Upp ur Kaninhålet: Multiskalemodellering för Hållbara Material

Density-functional theory (DFT) calculations can allow researchers to predict material properties based on atomic structures. However, such programs are limited to around 103 atoms. This is far from the molar (1023) level, and the view of a full device is even more clouded. The idea of this postdoc application is to develop a multiscale method that bridges this massive gap.

That would yield wider material insights. Also, the speed of computational testing makes it possible to screen materials that would otherwise not be tested.

While the vision of doing multiscale modeling for every field is huge, we will begin concretely by developing a combined macroscale/mesoscale/microscale method for modeling the charging of sodium-ion batteries with Prussian blue analogs (PBA) and sodium vanadium phosphates (SVP).

The next step is to develop, formalize, and classify algorithms for integrated multiscale modeling with these materials. We will then expand to other applications in batteries and beyond together with our collaboration partners.

The preliminary results indicate how finite element (FEM) and tight-binding density functional theory (DFTB) can be combined to predict device-level performance with PBA electrodes without first synthesizing the material.

Put together, this postdoc could have massive long-term benefits for many fields through improved material development using effective multiscale modeling.