Plasmonic triangular nanoprism sensors

Otsuki, Joe; Sugawa, Kosuke; Jin, Shota

doi:10.1039/d0ma00644k

Cited by 17 publications

(13 citation statements)

References 109 publications

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“…where E 0 is the electric field strength of the external illumination, m denotes the dielectric constant of the medium in which the nanoparticle is embedded and (ω) denotes the bulk dielectric function of the material [3,33,48]. Here, we use experimental bulk dielectric functions [49] to evaluate Φ tot (z, ω).…”

Section: Methodsmentioning

confidence: 99%

Plasmon-induced hot carriers from interband and intraband transitions in large noble metal nanoparticles

Jin,

Kahk,

Papaconstantopoulos

et al. 2022

Preprint

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Hot electrons generated from the decay of localized surface plasmons in metallic nanostructures have the potential to transform photocatalysis, photodetection and other optoelectronic applications. However, the understanding of hot-carrier generation in realistic nanostructures, in particular the relative importance of interband and intraband transitions, remains incomplete. Here we report theoretical predictions of hot-carrier generation rates in spherical nanoparticles of the noble metals silver, gold and copper with diameters up to 30 nanometers obtained from a novel atomistic linear-scaling approach. As the nanoparticle size increases the relative importance of interband transitions from d-bands to sp-bands relative to surface-enabled sp-band to sp-band transitions increases. We find that the hot-hole generation rate is characterized by a peak at the onset of the d-bands, while the position of the corresponding peak in the hot-electron distribution can be controlled through the illumination frequency. In contrast, intraband transitions give rise to hot electrons, but relatively cold holes. Importantly, increasing the dielectric constant of the environment removes hot carriers generated from interband transitions, while increasing the number of hot carriers from intraband transitions. The insights resulting from our work enable the design of nanoparticles for specific hot-carrier applications through their material composition, size and dielectric environment.

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Section: Methodsmentioning

confidence: 99%

Plasmon-induced hot carriers from interband and intraband transitions in large noble metal nanoparticles

Jin,

Kahk,

Papaconstantopoulos

et al. 2022

Preprint

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“…The sensitivity of Mie resonances to the local refractive index led to the development of plasmonic sensors based on spectral shifts. [54][55][56][57][58] First of all, the plasmonic recognition procedure is traditionally based on nanospheres of a known material (Au). Within our proposed approach, i.e., simultaneously detecting the particle size, its density in the solution, and the environmental RI, we can use a single measurement of an ensemble.…”

Section: Basic Two-parameter Plasmonic Scheme Based On Beer-lambert Lawmentioning

confidence: 99%

Mie Sensing with Neural Networks: Recognition of Nano‐Object Parameters, the Invisibility Point, and Restricted Models

Movsesyan

Besteiro

Wang

et al. 2021

Advcd Theory and Sims

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In this work, artificial neural networks (ANNs) are used to recognize nano-objects solely from the absorbance spectrum of a macroscopic sample. For this, ANNs with two recognition schemes are constructed. The first one is designed to recognize ensembles of dielectric scatterers. The second ANN model recognizes the dimensions of gold nanospheres in a mixture and the refractive index of a matrix. A challenge in the first scheme arises at and near the invisibility point, i.e., when the refractive index of nanoparticles is close to that of the medium. Of course, particle recognition in this regime faces fundamental physical limitations. However, such recognition near the invisibility point is possible, and this study reveals its unique properties. Interestingly, the recognition process for the refractive index in the vicinity of the invisibility point shows very small errors. In contrast, the errors for recognition of the radius grow strongly near this point. Another regime with limited recognition occurs when the extinction spectra are not unique and can correspond to different realizations of nanoparticle mixtures. The recognition schemes proposed and investigated herein can find their applications in sensing.

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“…Metal nanoparticles (NP) find their numerous applications in different fields of fundamental research, industry, and medicine , due to their unique optical properties, electronic structure, tunable surface sites for catalytical reactions, − and antibacterial and anticancer effects. , The gold nanoparticles represent a unique case that combines all these properties. They can be synthesized in different sizes and shapes − that are appropriate, e.g., for the task of dye photodegradation, local electromagnetic field generation, and molecular sensors …”

Section: Introductionmentioning

confidence: 99%

Machine Learning Analysis of Reaction Parameters in UV-Mediated Synthesis of Gold Nanoparticles

et al. 2023

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Gold nanoparticles represent an important class of functional nanomaterials for optoelectronics, biomedical applications, and catalysis. Therefore, controllable synthesis of nanoparticles with specified size and shape is important. Though reduction of gold ions is quite a simple process and may be performed with many different protocols, the reproducibility of the results and transfer of protocols between independent research groups remains a challenging task. Machine learning analysis based on statistical approaches is hardly applicable to the published data, since most of the researchers report only successful syntheses. In this work, we apply uniform sampling of the reaction parameter space. The concentrations of gold precursor, reducing agent, and surfactant were varied via an improved Latin hypercube sampling, and each run was performed under in situ UV−vis control. Based on the resulting set of optical spectra, we address the relevant chemical questions about nanoparticle formation, their shape, and period of growth. Our work demonstrates a data driven approach applied to the space of reaction parameters in a limited available set of experiments.

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Plasmonic triangular nanoprism sensors

Abstract: This review gives a one-stop account of LSPR sensors using Au and Ag nanoprisms from basic physics to recent applications.

Cited by 17 publications

References 109 publications

Plasmon-induced hot carriers from interband and intraband transitions in large noble metal nanoparticles

Plasmon-induced hot carriers from interband and intraband transitions in large noble metal nanoparticles

Mie Sensing with Neural Networks: Recognition of Nano‐Object Parameters, the Invisibility Point, and Restricted Models

Machine Learning Analysis of Reaction Parameters in UV-Mediated Synthesis of Gold Nanoparticles

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