Principles and Applications of Resonance Energy Transfer Involving Noble Metallic Nanoparticles
Overview
Authors
Affiliations
Over the past several years, resonance energy transfer involving noble metallic nanoparticles has received considerable attention. The aim of this review is to cover advances in resonance energy transfer, widely exploited in biological structures and dynamics. Due to the presence of surface plasmons, strong surface plasmon resonance absorption and local electric field enhancement are generated near noble metallic nanoparticles, and the resulting energy transfer shows potential applications in microlasers, quantum information storage devices and micro-/nanoprocessing. In this review, we present the basic principle of the characteristics of noble metallic nanoparticles, as well as the representative progress in resonance energy transfer involving noble metallic nanoparticles, such as fluorescence resonance energy transfer, nanometal surface energy transfer, plasmon-induced resonance energy transfer, metal-enhanced fluorescence, surface-enhanced Raman scattering and cascade energy transfer. We end this review with an outlook on the development and applications of the transfer process. This will offer theoretical guidance for further optical methods in distance distribution analysis and microscopic detection.
Biomaterials Mimicking Mechanobiology: A Specific Design for a Specific Biological Application.
Donati L, Valicenti M, Giannoni S, Morena F, Martino S Int J Mol Sci. 2024; 25(19).
PMID: 39408716 PMC: 11476540. DOI: 10.3390/ijms251910386.
Recent Advances in Research from Nanoparticle to Nano-Assembly: A Review.
Bandaru S, Arora D, Ganesh K, Umrao S, Thomas S, Bhaskar S Nanomaterials (Basel). 2024; 14(17).
PMID: 39269049 PMC: 11397018. DOI: 10.3390/nano14171387.
Metal Material Processing Using Femtosecond Lasers: Theories, Principles, and Applications.
He Z, Lei L, Lin S, Tian S, Tian W, Yu Z Materials (Basel). 2024; 17(14).
PMID: 39063677 PMC: 11277908. DOI: 10.3390/ma17143386.
Design of Low-Noise CMOS Image Sensor Using a Hybrid-Correlated Multiple Sampling Technique.
Youn S, Yun S, Lee H, Park K, Kim J, Kim S Sensors (Basel). 2023; 23(23).
PMID: 38067924 PMC: 10708822. DOI: 10.3390/s23239551.