Results 191 to 200 of about 5,958,127 (312)
Advanced Materials, EarlyView.Biomechanical‐to‐electrical energy conversion devices are uniquely suited for self‐driven physiological information monitoring and powering human–computer interaction systems. These devices based on micro‐/nanoarchitectured inorganic dielectric materials (MNIDMs) have shown ultrahigh electromechanical performance and thus great potential for practical ...
Jia‐Han Zhang +12 more
wiley +1 more source
Superior Adhesion of Monolayer Amorphous Carbon to Copper
Advanced Materials, EarlyView.The adhesion energy of monolayer amorphous carbon on copper substrate is 85 J m−2, 13 times higher than that of graphene due to covalent‐like bonding between the sp2 carbon structure to copper. X‐ray photoelectron spectroscopy (XPS), near‐edge X‐ray absorption (NEXAFS), and (density functional theory) DFT calculations are used to elucidate the ...
Hongji Zhang +27 more
wiley +1 more source
A mathematical model platform for optimizing a multiprojection breast imaging system [PDF]
, 2008 Amarpreet S. Chawla +4 more
openalex +1 more source
Glaphene: A Hybridization of 2D Silica Glass and Graphene
Advanced Materials, EarlyView.‘Glaphene’, a novel hybrid material combining 2D silica glass and graphene, is synthesized via a scalable liquid precursor‐based vapor‐phase growth. This study reveals interlayer hybridization beyond van der Waals interactions, leading to emergent semiconducting behavior.
Sathvik Ajay Iyengar +10 more
wiley +1 more source
The mathematics of continuous-variable simulation optimization [PDF]
, 2008 Sujin Kim, Shane G. Henderson
openalex +1 more source
On‐Chip Active Supercoupled Topological Cavity
Advanced Materials, EarlyView.The on‐chip supercoupled cavity device is demonstrated realizing a record cavity excitation distance exceeding three wavelengths, leveraging the valley‐conserved supercoupling mechanism in the valley Hall topological system. This optothermal tunable design enables new degrees of freedom for supercoupled photonic cavities in mux‐demux, lasers, sensors ...
Ridong Jia +7 more
wiley +1 more source
Characterization and Inverse Design of Stochastic Mechanical Metamaterials Using Neural Operators
Advanced Materials, EarlyView.This study presents a DeepONet‐based machine learning framework for designing stochastic mechanical metamaterials with tailored nonlinear mechanical properties. By leveraging sparse but high‐quality experimental data from in situ micro‐mechanical tests, high predictive accuracy and enable efficient inverse design are achieved.
Hanxun Jin +7 more
wiley +1 more source
Drilling cost optimization in a hydrocarbon field by combination of comparative and mathematical methods [PDF]
, 2009 Abouzar Bahari, A. Baradaran Seyed
openalex +1 more source