Call for Research Proposals: Battery Data and AI Programme (UK)

The Faraday Institution Battery Data and AI Sprint Projects provide funding to improve battery data consistency, metadata standards, and artificial intelligence (AI)-driven battery research. The programme offers up to £0.4 million total funding at 80% FEC, with individual sprint projects expected to receive approximately £100,000 for six-month research activities.

Overview of the Faraday Institution Battery Data and AI Sprint Projects

The Faraday Institution is inviting research proposals for Battery Data and AI Sprint Projects designed to strengthen battery research through improved data management, standardisation, and artificial intelligence applications.

The programme focuses on creating more consistent battery data and metadata practices across Faraday Institution research programmes. It aims to support researchers in developing AI-based approaches that can accelerate battery science, innovation, and technology development.

The projects will build on existing research efforts related to:

• Battery data capture.
• Standardised cell assembly practices.
• Metadata consistency.
• Data-driven battery science.
• AI-enabled research methods.

Purpose of the Funding Programme

The main goal of the Battery Data and AI Sprint Projects is to establish a stronger foundation for AI-driven battery research by improving how battery data is collected, structured, shared, and analysed.

The programme aims to:

• Improve consistency of battery research data.
• Develop standardised battery metadata frameworks.
• Support AI applications in battery science.
• Encourage better data curation practices.
• Align battery research data with international standards where appropriate.
• Improve collaboration across the battery innovation ecosystem.

Key Research Areas Supported

Projects should focus on battery data innovation and AI-enabled research approaches.

Supported activities may include:

• Pilot projects for battery data standardisation.
• Testing standardised data and metadata frameworks.
• Developing improved battery data capture methods.
• Creating AI-led battery science approaches.
• Supporting standardised data curation.
• Improving data sharing practices across research programmes.

Projects should demonstrate practical value for future battery research and innovation.

Why Battery Data Standardisation Matters

Battery research generates large volumes of complex scientific data. However, inconsistent data formats, incomplete metadata, and different research practices can make it difficult to compare results or apply AI technologies effectively.

Improved battery data standards can help:

• Accelerate battery discoveries.
• Improve research reproducibility.
• Enable machine learning applications.
• Support collaboration between researchers and industry.
• Reduce duplication of research efforts.
• Strengthen future battery technology development.

Funding Amount and Project Duration

The programme provides:

• Total funding: Up to £0.4 million at 80% FEC.
• Expected individual project funding: Approximately £100,000.
• Project duration: Six months.

The earliest possible grant start date is:

• 1 October 2026

Projects with slightly shorter durations may be considered with prior approval.

Funding beyond March 2027 remains subject to review by the Department for Business and Trade.

Who Is Eligible to Apply?

Applicants must meet UK Research and Innovation (UKRI) eligibility requirements.

Eligible applicants must include:

• A lead applicant who satisfies UKRI eligibility rules.
• A lead research organisation that meets UKRI requirements.

Projects should involve researchers with expertise relevant to:

• Battery science.
• Data management.
• Artificial intelligence.
• Machine learning.
• Research innovation.

Research Collaboration Requirements

Applicants are encouraged to work across the battery innovation ecosystem.

Projects should support collaboration between:

• Universities.
• Research organisations.
• Industry partners.
• Battery technology stakeholders.

Applicants should demonstrate how their work contributes to wider battery research advancement.

How to Apply for Battery Data and AI Sprint Projects

Applications must be submitted through the Faraday Institution Flexi-Grant portal.

Step 1: Develop the Project Proposal

Applicants must clearly explain:

• The battery data challenge being addressed.
• Research objectives.
• Proposed activities.
• Expected benefits.
• Contribution to AI-driven battery science.

Step 2: Prepare Required Application Information

The proposal must include:

• Challenge statement.
• Project aims and objectives.
• Project scope.
• Expected benefits.
• Current state of the art.
• Justification for funding.
• CV of project leader.
• CV of Postdoctoral Research Associate (PDRA), where applicable.
• Letters of support.

Step 3: Obtain Supporting Documents

Applicants must provide:

• Letter of support from university head of department.
• Letters of support from industry partners, if involved.

Step 4: Submit Through Flexi-Grant Portal

Applicants should ensure all required documents are completed and submitted before the deadline.

Project Expectations and Responsibilities

Successful applicants must follow Faraday Institution grant requirements.

Funded projects are expected to:

• Follow grant terms and management principles.
• Support collaboration across the innovation chain.
• Provide access to facilities for other Faraday Institution-funded institutions where appropriate.
• Follow requirements related to research outputs.
• Comply with intellectual property (IP) conditions.

Assessment and Selection Process

Applications will be reviewed through an independent assessment process.

The evaluation process includes:

• Review by an independent expert panel.
• Consideration of panel recommendations.
• Final funding decisions by the Faraday Institution.

The final selection will follow a portfolio approach to ensure a balanced range of funded projects.

Common Mistakes to Avoid

Applicants should avoid:

• Submitting projects unrelated to battery data or AI innovation.
• Failing to explain practical benefits.
• Providing unclear data standardisation approaches.
• Missing supporting letters.
• Ignoring UKRI eligibility requirements.
• Not demonstrating collaboration potential.

Tips for a Strong Application

Applicants can strengthen their proposals by:

• Clearly defining the battery data challenge.
• Explaining how AI methods will create value.
• Demonstrating technical expertise.
• Showing alignment with international data standards.
• Including strong academic and industry partnerships.
• Providing measurable project outcomes.

Frequently Asked Questions (FAQ)

What are the Faraday Institution Battery Data and AI Sprint Projects?

These are short-term research projects designed to improve battery data consistency, metadata standards, and AI-driven approaches in battery science.

How much funding is available?

The programme provides up to £0.4 million total funding at 80% FEC, with individual projects expected to receive around £100,000.

How long will projects run?

Sprint projects will run for six months, with the earliest start date of 1 October 2026.

Who can apply?

Eligible UKRI applicants, including qualifying lead researchers and research organisations, can apply.

What types of projects are supported?

Projects may focus on battery data standardisation, metadata frameworks, AI-led battery science, and improved data curation.

How are applications evaluated?

Applications are reviewed by an independent panel, and final funding decisions are made through the Faraday Institution’s independent review process.

Is industry collaboration required?

Industry collaboration is encouraged, and applicants may include industry support letters to strengthen their proposals.

Conclusion

The Faraday Institution Battery Data and AI Sprint Projects provide an opportunity to advance battery research through better data practices and artificial intelligence innovation.

By improving battery data consistency, supporting AI-driven research methods, and encouraging collaboration across academia and industry, the programme aims to accelerate the development of next-generation battery technologies and strengthen the future energy innovation ecosystem.