This award is made in response to Dear Colleague Letter 24-130, as part of the ECosystem for Leading Innovation in Plasma Science and Engineering (ECLIPSE) interdisciplinary program. The award supports an effort to advance the predictive modeling capabilities of low-temperature plasmas (LTPs) for improved fabrication of microelectronics systems. LTPs are weakly ionized gases that play an important role in many industrial applications, including materials processing, spacecraft propulsion, and hypersonic flights. Predictive models of LTPs can help to advance the understanding of how to control physical and chemical processes within a low temperature plasma, and how to design the next-generation industrial systems. The main objective of this project is to develop theoretically accurate and computationally efficient models that can capture the critical physical and chemical processes in LTPs. The research will be conducted in conjunction with Applied Materials, which will help enhance industry workforce development in the United States. Fluid equations are typically derived by taking the moments of the first-principles gas kinetic equations, such as the Boltzmann equation. The main problem of the state-of-the-art fluid models for LTPs, including drift-diffusion models and local approximation, is the inability to account for nonlocal effects of electrons. While kinetic models, such as particle-in-cell Monte Carlo collision simulations, capture such nonlocal phenomena, the co