Non-thermal Plasma Jet Sintering of Indium Tin Oxide (ITO) Thin Films based on Bayesian Optimization

Due to their stretchability, transparency, and biocompatibility, flexible devices are widely used in wearables, sensors, touch screens, and similar technologies. One approach to manufacturing flexible devices is the deposition of nanomaterial-containing inks using techniques such as ink-jet printing and screen printing. Once deposited, films need to be sintered to create a uniform film of the underlying nanomaterial. However, conventional sintering requires high temperatures, which creates challenges for heat-sensitive substrates such as those used in flexible devices. Non-thermal plasma jet sintering has emerged as a promising, cost-effective, and low-temperature technique to address this issue. This method employs a dielectric barrier discharge (DBD) plasma jet setup operating at room temperature and standard pressure, enabling the sintering of nanoink thin films without damaging the substrate or film surface. Previous studies have successfully utilized this technique to enhance the electrical conductivity of silver nanoparticle thin films with a controllable substrate temperature below 50 °C. In this research, we aim to optimize the electrical conductivity of indium tin oxide (ITO) thin films while ensuring a controlled substrate temperature below 30 °C. To achieve this, we employ a Bayesian optimization machine learning approach to identify the optimal settings for crucial input parameters, including jet flow rate, applied voltage, input frequency, gap distance, number of cycles, pulse-on time, and pulse-off time. The overall performance of non-thermal plasma jet sintering is compared to thermal sintering using identically fabricated ITO films as a benchmark.