Bethel College

This work introduces FiberPro 1.0, a large language model-driven multi-agent framework that couples high-throughput focused rotary jet spinning (FRJS) with real-time experimental feedback, converging on spinnable formulations within an average of about two iterations for three proteins with no prior FRJS precedent (soy protein isolate, keratin, bovine serum albumin), and uses it to design a zein-poly(ethylene oxide)-curcumin (Zein-PC) active coating that deposits conformally on diverse produce and combines antibacterial and antioxidant activity, pH-responsive colorimetric sensing, and image-based shelf-life prediction.

This work introduces FiberPro 1.0, a large language model-driven multi-agent framework that couples high-throughput focused rotary jet spinning (FRJS) with real-time experimental feedback, converging on spinnable formulations within an average of about two iterations for three proteins with no prior FRJS precedent (soy protein isolate, keratin, bovine serum albumin), and uses it to design a zein-poly(ethylene oxide)-curcumin (Zein-PC) active coating that deposits conformally on diverse produce and combines antibacterial and antioxidant activity, pH-responsive colorimetric sensing, and image-based shelf-life prediction.