What does this research mean for the field?

Silver nanoparticles synthesized from guava leaf extract provide an accurate and reliable colorimetric method for detecting and quantifying amoxicillin in pharmaceutical formulations. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

To develop and validate a green colorimetric quantification method for amoxicillin in pharmaceutical formulations using silver nanoparticles synthesized from Psidium guajava leaf extract.

September 3, 2026Results in ChemistryOpen Access

Surface plasmon resonance-based colorimetric sensing of amoxicillin in pharmaceuticals using Psidium guajava leaf extract-mediated silver nanoparticles

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Authors

QTQuoc-An Trieu TMTam Minh Mai DVDong Nguyen Van

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Overview

Analytical study reveals surface plasmon resonance-based amoxicillin detection in pharmaceuticals using plant-synthesized silver nanoparticles, indicating a viable green chemistry approach.

Key Points

To develop and validate a green colorimetric quantification method for amoxicillin in pharmaceutical formulations using silver nanoparticles synthesized from Psidium guajava leaf extract.
Synthesized silver nanoparticles using guava leaf extract (AgNPs-GuLE) and optimized assay parameters including pH (4–4.5), nanoparticle-to-analyte volume ratio (1:1), and buffer concentration (160 mM).
Characterized nanoparticle aggregation mechanisms in the presence of amoxicillin using dynamic light scattering (DLS) and scanning transmission electron microscopy (STEM).
Validated the analytical method across commercial pharmaceutical dosage forms including capsules, tablets, and powders.
The assay achieved a linear detection range of 2–10 mg/L with a limit of detection of 2.5 mg/L and a limit of quantification of 2.7 mg/L.
Method precision and accuracy demonstrated an analytical recovery rate of 108.8% (± 6.3%), repeatability relative standard deviation (RSDr) of 2.8%, and intermediate precision (RSDI) of 6.5%.
Quantification of commercial amoxicillin formulations met standard regulatory thresholds, yielding recoveries within the acceptable 90–110% range.

Cite This Study

Trieu et al. (2026) studied this question.

synapsesocial.com/papers/6a99355b636c6408cfa7d899 https://doi.org/10.1016/j.rechem.2026.103823

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September 3, 2026Results in ChemistryOpen Access

Surface plasmon resonance-based colorimetric sensing of amoxicillin in pharmaceuticals using Psidium guajava leaf extract-mediated silver nanoparticles

View Full Paper

Ask AI

Bookmark

Authors

QTQuoc-An Trieu TMTam Minh Mai DVDong Nguyen Van

Discussion

Member takes

Overview

Analytical study reveals surface plasmon resonance-based amoxicillin detection in pharmaceuticals using plant-synthesized silver nanoparticles, indicating a viable green chemistry approach.

Key Points

To develop and validate a green colorimetric quantification method for amoxicillin in pharmaceutical formulations using silver nanoparticles synthesized from Psidium guajava leaf extract.
Synthesized silver nanoparticles using guava leaf extract (AgNPs-GuLE) and optimized assay parameters including pH (4–4.5), nanoparticle-to-analyte volume ratio (1:1), and buffer concentration (160 mM).
Characterized nanoparticle aggregation mechanisms in the presence of amoxicillin using dynamic light scattering (DLS) and scanning transmission electron microscopy (STEM).
Validated the analytical method across commercial pharmaceutical dosage forms including capsules, tablets, and powders.
The assay achieved a linear detection range of 2–10 mg/L with a limit of detection of 2.5 mg/L and a limit of quantification of 2.7 mg/L.
Method precision and accuracy demonstrated an analytical recovery rate of 108.8% (± 6.3%), repeatability relative standard deviation (RSDr) of 2.8%, and intermediate precision (RSDI) of 6.5%.
Quantification of commercial amoxicillin formulations met standard regulatory thresholds, yielding recoveries within the acceptable 90–110% range.

Cite This Study

Trieu et al. (2026) studied this question.

synapsesocial.com/papers/6a99355b636c6408cfa7d899 https://doi.org/10.1016/j.rechem.2026.103823

View Full Paper

Ask AI

Bookmark