The group researches basic plasma physics and various plasma applications including plasma sources for microelectronics and electric grid, electric propulsion, plasma synthesis of nanomaterials, and machine learning methods for plasma science and technology.
Plasma reactors are used in semiconductor and quantum device nanofabrication for etching or deposition of surface materials by generating various chemically active species. Plasma reactors for etching typically operate at low pressure (less than ~100mTorr) while plasma reactors for deposition operate at high pressure (>100Torr). Correspondingly, we use particle-in-cell codes for modeling of low-pressure reactors and CFD (computational fluid dynamics) for high-pressure reactors. Surface and volume chemistry is modeled using ab initio quantum chemistry codes (see the modeling tools section). Extensive validation and verification procedures are used to ensure the accuracy of predictive modeling. Theoretical analysis is carried out to verify the code results and to develop an understanding of complex processes and scaling laws.
Plasma devices used for electric grid applications (i.e. plasma switches) and electric propulsion typically operate at low pressure (less than ~100 mTorr up to microTorr). We use state of the art particle-in-cell codes to model these plasmas, which are often subject to various instabilities that lead to anomalous transport or structure formation. Using theory and simulations, our group aids in the development of new plasma systems and the optimization of existing designs.
For many applications, an easy way to control plasma parameters and to deliver energy to the system is by injecting particle beams into the plasma. Correspondingly, beam - plasma interactions are important for such cases. Collective phenomena such as streaming and filamentation instabilities are studied using PIC simulations and analytical theory.
Recently, plasmas have been used to synthesize various nanomaterials (graphene, carbon and boron nitride nanotubes, nanodiamonds, etc.). We use integrated modeling involving a fluid description of the plasma combined with quantum chemistry models for the reactions involved in the growth of nanomaterials. This integrated modeling enables us to describe these complex processes and optimize plasma reactors for nanomaterial synthesis.