MétaCan
Menu
Back to cohort
Record W3133337221 · doi:10.1016/j.sbsr.2021.100406

Fast, highly sensitive and label free detection of small genetic sequence difference of DNA using novel Surface-Enhanced Raman Spectroscopy nanostructured sensor

2021· article· en· W3133337221 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSensing and Bio-Sensing Research · 2021
Typearticle
Languageen
FieldMaterials Science
TopicGold and Silver Nanoparticles Synthesis and Applications
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNatural Sciences and Engineering Research Council of CanadaAmerican University of Sharjah
KeywordsRaman spectroscopySurface-enhanced Raman spectroscopyBiomoleculeMaterials scienceNanotechnologyNanoparticleIsotropic etchingAnalytical Chemistry (journal)SpectroscopySiliconEtching (microfabrication)OptoelectronicsChemistryRaman scatteringChromatographyOptics

Abstract

fetched live from OpenAlex

In this work we present a fast and label-free technique for biomolecules detection. The approach has been proved to be powerful to investigate small DNA mutation. Surface enhanced Raman spectroscopy (SERS) is an outstanding technique for DNA analyses by providing a specific fingerprint of chemical structure with a high sensitivity in a very short acquisition time. Homogeneous decoration of Silicon nanowires (SiNWs) by silver nanoparticles (Ag-NPs) was carried out using pulsed laser deposition (PLD) technique. SiNWs have been synthesized via metal-assisted chemical etching (MACE) method. We investigate in this work the effect of the Ag-NPs nanodecoration conditions through the variation of the laser ablation pulses number (NLAP). Thus, the Ag-NPs decorated SiNWs were used as sensors to detect organic and biomolecules by means of Surface Enhanced Raman Spectroscopy (SERS). By varying the NLAP, we were able to identify the optimal combination of Ag-NPs' size and surface coverage that yields the highest SERS signal. SEM images revealed well-ordered SiNWs (~2.4 μm-long and 30–60 nm diam.) with their uniform decoration by Ag-NP. High resolution-TEM analyses confirmed the effective decoration of the SiNWs by Ag-NPs of which average size is found to increase linearly from ~20 to 50 nm when the NLAP is increased from 500 to 10,000. The Ag-NPs/SiNWs matrix shows significantly higher (150 fold) Raman signal compared to their Ag-NPs-decorated-flat‑silicon counterparts. We found that SERS efficiency is sensitive to the nanoparticles size and reaches its maximum of (1.6 × 106) for the Ag-NPs having the optimal diameter of ~40 nm (obtained at NLP = 5000). The developed sensor proved to be highly sensitive to detect upto pico-molar concentrations of R6G. These Ag-NPs/SiNWs probes were demonstrated to have outstanding potential for label free detection of DNA samples with high sensitivity and reproducibility. It was found that the developed nanohybrid sensor is able to differentiate DNAs with very small genetic sequence difference.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.661

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.069
GPT teacher head0.309
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it