Towards Optimal Mixing: Enabling Autonomous Experimentation via Quantitative Emulsion Assessment

Hitoha Sato, YusakuNakajima, KESAAKI MINEMURA, Yuta Kawahara, Naotaka Tanaka, Kanta Ono

Published: 15 Mar 2026, Last Modified: 22 Apr 2026AI4X-AC 2026 PosterEveryoneRevisionsBibTeXCC BY 4.0
Submission Type: I want my submission to be considered for poster only
Keywords: Autonomous experimentation, Emulsification, Real-time mixing evaluation, Closed-loop optimization, Machine-learning-driven process optimization, Non-destructive in situ measurement
TL;DR: A real-time, non-destructive metric is proposed for quantitative evaluation of emulsification process toward closed-loop autonomous optimization.
Confirmation Of Submission Requirements: I submit an abstract. It uses the template provided on the submission page and is no longer than 2 pages.
PDF: pdf
Submission Number: 234