# 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.

## Key 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.