Molecular Universe (MU-3.0) Live Demo

MU-StarSeeker in MU-3.0 release expands Molecular Universe from AI-assisted research workflow toagent-managed materials discovery automation, from molecule search andformulation optimization to cell performance prediction and manufacturingquality guidance

Traditional battery R&D is slow, fragmented, and resource-intensive. Developing and commercializing a new chemistry could take 10 years to go from lab-scale R&D through A-sample, B-sample, C-sample and finally SOP, involving tedious manual iterations across materials search, formulation, simulations, testing, and validation. Starting with MU-3.0 release, MU-StarSeeker is built to disrupt that traditional model by turning isolated research steps into automated and continuously learning agent-managed workflow.

Key Features Highlights:

• MU-3.0 extends coverage to Sodium-ion (Na-ion) chemistry to reflect its rapidly growing share in the energy storage market.

• Integrated dry and wet data loops connect simulation with autonomous labs (“A-Labs”), accelerating experimental validation and reducing R&D bottlenecks.

• Cloud, on-premise, and “in-a-box” deployment options are available to support different enterprise environments, with considerations for data security and scalability.

1. MU-StarSeeker, Agent-Managed Material Discovery Workflow Automation

MU-StarSeeker transforms Molecular Universe’s core workflow—Ask, Search, Formulate, Design, Predict, and Manufacture—into a Skill-based automation architecture where users can compose customized workflows by combining Skills and delegate complex, multi-step discovery processes to an agent that orchestrates them end-to-end; for example, instead of manually iterating across molecule search, formulation testing, bulk property evaluation, and cell-level validation across hundreds of candidates, users can launch an MU-StarSeeker workflow and return to a ranked set of optimized formulations, while the system provides both standard Skills maintained by Molecular Universe and the ability for users and enterprises to develop proprietary Skills capturing internal workflows and expertise, enabling a major leap in automation and standardization while still preserving access to individual features for users who prefer hands-on control and transparency.

2. MU-3.0 Supports Both Lithium and Sodium Chemistries

With their low cost, high safety, superior fast charging and low temperature performance, and abundant and sustainable nature as compared with Lithium-ion (Li-ion) batteries, Na-ion batteries are quickly gaining popularity and market shares in energy storage applications. Na-ion chemistry is also one of the most searched prompts in Molecular Universe. Starting with MU-3.0, all services have been expanded to cover Na-ion. The popular molecular dynamics simulation engine and our proprietary force field in Formulate has been reengineered from the ground up to work just as well for Na-ion as it did for Li-ion, providing robust and accurate property prediction and analysis in a timely manner.

3. Closed-Loop Dry and Wet Data Through Autonomous Labs or 'A-labs'

MU-3.0 connects computational prediction with experimental validation through integrated dry and wet data workflows, allowing users to initiate wet data requests via individual features or MU-StarSeeker–managed Skills routed to high-throughput A-Labs; this creates a closed-loop system where agents generate hypotheses, simulations screen molecules and formulations and predict cell-level performance, and A-Labs return ground-truth results that continuously improve the platform, reducing unnecessary experiments, improving prediction accuracy, and accelerating discovery of safer, higher-performing chemistries, while also recognizing dry data’s inherent limits versus experimentally measured wet data and supporting sensitive deployments through on-premise “Search-in-a-Lab” and “Formulate-in-a-Lab” configurations combining MU-3.0 capabilities with local compute and A-Lab infrastructure.

4. Enterprise Deployment and Business Impact

MU-3.0 is available through both cloud and on-premise deployment, supporting enterprise requirements for scalability, speed, security, and data control. For large enterprise users, MU offers “in-a-box” solutions including Search-in-a-Box, Formulate-in-a-Box, and Predict-in-a-Box. These offerings support single-molecule property search, formulation-level bulk property simulations, and device-level performance predictions, and are already generating revenue and bookings from large enterprise users. By compressing R&D timelines, reducing experimental wastes, standardizing best practices, and accelerating the path from chemistry concept to product deployment, MU-3.0 creates significant value for customers in drones, robotics, energy storage, and mobility.