The aim of this work is to build a numerical model of hydrogen plasma inside a microwave plasma chemical vapor deposition system. This model will help in understanding and optimizing the conditions for the growth of carbon nanostructures. A 2D axisymmetric model of the system is implemented using the finite element high frequency Maxwell solver and the heat transfer solver in COMSOL Multiphysics. The system is modeled to study variation in parameters with reactor geometry, microwave power, and gas pressure. The results are compared with experimental measurements from the Q-branch of the H2 Fulcher band of hydrogen using an optical emission spectroscopy technique. The parameter γ in Füner's model is calibrated to match experimental observations at a power of 500 W and 30 Torr. Good agreement is found between the modeling and experimental results for a wide range of powers and pressures. The gas temperature exhibits a weak dependence on power and a strong dependence on gas pressure. The inclusion of a vertical dielectric pillar that concentrates the plasma increases the maximum electron temperature by 70%, the maximum gas temperature by 50%, and the maximum electron number density by 70% when compared to conditions without the pillar at 500 W and 30 Torr. Experimental observations also indicate intensified plasma with the inclusion of a pillar.
Microscale plasma actuators operate at lower voltages than their macroscale counterparts and allow easy integration into microsystems. Field-emission driven microplasma actuators can be applied for gas flow enhancement in microchannels for pumping and microcombustion applications. The present work studies the feasibility of microplasma actuation as a pump for gaseous microchannel flow. We use 2D Particle-In-Cell / Monte Carlo Collisions (PIC/MCC) method to calculate the volumetric force generated by field-emission driven micro dielectric barrier discharge (DBD). The simulations show that the induced volumetric force and heat source scale inversely with the dielectric thickness. A volumetric force of 1000 μN/mm3 with Joule heat source of 6 W/mm3 for an input power of 16 mW/m was obtained for a dielectric thickness of 3 μm per DBD. This force couples with the momentum flow in the microchannel in the solution of the Navier-Stokes equations. The flow enhancement increased with the decreasing Reynolds number (Re). In a long microchannel (40 mm) at Re = 73, the actuation lead to 22% increase in mass flow rate. However the vorticity induced by heating reduced this gain by 0.03%. In a short microchannel (1.5 mm) without pressure gradient, the actuator induced flow rate was found to be higher than that of a conventional DBD pump. The inclusion of heat source further enhanced the flow by 0.05% in the short channels.
This work presents a new user-friendly lyophilization simulation and process optimization tool, freely available under the name LyoPRONTO. This tool comprises freezing and primary drying calculators, a design-space generator, and a primary drying optimizer. The freezing calculator performs 0D lumped capacitance modeling to predict the product temperature variation with time which shows reasonably good agreement with experimental measurements. The primary drying calculator performs 1D heat and mass transfer analysis in a vial and predicts the drying time with an average deviation of 3% from experiments. The calculator is also extended to generate a design space over a range of chamber pressures and shelf temperatures to predict the most optimal setpoints for operation. This optimal setpoint varies with time due to the continuously varying product resistance and is taken into account by the optimizer which provides varying chamber pressure and shelf temperature profiles as a function of time to minimize the primary drying time and thereby, the operational cost. The optimization results in 62% faster primary drying for 5% mannitol and 50% faster primary drying for 5% sucrose solutions when compared with typical cycle conditions. This optimization paves the way for the design of the next generation of lyophilizers which when coupled with accurate sensor networks and control systems can result in self-driving freeze dryers.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.