IAEA Launches Global Research Project Using AI to Predict Radiation Effects on Polymers

Polymers—used extensively in cable insulation, medical devices, plastics, and industrial components—undergo significant structural changes when exposed to radiation.

The International Atomic Energy Agency (IAEA) has announced a new five-year global research initiative inviting scientific institutions to develop machine learning (ML) tools capable of predicting how polymers behave under ionizing radiation—a long-standing challenge in materials science.

The project, titled “Data-driven Prediction of Structural Changes in Polymers Induced by Radiation,” seeks to accelerate innovation in industries ranging from nuclear energy to healthcare by replacing costly trial-and-error experimentation with data-driven modelling.

A Critical Challenge in Modern Materials Science

Polymers—used extensively in cable insulation, medical devices, plastics, and industrial components—undergo significant structural changes when exposed to radiation. These changes include:

• Cross-linking, which can strengthen materials

• Chain scission, which can weaken them

• Oxidation, affecting durability and performance

While these effects can be beneficial when controlled, predicting them remains a major obstacle.

Currently, engineers must rely on time-consuming and expensive experimental testing for each new application, slowing down technological progress and increasing costs.

Data Gap Holding Back AI Innovation

Although machine learning has transformed fields like weather forecasting and finance, its application to radiation–polymer interactions has been limited due to fragmented and incomplete data.

Key challenges include:

• Decades of research scattered across academic literature

• Proprietary industrial data not publicly accessible

• Lack of standardized, validated datasets

This absence of a unified database has prevented ML systems from identifying patterns and making reliable predictions.

IAEA’s Solution: A Global Data-Driven Approach

The new Coordinated Research Project (CRP), running from 2026 to 2031, aims to overcome these barriers by building the first comprehensive, validated global database of radiation-induced polymer changes.

The initiative will focus on three core pillars:

1. Building a Structured Global Database

• Consolidating and standardizing existing research data

• Validating findings from decades of studies

2. Conducting Targeted Experiments

• Filling critical data gaps where evidence is missing or inconsistent

• Generating new high-quality datasets

3. Developing Machine Learning Models

• Training AI systems to predict polymer behaviour under radiation

• Simulating outcomes across different materials and conditions

The ultimate goal is to enable predictive modelling tools that can guide polymer design and application without the need for extensive physical testing.

Wide-Ranging Applications Across Industries

Improved predictive capabilities could have significant impacts in:

• Nuclear energy: Enhancing durability of reactor materials and cables

• Healthcare: Optimising sterilization processes for medical equipment

• Manufacturing: Designing more resilient plastics and composites

• Environmental sustainability: Reducing waste and energy use in material testing

By improving efficiency and reducing uncertainty, the project could accelerate innovation across multiple sectors.

Global Collaboration and Capacity Building

The IAEA is calling on research organizations worldwide to participate in the project, encouraging:

• Inclusion of women and early-career researchers

• Collaboration between academic institutions and industry partners

Participating teams will be assigned specific polymers and research tasks, contributing to a coordinated global effort.

How to Participate

Interested organizations must submit proposals by:

• Deadline: 29 May 2026

• Submission: Via email to the IAEA’s Research Contracts Administration Section

• Using official templates available through the Coordinated Research Activities platform

Both research and technical contract proposals are eligible under the same application framework.

A Step Toward Smarter, Faster Innovation

By combining nuclear science with artificial intelligence, the IAEA initiative represents a significant shift toward data-driven materials engineering.

If successful, it could reduce development timelines, lower costs, and enable more precise design of materials exposed to radiation—helping industries move from experimentation to prediction.