Spray drying is a versatile and well-established technique used to produce materials with precisely controlled morphologies, enabling the generation of nanostructured particles with high surface area and purity, suitable for diverse applications. This review explores the optimization of spray drying parameters such as inlet temperature, air velocity, nozzle type, and precursor characteristics, which are critical for achieving desired particle characteristics such as size, shape, and morphology. The review discusses the broad industrial applications of spray drying, including the creation of pigments, catalysts, cosmetics, and drug delivery systems, and highlights various particle structure such as hollow, porous, and encapsulated particles, which offer specific benefits for different applications. Furthermore, it emphasizes the importance of integrating experimental and theoretical approaches, including computational fluid dynamics (CFD), to advance the understanding and optimization of the spray drying process. By providing review on the recent advancements and methods in spray drying technology, this paper offers valuable insight for researchers and professionals aiming to enhance material design and process efficiency for a range of industrial applications.
In clean rooms for semiconductor manufacturing processes, automation and robotization are being promoted to reduce the number of workers, but workers are still the main source of particle generation. Reducing particle generation is an important issue not only from the perspective of improving product yield, but also from the perspective of energy conservation by reducing the number of ventilation cycles. Various studies have been conducted on the amount of particle generated by workers performing simulated operations. However, these studies lacked reproducibility because the simulated motions were categorized by the type and number of movements and did not consider individual differences among subjects, such as arm swing width and swing force. In this paper, we used optical motion capture to capture simulated motions in real time, simultaneously measuring motion intensity and evaluating particle generation. We devised a method to measure particle separately from body-derived and exhalation-derived particles, evaluated and discussed it together with the measurement of motion intensity.