A Survey of Artificial Intelligence and High Performance Computing Applications to Fusion Commercialization

The document argues that AI and HPC are transforming fusion development from an empirical, physical testing process to an 'in silico' approach, significantly reducing the time and cost required to reach commercial viability. It identifies five critical technical areas where these tools are essential: materials selection, high-temperature superconductors, inertial fusion energy (IFE) challenges, tritium breeding/extraction, and plasma diagnostics and control. Furthermore, the report suggests that AI can support the creation of fit-for-purpose regulations and reduce the Levelized Cost of Electricity (LCOE) through predictive maintenance and optimized remote handling. The authors highlight a symbiotic relationship where AI accelerates fusion's development, and fusion eventually provides the carbon-free, firm power required to sustain the energy-intensive growth of AI data centers.

• AI and HPC are shifting fusion development from a manual, empirical process of building and testing physical machines to 'in silico' design, which uses parameter sweeping and multi-objective optimization to narrow design configurations and balance energy yield with cost-effectiveness.
• The report identifies five priority technical areas where AI and HPC accelerate solutions: predicting material behavior in extreme environments, optimizing high-temperature superconductor (HTS) manufacturing to avoid 'quenches', improving laser driver accuracy for inertial fusion energy (IFE), maximizing the tritium breeding ratio (TBR), and enabling autonomous plasma steering and disruption prevention.
• AI and HPC can lower the Levelized Cost of Electricity (LCOE) for fusion by enabling modular designs and reducing plant downtime through AI-driven predictive maintenance and the optimization of remote handling systems (RHS) using deep reinforcement learning.
• The private fusion sector has seen rapid growth, with over $8 billion in total equity investments, more than $7 billion of which was raised since 2020, and the number of companies increasing from 10 in 2017 to over 40.
• A symbiotic relationship exists between AI and fusion: AI tools accelerate the delivery of fusion energy, while fusion's potential as a source of emissions-free firm power can meet the surging energy demands of AI data centers.

APA

de Vicente, S. G., Hermann, L., Brister, J., Grandas, D., Sowder, A., James, R., Fonseca, F. R., Bistline, J., Gorgian, T., Woodruff, S., Moore, J., Mburu, N., Higginbottom, A., Oatley, R., Bansal, A., Clemenger, I., Karaveyeu, Y., Obeng-Akrofi, E., & Rainford, T. (2024). A Survey of Artificial Intelligence and High Performance Computing Applications to Fusion Commercialization. Clean Air Task Force. https://cdn.catf.us/wp-content/uploads/2024/11/04152245/fusion-ai-executive-summary.pdf

Chicago

de Vicente, Sehila Gonzalez, Laura Hermann, Jay Brister, Diana Grandas, Andrew Sowder, Romey James, Francisco Ralston Fonseca, et al. A Survey of Artificial Intelligence and High Performance Computing Applications to Fusion Commercialization. Clean Air Task Force, 2024. https://cdn.catf.us/wp-content/uploads/2024/11/04152245/fusion-ai-executive-summary.pdf.

Wikipedia

{{cite report |last1=de Vicente |first1=Sehila Gonzalez |last2=Hermann |first2=Laura |last3=Brister |first3=Jay |last4=Grandas |first4=Diana |last5=Sowder |first5=Andrew |last6=James |first6=Romey |last7=Fonseca |first7=Francisco Ralston |last8=Bistline |first8=John |last9=Gorgian |first9=Todd |display-authors=etal |title=A Survey of Artificial Intelligence and High Performance Computing Applications to Fusion Commercialization |publisher=Clean Air Task Force |date=November 2024 |url=https://cdn.catf.us/wp-content/uploads/2024/11/04152245/fusion-ai-executive-summary.pdf |access-date=23 October 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{devicente2024survey, author = {de Vicente, Sehila Gonzalez and Hermann, Laura and Brister, Jay and Grandas, Diana and Sowder, Andrew and James, Romey and Fonseca, Francisco Ralston and Bistline, John and Gorgian, Todd and Woodruff, Simon and Moore, Jack and Mburu, Naomi and Higginbottom, Alex and Oatley, Ryan and Bansal, Amolika and Clemenger, Isaac and Karaveyeu, Yan and Obeng-Akrofi, Eugenia and Rainford, Thomas}, title = {{A Survey of Artificial Intelligence and High Performance Computing Applications to Fusion Commercialization}}, institution = {Clean Air Task Force}, year = {2024}, month = nov, url = {https://cdn.catf.us/wp-content/uploads/2024/11/04152245/fusion-ai-executive-summary.pdf}, urldate = {2026-10-23}, note = {Indexed by Climate Insights Directory} }