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KAIST Develops Next-Generation Self-Powered Wearable Sensor Resilient to 668% Elongation
Wearable medical devices that monitor heart rate, respiration, and joint movements for long periods without battery concerns, electronic skins that sense external stimuli like human skin, and soft robots made of flexible materials that move freely have all come one step closer to reality. KAIST researchers have developed a self-powered sensor (a sensor that generates electricity on its own without a battery) that can stretch up to 668% while producing stable electrical signals.
KAIST announced on June 18th that a research team led by Professor Miso Kim from the Department of Mechanical Engineering has overcome the durability limitations of conventional piezoelectric fiber sensors (fiber-type sensors that convert pressure or movement into electrical signals) and successfully developed a highly stretchable piezoelectric fiber sensor that operates stably even under repeated deformation.
The core material of the sensor, piezoelectric polymer, is a polymeric material that generates electricity when subjected to mechanical force. Although its lightweight and flexible nature makes it suitable for skin-attachable wearable sensors, conventional piezoelectric fiber sensors suffered from signal degradation during repeated stretching or bending, as the electrode layer collecting electrical signals and the piezoelectric layer generating electricity would become damaged. Furthermore, while coiling the fibers can increase stretchability to allow greater elongation, maintaining electrical stability remained a significant challenge.
To resolve these issues, the research team developed a "Hierarchical Resilient Design" strategy, engineering the sensor to withstand deformation across multiple levels—from its constituent materials and electrodes to its overall structure. Simply put, just as a rubber band returns to its original shape after repeated stretching, the sensor is designed to self-maintain its performance after cyclical deformation.
First, the research team embedded elastic polymer microparticles inside the piezoelectric nanofibers to create a closely interlocking structure. This creates a supportive effect similar to Velcro, helping the sensor recover its original shape even after being repeatedly stretched.
Additionally, they designed the interface so that the electricity-collecting electrode and the electricity-generating piezoelectric layer connect seamlessly. By strongly bonding different materials together, they ensured they would not easily delaminate under impact or deformation, allowing the sensor to maintain a stable electrical signal even when significantly stretched or bent.
Applying this design to a coil structure, the research team successfully stretched the sensor up to 668%—approximately 6.7 times its original length—while maintaining a stable output. The developed sensor generated consistent electrical signals under various movements, including stretching, bending, and pressing.
Furthermore, the research team fabricated the sensor not only in coil forms but also in knot configurations, confirming its stable operation under repeated forces or sudden impacts. By leveraging artificial intelligence (AI) to analyze the sensor signals, they were also able to accurately distinguish between different movements, such as pressing, bending, and stretching.
This study holds great significance as it presents a self-powered sensor platform that simultaneously achieves high stretchability and long-term stability without requiring a battery. In particular, because it enables stable signal measurement in environments undergoing repeated deformation, it is expected to be utilized in developing next-generation wearable medical devices for long-term monitoring of various biosignals, including heart rate, respiration, joint movement, and muscle activity. It is also projected to expand its range of applications to digital healthcare devices, electronic skins, and sensory sensors for soft robots by making devices lighter and more convenient to use.
"The core achievement of this research is that it simultaneously secured mechanical resilience and electrical reliability by combining fiber structure design with electrode interface engineering (a technology that controls the boundary where different materials meet)," said Professor Miso Kim. She added, "In the future, we expect it to be applied to wearable medical devices requiring long-term wear, electronic skins, and sensory sensors for soft robots, enabling more accurate and continuous biosignal monitoring."
The research findings, with researcher Yong Jun Choi as the first author, were published on March 10, 2026, in ACS Nano (Impact Factor 16.1), a world-renowned academic journal in the fields of nanotechnology and materials science.
Paper Title: Mechanically and Functionally Resilient Piezoelectric Fiber Coils and Knots for Reliable Self-Powered Sensing DOI: doi/10.1021/acsnano.5c19628 Author Information: Yong Jun Choi 1 (KAIST, First Author), JungHun Park 1 (KAIST, Co-author), Jisoo Nam 1 (KAIST, Co-author), Gi-Dong Sim 1 (KAIST, Co-author), Myung-Gil Kim 2 (Sungkyunkwan University, Co-author), Miso Kim (KAIST, Corresponding Author)
This research was conducted with support from the BRIDGE Convergence Research and Development Program (RS-2023-00254689), the Nano·Material Technology Development Program (RS-2024-00468995), and the Next-Generation Semiconductor-Compatible Micro-Substrate Technology Development Program (RS-2024-00433654) funded by the National Research Foundation of Korea under the Ministry of Science and ICT.
2026.06.18 View 3175 -
Tracking Atoms during Fuel Cell Cycles: KAIST Team Reveals the Atomic-Scale Secret Behind Fuel Cell Catalyst Durability
<Professor Yongsoo Yang, Professor Eun-Ae Cho, Dr. Chaehwa Jeong, Dr. Joohyuk Lee, Dr. Hyesung Cho, Researcher Kwangho Lee from KAIST>
Hydrogen fuel cell vehicles have long been hailed as the future of clean mobility: cars that emit nothing but water while delivering high efficiency and power density. Yet a stubborn obstacle remains. The heart of the fuel cell, the platinum-based catalyst, is both expensive and prone to degradation. Over time, the catalyst deteriorates during operation, forcing frequent replacements and keeping hydrogen vehicles costly.
Understanding why and how these catalysts degrade at the atomic level is a longstanding challenge in the catalysis research. Without this knowledge, designing truly durable and affordable fuel cells for mass adoption remains out of reach.
Now, a team led by Professor Yongsoo Yang of the Department of Physics at KAIST (Korea Advanced Institute of Science and Technology), in collaboration with Professor Eun-Ae Cho of KAIST’s Department of Materials Science and Engineering, researchers at Stanford University and the Lawrence Berkeley National Laboratory, has successfully tracked the three-dimensional change of individual atoms inside fuel cell catalysts during thousands of operating cycles. The results provide unprecedented insight into the atomic-scale degradation mechanisms of platinum-nickel (PtNi) catalysts, and demonstrate how gallium (Ga) doping dramatically improves both their performance and durability.
A New Atomic “CT Scan” for Catalysts
To achieve this breakthrough, the team utilized a neural network-assisted atomic electron tomography (AET) technique. Much like a CT scan in a hospital reconstructs the inside of the human body from X-ray images, AET determines the positions of thousands of atoms inside nanomaterials from high-resolution electron microscopy images taken at many different angles. By combining these reconstructions with advanced AI-based data correction, the researchers were able to map the exact 3D coordinates and chemical identity of every atom in the nanoparticle catalysts.
This allowed them to directly observe—at single-atom resolution—how the catalysts changed in structure, chemical composition, and internal strain as they were cycled thousands of times under fuel cell operating conditions.
Key Findings: Why Gallium Makes a Difference
The researchers compared conventional PtNi catalysts with Ga-doped PtNi catalysts. The results revealed:
a) Shape stability: While undoped PtNi particles gradually lost their advantageous octahedral shape and became more spherical (i.e., the fraction of highly active {111} facets has been reduced), Ga-doped particles retained their octahedral shape even after 12,000 cycles.
b) Chemical stability: In PtNi catalysts, nickel atoms leached from both the surface and subsurface regions, driving structural instability. In Ga-doped catalysts, surface nickel was largely preserved, preventing collapse of the structure.
c) Strain preservation: The compressive strain in PtNi particles, crucial for optimizing oxygen reduction activity, relaxed substantially over time. In contrast, Ga-doped particles maintained near-optimal strain.
d) Catalytic performance: By integrating these factors, the researchers showed that while undoped PtNi catalysts lost ~17% of their oxygen reduction activity after 12,000 cycles, Ga-doped PtNi catalysts lost only ~4% and maintained superior activity throughout.
Dr. Yang, who led the research, explained the significance of the results: “These results represent the first time the true 3D atomic-scale degradation dynamics of fuel cell catalysts have been directly visualized. Our findings not only reveal why gallium doping works, but also establish a powerful framework for rationally designing durable, high-efficiency catalysts.”
Implications for a Hydrogen-Powered Future
The study demonstrates that neural network-assisted AET can reveal how nanomaterials evolve during real operating conditions, overcoming the limitations of traditional 2D imaging and ensemble-averaged methods. Beyond PtNi catalysts, the technique can be applied to a wide range of nanomaterials and catalytic systems, helping to design the next generation of energy materials with atomic precision.
For the hydrogen economy, this means that more durable catalysts could extend the lifetime of fuel cells, lower replacement costs, and accelerate the widespread adoption of hydrogen-powered vehicles and clean energy technologies.
[Figure 1] Three-dimensional atomic structures and catalytic activity of Ga-doped PtNi nanoparticles during potential cycling. The top row shows the 3D atomic structures at different stages (Pristine to 12,000 cycles; blue: platinum, pink: nickel). The bottom row visualizes oxygen reduction reaction (ORR) catalytic activity, where red indicates higher activity. Gallium doping stabilizes the octahedral geometry and preserves highly active {111} facets, enabling sustained catalytic performance even after extensive cycling.
This research, with Chaehwa Jeong, Juhyeok Lee, Hyesung Jo, KwangHo Lee from the KAIST as co-first authors, was published online in Nature Communications on August 28th (Title: Atomic-scale 3D structural dynamics and functional degradation of Pt alloy nanocatalysts during the oxygen reduction reaction).
The study was mainly supported by the National Research Foundation of Korea (NRF) Grants funded by the Korean Government (MSIT).
2025.09.15 View 3735