Multiscale Computational Study of Electronic Structure and Properties of Electrochemical Nano-Systems
Authors: Gusarov Sergey 
Published: February 2020

Over the past few decades the electrochemistry of nano-sized systems has shown a strong growth worldwide in many areas of research and proved its significance in today’s competitive environment. However, there still remains an enormous potential for further development which could revolutionize many areas of human life. Unfortunately, in some cases, that potential is screened out by complexity and multilevel character of systems and processes at a nanometer scale. The success of future applications in a high-tech industry requires deep understanding of fundamental mechanisms on different levels of description and their communication. That could be provided only by appropriate combination of experimental study with predictive theoretical modeling. Nowadays, more and more scientists in different fields of chemistry are using computational modeling methods in their research, either as a technique per se, or as a complement to experimental work. However, despite the increasing attention to computational nanoscience and biology the specificity of application of standard theoretical and computational modeling in nanotechnology is complicated due to complexity of the systems of interest and needs to be discussed separately, especially in the view of multilevel representation of systems and processes on nanoscale.

Modern methods of computational chemistry comprise a variety of approximations allowing to model relatively simple properties as well as complex processes such as catalytic reactions or electronic transport. One of the major tasks of computational chemistry in electrochemistry is to explore a large number of potential systems in order to select the most appropriate candidates for further detailed study. Sometimes this leads to many difficulties because the computational cost increases exponentially with complexity of process of interest. For example, the modeling of chemical reactions on electrode requires to explore the multidimensional potential energy surface (PES) in reaction coordinates (distances, orientations …) which could be very complex. From other side for the task of preliminary selection one does not need a high accuracy and simple estimation is often enough. In that case the computationally expensive modeling could be efficiently replaced by study of appropriate precursors.

It is well known that chemical reactions are mainly defined by wave function/electronic density of active regions, so the study of electronic structure of the atoms directly involved in the reaction of interest could provide valuable information for the preliminary analysis. Moreover, recently a number of efficient methods to study of electronic structure was developed which allows in combination with multiscale approximations quickly and efficiently model a large systems. Unfortunately many of that approximations are not frequently used in practical applications and researchers are still operate with simplified models (like HOMO/LUMO model) which are easy understandable and intuitive but does not count many things (methodological and physical/chemical), like dependence from DFT-functional, density redistribution and orbitals correlation, etc.

The work reviews the latest achievements in the development of electronic structure analysis methods [1] (Fukui indexes, fragment analysis, transition orbitals, transmission spectra, etc.) and their application to study electronic structure of complex systems. The presentation is supplemented by a number of practical examples that shows how the new tools could improve the quality of analysis.

E. Baerends, T. Ziegler, J. Autschbach, D. Bashford, A. Bérces, F. Bickelhaupt, C. Bo, P. Boerrigter, L. Cavallo, D. Chong, L. Deng, R. Dickson, D. Ellis, M. van Faassen, L. Fan, T. Fischer, C. Guerra, M. Franchini, A. Ghysels, A. Giammona, S. van Gisbergen, A. Götz, J. Groeneveld, O. Gritsenko, M. Grüning, S. Gusarov, F. Harris, P. van den Hoek, C. Jacob, H. Jacobsen, L. Jensen, J. Kaminski, G. van Kessel, F. Kootstra, A. Kovalenko, M. Krykunov, E. van Lenthe, D. McCormack, A. Michalak, M. Mitoraj,S. Morton, J. Neugebauer, V. Nicu, L. Noodleman, V. Osinga, S. Patchkovskii, M. Pavanello, P. Philipsen, D. Post, C. Pye, W. Ravenek, J. Rodríguez, P. Ros, P. Schipper, G. Schreckenbach, J. Seldenthuis, M. Seth, J. Snijders, M. Solà, M. Swart, D. Swerhone, G. Velde, P. Vernooijs, L. Versluis, L. Visscher, O. Visser, F. Wang, T. Wesolowski, E. van Wezenbeek, G. Wiesenekker, S. Wolff, T. Woo and A. Yakovlev, Amsterdam Density Functional 2013, SCM, Theoretical Chemistry, Vrije Universiteit, Amsterdam, The Netherlands, 2013

Figure 1