Results 91 to 100 of about 68,467 (331)
An idea of designing novel sensors is proposed by creating appropriate Schottky barriers and vacancies between isomorphous Core‐CuOii/ Shell‐CuOi secondary microspheres and enhancing catalytic and spill‐over effects, and electronegativity via spontaneous biphasic separation, self‐assembly, and trace‐Ni‐doping.
Bala Ismail Adamu +8 more
wiley +1 more source
Advanced materials for solid-state refrigeration
Recent progress on caloric effects are reviewed. The application of external stimuli such as magnetic field, hydrostatic pressure, uniaxial stress and electric field give rise respectively to magnetocaloric, barocaloric, elastocaloric and electrocaloric ...
Acet, Mehmet +2 more
core +1 more source
What Do Large Language Models Know About Materials?
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
Twenty-one distinct AlxCoCrFeNi alloys were rapidly prepared by laser alloying an equiatomic CoCrFeNi substrate with Al powder to create an alloy library ranging x=0.15-1.32.
Borisevich, Albina +4 more
core +1 more source
Data-Driven Discovery and Synthesis of High Entropy Alloy Hydrides with Targeted Thermodynamic Stability [PDF]
Matthew Witman +8 more
openalex +1 more source
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice +2 more
wiley +1 more source
Current status and prospects in machine learning-driven design for refractory high-entropy alloys
Due to excellent comprehensive properties such as high strength, high hardness, and excellent high-temperature oxidation resistance, the refractory high-entropy alloys have broad application prospects and research value in the fields of aerospace and ...
GAO Tianchuang +3 more
doaj +1 more source
A differential cluster variation method for analysis of spiniodal decomposition in alloys
A differential cluster variation method (DCVM) is proposed for analysis of spinoidal decomposition in alloys. In this method, lattice symmetry operations in the presence of an infinitesimal composition gradient are utilized to deduce the connection ...
Gao, Huajian, Liu, Zhi-Rong
core +1 more source
Discovery of high-entropy ceramics via machine learning [PDF]
Although high-entropy materials are attracting considerable interest due to a combination of useful properties and promising applications, predicting their formation remains a hindrance for rational discovery of new systems.
Curtarolo, Stefano +9 more
core +1 more source
In this experimental study, the mechanical properties of additively manufactured Ti‐6Al‐4V lattice structures of different geometries are characterized using compression, four point bending and fatigue testing. While TPMS designs show superior fatigue resistance, SplitP and Honeycomb lattice structures combine high stiffness and strength. The resulting
Klaus Burkart +3 more
wiley +1 more source

