Results 151 to 160 of about 1,347,292 (277)
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
Incline dependence of the power-duration relationship in cross-country skiing. [PDF]
Horvath M +6 more
europepmc +1 more source
Graph Spectra Based Controlled Islanding for Low Inertia Power Systems
Lei Ding +3 more
openalex +2 more sources
This review explores functional and responsive materials for triboelectric nanogenerators (TENGs) in sustainable smart agriculture. It examines how particulate contamination and dirt affect charge transfer and efficiency. Environmental challenges and strategies to enhance durability and responsiveness are outlined, including active functional layers ...
Rafael R. A. Silva +9 more
wiley +1 more source
Research on energy-saving algorithm of HVAC multi-agent system consensus based on event-triggered mechanism. [PDF]
Wu W, Shi S, Lin M, Gong H, Li J.
europepmc +1 more source
MOFs and COFs in Electronics: Bridging the Gap between Intrinsic Properties and Measured Performance
Metal‐organic frameworks (MOFs) and covalent organic frameworks (COFs) hold promise for advanced electronics. However, discrepancies in reported electrical conductivities highlight the importance of measurement methodologies. This review explores intrinsic charge transport mechanisms and extrinsic factors influencing performance, and critically ...
Jonas F. Pöhls, R. Thomas Weitz
wiley +1 more source
Intelligent fault prediction and diagnosis for wind-powered heating systems using graph neural networks. [PDF]
Wang Y, Zhao J, Tang D, Zhao W, Huang S.
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
Graph Based, Adaptive, Multiarm, Multiple Endpoint, Two-Stage Designs. [PDF]
Mehta C, Mukhopadhyay A, Posch M.
europepmc +1 more source
Development of Cyber-Attack Scenarios for Nuclear Power Plants Using Scenario Graphs [PDF]
Woogeun Ahn +3 more
openalex +1 more source

