What does this research mean for the field?

Artificial intelligence and machine learning can significantly enhance the design, synthesis, and performance of plasmonic sensors for various applications. Novelty: ClaimNovelty.SYNTHESIS. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

This work aims to explore how artificial intelligence and machine learning can advance plasmonic sensing technologies.

February 27, 2026Chemical Society ReviewsOpen Access

Artificial intelligence and machine learning for plasmonic and surface-enhanced sensing

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Authors

AGAilsa GeddisRegroupement Québécois sur les Matériaux de Pointe HWHannah WilliamsRegroupement Québécois sur les Matériaux de Pointe SBSaba BashirRegroupement Québécois sur les Matériaux de Pointe

Discussion

Member takes

Implication

This review explores AI/ML applications to improve plasmonic sensing sensitivity and robustness in various fields, indicating promising developments.

Key Points

This work aims to explore how artificial intelligence and machine learning can advance plasmonic sensing technologies.
Reviewing current techniques in plasmonic sensing
Discussing AI/ML tools for design and analysis
Identifying applications benefiting from AI/ML integration
AI/ML tools can enhance sensor sensitivity and selectivity
Improved data analysis in plasmonic sensing experiments
AI/ML offers pathways for robust sensor design

Cite This Study

Geddis et al. (2026) studied this question.

synapsesocial.com/papers/69a1359eed1d949a99abfaac https://doi.org/10.1039/d5cs01522g

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February 27, 2026Chemical Society ReviewsOpen Access

Artificial intelligence and machine learning for plasmonic and surface-enhanced sensing

View Full Paper

Ask AI

Bookmark

Authors

Discussion

Member takes

Implication

This review explores AI/ML applications to improve plasmonic sensing sensitivity and robustness in various fields, indicating promising developments.

Key Points

This work aims to explore how artificial intelligence and machine learning can advance plasmonic sensing technologies.
Reviewing current techniques in plasmonic sensing
Discussing AI/ML tools for design and analysis
Identifying applications benefiting from AI/ML integration
AI/ML tools can enhance sensor sensitivity and selectivity
Improved data analysis in plasmonic sensing experiments
AI/ML offers pathways for robust sensor design

Cite This Study

Geddis et al. (2026) studied this question.

synapsesocial.com/papers/69a1359eed1d949a99abfaac https://doi.org/10.1039/d5cs01522g

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