$1,500,000 OFFICE OF MULTIDISCIPLINARY AC, BIOMATERIALS PROGRAM, DMREF

AI-guided discovery of next-generation energy-storage materials — ion-conducting peptide electrolytes (DMREF) (NSF AI grant $1.5M)

University of Illinois at Urbana-Champaign Illinois Started Oct 2025

The NSF awarded about $1.5M to discover safe, thermally stable solid ion-conducting materials — helical "peptide electrolytes" — via an AI-guided approach. Using precisely sequenced peptides (biological macromolecules), the project studies how helical structure enhances ion conduction, targeting next-generation energy storage beyond lithium-ion safety concerns.

Grant overview (primary data)

  • Award amount$1,500,000
  • RecipientUniversity of Illinois at Urbana-Champaign (Illinois)
  • ProgramOFFICE OF MULTIDISCIPLINARY AC, BIOMATERIALS PROGRAM, DMREF
  • Period2025-10-01 〜 2029-09-30
  • FunderU.S. National Science Foundation (NSF) / NSF

Key points

  • Discovers safe, thermally stable solid ion conductors (peptide electrolytes) via AI-guided design
  • Uses precisely sequenced peptides whose helical structure can be controlled
  • Focuses on controlled arrangement of ion-conducting groups and a helix-length macrodipole
  • Targets next-generation energy storage beyond lithium-ion safety concerns
  • About $1.5M; DMREF (Biomaterials); Illinois
  • The 120 NSF AI-related awards this site holds as of 2026-09-01 reach 37 states, but only 17 have more than one receiving institution.

The NSF awarded about $1,500,000 to AI-guided discovery of ion-conducting peptide electrolytes (NSF Award 2522611; program: DMREF / Biomaterials; Illinois).

1Safe, thermally stable ion-conducting materials

Per the abstract (non-technical), energy-storage technologies like batteries critically require safe and thermally stable ion-conducting materials. Lithium-ion batteries are pervasive, but safety concerns have prompted new solid-state ion conductors. To date, nearly all solid polymer ion conductors are synthetic materials lacking precisely defined structures.

In contrast, biological macromolecules such as peptides have precisely defined sequences, allowing control over 3D molecular structure, such as helical elements.

2The role of the peptide helix

The project aims to understand the role of peptide helices in enhanced ion conduction, focusing on (1) arranging ion-conducting groups in controlled ways and (2) a macrodipole along the backbone that grows with helix length. This will enable a new class of helical peptide ion conductors for enhanced energy storage.

A wide range of peptide chemistries will be designed and synthesized using an AI-guided discovery approach to understand how chemistry, sequence, helical character, and arrangement of ion-conducting groups affect performance — a key outcome being to understand how peptide molecular structure affects ion transport for next-generation energy-storage materials.

3Within a state, the institutions scatter too

The 120 NSF AI-related awards this site holds as of 2026-09-01 spread across 37 states, but only 17 of those states have more than one institution receiving an award. The other 20 have exactly one.

States reached37across 120 awards
States with more than one institution17
States with a single institution20

Read by state the distribution looks wide, yet rather more than half of it rests on a single institution. A map coloured by state says that AI research exists there, not how deep it runs. Describing the spread means keeping the count of states and the count of institutions apart.

Why it matters

A case applying AI to energy-storage material design. For those tracking solid-state batteries, energy storage, and AI-driven (inverse) materials design, a useful read on the direction of U.S. research investment.

FAQ

Why design materials with AI?
The space of chemistry, sequence, and structure is vast, so AI helps design and narrow promising candidates, combined with synthesis and testing to accelerate discovery.
What is DMREF?
Designing Materials to Revolutionize and Engineer our Future — an NSF program integrating computation, data, and experiment to accelerate materials discovery.

Sources (primary)

Source: NSF Award Search (U.S. National Science Foundation, public domain). Amounts are the obligated amount. For privacy, we do not handle principal investigator names.

#AI#NSF#Research grant#Materials science#Batteries#AI for Science
Disclaimer: This site independently summarizes and classifies information based on official data sources. Always verify the latest and accurate information with the official sources. Content on finance, health, legal, and security is information, not advice. This site is not an official website of the U.S. government.