Computational Modelling of Polymers: A Coffee with Christophe

In our interview series, "A Coffee with…," we give the floor to our awesome colleagues. Christophe kicks things off by shedding light on the decisive role of Molecular Dynamics Simulations in polymer research. But why are these simulations garnering such attention, and what crucial insights do they offer?

Let’s start with the warm-up and a first simple question: Tea, coffee, or water?  
Coffee, 2 sugars, with milk! At home, I usually go for oat milk, but I’m not fussy. 
 

What would you title your autobiography?  
"When Belgian Chocolate Meets English Toffee: Global Adventures with Science." 
Toffee is my nickname and I’m from Belgium, hence the slight pun. I think the autobiography would have to focus on my experiences living in 7 different countries and my continued education in scientific subjects (and beyond)! 
 

What's your favorite element from the periodic table and why?  
I think all scientists end up answering this question with the element that featured most heavily in their PhDs, and I’m afraid I’m no exception here. Strontium! We use it in atomic physics for laser cooling and doing some very cool (pun perhaps slightly intended...) physics. Actually, one of my favorite memories about visiting the lab I worked together with was seeing a little ball of ultracold strontium atoms, sitting in their little trap, glowing a beautiful blue color. Beyond that, though, strontium has a bunch of different isotopes (even the nuclear physics of strontium is fascinating), and it has two electrons in its outer shell, making the actual chemistry complicated enough to be interesting but not too complicated to understand! 

Cool, let's delve further into science, specifically focusing on molecular dynamics, where you are an expert. 

Molecular Dynamics Simulations, and beyond, are becoming more and more indispensable as tools to support research in polymers. Can you tell us what are the most important insights you can derive from an in-silico approach?  
To me, the most important insights are always related to the underlying physics. You can do experiments in the lab or pen-and-paper theoretical work for as long as it takes, but neither approach can quite give you the insights that just watching atoms move around in a simulation will give you. 

There are, of course, several important caveats to keep in mind while running simulations, but overall, the trends are usually well reproduced by atomistic simulations, and it’s these trends that tell you exactly what’s going on in your experiment. So instead of having endless trial-and-error experiments to gain insights into the physics, you can run a few simulations and get those same insights much faster, and with more mechanistic detail! 

You are our expert in polymers, chemical formulations, and related properties. What is so challenging in the investigation of such systems with molecular dynamics simulations?  
Well, I guess there are two main issues at hand here. Firstly, the approximations that are made to enable these molecular dynamics can be a bit drastic, depending on the system. In particular, the way the forces are calculated can give wrong results if you’re not careful, so it’s important to pay attention to the details here. Secondly, you have to make sure that your simulation really is a model of the experiment! It’s easy to throw a bunch of molecules in a box, but that isn’t necessarily going to look like how those molecules would be set up in your experiment. Sometimes, a bit of care must be taken to ensure that you’re simulating the right thing. 
 

In your daily work, you support the software development team to implement simulation tools into our QuantistryLab. How do you translate scientific theories and concepts into a cloud-based platform? What are the challenges? And the final objective?  
A lot of tools and scientific theories have existed for a long time, and the molecular dynamics field is mature enough that we can rely on these standard tools. That said, I would say the biggest roadblock is the automation of the setup for running simulations. As academic researchers, it’s easy to fiddle a little bit and get something to work using some customized setup for every different simulation, but to make a cloud-based platform you have to fully account for every different possible scenario. As for the final objective... I’m not sure there is one per se! There are always new theories, new methods, etc. Coming out of academic research, and in the end, our goal is to make these accessible to our clients without making the platform prohibitively complicated. 
 

You are a theoretical physicist. We love that. What is the most mind-boggling theory you have learned?  
There are so many to choose from! I could go into detail on a bunch of different things that are mind-boggling in the sense that they’re just really hard to wrap your head around (most of quantum mechanics, for example). Instead, I think I’ll answer this with something that stood out during my undergraduate course as a complete “wow, that’s crazy” moment. 

There’s a set of 4 equations called Maxwell’s equations that basically cover everything you may want to know about electricity and magnetism. Now, if you just say “well if there’s no charge, let’s just consider empty space and see what we get” what you get is... light! Specifically, you can derive the speed of light. At the time this completely blindsided me, because I totally didn’t expect that. Just goes to show how much of physics is interconnected! 
 

And last, but not least, as a final question: Which scientist from any era would you like to have a coffee with? 
I’ll have to go with Marie Sklodowska Curie. I think she’s probably one of the most impressive human beings that ever lived, with a drive and an intelligence that put her head and shoulders above most scientists of the time despite so many roadblocks in her way. Though I think I’d probably be extremely intimidated by the whole interaction!

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