Hybrid Materials

Research into future technologies has come to focus on miniature multi-material devices and nanostructures, with the intent of harnessing quantum mechanical phenomena to perform an automated function such as generating signals or separating atoms or charges. Organic and inorganic materials are frequently employed side-by-side to take advantage of their unique capabilities. While the properties of the individual substances or bulk materials are known, it is not always possible to predict or measure what occurs at the boundary between them.

We apply our electronic structure theory and machine learning methods to organic-molecule protected noble metal clusters, DNA-stabilized silver clusters, and organic films on inorganic semiconductors and metals. These systems hold great potential for applications in electronic devices, catalysis, biochemical sensing and medical treatments.


Bayesian inference of atomistic structure in functional materials, M. Todorović, M. U. Gutmann, J. Corander and P. Rinke, npj Comp. Mat. 5, 35(2019) 

Optical Properties of Silver-Mediated DNA from Molecular Dynamics and Time Dependent Density Functional Theory, E. Makkonen, P. Rinke, O. Lopez-Acevedo, and X. Chen, Int. J. Mol. Sci. 19, 2346 (2018) 

Charge-transfer driven nonplanar adsorption of F4TCNQ molecules on epitaxial graphene, A. Kumar, K. Banerjee. M. Dvorak. F. Schulz. A. Harju, P. Rinke and P. Liljeroth, ACS Nano 11, 4960 (2017)