Tag: computational materials science

Materiomics Chronicles: week 5

After week four, this fifth week of the academic year is most arguably the most intense and hectic week of teaching. With 22h of classes and still two classes that needed to be prepared from scratch (even including weekends time was running out), I’m tired but happy it is over. However, all the effort is worth it, and I was happy to hear the students of our materiomics program at UHasselt appreciate the effort put into creating their classes, during an evaluation meeting.

The corral is an artificial structure created from 48 iron atoms (the sharp peaks) on a copper surface. The wave patterns in this scanning tunneling microscope image are formed by copper electrons confined by the iron atoms. Don Eigler and colleagues created this structure in 1993 by using the tip of a low-temperature scanning tunneling microscope (STM) to position iron atoms on a copper surface, creating an electron-trapping barrier. This was the first successful attempt at manipulating individual atoms and led to the development of new techniques for nanoscale construction.source: https://www.nisenet.org/catalog/scientific-image-quantum-corral-top-view

The corral is an artificial structure created from 48 iron atoms (the sharp peaks) on a copper surface. The wave patterns in this scanning tunneling microscope image are formed by copper electrons confined by the iron atoms. Don Eigler and colleagues created this structure in 1993 by using the tip of a low-temperature scanning tunneling microscope (STM) to position iron atoms on a copper surface, creating an electron-trapping barrier. This was the first successful attempt at manipulating individual atoms and led to the development of new techniques for nanoscale construction.
source: https://www.nisenet.org/catalog/scientific-image-quantum-corral-top-view

For the second bachelor students in chemistry the introduction to quantum chemistry finally put them into contact with some “real” quantum mechanics when they were introduced into the world of potential barriers, steps, and wells. Though these are still abstract and toy-model in nature, they provide a first connection with reality, where they can be seen as crude approximations of the potential experienced by valence electrons near the surface, or STM experiments. They were also introduced to my favorite quantum system related to this course: the quantum corral. Without any effort it can be used in half a dozen situations with varying complexity to show and learn basic quantum mechanics. For the third bachelor chemistry students the course quantum and computational chemistry finally provided them the long promised first example of a non-trivial quantum chemical object: The Helium atom. With it’s two electrons, we break free of the H-atom(-like)  world. Using perturbation theory and Slater determinant wave functions, we made our first approximations of its energy. In addition, these students also had a seminar for their course Introductory lectures in preparation to the bachelor project (Kennismakingstraject m.b.t. stage en eindproject, in Dutch). During this lecture I gave a brief introduction and overview of the work I did in the past and the work we do in our research group QuATOMs, which although “quantum” is quite different of what the students experience during their courses on quantum chemistry.

In the materiomics program, the first master students continued their travels into the basics of force-fields during the lecture of the course Fundamentals of materials modelling. The exercise class of this week upped the ante by moving from ASE to LAMMPS for practical modeling of alkane chains, which was also the topic of their second lab session. In the course Properties of functional materials, we investigated the ab initio modelling of vibrations. During the exercise classes we investigated precalculated phonon spectra in the materials-project database, as well as calculated our own vibrational spectrum at the gamma-point of the first Brillouin zone. During the second master course Machine learning and artificial intelligence in modern materials science the central theme was GIGO (Garbage-In-Garbage-Out). How can we make sure our data is suitable and good enough for our models to return useful results. We therefore looked into data-preparation & cleaning, as well as  clustering methods.

At the end of this week, we have added another 22h of live lectures and ~1h of video lectures, putting our semester total at 74h of live lectures. Upwards and onward to week 6.

Materiomics Chronicles: week 4

Week four of the academic year at the chemistry and materiomics programs of UHasselt, we are stepping up the pace a bit…at least for me. The students continue to dive deeper into the various subjects furthering their knowledge gained in the previous weeks.

In the bachelor chemistry program, the third bachelor chemistry extended their knowledge of variational theory to excited states, in the course quantum and computational chemistry. They also saw some first glimpses of the mathematical setup which makes the use of computational methods so important and powerful in quantum chemistry.  Finally they proved the Hellmann-Feynman Theorem which makes structure optimization in quantum chemistry practically feasible. For the second bachelor chemistry, the course introduction to quantum chemistry was focused on the time-dependent Schrödinger equation and the uncertainty principle.

In the first master materiomics, I was the  main player this week (and will also be so next week) teaching the classes of two of the three courses. In the course Properties of functional materials, the second module started, which is centered on the computational (quantum mechanical) modeling of materials properties. Here the students build on their recently acquired expertise in DFT to gain further insights into electronic structure calculations both in theory and in practice. In addition, the students also had their first seminar presentation where they present their understanding after studying two papers within the context of the concepts presented during the first module of the course. In the course Fundamentals of materials modelling, we moved to a new level of modeling: atomistic modeling using force-fields. The freshly gained knowledge was also here directly applied through the modeling of bulk aluminum using the ASE library in a jupyter notebook. (For many a first contact with python.) Finally, the students of the second master learned about “dynamical” modeling, in the course on Density Functional Theory, covering NEB calculations for energy barriers as well as basic molecular dynamics (with examples such as the water molecule below).


At the end of this week, we have added another 17h of live lectures and ~1h of video lectures, putting our semester total at 52h of live lectures. Upwards and onward to week 5.

Materiomics Chronicles: week 3

In week three of the academic year at the chemistry and materiomics programs of UHasselt, the students started to put their freshly gained new knowledge of weeks 1 and 2 into practice with a number of exercise classes.

For the second bachelor chemistry students, this meant performing their first calculations within the context of the course introduction to quantum chemistry. At this point this is still very mathematical (e.g., calculating commutators) and abstract (e.g., normalizing a wave function or calculating the probability of finding a particle, given a simple wave function), but this will change, and chemical/physical meaning will slowly be introduced into the mathematical formalism. For the third bachelor chemistry, the course quantum and computational chemistry continued with perturbation theory, and we started with the variational method as well. The latter was introduced through the example of the H atom, for which the exact variational ground state was recovered starting from a well chosen trial wave function.

Infinite polymethylene glycol (POM) chain.

Ball-and-stick representation of an infinite polymethylene glycol (POM) chain.

In the master materiomics, the first master course fundamentals of materials modelling, dove into the details underpinning DFT introducing concepts like pseudo-potentials, the frozen-core approximation, periodic boundary conditions etc. This knowledge was then put into practice during a second exercise session working on the supercomputer, as a last preparation for the practical lab exercise the following day. During this lab, the students used the supercomputer to calculate the Young modulus of two infinite linear polymers. An intense practical session which they all executed with great courage (remember 2 weeks ago they never heard of DFT, nor had they accessed a supercomputer). Their report for this practical will be part of their grade.

For the second master materiomics, the course focused on Density Functional Theory consisted of a discussion lecture, covering the topics the students studied during their self study assignments. In addition, I recorded two video lectures for the blended learning part of the course. For the course Machine learning and artificial intelligence in modern materials science self study topics were covered in such a discussion lecture as well. In addition, the QM9 data set was investigated during an exercise session, as preparation for further detailed study.

At the end of this week, we have added another 16h of live lectures and ~1h of video lectures, putting our semester total at 35h of live lectures. Upwards and onward to week 4.

Materiomics Chronicles: week 1

The first week of the academic year at UHasselt has come to an end, while colleagues at UGent and KULeuven are still preparing for the start of their academic year next week. Good luck to all of you.

This week started full throttle for me, with classes for each of my six courses. After introductions in classes with new students (for me) in the second bachelor chemistry and first master materiomics, and a general overview in the different courses, we quickly dove into the subject at hand.

The second bachelor students (introduction to quantum chemistry) got a soft introduction into (some of) the historical events leading up to the birth of quantum mechanics such as the black body radiation, the atomic model and the nature of light. They encountered the duck-rabbit of particle-wave duality and awakened their basic math skills with the standing wave problem. For the third bachelor students, the course on quantum and computational chemistry started with a quick recap of the course introduction to quantum mechanics, making sure they are all again up to speed with concepts like braket-notation and commutator relations.

For the master materiomics it was also a busy week. We kicked of the 1st Ma course Fundamentals of materials modeling, which starts of calm and easy with a general picture of the role of computational research as third research paradigm. We discussed in which fields computational research can be found (flabbergasting students with an example in Theology: a collaboration between Sylvia Wenmackers & Helen De Cruz),  approximation vs idealization, examples of materials research at different scales, etc. As a homework assignment the students were introduced into the world of algorithms through the lecture of Hannah Fry (Should computers run the world). For the  2nd Ma, the courses on Density Functional Theory and Machine learning and artificial intelligence in modern materials science both started. The lecture of the former focused on the nuclear wave function and how we (don’t) deal with it in DFT, but still succeed in optimizing structures. During the lecture on AI we dove into the topics of regularization and learning curves, and extended on different types of ensemble models.

At the end of week 1, this brings me to a total of 12h of lectures. Upwards and onward to week 2.

Hydration sphere structure of architectural molecules: polyethylene glycol and polyoxymethylene oligomers

Authors: Ahmed M. Rozza, Danny E. P. Vanpoucke, Eva-Maria Krammer, Julie Bouckaert, Ralf Blossey, Marc F. Lensink, Mary Jo Ondrechen, Imre Bakó, Julianna Oláh, and Goedele Roos
Journal: Journal of Molecular Liquids 384, 122172 (2023)
doi: 10.1016/j.molliq.2023.122172
IF(2021): 6.633
export: bibtex
pdf: <JMolLiq>


Graphical Abstract: PEG or POM, similar in structure though very different in their solvation. Is this due to structure or charge(distribution)?


Non-toxic, chemically inert, organic polymers as polyethylene glycol (PEG) and polyoxymethylene (POM) have versatile applications in basic research, industry and pharmacy. In this work, we aim to characterize the hydration structure of PEG and POM oligomers by exploring how the solute disturbs the water structure compared to the bulk solvent and how the solute chain interacts with the solvent. We explore the effect of (i) the C-C-O (PEG) versus CO (POM) constitution of the chain and (ii) chain length. To this end, MD simulations followed by clustering and topological analysis of the hydration network, as well as by quantum
mechanical calculations of atomic charges are used. We show that the hydration varies with chain conformation and length. The degree of folding of the chain impacts its degree of solvation, which is measurable by different parameters as for example the number of water molecules in the first solvation shell and the solvent accessible surface. Atomic charges calculated on the oligomers in gas phase are stable throughout conformation and chain length and seem not to determine solvation. Hydration however induces charge transfer from the solute molecule to the solvent, which depends on the degree of hydration.


E-MRS Spring meeting 2023

In march 2019, Belgium went into COVID-lock down while I attended the yearly diamond conference (SBDD25). Since then, I have been in a bit of a conference lock down myself as well. By visiting the 2023 spring meeting of E-MRS, this lock down has been lifted for international conferences (outside Belgium). Inside Belgium, there was already the DFT-2022 in Brussels, where I was also part of the National Scientific Committee, and of course SBDD26 & SBDD27, which as a diamond researcher you can not miss.

Coming back to Strassbourg for E-MRS brings back some memories, and generated some nice new ones. This year there was a nice Symposium called “Computations for materials – discovery, design and the role of data“[program] which got my full attention. During the first session on AI-accelerated Materials discovery, I had the pleasure to present some of my own work on the Machine Learning of small data sets (cf. papers on the average model, and UV-curable inks). The symposium was nicely coinciding with much of my interest, and showed two (not unexpected, and maybe symposium biased) trends:

  1.  There is an important evolution toward lab-automation and use of robotics (people don’t want to manually build dozens of battery cells or perform hundreds of repetitive synthesis experiments for materials optimization. This shows the future materials scientist, be it a chemist, physicist or engineer will have to become a robotics and/or programming expert as well. This only strengthens me in my vision for our materiomics [NL] students at UHasselt. These skills will be essential for their future scientific career development.
  2. Machine Learning and Artificial Intelligence will play an important role in future materials design. However, we need a better understanding of what we are doing, and not just use any method and accept it as “excellent” because the R² value is high. For now, we can still get away with the latter, but this will not last much longer. It will become more important to have a simple but interpretable model, rather than a complex (over-fitting) Deep Learning Neural Network without understanding of the underlying physics and chemistry. Also here we will have to put in some effort within the materiomics program.


So after an interesting International conference, and making some new contacts…it is time to return home, four more courses need to be prepared from scratch for coming academic year.

A machine learning approach for the design of hyperbranched polymeric dispersing agents based on aliphatic polyesters for radiation curable inks

Authors: Danny E.P. Vanpoucke, Marie A.F. Delgove, Jules Stouten, Jurrie Noordijk, Nils De Vos, Kamiel Matthysen, Geert G.P. Deroover, Siamak Mehrkanoon, and Katrien V. Bernaerts
Journal: Polymer International 71(8), 966-975 (2022)
doi: 10.1002/pi.6378
IF(2021): 3.213
export: bibtex
pdf: <PI> (Open Access) (Cover Paper)


An ensemble based machine learning model for small datasets was used to predict the relationship between the dispersant structure and the pigment dispersion quality (particle size) for radiation curable formulations.
Graphical Abstract:An ensemble based machine learning model for small datasets was used to predict the relationship between the dispersant structure and the pigment dispersion quality (particle size) for radiation curable formulations.


Polymeric dispersing agents were prepared from aliphatic polyesters consisting of δ-undecalactone (UDL) and β,δ-trimethyl-ε-caprolactones (TMCL) as biobased monomers, which are polymerized in bulk via organocatalysts. Graft copolymers were obtained by coupling of the polyesters to poly(ethylene imine) (PEI) in the bulk without using solvents. Different parameters that influence the performance of the dispersing agents in pigment based UV-curable matrices were investigated: chemistry of the polyester (UDL or TMCL), weight ratio of polyester/PEI, molecular weight of the polyesters and of PEI. The performance of the dispersing agents was modelled using machine learning in order to increase the efficiency of the dispersant design. The resulting models were presented as analytical models for the individual polyesters and the synthesis conditions for optimal performing dispersing agents were indicated as a preference for high molecular weight polyesters and a polyester dependent maximum weight ratio polyester/PEI.

Animation of TMCL model 6

Animation of TMCL model 6


Localized vibrational modes of GeV-centers in diamond: Photoluminescence and first-principles phonon study

Authors: Kirill N. Boldyrev, Vadim S. Sedov, Danny E.P. Vanpoucke, Victor G. Ralchenko, & Boris N. Mavrin
Journal: Diam. Relat. Mater 126, 109049 (2022)
doi: 10.1016/j.diamond.2022.109049
IF(2020): 3.315
export: bibtex
pdf: <DRM>


GeV split vacancy defect in diamond and the phonon modes near the ZPL.
Graphical Abstract: GeV split vacancy defect in diamond and the phonon modes near the ZPL.


The vibrational behaviour of the germanium-vacancy (GeV) in diamond is studied through its photoluminescence spectrum and first-principles modeled partial phonon density of states. The former is measured in a region below 600 cm−1. The latter is calculated for the GeV center in its neutral, charged, and excited state. The photoluminescence spectrum presents a previously unobserved feature at 248 cm−1 in addition to the well-known peak at 365 cm−1. In our calculations, two localized modes, associated with the GeV center and six nearest carbon atoms (GeC6 cluster) are identified. These correspond to one vibration of the Ge ion along with the [111] orientation of the crystal and one perpendicular to this direction. We propose these modes to be assigned to the two features observed in the photoluminescence spectrum. The dependence of the energies of the localized modes on the GeV-center and their manifestation in experimental optical spectra is discussed.

On the influence of water on THz vibrational spectral features of molecular crystals

Authors: Sergey Mitryukovskiy, Danny E. P. Vanpoucke, Yue Bai, Théo Hannotte, Mélanie Lavancier, Djamila Hourlier, Goedele Roos and Romain Peretti
Journal: Physical Chemistry Chemical Physics 24, 6107-6125 (2022)
doi: 10.1039/D1CP03261E
IF(2020): 3.676
export: bibtex
pdf: <PCCP>


Graphical Abstract: Comparison of the measured THz spectrum of 3 phases of Lactose-Monohydrate to the calculated spectra for several Lactose configurations with varying water content.


The nanoscale structure of molecular assemblies plays a major role in many (µ)-biological mechanisms. Molecular crystals are one of the most simple of these assemblies and are widely used in a variety of applications from pharmaceuticals and agrochemicals, to nutraceuticals and cosmetics. The collective vibrations in such molecular crystals can be probed using terahertz spectroscopy, providing unique characteristic spectral fingerprints. However, the association of the spectral features to the crystal conformation, crystal phase and its environment is a difficult task. We present a combined computational-experimental study on the incorporation of water in lactose molecular crystals, and show how simulations can be used to associate spectral features in the THz region to crystal conformations and phases. Using periodic DFT simulations of lactose molecular crystals, the role of water in the observed lactose THz spectrum is clarified, presenting both direct and indirect contributions. A specific experimental setup is built to allow the controlled heating and corresponding dehydration of the sample, providing the monitoring of the crystal phase transformation dynamics. Besides the observation that lactose phases and phase transformation appear to be more complex than previously thought – including several crystal forms in a single phase and a non-negligible water content in the so-called anhydrous phase – we draw two main conclusions from this study. Firstly, THz modes are spread over more than one molecule and require periodic computation rather than a gas-phase one. Secondly, hydration water does not only play a perturbative role but also participates in the facilitation of the THz vibrations.

The 0.5THz finger-print mode of alpha-Lactose Monohydrate.

The 0.5 THz finger-print mode of alpha-lactose monohydrate.

Deep Eutectic Solvents as Non-flammable Electrolytes for Durable Sodium-ion Batteries

Authors: Dries De Sloovere, Danny E. P. Vanpoucke, Andreas Paulus, Bjorn Joos, Lavinia Calvi, Thomas Vranken, Gunter Reekmans, Peter Adriaensens, Nicolas Eshraghi, Abdelfattah Mahmoud, Frédéric Boschini, Mohammadhosein Safari, Marlies K. Van Bael, An Hardy
Journal: Advanced Energy and Sustainability Research 3(3), 2100159 (2022)
doi: 10.1002/aesr.202100159
IF(2022): ??
export: bibtex
pdf: <AdvEnSusRes> (OA)


Graphical Abstract: Understanding the electronic structure of Na-TFSI interacting with NMA.


Sodium-ion batteries are alternatives for lithium-ion batteries in applications where cost-effectiveness is of primary concern, such as stationary energy storage. The stability of sodium-ion batteries is limited by the current generation of electrolytes, particularly at higher temperatures. Therefore, the search for an electrolyte which is stable at these temperatures is of utmost importance. Here, we introduce such an electrolyte using non-flammable deep eutectic solvents, consisting of sodium bis(trifluoromethane)sulfonimide (NaTFSI) dissolved in N-methyl acetamide (NMA). Increasing the NaTFSI concentration replaces NMA-NMA hydrogen bonds with strong ionic interactions between NMA, Na+, and TFSI. These interactions lower NMA’s HOMO energy level compared to that of TFSI, leading to an increased anodic stability (up to ~4.65 V vs Na+/Na). (Na3V2(PO4)2F3/CNT)/(Na2+xTi4O9/C) full cells show 74.8% capacity retention after 1000 cycles at 1 C and 55 °C, and 97.0% capacity retention after 250 cycles at 0.2 C and 55 °C. This is considerably higher than for (Na3V2(PO4)2F3/CNT)/(Na2+xTi4O9/C) full cells containing a conventional electrolyte. According to the electrochemical impedance analysis, the improved electrochemical stability is linked to the formation of more robust surface films at the electrode/electrolyte interface. The improved durability and safety highlight that deep eutectic solvents can be viable electrolyte alternatives for sodium-ion batteries.