Center for Molecular Modeling - R. Goeminne

Design of a Tunable, High-performance Mixed Matrix Membrane Platform for Gas Separations

mieke — Tue, 30 Sep 2025 14:03:08 +0000

T. Xiaoyu, S. Robijns, A. Lamaire, R. Goeminne, N. De Witte, M. Dickmann, R. Verbeke, T. Van der Donck, R. de Oliveira Silva, Q. Ke, Y. Li, I. Aslam, C. Van Goethem, T. Donckels, R. Helm, D. Sakellariou, T. Van Assche, V. Van Speybroeck, M. Dusselier, I. Vankelecom

Advanced Materials

37(34): 2502393

2025

DOI

http://dx.doi.org/10.1002/adma.202502393

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Advanced Materials - 2025 - Tan - Design of a Tunable High‐performance Mixed Matrix Membrane Platform for Gas Separations.pdf

Ab Initio Predictions of Adsorption in Flexible Metal–Organic Frameworks for Water Harvesting Applications

leen — Tue, 21 Jan 2025 08:36:58 +0000

R. Goeminne, V. Van Speybroeck

JACS (Journal of the American Chemical Society)

147, 4, 3615-3630

2025

Abstract

Metal–organic frameworks such as MOF-303 and MOF-LA2–1 have demonstrated exceptional performance for water harvesting applications. To enable a reticular design of such materials, an accurate prediction of the adsorption properties with chemical accuracy and fully accounting for the flexibility is crucial. The computational prediction of water adsorption properties in MOFs has become standard practice, but current methods lack the predictive power needed to design new materials. Limitations stem from the way the interatomic potential is described and the inadequate consideration of the framework flexibility. Herein, we showcase a methodology to obtain chemically accurate adsorption isotherms that fully account for framework flexibility. The method relies on very accurate and efficiently trained machine learning potentials and transition matrix Monte Carlo simulations to account for framework flexibility. For MOF-303, quantitatively accurate adsorption isotherms are obtained, provided an accurately benchmarked electronic structure method is used to train the machine learning potential, and local and global framework flexibility is accounted for. The broader applicability is shown through the study of MOF-333 and MOF-LA2–1. Analysis of the water density profiles in the MOFs gives insight into the factors governing the shape and origin of the isotherm. An optimal water harvester should have initial seeding sites with intermediate adsorption strength to prevent detrimental low-pressure water uptake. To increase the working capacity, linker extension strategies can be used while maintaining the initial seeding sites, as was done in MOF-LA2–1. The methodology can be applied to other guest molecules and MOFs, enabling the future design of MOFs with specific adsorption properties.

Gold Open Access

DOI

https://doi.org/10.1021/jacs.4c15287

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ab-initio-predictions-of-adsorption-in-flexible-metal-organic-frameworks-for-water.pdf

Computational Modeling of Reticular Materials: The Past, the Present, and the Future

leen — Tue, 21 Jan 2025 08:23:21 +0000

W. Temmerman, R. Goeminne, K. S. Rawat, V. Van Speybroeck

Advanced Materials

2024

Abstract

Reticular materials rely on a unique building concept where inorganic and organic building units are stitched together giving access to an almost limitless number of structured ordered porous materials. Given the versatility of chemical elements, underlying nets, and topologies, reticular materials provide a unique platform to design materials for timely technological applications. Reticular materials have now found their way in important societal applications, like carbon capture to address climate change, water harvesting to extract atmospheric moisture in arid environments, and clean energy applications. Combining predictions from computational materials chemistry with advanced experimental characterization and synthesis procedures unlocks a design strategy to synthesize new materials with the desired properties and functions. Within this review, the current status of modeling reticular materials is addressed and supplemented with topical examples highlighting the necessity of advanced molecular modeling to design materials for technological applications. This review is structured as a templated molecular modeling study starting from the molecular structure of a realistic material towards the prediction of properties and functions of the materials. At the end, the authors provide their perspective on the past, present of future in modeling reticular materials and formulate open challenges to inspire future model and method developments.

DOI

https://doi.org/10.1002/adma.202412005

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Computational Modeling of Reticular Materials.pdf

Water motifs in zirconium metal-organic frameworks induced by nanoconfinement and hydrophilic adsorption sites

sven — Tue, 19 Nov 2024 15:52:56 +0000

A. Lamaire, J. Wieme, S. Vandenhaute, R. Goeminne, S.M.J. Rogge, V. Van Speybroeck

Nature Communications

15, 9997

2024

Abstract

The intricate hydrogen-bonded network of water gives rise to various structures with anomalous properties at different thermodynamic conditions. Nanoconfinement can further modify the water structure and properties, and induce specific water motifs, which are instrumental for technological applications such as atmospheric water harvesting. However, so far, a causal relationship between nanoconfinement and the presence of specific hydrophilic adsorption sites is lacking, hampering the further design of nanostructured materials for water templating. Therefore, this work investigates the organisation of water in zirconium-based metal-organic frameworks (MOFs) with varying topologies, pore sizes, and chemical composition, to extract design rules to shape water. The highly tuneable pores and hydrophilicity of MOFs makes them ideally suited for this purpose. We find that small nanopores favour orderly water clusters that nucleate at hydrophilic adsorption sites. Favourably positioning the secondary adsorption sites, hydrogen-bonded to the primary adsorption sites, allows larger clusters to form at moderate adsorption conditions. To disentangle the importance of nanoconfinement and hydrophilic nucleation sites in this process, we introduce an analytical model with precise control of the adsorption sites. This sheds a new light on design parameters to induce specific water clusters and hydrogen-bonded networks, thus rationalising the application space of water in nanoconfinement.

Gold Open Access

DOI

http://dx.doi.org/10.1038/s41467-024-54358-z

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Reaching quantum accuracy in predicting adsorption properties for ethane/ethene in ZIF-8 at the low pressure regime

leen — Tue, 11 Jun 2024 12:18:41 +0000

S. Ravichandran, M. Najafi, R. Goeminne, J. F. M. Denayer, V. Van Speybroeck, L. Vanduyfhuys

Journal of Chemical Theory and Computation

20, 12, 5225-5240

2024

Abstract

Nanoporous materials in the form of metal−organicframeworks such as zeolitic imidazolate framework-8 (ZIF-8) arepromising membrane materials for the separation of hydrocarbonmixtures. To compute the adsorption isotherms in suchadsorbents, grand canonical Monte Carlo simulations have provento be very useful. The quality of these isotherms depends on theaccuracy of adsorbate−adsorbent interactions, which are mostlydescribed using force fields owing to their low computational cost.However, force field predictions of adsorption uptake often showdiscrepancies from experiments at low pressures, providing theneed for methods that are more accurate. Hence, in this work, wepropose and validate two novel methodologies for the ZIF-8/ethane and ethene systems; a benchmarking methodology toevaluate the performance of any given force field in describing adsorption in the low-pressure regime and a refinement procedure torescale the parameters of a force field to better describe the host−guest interactions and provide for simulation isotherms with closeagreement to experimental isotherms. Both methodologies were developed based on a reference Henry coefficient, computed withthe PBE-MBD functional using the importance sampling technique. The force field rankings predicted by the benchmarkingmethodology involve the comparison of force field derived Henry coefficients with the reference Henry coefficients and ranking theforce fields based on the disparities between these Henry coefficients. The ranking from this methodology matches the rankingsmade based on uptake disparities by comparing force field derived simulation isotherms to experimental isotherms in the low-pressure regime. The force field rescaling methodology was proven to refine even the worst performing force field in UFF/TraPPE.The uptake disparities of UFF/TraPPE improved from 197% and 194% to 11% and 21% for ethane and ethene, respectively. Theproposed methodology is applicable to predict adsorption across nanoporous materials and allows for rescaled force fields to reachquantum accuracy without the need for experimental input.

DOI

https://doi.org/10.1021/acs.jctc.4c00293

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ravichandran-et-al-2024-reaching-quantum-accuracy-in-predicting-adsorption-properties-for-ethane-ethene-in-zeolitic.pdf

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Gas adsorption and framework flexibility of CALF-20 explored via experiments and simulations

rgoeminne — Mon, 13 May 2024 09:07:26 +0000

R. Oktavian, R. Goeminne, L.T. Glasby, P. Song, R. Huynh, O. T. Qazvini, O. Ghaffari-Nik, N. Masoumifard, J. L. Cordiner, P. Hovington, V. Van Speybroeck, P. Z. Moghadam

Nature Communications

15, 3898

2024

Abstract

In 2021, Svante, in collaboration with BASF, reported successful scale up of CALF-20 production, a stable MOF with high capacity for post-combustion CO₂ capture which exhibits remarkable stability towards water. CALF-20’s success story in the MOF commercialisation space provides new thinking about appropriate structural and adsorptive metrics important for CO₂ capture. Here, we combine atomistic-level simulations with experiments to study adsorptive properties of CALF-20 and shed light on its flexible crystal structure. We compare measured and predicted CO₂ and water adsorption isotherms and explain the role of water-framework interactions and hydrogen bonding networks in CALF-20’s hydrophobic behaviour. Furthermore, regular and enhanced sampling molecular dynamics simulations are performed with both density-functional theory (DFT) and machine learning potentials (MLPs) trained to DFT energies and forces. From these simulations, the effects of adsorption-induced flexibility in CALF-20 are uncovered. We envisage this work would encourage development of other MOF materials useful for CO₂ capture applications in humid conditions.

Gold Open Access

DOI

https://doi.org/10.1038/s41467-024-48136-0

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s41467-024-48136-0.pdf

DFT-Quality Adsorption Simulations in Metal–Organic Frameworks Enabled by Machine Learning Potentials

rgoeminne — Thu, 31 Aug 2023 11:47:49 +0000

R. Goeminne, L. Vanduyfhuys, V. Van Speybroeck, T. Verstraelen

Journal of Chemical Theory and Computation (JCTC)

19, 18, 6313-6325

2023

Abstract

Nanoporous materials such as metal–organic frameworks (MOFs) have been extensively studied for their potential for adsorption and separation applications. In this respect, grand canonical Monte Carlo (GCMC) simulations have become a well-established tool for computational screenings of the adsorption properties of large sets of MOFs. However, their reliance on empirical force field potentials has limited the accuracy with which this tool can be applied to MOFs with challenging chemical environments such as open-metal sites. On the other hand, density-functional theory (DFT) is too computationally demanding to be routinely employed in GCMC simulations due to the excessive number of required function evaluations. Therefore, we propose in this paper a protocol for training machine learning potentials (MLPs) on a limited set of DFT intermolecular interaction energies (and forces) of CO₂ in ZIF-8 and the open-metal site containing Mg-MOF-74, and use the MLPs to derive adsorption isotherms from first principles. We make use of the equivariant NequIP model which has demonstrated excellent data efficiency, and as such an error on the interaction energies below 0.2 kJ mol^–1 per adsorbate in ZIF-8 was attained. Its use in GCMC simulations results in highly accurate adsorption isotherms and heats of adsorption. For Mg-MOF-74, a large dependence of the obtained results on the used dispersion correction was observed, where PBE-MBD performs the best. Lastly, to test the transferability of the MLP trained on ZIF-8, it was applied to ZIF-3, ZIF-4, and ZIF-6, which resulted in large deviations in the predicted adsorption isotherms and heats of adsorption. Only when explicitly training on data for all ZIFs, accurate adsorption properties were obtained. As the proposed methodology is widely applicable to guest adsorption in nanoporous materials, it opens up the possibility for training general-purpose MLPs to perform highly accurate investigations of guest adsorption.

DOI

http://dx.doi.org/10.1021/acs.jctc.3c00495

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Nuclear quantum effects on zeolite proton hopping kinetics explored with machine learning potentials and path integral molecular dynamics

massimo — Wed, 27 Jul 2022 12:51:36 +0000

M. Bocus, R. Goeminne, A. Lamaire, M. Cools-Ceuppens, T. Verstraelen, V. Van Speybroeck

Nature Communications

14, 1008

2023

Abstract

Proton hopping is a key reactive process within zeolite catalysis. However, the accurate determination of its kinetics poses major challenges both for theoreticians and experimentalists. Nuclear quantum effects (NQEs) are known to influence the structure and dynamics of protons, but their rigorous inclusion through the path integral molecular dynamics (PIMD) formalism was so far beyond reach for zeolite catalyzed processes due to the excessive computational cost of evaluating all forces and energies at the Density Functional Theory (DFT) level. Herein, we overcome this limitation by training first a reactive machine learning potential (MLP) that can reproduce with high fidelity the DFT potential energy surface of proton hopping around the first Al coordination sphere in the H-CHA zeolite. The MLP offers an immense computational speedup, enabling us to derive accurate reaction kinetics beyond standard transition state theory for the proton hopping reaction. Overall, more than 0.6 μs of simulation time was needed, which is far beyond reach of any standard DFT approach. NQEs are found to significantly impact the proton hopping kinetics up to ~473 K. Moreover, PIMD simulations with deuterium can be performed without any additional training to compute kinetic isotope effects over a broad range of temperatures.

Gold Open Access

DOI

https://doi.org/10.1038/s41467-023-36666-y

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2023_NatComm_v14_p1008.pdf

Accurately Determining the Phase Transition Temperature of CsPbI3 via Random-Phase Approximation Calculations and Phase-Transferable Machine Learning Potentials

tbraeckevelt — Sat, 11 Jun 2022 18:44:03 +0000

T. Braeckevelt, R. Goeminne, S. Vandenhaute, S. Borgmans, T. Verstraelen, J.A. Steele, M. Roeffaers, J. Hofkens, S.M.J. Rogge, V. Van Speybroeck

Chemistry of Materials

34, 19, 8561–8576

2022

Abstract

While metal halide perovskites (MHPs) have shown great potential for various optoelectronic applications, their widespread adoption in commercial photovoltaic cells or photosensors is currently restricted, given that MHPs such as CsPbI₃ and FAPbI₃ spontaneously transition to an optically inactive nonperovskite phase at ambient conditions. Herein, we put forward an accurate first-principles procedure to obtain fundamental insight into this phase stability conundrum. To this end, we computationally predict the Helmholtz free energy, composed of the electronic ground state energy and thermal corrections, as this is the fundamental quantity describing the phase stability in polymorphic materials. By adopting the random phase approximation method as a wave function-based method that intrinsically accounts for many-body electron correlation effects as a benchmark for the ground state energy, we validate the performance of different exchange-correlation functionals and dispersion methods. The thermal corrections, accessed through the vibrational density of states, are accessed through molecular dynamics simulations, using a phase-transferable machine learning potential to accurately account for the MHPs’ anharmonicity and mitigate size effects. The here proposed procedure is critically validated on CsPbI₃, which is a challenging material as its phase stability changes slowly with varying temperature. We demonstrate that our procedure is essential to reproduce the experimental transition temperature, as choosing an inadequate functional can easily miss the transition temperature by more than 100 K. These results demonstrate that the here validated methodology is ideally suited to understand how factors such as strain engineering, surface functionalization, or compositional engineering could help to phase-stabilize MHPs for targeted applications.

Open Access version available at UGent repository

Gold Open Access

DOI

https://doi.org/10.1021/acs.chemmater.2c01508

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acs.chemmater.2c01508.pdf

Charting the Complete Thermodynamic Landscape of Gas Adsorption for a Responsive Metal-Organic Framework

rgoeminne — Wed, 24 Mar 2021 14:13:22 +0000

R. Goeminne, S. Krause, S. Kaskel, T. Verstraelen, J.D. Evans

JACS (Journal of the American Chemical Society)

143, 11, 4143–4147

2021

Abstract

New nanoporous materials have the ability to revolutionize adsorption and separation processes. In particular, materials with adaptive cavities have high selectivity and may display previously undiscovered phenomena, such as negative gas adsorption (NGA), in which gas is released from the framework upon an increase in pressure. Although the thermodynamic driving force behind this and many other counterintuitive adsorption phenomena have been thoroughly investigated in recent years, several experimental observations remain difficult to explain. This necessitates a comprehensive analysis of gas adsorption akin to the conformational free energy landscapes used to understand the function of proteins. We have constructed the complete thermodynamic landscape of methane adsorption on DUT-49. Traversing this complex landscape reproduces the experimentally observed structural transitions, temperature dependence, and the hysteresis between adsorption and desorption. The complete thermodynamic description presented here provides unparalleled insight into adsorption and provides a framework to understand other adsorbents that challenge our preconceptions.

DOI

https://doi.org/10.1021/jacs.1c00522

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