Results 171 to 180 of about 700,233 (319)
Using novel probe‐based metrics, this study evaluates lattice structures on criteria critical to cellular solid optimization. Triply‐periodic minimal surface (TPMS) lattices outperform other lattices, offering more predictable mechanical behavior in complex design spaces and, as a result, higher performance in optimized models.
Firas Breish+2 more
wiley +1 more source
High-Performance, Low-Cost Optical Coherence Tomography System Using a Jetson Orin Nano for Real-Time Control and Image Processing. [PDF]
Wang W+5 more
europepmc +1 more source
Molecular dynamics simulations are advancing the study of ribonucleic acid (RNA) and RNA‐conjugated molecules. These developments include improvements in force fields, long‐timescale dynamics, and coarse‐grained models, addressing limitations and refining methods.
Kanchan Yadav, Iksoo Jang, Jong Bum Lee
wiley +1 more source
Generic Diagramming Platform (GDP): a comprehensive database of high-quality biomedical graphics. [PDF]
Jiang S+13 more
europepmc +1 more source
In this manuscript, the processability of X2CrNiMo17‐12‐2 powder coated with silicon carbide, silicon, and silicon nitride nanoparticles is investigated. The amount of nanoparticles varies from 0.25 to 1 vol%. By coating the powder feedstock material with nanoparticles, an enlargement of the process window and an increase in the build rate are achieved.
Nick Hantke+5 more
wiley +1 more source
Elastic‐Wave Propagation in Chiral Metamaterials: A Couple‐Stress Theory Perspective
The intrinsic chirality of chiral metamaterials renders an effective medium based on the classical continuum theory ineffective for predicting their acoustic activity. This limitation is addressed in the present study by employing augmented asymptotic homogenization to derive a couple‐stress‐based effective medium, enabling accurate predictions in the ...
Shahin Eskandari+5 more
wiley +1 more source
Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani+4 more
wiley +1 more source
Hybrid optimization technique for matrix chain multiplication using Strassen's algorithm. [PDF]
Thota S, Bikku T, T R.
europepmc +1 more source
MNPR: A Framework for Real-Time Expressive Non-Photorealistic Rendering of 3D Computer Graphics
Santiago E. Montesdeoca+6 more
openalex +1 more source
This study examines the mechanical properties of triply periodic minimal surfaces (TPMS)‐based lattices, analyzing 36 architectures in elastic and plastic regimes. It evaluates the applicability of beam‐based scaling laws to TPMS lattices. Rigidity arises from the alignment of members with the load direction and solid regions preventing rotation.
Lucía Doyle+2 more
wiley +1 more source