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Updated: Aug 5, 2026
08:13
A Filter-based Surface Enhanced Raman Spectroscopic Assay for Rapid Detection of Chemical Contaminants
Published on: February 19, 2016
Intelligent chemical sensors: learning-enabled platforms for adaptive chemical detection
Rashida Batool1, Nazmina Imrose Sonil2, Muhammad Faizan Nazar1
1Department of Chemistry, Division of Science and Technology, University of Education Lahore 54770 Pakistan.
RSC Advances
|July 29, 2026
Summary
Intelligent chemical sensors use adaptive behavior for better performance. This review explores how functional materials and learning paradigms create adaptive chemical detection systems for complex environments.
Area of Science:
- Materials Science
- Sensor Technology
- Artificial Intelligence
Background:
- Conventional chemical sensors lack adaptability in complex environments.
- Advances in sensing materials necessitate intelligent system design.
Purpose of the Study:
- To review intelligent chemical sensors as learning-enabled platforms.
- To provide a materials-centric, system-aware perspective on adaptive chemical detection.
Main Methods:
- Discussing integration of intelligence in sensing pipelines.
- Exploring adaptive transduction strategies with hybrid materials and responsive ceramics.
- Examining learning paradigms and integrated sensing architectures.
Main Results:
- Functional materials enhance selectivity, plasticity, and dynamic sensitivity.
- System-level incorporation and learning-assisted interpretation improve reliability.
- Representative examples showcase intelligent material-device system coupling.
Conclusions:
- Intelligent chemical sensors bridge materials innovation and intelligent system design.
- Key challenges include material stability, interpretability, data scarcity, and energy efficiency.
- Emerging directions include memory-enabled interfaces and autonomous sensing ecosystems.
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