Graphene-Based Sensors and Biosensors Fabricated via Pulsed Laser Deposition for Chemical and Biological Threat Detection: A Comprehensive Roadmap

TL;DR

This paper outlines a roadmap for developing graphene-based sensors to detect chemical and biological threats, emphasizing scalable fabrication and real-world performance.

Contribution

A modular, non-linear roadmap for translating graphene sensing from lab to field, using pulsed laser deposition for improved sensor reproducibility.

Findings

Pulsed laser deposition (PLD) enables tunable graphene thickness and interface control for better sensor performance.

A feedback-driven framework connects planning, modeling, fabrication, diagnostics, and field validation for deployable CBRN sensors.

Multiscale diagnostics and operational metrics help refine sensor design for real-world deployment.

Abstract

What are the main findings?
We propose a modular, non-linear roadmap for graphene Chemical, Biological, Radiological and Nuclear (CBRN) sensing that links planning, modeling, fabrication, multiscale diagnostics, and field validation.Pulsed laser deposition (PLD) is identified as a controllable, substrate-flexible route to engineer graphene thickness/defects and interfaces, improving sensor reproducibility.

We propose a modular, non-linear roadmap for graphene Chemical, Biological, Radiological and Nuclear (CBRN) sensing that links planning, modeling, fabrication, multiscale diagnostics, and field validation.

Pulsed laser deposition (PLD) is identified as a controllable, substrate-flexible route to engineer graphene thickness/defects and interfaces, improving sensor reproducibility.

What is the implication of the main finding?
The roadmap provides a deployability-oriented framework to translate graphene sensing from lab demonstrations to operational CBRN platforms through iterative, feedback-driven development.PLD-enabled control of material properties and interfaces supports scalable fabrication strategies and more consistent device performance across substrates and batches.

The roadmap provides a deployability-oriented framework to translate graphene sensing from lab demonstrations to operational CBRN platforms through iterative, feedback-driven development.

PLD-enabled control of material properties and interfaces supports scalable fabrication strategies and more consistent device performance across substrates and batches.

Graphene-based sensors and biosensors are attractive candidates for chemical and biological threat detection due to their high surface sensitivity, rapid transduction, and low-power operation, yet real-world deployment remains constrained by cross-sensitivity, interface instability in biosensing, and limited validation under operational conditions. This review consolidates key requirements for Chemical, Biological, Radiological, and Nuclear (CBRN) detection and proposes a structured roadmap to guide the transition from laboratory demonstrations to field-relevant sensing systems. The roadmap is explicitly modular and non-linear, integrating (i) qualitative research planning and gap analysis, (ii) computational screening via molecular docking as a hypothesis-generation tool with well-defined limitations, (iii) graphene electrode fabrication and functionalization using pulsed laser deposition (PLD) to enable tunable thickness/defect engineering and strong interface control, (iv) multiscale characterization combining laboratory methods with in situ/portable diagnostics, and (v) field-oriented performance evaluation focused on response time, stability, selectivity against industrial interferents, and false-positive/false-negative behavior. Iterative feedback loops connect all modules, enabling progressive refinement of material processing, recognition chemistry, and device architecture. By framing success in terms of technology-maturity progression and operational metrics, this roadmap provides a practical, defense-relevant framework for developing deployable graphene-based CBRN sensing platforms.

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