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It is demonstrated that researchers may make environmentally sustainable choices in research practices by making deliberate choices about agentic AI use, and that the use of LLMs versus other software largely drives the power consumption difference.
This work presents a unified framework that encompasses existing DC methods and extends the task-specific notion of DC to a more general and formal definition using notions of discrepancy, which quantify the distance between probability distribution in different regimes.
Crystal structure prediction (CSP) from powder diffraction data is a central challenge in materials chemistry. Machine learning (ML) models show promise, but most are trained on idealized simulated data, limiting reliability on real experiments. Here, we assess real-world behaviour using the previously published deCIFe...
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