SANTA: Smart and Automated Nanomanufacturing Technologies with Artificial Intelligence

With the rise of "nanomedicine" through the nanotechnology-enabled vaccines during the recent pandemic, there is a pressing need for advanced manufacturing technologies that can overcome the challenges of large-scale good manufacturing practice (GMP) production. Conventional methods for synthesizing pharmaceutical nanoparticles are limited by poorly characterised batch reactors, whilst relatively new technologies with flow systems in small (micrometre) scale enable precise control over nanoparticle features. Electrohydrodynamic (EHD) processes are a collection of state-of-the-art fabrication techniques that can generate structural features in micron to nano-size. Despite theoretical models and simulations to understand the mechanisms involved in EHD were developed, large-scale production with EHD is still hindered by the complex behaviour of the electrified jets and the lack of predictive models that encompass a plethora of process parameters. In addition, translation of the EHD process into industry is limited by human resources that possess expertise and multidisciplinary knowledge. This project aims to use machine learning (ML) as an extension of Industry 4.0 to regulate the key EHD process parameters as well as the workflow to achieve a sustainable manufacturing process and machine intelligence. Predictive and optimization ML algorithms will be developed to facilitate process monitoring and quality control through in-line systems and automation.