UNIVERSITY PARK, Pa. — Despite the prevalence of synthetic materials across different industries and scientific fields, most are developed to serve a limited set of functions. To address this inflexibility, researchers at Penn State, led by Hongtao Sun , assistant professor of industrial and manufacturing engineering (IME), have developed a fabrication method that can print multifunctional "smart synthetic skin" — configurable materials that can be used to encrypt or decrypt information, enable adaptive camouflage, power soft robotics and more.
Using their novel approach, the team made a programmable smart skin out of hydrogel — a water-rich, gel-like material. Compared to traditional synthetic materials with fixed properties, the smart skin enables enhanced multifunctionality, allowing researchers to adjust the gel's dynamic control of optical appearance, mechanical response, surface texture and shape morphing when exposed to external stimuli such as heat, solvents or mechanical stress.
The team detailed their work in a paper published in Nature Communications . Their paper was also featured in Editors' Highlights .
According to Sun, principal investigator on the project, the idea for the material was sparked by the natural biology of cephalopods, like the octopus, that can control their skin's appearance to camouflage themselves from predators or communicate with each other.
"Cephalopods use a complex system of muscles and nerves to exhibit dynamic control over the appearance and texture of their skin," Sun said. "Inspired by these soft organisms, we developed a 4D-printing system to capture that idea in a synthetic, soft material."
Sun, who holds additional affiliations in biomedical engineering, material science and engineering and the Materials Research Institute at Penn State, described the team's method as 4D-printing because it produces 3D objects that can reactively adjust based on changes in the environment. The team used a technique known as halftone-encoded printing — which translates image or texture data onto a surface in the form of binary ones and zeros — to encode digital information directly into the material, similarly to the dot patterns used in newspapers or photographs. This technique allows the team to essentially program their smart skin to change appearance or texture through exposure to stimuli.
These patterns control how different regions of the material respond to their environment, with some areas deswelling or softening more than others when exposed to changes in temperature, liquids or mechanical forces. By carefully designing the patterns, the team can decide how the material behaves overall.
"In simple terms, we're printing instructions into the material," Sun explained. "Those instructions tell the skin how to react when something changes around it."
According to Haoqing Yang, a doctoral candidate studying IME and first author of the paper, one of the most striking demonstrations of the smart skin is its ability to hide and reveal information. To showcase this feature, the team encoded a photo of the Mona Lisa onto the smart skin. When the film was washed with ethanol, the film appeared transparent, showing no visible image. However, the Mona Lisa became fully visible after immersion in ice water, or during gradual heating.
Although the Mona Lisa was used as a demonstration, Yang explained that the team's printing method allows them to encode any desired image onto the hydrogel.
"This behavior could be used for camouflage, where a surface blends into its environment, or for information encryption, where messages are hidden and only revealed under specific conditions," Yang said.
The team also showed that hidden patterns can be uncovered by gently stretching the material and measuring how it deforms via digital image correlation analysis. This means information can be revealed not just by sight, but also through mechanical deformation, adding another layer of security.
The material proved highly malleable — the smart skin could easily transform from a flat sheet into non-traditional, bio-inspired shapes with complex textures, according to Sun. Unlike many other shape-morphing materials, this effect does not require multiple layers or different materials. Rather, these shapes and textured surfaces — like those seen on cephalopod skin — can be controlled by the digitally printed halftone pattern within a single sheet.
Building on these shape-morphing capabilities, the researchers showed that the smart skin can combine multiple functions simultaneously. By carefully co-designing the halftone patterns, the team was able to encode the Mona Lisa image directly into flat films that later emerged as the material transformed into 3D shapes. As the flat sheets curved into dome-like structures, the hidden image information gradually became visible, demonstrating how changes in shape and appearance can be programmed together.
"Similar to how cephalopods coordinate body shape and skin patterning, the synthetic smart skin can simultaneously control what it looks like and how it deforms, all within a single, soft material," Sun said.
According to Sun, this work builds on previous efforts to 4D-print smart hydrogels, also published in Nature Communications . In that study, the team focused on the co-design of mechanical properties and programmable 2D-to-3D shape morphing. In the present work, the team developed a halftone-encoded 4D printing method to co-design more functions within a single smart hydrogel film.
Looking ahead, the team plans to develop a general and scalable platform that enables precise digital encoding of multiple functions into a single adaptive smart material system.
"This interdisciplinary research at the intersection of advanced manufacturing, intelligent materials and mechanics opens new opportunities with broad implications for stimulus-responsive systems, biomimetic engineering, advanced encryption technologies, biomedical devices and more," Sun said.
Other co-authors affiliated with Penn State include Haotian Li and Juchen Zhang, two doctoral candidates in IME; and Tengxiao Liu , a lecturer in biomedical engineering. Additionally, H. Jerry Qi, professor of mechanical engineering at Georgia Institute of Technology, collaborated on this work.
