Sensitive detection of mid- and long-wave infrared is crucial for night vision, environmental monitoring, autonomous driving, and more. However, traditional high-performance infrared detectors typically require cryogenic cooling or an external bias voltage, leading to high power consumption, large volume, and costly systems. Developing new infrared-sensitive materials and devices that can operate at room temperature in a self-powered manner has been a long-standing goal in the field.
Recently, a research team from Donghua University, the Hangzhou Institute for Advanced Study of the University of Chinese Academy of Sciences (UCAS), and the Shanghai Institute of Technical Physics made a breakthrough. They discovered that niobium/tantalum-tellurium binary compounds with charge density wave are ideal candidates for high-performance, self-powered infrared detection. The related findings were recently published in the journal Nano Research .
A charge density wave is a collective electronic ordered state that can induce a narrow bandgap near the material's Fermi level, enabling an efficient response to low-energy photons such as infrared light. "Our work systematically investigated four materials: one-dimensional NbTe 4 and TaTe 4 , and two-dimensional NbTe 2 and TaTe 2 ," explained by Haijie Chen, a researcher at Donghua University and one of the corresponding authors of the study. "We found that they all exhibit significant photoresponse in the mid- to long-wave infrared band, dominated by the photothermoelectric effect, and can operate stably under zero bias, i.e., in a self-powered mode."
The performance of the two-dimensional material NbTe₂ was particularly impressive. Under illumination at 4 μm and 8.47 μm, its detectivity reached 1.64×10 8 Jones and 1.29×10 8 Jones, respectively. "These materials are semimetallic and can absorb incident light across a broad spectrum," Chen added. "The resulting photothermal gradient is then converted into an electrical signal via the Seebeck effect. This mechanism allows our detectors to function without any external power source."
Beyond the excellent detector performance, another highlight of the research is the deep integration of hardware with AI software. The team built a single-pixel infrared imaging system based on the self-powered Nb/Ta-Te detector. While single-pixel imaging systems are simple in structure, their image resolution is often limited. The researchers introduced a deep learning model based on a U-Net architecture for image super-resolution reconstruction.
"We fed the low-resolution images captured by the detector into the AI model for processing," Chen described. "The detail and clarity of the processed images were significantly enhanced, with a model recognition accuracy of 96.4%. This preliminarily validates the feasibility of a complete technical chain, from new materials to core devices and intelligent sensing applications."
This work not only expands the material systems available for mid- and long-wave infrared detection and reveals the universality of the photothermoelectric effect in this class of charge density wave materials but, more importantly, demonstrates a viable approach for building next-generation room-temperature, low-power, intelligent infrared optoelectronic systems. Such self-powered detectors hold broad application prospects in fields like wearable sensing, IoT nodes, and redundant perception systems for autonomous driving.
Looking ahead, the research team plans to further optimize the material and device structure to improve response speed and promote their integration and validation in specific application scenarios.
Other contributors to this work include Hao Gu, Suifeng Xiong, Futing Sun, Chao Guo, Jingyu Zhang, Wen Chen, Yunluo Wang, Zesen Gao, Xinyue Zhao, Xiaohan Zhang, and Lili Yang from Donghua University; Zhongyang Yu, Haoxuan Li, Qirui Sun, He Zhu, Yufeng Shan, and Ning Dai from the Hangzhou Institute for Advanced Study, UCAS; and Yongzhe Wang from the Shanghai Institute of Ceramics, CAS. The research represents a collaborative effort across multiple institutions.
This work was supported by the the AI-Enhanced Research Program of Shanghai Municipal Education Commission (SMEC-AI-DHUZ-02), Donghua University 2025 Cultivation Project of Discipline Innovation (xkcx-202514), National Natural Science Foundation of China (22101045, 62304061, U2141240, 62175045), National Key Research and Development Program of China (No. 2023YFA1608701, 2023YFB2806703), and "Pioneer" and "Leading Goose" R&D Program of Zhejiang (2025C02036).
D OI Link:
https://doi.org/10.26599/NR.2026.94908526
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.
Nano Research
Semimetallic Nb/Ta-Te Phases with Charge Density Wave for Mid- and Long-wave Infrared Detection
8-Jun-2026