Silicone/PDMS test coupons engineered to reproduce skin-like wetting behavior by controlling contact-line pinning, spreading, smearing, and transfer of complex aqueous fluids. Combines oxide infiltration, patterned chemistry, and laser micro/nanotexturing to tune friction and wetting hysteresis. Designed for consumer product testing, skin-contact applications, and formulation development; supported by validated wetting models and open-source simulations.
The offering is a family of silicone/PDMS test surfaces, or coupons, engineered to behave like human skin when interacting with complex aqueous fluids. Conventional silicone materials tend to shed fluids because of their low surface energy; these coupons address that by controlling contact-line pinning and wetting hysteresis at the surface. The result is a platform for reliably reproducing skin-like spreading, smearing, transfer, and friction behavior in controlled laboratory and product-development settings.
Potential applications include evaluation of skincare, cosmetic, and rinse-off formulations; consumer product testing; and other contexts where a durable, tunable skin surrogate is needed to assess fluid behavior or mechanical interaction. The surfaces are designed to provide repeatable metrics that can support formulation and product-development decisions.
The design combines three surface-engineering approaches:
The design process is supported by a validated wetting model, open-source simulations, and physics-informed neural networks (PINNs) that predict static angles, hysteresis bounds, and durability behavior.
Characterization and validation:
The surfaces are at an early, active research and validation stage. The program is structured to progress from baseline characterization and design exploration through fabrication of 20–30 candidate designs, screening against pinning and friction targets, and durability optimization over a 12-month timeline. Deliverables include optimized coupons, validated fabrication and test protocols, and a documented scale-up path via molding. Because performance is application-dependent, users should expect to validate the surfaces against their own target fluids and protocols.
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