Results 151 to 160 of about 456,099 (285)
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
Multiobjective Optimization Analysis of Gas-Steam Combined Cycle Coupled with Photovoltaic-Driven Hydrogen Electrolyzer System. [PDF]
Chai L +5 more
europepmc +1 more source
A reproducible synthesis to control 3D/0D phase ratios via water‐tuned solvent–antisolvent methods is presented. Enhanced scintillation yield and ultrafast decay are achieved. Defect‐driven emission mechanisms are revealed through cathodoluminescence and radioluminescence, shedding light on the underexplored role of the 0D Cs4PbBr6 and mixed 0D/3D ...
Mario Calora +18 more
wiley +1 more source
Quantitative Evaluation of the Blending Between Virgin and Aged Aggregates in Hot-Mix Recycled Asphalt Mixtures. [PDF]
Zou H +6 more
europepmc +1 more source
A food‐grade cooling composite made from starch and recycled eggshell powder offers a scalable, ultra‐low‐cost solution for passive daytime radiative cooling. Easily prepared using basic kitchen tools, this material empowers communities, even in areas with limited infrastructure, to stay cooler during worsening summer heat waves.
Qimeng Song +3 more
wiley +1 more source
Statistical optimization of crumb rubber modified bitumen performance through material blending analysis. [PDF]
Memon NA +5 more
europepmc +1 more source
Multicolor optoelectronic synapses are realized by vertically integrating solution‐processed MoS2 thin‐film and SWCNT. The electronically disconnected but interactive MoS2 enables photon‐modulated remote doping, producing a bi‐directional photoresponse.
Jihyun Kim +8 more
wiley +1 more source
Enhancing the robustness of a near-infrared (NIR) model for determining the blending proportion of cut tobacco by accounting for variations in moisture content. [PDF]
Lai J +5 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

