Industrial Internet is a product of the deep integration of new-generation information and communication technology and modern industrial technology, serving as an engine for new-type industrialization and new-quality productive forces. With the goal of "efficient collaboration of field-level industrial heterogeneous networks", this platform has successfully developed Time Sensitive Networking (TSN) technology and its core equipment supporting large-scale data interaction based on domestic CPUs and independently customized operating systems, including self-controlled high-end industrial Internet of Things gateways, testbeds, and related industrial software. It has broken through a series of key technical bottlenecks, including a cycle time of less than 10μs (approaching the theoretical limit), jitter below 500ns, and scheduling of over a thousand flows at the ten-millisecond level, reaching an international leading level. It is the only gateway device selected in the first batch of TSN industry chain directories in China. A TSN testbed with the largest number of nodes in China has been built, supporting heterogeneous traffic simulation, device protocol consistency, and key performance testing. A complete set of software such as an efficient and scalable integrated engine for network scheduling and configuration has been successfully developed, enabling efficient and convenient automatic configuration generation and on-demand customized configuration operation deployment. Related achievements have been verified in more than 10 enterprises such as COMAC, SUPCON, CRRC, and Liuzhou Iron and Steel, and are providing key technical support for the development of major equipment such as software-defined satellites and automated testing for the final assembly of large aircraft.

Collaborating organizations: Key Laboratory of System Control and Information Processing of the Ministry of Education, Shanghai Key Laboratory of Industrial Network System Perception and Control, Shanghai Collaborative Innovation Center for Industrial Internet, National Engineering Technology Research Center for Commercial Aircraft Manufacturing

Platform Principal: Professor Chen Cailian, cailianchen@sjtu.edu.cn

Intelligent equipment is the material foundation of modern industrial production systems, representing the integration and deep fusion of advanced manufacturing technology, information technology, and intelligent technology. Intelligent sensing and actuation technology are the critical foundations of intelligent equipment, providing strategic technological support for basic industries such as energy development, intelligent manufacturing, aerospace, and defense industries. Positioned in applied basic research, this research platform focuses equally on defense and civilian scientific research. It conducts high-level and cutting-edge basic research on new principles, methods, and technologies in the system dynamics of intelligent equipment, including micro-nano electromechanical systems, surface mechanics and functional devices, flexible actuation and sensing, micro-vibration and control, magnetic levitation detection theory and technology, reliability design theory and technology, etc. It is the first to propose the femtosecond laser interference method for vibration measurement and dynamic imaging at ultra-high frequencies and extremely low amplitudes, reaching an international leading level. Related research achievements have yielded innovative theoretical and technological advancements in the design of complex equipment systems, rotor dynamics of aviation engine rotors, structural dynamics and control of aerospace equipment, and key nuclear power equipment. Domestic and international research institutions, enterprises, and institutions have come to conduct collaborative research, commissioned development, and analytical testing, providing key technological support for the development of intelligent equipment, independent research and development of defense equipment, and technological progress in spacecraft and manufacturing equipment.

Collaborating Organization: National Key Laboratory of Mechanical System and Vibration

Platform Principal: Professor Zhang Wenming, wenmingz@sjtu.edu.cn

The Center for Neutron Science Research is a university-level research platform at Shanghai Jiao Tong University. It is committed to developing advanced non-destructive characterization technologies for neutron large scientific facilities, vigorously promoting the application of neutron technology in aerospace, nuclear power defense, chemical engineering, biomedicine, high-speed rail, marine engineering, and basic research fields. The center aims to break through engineering and technological bottlenecks and explore the frontiers of science. The center has established close cooperation with the China Mianyang Research Reactor, building the "Hetu" cold neutron high-resolution stress spectrometer and the "Luoshu" ultra-long multi-mode neutron small-angle scattering spectrometer. It also possesses a complete set of advanced characterization facilities, including in-situ electron microscopy, in-situ micro-nano mechanics platforms, and X-ray diffractometers. At the same time, the center has in-depth cooperation with scientific research institutions such as the Shanghai Synchrotron Radiation Facility and the French Atomic Energy Commission. Guided and supported by a team of advisory academicians, the center strives to build a world-class interdisciplinary platform for neutron scattering material characterization.

Platform Principal: Professor Zhong Shengyi, shengyi.zhong@sjtu.edu.cn

The Clean Energy Research Center at Paris College of Excellence Engineers actively responds to the national new energy strategy, promotes the optimization and upgrading of the global energy structure, focuses on the core technological breakthroughs and industrial applications of hydrogen energy. Its research scope covers hydrogen utilization - fuel cells, hydrogen production - electrolysis of water, and clean fuels - electrochemical production of ammonia. The research involves catalyst material development, membrane electrode-stack preparation, multi-phase, multi-component, and multi-scale numerical simulation, DFT theoretical calculations, and the application of deep learning in catalyst design and battery life prediction. The main research directions include:

1. Construction and mechanism research of fuel cell/electrolysis water hydrogen production catalysts
2. Mass transfer mechanism research, structural design, and performance optimization of fuel cell membrane electrodes
3. System optimization and mechanism exploration of lithium-mediated ammonia synthesis
4. Revealing key catalytic conversion mechanisms through first-principles functional theory calculations
5. Deep learning assisting in multi-catalyst design, battery gas flow research, and life prediction

Platform Principal: Associate Professor Wei Guanghua, ghwei@sjtu.edu.cn

The Industrial Intelligence Laboratory at Paris College of Excellence Engineers was established in 2021, based on the country's significant needs in nuclear power planning, digitization, and other critical areas. It conducts cutting-edge exploration and applied basic research aimed at advanced nuclear power material lifetime and safety evaluation. The laboratory focuses on multi-scale simulation computation and software development, in-situ experimental analysis methods, utilizing modeling theories and methodologies spanning different spatial and temporal scales. It independently develops mathematical and physical models and codes to simulate and analyze the interrelations between processes from the atomic scale to the macroscopic scale, understanding material service behavior, especially mechanical properties, from different physical levels. This provides support for the safe design and operation of major equipment.

The research team has long been engaged in studying the service performance of key nuclear power materials, such as irradiation embrittlement of reactor pressure vessel (RPV) steel and irradiation corrosion of zirconium alloy fuel cladding. They have accumulated experience in multi-scale simulations such as first-principles calculations, molecular dynamics, cluster dynamics, phase-field, finite element methods, as well as macro- and micro-scale experiments using accelerators, in-situ transmission electron microscopy, three-dimensional atom probes, positron annihilation, nanoindentation, and more. Currently, they are in charge of research projects funded by the National Natural Science Foundation of China, the Shanghai Natural Science Foundation, and the China National Nuclear Corporation.

Platform Principal: Professor Chen Liang,  Tenure-Track Associate Professor, Email: liang.chen@sjtu.edu.cn

Engineering Scientific Computing and Digital Twin technology are the products of the deep integration of engineering and digital technology, serving as an important engine for promoting national economic and social development. Aiming at "supporting the design and operation of major projects such as nuclear energy power," this platform proposes new computational frameworks, models, and methodologies based on system modeling theory and simulation technology, providing an essential scientific computing theoretical foundation and corresponding computational platform for the in-depth development of these fields. The platform's research directions cover multiple areas including scientific computing, optimization, artificial intelligence, data assimilation, model reduction, uncertainty quantification, neutron noise, online monitoring and protection, fault diagnosis, and more. It has achieved creative results in nuclear reactor engineering scientific computing theory and online monitoring technology, winning awards such as the Sichuan Provincial Science and Technology Progress Award, the China Nuclear Energy Industry Association Science and Technology Award, and the China Patent Excellence Award. Responding to the significant strategic needs of advanced national nuclear power technology and the forefront of next-generation advanced nuclear reactor technology, the platform is committed to developing reactor real-time digital twin and intelligent support technology. With the goal of "fast and accurate calculations," the platform systematically conducts theoretical modeling, numerical analysis, and specialized software development, providing strong support for the operational flexibility, mobility of China's nuclear power plants, as well as the safety, economy, digitization, and intelligence of national major nuclear energy projects such as "Hualong One" from both basic theory and engineering application dimensions.

Collaborating Units: Key Laboratory of System Control and Information Processing, Ministry of Education; National Key Laboratory of Nuclear Reactor Technology; Shanghai Jiao Tong University Chongqing Artificial Intelligence Research Institute

Platform Principal: Professor Gong Helin, Tenure-Track Associate Professor, gonghelin@sjtu.edu.cn