AI Discovers Breakthrough Material to Remove Radioactive Iodine

AI discovers material for radioactive iodine cleanup

Managing radioactive waste remains one of the most critical challenges in advancing nuclear energy technology. In particular, radioactive iodine—especially isotope I-129—presents a long-lasting environmental hazard due to its extreme toxicity, high mobility, and a half-life exceeding 15 million years. Now, researchers in South Korea have leveraged artificial intelligence (AI) to discover a powerful new material capable of removing radioactive iodine from contaminated environments.

This breakthrough, published in the Journal of Hazardous Materials, could revolutionize nuclear waste management and environmental remediation strategies globally.

AI Accelerates Materials Discovery

A team led by Professor Ho Jin Ryu from the Department of Nuclear and Quantum Engineering, in collaboration with Dr. Juhwan Noh at the Korea Research Institute of Chemical Technology, adopted a machine learning approach to design new materials for iodine adsorption. By applying active learning algorithms, they efficiently screened thousands of potential compounds, dramatically reducing the time and effort needed compared to traditional trial-and-error experiments.

The team focused on a class of compounds called Layered Double Hydroxides (LDHs), which can incorporate a wide range of metal ions into their structure. The AI-driven search led to the discovery of a multi-metal LDH—Cu₃(CrFeAl)—comprising copper, chromium, iron, and aluminum, which demonstrated exceptional performance, removing over 90% of iodate from water samples.

Implications for Nuclear Waste Remediation

Radioactive iodine is a significant component of nuclear waste, often found in water as iodate (IO₃⁻). Current silver-based adsorbents lack sufficient binding strength for iodate, making them less effective for cleanup efforts. The newly discovered LDH addresses these limitations with superior chemical affinity and structural robustness, enabling efficient and scalable removal of radioactive contaminants.

This advancement is particularly timely as nuclear energy plays an increasingly central role in global efforts to achieve carbon neutrality, necessitating safer waste management practices.

Next Steps and Commercialization

The research team has filed both domestic and international patents for this technology and is working on scaling it for practical applications, including filters for treating contaminated water and iodine-adsorbing powders. Industry-academia collaborations are underway to bring this innovation to market, which could have significant implications for nuclear facility decontamination and environmental protection.

Read the full article here: AI helps discover optimal new material for removing radioactive iodine contamination.

Sponsored by PWmat (Lonxun Quantum) – a leading developer of GPU-accelerated materials simulation software for cutting-edge quantum, energy, and semiconductor research. Learn more about our solutions at: https://www.pwmat.com/en

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#ArtificialIntelligence #MaterialsScience #NuclearWaste #EnvironmentalRemediation #RadioactiveIodine #MachineLearning #QuantumServerNetworks #PWmat

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