Direct ink writing nanogenerator: Texture structure and its influence on the piezoelectric performance

As an additive manufacturing technique enabling complex geometric fabrication, direct ink writing (DIW) has established itself as a cornerstone technology for flexible electronics production. However, the inherent filament deposition process introduces anisotropic surface morphologies with stochastic texture patterns. Systematic investigation into the causal relationship between these topographical features and device performance is imperative for advancing performance-optimized flexible sensor architectures.

A research team from Harbin Institute of Technology, China, has quantified the influence of surface wave texture peak-to-valley (PV) values on piezoelectric nanogenerator outputs and proposed a PV control strategy for DIW-printed surfaces based on overlap ratio optimization. Their study, published in Nano Research on April 7, 2025, demonstrates that optimized nanogenerators can detect human motion states with high precision and have been successfully applied in badminton match analysis.

“Wearable sensors can capture real-time human motion signals and wirelessly transmit these signals over long distances via IoT technology, enabling applications ranging from health monitoring to human-machine interaction," explained Haitao Liu, senior author of the paper and Professor at the School of Mechatronics Engineering, and deputy dean of Institute of Advanced Technology. "This innovation addresses a critical gap in flexible sensor design by revealing how 3D-printed surface textures fundamentally alter energy conversion performance. Larger PV values create 'dead zones' with reduced stress distribution, directly impacting electric field intensity."

To resolve microscale heterogeneity in composite materials, the team employed a homogenization method using representative volume elements (RVEs) modeled via Monte Carlo simulations. Their computational framework calculated equivalent piezoelectric parameters while analyzing stress distribution and electric field intensity across varying PV values. Key findings revealed that increasing the surface PV value from 14.29 μm to 80.86 μm decreased piezoelectric sensitivity by 13%, from 0.832 V/N to 0.723 V/N.

Experimental validation showcased the nanogenerator's capabilities: Detection of finger-bending angles with proportional voltage outputs; A machine learning model achieving 97.89% accuracy in classifying standing, walking, and running/jumping states; Successful deployment in badminton match analysis to quantify athlete exertion patterns.

"Flexible sensors will enable transformative applications in intelligent healthcare," Liu emphasized.

Authors of the paper include Xiaoquan Shi, Mingxuan Xu, Hangqi Zhang, Yazhou Sun, Ruixuan Wang, Zikai Yuan, and Haitao Liu.

About Nano Research

Nano Research is a peer-reviewed, open access, international and interdisciplinary research journal, sponsored by Tsinghua University and the Chinese Chemical Society, published by Tsinghua University Press on the platform SciOpen. It publishes original high-quality research and significant review articles on all aspects of nanoscience and nanotechnology, ranging from basic aspects of the science of nanoscale materials to practical applications of such materials. After 18 years of development, it has become one of the most influential academic journals in the nano field. Nano Research has published more than 1,000 papers every year from 2022, with its cumulative count surpassing 7,000 articles. In 2024 InCites Journal Citation Reports, its 2024 IF is 9.0 (8.7, 5 years), and it continues to be the Q1 area among the four subject classifications. Nano Research Award, established by Nano Research together with TUP and Springer Nature in 2013, and Nano Research Young Innovators (NR45) Awards, established by Nano Research in 2018, have become international academic awards with global influence.