Results 41 to 50 of about 2,664 (142)
Electrical Conductivities of Conductors, Semiconductors, and Their Mixtures at Elevated Temperatures
This article presents a comprehensive review of temperature‐dependent electrical conductivity data for multiple material classes at elevated temperatures, highlighting a persistent conductivity gap between metals and semiconductors in the range of 102$\left(10\right)^{2}$– 107$\left(10\right)^{7}$ S/m. Metal–ceramic irregular metamaterials are proposed
Valentina Torres Nieto, Marcia A. Cooper
wiley +1 more source
A combined finite element and phase‐field approach predicts the evolution of microstructure during the directional solidification of Ni‐based superalloys. The model reveals how withdrawal rate, temperature gradient, and wall thickness control the dendrite spacing, highlighting the strong effect of surface regions in thin sections where dendrite growth ...
Sean Böhm +3 more
wiley +1 more source
This study presents novel anti‐counterfeiting tags with multilevel security features that utilize additional disguise features. They combine luminescent nanosized Ln‐MOFs with conductive polymers to multifunctional mixed‐matrix membranes and powder composites. The materials exhibit visible/NIR emission and matrix‐based conductivity even as black bodies.
Moritz Maxeiner +9 more
wiley +1 more source
Relative Entropy, Gaussian Concentration and Uniqueness of Equilibrium States. [PDF]
Chazottes JR, Redig F.
europepmc +1 more source
A pore tuning strategy to amplify the multi‐site MOF‐SO2 interactions is proposed to achieve an enhanced trace SO2 capture and chemiresistive sensing in highly stable isostructural DMOFs by annelating benzene rings. This work provides a facile strategy to achieve tailor‐made stable MOF materials for specific multifunctional applications.
Shanghua Xing +9 more
wiley +1 more source
This study examines how pore shape and manufacturing‐induced deviations affect the mechanical properties of 3D‐printed lattice materials with constant porosity. Combining µ‐CT analysis, FEM, and compression testing, the authors show that structural imperfections reduce stiffness and strength, while bulk material inhomogeneities probably enhance ...
Oliver Walker +5 more
wiley +1 more source
Review of Approaches to Minimise the Cost of Simulation-Based Optimisation for Liquid Composite Moulding Processes. [PDF]
Chai BX +6 more
europepmc +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
Mg‐based thermoelectrics are among the most promising candidates for power generation applications but their performance is compromised by Mg loss at device operation temperatures due to the higher chemical potential of Mg (μMg${\mu}_{\mathrm{Mg}}$) inside the material compared to the environment.
Aryan Sankhla +2 more
wiley +1 more source
Multivariate Kalman filtering for spatio-temporal processes. [PDF]
Ferreira G, Mateu J, Porcu E.
europepmc +1 more source

