arXiv:2603.28787v1 Announce Type: cross
Abstract: Traditional liquid identification instruments are often unavailable to the general public. This paper shows the feasibility of identifying unknown liquids with commercial lightweight devices, such as a…
arXiv:2602.06241v3 Announce Type: replace
Abstract: High-fidelity simulations of laser welding capture complex thermo-fluid phenomena, including phase change, free-surface deformation, and keyhole dynamics, however their computational cost limits larg…
arXiv:2603.28987v1 Announce Type: cross
Abstract: Aircraft design relies heavily on solving challenging and computationally expensive Multidisciplinary Design Optimization problems. In this context, there has been growing interest in multi-fidelity mo…
arXiv:2603.28325v2 Announce Type: replace-cross
Abstract: Biomedical knowledge resources often either preserve evidence as unstructured text or compress it into flat triples that omit study design, provenance, and quantitative support. Here we present…
arXiv:2603.29865v1 Announce Type: cross
Abstract: Wildfires cause major losses worldwide, and the frequency of fire-weather conditions is likely to increase in many regions. We study the allocation of suppression resources over time on a graph-based r…
arXiv:2603.28707v2 Announce Type: replace-cross
Abstract: We present a physics-based neural network framework for the discovery of constitutive models in fully coupled thermomechanics. In contrast to classical formulations based on the Helmholtz energ…
arXiv:2603.28690v1 Announce Type: new
Abstract: Stable and reliable supplies of rare-Earth minerals and critical raw materials (CRMs) are essential for the development of the European Union. Since a large share of these materials enters the Union from…
arXiv:2603.27448v1 Announce Type: new
Abstract: Generating executable CAD programs from images requires alignment between visual geometry and symbolic program representations, a capability that current methods fail to learn reliably as design complexi…
arXiv:2603.06082v3 Announce Type: replace
Abstract: Recent advances in deep learning inspired neural network-based approaches to computational materials discovery (CMD). A plethora of problems in this field involve finding materials that optimize a ta…
arXiv:2603.28325v1 Announce Type: cross
Abstract: Biomedical knowledge resources often either preserve evidence as unstructured text or compress it into flat triples that omit study design, provenance, and quantitative support. Here we present Evidenc…