Advanced Detection for Defence and Civil Protection.
High-temperature GC-IMS and AI-driven analytics for rapid identification of chemical and biological threats.
Supporting armed forces, first responders and critical infrastructure protection.
TeChBioT produced 30 deliverables across 7 work packages over 38 months.
High-Performance Chemical Detection
HT-IMS
“High-temperature dual-polarity IMS supports rapid detection of volatile and low-volatile chemical threats and toxic industrial chemicals in constrained environments, with configurations that balance performance and endurance.”
HT-GC-IMS
“GC separation coupled to high-temperature IMS improves selectivity in complex backgrounds and supports pathways toward mobile and unmanned deployment.”
Pyrolysis-HT-GC-IMS
“Pyrolysis converts non-volatile chemicals and biological material into volatile fingerprints for subsequent GC-IMS detection in matrix-rich samples and surface contamination scenarios.”
Noise reduction, peak detection and classification using advanced AI and ML models.
Technology & AI Achievements
Technology achievements
Modular “one-platform / three-modes” architecture that can be configured as:
- HT-IMS
- HT-GC-IMS
- Py-HT-GC-IMS
to match threat volatility, matrix complexity and mission constraints.
The project demonstrated high-temperature dual-polarity IMS performance with a resolving-power of 70 and advanced high-temperature GC-IMS coupling to improve selectivity in complex chemical backgrounds, including key progress on thermal design and high-temperature materials compatibility.
In parallel, TeChBioT developed a low-cost Curie-point pyrolyzer concept and successfully coupled pyrolysis to GC-IMS workflows, enabling biological fingerprinting from largely non-volatile biological material.
Validation achievements
TeChBioT validated both chemical and biological workflows in field-relevant settings.
Chemical track
The IMS concept was integrated into a stand-off reconnaissance model using a mobile robotic deployment and demonstrated AI-supported alarm logic outdoors.Biological track
Py-GC-IMS was deployed in a mobile-lab configuration and paired with a practical water pre-concentration workflow, with reported identification capability and emphasis on robustness and usability under field constraints.
AI and data achievements
TeChBioT integrated AI/ML as a decision layer to transform complex IMS/GC-IMS data into operational classification and alarm outputs.
The project reported robust signal processing and peak-handling approaches including a wavelet-based method combined with persistent homology> for efficient, ROI-focused peak detection.
It demonstrated strong classification performance under domain shift between laboratory and outdoor conditions.
These AI components were developed alongside reference and benchmarking workflows to support dataset generation and model training for both chemical and biological detection tasks.
TeChBioT validated its concepts outdoors on both chemical and biological tracks to demonstrate field relevance beyond laboratory conditions.
EDF Project: 101103176
For chemical reconnaissance,
the high-temperature IMS module was integrated in a mobile deployment concept using an unmanned ground vehicle (UGV), showing that outdoor measurements can support stand-off detection and AI-assisted alarm logic under variable ambient conditions and complex backgrounds.
For biological response,
the pyrolysis-enabled GC-IMS workflow was deployed stationarily in a mobile-laboratory setting and paired with field-realistic sample preparation. A water concentration workflow based on filtration, recovery, pelleting and resuspension prior to Py-GC-IMS analysis demonstrated robust operation and identification capability, highlighting that practical matrix handling is integral to fieldable bio fingerprinting.
Beyond the project
TeChBioT has laid the foundation for next-generation high-temperature GC-IMS technologies supported by advanced AI. As the consortium moves beyond the project timeframe, several lines of research and development remain open for further exploration, validation and potential transition into operational or commercial systems.
- Scaling & ruggedising the technology for field deployment in mobile, unmanned, or networked systems
- Expanding the chemical and biological libraries with additional simulants and environmental backgrounds
- Advancing AI models through larger datasets, transfer learning and real-time detection capabilities
- Exploring dual-use applications (environmental monitoring, industrial safety, disaster response, UXO mapping)
- Evaluating integration with robots, drones, or sensor networks
- Engaging with standardisation and validation frameworks for chemical and biological detection
