Over the past years, AI has evolved rapidly, becoming increasingly sophisticated and capable of solving more complex problems. AI is deployed in sectors such as manufacturing, transportation, finance, education and healthcare. On the other hand, it has the potential to advance applications in nuclear science and technology.  

Using AI in nuclear science can aid in harnessing issues from food security to climate change. It has the potential to advance cancer staging in nuclear medicine and cancer treatment to accelerate progress towards the realization of fusion energy production, as well as to help protect global water resources from overexploitation, contamination and more. In a global scenario, after a global energy shortfall as a result of sudden transition, countries like Japan and Iceland are shifting their nuclear policy. 

Combating diseases 

AI is already applied to support the diagnosis and treatment of cancer through improved image interpretation and precise tumor contouring, enabling more accurate treatment plans and adaptive radiotherapy. Radiotherapy is a process tailored to the anatomical characteristic of the individual patient. The IAEA recently introduced a research project in this area.  

AI also plays a significant role in the IAEA’s Zoonotic Disease Integrated Action (ZODIAC) initiative to help experts better understand the impact of zoonotic diseases on human health and predict, assess and contain future outbreaks of such diseases.  

The food system and water availability 

AI tools, when combined with nuclear technologies, can help make food systems more sustainable and climate change resilient while addressing food and nutrition insecurity. Experts deploy AI to analyze data to enhance crop yields, estimate soil moisture, remediate radioactively contaminated land, detect and predict food fraud events and improve irrigation.  

Isotopic methods allow experts to analyze and track how water moves through different stages of the hydrological cycle. They can also understand what transformations occur in this cycle due to climate change. Experts already apply AI-based approaches to quickly analyze huge amounts of water-related isotopic data stored in global repositories. 

Fusion research  

Nuclear fusion represents an opportunity to achieve safe and sustainable energy. However, the research in this area requires substantial experimental and theoretical activity covering plasma physics and material science. AI-based methods offer opportunities for accelerating progress towards the realization of fusion energy by maximizing the amount and applicability of information extracted from experimental and simulation data. 

AI is used in data analysis, theoretical modelling and experiment design, helping to accelerate fundamental research in the realm of nuclear and atomic data evaluation and compilation and advancing technological innovation.  

By combining digital simulations with AI, the industry can optimize complex procedures and improve reactor design, performance and safety. It can increase the efficiency of operations and reduce maintenance costs.

Role of ML 

Machine learning aids in automating tasks and thereby increasing reliability and avoiding errors. In addition, AI has considerable analytical and predictive potential to help monitor power plant processes and detect anomalies. 

AI can contribute to nuclear security and safety at various levels. It can be used to process data from radiation detection systems to enhance the detection and identification of nuclear and other radioactive material. It can be applied to analyze data from physical protection systems to improve the detection of intruders.  

Safeguards rely on large amounts of data obtained by various means, such as satellite imagery, environmental sampling, gamma ray spectroscopy and video surveillance. AI can help nuclear inspectors and safeguard analysts with the analysis of these data. AI is expected to further improve the efficiency of safeguards implementation by reducing the number of repetitive tasks performed by inspectors. 

Source: Internation Atomic Energy Agency