(1231-D) Automating Agrochemical Formulation Development

Abstract: Agricultural products must perform reliably in a wide variety of temperatures, water conditions as well as final use equipment. The vast number of choices a formulation scientist is facing when developing a new product, led the team to seek out innovative approaches to automating solids and liquids dispensing to produce formulated agrochemical probe samples. With a focus on sustainable practices, the high throughput automation team seeks to maximize experimental data value and minimize research waste through utilization of adaptive experimentation as well as machine learning. Discussed herein will be innovative approaches to I) prepare formulations (sample dispense, mixing and milling) II) characterize the formulations produced and III) utilizing the information collected to design new products via machine learning and adaptive experimentation.