V. Van Speybroeck

The Gradient Curves Method: An improved strategy for the derivation of molecular mechanics valence force fields from ab initio data

T. Verstraelen, D. Van Neck, P.W. Ayers, V. Van Speybroeck, M. Waroquier
LECTURE SERIES ON COMPUTER AND COMPUTATIONAL SCIENCES
Volume 7A-B, page 576 -+
2006
P1

Abstract 

A novel force-field parameterization procedure[1] is proposed that surmounts well-known difficulties of the conventional least squares parameterization. The multidimensional ab initio training data are first transformed into individual one-dimensional data sets, each associated with one term in the force-field model. In the second step conventional methods call be used to fit each energy term separately to its corresponding data set. The first step call be completed without any knowledge of the analytical expressions for the energy terms. Moreover the transformed data sets dictate the form of these expressions, which makes the method very suitable for deriving valence force fields. During the transformation in the first step, continuity and least-norm criteria are imposed. The latter facilitate the intuitive physical interpretation of the energy terms that are fitted to the transformed data sets, a prerequisite for transferable force fields. Benchmark parameterizations have been performed oil three small molecules, showing that the new method results in physically intuitive energy terms, exactly when a conventional parameterization would suffer from parameter correlations, i.e. when the number of redundant internal coordinates in the force-field model increases.

Unraveling the Mechanisms of Zirconium Metal–Organic Frameworks-Based Mixed-Matrix Membranes Preventing Polysulfide Shuttling

W. Lu, Z. Pang, A. Lamaire, F. Liu, S.Dai, M. L. Pinto, R. Demir-Cakan, K. O. Tan, V. Van Speybroeck, V. Pimenta, C. Serre
Small Science
4, 2300339
2024
A1

Abstract 

Lithium-sulfur batteries are considered as promising candidates for next-generation energy storage devices for grid applications due to their high theoretical energy density. However, the inevitable shuttle effect of lithium polysulfides and/or dendrite growth of Li metal anodes hinder their commercial viability. Here, the microporous Zr fumarate MOF-801(Zr) was considered to produce thin (~15.6 µm, ~1mg cm²) mixed matrix membranes (MMM) as a novel interlayer for Li-S batteries. It was found that the MOF-801(Zr)/C/PVDF-HFP composite interlayer facilitates Li+ ions diffusion, and anchors polysulfides while promoting their redox conversion effectively. We demonstrated that MOF-801 effectively trapped polysulfides at the cathode side, and confirmed for the first time the nature of the interaction between the adsorbed polysulfides and the host framework, through a combination of solid-state NMR and molecular dynamics simulations. The incorporation of MOF-801(Zr)/C/PVDF-HFP MMM interlayer resulted in a notable enhancement in the initial capacity of Li-S batteries up to 1110 mA h g-1. Moreover, even after 50 cycles, a specific capacity of 880 mA h g-1 was delivered.

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

S. Borgmans, S.M.J. Rogge, L. Vanduyfhuys, V. Van Speybroeck
Journal of Chemical Theory and Computation
19, 24, 9032-9048
2024
A1

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

On the Prediction of Spectroscopic Fingerprints of Co2+ Complexes Relevant for the ZIF Nucleation Process

L. De Bruecker, M. Filez, V. Van Speybroeck
Inorganic Chemistry
Volume: 62, Issue: 40, Pages: 16304-16322
2023
A1

Abstract 

The nucleation process of zeolitic imidazolate frameworks (ZIFs) is to date not completely understood. Recently, it has been found that, during the formation of Co-ZIF-67, after mixing imidazole-type ligands with octahedral precursors containing oxygen-coordinated ligands, a metal–organic pool with a diversity of transition metal complexes (TMCs) is formed showing fingerprints of octahedral and tetrahedral Co2+ complexes with both types of ligands [Filez, M. Cell Rep. Phys. Sci. 2021, 2, 100680]. In order to further unravel this process, we aim to characterize the d–d transitions of the TMCs and focus on their number, intensity, and position, which change during the process and can thus serve as a fingerprint for the formed species. It was previously shown that the number of ligands and symmetry has a detrimental influence on the ground state properties of Co2+ TMCs. Herein, we investigate how far excited state properties of TMCs relevant during nanoporous formation processes can be predicted by time-dependent density functional theory (TDDFT) and ligand field density functional theory (LFDFT). As TMCs are known to be challenging systems with possibly degenerate ground states and double excitations, we first investigate the performance of both techniques on first-row octahedral aqua-complexes. With this knowledge, we then focus on tetrahedral Co2+ complexes with aqua and imidazole-type ligands in order to investigate in how far we can propose a spectroscopic fingerprint that allows us to follow the Co2+ complexes during the formation of Co-ZIF-67. The results of TDDFT and LFDFT are qualitatively in agreement and provide complementary information. We found that various features can be used to distinguish between the species. However, as LFDFT is not suited for TMCs possessing the extended imidazole-type ligands and double and spin-flip states are not included in TDDFT, both techniques need to be complemented with more advanced methods to obtain complete insight into the d–d excitations of TMCs with imidazole ligands. Therefore, we particularly explored ab initio ligand field theory, which is capable of describing double excitations and is, in contrast to LFDFT, suitable for TMCs with extended ligands.

The Electrophilic Aromatic Bromination of Benzenes: Mechanistic and Regioselective Insights from Density Functional Theory

X. Deraet, E. Desmedt, R. Van Lommel, V. Van Speybroeck, F. De Proft
Physical Chemistry Chemical Physics (PCCP)
25, 28581 - 28594
2023
A1

Abstract 

The electrophilic aromatic substitution of benzenes is part of any undergraduate organic chemistry textbook, yet the mechanism, and more precisely the Wheland intermediate, remains a matter of debate. In this paper, we have computed different reaction paths for the bromination of benzene, anisole and nitrobenzene at the B97X-D/cc-pVTZ level of theory. This revealed, independently of the considered benzenes, a clear kinetic preference for an addition-elimination mechanism, rather than a substitution. Moreover, both mechanisms do not involve a charged Wheland-like intermediate, not in the gas phase nor in the investigated solvents (CCl4 and acetonitrile). Insight into the regioselectivity of the bromination was provided using a combination of conceptual DFT reactivity indices, aromaticity indices, Wiberg bond indices and the non-covalent interaction index. The ortho/para directing effect of the electron-donating methoxy-group in anisole was retrieved and ascribed to a synergy between strong electron delocalisation and attractive interactions. In contrast, the preferred meta-addition on nitrobenzene could not be traced back to any of these effects, nor to the intrinsic reactivity property of the reactant. In this case, an electrostatic clash between the ipso-carbon of the ring and the nitrogen atom resulting from the later nature of the rate-determining step, with respect to anisole, appeared to play a crucial role.

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

R. Goeminne, L. Vanduyfhuys, V. Van Speybroeck, T. Verstraelen
Journal of Chemical Theory and Computation (JCTC)
19, 18, 6313-6325
2023
A1

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.

Operando modeling of zeolite catalyzed reactions using first principle molecular dynamics simulations

V. Van Speybroeck, M. Bocus, P. Cnudde, L. Vanduyfhuys
ACS Catalysis
13, 17, 11455-11493
2023
A1

Abstract 

Within this Perspective, we critically reflect on the role of first-principles molecular dynamics (MD) simulations in unraveling the catalytic function within zeolites under operating conditions. First-principles MD simulations refer to methods where the dynamics of the nuclei is followed in time by integrating the Newtonian equations of motion on a potential energy surface that is determined by solving the quantum-mechanical many-body problem for the electrons. Catalytic solids used in industrial applications show an intriguing high degree of complexity, with phenomena taking place at a broad range of length and time scales. Additionally, the state and function of a catalyst critically depend on the operating conditions, such as temperature, moisture, presence of water, etc. Herein we show by means of a series of exemplary cases how first-principles MD simulations are instrumental to unravel the catalyst complexity at the molecular scale. Examples show how the nature of reactive species at higher catalytic temperatures may drastically change compared to species at lower temperatures and how the nature of active sites may dynamically change upon exposure to water. To simulate rare events, first-principles MD simulations need to be used in combination with enhanced sampling techniques to efficiently sample low-probability regions of phase space. Using these techniques, it is shown how competitive pathways at operating conditions can be discovered and how broad transition state regions can be explored. Interestingly, such simulations can also be used to study hindered diffusion under operating conditions. The cases shown clearly illustrate how first-principles MD simulations reveal insights into the catalytic function at operating conditions, which could not be discovered using static or local approaches where only a few points are considered on the potential energy surface (PES). Despite these advantages, some major hurdles still exist to fully integrate first-principles MD methods in a standard computational catalytic workflow or to use the output of MD simulations as input for multiple length/time scale methods that aim to bridge to the reactor scale. First of all, methods are needed that allow us to evaluate the interatomic forces with quantum-mechanical accuracy, albeit at a much lower computational cost compared to currently used density functional theory (DFT) methods. The use of DFT limits the currently attainable length/time scales to hundreds of picoseconds and a few nanometers, which are much smaller than realistic catalyst particle dimensions and time scales encountered in the catalysis process. One solution could be to construct machine learning potentials (MLPs), where a numerical potential is derived from underlying quantum-mechanical data, which could be used in subsequent MD simulations. As such, much longer length and time scales could be reached; however, quite some research is still necessary to construct MLPs for the complex systems encountered in industrially used catalysts. Second, most currently used enhanced sampling techniques in catalysis make use of collective variables (CVs), which are mostly determined based on chemical intuition. To explore complex reactive networks with MD simulations, methods are needed that allow the automatic discovery of CVs or methods that do not rely on a priori definition of CVs. Recently, various data-driven methods have been proposed, which could be explored for complex catalytic systems. Lastly, first-principles MD methods are currently mostly used to investigate local reactive events. We hope that with the rise of data-driven methods and more efficient methods to describe the PES, first-principles MD methods will in the future also be able to describe longer length/time scale processes in catalysis. This might lead to a consistent dynamic description of all steps─diffusion, adsorption, and reaction─as they take place at the catalyst particle level.

Exploring the Charge Storage Dynamics in Donor–Acceptor Covalent Organic Frameworks Based Supercapacitors by Employing Ionic Liquid Electrolyte

A. Chatterjee, J. Sun, K. S. Rawat, V. Van Speybroeck, P. Van der Voort
SMALL
Volume: 19, Issue: 46
2023
A1

Abstract 

Two donor–acceptor type tetrathiafulvalene (TTF)-based covalent organic frameworks (COFs) are investigated as electrodes for symmetric supercapacitors in different electrolytes, to understand the charge storage and dynamics in 2D COFs. Till-date, most COFs are investigated as Faradic redox pseudocapacitors in aqueous electrolytes. For the first time, it is tried to enhance the electrochemical performance and stability of pristine COF-based supercapacitors by operating them in the non-Faradaic electrochemically double layer capacitance region. It is found that the charge storage mechanism of ionic liquid (IL) electrolyte based supercapacitors is dependent on the micropore size and surface charge density of the donor–acceptor COFs. The surface charge density alters due to the different electron acceptor building blocks, which in turn influences the dense packing of the IL near its pore. The micropores induce pore confinement of IL in the COFs by partial breaking of coulomb ordering and rearranging it. The combination of these two factors enhance the charge storage in the highly microporous COFs. The density functional theory calculations support the same. At 1 A g−1, TTF-porphyrin COF provides capacitance of 42, 70, and 130 F g−1 in aqueous, organic, and IL electrolyte respectively. TTF-diamine COF shows a similar trend with 100 F g−1 capacitance in IL.

Universal descriptors for zeolite topology and acidity to predict the stability of butene cracking intermediates

P. Cnudde, M. Waroquier, V. Van Speybroeck
Catalysis Science & Technology
13, 4857-4872
2023
A1

Abstract 

The influence of pore topology and acid strength on the adsorption of (iso)butene in Brønsted acid zeolites is investigated using a combination of static calculations and ab initio molecular dynamics simulations at operating conditions. The nature and lifetime of the adsorbed intermediates – a physisorbed alkene, a chemisorbed carbenium ion or an alkoxide – is assessed for a series of one-dimensional and three-dimensional zeolite topologies as well as metal substituted aluminophosphates with varying acid site strength. While alkoxides are elusive intermediates at high temperature, irrespective of the pore dimensions or acidity, the carbenium ion stabilization is highly correlated with the zeolite confinement and acid site strength. The impact of both topology and acidity can be nicely predicted by identifying universal descriptors such as the dispersion component of the isobutene adsorption energy (topology) and the ammonia adsorption energy (acidity). It is shown that the isobutene adsorption energies and protonation barriers follow clear linear correlations with these descriptors. Our findings yield essential insight into the reactivity differences for frameworks with a different topology and acidity. The activity of a zeolite for alkene conversion can for a large part be ascribed to variations in adsorption strength and its protonation ability.

The role of phonons in switchable MOFs: a model material perspective

A.E.J. Hoffman, I. Senkovska, L. Abylgazina, V. Bon, V. Grzimek, A.M. Dominic, M. Russina, M.A. Kraft, I. Weidinger, W.G. Zeier, V. Van Speybroeck, S. Kaskel
Journal of Materials Chemistry A
11, 28, 15286-15300
2023
A1

Abstract 

The large cell volume changes of switchable metal–organic frameworks (MOFs) render them as promising functional materials. Low-frequency phonon modes are known to influence the dynamic response of these materials. The pillared layer DUT-8(M) materials are prototypical examples of switchable MOFs, enabling switching between the closed and open pore phases, largely depending on the metal ions constituting the paddle wheel unit. However, the role of specific phonon modes in the softness of these materials is still rather unexplored. This study combines complementary spectroscopic techniques such as Raman spectroscopy, inelastic neutron scattering, and phonon acoustic spectroscopy (PAS) with density functional theory calculations (DFT) to unravel the vibrational properties of DUT-8(M) with different metal nodes (M = Ni, Co, Zn, Cu) to address these open questions. After analysis of the various experimental and theoretical spectroscopic data, the closed pore phase of DUT-8(Ni) appeared to be stiffer than that of the materials with Co and Zn. Experiments also show that the open pore phase of the Ni based compound is softer than those containing Zn and Co, although these findings could not be supported by theory. Nevertheless, DFT calculations could explain that changing the metal atom has mainly an impact on the phonon modes inducing changes in the paddle wheel unit. These results yield valuable insights into the role of the metal node on the observed flexibility in DUT-8(M) materials and can help to understand the mechanisms behind the phase transition in switchable MOFs.

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