Highly Responsive Self‐Healing and Degradable Piezoelectric Soft Machines

S Sujoy Kumar Ghosh (Berkeley Sensor and Actuator Center Department of Mechanical Engineering University of California Berkeley CA 94720 USA) S Subhajit Pal (Department of Bioengineering) K Krittish Roy (Department of Physics and Bernal Institute University of Limerick Limerick V94 T9PX Ireland) W Wei Yue Y Yuan Gao F Fan Xia P Peisheng He S Sabyasachi Sarkar (Department of Chemistry) M Megan Teng J Jongha Park (Berkeley Sensor and Actuator Center Department of Mechanical Engineering University of California Berkeley CA 94720 USA) P Peggy Tsao (Berkeley Sensor and Actuator Center Department of Mechanical Engineering University of California Berkeley CA 94720 USA) X Xiaosa Li (Berkeley Sensor and Actuator Center Department of Mechanical Engineering University of California Berkeley CA 94720 USA) S Syed A. M. Tofail (Department of Physics and Bernal Institute University of Limerick Limerick V94 T9PX Ireland) P Phillip B. Messersmith (Department of Bioengineering) L Liwei Lin (Department of Mechanical Engineering & Berkeley Sensor & Actuator Center)

Abstract

Abstract Piezoelectric materials that are simultaneously healable, stretchable, and degradable have remained an unmet challenge, limiting advancements in wearable and implantable electronics, where devices face multidimensional mechanical deformation, causing a risk of damage. To address this critical gap, a biocompatible piezoelectric material is developed for ultrahigh piezoelectric effects with DL‐alanine amino acid crystals, which is stretchable, healable, and degradable. The in situ grown DL‐alanine piezoelectric crystals within an ionically cross‐linked gelatin hydrogel matrix strengthen the piezoelectric properties with an ultrahigh voltage coefficient of 1.6 Vm N −1 . The combination of the piezo‐ionic property and crystal alignment results in a record‐breaking energy harvesting figure‐of‐merit value at 57.6 pm 2  N −1 to deliver outstanding mili‐watt level power outputs in proof‐of‐concept devices which can power up even several electric light bulbs. An elastically stretchable, damage resistant strain sensor is further optimized for real‐time healthcare monitoring and biomechanical motion tracking. By integrating machine learning algorithms, the sensing system intelligently classifies biomechanical activities with high accuracy, enabling advanced applications in healthcare, rehabilitation, and sports monitoring.

Article Details

Volume / Issue Vol. 37, Issue 39
Published October 01, 2025
ISSN 0935-9648
Publisher Unknown Publisher

Journal Info

Advanced Materials

Unknown Publisher

ISSN: 0935-9648 Physical Sciences

Authors (15)

S

Sujoy Kumar Ghosh

Berkeley Sensor and Actuator Center Department of Mechanical Engineering University of California Berkeley CA 94720 USA

S

Subhajit Pal

Department of Bioengineering

K

Krittish Roy

Department of Physics and Bernal Institute University of Limerick Limerick V94 T9PX Ireland

W

Wei Yue

Y

Yuan Gao

F

Fan Xia

P

Peisheng He

S

Sabyasachi Sarkar

Department of Chemistry

M

Megan Teng

J

Jongha Park

Berkeley Sensor and Actuator Center Department of Mechanical Engineering University of California Berkeley CA 94720 USA

P

Peggy Tsao

Berkeley Sensor and Actuator Center Department of Mechanical Engineering University of California Berkeley CA 94720 USA

X

Xiaosa Li

Berkeley Sensor and Actuator Center Department of Mechanical Engineering University of California Berkeley CA 94720 USA

S

Syed A. M. Tofail

Department of Physics and Bernal Institute University of Limerick Limerick V94 T9PX Ireland

P

Phillip B. Messersmith

Department of Bioengineering

L

Liwei Lin

Department of Mechanical Engineering & Berkeley Sensor & Actuator Center