Center for Molecular Modeling - S.M.J. Rogge

Challenges and Best Practices in Modeling Anisotropic Stresses in Soft Polymorphic Materials

sven — Thu, 08 Jan 2026 12:15:38 +0000

J. Neirynck, S. Geerinckx, S.M.J. Rogge

ACS Physical Chemistry Au

2026

Abstract

Soft polymorphic materials, such as metal–organic frameworks (MOFs) and covalent organic frameworks (COFs), often display distinct anisotropy. Yet, their phase transition behavior has been predominantly characterized under isotropic stimuli, such as temperature or pressure variations, up to now. In this work, we employed the Cauchystat to investigate how MIL-53(Al) and COF-5, two prototypical soft porous crystals, respond to anisotropic stresses instead. For MIL-53(Al), we showed that normal stresses induce a phase transition already at stresses below the critical hydrostatic pressure, depending on the directionality of the applied stress. For COF-5, we determined the critical shear stress needed to induce a layer instability, leading to delamination. In both cases, we highlighted the importance of selecting adequate values of the Cauchystat control parameters to obtain accurate predictions. Based on these insights, we formulated best practices to simulate phase transitions in soft porous crystals under nonhydrostatic loadings, which is required for, e.g., nanosensors and -dampers.

Gold Open Access

DOI

http://dx.doi.org/10.1021/acsphyschemau.5c00141

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Maximizing Porosity and Water Sorption in Covalent Organic Frameworks via β-Ketoenamine Linkages

sven — Thu, 21 Aug 2025 15:16:32 +0000

R. G. AbdulHalim, B. Garai, J. De Vos, S. Borgmans, L. Gkoura, S. Varghese, F. Benyettou, M. A. Olson, S.M.J. Rogge, A. Trabolsi

SMALL

e08046

2025

Abstract

Controlling the crystallinity and porosity of 2D covalent organic frameworks (2D COFs) is crucial for their applications in science and technology. Herein, the construction of 2D COFs, COF-TP-X, is reported using a multicomponent reaction strategy that introduces β-ketoenamine linkages into isostructural imine-linked COFs. This approach yields materials with exceptional crystallinity, stability, and tunable hydrophilicity. The integration of β-ketoenamine linkages promotes intralayer planarity via NH⋯O hydrogen bonds and enhances π-electronic conjugation within and between layers. By partially substituting (43 mol%) 1,3,5-triformylbenzene with 1,3,5-triformylphloroglucinol, an outstanding gravimetric surface area of 1,984 m² g⁻¹ and a pore volume of 0.8 cm³ g⁻¹ are achieved—a remarkable two-fold increase compared to mono-linker counterparts. Moreover, COF-TP-X exhibits an exceptional water uptake capacity of 0.70 g g⁻¹ (70 wt.%) and superior hydrolytic stability, as confirmed by over 200 cycles of water adsorption–desorption experiments. Furthermore, molecular simulations reveal the significant role of electrostatic interactions between β-ketoenamine linkages in enhancing interlayer stacking and crystallinity. The findings provide key insights into COF design via a mixed-linker strategy, representing a significant advancement in developing COFs with superior performance and paving the way for their industrial applications.

Open Access version available at UGent repository

Gold Open Access

DOI

http://dx.doi.org/10.1002/smll.202508046

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Artificial Intelligence Paradigms for Next-Generation Metal–Organic Framework Research

sven — Tue, 24 Jun 2025 08:59:53 +0000

A. Ozcan, F.-X. Coudert, S.M.J. Rogge, G. Heydenrych, D. Fan, A. P. Sarikas, S. Keskin, G. Maurin, G. E. Froudakis, S. Wuttke, I. Erucar

JACS (Journal of the American Chemical Society)

147, 27, 23367–23380

2025

Abstract

After the development of the famous “Transformer” network architecture and the meteoric rise of artificial intelligence (AI)-powered chatbots, large language models (LLMs) have become an indispensable part of our daily activities. In this rapidly evolving era, “all we need is attention” as Google’s famous transformer paper’s title [Vaswani et al., Adv. Neural Inf. Process. Syst. 2017, 30] implies: We need to focus on and give “attention” to what we have at hand, then consider what we can do further. What can LLMs offer for immediate short-term adaptation? Currently, the most common applications in metal–organic framework (MOF) research include automating literature reviews and data extraction to accelerate the material discovery process. In this perspective, we discuss the latest developments in machine-learning and deep-learning research on MOF materials and reflect on how their utilization has evolved within the LLM domain from this standpoint. We finally explore future benefits to accelerate and automate materials development research.

Open Access version available at UGent repository

Gold Open Access

DOI

http://dx.doi.org/10.1021/jacs.5c08214

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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High-Throughput Screening of Covalent Organic Frameworks for Carbon Capture Using Machine Learning

sven — Tue, 14 May 2024 14:50:15 +0000

J. De Vos, S. Ravichandran, S. Borgmans, L. Vanduyfhuys, P. Van der Voort, S.M.J. Rogge, V. Van Speybroeck

Chemistry of Materials

36, 9, 4315-4330

2024

Abstract

Postcombustion carbon capture provides a high-potential pathway to reduce anthropogenic CO₂ emissions in the short term. In this respect, nanoporous materials, such as covalent organic frameworks (COFs), offer a promising platform as adsorbent beds. However, due to the modular nature of COFs, an almost unlimited number of structures can possibly be synthesized. To efficiently identify promising materials and reveal performance trends within the COF material space, we present a computational high-throughput screening of 268,687 COFs for their ability to efficiently and selectively separate CO₂ from the flue gas of power plants using a pressure swing adsorption process. Furthermore, we demonstrate that our screening can be significantly accelerated using machine learning to identify a set of promising materials. These are subsequently characterized with high accuracy, taking into account the effects of competitive adsorption and coadsorption. Our screening reveals that imide, (keto)enamine, and (acyl)hydrazone COFs are particularly interesting for carbon capture. Additionally, the best-performing materials are 3D COFs possessing strong CO₂ adsorption sites between aromatic rings at opposite sides of pores with a diameter of 1.0 nm. In 2D COFs, a significant influence of the framework chemistry, such as imide linkages or fluoro groups, is observed. Our design rules can guide experimental researchers to construct high-performing COFs for CO₂ capture.

Gold Open Access

DOI

http://dx.doi.org/10.1021/acs.chemmater.3c03230

Additivity of atomic strain fields as a tool to strain-engineering phase-stabilized CsPbI3 perovskites

leen — Mon, 13 Nov 2023 10:15:01 +0000

J. Teunissen, T. Braeckevelt, I. Skvortsova, J. Guo, B. Pradhan, E. Debroye, M. Roeffaers, J. Hofkens, S. Van Aert, S. Bals, S.M.J. Rogge, V. Van Speybroeck

The Journal of Physical Chemistry C

127, 48, 23400-23411

2023

Abstract

CsPbI₃ is a promising perovskite material for photovoltaic applications in its photoactive perovskite or black phase. However, the material degrades to a photovoltaically inactive or yellow phase at room temperature. Various mitigation strategies are currently being developed to increase the lifetime of the black phase, many of which rely on inducing strains in the material that hinder the black-to-yellow phase transition. Physical insight into how these strategies exactly induce strain as well as knowledge of the spatial extent over which these strains impact the material is crucial to optimize these approaches but is still lacking. Herein, we combine machine learning potential-based molecular dynamics simulations with our in silico strain engineering approach to accurately quantify strained large-scale atomic structures on a nanosecond time scale. To this end, we first model the strain fields introduced by atomic substitutions as they form the most elementary strain sources. We demonstrate that the magnitude of the induced strain fields decays exponentially with the distance from the strain source, following a decay rate that is largely independent of the specific substitution. Second, we show that the total strain field induced by multiple strain sources can be predicted to an excellent approximation by summing the strain fields of each individual source. Finally, through a case study, we illustrate how this additive character allows us to explain how complex strain fields, induced by spatially extended strain sources, can be predicted by adequately combining the strain fields caused by local strain sources. Hence, the strain additivity proposed here can be adopted to further our insight into the complex strain behavior in perovskites and to design strain from the atomic level onward to enhance their sought-after phase stability.

Open Access version available at UGent repository

Gold Open Access

DOI

http://dx.doi.org/10.1021/acs.jpcc.3c05770

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OGRe: Optimal grid refinement protocol for accurate free energy surfaces and its application to proton hopping in zeolites and 2D COF stacking

leen — Mon, 02 Oct 2023 08:12:55 +0000

S. Borgmans, S.M.J. Rogge, L. Vanduyfhuys, V. Van Speybroeck

Journal of Chemical Theory and Computation

19, 24, 9032-9048

2024

Abstract

While free energy surfaces are the crux of our understanding in many chemical and biological processes, their accuracy is generally unknown. Moreover, many developments to improve their accuracy are often complicated, impeding their general use. Luckily, several tools and guidelines are already in place to identify these shortcomings, but they are typically lacking in flexibility or fail to systematically determine how to improve the accuracy of the free energy calculation. To overcome these limitations, this work introduces OGRe--a python package for optimal grid refinement in an arbitrary number of dimensions. OGRe is based on three metrics which gauge the confinement, consistency, and overlap of each simulation in a series of umbrella sampling (US) simulations, an enhanced sampling technique ubiquitously adopted to construct free energy surfaces for hindered processes. As these three metrics are fundamentally linked to the accuracy of the weighted histogram analysis method, adopted to generate free energy surfaces from US simulations, they facilitate a systematic construction of accurate free energy profiles, where each metric is driven by a specific umbrella parameter. This allows for the derivation of a consistent and optimal collection of umbrellas for each simulation, largely independent of the initial values, thereby dramatically increasing the ease-of-use towards accurate free energy surfaces. As such, OGRe is particularly suited to determined complex free energy surfaces, with large activation barriers and shallow minima, which underpin many physical and chemical transformations, and hence to further our fundamental understanding of these processes.

Gold Open Access

DOI

https://doi.org/10.1021/acs.jctc.3c01028

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Quantum tunneling rotor as a sensitive atomistic probe of guests in a metal-organic framework

sven — Thu, 20 Jul 2023 12:32:21 +0000

K. Titov, M.R. Ryder, A. Lamaire, Z. Zeng, A.K. Chaudhari, J. Taylor, E.M. Mahdi, S.M.J. Rogge, S. Mukhopadhyay, S. Rudić, V. Van Speybroeck, F. Fernandez-Alonso, J.-C. Tan

Physical Review Materials

7, 073402

2023

Abstract

Quantum tunneling rotors in a zeolitic imidazolate framework ZIF-8 can provide insights into local gas adsorption sites and local dynamics of porous structure, which are inaccessible to standard physisorption or x-ray diffraction sensitive primarily to long-range order. Using in situ high-resolution inelastic neutron scattering at 3 K, we follow the evolution of methyl tunneling with respect to the number of dosed gas molecules. While nitrogen adsorption decreases the energy of the tunneling peak, and ultimately hinders it completely (0.33 meV to zero), argon substantially increases the energy to 0.42 meV. Ab initio calculations of the rotational barrier of ZIF-8 show an exception to the reported adsorption sites hierarchy, resulting in anomalous adsorption behavior and linker dynamics at subatmospheric pressure. The findings reveal quantum tunneling rotors in metal-organic frameworks as a sensitive atomistic probe of local physicochemical phenomena.

Gold Open Access

DOI

http://dx.doi.org/10.1103/PhysRevMaterials.7.073402

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MOFs for long-term gas storage: Exploiting kinetic trapping in ZIF-8 for on-demand and stimuli-controlled gas release

sven — Mon, 26 Jun 2023 14:23:31 +0000

K. Heinz, S.M.J. Rogge, A. Kalytta-Mewes, D. Volkmer, H. Bunzen

Inorganic Chemistry Frontiers

10, 16, 4763-4772

2023

Abstract

In this study, we investigate the potential of metal–organic frameworks (MOFs) for long-term gas storage under ambient conditions. Specifically, we selected a MOF ZIF-8 (with a 0.34 nm large pore aperture), which exhibits a temperature- and pressure-regulated gating effect, and loaded it with sulphur hexafluoride (with a kinetic diameter of 0.55 nm). By optimising the loading conditions, we were able to achieve up to 33 wt% SF₆ loading into the pores of ZIF-8. Although MOFs featuring gating effects are known to adsorb gases larger than the pore openings, herein, by applying high pressure (and optionally elevated temperature), kinetic trapping of the gas guest was also achieved. When investigating the gas release under ambient conditions, three MOF samples of different crystal sizes (ca. 45 nm, 1.5 μm and 5 μm) were examined. Remarkably, for the largest crystals, more than 86% of the initially loaded gas remained trapped in the pores even after being exposed to air for 100 days under ambient conditions. Our findings indicate that the extremely slow release of SF₆ is due to the high activation energy for the guest diffusion through the narrow pore opening in ZIF-8, which was supported by both ab initio-based computational studies and experimental data including modulated thermogravimetric analysis. On the other hand, we also showed that the gas could be released on-demand by applying an elevated temperature or by exposing the MOF to an acidic environment, which opens possibilities for facile gas micro- and nano-dosing applications.

DOI

http://dx.doi.org/10.1039/D3QI01007D

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ReDD-COFFEE: A ready-to-use database of covalent organic framework structures and accurate force fields to enable high-throughput screenings

sven — Wed, 22 Mar 2023 00:05:31 +0000

J. De Vos, S. Borgmans, P. Van der Voort, S.M.J. Rogge, V. Van Speybroeck

J. Mater. Chem. A

11, 14, 7468-7487

2023

Abstract

Covalent organic frameworks (COFs) are a versatile class of building block materials with outstanding properties thanks to their strong covalent bonds and low density. Given the sheer number of hypothetical COFs envisioned via reticular synthesis, only a fraction of all COFs have been synthesized so far. Computational high-throughput screenings offer a valuable alternative to speed-up such materials discovery. Yet, such screenings vitally depend on the availability of diverse databases and accurate interatomic potentials to efficiently predict each hypothetical COF’s macroscopic behavior, which is currently lacking. Therefore, we herein present ReDD-COFFEE, the Ready-to-use and Diverse Database of Covalent Organic Frameworks with Force field based Energy Evaluation, containing 268 687 COFs and accompanying ab initio derived force fields that are shown to outperform generic ones. Our structure assembly approach results in a huge amount of computer-ready structures with a high diversity in terms of geometric properties, linker cores, and linkage types. Furthermore, the textural properties of the database are analyzed and the most promising COFs for vehicular methane storage are identified. By making the database freely accessible, we hope it may also inspire others to further explore the potential of these intriguing functional materials.

Gold Open Access

DOI

http://dx.doi.org/10.1039/D3TA00470H