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Contract Opportunity

TECHNOLOGY LICENSING OPPORTUNITY

Determining the Effects of Transient Active Agents and Events on Static and Semi-Static Populations

Novel methods for understanding the effects of transient active agents and events resulting in increased battery life, safety, and proliferation.

Opportunity: Idaho National Laboratory (INL), managed and operated by Battelle Energy Alliance, LLC (BEA), is offering to enter into a license or collaborative research agreement to commercialize this method for determining the effects of transient active agents and events. This technology transfer opportunity is part of a dedicated effort to convert government-funded research into job opportunities, businesses, and, ultimately, an improved way of life for the American people.

Overview: The battery industry is rapidly growing. However, battery adoption needs to be improved by addressing central issues of safety, longevity, and cost. Transient active agents (TAA) and transient events (TE) can influence the state of a static or semi-static population (SP) through interactions with the SP. Many cases of TAA/TE-SP interactions exist in natural and manufactured systems, such as material involved in regular duty cycles (e.g., batteries, reactors, consumer products, etc.) and biological populations responding to frequent exposure to TAA and TE. Brief analyses allow the investigation of distinct short-lived conditions (relative to the life of the SP) that might persist over hundreds or thousands of cycles.

Description: The invention is a computational method to determine the effects of transient active agents and events upon static or semi-static populations. It explicitly considers the chief factors tied to periodic transient events that impact battery stability and life in terms of the battery materials, battery design, and arbitrary operating conditions. The method can be an independent yet complementary route to existing CellSage tools to diagnose and predict aging processes in battery and non-battery applications. It can also support machine learning (ML) of complex aging processes.

Benefits:

• Increases the lifespan and safety of batteries


• Increases proliferation of battery energy storage


• Increases knowledge of cause-and-effect on system aging and how the modeling framework can support optimization of design and use conditions

Applications:

• Diagnostic and predictive analyses of material, system, and product lifecycles for batteries and energy storage systems.

Development Status: TRL 4: the system has been validated in a laboratory environment.

IP Status: Patent Application No. 18/001,304, “Analyzing Systems or Groups that Undergo Changes Over Time, and Related Devices and Systems,” BEA Docket No. BA-1178.

INL seeks to license the above intellectual property to a company with a demonstrated ability to bring such inventions to the market. Exclusive rights in defined fields of use may be available. Added value is placed on relationships with small businesses, start-up companies, and general entrepreneurship opportunities.

Please visit Technology Deployment’s website at https://inl.gov/inl-initiatives/technology-deployment for more information on working with INL and the industrial partnering and technology transfer process.

Companies interested in learning more about this licensing opportunity should contact Andrew Rankin at td@inl.gov.

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