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Permanent link to this article: https://dannyvanpoucke.be/special-issue-revolutions-in-the-integration-of-artificial-intelligence-and-machine-learning-in-carbon-based-materials-research/
Jul 20 2025
With the planned arrival of 2 more PhD students to the group, it is finally time to make work of a group logo. QuATOMs is no longer the small solitary one-man-show, but has grown in the last three years to 5 eager PhDs and already 3 Post-docs have been part of the team.
The green-on-black colorscheme is inspired by the oldschool terminals, while the mage penguin of course combines a reference to Tux as well as the sometimes magical nature of computational materials research.
Permanent link to this article: https://dannyvanpoucke.be/quatoms-group-logo/
Jul 08 2025
For the second year in a row, we are organising a summerschool with the master materiomics program, oriented at students in their second or third bachelor chemistry or physics. Within this summerschool the students are introduced into the various topics which play an important role in materials research. Today, as part of the quantum pillar, I had the pleasure to introduce the students into the world of computational research, with a focus on the application for quantum mechanical modelling. We learned for example, that it is practically impossible to store the wavefunction of a simple small molecule like benzene, it would require more great deal more than a mole of galaxies in mass to store it. With Density Functional Theory on the other hand, you can easily investigate it on a modern day laptop, as you only need the electron density.
Materiomics summerschool of 2025.
Permanent link to this article: https://dannyvanpoucke.be/summerschool-materiomics/
Jun 27 2025
Latex is one of the nicest tools for formatting documents, but also a rabbit hole when you want to get that one small feature to your liking. Many PhD students discover how months quickly vanish when trying to create the perfect template…and the situation does not improve with age :-). In a recent bout of rabbit chasing, I decided that I wanted to be able to have syntax highlighting for python available for a course syllabus I’m planning. Early searches looked hopefull as a simple to use package seems to be available for the job (and even suitable for other programing languages): minted. Which is promoted by the tutorial page on overleaf with regard to syntax highlighting. Installation is simple using the MikTex Console.(Though the latter first destroyed itself during an update, losing access to the Qtframework. But Once Miktex was reinstalled, installing minted is trivial.) Unfortunately, WinEdt had an issue which was sufficiently vaguely defined: it could be not installed, incorrectly installed, missing in the path, not accessible without a shell-escape, missing some environment variable…
After some searching (shell-escape switched on, added to the path, installing additional python support packages –>?seriously?) it became clear that the package was not installed entirely correctly. A .py script isn’t sufficient in windows, and an additional cmd script was needed (as well as python installation, which was a bit amazing as we are talking about latex, so there should be no need for python, but apparently minted is a python library, wrapped up for latex). So long story short, if you want to work with minted, you should add a small cmd script to the binary folder of your latex install (after “installing minted” using MikTex) which calls your python installation to execute the python script latexminted.py.
@echo off "C:\Path\To\Python\Install\python.exe" "C:\Path\To\MikTex\Minted\latexminted.py" %*
Permanent link to this article: https://dannyvanpoucke.be/highlighting-python-in-latex/
Jun 23 2025
MSc Thesis presentation of Brent Motmans and Eleonora Thomas (master materiomics students 2025). Both presenting applications of ML in materials research: Machine Learning particle sizes using small lab-scale datasets (Brent) and development of Machine Learned Interatomic Potentials for the modelling of (the dynamics of) H-based defects in diamond.
Today we had the MSc presentations of the master Materiomics. The culmination of two year of hard study and intens research activities resulting in a final master thesis paper. This year the QuATOMs group hosted two MSc students: Brent Motmans and Eleonora Thomas. Brent Motmans performed his research in a collaboration between the QuATOMs and DESINe groups, and investigated the application of small data machine learning for the prediction of the particle size of Cu nanoparticles. His study shows that even with a dataset of less than 20 samples a reasonable 6 feature model can be created. As in previous research, he found that standard hyperparameter tuning fails, but human intervention can resolve this issue. Eleonora Thomas on the other hand introduced Machine Learned Interatomic Potentials (MLIPs) into the group. By investigating different in literature available MLIPs, she pinpointed strengths and weaknesses of the different models, as well as the technical needs for persuing such research further in our group. As collatoral, she was able to generate a model for H diffusion in diamond, with an MAE for the total energy of <10meV/atom, competing with models like google deep-mind’s GNoME.
While working on their MSc thesis, Brent and Eleonora also applied for fellowship funding for a PhD position, and we are happy to announce both Brent and Eleonora won their grant, and will be starting in the QuATOMs group as new PhD students comming academic year. Eleonora Thomas will be working on the modelling of Lignin solvation, while Brent will work in a collaboration with the HyMAD group on the modeling of hybrid perovskites.
Permanent link to this article: https://dannyvanpoucke.be/msc-materiomics-defences-new-quatoms-members/
Feb 14 2025
Authors: | Goedele Roos, Danny E.P. Vanpoucke, and Jane S. Murray |
Journal: | ChemPhysChem 26(7), e202401065 (2025) |
doi: | 10.1002/cphc.202401065 |
IF(2023): | 2.3 |
export: | bibtex |
pdf: | <ChemPhysChem_26> |
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Graphical Abstract: Schematic representation of the electrostatic potential within a water molecule along the lines between the atoms. The color background shows the electrostatic potential on the 0.001 a.u. contour of the density. The Vs,min and Vs,max points on the surface are indicated. |
This paper discusses the use of the electrostatic potential in both recent and older literature, with an emphasis upon a 2022 Molecular Physics article by Politzer and Murray entitled “Atoms do exist in molecules: analysis using electrostatic potentials at nuclei“. We discuss electrostatic potentials at nuclei and how they easily lead to atoms in molecules, without physically separating the individual atoms. We further summarize the work by the Politzer group on definitions of atomic radii by means of the electrostatic potential. The earlier studies began in the 1970’s and continued through the 1990’s. Unfortunately, access to these older publications is often limited, cfr. digital libraries often limit the authorized access until a certain publication year, and these papers are often not cited in current publications. Although still being highly interesting and relevant, this older literature is in danger of being lost. Digging into this older literature thus opens up new views. Our feeling is that Peter passed ‘on’ a vision that boundaries do not exist between atoms in molecules, but that some useful and meaningful radii can be obtained using the electrostatic potential between atoms in molecules.
Permanent link to this article: https://dannyvanpoucke.be/2025-paper-esp-politzer-rev-en/
Jan 21 2025
One of the most joyful parts of teaching, is when you read a student paper and see their joy of the research shine through.
This year was the second year I taught the course “Machine Learning and Artificial Intelligence in modern materials science“, an elective course in the second master materiomics program. As with my other computational courses, there is a strong hands-on component present in this course: a semester long homework assignment, culminating in a paper and presentation of the work done. The basic idea behind the assignment is simple: Take the QM9 dataset and study it using machine learning and artificial intelligence, incorporating things you learn during the course. In practice this means a lot of coding with for example scikit-learn in combination with using every ounce of physical and chemical intuition they gathered during their previous courses. The absolute freedom generally results in some initial trepidation, but intermediate feedback and the growing understanding that the journey is the the actual goal results in some amazing work.
At the end of the semester, I had three papers before me, which could only be written by these three students (Materiomics is a new program, so having 3 of the 7 students picking a rather hard core computational course is good 😉 ). You could feel their own backgrounds and interests seeping through, as well as the fun they had doing so. There was the engineer who approached the problem from a pipeline perspective, the chemist comparing the efficacy of various fingerprints as features, and the physicist who build a new small fingerprint from scratch creating a linear regression model that outperformed all else having R² =1. The last one is a very nice example of frugal computing, of which we do need more in a world suffering climate change. It was also interesting to see also how three totally different stories also hint at the same underlying properties of the dataset (same target being the hardest to predict), a consistency which provides a level of meta-validation of the results. The students themselves also learned to be critical of their own work by comparing the results of different methods used to attack their own research question.
At the end of this course, it is clear they learned more about artificial intelligence than what is possible by just reading about it. The understood the entire workflow of which training is merely a small part, they learned directly the importance of having good quality data and features, and most importantly they learned that they themselves need to be the I in AI, to be successful…and finally, maybe us four should put our heads together and combine this work into a real research paper, as to celebrate the great research done as a “mere homework-assignment”.
Permanent link to this article: https://dannyvanpoucke.be/machine-learning-and-artificial-intelligence-in-modern-materials-science/
Jan 09 2025
Authors: | Thijs G.I. van Wijk, E. Aylin Melan, Rani Mary Joy, Emerick Y. Guillaume, Paulius Pobedinskas, Ken Haenen, and Danny E.P. Vanpoucke |
Journal: | Carbon 234, 119928 (2025) |
doi: | 10.1016/j.carbon.2024.119928 |
IF(2024): | 10.5 |
export: | bibtex |
pdf: | <Carbon> |
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Graphical Abstract: Schematic representation of the impact of hydrostatic and linear strain on the Zero Phonon Line of the neutral GeV defect in diamond. |
Color centers in diamond, such as the GeV center, are promising candidates for quantum-based applications. Here, we investigate the impact of strain on the zero-phonon line (ZPL) position of GeV0. Both hydrostatic and linear strain are modeled using density functional theory for GeV0concentrations of 1.61 % down to 0.10 %. We present qualitative and quantitative differences between the two strain types: for hydrostatic tensile and compressive strain, red- and blue-shifted ZPL positions are expected, respectively, with a linear relation between the ZPL shift and the experienced stress. By calculating the ZPL shift for varying GeV0 concentrations, a shift of 0.15 nm/GPa (0.38 meV/GPa) is obtained at experimentally relevant concentrations using a hybrid functional. In contrast, only red-shifted ZPL are found for tensile and compressive linear strain along the ⟨100⟩ direction. The calculated ZPL shift exceeds that of hydrostatic strain by at least one order of magnitude, with a significant difference between tensile and compressive strains: 3.2 and 4.8 nm/GPa (8.1 and 11.7 meV/GPa), respectively. In addition, a peak broadening is expected
due to the lifted degeneracy of the GeV0 eg state, calculated to be about 6 meV/GPa. These calculated results are placed in perspective with experimental observations, showing values of ZPL shifts and splittings of comparable magnitude.
Permanent link to this article: https://dannyvanpoucke.be/2025-paper-strainedgev-en/
Jan 03 2025
Since the first of January 2025, the QuATOMs group has been strengthened with a new member: Minh-Thu Bui.
She is an expert in polymer chemistry, with a MSc in Polymers for advanced Technologies from the university of Grénoble. The coming four years she will be working on the QuantumLignin project. In this project, she’ll investigate the structure-property relations of lignin building blocks, with the aim of creating an additive model suitable for predicting the properties of mixed lignin samples. With her life motto: “Don’t wait for the perfect moment. Take the moment and make it perfect.” I’m sure we can expect great things to happen in the theoretical lignin field, the coming years.
Welcome to the QuATOMs team, we look forward to your enthusiasm and the intuition you bring to the team.
Permanent link to this article: https://dannyvanpoucke.be/new-quatoms-group-member-minh-thu-bui/
Jan 01 2025
2023 and 2024 have been an intense ride, with both the materiomics program, the tenure track and the research group. Since the previous overview in 2022, the QuATOMs group has seen some growth with the arrival of three new members (Pauline Castenetto, Thijs van Wijk, and Aylin Melan). In addition, Emerick Guillaume defended his PhD on the study of diamond growth.
These are not the only things which happened the last two years, so let us look back at 2023 and 2024 one last time, keeping up with  tradition.
Cover Nature Reviews Physics: Accuracy of DFT
Permanent link to this article: https://dannyvanpoucke.be/review-of-2024/