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Sven geselecteerd als nieuw lid Jonge Academie

© Jonge Academie (2023)

Vanaf 2023 tot 2028 zal CMM-er Sven Rogge de Jonge Academie vervoegen. Sven ambieert om tijdens zijn termijn de aandacht voor onderzoek in al zijn facetten aan te wakkeren, en dit zowel bij de brede bevolking als bij de verschillende beleidsniveaus.

Om dit doel te bereiken, wil Sven verder inzetten op de uitbouw van wetenschapscommunicatie voor de brede onderzoeksgemeenschap. Enerzijds beoogt hij hiermee een meer diverse groep mensen te overtuigen de stap te zetten naar een studie of carrière in de verschillende takken van de wetenschap. Anderzijds zou dit helpen om onderzoekers en de brede maatschappij dichter met elkaar in contact te brengen om zo oplossingen aan te bieden voor toekomstige uitdagingen.

Sven is computationeel materiaalfysicus. Hij ontwikkelt computeralgoritmes om te begrijpen en voorspellen hoe realistische materialen zich gedragen, startende van hun atomaire structuur en de kwantummechanische wetten. Deze modellen laten toe om nieuwe materialen te ontwerpen en zo een antwoord te bieden op prangende duurzaamheidsvraagstukken door bijvoorbeeld broeikasgassen af te vangen of mechanische schokken efficiënt te absorberen.

De Jonge Academie is een interdisciplinaire en interuniversitaire ontmoetingsplaats van jonge toponderzoekers en kunstenaars met een eigen kijk op wetenschap, maatschappij, kunst en beleid. Zij selecteert ieder jaar, na een open oproep, een tiental nieuwe leden. De dertien nieuwe leden voor de termijn 2023-2028 worden plechtig geïnaugureerd op woensdagnamiddag 8 maart 2023 in het Paleis der Academiën in Brussel.

NY walking dinner CMM 2023

Friday January 20th, 2023 we welcomed the CMM family and friends to raise a glass to the new year. We were happy to reinstall an old tradition of meeting each other in person. We took a moment to look back at the past two years, looked forward to a promising and inspiring 2023 and felt thankful for what we have.

At CMM we can count on the strength and ambition of young people. In the past two years we welcomed 18 master students, 13 new researchers, a new ZAP member and a new project manager. To speak for their ambition, it might be mentioned that in 2021 and 2022 five of our researchers were able to receive an FWO fellowship. Although the covid-period was hard for our young researchers, five of them were able to successfully defend their PhD in the past two years and in 2023 we expect eight new PhDs. We are proud that since the very beginning in 2000, the CMM has successfully supported 66 PhD students. In 2023, all of them will be honored on our new PhD picture wall in the hallway.

We believe that the key to our success – both in research and teaching – is bringing together motivated people with an open vision and an eagerness for excellence through collaboration, without forgetting to care for each other. So to the whole CMM family and friends: thank you!

CMM assists in elucidating the capabilities of polymeric and zeolite membranes for gas adsorption

© KU Leuven - Xiaoyu Tan

The efficient separation of CO2 and methane or nitrogen gas poses an important industrial challenge, for instance for the purification of biogas or flue gasses. A new mixed-matrix membrane (MMM) developed by the KU Leuven is shown to outperform all existing polymer-based membranes in terms of CO2—CH4 mixed-gas selectivity and CO2 permeability. The role of the Na-SSZ-39 zeolite incorporated in the polymer membrane was elucidated with the aid of computational modelling performed by the CMM. The results of this collaborative study were recently published in Science.

Zeolites are not only used as catalysts in the petrochemical industry, but their high thermal and chemical stability makes them also ideally suited for other applications. In this work, the Na-SSZ-39 zeolite was embedded as a filler in a polymeric membrane, forming a zeolite-filled mixed-matrix membrane (MMM). In this way, a selective zeolite can be combined with less expensive and more processable polymers. Notwithstanding the challenging problem of obtaining an MMM with a high zeolite loading in combination with a defect-free polymer-zeolite interface and a highly selective zeolite, such a membrane was realized by the group of prof. Vankelecom (cMACS), which outperforms all existing polymer-based membranes and even most zeolite-only membranes.

Molecular insight in the gas adsorption behaviour of the zeolite was provided by the CMM. Using grand canonical Monte Carlo (GCMC) simulations, adsorption isotherms were constructed for unary and binary gas adsorption cases. Because of the CO2-philicity of the zeolite, due to the preferential electrostatic interaction between CO2 and the sodium ions in the zeolite, the methane uptake was observed to drastically reduce in the presence of CO2. Furthermore, quantum mechanical calculations of the diffusion barrier also showed a difference of almost 20 kJ/mol between CO2 and methane, thus confirming the experimentally observed difference in diffusivity selectivity.

CMM authorsAran Lamaire, prof. Veronique Van Speybroeck

CMM contributes to the development of more durable materials for solar cells

Solar cells and other optoelectronic devices require materials that efficiently convert light into electron/hole pairs and electrical currents. A collaborative study led by the Roeffaers and Hofkens lab (KU Leuven) led to the engineering of such a material that can operate for several years. The group of prof. Van Speybroeck at CMM contributed to this research and publication with quantum mechanical insights. The results of our study were recently published in Nature Communications.

Metal halide perovskites are promising materials for optoelectronic applications. They absorb sunlight well, the generated electron/hole pairs can diffuse trough large parts of the materials, and they are inexpensive to produce. Among these perovskites, CsPbI3 continues to receive considerable interest given its superior stability under ambient conditions. The remaining bottleneck is the phase stability of the so-called black phase. This black phase is optoelectronically the most interesting one, but forms spontaneously only at high temperatures. This sought-after phase rapidly degrades at room temperature to a yellow phase with inferior optoelectronic properties. Both the experimental and computational work showed that defining a PbI2 microgrid hinders this degradation and thus drastically increases the material’s long-term stability.

The laser-defined PbI2 microgrid separates the CsPbI3 material into micrometer-sized domains. This created grid acts as an anchoring point for the black phase and prevents the local degradation of one domain from triggering the degradation of neighboring ones. To understand how the microgrid improves the stability of the CsPbI3 black phase, we performed dynamic quantum mechanical simulations. Although computationally expensive, modeling these quantum mechanical interactions is essential to understand what factors influence the relative phase stabilities of the black and yellow phases. We found that the anchoring on the microgrid inhibits the movements necessary for the transformation from the black to the yellow phase, and thus results in a long-term stable black-phase material usable for optoelectronic applications.

CMM authorsTom Braeckevelt, dr. Sven Rogge, prof. Veronique Van Speybroeck

Meeting report MOF2022

In September about 700 scientists from 45 countries gathered in Dresden for the 8th International Conference on Metal-Organic Frameworks and Open Framework Compounds (MOF2022). It was the first physical meeting after the COVID-19 crisis and an ideal platform for scientists, developers and users to reconnect and present their latest findings. Prof. Van Speybroeck and prof. Guy Maurin (CNRS, University of Montpellier) were invited to write the meeting report. Read the full report published in Nature Materials here.

PhD position at CMM for a computational scientist

We are partners in a MSCA DN-JD project (Doctoral Network – Joint Doctorate) SENNET. The aim of SENNET is to create disruptive sensor technology for indoor air quality by incorporating porous materials and sensor technology. The project has pooled the interdisciplinary and intersectoral expertise of leading members located in Belgium, Germany, France, Ireland, Moldova, Spain, the UK and the Netherlands.

We are looking for an excellent PhD student to work on the “characterization of adsorption and dielectric and refractive index response of MOFs and zeolites”. The objective is to accurately predict (1) the adsorption isotherms and selectivity, and (2) the dielectric constants and refractive index response of nanoporous materials towards various volatile organic compounds (VOCs). For this purpose, accurate material specific force fields and/or ab initio trained machine learning potentials for a variety of VOCs need to be constructed to simulate single- and multicomponent isotherms. Additionally, dielectric constants and refractive index responses should be calculated for certain VOCs using ab initio techniques such as density functional theory.

We are looking for a computational scientist with a solid background in atomistic molecular simulations, quantum mechanics, statistical physics and thermodynamics applied to material science.

The candidate should have or will soon obtain a master’s degree of a university or international equivalent in the field of Physics or Physical Engineering. Depending on the curriculum also a master’s in chemistry, chemical engineering or another related field might have the desired background. Experience with molecular simulation software (LAMMPS, DLPOLY, RASPA, Gaussian, VASP, CP2K, …) and coding (Python, C, …) is an advantage. Additionally, the candidate has a pro-active working style, the willingness to look beyond the borders of his/her own discipline and a strong motivation to work in a multidisciplinary team. (S)he is highly motivated to become an independent researcher. We expect a researcher with excellent communication skills and a strong motivation to collaborate with other researchers, within the CMM, the SENNET consortium and our networks.

The selected candidate will not only receive state-of-the-art science/technology training but will also benefit from a unique soft-skills training program within the frame of the MSCA doctoral network, which will kick-start his/her career as a highly employable professional in the EU and beyond. We will host the potential PhD student at Ghent University in our research group, the Center for Molecular Modeling. However, this PhD position will lead to a joint-PhD between Ghent University (CMM) and Université de Montpellier (CNRS). As such a first secondment of six months is planned at CNRS Montpellier under the supervision of prof. Guillaume Maurin. Another secondment of 2-3 months is planned at one of the industrial partners SCM (Software for Chemistry & Materials) for which Stan van Gisbergen will be supervisor.

The successful candidates will receive an attractive salary in accordance with the MSCA regulations for Recruited Researchers. At Ghent University PhD funding is foreseen for 48 months. All applications proceed through the on-line recruitment portal on the https://sennet-project.eu/ website. Please carefully read the eligibility criteria on the website. The initial deadline for on-line registration has been extended for our research position. Ideally the selected PhD student starts prior to March 1st, 2023.

Potluck breakfast @CMM

After three years we could finally organize our yearly potluck breakfast again. On Thursday morning October 13th, 2022 we welcomed six new master students and a new PhD student.

At the beginning of October Alen T. Mathew joined CMM to work together with Reza Mehdipour. Alen received his master’s degree in pharmaceutical chemistry from the Indian Institute of Technology. During his master thesis he studied the folding patterns of Tau protein using replica exchange molecular dynamics. At CMM his PhD project is mainly focused on membrane transporters and receptors, which he will study using molecular dynamics simulations and docking.

Hereafter you can find an overview of our new master students and their topics. We wish them and Alen a good time here at CMM and a lot of inspiration upon their scientific journey.

Bjarne De Bruyn - Extracting high-dimensional free energy surfaces from molecular simulations to accurately estimate the rate of physical and chemical processes

Sander De Meyer - The mystery of high-temperature superconductivity: ab-initio calculations using density-functional theory, downfolding and tensor networks

Bram Mornie - From Schrödinger to Newton: ab initio derived classical force fields versus machine learning potentials for zeolite properties

Lisa Ronsyn - Artificial intelligence-driven modeling of protein complexes

Wim Temmerman - Direct CO2 valorization on zeolite catalysts: Identifying olefin formation pathways in a complex molecular environment

Daan Verraes - Increasing the accuracy of quantum-mechanical simulations for strongly correlated functional materials by designing effective Hamiltonians

Congratulations dr. Maarten Cools-Ceuppens!

On September 15th our colleague Maarten Cools-Ceuppens successfully defended his PhD. During his defence Maarten presented his work entitled ‘Incorporating long-range interactions and polarization in machine learning potentials with explicit electrons’. He was supervised by prof. dr. ir. Toon Verstraelen and prof. dr. ir.  Joni Dambre.

Congratulations Maarten!

Summary of the PhD in laymen's terms

With molecular modeling, one can simulate the behavior of all kinds of materials at the level of individual atoms. At this length scale, systems composed of electrons and nuclei adhere to the laws of quantum mechanics, meaning that they can be simulated by solving the Schrödinger equation. In realistic applications, this approach requires an enormous amount of computing power, which remains challenging, even with today's supercomputers. In practice, one must resort to approximate methods instead. A force field is such a popular approximate method, in which electrons are no longer described explicitly, enabling simulations of larger atomistic systems over longer time scales.

For advanced applications, e.g. those involving charge transfer or polarization, conventional force fields do not capture all the relevant physics. Therefore, in this PhD, we have developed a new force field, in which electrons are re-introduced as semi-classical particles. This force field does capture the physics of charge transfer and polarization, yet without the computational burden of quantum-mechanical models. A machine-learning model was trained to incorporate the complex short-range quantum-mechanical interactions between semi-classical electrons. This new model can indeed learn these interactions automatically and truthfully, which was confirmed by accurate predictions of various electronic properties of organic molecules and periodic atomistic models of solids.

CMM @MOF2022 in Dresden

From September 4th until 7th, 2022, the 8th International Conference on Metal-Organic Frameworks and Open Framework Compounds (MOF2022) took place in Dresden. It was an ideal platform for scientists, developers and users to connect and present their novel generation of porous framework materials, discover new functions and meet experts from all disciplines. Of course, the CMM also attended this scientific meeting to show our latest results on metal-organic frameworks (MOFs).

Veronique Van Speybroeck was invited to talk about our challenging work on modeling spatiotemporal processes in realistic MOFs at length and time scales comparable to experimental observations. To bridge this gap towards larger length and time scales, one needs fundamentally new methods which combine the accuracy of density functional theory with the computational efficiency of classical force fields. The rapidly developing field of machine learning potentials may offer such a hybrid alternative.

Sven Rogge introduced the concept of strain engineering to quantify the impact building block alterations have on the local and overall flexibility in MOFs as well as to design MOFs for specific applications. Strain fields are local and time-dependent tensor quantities that describe a material’s deviation from its equilibrium structure under external triggers, thereby constituting an important fingerprint for (local) flexibility.

Sander Borgmans presented our protocol to explore the phase stability of covalent organic frameworks (COFs) exhibiting the flexible dia topology. With a case study he demonstrated how we successfully described the observed flexibility in COF-300, using an umbrella sampling protocol relying on judiciously chosen collective variables that describe the transitions.

Alexander Hoffman talked about the work we have done together with the group of Stefan Kaskel (Institute of Inorganic Chemistry - Dresden University of Technology) and prof. Alexander Krylov (Kirensky Institute of Physics – Federal Research Center KSC SB RAS). In this contribution, he presented our new theoretical approach, supported by experimental Raman measurements, to identify rigid unit modes in a set of MIL-53-type materials i.e. soft porous crystals with a winerack topology.

During the poster session Aran Lamaire introduced our work on getting Atomic insight in the flexibility and heat transport properties of MIL-53(Al) for water-adsorption applications.

CMM attends DFT2022 Conference in Brussels

Last week the CMM attended the 19th International Conference on Density Functional Theory and its Applications in Brussels (https://www.dft2022.be/). The conference covers a broad range of topics in the field, from the latest theoretical developments to cutting-edge applications in chemistry and physics, bringing together scientists from all over the world.

Stefaan Cottenier was invited to talk about his efforts on comparing different DFT methods and codes. If you use DFT to predict a property of a crystal, how confident can you be that the prediction is computed in a bug-free way? And if your DFT-code uses pseudopotentials, can you trust the pseudopotential does not modify your predictions? If you want an answer to these questions, feel free to (re)watch his talk here.

Tom Braeckevelt presented our recent work on metal halide perovskites (MHPs). In the past decade, MHPs have shown great potential for various optoelectronic applications. However, their spontaneous transition to an inactive yellow phase impedes the widespread adoption of, e.g., CsPbI3 and FAPbI3. Using RPA calculations and phase-transferable machine learning potentials we determined the transition temperature of MHPs.

YingXing Cheng elaborated on a new ACKS2ω model, which offers a solid connection between the quantum-mechanical description of frequency-dependent response and computationally efficient force-field models. With this methodology we want to propose an alternative for today’s quantum-mechanics-based methods, which are still computationally expensive for extended systems.

Finally the CMM was also represented with two posters. Liesbeth De Bruecker presented our computational study of the electronic structure of Co2+ Aqua-Complexes and Sander Vandenhaute introduced our work on Machine Learning Potentials for Activated Processes using Active Learning.

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