Research Highlights

Argonne helps develop innovative ways to design experiments and evaluate methods efficiently.

Workshop at Argonne National Laboratory explores AI-driven urban planning and resilience through detailed simulations and data integration.

In a study published in the 2025 IEEE International Conference on eScience, researchers developed an active learning algorithm that doubles the rate of high-quality materials discovery, accelerating the search for advanced materials with generative AI.

Long-term observations and model simulations reveal how urbanization and lakes jointly shape Chicago rainfall

In a study published in Communications Materials, scientists showed that calcite dissolves fastest in strained regions, revealing how defects and strain drive mineral reactivity and enabling more accurate models of mineral behavior.

In a study published in Physical Review A, researchers observed a surprising pseudo-resonance in neon gas using RIXS, revealing a new mechanism that can cause spurious signals in x-ray emission spectra during advanced chemical analysis.