Year: 2026
Type: article
Abstract: This work represents the first step toward the implementation of a self-driving laboratory for polymer foaming. We exploit robotics, process control, and simple optical measurements to conduct the foaming process and analyze the quality of the produced foam. The experiments are autonomously driven by a computer, and the product analysis allows the adaptive tuning of the foaming process. A robotic manipulator handles the polymer samples, and the control system is responsible for the experiment execution, supervision, and evaluation. We choose poly-ε-caprolactone as a reference polymer material, and we propose a novel approach for the measurement of the foam density and the qualitative assessment of its morphology. To this aim, the system includes a customized testing platform for 3D scanning and RGB image acquisition of the foam top surface, which can be easily extended to the measurement of other material properties. We describe the automated experimental workflow and define the advantages and limitations of the density measurement and morphology analysis. Besides granting process optimization and high-throughput experimentation, the development of a self-driving laboratory for polymer foaming promotes safety, innovative teaching methods, and enhanced sharing of resources, materials, and equipment with research institutions and industry partners. The collection of big data will foster the implementation of an AI-driven experimental management.
Source: ACS Omega
Institution: University of Naples Federico II
Language: English
Subfield: Polymers and Plastics
Field: Materials Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,935
Awards: G9000845084, G9000847767
OpenAlex ID: W7215106871