The industry holds high expectations for photonic chips, which play a crucial role in data centers, especially in high-bandwidth and energy-efficient data transmission. With the growing demand for efficient data processing driven by the rise of artificial intelligence, cloud computing, and IoT devices, the research and development of photonic chips have become increasingly urgent.
China’s First Photonic Chip Pilot Line Launched in Wuxi
On September 25th, the first domestic photonic chip pilot line built by the Wuxi Photonic Chip Research Institute of Shanghai Jiao Tong University was officially launched. After the pilot line becomes operational, it is expected to reach an annual production capacity of 10,000 wafers. The first PDK will be released in the first quarter of 2025, providing external chip fabrication services.
The photonic chip pilot platform covers an area of 17,000 square meters, integrating research, production, and services. It is equipped with more than 100 top-tier international CMOS process machines, supporting a full closed-loop process for lithium niobate photonic chips, from lithography, thin film deposition, etching, wet processing, cutting, measurement, to packaging. The platform also supports other material systems like silicon and silicon nitride.
Jinan Achieves World’s First 12-Inch Lithium Niobate Crystal
in May of this year, Shandong Hengyuan Semiconductor Technology Co., Ltd. in Jinan successfully developed a 12-inch (300mm diameter) large-sized optical-grade lithium niobate crystal.
Shandong Hengyuan Semiconductor has been dedicated to the R&D of optoelectronic materials such as lithium niobate and lithium tantalate, as well as piezoelectric materials. Through technological advancements, the company has started mass production of 6-8 inch Z-axis and X-axis optical-grade lithium niobate crystals. Within three years, Hengyuan plans to increase its annual wafer production to 250,000 units.
Chinese Scientists Develop Mass-Produced New “Optical Silicon” Chips
In early May, the research team led by researcher Ou Xin at the Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, made a breakthrough in the preparation of lithium tantalate heterogeneously integrated wafers and high-performance photonic chips. They successfully developed a new type of “optical silicon” chip that can be mass-produced. The research results were published in Nature on May 8th.
Tsinghua University Team Releases AI Photonic Chip
In August, Tsinghua University announced that the research group led by Professor Fang Lu from the Department of Electronic Engineering and the team led by Academician Dai Qionghai from the Department of Automation pioneered a fully forward intelligent optical computing training architecture. They developed the “Taiji-II” optical training chip, enabling efficient and precise training of large-scale neural networks in optical computing systems. This research, titled “All-Forward Training of Optical Neural Networks,” was published in Nature.
The previously released Taiji-I, in April, achieved 879 T MACS/mm²area efficiency and 160 TOPS/W energy efficiency, marking the first time optical computing was applied to complex AI tasks such as natural scene recognition with thousands of categories and cross-modal content generation.
Chinese Team Successfully Develops Fully Programmable Topological Photonic Chip
In late May, the “Extreme Optics Innovation Research Team” from Peking University’s School of Physics, in collaboration with Researcher Yang Yan from the Institute of Microelectronics, Chinese Academy of Sciences, proposed and realized a fully programmable topological photonic chip based on large-scale integrated optics.
The chip built on a reconfigurable integrated optical micro-ring array, integrates 2,712 components in an area of just 11mm x 7mm. It successfully achieved the world’s first fully programmable optical artificial atomic lattice. The researchers also experimentally validated multiple topological phenomena on a single-chip platform, including dynamic topological phase transitions, multi-lattice topological insulators, statistical topological robustness, and Anderson topological insulators.