Can AI invent new materials to add to the periodic table ?
Cast your vote — then read what our editor and the AI models found.
Current AI systems excel at modeling hypothetical chemical structures and predicting stable isotopes, but none can “discover” and name a new element in the formal IUPAC sense—elements must be synthesized in accelerator laboratories and verified through repeated experimental observation before official addition to the periodic table. Recent machine-learning models (e.g., GNoME) accelerate the enumeration of previously unknown stable inorganic compounds, yet these are extended materials rather than new elements that would require altering the table itself. Thus, while AI augments discovery pipelines, it remains an assistive tool; only experimental nuclear physics can expand the periodic table. SOURCE: International Union of Pure and Applied Chemistry — https://iupac.org
— Enriched May 13, 2026
Currently, AI can assist in the discovery of new materials by predicting their properties and behavior, but it cannot independently invent new elements to add to the periodic table. The process of discovering new elements involves complex experiments and verification by the scientific community. AI can, however, help scientists identify potential new materials and their properties by analyzing large datasets and running simulations. This can accelerate the discovery process, but human scientists are still necessary to design and conduct experiments to verify the existence and properties of new materials. Researchers use AI to screen potential new materials and predict their behavior under various conditions, which can help focus experimental efforts. While AI is a powerful tool in the discovery of new materials, the actual creation of new elements is a complex process that requires careful experimentation and verification. The addition of new elements to the periodic table is overseen by the International Union of Pure and Applied Chemistry (IUPAC), which ensures that new elements meet strict criteria for recognition. AI's role in materials science is rapidly evolving, and it is likely to play an increasingly important role in the discovery of new materials in the future.
— Enriched May 13, 2026 · Source: Science Magazine — International Union of Pure and Applied Chemistry
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Status last checked on May 13, 2026.
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