Conventional cameras and computer vision systems typically divide the work of seeing and interpreting an image between separate components. Photodetectors first convert light into electrical signals, after which processors move and analyze the data. That constant transfer consumes energy and introduces latency, particularly in applications such as autonomous vehicles, robotics, wearable electronics, and high-speed industrial inspection. A research team in China has now demonstrated a reconfigurable photodiode that can begin processing visual information at the point of detection, potentially reducing the costly movement of data between sensors and computing hardware.
The device was developed by researchers led by Xiaoxian Zhang and Yongsheng Wang at Beijing Jiaotong University, in collaboration with Yuchao Yang and Yaoyu Tao at Peking University. Their approach combines an ambipolar semiconductor, tungsten diselenide, or WSe₂, with a thin ferroelectric layer made from hafnium zirconium oxide, known as HfₓZr₁₋ₓO₂ or HZO. The resulting architecture is designed to function not merely as a light sensor, but as a programmable optical computing element capable of changing how it responds to incoming light.
At the heart of the device is a sub-20-nanometer HZO ferroelectric film integrated with a split-gate structure. Ferroelectric materials possess a switchable internal electric polarization. Once that polarization is changed, it can continue influencing the electronic behavior of a device even after the programming voltage is removed. In this photodiode, the polarization of the HZO layer modifies the electrical environment of the WSe₂ channel, allowing the researchers to control the polarity of the device and reconfigure its photocurrent response.
WSe₂ is particularly useful for this purpose because it is ambipolar. Depending on the surrounding electric field and gate conditions, it can conduct through either electrons or positively charged holes. The split-gate design takes advantage of this dual behavior to create a reconfigurable homojunction, a junction formed within the same semiconductor system rather than between conventional materials with different electronic properties. By switching the ferroelectric polarization, the researchers can alter the junction configuration and reverse the direction of the photocurrent.
One of the most notable features of the device is that it can switch its photocurrent polarity without requiring an external bias during operation. In conventional photodetectors, an applied voltage is often needed to drive current or tune the response, adding to energy consumption and complicating circuit integration. The reported architecture instead uses the stored polarization of the ferroelectric layer to establish the required electrostatic conditions internally. This enables light detection and signal modulation under zero external bias, an important step toward low-power sensing systems.
The programming process is also designed to be highly energy efficient. The researchers report a programming energy below one femtojoule, a scale that is extraordinarily small compared with the energy typically associated with moving data between a sensor and a processor. The device switches between states in approximately 50 microseconds and retains its programmed weight for more than 100 seconds. In this context, the “weight” represents the adjustable strength or sign of the device response, allowing it to act as an analog computational element rather than a simple on-or-off detector.
The team demonstrated that the photodiode could perform in-situ preprocessing of optical signals, including matrix-vector multiplication, a fundamental operation in artificial intelligence and neural-network algorithms. Matrix-vector multiplication normally requires large numbers of data transfers between memory and processing units. When implemented directly through the physical responses of devices, the operation can occur in parallel as light is detected, reducing the need for repeated digital conversion and memory access. The reconfigurable photocurrent of the WSe₂-HZO device provides a physical means of applying adjustable computational weights to optical inputs.
To test its practical potential, the researchers used the photodiode as a physical convolution kernel in simulated image edge-detection tasks. Convolution kernels apply mathematical weight patterns to neighboring pixels to identify features such as boundaries, contours, and fine structures. The device produced edge maps that were nearly indistinguishable from those generated by ideal software calculations. At its optimal programmed weight state, the system achieved a normalized mean squared error of approximately 3.2 × 10⁻⁴, indicating a close match between the hardware-generated and software-generated results.
The researchers say the work addresses several limitations that have slowed the development of neuromorphic vision hardware. Many existing devices provide only a unidirectional photocurrent, limiting their ability to represent positive and negative computational weights. Others depend on continuous external bias or require high programming voltages. Device concepts based on Schottky barriers or polymer ferroelectrics such as PVDF can also face challenges involving reliability, manufacturing compatibility, and scaling. By using HZO, a ferroelectric material more closely aligned with established semiconductor processing, the new design points toward a potentially CMOS-compatible route for integrating sensing, memory, and computation.
The result does not yet represent a complete commercial vision processor, but it provides a compact building block for future systems in which pixels detect, remember, and interpret optical information at the same physical location. Such architectures could be valuable in cameras that need to respond rapidly while operating on limited power, from edge-AI devices and smart sensors to wearable systems and autonomous machines. The study, published in Nano Research, illustrates how ferroelectric polarization and two-dimensional semiconductors can be combined to make photodetectors programmable, computational, and substantially more energy efficient.
Subject of Research: Reconfigurable ferroelectric photodiodes and in-sensor computing using HZO and ambipolar WSe₂.
Article Title: Achieving energy-efficient in-Sensor computing via ferroelectric reconfigurable homojunctions
News Publication Date: 12-May-2026
Web References: https://doi.org/10.26599/NR.2026.94908610; https://www.sciopen.com/journal/1998-0124
References: Nano Research, DOI: 10.26599/NR.2026.94908610
Image Credits: Nano Research, Tsinghua University Press
Keywords
In-sensor computing, neuromorphic vision, ferroelectric electronics, HfₓZr₁₋ₓO₂, HZO, WSe₂, ambipolar semiconductors, reconfigurable photodiodes, CMOS-compatible devices, edge detection, optical computing, low-power electronics
