Results 121 to 130 of about 78,535 (255)

Mitigating stimulated Brillouin scattering in multimode fibers with focused output via wavefront shaping. [PDF]

Nat Commun, 2023
Chen CW, Nguyen LV, Wisal K, Wei S, Warren-Smith SC, Henderson-Sapir O, Schartner EP, Ahmadi P, Ebendorff-Heidepriem H, Stone AD, Ottaway DJ, Cao H.   +11 more
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

Progress in Spectral Information Processing Technology for Brillouin Microscopy

Photonics
This paper systematically reviews the key spectral information extraction methods in Brillouin microscopy, aiming to address the core challenge of accurately extracting material mechanical parameters from raw spectra.
Zhaohong Liu, Xiaoxuan Li, Xiaorui Sun, Zihan Yu, Yunjun Gao, Yun Zhang, Yu Zhou, Qiang Su, Yuanqing Xia, Yulei Wang, Zhiwei Lv   +10 more
doaj   +1 more source

Brillouin Scattering Selection Rules in Polarization-Sensitive Photonic Resonators. [PDF]

ACS Photonics, 2023
Rodriguez A, Priya P, Cardozo de Oliveira ER, Harouri A, Sagnes I, Pastier F, Le Gratiet L, Morassi M, Lemaître A, Lanco L, Esmann M, Lanzillotti-Kimura ND.   +11 more
europepmc   +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

Tuning of the Brillouin scattering properties in microstructured optical fibers by liquid infiltration. [PDF]

Sci Rep, 2023
Catalano E, Vallifuoco R, Zeni L, Dufour A, Marin E, Girard S, Minardo A.   +6 more
europepmc   +1 more source

First‐Principles Investigation of the Electronic, Phonon, Optical, and Elastic Properties of AgBiTeSe

Advanced Physics Research, EarlyView.
This study presents a first‐principles investigation of the electronic, vibrational, optical, and elastic properties of AgBiTeSe. The results highlight its metallic behavior, dynamic stability, strong optical absorption, and promising thermoelectric potential.
Nilufer Yesmin Tanisa, Munshi H. M. Rahat, Sayed Bony Amin, Md. Karimul Islam   +3 more
wiley   +1 more source

Sound Velocity and Equation of State of Ballistic Gelatin by Brillouin Scattering. [PDF]

Materials (Basel), 2023
Ahart M, Hemley RJ.
europepmc   +1 more source

The Virial Expansion of the Hydrogen Equation of State in Comparison to PIMC Simulations: The Quasiparticle Concept, IPD, and Ionization Degree

Contributions to Plasma Physics, EarlyView.
ABSTRACT The properties of plasmas in the low‐density limit are described by virial expansions. Analytical expressions are known for the lowest virial coefficients from Green's function approaches. Recently, accurate path‐integral Monte Carlo (PIMC) simulations were performed for the hydrogen plasma at low densities by Filinov and Bonitz (Phys. Rev.
Gerd Röpke, Chengliang Lin, W. Ebeling, H. Reinholz   +3 more
wiley   +1 more source

Fast Feature Extraction Method for Brillouin Scattering Spectrum of OPGW Optical Cable Based on BOTDR. [PDF]

Sensors (Basel), 2023
Chen X, Yu H.
europepmc   +1 more source