Evidence map›Paper›PMID 39899114›Full record

ArticleAnalytical and bioanalytical chemistry2025

Requirements for fast multianalyte detection and characterisation via electrochemical-assisted SERS in a reusable and easily manufactured flow cell.

Maximilian E Blaha, Anish Das, Detlev Belder

Abstract read
In one paragraph

Article in Analytical and bioanalytical chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Maximilian E BlahaInstitute for Analytical Chemistry, Leipzig University, Linnéstraße 3, 04103, Leipzig, Germany.
Anish DasInstitute for Analytical Chemistry, Leipzig University, Linnéstraße 3, 04103, Leipzig, Germany.
Detlev BelderInstitute for Analytical Chemistry, Leipzig University, Linnéstraße 3, 04103, Leipzig, Germany. belder@uni-leipzig.de.ORCID http://orcid.org/0000-0001-6295-8706

Funding

Deutsche Forschungsgemeinschaft 460566006
6 · The paper itself

Abstract

Surface-enhanced Raman spectroscopy (SERS) is a highly sensitive analytical technique that captures vibrational spectra of analytes adsorbed to rough coin metal surfaces with remarkable signal intensities. However, its wider application is limited by challenges in substrate range, quantification, and the disposable nature of SERS substrates partly due to irreversible analyte adsorption-commonly referred to as the 'memory effect'. Overcoming these limitations and achieving real-time analysis in flow-through systems remains a key challenge for the advancement of SERS. This study presents a SERS flow cell incorporating an Ag-based SERS substrate and a Pt counter-electrode, enabling the investigation of how electrochemical methods can address existing challenges. Our approach demonstrates that signal intensities can be both enhanced and spectroelectrochemically modified. Additionally, the combination of constant solvent flow and electrochemical potentials enhances the longevity of the SERS substrate, facilitating multianalyte measurements while mitigating the memory effect. Key parameters have been systematically studied, including SERS substrate materials (silver and copper), solvents, buffers, supporting electrolytes, and electrochemical protocols. We achieved consistent and reproducible electrochemical tuning of SERS signals by using halogen-free electrolytes in polar solvents commonly used in techniques like HPLC. The versatility of the system was validated through the analysis of several model compounds and the sequential detection of multiple analytes. We also successfully applied the system to detect and characterise contaminants and pharmaceuticals, highlighting its potential for a wide range of analytical applications.

Indexed as

Electrochemical SERSFlow cellHPLCSERS substratesSurface-enhanced Raman spectroscopy

Identifiers

PMID39899114
PMCPMC11914304

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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.