Evidence map›Paper›PMID 29703986›Full record

ArticleScientific reports2018

Improved method for estimating adlayer thickness and bulk RI change for gold nanocrescent sensors.

Ahmed Abumazwed, Wakana Kubo, Takuo Tanaka, Andrew G Kirk

Abstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ahmed AbumazwedDepartment of Electrical and Computer Engineering, McGill University, Montreal, H3A 2A9, Canada. ahmed.abumazwed@mail.mcgill.ca.
Wakana KuboDepartment of Electrical and Electronic Engineering, Tokyo University of Agriculture and Technology, Tokyo, 184-8588, Japan.
Takuo TanakaMetamaterials Laboratory, RIKEN, Wako, Saitama, 351-0198, Japan.
Andrew G KirkDepartment of Electrical and Computer Engineering, McGill University, Montreal, H3A 2A9, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper presents a novel method employing the maximum likelihood estimation (MLE) technique alongside a nonlinear sensor response model to improve and extract more quantitative sensing results for localized surface plasmon resonance biosensors. The nonlinear response model treats the sensor response as a nonlinear function of the biomolecular adlayer thickness. This method makes use of the multiple resonance characteristic of nanocrescent structures in order to estimate the adlayer thickness and bulk refractive index (RI) change. Nanoimprint lithography is used here to fabricate the nanostructures. The finite element method (FEM) is used to model the nanocrescents and numerically validate the nonlinear-MLE method. Comparing to the established linear model, the proposed nonlinear-MLE method achieves 75% improvement in the limit of detection based on the estimated adlayer thickness and improves the bulk RI resolution by two orders of magnitude.

Identifiers

PMID29703986
PMCPMC5923337

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.