My research focuses on in silico studies of the morphological phenomena in engineered and natural heterogeneous systems with application to energy, nanotechnology, biomedical engineering, and materials science. Put simply, morphology is a spatial distribution of vastly different mediums, and is critical to the performance of many engineering systems, such as organic solar cells, batteries or drug delivery systems. The ability to understand morphology and to link it with properties of devices (e.g. optical, mechanical, chemical, etc.) has a potential to change how such devices are designed, leading to faster, more economical and more environmentally friendly manufacturing. Integration of computational thinking with experimental techniques makes a unique combination that underpins scientific progress. Specifically, such a combination is indispensable to study nanoscale systems, where purely experimental approaches, although impressive, are still limited, due to the interplay between resolution and accessible domain size, and their complexity and prohibitive cost. I have significant experience in scientific computing - many years of prototyping and development of scientific applications for computational physics, especially thermomechanics and materials science. In my work, I combine efficient numerical methods with high performance computing techniques to tackle large scale problems arising in my application domain.
Computational mechanics, computational materials science, heat and mass transfer, renewable energy, solar cells, batteries, nanocharacterization of 2D and 3D nanomaterials, modeling nanomanufacturing, accelerated design of materials, linking process–structure–property, numerical modeling of morphology evolution, computational fluid dynamics, multi-phase flow, micro-fluidics, optimization, scientific computing, high-performance computing and large-scale problems.