Results 41 to 50 of about 15,043 (195)
Advanced Engineering Materials, EarlyView.Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch +3 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari +5 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.Digitalizing electroplating requires both domain knowledge and interoperability. This work introduces PlatOn, a domain ontology for trivalent chromium plating and coating characterization, and a hybrid pipeline that aligns it to a mid‐level reference ontology by combining eight similarity metrics with language model reasoning. Expert‐validated mappings
Janik Harter +10 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani +7 more
wiley +1 more source
Toward Full Interoperability in Materials Science: Integrating Workflows With Knowledge Graphs
Advanced Engineering Materials, EarlyView.The connection of conceptual workflow design, portable execution, and ontology‐based semantics leading to provenance‐rich knowledge graphs are main contributors to interoperability in materials science and a prerequisite to AI‐assisted orchestration and for interoperable Materials Acceleration Platforms.
Jan Janssen +14 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.This perspective reframes additive manufacturing for electrical machines as a qualification‐limited materials and architecture design problem. It links process–structure–property–performance relationships to magnetic, conducting, dielectric, and thermal property windows, highlighting where AM can enable segmented magnetic circuits, permanent magnet ...
Dénes Fodor, Loránd Szabó
wiley +1 more source
A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys
Advanced Engineering Materials, EarlyView.High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin +14 more
wiley +1 more source
Advanced Materials, EarlyView.Spatiotemporal control over cell behavior within bioprinted constructs remains a key challenge in biofabrication. Volumetric bioprinting using multi‐wavelength light sources permits to activate light‐sensitive intracellular proteins as well as optogenetic gene and protein expression circuits in bioprinted cells, in addition to enabling fast printing of
Davide Ribezzi +14 more
wiley +1 more source
Advanced Optical Materials, EarlyView.Disordered plasmonic metasurfaces enable advanced control over light scattering through disorder engineering. A theoretical model based on multiple scattering theory is developed to predict the coherent reflection and transmission of light from disordered metasurfaces with arbitrary pair correlations.
Jialin Hu, Kevin Vynck
wiley +1 more source
Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback
Advanced Robotics Research, EarlyView.BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat +4 more
wiley +1 more source