MIT Researchers Unveil Model Predicting Long-Term Nuclear Waste Behavior, Boosting Storage Confidence

Date:

Cambridge, MA – July 18, 2025 –

Scientists at the Massachusetts Institute of Technology (MIT) have unveiled a sophisticated new model designed to predict the long-term effects of nuclear waste on underground disposal systems, a critical advancement in the quest for safe and publicly trusted solutions for high-level radioactive waste. The research, published today, demonstrates that the model’s simulations accurately match experimental results from a leading underground research laboratory in Switzerland, providing a significant boost to the credibility of geological repository designs.

Disposing of nuclear waste in deep underground geological formations is widely considered the safest long-term solution for managing the hazardous byproducts of nuclear power. However, building public and policymaker trust in these solutions, which must remain secure for tens to hundreds of thousands of years, has been a persistent challenge. The complexity of predicting interactions between highly radioactive waste and surrounding engineered and natural materials over such vast timescales necessitates robust scientific validation.

A New Computational Tool for Complex Interactions

The MIT study, co-authored by researchers including Dr. Zhandos Sarsenbayev and Dr. Stephen Wainwright, leverages new, high-performance-computing software to improve the modeling of these intricate interactions. The focus of their work was on how nuclear waste reacts with cement-clay barriers, which are key materials proposed for use in engineered barrier systems and geological repositories globally.

One of the long-standing challenges in understanding these interactions has been the irregular mixing of materials deep underground and the inability of existing models to account for electrostatic effects associated with negatively charged clay minerals within the barriers. The new model, however, successfully integrates these complexities.

“These powerful new computational tools, coupled with real-world experiments like those at the Mont Terri research site in Switzerland, help us understand how radionuclides will migrate in coupled underground systems,” stated Dr. Sarsenbayev, first author of the new study.

Swiss Lab Provides Crucial Validation

A critical aspect of the MIT research is its successful comparison with decades of experimental data from the Mont Terri Rock Laboratory in Switzerland. This underground research facility is globally renowned for providing invaluable datasets on the interactions between cement and clay, simulating the conditions found in deep geological repositories.

The simulations generated by the MIT team’s new model aligned remarkably well with the experimental results from Mont Terri. This strong correlation demonstrates that the model can successfully account for electrostatic effects and the long-term interaction between materials over time. As Dr. Sarsenbayev noted, “This is all driven by decades of work to understand what happens at these interfaces.”

Building Public Confidence and Informing Policy

The implications of this validated model are far-reaching. It could potentially replace older, less comprehensive models currently used for safety and performance assessments of underground geological repositories. For countries considering deep geological disposal, such as the United States, these models could be instrumental in dictating the most appropriate materials to use. While clay is currently a favored storage material, the model could also be applied to assess other potential media like salt formations.

Ultimately, the researchers hope their study will contribute significantly to building long-term public and policymaker confidence in nuclear waste storage solutions. By providing a more accurate and validated scientific basis for predicting the fate of radionuclides in the subsurface, this interdisciplinary research aims to foster greater acceptance and support for the necessary long-term management of nuclear waste.

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