Results 111 to 120 of about 89,932 (268)
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
Rare earths and rare-earth deposits in Canada
J L Jambor, W D Sinclair
openaire +1 more source
Rare-Earth-Attached Polymers for WLEDs: Recent Progress and Perspectives. [PDF]
Lan Q +5 more
europepmc +1 more source
Sustainability assessment requires methodologies that appropriately distinguish between additive and non‐additive material properties. A toxicity‐weighted scoring system is developed and applied that accounts for the disproportionate influence of highly toxic constituents through nonlinear weighting functions, providing more realistic estimates than ...
Seth Mehalic +2 more
wiley +1 more source
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
Rare Earth-Enhanced Laser Cladding Metal-Based Coatings: A Review. [PDF]
Xiao J +8 more
europepmc +1 more source
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
Exceptional Rare-Earth Half-Heusler Thermoelectrics With Sublattice Softening. [PDF]
Miao P +10 more
europepmc +1 more source
Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose +7 more
wiley +1 more source
An Integrative Approach Toward Bio-Inspired Sequestration of Rare Earth Elements. [PDF]
Perevedentseva Y +9 more
europepmc +1 more source

