Electrochemically assisted wide area Raman with standard curved surface quantification method.

Area of Science:

• Analytical Chemistry
• Spectroscopy
• Electrochemistry

Background:

• Reproducibility in surface-enhanced Raman scattering (SERS) quantitative detection is hindered by substrate fabrication inconsistencies and uneven sample distribution.
• Signal fluctuations within and between SERS substrates pose a significant challenge for reliable quantitative analysis.

Purpose of the Study:

• To develop a novel SERS quantitative method with enhanced reproducibility.
• To address the limitations of traditional SERS quantification by accounting for substrate-specific properties.

Main Methods:

• A new SERS quantitative method was proposed, considering SERS signal intensity, electromagnetic enhancement, sample concentration, and substrate specific surface area.
• Substrate surface area was determined using electrochemical technology (cyclic voltammetry).
• A 3D standard curved surface model (CV-standard curved surface) was developed by integrating surface area information into the standard curve, correcting inter-substrate signal differences.

Main Results:

• The proposed method effectively corrects signal differences between substrates, improving SERS quantitative detection reproducibility.
• Combined with wide-area Raman methods, within-substrate differences were reduced.
• Using malachite green as a probe, the CV-standard curved surface model achieved a root mean square error (RMSE) of 0.26 and a relative error (RE) of 0.25.
• Significant reduction in detection error was observed compared to the traditional standard curve method.

Conclusions:

• The novel SERS quantitative method demonstrates improved reproducibility and accuracy.
• The approach of incorporating substrate surface area information offers a promising strategy for various SERS quantitative applications.
• This technique has potential for broad application in SERS-based quantitative detection.