Optimisation of Breeding Blanket Composition in a DT Spherical Fusion Generator | Polygence

Optimisation of Breeding Blanket Composition in a DT Spherical Fusion Generator

Project by Polygence alum Anay

Optimisation of Breeding Blanket Composition in a DT Spherical Fusion Generator

Project's result

Research paper presented at 2 local symposiums

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Summary

Nuclear fusion, a promising candidate for long-term clean energy production, is the focus of numerous global experiments. Despite its potential, achieving self-sustaining and commercially viable fusion reactions presents significant engineering challenges. These include maintaining extremely high temperatures and pressures in the device’s plasma region, managing the high-energy (14.07 MeV) neutrons produced in a deuterium-tritium (D-T) reaction that can damage the walls, and sustaining the reaction over extended periods. Two critical factors in assessing the commercial viability and longevity of a fusion generator are the Tritium Breeding Ratio (TBR) and the Displacement per Atom (DPA).

This research paper explores various factors influencing the TBR and DPA in a fusion generator and seeks to determine the optimal thickness and material for the breeding blanket layer in a spherical generator design. The study employs neutronics simulations with the OpenMC module. The results provide valuable insights into the generator’s performance. Given the short half-life of tritium (approximately 12.33 years), a key fuel in the D-T reaction, it is crucial to generate tritium within the generator itself. Achieving a TBR greater than unity is vital for the commercial feasibility of a fusion device, as it indicates that it produces more tritium than it consumes. Minimising the DPA experienced by the generator walls is also important, as high DPA values can alter the physical and mechanical properties of the material.

https://dpl6hyzg28thp.cloudfront.net/media/Optimisation_of_Breeding_Blanket_Composition.pdf

Soha

Soha

Polygence mentor

MSE Master of Science in Engineering

Subjects

Physics, Engineering

Expertise

Physics, Robotics, Nuclear Physics Fission/Fusion Energy, Clean Energy, Environmental Science, Nuclear Security, Global Security Questions in Artificial Intelligence/Policy, Nuclear Weapons, Fintech / Finance

Anay

Anay

Student

Hi! I’m Anay, an incoming freshman at Columbia University with a passion for applied mathematics and physics. I worked on a project focused on optimizing nuclear fusion generators — combining theory with real-world innovation to explore the future of clean energy.

Graduation Year

2029

Project review

“Polygence was truly a transformative experience for me. As someone deeply interested in applied math and physics, the program gave me the perfect platform to dive into a topic I genuinely care about — optimizing nuclear fusion generators. What sets Polygence apart is its flexibility, structure, and emphasis on student-driven exploration. I wasn’t just completing a project — I was encouraged to think critically, ask big questions, and connect my academic passions to real-world impact.”

About my mentor

“Working with Soha through Polygence was one of the most valuable parts of my research journey. She brought not only deep expertise in physics and engineering, but also a genuine passion for mentorship that made every session insightful and motivating. Soha had a unique ability to make complex concepts clear and engaging, and she consistently encouraged me to think deeper and approach problems from multiple angles. Her support went far beyond just technical guidance — she helped me build confidence in my ideas, sharpen my research skills, and take ownership of my project. Thanks to Soha’s mentorship, I felt like a real contributor to the field I’m passionate about. I’m incredibly grateful for her guidance and would recommend her to any student who’s eager to explore STEM at a high level.”