Tianjin, a major economic hub in northern China, is transitioning from a traditional industrial city into a modern metropolis by expanding into emerging industries such as artificial intelligence, new energy and new materials through technological innovation and industrial upgrades, deputies to the National People's Congress said during the country's annual legislative sessions.

Tianjin's gross domestic product grew 5.1 percent last year, with key industrial chains in artificial intelligence and biomedicine continuing to expand. The Tianjin-Nankai Higher Education Science and Innovation Park has attracted more than 3,000 tech companies, with an annual output value exceeding 50 billion yuan ($6.9 million), becoming a core driver of regional innovation, according to local government data.

"These achievements are inseparable from the promotion of scientific research results and their transfer into technology," said Chen Jun, a deputy to the 14th National People's Congress and vice-president of Nankai University.

"Technological innovation is a core element in developing new quality productive forces, with the utilization of scientific and technological achievements as an important path," he said.

As a national lawmaker, Chen proposed establishing a national technology transfer center in Tianjin to create a hub for transforming scientific breakthroughs into industry applications across northern China. He also called for increased central government financial support, including policies such as special bonds and tax reductions, to strengthen platform development.

"If the transformation path is not smooth, many scientific and technological achievements will just 'sleep' in the laboratory, losing their application and economic value," he said.

To bridge the gap between research and industry, Tianjin has introduced a series of policies in recent years. In May, the city issued "Several Measures to Further Promote the Innovative Reform of the Transformation of Scientific and Technological Achievements" to accelerate the transition from laboratory research to industrial production.

"We launched the Tianjin-Nankai Higher Education Science and Innovation Park in 2023 to effectively connect university and enterprise resources, serving as an excellent demonstration of bridging the 'last mile' of technology transfer," said Zhang Gong, Tianjin's mayor and an NPC deputy.

With industrial upgrading, demand for skilled workers in Tianjin has surged. Chen said Nankai University, Tianjin University and the Haihe Laboratory serve as key research platforms for talent development.

The city is promoting collaborative training programs between schools and enterprises, such as "biomedicine plus AI" and "new materials plus AI," while attracting top academic teams to tackle technical challenges and drive innovation.

"We have a heavy task in talent cultivation. Enabling young scientific and technological talents to 'take the lead' in new fields and new eras is key to supporting high-quality development," Chen said.

Chen, an academician at the Chinese Academy of Sciences and an expert in new energy chemical materials, said artificial intelligence is transforming the development of new energy battery materials, significantly improving research efficiency and shortening development cycles.

"Traditional battery research and development relies on a 'trial and error' approach and a linear 'experiment verification plus simulation' model, which requires extensive time for material selection and formula optimization — not to mention the need for costly high-end instruments," Chen said.

AI-powered automation has streamlined the process, allowing robots to conduct high-throughput experiments around the clock while AI analyzes experimental data, optimizes designs and automates adjustments.

"Through robots running nonstop 24 hours a day, AI can quickly analyze experimental spectra, extract parameters and feed them into simulation platforms for optimized designs. If the plan does not meet standards, the system automatically iterates. Feasible plans go directly into production, significantly shortening the time from laboratory to mass production," Chen said.

AI has also revolutionized quality inspection in battery production. Computer vision-based detection systems can identify defects such as electrode cracks and impurities with efficiency more than 100 times higher than manual inspection. AI is also integrated into battery manufacturing and management systems, enabling smarter production and monitoring, he said.

BYD's intelligent process system, developed using reinforcement learning algorithms, increased the electrode coating yield rate from 88 percent to 99.5 percent, while AI digital twin technology shortened trial production cycles by 60 percent, significantly accelerating product launches, according to the company.

NIO's AI-powered battery management system, which uses transfer learning, has kept battery life prediction errors within 3 percent, increasing the residual value of used electric vehicle batteries by 15 percent. AI is reshaping the competitiveness of the new energy vehicle industry, the company said in previous interviews with China Industry News.

Chen said the deep integration of AI and new energy batteries is paving the way for "digital twin batteries," which can map and simulate battery performance in real-time, providing greater convenience for researchers and consumers.

"In the next one to two years, we aim to develop solid-state batteries with an energy density of 600 watt-hours per kilogram, enabling electric vehicles to travel more than 1,000 kilometers on a single charge," Chen said.

"This also means improved product performance and reduced costs, ultimately benefiting consumers, who will be able to access better-performing and more affordable new energy batteries more quickly," he said.