Evidence map›Paper›PMID 41641873›Full record

ArticleThe journal of physical chemistry. B2026

Efficient Prediction of Multicomponent Adsorption Isotherms and Enthalpies of Adsorption in MOFs Using Classical Density Functional Theory.

Nadine Thiele, Tiong Wei Teh, Benjamin Bursik, Marcel Granderath, Gernot Bauer, Vincent Dufour-Décieux, Philipp Rehner, Rolf Stierle, André Bardow, Niels Hansen and 1 more

Abstract read
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In one paragraph

Article in The journal of physical chemistry. B, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Nadine ThieleInstitute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany.
Tiong Wei TehInstitute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany.ORCID 0009-0005-5218-2277
Benjamin BursikInstitute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany.ORCID 0000-0003-2337-7014
Marcel GranderathEnergy & Process Systems Engineering, Department of Mechanical and Process Engineering, ETH Zurich, Tannenstrasse 3, 8092 Zurich, Switzerland.ORCID 0009-0008-1846-4424
Gernot BauerInstitute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany.ORCID 0000-0002-5211-5358
Vincent Dufour-DécieuxEnergy & Process Systems Engineering, Department of Mechanical and Process Engineering, ETH Zurich, Tannenstrasse 3, 8092 Zurich, Switzerland.ORCID 0000-0001-9654-4923
Philipp RehnerEnergy & Process Systems Engineering, Department of Mechanical and Process Engineering, ETH Zurich, Tannenstrasse 3, 8092 Zurich, Switzerland.ORCID 0000-0001-9750-5037
Rolf StierleInstitute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany.ORCID 0000-0001-7475-7207
André BardowEnergy & Process Systems Engineering, Department of Mechanical and Process Engineering, ETH Zurich, Tannenstrasse 3, 8092 Zurich, Switzerland.ORCID 0000-0002-3831-0691
Niels HansenInstitute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany.ORCID 0000-0003-4366-6120
Joachim GrossInstitute of Thermodynamics and Thermal Process Engineering, University of Stuttgart, Pfaffenwaldring 9, 70569 Stuttgart, Germany.ORCID 0000-0001-8632-357X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We demonstrate that classical density functional theory (DFT) based on the PC-SAFT equation of state is a fast, accurate, and predictive model to predict multicomponent adsorption in porous materials, which is an essential step toward the design of next-generation adsorbents for relevant applications. Using GPU acceleration, adsorption isotherms and adsorption enthalpies can be obtained in a matter of seconds, which is several orders of magnitude faster than grand canonical Monte Carlo (GCMC) simulations. Using metal-organic frameworks as adsorbents and non- or weakly polar molecules as adsorbates, we validate our approach by performing GCMC simulations for binary, ternary, and quaternary mixtures with practically relevant applications, such as noble gas separations (Kr/Xe, Ar/Kr/Xe), direct dry air capture (CO

Identifiers

PMID41641873
PMCPMC12926958

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.