Near-field and Far-field Optical Properties of Silver Nanospheres: Theoretical and Experimental Investigations of the Size, Shape, Dielectric Environment, and Composition Effects

2021 ◽  
Vol 57 (6) ◽  
pp. 1180-1190
Author(s):  
Marzieh Khademalrasool ◽  
Mansoor Farbod ◽  
Mohammad Davoud Talebzadeh
Nanoscale ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 5402-5411 ◽  
Author(s):  
Min Xi ◽  
Björn M. Reinhard

The effect of composition and tip morphology on the far-field optical response of Ag–Au–Ag nanorods with Au bipyramid core is quantified, and the near-field associated with standing plasmon waves in nanorods on silicon substrates is investigated.


2015 ◽  
Vol 112 (33) ◽  
pp. 10292-10297 ◽  
Author(s):  
Michael B. Ross ◽  
Jessie C. Ku ◽  
Martin G. Blaber ◽  
Chad A. Mirkin ◽  
George C. Schatz

Bottom-up assemblies of plasmonic nanoparticles exhibit unique optical effects such as tunable reflection, optical cavity modes, and tunable photonic resonances. Here, we compare detailed simulations with experiment to explore the effect of structural inhomogeneity on the optical response in DNA-gold nanoparticle superlattices. In particular, we explore the effect of background environment, nanoparticle polydispersity (>10%), and variation in nanoparticle placement (∼5%). At volume fractions less than 20% Au, the optical response is insensitive to particle size, defects, and inhomogeneity in the superlattice. At elevated volume fractions (20% and 25%), structures incorporating different sized nanoparticles (10-, 20-, and 40-nm diameter) each exhibit distinct far-field extinction and near-field properties. These optical properties are most pronounced in lattices with larger particles, which at fixed volume fraction have greater plasmonic coupling than those with smaller particles. Moreover, the incorporation of experimentally informed inhomogeneity leads to variation in far-field extinction and inconsistent electric-field intensities throughout the lattice, demonstrating that volume fraction is not sufficient to describe the optical properties of such structures. These data have important implications for understanding the role of particle and lattice inhomogeneity in determining the properties of plasmonic nanoparticle lattices with deliberately designed optical properties.


Author(s):  
Jason M. Anderson ◽  
Devin O. Stewart ◽  
William K. Blake

Turbulent boundary layer flows over rough surfaces are known to produce elevated far-field acoustic sound levels. The nature by which surface irregularities alter the near-field surface pressures and subsequently affect the sound generation to the scattering of high wavenumber convective pressures to low wavenumber acoustic pressures, which is typically interpreted as a dipole-like source. The focus of the current investigation is the experimental interrogation of both near- and far-field pressures due to the flow over roughened surfaces in order to identify the source mechanisms and to validate physical models of roughness sound. For rough surfaces composed of large geometrical elements (defined by large Reynolds numbers based on roughness height and friction velocity), such as hemispheres and cubes, the measured near-field surfaces pressures indicate that the local interstitial flows become important in determining the sound radiation characteristics. In order to describe the aeroacoustic source region, scaling laws are developed for surface pressures at locations around the roughness elements for various roughness configurations and flow speeds. Relationships between surface pressures amongst the rough surface elements and far-field pressures measured at several directional aspects were examined to identify roughness sound source mechanisms. Measurements of a dipole directivity pattern and dipole efficiency factors obtained when normalizing radiated sound by surface pressures offer support to the scattering theories for roughness sound. Using existing pressure scattering models as a basis, an empirical model for roughness sound is generated.


2001 ◽  
Vol 89 (2) ◽  
pp. 1138-1144 ◽  
Author(s):  
B. Dumay ◽  
N. Richard ◽  
T. David ◽  
E. Bourillot ◽  
F. Scheurer ◽  
...  

2019 ◽  
Vol 36 (7) ◽  
pp. E36 ◽  
Author(s):  
Iman Ragheb ◽  
Macilia Braik ◽  
Abdelaziz Mezeghrane ◽  
Leïla Boubekeur-Lecaque ◽  
Abderrahmane Belkhir ◽  
...  

Nanoscale ◽  
2019 ◽  
Vol 11 (37) ◽  
pp. 17444-17459 ◽  
Author(s):  
Jing He ◽  
Chang He ◽  
Chao Zheng ◽  
Qian Wang ◽  
Jian Ye

Ultrafast and computing resource-saving prediction of the far- and near-field optical properties of plasmonic nanoparticles and inverse design of their dimensions from the far-field spectra can be realized using machine learning.


Sign in / Sign up

Export Citation Format

Share Document