Results 191 to 200 of about 1,816,894 (319)

Nonlinear Distortion by Stimulated Brillouin Scattering in Kramers-Kronig Receiver Based Optical Transmission. [PDF]

Sensors (Basel), 2022
Zhu Y, Du J, Shen W, He Z.
europepmc   +1 more source

A Comprehensive Assessment and Benchmark Study of Large Atomistic Foundation Models for Phonons

Advanced Intelligent Discovery, EarlyView.
We benchmark six large atomistic foundation models on 2429 crystalline materials for phonon transport properties. The rapid development of universal machine learning potentials (uMLPs) has enabled efficient, accurate predictions of diverse material properties across broad chemical spaces.
Md Zaibul Anam, Ogheneyoma Aghoghovbia, Mohammed Al‐Fahdi, Lingyu Kong, Victor Fung, Ming Hu   +5 more
wiley   +1 more source

Off-Axis Illumination and Epicollection Confocal Brillouin Scattering Microspectroscopy. [PDF]

Anal Chem
Yui H, Fujiyama Y, Urashima SH, Ota T, Hibino H.   +4 more
europepmc   +1 more source

In-Situ Imaging of a Light-Induced Modification Process in Organo-Silica Films via Time-Domain Brillouin Scattering. [PDF]

Nanomaterials (Basel), 2022
Sandeep S, Vishnevskiy AS, Raetz S, Naumov S, Seregin DS, Husiev A, Vorotilov KA, Gusev VE, Baklanov MR.   +8 more
europepmc   +1 more source

HIGH THROUGHPUT STIMULATED BRILLOUIN SCATTERING SPECTROSCOPY

Brillouin light scattering arises from the coupled interaction between light and material acoustic phonons. The measurand of Brillouin scattering is the characteristic frequency difference between incident and scattered light which depends on the local ...
Rosvold, Jake Robert
core   +1 more source

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

Advanced Intelligent Discovery, EarlyView.
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez, Cibrán López, Edgardo Saucedo, Teruyasu Mizoguchi, Claudio Cazorla   +4 more
wiley   +1 more source

Long Range Raman-Amplified Distributed Acoustic Sensor Based on Spontaneous Brillouin Scattering for Large Strain Sensing. [PDF]

Sensors (Basel), 2022
Bakhtiari Gorajoobi S, Masoudi A, Brambilla G.   +2 more
europepmc   +1 more source

Probing Machine Learning Interatomic Potentials on Ion Transport Properties

Advanced Intelligent Discovery, EarlyView.
We perform a systematic benchmark of six state‐of‐the‐art universal machine learning interatomic potentials on their ability to predict ion transport properties in lithium‐ and sodium‐based superionic conductors relevant to all‐solid‐state batteries.
Ogheneyoma Aghoghovbia, Ming Hu, Adji Bousso Dieng   +2 more
wiley   +1 more source

Temperature sensing based on slow light via stimulated Brillouin scattering in M-shaped few-mode fiber. [PDF]

PLoS One
Li LJ, Hou SL.
europepmc   +1 more source

Numerical model for enhancing stimulated Brillouin scattering in optical microfibers. [PDF]

F1000Res, 2021
Yeap SH, Emami SD, Abdul-Rashid HA.
europepmc   +1 more source