Periodic Reporting for period 1 - Sensor4Diabetes (Hybrid sensor for diabetes detection from exhaled breath using nanoparticles loaded 1D metal oxides)
Berichtszeitraum: 2020-10-01 bis 2022-09-30
Traditionally, blood glucose is monitored to diagnose diabetes via invasive and painful techniques. In recent years, minimally invasive glucose sensing mechanisms such as continuous glucose monitoring (CGM) devices have been developed to alert an individual before they begin experiencing low or high level of blood glucose. The sensors in the CGM system are implanted underneath the skin and require frequent calibration, which need to be replaced frequently. This operation is highly inconvenient and this device is very expensive. Therefore, there is a high demand for non-invasive, affordable and rapid detection devices for continuous monitoring of diabetes, which is searched by the researchers worldwide. Early and affordable diabetes detection technology for monitoring and management of diabetes will help hundreds of thousands people to reduce serious health problems and life threatening side effects. The ‘Sensor4Diabetes’ project aims to develop non-invasive impedometric and photonic based hybrid sensors for detecting and monitoring diabetes from exhaled breath.
According to the International Diabetes Federation (IDF), in 2021 worldwide about 537 million people in the 20-79 age range had diabetes and estimated to be 783 million by the year of 2045. Diabetes is responsible for 6.7 million deaths in 2021. Due to the increased incidence, the associated healthcare expenditure has risen to 918 billion Euros in 2021 and estimated to be 998 billion Euros by 2045. Worldwide governments are struggling to cover the cost of diabetes. The outcomes of this project will be actions which can readily be implemented to speed the early identification of the disease for saving health services billions of Euros annually and significantly improve lives. ‘Sensor4Diabetes’ targets achieving early identification and thus better monitoring of diabetes. This project will open doors for further studies and innovation action, not only in Europe but also in other countries and in the developing world, to inspire the innovators to further develop suitable tools for people of all groups, different ethnicities, races, ages and social status. The project addresses several of the key UN Sustainable Development Goals (such as Goal 1 ‘erasing poverty’; Goal 9, promoting ‘innovation’ (involving developing countries as well); Goal 10, ‘reducing inequality’ and most importantly Goal 3 (‘Health’).
The overall objective of ‘Sensor4Diabtes’ project is to develop novel hybrid breath analysing sensor based on semiconducting metal oxide nanostructures to diagnose diabetes by employing both impedometric and photonic methods. The main drive of the breath sensor is to provide miniaturize, continuous, real-time, non-invasive and mobile device for detection and monitoring of diabetes at a lower cost.
According to the International Diabetes Federation (IDF), in 2021 worldwide about 537 million people in the 20-79 age range had diabetes and estimated to be 783 million by the year of 2045. Diabetes is responsible for 6.7 million deaths in 2021. Due to the increased incidence, the associated healthcare expenditure has risen to 918 billion Euros in 2021 and estimated to be 998 billion Euros by 2045. Worldwide governments are struggling to cover the cost of diabetes. The outcomes of this project will be actions which can readily be implemented to speed the early identification of the disease for saving health services billions of Euros annually and significantly improve lives. ‘Sensor4Diabetes’ targets achieving early identification and thus better monitoring of diabetes. This project will open doors for further studies and innovation action, not only in Europe but also in other countries and in the developing world, to inspire the innovators to further develop suitable tools for people of all groups, different ethnicities, races, ages and social status. The project addresses several of the key UN Sustainable Development Goals (such as Goal 1 ‘erasing poverty’; Goal 9, promoting ‘innovation’ (involving developing countries as well); Goal 10, ‘reducing inequality’ and most importantly Goal 3 (‘Health’).
The overall objective of ‘Sensor4Diabtes’ project is to develop novel hybrid breath analysing sensor based on semiconducting metal oxide nanostructures to diagnose diabetes by employing both impedometric and photonic methods. The main drive of the breath sensor is to provide miniaturize, continuous, real-time, non-invasive and mobile device for detection and monitoring of diabetes at a lower cost.
To achieve the aim and objectives of ‘Sensor4Diabetes’ project, an in-house built thermal oxidation setup was constructed for synthesising 1D semiconducting metal oxide (SMO) nanostructures. Various 1D SMOs such as TiO2, core-shell TiO2-Al2O3, ZnO and CuO was synthesized by thermal oxidation process on Ti, Ti-6Al-4V, brass and Cu substrates, respectively. The growth of 1D nanostructures were optimised. The residual stress inside the particles was measured by XRD-sin2ψ technique. For hybrid mode of sensing, the nanolayers of metal oxides (TiO2 and WO3) were deposited on grated optical fibre using atomic layer deposition (ALD) procedure. The SMOs were characterized by FESEM, EDX, TEM, XRD, and XPS.
Metal oxides were deposited on Au interdigitated substrates and optical fibres for impedometric and hybrid sensing. The substrates were connected to DAQ system with Au wires for measuring the resistance of the sensor in the presence of specific breath environment. For hybrid mode of sensing (both impedometric and photonic simultaneously), a light source and detector was connected with the grated optical fibre surrounded by SMO. The SMO on optical fibre was connected with DAQ system. The resistance and refractive index of SMOs is changed in the presence of breath biomarkers in impedometric and photonic sensing, respectively.
An in-house built experimental setup was constructed for gas sensing experiments. The response, stability, selectivity, optimum operating temperature, detection limit, response time and recovery time was tested of the sensors.
Results revealed four types of morphological variations such as stacked, ribbon, plateau and lamp-post shaped TiO2 nanostructures on oxidized Ti substrates. The 1D TiO2, ZnO and CuO nanostructures have tetragonal rutile, hexagonal wurtzite, and monoclinic structure, respectively. Residual stress is beneficial for 1D growth during thermal oxidation. The growth of nanolayers of SMOs on grated optical fibres via ALD process was optimised.
The SMOs (TiO2 and ZnO based nanostructures) are capable of detecting acetone and ethanol in synthetic breath. The sensors works at high temperatures in the range of 450 to 650 °C. The response of the sensors varied from 10 to 105 depending on SMOs, sensing temperature and concentration of breath biomarker. The response and recovery time of the sensors are in between 3 to 15 min. Based on the findings, the sensors are capable of detecting diabetic biomarkers in breath.
Finally, the project outcome is disseminated through workshops, raising public awareness, website and blog, conference proceedings, journal papers, seminar and outreach activities directed to industry. So far, three conference proceedings, two journal papers and one book chapter have been published from the outcome of this project. Two more journal papers are under preparation.
Metal oxides were deposited on Au interdigitated substrates and optical fibres for impedometric and hybrid sensing. The substrates were connected to DAQ system with Au wires for measuring the resistance of the sensor in the presence of specific breath environment. For hybrid mode of sensing (both impedometric and photonic simultaneously), a light source and detector was connected with the grated optical fibre surrounded by SMO. The SMO on optical fibre was connected with DAQ system. The resistance and refractive index of SMOs is changed in the presence of breath biomarkers in impedometric and photonic sensing, respectively.
An in-house built experimental setup was constructed for gas sensing experiments. The response, stability, selectivity, optimum operating temperature, detection limit, response time and recovery time was tested of the sensors.
Results revealed four types of morphological variations such as stacked, ribbon, plateau and lamp-post shaped TiO2 nanostructures on oxidized Ti substrates. The 1D TiO2, ZnO and CuO nanostructures have tetragonal rutile, hexagonal wurtzite, and monoclinic structure, respectively. Residual stress is beneficial for 1D growth during thermal oxidation. The growth of nanolayers of SMOs on grated optical fibres via ALD process was optimised.
The SMOs (TiO2 and ZnO based nanostructures) are capable of detecting acetone and ethanol in synthetic breath. The sensors works at high temperatures in the range of 450 to 650 °C. The response of the sensors varied from 10 to 105 depending on SMOs, sensing temperature and concentration of breath biomarker. The response and recovery time of the sensors are in between 3 to 15 min. Based on the findings, the sensors are capable of detecting diabetic biomarkers in breath.
Finally, the project outcome is disseminated through workshops, raising public awareness, website and blog, conference proceedings, journal papers, seminar and outreach activities directed to industry. So far, three conference proceedings, two journal papers and one book chapter have been published from the outcome of this project. Two more journal papers are under preparation.
Hybrid sensor is a new concept for detecting breath biomarkers. The presence of nano-sized SMOs enhances the performance of breath analyser by increasing surface-to-volume ratio. Loading of nanoparticles enhances the catalytic activity of the 1D nanostructures which will result in better performance. The hybrid technology enables the high selectivity of the sensor in the complex environment of human exhaled breath. It is expected that such concept will be utilised in future for detecting other diseases from exhaled breath including kidney diseases, lungs inflammation, airway inflammations, bacterial infection, and liver diseases.
The ‘Sensor4Diabetes’ has potential socio-economic and wider societal implications as mentioned below:
1. Self-monitoring invasive technique will be replaced by a non-invasive breath biopsy procedure for diabetes resulting in better management of the disease. Such technology will eliminate the requirement of skilled health-care personal.
2. It would be possible to diagnose pregnant, critically ill, severely injured, sleeping and unconscious patients, which is not approved for CGM sensor.
3. The diabetes monitoring cost will be reduced by a ‘one time’ expenditure on breath analysis sensor.
4. It would be possible to detect diabetes at the earliest stage and enable treatment promptly, as breath biomarkers are the direct product of metabolism.
5. Breath biopsy can be correlated with other metabolic parameters, such as β-hydroxybutyrate, insulin, and lipid level.
6. ‘Sensor4Diabetes’ will enable personalised treatment based on breath biomarkers.
7. Such technology will create a technology platform to detect and monitor other diagnosable diseases, such as kidney diseases, lung inflammations, liver diseases, schizophrenia, bacterial infection, and asthma.
The ‘Sensor4Diabetes’ has potential socio-economic and wider societal implications as mentioned below:
1. Self-monitoring invasive technique will be replaced by a non-invasive breath biopsy procedure for diabetes resulting in better management of the disease. Such technology will eliminate the requirement of skilled health-care personal.
2. It would be possible to diagnose pregnant, critically ill, severely injured, sleeping and unconscious patients, which is not approved for CGM sensor.
3. The diabetes monitoring cost will be reduced by a ‘one time’ expenditure on breath analysis sensor.
4. It would be possible to detect diabetes at the earliest stage and enable treatment promptly, as breath biomarkers are the direct product of metabolism.
5. Breath biopsy can be correlated with other metabolic parameters, such as β-hydroxybutyrate, insulin, and lipid level.
6. ‘Sensor4Diabetes’ will enable personalised treatment based on breath biomarkers.
7. Such technology will create a technology platform to detect and monitor other diagnosable diseases, such as kidney diseases, lung inflammations, liver diseases, schizophrenia, bacterial infection, and asthma.