O1 (WP1) – Elaboration of the protocol for optimal sensor composition and design and preparation of composites for future synthesis
Deliverables:
Description of work:
- WP1.1: Ab initio simulations of transition metal oxide (TMO) nanoparticles (Fe3 O 4 , SnO2 , ZnO) on different carbon-based substrates. Numerical simulations of the Cortisol interaction with TMO nanoparticles to select the optimal sensor composition (Orca, siesta)
- WP1.2: Fabrication of sensing substrates based on graphene-pyrolle and CNT-pyrolle composites, employing electrochemical methods for pytolle deposition. Procurement of the equipment for the entire project.
- WP1.3: Design of a portable sensor adapted for direct skin contact, with the handy interface for direct connection to the phone/computer USB port
O2 (WP2) – Implementation of the sensor array as an easy to handle device
Deliverable:
- D5 TMO deposition protocol on carbon-pyrrole composites.
- D6 Fabrication protocol on the carbon-based support decorated with TMO nanoparticle.
- D7 Raport on the sensing layer structure and properties
- D8 Sensor design and implementation protocol
Description of work:
- WP2.1: Implementation of sensing layer. Decoration of graphene/CNT-pyrrole composites with TMO nanoparticles.
- WP2.2: Fabrication of the sensing layer of hybridized sp2/sp3 carbon decorated by transition metal oxide nanoparticles.
- WP2.3: Characterization of the obtained materials and composites by Raman Spectroscopy, SEM. Interpretation of the characterization results to determine the sensing layer composition and structure.
- WP2.4: Printing of the organic electric circuit through laser/ink-jet printing. Assembling of the electronic circuit and the sensing layers into functional sensor prototypes.
O3 (WP3) – WP3 Sensor platform validation
Deliverable: Database, trained and tested machine learning tools
- D9 Comparative analysis of different types of cortisol sensors
- D10 Validation report for the cortisol sensor
- D11 The difference between the expected and real senor performance
- D12 Optimized sensor fabrication - I
Description of work:
- WP3.1: Selection of the most efficient sensing platform (the sensor with the lowest detection limit) based on electrochemical measurements in solutions with different cortisol concentrations.
- WP3.2:Validation of the selected sensor based on electrochemical measurements by determining the following parameters: detection limit, accuracy, linearity range, sensitivity, precision, reproducibility in cortisol solutions.
- WP3.3: Fabrication of the selected type of sensor prototype-I.
O4 (WP4) – Impovement and validation of sensor functionality in the presence of interferents
Deliverable: Characterization of transport mechanisms
- D13 Report on cortisol sensor behaviour in the presence of interferents. Database of biosensor electrochemical response in cortisol solutions with interferents.
- D14 AI algorithm for analysis of sensor electrochemical response for cortisol solutions with interferents.
- D15 ptimized fabrication of sensor alpha prototype - II
Description of work:
- WP4.1: Electrochemical measurements of sensor responses in artificial sweat solution with different cortisol concentrations and interferents (urea, glucose, alcohol) in order to obtain the massive data collection for machine learning applications.
- WP4.2: Analysis of obtained experimental curves using Data Science approach. Implementation and testing of an artificial intelligence based program for the separation of cortisol originated signals from the interferents, validation of sensor alpha prototype specificity.
- WP4.3: Fabrication of the selected type of sensor prototype - II.