# Collaborative Research: MFS-SPEED: AI-Driven Design of Architecturally Varied and Deconstructable Polymers for a Comprehensive Circular Plastics Economy

> **NSF 01002526DB NSF RESEARCH & RELATED ACTIVIT** · University of California-Berkeley (CA) · $588,903

## Abstract

In this project, artificial intelligence (AI) will be used to design new sustainable polymeric materials with a range of properties and that can be recycled without the need for costly and inefficient separation from mixed waste streams. Today’s plastic waste challenge exists at a scale of megatons per day across tens of thousands of applications and products. The researchers will create new types of depolymerizable plastics derived from simple feedstocks, and they will develop physics-informed AI models to aid design of these plastics such that they meet a variety of product specifications across a wide range of properties. Ultimately, this approach enables products of all different types, functions, and lifetimes to be integrated into a single recycling stream and accelerates their discovery-to-use timeline. The results and methods developed by this research will be publicly accessible for industrial benchmarking and include code and tutorials for users to perform AI-guided design on their own materials. Through this research, a new generation of scientists will be trained to work at the emerging intersection of polymer materials design and AI model development and use.

With this award, the project will develop physics-informed AI and synthesize architecturally varied and deconstructable (ADD) polymers by cationic ring-opening polymerization (CROP) with controlled chain length, branching, and dynamic bond incorporation. This work will create new synthetic strategies to c

## Key facts

- **NSF award ID:** 2519577
- **Awardee organization:** University of California-Berkeley (CA)
- **SAM.gov UEI:** GS3YEVSS12N6
- **PI:** Brooks A Abel
- **Primary program:** 01002526DB NSF RESEARCH & RELATED ACTIVIT
- **All programs:** Artificial Intelligence (AI), CAS-Critical Aspects of Sustainability, Advanced Manufacturing, SusChEM
- **Estimated total:** $588,903
- **Funds obligated:** $588,903
- **Transaction type:** Standard Grant
- **Period:** 09/01/2025 → 08/31/2028

## Primary source

NSF Award Search: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2519577

## Citation

> US National Science Foundation, Award 2519577, Collaborative Research: MFS-SPEED: AI-Driven Design of Architecturally Varied and Deconstructable Polymers for a Comprehensive Circular Plastics Economy. Retrieved via AI Analytics 2026-06-08 from https://api.ai-analytics.org/grant/nsf/2519577. Licensed CC0.

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