Kinetic Monte Carlo method refers to a broad class of numerical algorithms utilizing random numbers to solve real-world problems. A physical system is propagated from state to state with transition probabilities which capture the physics of the systems and the environment, fulfilling the detailed balance. One obtains various characteristics such as single trajectories through the system or ensemble averaged measures such as current densities, mobilities, etc. Challenges arise from (i) the computational complexity, (ii) the accurate representation of molecules or solids, (iii) and to model the correct physics behind the processes. Our research covers the development of kMC methods for electronic and ionic transport, full solar cells or memristors, and hybrid electrochemical systems.
Covered Topics: C++ programming, software architecture, multiscale methods, various applications.
