My name is Bruno and I’m a postdoctoral fellow in the group of Michel Côté  at the University of Montréal. Our group focuses on developing “beyond ab initio” numerical methods in order to model organic molecules, polymers and interfaces for applications in organic photovoltaics.

Organic materials offer great promises for photovoltaic applications, mainly because they would be very cheap to produce. Indeed, we are constantly surrounded by plastics of various kinds, so there already exists a large chemical industry that can handle vats of the stuff. Wouldn’t it be great if you could just buy 100 square meters of rolled up photovoltaic plastic films at a local hardware store, unfurl it on the roof at home and get some of the Sun’s sweet power for (almost) free?

Well that’s still science fiction at this point but our group’s goal is to help make it happen. There are very many possible organic compounds and polymers,and exponentially more possible combinations which could do the trick. It’s like looking for a needle in a haystack, really. My colleagues in organic chemistry tell me it takes a student one year to create a new compound; that’s a lot of resources lost if the compound turns out to be a dud. Chemists of course have great intuition, and can discard some unlikely candidates right away. However, it is not always so obvious from the start whether a given molecule will have all the right properties for photovoltaic applications; that’s where we come in.

It is much cheaper to simulate numerically the properties of a new candidate molecule than to actually cook it in the lab and then measure its properties. The theory behind those models isn’t perfect of course, and experimental measurements have the last word, but efficient simulation tools can allow us to scan large databases of candidates and discard the crazies, leaving only probable candidates for further investigation. The rub lies in having an algorithm which is precise
enough to be useful, but runs fast enough so we can simulate those large organic molecules! We have been working hard on developing such a method, and we hope
to produce exciting results soon!

Colleagues and I visited the group of Professor Holdcroft at Simon Fraser in Vancouver at the beginning of April (see our photojournal of the trip here ). From our very engaging discussions with Professor Holdcroft and his students emerged a fact well known to experimentalists, but perhaps sometimes glossed over by ab initio-ists such as myself: morphology is critical to good performance! Indeed, photovoltaic devices rely on bulk heterojunctions to harvest the Sun’s energy: an electron donor compound is mixed with an electron acceptor (often PCBM), forming an intricate network of domains at whose interfaces excitons must dissociate and through which charge carriers must percolate. Obviously the shape, size and orientations of these domains will affect device performance greatly, and knowing the energy levels of single molecules are not sufficient to fully characterize the performance one can hope to reach with a given device. Furthermore, the ideal material should self-assemble to the optimal geometry without excessive human intervention; the more complicated the steps that are needed, the higher the cost of the final product!

Therein lies a bit of a terra incognita for me. I think we can do a great job at predicting the properties of a single molecule or polymer, but how can we scale up our modeling, and use the appropriate microscopic information to predict the behavior of mesoscopic (or even macroscopic) devices? This is a topic I want to know more about! Thanks for reading, and it was great to see you all in Hamilton at the 2013 Next Generation Solar conference!

Bruno Rousseau

-Bruno Rousseau

Postdoctoral Fellow

Department of Physics, University of Montreal

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