Dataset Information

Hybrid Porous Silicon Biosensors Using Plasmonic and Fluorescent Nanomaterials: A Mini Review.

ABSTRACT: During the last two decades, porous silicon (PSi) has been proposed as a high-performance biosensing platform due to its biocompatibility, surface tailorability, and reproducibility. This review focuses on the recent developments and progress in the area related to hybrid PSi biosensors using plasmonic metal nanoparticles (MNPs), fluorescent quantum dots (QDs), or a combination of both MNPs and QDs for creating hybrid nanostructured architectures for ultrasensitive detection of biomolecules. The review discusses the mechanisms of sensitivity enhancement based on Localized Surface Plasmon Resonance (LSPR) of MNPs, Fluorescence Resonance Energy Transfer (FRET) in the case of MNPs/QDs donor-acceptor interactions, and photoluminescence/fluorescence enhancement resulting from the embedded fluorescent QDs inside the PSi microcavity. The review highlights the key features of hybrid PSi/MNPs/QDs biosensors for dual-mode detection applications.

SUBMITTER: Abu-Thabit N

PROVIDER: S-EPMC7272471 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Hybrid Porous Silicon Biosensors Using Plasmonic and Fluorescent Nanomaterials: A Mini Review.

Abu-Thabit Nedal N Ratemi Elaref E

Frontiers in chemistry 20200529

During the last two decades, porous silicon (PSi) has been proposed as a high-performance biosensing platform due to its biocompatibility, surface tailorability, and reproducibility. This review focuses on the recent developments and progress in the area related to hybrid PSi biosensors using plasmonic metal nanoparticles (MNPs), fluorescent quantum dots (QDs), or a combination of both MNPs and QDs for creating hybrid nanostructured architectures for ultrasensitive detection of biomolecules. The ...[more]

PMID: 32548094

Similar Datasets

Project description:In this work, we have designed highly sensitive plasmonic metasensors based on atomically thin perovskite nanomaterials with a detection limit up to 10-10 refractive index units (RIU) for the target sample solutions. More importantly, we have improved phase singularity detection with the Goos-Hänchen (GH) effect. The GH shift is known to be closely related to optical phase signal changes; it is much more sensitive and sharp than the phase signal in the plasmonic condition, while the experimental measurement setup is much more compact than that of the commonly used interferometer scheme to exact the phase signals. Here, we have demonstrated that plasmonic sensitivity can reach a record-high value of 1.2862 × 109 µm/RIU with the optimum configurations for the plasmonic metasensors. The phase singularity-induced GH shift is more than three orders of magnitude larger than those achievable in other metamaterial schemes, including Ag/TiO2 hyperbolic multilayer metamaterials (HMMs), metal-insulator-metal (MIM) multilayer waveguides with plasmon-induced transparency (PIT), and metasurface devices with a large phase gradient. GH sensitivity has been improved by more than 106 times with the atomically thin perovskite metasurfaces (1.2862 × 109 µm/RIU) than those without (918.9167 µm/RIU). The atomically thin perovskite nanomaterials with high absorption rates enable precise tuning of the depth of the plasmonic resonance dip. As such, one can optimize the structure to reach near zero-reflection at the resonance angle and the associated sharp phase singularity, which leads to a strongly enhanced GH lateral shift at the sensor interface. By integrating the 2D perovskite nanolayer into a metasurface structure, a strong localized electric field enhancement can be realized and GH sensitivity was further improved to 1.5458 × 109 µm/RIU. We believe that this enhanced electric field together with the significantly improved GH shift would enable single molecular or even submolecular detection for hard-to-identify chemical and biological markers, including single nucleotide mismatch in the DNA sequence, toxic heavy metal ions, and tumor necrosis factor-α (TNFα).

Dataset Information

Hybrid Porous Silicon Biosensors Using Plasmonic and Fluorescent Nanomaterials: A Mini Review.

Publications

Hybrid Porous Silicon Biosensors Using Plasmonic and Fluorescent Nanomaterials: A Mini Review.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure