exemple de titre - iaria
TRANSCRIPT
Faculté Polytechnique
Detection of Antibiotics with MolecularlyImprinted Polymers:
Hugues [email protected]
November 2020
ALLSENSORS 2020
Theoretical Understanding of DetectionMechanisms using EIS and MolecularDynamics
Université de Mons
Sensors for a Practical Implementation
2
Antimicrobial resistance
Primary infection
Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Sensors for a Practical Implementation
2
Antimicrobial resistance
Inadequate antibiotic treatment or bacterial
resistance mutation
Primary infection
Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Sensors for a Practical Implementation
2
Antimicrobial resistance
Proliferation of resistant bacteria
Inadequate antibiotic treatment or bacterial
resistance mutation
Primary infection
Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Sensors for a Practical Implementation
2
Antimicrobial resistance
Solution : limit the amount of antibiotic used
Proliferation of resistant bacteria
Inadequate antibiotic treatment or bacterial
resistance mutation
Primary infection
Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Sensors for a Practical Implementation
2
Antimicrobial resistance
Solution : limit the amount of antibiotic used
Proliferation of resistant bacteria
Inadequate antibiotic treatment or bacterial
resistance mutation
Primary infection
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Widely used in the food industry
Must be controlled
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Sensors for a Practical Implementation
2
Antimicrobial resistance
Solution : limit the amount of antibiotic used
Proliferation of resistant bacteria
Inadequate antibiotic treatment or bacterial
resistance mutation
Primary infection
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Widely used in the food industry
Must be controlled
Case of PenG in milk :
MRL fixed by European Union at 4 ppb
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Analyte
Transduction Mechanisms
3
Suitable measurement techniques must consumeas few energy as possible
Conductivity measurements
Ω
R1
R2Sensitive
layer
Insulating Substratee-
e-
Gold
Electrode
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Université de Mons
Analyte
Transduction Mechanisms
3
Suitable measurement techniques must consumeas few energy as possible
Conductivity measurements
Ω
R1
R2Sensitive
layer
Insulating Substratee-
e-
Gold
Electrode
Sensitive Material should be :
• Semi-conductor
• Sensitive to the target molecule
• Easily processible
• Allowing low energy measurement
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Université de Mons
Analyte
Transduction Mechanisms
3
Suitable measurement techniques must consumeas few energy as possible
Conductivity measurements
Ω
R1
R2Sensitive
layer
Insulating Substratee-
e-
Gold
Electrode
Sensitive Material should be :
• Semi-conductor
• Sensitive to the target molecule
• Easily processible
• Allowing low energy measurement
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Conducting Polymers
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Université de Mons
Conducting Polymers
4
Polymers are usually considered as insulator
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Usually materials are separated in three main groups according to their conducting properties
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Université de Mons
Conducting Polymers
4
Polymers are usually considered as insulator
(Semi)Conducting properties only for conjugated polymers
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Université de Mons
Doping for Conducting Polymers
5
However usually considered as insulators, some polymers can carry charg
(De)doping possibilities allow to modify physical properties of the sensitive material
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
By doping, it is possible to significantly increasethe polymer conductivity
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Université de Mons
Doping for Conducting Polymers
5
However usually considered as insulators, some polymers can carry charg
(De)doping possibilities allow to modify physical properties of the sensitive material
Sensitive Not Selective
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
By doping, it is possible to significantly increasethe polymer conductivity
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Université de Mons
How to Solve Selectivity Issue ?
6
Molecularly Imprinted Polymer (MIP) :Target molecule integrated in polymer matrix
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Université de Mons
How to Solve Selectivity Issue ?
6
Highly adaptable, just need to change the template
Significantly increase of selectivity
Molecularly Imprinted Polymer (MIP) :Target molecule integrated in polymer matrix
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Université de Mons
Sensitive Layer Synthesis
7
Functional monomer : Pyrrole carboxilic acid
Crosslinker :Pyrrole
H
Target molecule / Template: Peniciline G
Penicillin G is chosen as template molecule
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Université de Mons
Sensitive Layer Synthesis
7
Penicillin G is chosen as template molecule
Schematic Representation
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Université de Mons
Sensitive Layer Synthesis
7
pH modification
Temperature adjustment
Penicillin G is chosen as template molecule
Schematic Representation
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Université de Mons
Sensitive Layer Synthesis
7
pH modification
Oxidant addition
Temperature adjustment
Penicillin G is chosen as template molecule
Schematic Representation
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Université de Mons
Sensitive Layer Synthesis
7
Immersion in extraction solution
Penicillin G is chosen as template molecule
Schematic Representation
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
IDE on PET
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Université de Mons
Sensitive Layer Synthesis
7
Immersion in extraction solution
Penicillin G is chosen as template molecule
Schematic Representation
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
IDE on PET
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Université de Mons
Polymerization solution optimization
Molecular Dynamics Simulations
8
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
2000 molecules of
Water
15 molecules of Pyrrole
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Conception of boxes
Université de Mons
Polymerization solution optimization
Molecular Dynamics Simulations
8
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
2000 molecules of
Water
7 molecules of Pyrrole-3-
carboxylic acid
15 molecules of Pyrrole
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Conception of boxes
Université de Mons
Polymerization solution optimization
Molecular Dynamics Simulations
8
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
1 molecule of PenG
2000 molecules of
Water
7 molecules of Pyrrole-3-
carboxylic acid
15 molecules of Pyrrole
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Conception of boxes
Université de Mons
Polymerization solution optimization
Molecular Dynamics Simulations
9
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Homogenization
Université de Mons
Polymerization solution optimization
Molecular Dynamics Simulations
10
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Back to ambient conditions
Université de Mons
Polymerization solution optimization
Molecular Dynamics Simulations
11
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Hugues Charlier ([email protected]) – ALLSENSORS 2020
System analysis
Université de Mons
Polymerization solution optimization
Molecular Dynamics Simulations
11
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Hugues Charlier ([email protected]) – ALLSENSORS 2020
System analysis
Université de Mons
Polymerization solution optimization
Molecular Dynamics Simulations
11
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Hugues Charlier ([email protected]) – ALLSENSORS 2020
System analysis
Université de Mons
Polymerization solution optimization
Molecular Dynamics Simulations
11
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Hugues Charlier ([email protected]) – ALLSENSORS 2020
System analysis
Université de Mons
Polymerization solution optimization
Molecular Dynamics Simulations
11
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
For 1 PenG molecule :
11 < Py < 15
4 < PyCOOH < 10
Hugues Charlier ([email protected]) – ALLSENSORS 2020
System analysis
Université de Mons
Polymerization solution optimization
Molecular Dynamics Simulations
11
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
For 1 PenG molecule :
11 < Py < 15
4 < PyCOOH < 10
Experimentally
Hugues Charlier ([email protected]) – ALLSENSORS 2020
System analysis
Université de Mons
Polymerization solution optimization
Molecular Dynamics Simulations
11
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
For 1 PenG molecule :
11 < Py < 15
4 < PyCOOH < 10
Experimentally
Hugues Charlier ([email protected]) – ALLSENSORS 2020
System analysis
Université de Mons
Application of alternative current,in a 3-electrode system, atvariable frequency allowing topoint out different kind ofinterfacial reaction.
Electrochemical Impedance Spectroscopy
12
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Université de Mons
Electrochemical Impedance Spectroscopy
13
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
NIPMIP
Ph
ase
Mag
nit
ud
e
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Université de Mons
Electrochemical Impedance Spectroscopy
13
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
NIPMIP
Ph
ase
Mag
nit
ud
e
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Université de Mons
Electrochemical Impedance Spectroscopy
13
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Université de Mons
Idea :
Develop an electric equivalent circuit whoseelements parameters are equivalent to physicalproperties of the real system.
Impedance Spectroscopy Models
14Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Idea :
Develop an electric equivalent circuit whoseelements parameters are equivalent to physicalproperties of the real system.
Impedance Spectroscopy Models
14Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Idea :
Develop an electric equivalent circuit whoseelements parameters are equivalent to physicalproperties of the real system.
Impedance Spectroscopy Models
14Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Idea :
Develop an electric equivalent circuit whoseelements parameters are equivalent to physicalproperties of the real system.
Impedance Spectroscopy Models
14Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Idea :
Develop an electric equivalent circuit whoseelements parameters are equivalent to physicalproperties of the real system.
Impedance Spectroscopy Models
14Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Time Constant
Université de Mons
Idea :
Develop an electric equivalent circuit whoseelements parameters are equivalent to physicalproperties of the real system.
Impedance Spectroscopy Models
14Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Idea :
Develop an electric equivalent circuit whoseelements parameters are equivalent to physicalproperties of the real system.
Impedance Spectroscopy Models
14Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Idea :
Develop an electric equivalent circuit whoseelements parameters are equivalent to physicalproperties of the real system.
Impedance Spectroscopy Models
14Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Obtained fitting results at 0 ppb :
Fitting Results on Different Sensors
15Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Obtained fitting results at 0 ppb :
Fitting Results on Different Sensors
15Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
50
500
5000
50000
500000
1E-02 1E-01 1E+00 1E+01 1E+02 1E+03 1E+04 1E+05
Ma
gn
itu
de
(Oh
m)
Frequency (Hz)
pH 3.2 pH 3.2 fitted
pH 2.25 pH 2.25 fitted
pH 1.5 pH 1.5 fitted
Université de Mons
Obtained fitting results at 0 ppb :
Fitting Results on Different Sensors
15Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
0
10
20
30
40
50
60
70
80
1E-02 1E-01 1E+00 1E+01 1E+02 1E+03 1E+04 1E+05
Ph
ase
Frequency (Hz)
pH 3.2 pH 3.2 fitted
pH 2.25 pH 2.25 fitted
pH 1.5 pH 1.5 fitted
Université de Mons
Obtained fitting results for a single sensor :
Fitting Results at Different PenG Concentrations
16Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Main variations of the fitting parameters with an increase of PenG concentration :
17
Fitting Parameters Variation
Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Main variations of the fitting parameters with an increase of PenG concentration :
17
Fitting Parameters Variation
Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Main variations of the fitting parameters with an increase of PenG concentration :
17
Fitting Parameters Variation
Ws - Finite Length Warburg
𝑍 = 𝑅 ∙tanh 𝑗 ∙ 𝑇 ∙ ω 𝑃
𝑗 ∙ 𝑇 ∙ ω 𝑃
Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Main variations of the fitting parameters with an increase of PenG concentration :
17
Fitting Parameters Variation
Ws - Finite Length Warburg
𝑍 = 𝑹 ∙tanh 𝑗 ∙ 𝑻 ∙ ω 𝑷
𝑗 ∙ 𝑻 ∙ ω 𝑷
Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Main variations of the fitting parameters with an increase of PenG concentration :
17
Fitting Parameters Variation
Ws - Finite Length Warburg
𝑍 = 𝑹 ∙tanh 𝑗 ∙ 𝑻 ∙ ω 𝑷
𝑗 ∙ 𝑻 ∙ ω 𝑷
Resistive Parameter
𝑻 =𝑳𝟐
𝑫with L, the diffusion Thickness and D, the effective diffusion coefficient
Diffusion parameter (0<P<1)
Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Main variations of the fitting parameters with an increase of PenG concentration :
18
Fitting Parameters Variation
Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Main variations of the fitting parameters with an increase of PenG concentration :
18
Fitting Parameters Variation
Getting close to a one dimension diffusion
Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Main variations of the fitting parameters with an increase of PenG concentration :
18
Fitting Parameters Variation
Getting close to a one dimension diffusion
Diffusion thickness ↘
Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Main variations of the fitting parameters with an increase of PenG concentration :
18
Fitting Parameters Variation
Getting close to a one dimension diffusion
Diffusion thickness ↘
Ppy/PBS charge transfer resistance ↗
Hugues Charlier ([email protected]) – ALLSENSORS 2020
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Université de Mons
Conclusions
19
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Theoretical optimization of the composition ofthe polymerization solution
Determination of the variation of physicalparameters of the sensitive layer during thedetection
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Université de Mons
❑ Further investigations on the polymerization solution composition
❑ Model the extraction phenomenon
❑ Model the detection phenomenon
❑ Perform DFT analysis (in order to verify optical measurement results)
Prospects
20
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Hugues Charlier ([email protected]) – ALLSENSORS 2020
Université de Mons
Thanks for your attention
21
INTRODUCTION | THEORETICAL REMINDERS | SENSORS’ CONCEPTION | MODELING | SENSORS’ PERFORMANCE | CONCLUSION AND PROSPECTS
Hugues Charlier ([email protected]) – ALLSENSORS 2020