Modelling of molecules, materials, and processes is nowadays an integral part of both academic and industrial research activities. In FinnCERES, the central role of modelling has been recognized from the early planning stages, and one of the key goals in building up the ecosystem has been the tight integration of experimental research and modelling.
The length scales spanned by FinnCERES modelling activities are stunning: our modelling groups research biomaterials and related processes from the level of individual electrons to the level of industrial plants. The variety of time scales is just as staggering: we can model femtosecond-scale vibrations of individual molecules, and on the other hand, we can study material deformations that happen over the timespan of several years! With almost 20 modelling research teams bringing their own expertise into the FinnCERES ecosystem, we are all set for discovering the biomaterials of future.
Modelling research has many kinds of roles in FinnCERES. At the very fundamental level, the purpose of modelling is to increase the molecular-level understanding of lignocellulosic biomass. Tailoring of functional lignocellulosic materials requires that we understand the structural details of lignocellulosic building blocks and their interactions with water. Here, molecular modelling offers atomic-level insights that can be combined with the experimental findings.
On a practical level, modelling is a sustainable and safe approach to biomaterials research, reducing the amount of experiments, human work, and chemicals. For example, let’s say that we would like to change the optical properties of nanocellulose crystals. In this case, it is much more cost efficient to build an atomistic model of the material, test the optoelectronic impact of hundred dopant molecules computationally, and focus experimental work only on the most promising 2-3 dopant molecules.
In FinnCERES, we have all the right building blocks for successful collaboration between modelling groups and experimental researchers. First, there has been a positive mindset of integrating modelling in our research activities right from the beginning. Second, there is a wide array of modelling expertise so that we can find a good match between the modelling know-how and experimental needs. And most importantly, the FinnCERES ecosystem is a true community where experimental and computational researchers meet and discuss regularly. It could easily take a year to build up good mutual understanding of a research problem, and this is particularly true for combining modelling and experimental research.
For a successful collaboration between modelling and experiment, the research problem has to be defined in such a way that the modelling people can build a reasonable model out of it. And the modelling results have to be translated back to useful inputs for the experiments. This can be a tough task, considering that often there can even be lack of mutual terminology in the beginning. The upside is that everybody’s understanding of the problem at hand typically improves already based on the initial discussions and planning sessions. That is, before any calculations have even been carried out!