Developing and Validating a High-Throughput Robotic System for the Accelerated Development of Porous Membranes
🤖 AI Summary
Traditional development of porous polymeric membranes relies heavily on manual trial-and-error, resulting in low efficiency and poor reproducibility.
Method: This study establishes an automated membrane fabrication and characterization platform based on non-solvent-induced phase separation (NIPS), integrating automated solution preparation, doctor-blade casting, controlled immersion precipitation, and in situ compression testing.
Contribution/Results: We introduce a novel approach that automatically infers membrane stiffness, porosity, and internal homogeneity from compression stress–strain curves—overcoming key limitations of conventional characterization. The modular architecture enables high-throughput parallel experimentation and seamless integration into self-driving laboratories. The system successfully reproduces established structure–property relationships governed by polymer concentration and ambient humidity, demonstrating its efficacy and reliability in precise parameter control, enhanced data consistency, and high-throughput screening. This work provides a scalable technological paradigm for intelligent membrane material development.
Application Category
📝 Abstract
The development of porous polymeric membranes remains a labor-intensive process, often requiring extensive trial and error to identify optimal fabrication parameters. In this study, we present a fully automated platform for membrane fabrication and characterization via nonsolvent-induced phase separation (NIPS). The system integrates automated solution preparation, blade casting, controlled immersion, and compression testing, allowing precise control over fabrication parameters such as polymer concentration and ambient humidity. The modular design allows parallel processing and reproducible handling of samples, reducing experimental time and increasing consistency. Compression testing is introduced as a sensitive mechanical characterization method for estimating membrane stiffness and as a proxy to infer porosity and intra-sample uniformity through automated analysis of stress-strain curves. As a proof of concept to demonstrate the effectiveness of the system, NIPS was carried out with polysulfone, the green solvent PolarClean, and water as the polymer, solvent, and nonsolvent, respectively. Experiments conducted with the automated system reproduced expected effects of polymer concentration and ambient humidity on membrane properties, namely increased stiffness and uniformity with increasing polymer concentration and humidity variations in pore morphology and mechanical response. The developed automated platform supports high-throughput experimentation and is well-suited for integration into self-driving laboratory workflows, offering a scalable and reproducible foundation for data-driven optimization of porous polymeric membranes through NIPS.
Problem
Research questions and friction points this paper is trying to address.
Automates porous membrane fabrication to reduce labor and trial-error
Integrates precise control of fabrication parameters for consistency
Enables high-throughput data-driven optimization of membrane properties
Innovation
Methods, ideas, or system contributions that make the work stand out.
Automated platform for membrane fabrication via NIPS
Modular design enables parallel processing and consistency
Compression testing estimates stiffness and porosity
🔎 Similar Papers
No similar papers found.
