SubsidieMeestersMetal-Organic-Framework Kinetic Array for Diabetes Detection
This project aims to develop a novel sensor using metal-organic frameworks to selectively detect volatile organic compounds in breath for non-invasive diabetes diagnosis.
Projectdetails
Introduction
Diabetes mellitus is a global health concern affecting 537 million people and resulting in over 6.7 million deaths yearly. Diagnosis currently relies on blood analysis, which is expensive, time-consuming, and invasive.
Alternative Diagnosis Method
Breath analysis based on the detection of volatile organic compounds (VOCs) is a promising non-invasive alternative. However, selectively measuring specific VOCs in breath is challenging due to:
- Low concentrations of VOCs
- Presence of interfering compounds
Need for Novel Technology
Since current miniature sensors cannot efficiently distinguish between VOCs, there is a need for a novel technology capable of distinguishing a VOC of interest from a complex background.
Project Aim
This project aims to address this challenge by combining a highly promising class of porous crystalline materials, metal-organic frameworks (MOFs), with sensor technology.
Sensing Concept
A novel sensing concept based on the kinetic selectivity in the pores of the MOFs will be leveraged to mimic nature’s approach to olfaction and enable selective sensing.
Demonstrator Development
A demonstrator will be established to enable diabetes mellitus diagnosis and prove the breakthrough potential of this disruptive sensing platform.
Financiële details & Tijdlijn
Financiële details
| Subsidiebedrag | € 150.000 |
| Totale projectbegroting | € 150.000 |
Tijdlijn
| Startdatum | 1-11-2024 |
| Einddatum | 30-4-2026 |
| Subsidiejaar | 2024 |
Partners & Locaties
Projectpartners
- KATHOLIEKE UNIVERSITEIT LEUVENpenvoerder
Land(en)
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Vergelijkbare projecten uit andere regelingen
| Project | Regeling | Bedrag | Jaar | Actie |
|---|---|---|---|---|
Kinetic selectivity in molecular sieve sensorsKISSIES aims to develop a novel sensor technology using tailored metal-organic frameworks to selectively detect volatile organic compounds in complex environments, enhancing applications in health and safety. | ERC COG | € 2.480.500 | 2022 | Details |
Smart Electronic Olfaction for Body Odor DiagnosticsSMELLODI aims to digitize and synthesize olfactory information for remote disease diagnostics and assist individuals with olfactory disorders using advanced sensor technology and machine learning. | EIC Pathfinder | € 3.263.781 | 2022 | Details |
Towards the ultimate breath analysis -based continuous healthcareVOCORDER aims to develop a compact, efficient breath analysis device using advanced laser technology and AI to provide holistic health monitoring seamlessly integrated into daily life. | EIC Pathfinder | € 3.873.437 | 2023 | Details |
Atomistic Modeling of Advanced Porous Materials for Energy, Environment, and Biomedical ApplicationsThis project aims to develop a materials intelligence ecosystem to assess guest storage and transport properties of millions of MOFs, enhancing their applications in energy, environmental, and biomedical fields. | ERC COG | € 2.000.000 | 2024 | Details |
Kinetic selectivity in molecular sieve sensors
KISSIES aims to develop a novel sensor technology using tailored metal-organic frameworks to selectively detect volatile organic compounds in complex environments, enhancing applications in health and safety.
Smart Electronic Olfaction for Body Odor Diagnostics
SMELLODI aims to digitize and synthesize olfactory information for remote disease diagnostics and assist individuals with olfactory disorders using advanced sensor technology and machine learning.
Towards the ultimate breath analysis -based continuous healthcare
VOCORDER aims to develop a compact, efficient breath analysis device using advanced laser technology and AI to provide holistic health monitoring seamlessly integrated into daily life.
Atomistic Modeling of Advanced Porous Materials for Energy, Environment, and Biomedical Applications
This project aims to develop a materials intelligence ecosystem to assess guest storage and transport properties of millions of MOFs, enhancing their applications in energy, environmental, and biomedical fields.