Strain-regulated integration: novel detector achieves visual-tactile fusion perception
image: (a) Illustration of multisensory integration in biological neural systems: visual (light) and tactile (force) stimuli are received by sensory receptors, converted into electrical signals, and processed through synaptic networks in the neural center for coordinated perception and recognition of the external environment. (b) Schematic of the artificial biomimetic sensing device based on the MnSe/α-In2Se3 van der Waals heterostructure. This flexible device can simultaneously receive optical signals and mechanical strain signals, directly coupling dual-modal information into tunable photocurrent via the piezophototronic effect, mimicking the cross-modal integration of biological systems.
Credit: Nano Research, Tsinghua University Press
In complex or low-light environments, relying solely on visual information often makes it difficult to accurately identify objects. Humans can perceive surface textures through tactile sensations to assist visual judgments. Inspired by this, researchers have long sought to develop intelligent devices capable of simultaneously sensing light and force, achieving "visual-tactile fusion perception" akin to humans, thereby enhancing machine recognition capabilities in ambiguous environments.
Recently, a team from the University of Electronic Science and Technology of China (in collaboration with the Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences) made significant progress in strain-modulated optoelectronic perception and neuromorphic vision systems. Their findings were published in Nano Research on February 26, 2026.
The study proposed a flexible photodetector based on a MnSe/α-In2Se3 van der Waals heterostructure, utilizing the piezophototronic effect to achieve bidirectional strain-regulated photoresponse. Under 0.303% tensile strain, the photoresponsivity increased by 203.9%, while under -0.236% compressive strain, it was suppressed by 50.4%. For the first time, strain signals were introduced as a fourth perceptual channel to construct a neuromorphic recognition system integrating visual-tactile fusion.
In a blurred image classification task, the system significantly improved recognition accuracy from 63% to 86% with only 50 training cycles, approaching the benchmark for clear image recognition (89%). Moreover, it eliminated the need for analog-to-digital conversion, greatly reducing system complexity. This work provides new materials and insights for intelligent sensing, bionic robotics, and low-power vision chips.
DOI Link:
https://doi.org/10.26599/NR.2026.94908320
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 8,000 articles. In 2025 InCites Journal Citation Reports, its 2025 IF is 9.4 (8.3, 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.