# Borohydride Synthesis of Silver Nanoparticles for SERS Platforms: Indirect Glucose Detection and Analysis Using Gradient Boosting

## TL;DR

This paper presents a method to create silver nanoparticle-coated substrates for detecting glucose in biological fluids using Raman spectroscopy and machine learning.

## Contribution

A novel AgNP synthesis method and integration with gradient boosting for accurate glucose detection in SERS platforms.

## Key findings

- AgNP substrates achieved a high enhancement factor of up to 105 for 4-MBA detection.
- Glucose detection was enabled in the 1–10 mM range using GOx-functionalized substrates.
- Gradient boosting models achieved high accuracy (R2 = 0.971) and a low detection limit (0.66 mM).

## Abstract

In recent years, non-invasive methods for the analysis of biological fluids have attracted growing interest. In this study, we propose a straightforward approach to fabricating silver nanoparticle (AgNP)-coated non-woven polyacrylonitrile substrates for surface-enhanced Raman scattering (SERS). AgNPs were synthesized directly on the substrate using borohydride reduction, ensuring uniform distribution. The optimized SERS substrates exhibited a high enhancement factor (EF) of up to 105 for the detection of 4-mercaptobenzoic acid (4-MBA). To enable glucose sensing, the substrates were further functionalized with glucose oxidase (GOx), allowing detection in the 1–10 mM range. Machine learning classification and regression models based on gradient boosting were employed to analyze SERS spectra, enhancing the accuracy of quantitative predictions (R2 = 0.971, accuracy = 0.938, limit of detection = 0.66 mM). These results highlight the potential of AgNP-modified substrates for reliable and reusable biochemical sensing applications.