1 citations · 2 across the 5 of their papers we have counts for
4 papers · 1 filter
Which alloy composition,what process parameters? Inferring the recipe from optimized metallic microstructure and texture
Mahish K. Guru, Jan Bohlen, Louam Lemjid +3
The mechanical properties of a metallic alloy are set by its microstructure and texture: the size and shape of its grains and the orientation of their crystals. That structure is i…
Molecular Déjà Vu: Digit-Level Retrieval of Molecular Properties in Frontier Language Models
Matthias Busch, Marius Tacke, Sviatlana V. Lamaka +4
Large language models (LLMs) are increasingly employed to predict molecular properties. However, prediction error alone cannot distinguish prediction from retrieval of published va…
LLM-driven design of physics-constrained constitutive models: two agents are better than one
Marius Tacke, Matthias Busch, Kian Abdolazizi +4
Developing constitutive models that capture how materials deform under load traditionally requires years of specialized expertise in continuum mechanics, machine learning, and scie…
In-Context Molecular Property Prediction with LLMs: A Blinding Study on Memorization and Knowledge Conflicts
Matthias Busch, Marius Tacke, Sviatlana V. Lamaka +4
The capabilities of large language models (LLMs) have expanded beyond natural language processing to scientific prediction tasks, including molecular property prediction. However,…