Eacomp, an AI for Science (AI4S) startup founded by Associate Professor Zheng Jiaxin of Peking University Shenzhen Graduate School, has completed a strategic funding round in the hundreds of millions of RMB, exclusively invested by Contemporary Amperex Technology Co., Limited (CATL). The company specializes in Battery Design Automation (BDA).
The investment marks CATL’s first strategic move in the AI4S sector and reflects a broader shift in how advanced materials and energy technologies are developed—moving from trial-and-error experimentation toward AI-driven, simulation-based design. It also highlights Peking University Shenzhen Graduate School’s growing role in translating academic research into real-world industrial impact.
A Platform for AI-Driven Battery Design
Founded in 2020, Eacomp has built a general-purpose materials R&D platform that combines AI with full-process simulation, covering the entire lifecycle of materials from discovery and manufacturing to production and service. Its solutions have been validated by dozens of leading industrial enterprises.
The company’s BDA platform addresses a longstanding bottleneck in battery development: the slow, costly nature of traditional R&D. “Developing a battery cell through the conventional approach typically takes one to two years,” said Zheng, who is also a tenured associate professor at the School of Advanced Materials and the School of AI for Science. “With our BDA platform, that cycle can be compressed to six months or even less—helping companies iterate faster, improve performance, cut R&D costs, and bring products to market sooner.”
The “Physics × AI” Approach
Lithium batteries involve complex, cross-disciplinary interactions among materials science, physics, chemistry, and electrochemistry. Traditional computer-aided engineering (CAE) simulation offers precision but struggles with high-dimensional, nonlinear problems. Purely data-driven AI models excel at pattern recognition but depend heavily on large, high-quality datasets and often generalize poorly.
Eacomp’s answer is a “Physics × AI” approach. Physics-based simulation provides rigorous scientific constraints and generates high-quality synthetic data to compensate for scarce experimental data. AI algorithms, in turn, accelerate model iteration and handle complex nonlinear coupling—enabling AI to be deployed effectively in real industrial settings.
Research and Industry Collaboration
In 2025, Eacomp and CATL jointly published the design framework for the world’s first AI-driven automated lithium battery design platform in National Science Open. Their jointly developed cross-scale simulation and AI algorithms for electrolyte formulation can accurately reproduce complex SEI film formation and enable both forward prediction and inverse design of electrolyte formulations based on performance targets (Nature Machine Intelligence, 2026).
The company’s platform integrates with enterprise systems such as ERP, MES, and LIMS, transforming fragmented historical data into enterprise-specific knowledge bases and creating a sustainable data flywheel. To date, Eacomp has partnered with more than 30 leading enterprises in new energy and new materials, with growing repeat business and deepening strategic collaborations.
Beyond batteries, the company has extended its cross-scale algorithm capabilities to semiconductors, optoelectronics, ceramics, alloys, fine chemicals, and composites—building benchmark Materials Design Automation (MDA) cases across sectors. It has also developed several in-house materials pipelines, with mass production planned for the second half of 2026.
Looking Ahead
Over the next year, Eacomp plans to strengthen its presence in new energy and new materials while expanding into overseas markets. In the longer term, the company aims to scale its “Physics × AI” technology across battery applications, co-lead the development of industry standards for Battery Design Automation, and build a physics-AI operating system for wet laboratories—creating an unattended, closed-loop R&D workflow.
“Our goal is to become a globally leading provider of ‘Physics × AI’ solutions for new energy and new materials,” Zheng said.
