Mateusz Jackowski

The advancement of plasma technology is intricately linked with the utilization of computational fluid dynamics (CFD) models, which play a pivotal role in the design and optimization of industrial-scale plasma reactors. This comprehensive compilation encapsulates the evolving landscape of plasma reactor design, encompassing fluid dynamics, chemical kinetics, heat transfer, and radiation energy. By employing diverse tools such as FLUENT, Python, MATLAB, and Abaqus, CFD techniques unravel the complexities of turbulence, multiphase flow, and species transport. The spectrum of plasma behavior equations, including ion and electron densities, electric fields, and recombination reactions, is presented in a holistic manner. The modeling of non-thermal plasma reactors, underpinned by precise mathematical formulations and computational strategies, is further empowered by the integration of machine learning algorithms for predictive modeling and optimization. From biomass gasification to intricate chemical reactions, this work underscores the versatile potential of plasma hybrid modeling in reshaping various industrial processes. Within the sphere of plasma catalysis, modeling and simulation methodologies have paved the way for transformative progress. Encompassing reactor configurations, kinetic pathways, hydrogen production, waste valorization, and beyond, this compilation offers a panoramic view of the multifaceted dimensions of plasma catalysis. Microkinetic modeling and catalyst design emerge as focal points for optimizing CO2 conversion, while the intricate interplay between plasma and catalysts illuminates insights into ammonia synthesis, methane reforming, and hydrocarbon conversion. Leveraging neural networks and advanced modeling techniques enables predictive prowess in the optimization of plasma-catalytic processes. The integration of plasma and catalysts for diverse applications, from waste valorization to syngas production and direct CO2/CH4 conversion, exemplifies the wide-reaching potential of plasma catalysis in sustainable practices. Ultimately, this anthology underscores the transformative influence of modeling and simulation in shaping the forefront of plasma-catalytic processes, fostering innovation and sustainable applications.

Due to current trends in beer consumption, as well as social aspects, such as the education of society on combining drinking and driving, intensive research and development efforts have been recently focused on producing low-alcohol beers and non-alcoholic beers with a sensory profile appealing to consumers. There are plenty of methods for obtaining such beverages; one of these methods involves utilizing non-conventional yeasts for wort fermentation. In this work, the production of low-alcohol beer using commercially available Saccharomycodes ludwigii and Torulaspora delbrueckii strains were compared. The results showed that Torulaspora delbrueckii achieved the lowest level of attenuation, producing beer with an ethanol concentration of 2.58% vol. Saccharomycodes ludwigii displayed a slightly higher level of attenuation; however, its alcohol concentration was slightly lower than in the case of Torulaspora delbrueckii and reached 2.50% vol. Fully fermented beers produced using Saccharomycodes ludwigii and Torulaspora delbrueckii represented reduced ethanol concentrations by 12% and 15%, respectively, in comparison to Saccharomyces cerevisiae. Nevertheless, in order to produce non-alcoholic beers, arrested fermentation is necessary. In such a case, Saccharomycodes ludwigii reached the highest level of attenuation among non-alcoholic beers.