Results 101 to 110 of about 1,251,586 (168)
Observation of inherent chiral Smith-Purcell effect via symmetry breaking. [PDF]
Zhu JF +11 more
europepmc +1 more source
From optical architectures to actual deployment a review of online process spectroscopy in industrial environments. [PDF]
Zhuo H +6 more
europepmc +1 more source
A multimode fiber probe collects far more of the near field than a single‐mode one, but scrambles the phase into speckle. Phase conjugation on a spatial light modulator restores the wavefront, concentrating the signal up to 165‐fold at a single detector pixel and recovering the full phase of propagating surface plasmon polaritons where conventional ...
Juntaek Oh +4 more
wiley +1 more source
Dual-Polarized Thermal Emission from a Bilayer Twisted-Grating Metasurface. [PDF]
Zhang X, Yang C, Cai W, Zhang Z.
europepmc +1 more source
Direct Grating Writing (DGW) has been developed over the past decade as a means of rapidly prototyping waveguides with integrated Bragg grating structures in silica-on-silicon substrates [1].
Snow, Benjamin +8 more
core +1 more source
Toroidal Dipole‐Dominated High‐Performance Optical Sensors via Nanoimprinted Tetramer Architectures
We developed a scalable low‐cost nanoimprinted tetramer architecture (NTA) sensor using two‐step nanoimprint lithography. It comprises polystyrene nanopillar tetramer arrays on a PS waveguide and gold mirror, supporting a toroidal‐dipole‐mediated resonant mode at 810 nm with a simulated Q of 3124.
Hongsen Zhao +8 more
wiley +1 more source
FastNano Liquid: An Automated Platform for Small‐Angle X‐ray Scattering‐Based Materials Discovery
We present FastNano Liquid, an automated small‐ and wide‐angle X‐ray scattering platform for the combined synthesis and characterization of (nano)materials. The platform is coupled to varied reactor workflows for both in situ studies of reaction kinetics and ex situ screening of synthesis conditions to support machine learning‐guided exploration ...
Pierre‐Baptiste Flandrin +16 more
wiley +1 more source
A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin +14 more
wiley +1 more source
Cathodoluminescence Wavefront Retrieval. [PDF]
Machfuudzoh I, Horisaki R, Sannomiya T.
europepmc +1 more source
Precise measurement of the Kerr coefficient using phase-sensitive pump-probe hyperspectral imaging. [PDF]
Wahlstrand JK, Cruz CD.
europepmc +1 more source

