Allow me to congratulate you for being the recipient of the first Walter Thiel Award. What are your thoughts on receiving this honour?
I was very happy to receive the award. There were many important people along the way that acted as mentors and collaborators, and I want to say thank you to everyone who helped me. The one thing that has always fascinated me is the question of how we can get the most insight out of the computer simulations we perform and then later how we can use this information to develop new molecules… I was grateful that this task, gaining insight rather than just producing numbers, was recognised as being an important part of computational chemistry.
Could you elaborate a bit on your research interests?
We are interested in how molecules interact with light. Especially in materials science, researchers develop molecules for specific purposes – for example, for photovoltaics, for light emission, batteries, or optical sensors. If you have a specific application in mind, how do you know what the molecule should look like? You have three ways. One way is you synthesize lots of molecules and see if they do what you want them to do. The second way is, you do computations on a lot of molecules, and see what results you get. The third way is to understand the principles and then try to use those to build design rules. The third way is what drives me. More generally I am interested in how we can understand what happens behind the scenes rather than just producing data, and how we can really visualize what happens to the molecules during the processes we’re studying.
Being up to date with the latest technological developments must be crucial in your area. Could you give us some insight into what is happening on this forefront of science?
Technological advances have greatly increased the types of computations we can perform. But this also means that the amount of data produced increases greatly. We may run the supercomputer for a couple of hours and then at the end of the day, we just report one number, the energy. Now the question is – how can we do more? How can we draw pictures about the processes that happen and how can we learn more about the underlying physical developments. Let’s look at maybe something concrete. We want to know, for example, what happens to DNA after it gets hit by a photon in the sun. We can run computations that produce lots of data. But how do we talk about these results? Maybe a photon is absorbed by one DNA base, or two the same time. Maybe while the photon is absorbed an electron is transferred to a charged state? So the question is how we translate the results from computations into this kind of language.
How does the rapid development of Artificial Intelligence affect computational chemistry?
I’m kind of hesitant when it comes to AI. It can generate results but then you don’t know where these results come from. It may be more interesting to learn about the path of getting there rather than simply knowing the final outcome. This way, AI, in a sense hides the stuff that I’m interested in. If we can understand the equations, which may be obscured by AI, then we can make predictions about molecules without the need of running all the computations.
How does computational chemistry relate to more “traditional” areas of the discipline
I work a lot with synthetic chemists. Sometimes they made the molecule, and then they just want one picture or one number to support their paper. But sometimes it is really about developing new molecules on the computer. We are trying to understand design rules: what do the underlying equations tell us about what the molecule has to look like? You have to have this feedback loop where, from the computational/theoretical side, you tell the synthetic chemists what the molecule should look like – then, they synthesize it.
Can you describe some of the challenges computational chemists face?
A big challenge is how the field will be redefined by machine learning and artificial intelligence. The question is, how our work will look in 10 or 20 years when it’s much more prominent. I mean, computational chemistry is the field that really profits from all the technological advances – but we have to adapt. I think it’s interesting when I compare what I’m doing now to what I did 15 years ago for my master’s thesis. What seemed really cutting edge 15 years ago is just routine now. On the one hand, I think modern technologies allow us to do things we were not able to do before, so this is a very exciting time for computational chemistry – but the challenge is facing how these developments will change the field.
You have mentioned your master’s thesis. Thinking about those young chemists who are considering Computational Chemistry as their future subject – is there anything you wish you would’ve known during this time, or at the beginning of your career?
My advice is: learn how to program and automate things. The amazing thing about computational chemistry is that you can just write a little computer program that does all repetitive tasks automatically. Often you see people just doing the same thing over and over again. In a traditional lab you kind of have to do it: you have to do the same column chromatography 20 times in a row – but if you work on a computer, you just need to write a little program that does this for you. You can make your life easier by learning all the different tools for automating things, for visualisation, etc.
A bit later, when you start having your own thoughts and ideas, be brave and pursue those ideas, do the things that fascinate you. When you start out, you still see things from a different perspective, use this to your advantage to build up your unique profile.
What would you consider your biggest achievement?
During my PhD I wrote a few lines of code that allow us to analyse quantum chemistry computations of excited states. Later, after my son was born, I decided to release the code and named it after him, using the acronym TheoDORE (theoretical density orbital relaxation and exciton analysis). At the time, this was mostly a joke, and I did not expect that people would actually download the code. But then it really took off. Now, whenever I go to a conference, people tell me about how they are using TheoDORE in their work. It makes me proud that I could develop something that makes a difference to so many people.
Thank you – this interview is coming to an end, but we would be delighted to hear any final thoughts or messages you have for our readers.
Generally speaking, enjoy your work and be brave. Be brave to apply for a job, even if you feel you are not ready for it. Be brave to pursue your ideas, even if others tell you they are not relevant.