Junggeon Park, Joanne Hwang, Yujin Ahn, Jiye Lee, Christian Hurd, Hyegi Min, Sehong Kang, Freddy Ward, Simon A Rogers, Heidi Phillips, Rashid Bashir, Hyunjoon Kong
Surgical training phantoms are widely used for high-fidelity clinical training, human-machine interaction, and robotic manipulation. However, existing silicone- and hydrogel-based phantoms are limited by excessive elastic response, mechanical fragility, and rapid dehydration, resulting in inaccurate tactile feedback during clinical procedures. Here, we introduce PHANTOM (3D photolithographic, anti-drying, tough, and mechano-tunable) gels, an ECM-inspired single-network glycerogel platform that reproduces tissue-like softness, viscoelasticity, and toughness while maintaining long-term ambient stability. By systematically tuning acrylamide concentration and cross-linking density to regulate polymer entanglement and network density, we defined a predictable relationship between formulation and mechanics within a simple single-network architecture. A regression-based predictive framework was subsequently used to facilitate inverse design of gel formulations that replicate organ-specific viscoelastic signatures, including those of heart and liver tissues. Mechanically matched PHANTOM gels exhibited realistic tissue-relevant mechanical response during incision, suturing, and puncture testing, as well as gravity-dependent deformation consistent with native soft tissues. Furthermore, these gels enabled 3D fabrication of target organs, including heart and kidney, with accurate internal anatomies. Together, these results demonstrate that coordinated control of polymer network density and cross-linking provides a rational pathway to decouple toughness, softness, and viscoelastic dissipation within a single-network hydrogel system, establishing a scalable ECM-inspired strategy for patient-specific surgical simulation and organ phantom fabrication.