Tag: conference

Workshop Machine Learning for Coatings: ML in the Lab (day 5)

On the fifth and final day of the workshop we return to the lab. Our task as a group: optimize our raspberry pink lacquer with regard to hardness, glossiness and chemical resistance.

The four cans of base material made during day 1 of the workshop were mixed to make sure we were all using the same base material (there are already sufficient noise introducing variables present, so any that can be eliminated should be.). Next, each team got a set of recipes generated with the ML algorithm to create. The idea was to parallelise the human part of the process. This would actually also have made for a very interesting exercise to perform in a computer science program. It showed perfectly how bottlenecks are formed and what impact is of serial sections and access/distribution of resources (or is this just in my mind? 😎  ).  After a first round of samples, we already tried to improve the performance of our unit by starting the preparation of the next batch (prefetching 😉 ) while the results of the previous samples were entered into the ML algorithm, and that was run.

At the end of two update rounds, we discussed the results, there were already some clear improvements visible, but a few more rounds would have been needed to get to the best situation. A very interesting aspect to notice during such an exercise, is the difference in the concept of accuracy for the experimental side and the computational side of the story. While the computer easily spits out values in grams with 10 significant digits, at the experimental side of the story it was already extremely hard to get the same amounts with an accuracy of 0.02 gram (the present air currents give larger changes on the scale).

This workshop was a very satisfying experience. I believe I learned most with regard to Machine Learning from the unintentional observation in the lab. Thank you Christian and Kevin!  

 

Workshop Machine Learning for Coatings: Stochos and DGCN (day 4)

Day 4 of the workshop is again a machine learning centered day. Today we were introduced into the world of Gaussian Processes, and ML approach which is rooted in statistics and models data by looking at the averages of a distribution of functions…it is a function of functions. In contrast to most other ML approaches it is also very well suited for small data sets, which is why I had my eye on them already for quite some time. However, Gaussian Processes are not perfect and interestingly enough, their drawbacks and benefits seem quite complementary with the benefits and drawbacks to neural networks. Deep Gaussian Covariance Networks (DGCN) find their origin in this observation, and were designed with the idea of compensating the drawbacks of both approaches by combining them. The resulting approach is rather powerful and in contrast to any other ML approach: it does not have any hyper-parameter!!

Tomorrow, during the last day of the workshop, we will be using this DGCN to optimize our raspberry pink lacquers.

Workshop Machine Learning for Coatings: First Machine Learning (day 3)

Gartner hype cycle. Courtesy of Kevin Cremanns.

Gartner hype cycle. Courtesy of Kevin Cremanns.

Today the workshop shifted gears a bit. We left the experimental side of the story and moved fully into the world of machine learning. This change went hand-in-hand with a doubling of the number of participants, showing how a hot-topic machine learning really is.  Kevin Cremanns, who is presenting this part of the workshop, started by putting things into perspective a bit, and warned everyone not to hope for magical solutions (ML and AI have their problems), while at the same time presenting some very powerful examples of what is possible. A fun example is the robotic arm learning to flip pancakes:



During the introduction, all the usual suspects of machine learning passed the stage. And although you can read about them in every ML-book, it is nice to hear them discussed by someone who uses them on a daily basis. This mainly because practical details (often omitted in text-books) are also mentioned, helping one to avoid the same mistakes many have made before you. Furthermore, the example codes provided are extremely well documented, making them an interesting source of teaching material (the online manuals for big libraries like sci-kit learn or pandas tend to be too abstract, too big, and too intertwined for new users).

All-in-all a very interesting day. I look forward to tomorrow, as then we will be introduced into the closed source machine learning library developed at the University Hochschule Niederrhein.

Workshop Machine Learning for Coatings: Magical Humans (day 2)

Today was the second day of the machine learning workshop on coatings. After having focused on the components of coatings, today our focus went to characterization and deposition. The set of available characterization techniques is as extensive as the possible components to use. There was, however, one thing which grabbed my attention: “The magical human observer”. Several characterization techniques were presented to heavily rely on the human observer’s opinion and FingerspitzengefĂŒhl.  Sometimes this even came with the suggestion that such a human observer outperforms the numerical results of characterization machinery. This makes me wonder if this isn’t an indication of a poor translation of the human concept to the experiment intended to perform the same characterization. Another important factor to keep in mind when building automation frameworks and machine learning models.

In the afternoon, we again put on our lab coats and goggles. The task of the day: put our raspberry pink lacquer on different substrates and characterize the glossiness (visually) and the pendulum hardness.

Tomorrow the machine learning will kick in.

Workshop Machine Learning for Coatings (day 1)

Today was the first day of school…not only for my son, but for me as well. While he bravely headed for the second grade of primary school, I was en route to the first day of a week-long workshop on Machine Learning and Coatings technology at the Hochschule Niederrhein in Krefeld. A workshop combining both the practical art of creating coating formulations and the magic of simulation, more specifically machine learning.

During my career as a computational materials researcher, I have worked with almost every type of material imaginable (from solids to molecules, including the highly porous things in between called MOFs), and looked into every aspect available, be it configuration (defects , surfaces, mixtures,…) or materials properties (electronic structure, charge transfer, mechanical behavior and spin configurations). But each and every time, I did this from a purely theoretical perspective*. As a result, I have not set foot in a lab (except when looking for a colleague) since 2002 or 2003, so you can imagine my trepidation at the prospect of having to do “real” lab-work during this workshop.

Participating in such a practical session— even such a ridiculously simple and safe one— is a rather interesting experience. The safety-goggles, white-coat and gloves are cool to wear, true, but from my perspective as a computational researcher who wants to automate things, this gives me a better picture of what is going on. For example, we** carefully weigh 225.3 grams of a liquid compound and add 2.2 grams of another (each with an accuracy of about 0.01 gram). In another cup, we collect two dye compounds (powders), again trying our best to perfectly match the prescribed quantities. But when the two are combined in the mixer it is clear that a significant quantity (multiple grams) are lost, just sticking to the edge of the container and spatula. So much for carefully weighing (of course a pro has tricks and skills to deal with this better than we did, but still). Conclusion: (1)Error bars are important, but hard to define. (2) Mixtures made by hand or by a robot should be quite different in this regard.

For the theoretical part of my brain, mixing 10 compounds is just putting them in the same box and stir, mix or shake. Practice can be quite different, especially if you need 225 grams of compound A, and 2.2 grams of compound B. This means that for the experimentalist there is a “natural order” for doing things. This order does not exist at the theoretical side of the spectrum***, where I build my automation and machine learning. This, in addition to the implicit interdependence of combined compounds, gives the high-dimensional space of possible mixtures a rather contorted shape. This gives rise to several questions begging for answers, such as: how important is this order, and can we (ab)use all this to make our search space smaller (but still efficient to sample).

At the end of the day, I learned a lot of interesting things and our team of three ended up with a nice raspberry pink varnish.

Next, day two, where we will characterize our raspberry pink varnish.

 

Footnotes

* Yes, I do see how strange this may appear for someone whose main research focus is aimed at explaining and predicting experiments. 🙂
** We were divided in teams of 2-3 people, so there were people with actual lab skills nearby to keep me safe. However, if this makes you think I was just idly present in the background, I have to disappoint you. I am brave enough to weigh inanimate powders and slow flowing resins 😉 .
*** Computational research in its practice uses aspects of both the experimental and theoretical branches of research. We think as theoreticians when building models and frameworks, and coax our algorithms to a solution with a gut-feeling and FingerspitzengefĂŒhl only experimentalists can appreciate.

VSC-users day 2019

It is becoming an interesting yearly occurrence: the VSC user day. During this 5th edition, HPC users of the various Flemish universities gather together at the Belgian Royal Academy of Science (KVAB) to present their state-of-the-art work using the Flemish Tier-1 and Tier-2 supercomputers. This is done during a poster-presentation session. This year, I presented my work with regard to vibrational spectra in solids and periodic systems. In contrast to molecules, vibrational spectra in solids are rarely investigated at the quantum mechanical level due to their high cost. I show that imaginary modes are not necessarily a result of structural instabilities, and I present a method for identifying the vibrational spectrum of a defect.

Poster for the VSC user day 2019.

In addition, international speakers discuss recent (r)evolutions in High Performance Computing, and during workshops, the participants are introduced in new topics such as GPU-computing, parallelization, and the VSC Cloud and data platform. The possibilities of GPU were presented by Ehsan, of the VSC, showing extreme speedups of 10x to 100x, strongly depending on the application, the graphics card. It is interesting to see that simple CUDA prama’s can be used to obtain such effects
maybe I should have a go at them for the Hirshfeld and phonon parts of my HIVE code
if they can deal with quadruple precision, and very large arrays. During the presentation of Joost Vandevondele (ETH ZĂŒrich) we learned what the future holds with regard to next generation HPC machines. As increasing speed becomes harder and harder to obtain, people are again looking into dedicated hardware systems, a situation akin to the founding days of HPC. Whether this is a situation we should applaud remains to be seen, as it means that we are moving back to codes written for specific machines. This decrease in portability will probably be alleviated by high level scripting languages (such as python), which at the same time result in a significant loss of the initial gain. (Think of the framework approach to modern programming which leads to trivial applications requiring HPC resources to start.)

In addition, this year the HPC-team of the TIER-1 machine is present for a panel discussion, presenting the future of the infrastructure. The machine nearly doubled in size which is great news. Let us hope that in addition for financing hardware, there is also a significant budget considered for a serious extension of a dedicated HPC support team. Running a Tier-1 machine is not something one does as a side-project, but which requires a constant vigilance of a dedicated team to deal with software updates, resulting compatibility issues, conflicting scripts and just hardware and software running haywire because they can.

With this hope, I look toward the future. A future where computational research is steadily are every quickly is becoming common place in the fabric om academic endeavors.

MRS seminar: Topological Insulators

Bart Sorée receives a commemorative frame of the event. Foto courtesy of Rajesh Ramaneti.

Today I have the pleasure of chairing the last symposium of the year of the MRS chapter at UHasselt. During this invited lecture, Bart Sorée (Professor at UAntwerp and KULeuven, and alumnus of my own Alma Mater) will introduce us into the topic of topological insulators.

This topic became unexpectedly a hot topic as it is part of the 2016 Nobel Prize in Physics, awarded last Saturday.

This year’s Nobel prize in physics went to: David J. Thouless (1/2), F. Duncan M. Haldane (1/4) and J. Michael Kosterlitz (1/4) who received it

“for theoretical discoveries of topological phase transitions and topological phases of matter.”

On the Nobel Prize website you can find this document which gives some background on this work and explains what it is. Beware that the explanation is rather technical and at an abstract level. They start with introducing the concept of an order parameter. You may have heard of this in the context of dynamical systems (as I did) or in the context of phase transitions. In the latter context, order parameters are generally zero in one phase, and non-zero in the other. In overly simplified terms, one could say an order parameter is a kind of hidden variable (not to be mistaken for a hidden variable in QM) which becomes visible upon symmetry breaking. An example to explain this concept.

Example: Magnetization of a ferromagnet.

In a ferromagnetic material, the atoms have what is called a spin (imagine it as a small magnetic needle pointing in a specific direction, or a small arrow). At high temperature these spins point randomly in all possible directions, leading to a net zero magnetization (the sum of all the small arrows just lets you run in circles going nowhere). This magnetization is the order parameter. At the high temperature, as there is no preferred direction, the system is invariant under rotation and translations (i.e. if you shift it a bit or you rotate it, or both you will not see a difference) When the temperature is lower, you will cross what is called a critical temperature. Below this temperature all spins will start to align themselves parallel, giving rise to a non-zero magnetization (if all arrows point in the same direction, their sum is a long arrow in that direction). At this point, the system has lost the rotational invariance (because all spins point in  direction, you will know when someone rotated the system) and the symmetry is said to have broken.

Within the context of phase transitions, order parameters are often temperature dependent. In case of topological materials this is not the case. A topological material has a topological order, which means both phases are present at absolute zero (or the temperature you will never reach in any experiment no matter how hard you try) or maybe better without the presence of temperature (this is more the realm of computational materials science, calculations at 0 Kelvin actually mean without temperature as a parameter). So the order parameter in a topological material will not be temperature dependent.

Topological insulators

To complicate things, topological insulators are materials which have a topological order which is not as the one defined above 😯 —yup why would we make it easy 🙄 . It gets even worse, a topological insulator is conducting.

OK, before you run away or loose what is remaining of your sanity. A topological insulator is an insulating material which has surface states which are conducting. In this it is not that different from many other “normal” insulators. What makes it different, is that these surface states are, what is called, symmetry protected. What does this mean?

In a topological insulator with 2 conducting surface states, one will be linked to spin up and one will be linked to spin down (remember the ferromagnetism story of before, now the small arrows belong to the separate electrons and exist only in 2 types: pointing up=spin up, and pointing down=spin down). Each of these surface states will be populated with electrons. One state with electrons having spin up, the other with electrons having spin down. Next, you need to know that these states also have a real-space path let the electrons run around the edge of material. Imagine them as one-way streets for the electrons. Due to symmetry the two states are mirror images of one-another. As such, if electrons in the up-spin state more left, then the ones in the down-spin state move right. We are almost there, no worries there is a clue. Now, where in a normal insulator with surface states the electrons can scatter (bounce and make a U-turn) this is not possible in a topological insulator. But there are roads in two directions you say? Yes, but these are restricted. And up-spin electron cannot be in the down-spin lane and vice versa. As a result, a current going in such a surface state will show extremely little scattering, as it would need to change the spin of the electron as well as it’s spatial motion. This is why it is called symmetry protected.

If there are more states, things get more complicated. But for everyone’s sanity, we will leave it at this.  😎

tUL Life Sciences Research Day 2016

Yesterday was the tUL Life Sciences Research Day 2016. A conference event build around finding collaboration possibilities between the University of Hasselt in Belgium and the University of Maastricht (The Netherlands)…after all tUL is the “transnational University Limburg” which brings two universities together that are only separated some 26 km, but you have to cross a national border.

Although Life sciences itself is not my personal niche, I went to look for opportunities, as nano-particles which are used for drug delivery often consist of metals or oxides. These materials on the other hand are my niche. I used my current work on MOFs as a means to show what is possible from the ab-initio point of view, and presented this as a poster.

tUL Life Science Research Day 2016 Poster

Poster presented at the tUL Life Sciences Research Day, depicting my work on the unfunctionalized and the functionalized MIL-47(V) MOF.

Colloquium on Porous Frameworks: Day 2

Program Porous Frameworks ColloquiumOn Monday, we had the second day of our colloquium on Porous Frameworks, containing no less than 4 full sessions, covering all types of frameworks. We started the day with the invited presentation of Prof. Dirk De Vos of the KU Leuven, who discussed the breathing behavior in Zr and Ti containing MOFs, including the work on the COK-69 in which I was involved myself. In the MOFs presented, the breathing behavior was shown to originate from the folding of the linkers, in contrast to breathing due to the hinging motion of the chains in MIL-47/53 MOFs.

After the transition metals, things were stepped up even further by Dr. Stefania Tanase who talked about the use of lanthanide ions in MOFs. These lanthanides give rise to coordinated water molecules which appear to be crucial to their luminescence. Prof. Donglin Jiang, of JAIST in Japan, changed the subject to the realm of COFs, consisting of 2D porous sheets which, through Van Der Waals interactions form 3D structures (similar to graphite). The tunability of these materials would make them well suited for photoconductors and photoenergy conversion (i.e. solar cells).

With Prof. Rochus Schmid of the University of Bochum we delved into the nitty-gritty details of developing Force-Fields for MOFs. He noted that such force-fields can provide good first approximations for structure determination of new MOFs, and if structure related terms are missing in the force-field these will pop up as missing phonon-frequencies.

Prof. Monique Van der Veen showed us how non-polar guest molecules can make a MOF polar, while Agnes Szecsenyi bravely tackled the activity in Iron based MIL-53 MOFs from the DFT point of view. The row of 3 TU Delft contributions was closed by the invited presentation of Prof. Jorge Gascon who provided an overview of the work in his group and discussed how the active sites in MOFs can be improved through cooperative effects.

Prof. Jaroslaw Handzlik provided the last invited contribution, with a comparative theoretical study of Cr-adsorption on various silicate based materials (from amorphous silicate to zeolites). The final session was then closed by the presentations of Dr. Katrine Svane (Bath University) who discussed the effect of defects in UiO-66 MOFs in further detail and Marcus Rose presenting his findings on hyper-crosslinked Polymers, a type of COFs with an amorphous structure and a wide distribution in different pore sizes.

This brought us to a happy end of a successful colloquium, which was celebrated with a drink in the city center of Groningen. Tuesday we traveled back home, such that Wednesday Sylvia could start at the third part of the conference-holiday roller coaster by leaving for Saltzburg.

Colloquium on Porous Frameworks: Day 1

Program Porous Frameworks ColloquiumToday the CMD26 conference started in Groningen, and with its kick-off also our own 2-day colloquium on porous frameworks (aka MOFs, COFs and Zeolites) was launched. During the two sessions of the day, the focus mainly went out to the Zeolites, with Prof. Emiel Hensen of the Technical university of Eindhoven introducing us to the subject and discussing how new zeolites could be designed in a more rational way. He showed us how the template used during synthesis plays a crucial role in the final growth and structure. Dr. Nakato explained how alkali-metal nanoclusters can undergo insulator to metal transitions when incorporated in zeolites (it is due to the competition between electron-electron repulsion and electron-phonon coupling), while Dr. De Wijs informed us on how Al T-sites need to be ordered and assigned in zeolites to allow for the prediction of NMR parameters.

After the coffee break Dr. Palcic, from the Rudjer Boskovic Institute in Croatia, taught us about the role of heteroatoms in zeolites. She told us that even though more than 2 million theoretical structures exist, only 231 have officially been recognized as having been synthesized, so there is a lot more work to be done. She also showed that to get stable zeolites with pores larger than 7-8 Angstrom one needs to have 3 and 4-membered rings in the structure, since these lead to more rigid configurations. Unfortunately these rings are themselves less stable, and need to be stabilized by different atoms at the T-sites.

Dr. Vandichel, still blushing from his tight traveling scheme, changed the subject from zeolites to MOFs, in providing new understanding in the role of defects in MOFs on their catalytic performance. Dr. Liu changed the subject even further with the introduction of COFs and showing us how Hydrogen atoms migrate through these materials. Using the wisdom of Bruce Lee :

You must be shapeless, formless, like water. When you pour water in a cup, it becomes the cup. When you pour water in a bottle, it becomes the bottle. When you pour water in a teapot, it becomes the teapot.

he clarified how water behaves inside these porous materials. Our first colloquium day was closed by Ir. Rohling, who took us back to the zeolite scene (although he was comparing the zeolites to enzymes). He discussed how reactivity in zeolites can be tweaked by the confinement of the reacting agents, and how this can be used for molecule identification. More importantly he showed how multiple active site collaborate, making chemical reactions much easier than one would expect from single active site models.

After all was said and done, it was time to relax a little during the conference welcome reception. And now time to prepare for tomorrow, day 2 of our colloquium on porous frameworks.