V. Van Speybroeck

Exploring the phase stability in interpenetrated diamondoid covalent organic frameworks

S. Borgmans, S.M.J. Rogge, J. De Vos, P. Van der Voort, V. Van Speybroeck
Communications Chemistry
6, 1, 5
2023
A1

Abstract 

Soft porous crystals, which are responsive to external stimuli such as temperature, pressure, or gas adsorption, are being extensively investigated for various technological applications. However, while substantial research has been devoted to stimuli-responsive metal-organic frameworks, structural flexibility in 3D covalent organic frameworks (COFs) remains ill-understood, and is almost exclusively found in COFs exhibiting the diamondoid (dia) topology. Herein, we systemically investigate how the structural decoration of these 3D dia COFs—their specific building blocks and degree of interpenetration—as well as external triggers such as temperature and guest adsorption may promote or suppress their phase transformations, as captured by a collection of 2D free energy landscapes. Together, these provide a comprehensive understanding of the necessary conditions to design flexible diamondoid COFs. This study reveals how their flexibility originates from the balance between steric hindrance and dispersive interactions of the structural decoration, thereby providing insight into how new flexible 3D COFs can be designed.

Open Access version available at UGent repository
Gold Open Access

DOI 

http://dx.doi.org/10.1038/s42004-022-00808-y

How water and ion mobility affect the NMR fingerprints of the hydrated JBW zeolite: a combined computational-experimental investigation

S. Vanlommel, A.E.J. Hoffman, S. Smet, S. Radhakrishnan, K. Asselman, C. V. Chandran, E. Breynaert, C. Kirschhock, J.A. Martens, V. Van Speybroeck
Chemistry - A European Journal
28, 68, e202202621
2022
A1

Abstract 

An important aspect within zeolite synthesis is to make fully tunable framework materials with controlled aluminium distribution. A major challenge in characterising these zeolites at operating conditions is the presence of water. In this work, we investigate the effect of hydration on the 27 Al NMR parameters of the ultracrystalline K,Na-compensated aluminosilicate JBW zeolite using experimental and computational techniques. The JBW framework, with Si/Al ratio of 1, is an ideal benchmark system as a stepping stone towards more complicated zeolites. The presence and mobility of water and extraframework species directly affect NMR fingerprints. Excellent agreement between theoretical and experimental spectra is obtained provided dynamic methods are employed with hydrated structural models. This work shows how NMR is instrumental in characterising aluminium distributions in zeolites at operating conditions.

Gold Open Access

DOI 

https://doi.org/10.1002/chem.202202621

Insights into the mechanism and reactivity of zeolite catalyzed alkylphenol dealkylation

M. Bocus, V. Van Speybroeck
ACS Catalysis
12, 22, 14227–14242
2022
A1

Abstract 

In the stride toward the production of low-carbon-footprint commodity chemicals, the development of a complete wood biorefinery plays a pivotal role. The lignin fraction of wood can be depolymerized and demethoxylated mainly into 4-alkylphenols. These phenolic compounds can further catalytically be C-dealkylated within the H-ZSM-5 zeolite at relatively high temperatures and in the presence of steam, producing phenol and olefins. Experimentally, the dealkylation reaction was found to have two striking features: first, different reactants possess very different reactivity. 4-Ethylphenol (4-EP) is somehow less reactive than 4-n-propylphenol (4-n-PP), which is in turn much less reactive than 4-isopropylphenol (4-iso-PP). Second, cofeeding of steam in the reaction mixture was necessary to prevent rapid and reversible catalyst deactivation. Herein, a combination of static and dynamic density functional theory (DFT) simulations is used to unravel the molecular and mechanistic origin of these observations. Free-energy profiles obtained from static calculations confirm the experimentally observed reactivity sequence, where our computations show that the secondary nature of the alkyl carbon involved in 4-iso-PP dealkylation strongly stabilizes the respective transition states. To investigate the effect of water on the mobility of the reactive species and their interaction with the active site, we investigated the diffusion of phenol along the H-ZSM-5 straight channel in the presence of water loadings from 0 to 3 molecules per zeolite unit cell. We show that water has a strongly beneficial effect in promoting desorption and diffusion of phenol away from the Brønsted acid site through competitive adsorption and by the formation of hydrogen bond chains with the diffusing phenol. This effect could lead to a shorter residence time inside the zeolite, preventing active site poisoning and condensation to bulkier biphenylether moieties.

DOI 

https://doi.org/10.1021/acscatal.2c03844

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

M. Bocus, R. Goeminne, A. Lamaire, M. Cools-Ceuppens, T. Verstraelen, V. Van Speybroeck
Nature Communications
14, 1008
2023
A1

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

Unfolding the terahertz spectrum of soft porous crystals: rigid unit modes and their impact on phase transitions

A.E.J. Hoffman, I. Senkovska, J. Wieme, A. Krylov, S. Kaskel, V. Van Speybroeck
Journal of Materials Chemistry A
10 (33), 17254-17266
2022
A1

Abstract 

Phase transitions in exible metal-organic frameworks or soft porous crystals are mediated by low-frequency phonons or rigid-unit modes. The alteration of specic building blocks may change the lattice dynamics of these frameworks, which can inuence the phase transition mechanism. In this work, the impact of building block substitution on the rigid-unit modes in exible MIL-53 analogs with a winerack topology will be investigated via ab initio lattice dynamics calculations. First, the accuracy of the theoretical simulations is veried via experimental Raman measurements, which provide unique ngerprint vibrations in the terahertz range to characterize the phase transition. Following analysis of the low-frequency vibrations shows that there exists a set of universal rigid-unit modes inducing translations and/or rotations of the building blocks. The theoretical results demonstrate that linker substitutions have a large eect on the rigid-unit mode frequencies, whereas this is less so for inorganic chain substitutions. These ndings may help to rationally tune the phonon frequencies in soft porous crystals.

Gold Open Access

DOI 

http://dx.doi.org/10.1039/d2ta01678h

How the Layer Alignment in Two-dimensional Nanoporous Covalent Organic Frameworks Impacts Its Electronic Properties

K. S. Rawat, S. Borgmans, T. Braeckevelt, C.V. Stevens, P. Van der Voort, V. Van Speybroeck
ACS Applied Nano Materials
5, 10, 14377-14387
2022
A1

Abstract 

Two-dimensional nanoporous covalent organic frame-works (2D COFs) have gathered significant interest due to their wide range of applications. Due to the lack of strong covalent interlayer interactions, their layers can be stacked in countless ways, each resulting in unique nanoscale characteristics impacting the structural, chemical, and electronic properties. To characterize and understand the layer stacking in 2D COFs and its effect on the structural and electronic properties, we carried out a detailed density functional theory investigation on four materials, CTF-1, COF-1, COF-5, and Pc-PBBA. This entailed an in-depth evaluation of the potential energy as a function of the interlayer distance and offset, the powder X-ray diffraction (PXRD) pattern, and the electronic properties. From the potential energy surfaces, the typical slipped AA-stacking configuration was confirmed as optimal for each of the 2D COFs, with a slight offset from a perfect alignment of the layers. The statically calculated PXRD patterns based on these optimized stacking configurations showed discrepancies when compared to experimental data. Instead, when properly accounting for dynamic fluctuations by calculating the average diffraction pattern over the course of a molecular dynamics simulation, a better agreement with the experiment is obtained. Different stacking configurations also profoundly affected the electronic band structure of COFs as the interlayer pi-pi interactions are significantly impacted by the layer offset. Evidently, with decreasing layer offsets, the pi-pi interactions increase due to the layer alignment, leading to a decrease in the band gap and an increase in interlayer charge mobility. Our study highlights the need for accurate modeling of the stacking configuration in 2D COFs as a small-scale deviation in the adjacent layer position can significantly affect the structural and electronic properties.

DOI 

https://doi.org/10.1021/acsanm.2c02647

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

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
A1

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

How Reproducible are Surface Areas Calculated from the BET Equation?

J.W.M. Osterrieth, J. Rampersad, D. Madden, N. Rampal, L. Skoric, B. Connolly, M.D. Allendorf, V. Stavila, J.L Snider, R. Ameloot, J. Marreiros, C. Ania, D. Azevedo, E. Vilarrasa-Garcia, B.F. Santos, X.-H. Bu, Z. Chang, H. Bunzen, N.R. Champness, S.L. Griffin, B. Cheng, R.-B. Lin, B. Coasne, S. Cohen, J.C. Moreton, Y.J. Colón, L. Chen, R. Clowes, F.-X. Coudert, Y. Cui, B. Hou, D.M. D'Alessandro, P.W. Doheny, M. Dincă, C. Sun, C. Doonan, M.T. Huxley, J.D. Evans, P. Falcaro, R. Ricco, O. Farha, K.B. Idrees, T. Islamoglu, P. Feng, H. Yang, R.S. Forgan, D. Bara, S. Furukawa, E. Sanchez, J. Gascon, S. Telalović, S.K. Ghosh, S. Mukherjee, M.R. Hill, M.M. Sadiq, P. Horcajada, P. Salcedo-Abraira, K. Kaneko, R. Kukobat, J. Kenvin, S. Keskin, S. Kitagawa, K.-i. Otake, R.P. Lively, S.J.A. DeWitt, P.L. Llewellyn, B.V. Lotsch, S.T. Emmerling, A.M. Pütz, C. Martí-Gastaldo, N.M. Padial, J. García-Martínez, N. Linares, D. Maspoch, J.A. Suárez del Pino, P.Z. Moghadam, R. Oktavian, R.E. Morris, P.S. Wheatley, J. Navarro, C. Petit, D. Danaci, M.J. Rosseinsky, A.P. Katsoulidis, M. Schroeder, X. Han, S. Yang, C. Serre, G. Mouchaham, D.S. Sholl, R. Thyagarajan, D. Siderius, R.Q. Snurr, R.B. Goncalves, S. Telfer, S.J. Lee, V.P. Ting, J.L. Rowlandson, T. Uemura, T. Iiyuka, M.A. van der Veen, D. Rega, V. Van Speybroeck, S.M.J. Rogge, A. Lamaire, K.S. Walton, L.W. Bingel, S. Wuttke, J. Andreo, O. Yaghi, B. Zhang, C.T. Yavuz, T.S. Nguyen, F. Zamora, C. Montoro, H. Zhou, A. Kirchon, D. Fairen-Jimenez
Advanced Materials
34, 27, 2201502
2022
A1

Abstract 

Porosity and surface area analysis play a prominent role in modern materials science. At the heart of this sits the Brunauer–Emmett–Teller (BET) theory, which has been a remarkably successful contribution to the field of materials science. The BET method was developed in the 1930s for open surfaces but is now the most widely used metric for the estimation of surface areas of micro- and mesoporous materials. Despite its widespread use, the calculation of BET surface areas causes a spread in reported areas, resulting in reproducibility problems in both academia and industry. To prove this, for this analysis, 18 already-measured raw adsorption isotherms were provided to sixty-one labs, who were asked to calculate the corresponding BET areas. This round-robin exercise resulted in a wide range of values. Here, the reproducibility of BET area determination from identical isotherms is demonstrated to be a largely ignored issue, raising critical concerns over the reliability of reported BET areas. To solve this major issue, a new computational approach to accurately and systematically determine the BET area of nanoporous materials is developed. The software, called “BET surface identification” (BETSI), expands on the well-known Rouquerol criteria and makes an unambiguous BET area assignment possible.

Gold Open Access

DOI 

http://dx.doi.org/10.1002/adma.202201502

Machine Learning Potentials for Metal-Organic Frameworks using an Incremental Learning Approach

S. Vandenhaute, M. Cools-Ceuppens, S. DeKeyser, T. Verstraelen, V. Van Speybroeck
npj Computational Materials
9, 1, 19
2023
A1

Abstract 

Computational modeling of physical processes in metal-organic frameworks (MOFs) is highly challenging due to the presence of spatial heterogeneities and complex operating conditions which affect their behavior. Density functional theory (DFT) may describe interatomic interactions at the quantum mechanical level, but is computationally too expensive for systems beyond the nanometer and picosecond range. Herein, we propose an incremental learning scheme to construct accurate and data-efficient machine learning potentials for MOFs. The scheme builds on the power of equivariant neural network potentials in combination with parallelized enhanced sampling and on-the-fly training to simultaneously explore and learn the phase space in an iterative manner. With only a few hundred single-point DFT evaluations per material, accurate and transferable potentials are obtained, even for flexible frameworks with multiple structurally different phases. The incremental learning scheme is universally applicable and may pave the way to model framework materials in larger spatiotemporal windows with higher accuracy.

 

A flexible and scalable implementation of the methodology is available in Psiflow.

Gold Open Access

DOI 

http://dx.doi.org/10.1038/s41524-023-00969-x

Stable Amorphous Solid Dispersion of Flubendazole with High Drug Loading via Solvent Electrospinning

J. Becelaere, E. Van den Broeck, E. Schoolaert, V. Vanhoorne, J. F.R. Van Guyse, M. Vergaelen, S. Borgmans, K. Creemers, V. Van Speybroeck, C. Vervaet, R. Hoogenboom, K. De Clerck
Journal of controlled release
351, November 2022, Pages 123-126
2022
A1

Abstract 

In this work, an important step is taken towards the bioavailability improvement of poorly water-soluble drugs, such as flubendazole (Flu), posing a challenge in the current development of many novel oral-administrable therapeutics. Solvent electrospinning of a solution of the drug and poly(2-ethyl-2-oxazoline) is demonstrated to be a viable strategy to produce stable nanofibrous amorphous solid dispersions (ASDs) with ultrahigh drug-loadings (up to 55 wt% Flu) and long-term stability (at least one year). Importantly, at such high drug loadings, the concentration of the polymer in the electrospinning solution has to be lowered below the concentration where it can be spun in absence of the drug as the interactions between the polymer and the drug result in increased solution viscosity. A combination of experimental analysis and molecular dynamics simulations revealed that this formulation strategy provides strong, dominant and highly stable hydrogen bonds between the polymer and the drug, which is crucial to obtain the high drug-loadings and to preserve the long-term amorphous character of the ASDs upon storage. In vitro drug release studies confirm the remarkable potential of this electrospinning formulation strategy by significantly increased drug solubility values and dissolution rates (respectively tripled and quadrupled compared to the crystalline drug), even after storing the formulation for one year.

DOI 

https://doi.org/10.1016/j.jconrel.2022.09.028

Pages

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