cms/asset/846a7570-b292-4b44-9043-ea40c8d39788/aic18779-math-0002.png\"></span><mjx-container ctxtmenu_counter=\"25\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"><mjx-math aria-hidden=\"true\" location=\"graphic/aic18779-math-0002.png\"><mjx-semantics><mjx-mrow><mjx-msub data-semantic-children=\"0,1\" data-semantic- data-semantic-role=\"latinletter\" data-semantic-speech=\"upper N Subscript 2\" data-semantic-type=\"subscript\"><mjx-mrow><mjx-mtext data-semantic-annotation=\"clearspeak:unit\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"2\" data-semantic-role=\"latinletter\" data-semantic-type=\"text\"><mjx-c></mjx-c></mjx-mtext></mjx-mrow><mjx-script style=\"vertical-align: -0.15em;\"><mjx-mrow size=\"s\"><mjx-mn data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"2\" data-semantic-role=\"integer\" data-semantic-type=\"number\"><mjx-c></mjx-c></mjx-mn></mjx-mrow></mjx-script></mjx-msub></mjx-mrow></mjx-semantics></mjx-math><mjx-assistive-mml display=\"inline\" unselectable=\"on\"><math altimg=\"urn:x-wiley:00011541:media:aic18779:aic18779-math-0002\" display=\"inline\" location=\"graphic/aic18779-math-0002.png\" overflow=\"scroll\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><semantics><mrow><msub data-semantic-=\"\" data-semantic-children=\"0,1\" data-semantic-role=\"latinletter\" data-semantic-speech=\"upper N Subscript 2\" data-semantic-type=\"subscript\"><mrow><mtext data-semantic-=\"\" data-semantic-annotation=\"clearspeak:unit\" data-semantic-font=\"normal\" data-semantic-parent=\"2\" data-semantic-role=\"latinletter\" data-semantic-type=\"text\">N</mtext></mrow><mrow><mn data-semantic-=\"\" data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic-parent=\"2\" data-semantic-role=\"integer\" data-semantic-type=\"number\">2</mn></mrow></msub></mrow>$$ {\\mathrm{N}}_2 $$</annotation></semantics></math></mjx-assistive-mml></mjx-container>, <span data-altimg=\"/cms/asset/5256fe54-9950-4147-ba70-93dcf48e820e/aic18779-math-0003.png\"></span><mjx-container ctxtmenu_counter=\"26\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"><mjx-math aria-hidden=\"true\" location=\"graphic/aic18779-math-0003.png\"><mjx-semantics><mjx-mrow data-semantic-children=\"2,3\" data-semantic-content=\"3\" data-semantic- data-semantic-role=\"endpunct\" data-semantic-speech=\"CO Subscript 2 Baseline right parenthesis\" data-semantic-type=\"punctuated\"><mjx-msub data-semantic-children=\"0,1\" data-semantic- data-semantic-parent=\"4\" data-semantic-role=\"unknown\" data-semantic-type=\"subscript\"><mjx-mrow><mjx-mtext data-semantic-annotation=\"clearspeak:unit\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"2\" data-semantic-role=\"unknown\" data-semantic-type=\"text\"><mjx-c></mjx-c><mjx-c></mjx-c></mjx-mtext></mjx-mrow><mjx-script style=\"vertical-align: -0.15em;\"><mjx-mrow size=\"s\"><mjx-mn data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"2\" data-semantic-role=\"integer\" data-semantic-type=\"number\"><mjx-c></mjx-c></mjx-mn></mjx-mrow></mjx-script></mjx-msub><mjx-mo data-semantic- data-semantic-operator=\"punctuated\" data-semantic-parent=\"4\" data-semantic-role=\"closefence\" data-semantic-type=\"punctuation\" style=\"margin-left: 0.056em; margin-right: 0.056em;\"><mjx-c></mjx-c></mjx-mo></mjx-mrow></mjx-semantics></mjx-math><mjx-assistive-mml display=\"inline\" unselectable=\"on\"><math altimg=\"urn:x-wiley:00011541:media:aic18779:aic18779-math-0003\" display=\"inline\" location=\"graphic/aic18779-math-0003.png\" overflow=\"scroll\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><semantics><mrow data-semantic-=\"\" data-semantic-children=\"2,3\" data-semantic-content=\"3\" data-semantic-role=\"endpunct\" data-semantic-speech=\"CO Subscript 2 Baseline right parenthesis\" data-semantic-type=\"punctuated\"><msub data-semantic-=\"\" data-semantic-children=\"0,1\" data-semantic-parent=\"4\" data-semantic-role=\"unknown\" data-semantic-type=\"subscript\"><mrow><mtext data-semantic-=\"\" data-semantic-annotation=\"clearspeak:unit\" data-semantic-font=\"normal\" data-semantic-parent=\"2\" data-semantic-role=\"unknown\" data-semantic-type=\"text\">CO</mtext></mrow><mrow><mn data-semantic-=\"\" data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic-parent=\"2\" data-semantic-role=\"integer\" data-semantic-type=\"number\">2</mn></mrow></msub><mo data-semantic-=\"\" data-semantic-operator=\"punctuated\" data-semantic-parent=\"4\" data-semantic-role=\"closefence\" data-semantic-type=\"punctuation\" stretchy=\"false\">)</mo></mrow>$$ {\\mathrm{CO}}_2\\Big) $$</annotation></semantics></math></mjx-assistive-mml></mjx-container> and comparing them to results from Grand Canonical Monte Carlo (GCMC) simulations. For <span data-altimg=\"/cms/asset/b375642d-78ef-451c-b8c6-5be72dafd446/aic18779-math-0004.png\"></span><mjx-container ctxtmenu_counter=\"27\" ctxtmenu_oldtabindex=\"1\" jax=\"CHTML\" role=\"application\" sre-explorer- style=\"font-size: 103%; position: relative;\" tabindex=\"0\"><mjx-math aria-hidden=\"true\" location=\"graphic/aic18779-math-0004.png\"><mjx-semantics><mjx-mrow><mjx-msub data-semantic-children=\"0,1\" data-semantic- data-semantic-role=\"unknown\" data-semantic-speech=\"CO Subscript 2\" data-semantic-type=\"subscript\"><mjx-mrow><mjx-mtext data-semantic-annotation=\"clearspeak:unit\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"2\" data-semantic-role=\"unknown\" data-semantic-type=\"text\"><mjx-c></mjx-c><mjx-c></mjx-c></mjx-mtext></mjx-mrow><mjx-script style=\"vertical-align: -0.15em;\"><mjx-mrow size=\"s\"><mjx-mn data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic- data-semantic-parent=\"2\" data-semantic-role=\"integer\" data-semantic-type=\"number\"><mjx-c></mjx-c></mjx-mn></mjx-mrow></mjx-script></mjx-msub></mjx-mrow></mjx-semantics></mjx-math><mjx-assistive-mml display=\"inline\" unselectable=\"on\"><math altimg=\"urn:x-wiley:00011541:media:aic18779:aic18779-math-0004\" display=\"inline\" location=\"graphic/aic18779-math-0004.png\" overflow=\"scroll\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><semantics><mrow><msub data-semantic-=\"\" data-semantic-children=\"0,1\" data-semantic-role=\"unknown\" data-semantic-speech=\"CO Subscript 2\" data-semantic-type=\"subscript\"><mrow><mtext data-semantic-=\"\" data-semantic-annotation=\"clearspeak:unit\" data-semantic-font=\"normal\" data-semantic-parent=\"2\" data-semantic-role=\"unknown\" data-semantic-type=\"text\">CO</mtext></mrow><mrow><mn data-semantic-=\"\" data-semantic-annotation=\"clearspeak:simple\" data-semantic-font=\"normal\" data-semantic-parent=\"2\" data-semantic-role=\"integer\" data-semantic-type=\"number\">2</mn></mrow></msub></mrow>$$ {\\mathrm{CO}}_2 $$</annotation></semantics></math></mjx-assistive-mml></mjx-container>, accounting for Coulombic interactions is crucial for accurate predictions. Our findings show that cDFT closely replicates GCMC results while reducing computation time to a median of six minutes per material, making it a strong candidate for estimating adsorption properties in porous materials.","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":"62 1","pages":""},"PeriodicalIF":3.5000,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AIChE Journal","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1002/aic.18779","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
引用次数: 0

Abstract

Physical adsorption is crucial in many industrial processes, prompting researchers to develop new materials for energy-efficient processes. Porous adsorbents are particularly promising due to their design flexibility, and computational screening has accelerated the search for optimal materials. Recently, classical density functional theory (cDFT) has emerged as a faster screening alternative to state-of-the-art computational methods. However, its predictions have not been extensively validated, especially for materials involving strong Coulombic interactions. This article validates cDFT by calculating adsorption properties for over 500 Metal-Organic Frameworks with three adsorbates (CH4$$ \Big({\mathrm{CH}}_4 $$, N2$$ {\mathrm{N}}_2 $$, CO2)$$ {\mathrm{CO}}_2\Big) $$ and comparing them to results from Grand Canonical Monte Carlo (GCMC) simulations. For CO2$$ {\mathrm{CO}}_2 $$, accounting for Coulombic interactions is crucial for accurate predictions. Our findings show that cDFT closely replicates GCMC results while reducing computation time to a median of six minutes per material, making it a strong candidate for estimating adsorption properties in porous materials.
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AIChE Journal
AIChE Journal 工程技术-工程:化工
CiteScore
7.10
自引率
10.80%
发文量
411
审稿时长
3.6 months
期刊介绍: The AIChE Journal is the premier research monthly in chemical engineering and related fields. This peer-reviewed and broad-based journal reports on the most important and latest technological advances in core areas of chemical engineering as well as in other relevant engineering disciplines. To keep abreast with the progressive outlook of the profession, the Journal has been expanding the scope of its editorial contents to include such fast developing areas as biotechnology, electrochemical engineering, and environmental engineering. The AIChE Journal is indeed the global communications vehicle for the world-renowned researchers to exchange top-notch research findings with one another. Subscribing to the AIChE Journal is like having immediate access to nine topical journals in the field. Articles are categorized according to the following topical areas: Biomolecular Engineering, Bioengineering, Biochemicals, Biofuels, and Food Inorganic Materials: Synthesis and Processing Particle Technology and Fluidization Process Systems Engineering Reaction Engineering, Kinetics and Catalysis Separations: Materials, Devices and Processes Soft Materials: Synthesis, Processing and Products Thermodynamics and Molecular-Scale Phenomena Transport Phenomena and Fluid Mechanics.
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