This paper presents the use of a statistical approach to estimate physical/electrochemical parameters of impedance spectroscopy experiments performed with a realistic nanoelectrodes array biosensor platform. The Bayesian estimation methodology is based on the combination of nanobiosensor simulations, performed with the ENBIOS tool, with Markov-Chain Monte Carlo (MCMC) analyses. A simple 1D electrode-electrolyte geometry is first considered as a validation test case, allowing the accurate estimation of Stern layer permittivity and salt concentration, as set by a reference analytical model. Then, full 3D analyses of the nanoelectrodes’ array system are performed in order to estimate a number of relevant parameters for measurements in electrolyte. Furthermore, moving to more challenging test cases, size/permittivity of microparticles suspended in electrolyte will also be discussed. This methodology allows for the determination of impedance spectroscopy data parameters, and quantification of parameter uncertainties in these multi-variable detection problems. It is thus a very promising approach in order to improve the precision of biosensor measurement predictions, which are intrinsically affected by many parameters.

Calibration, Compensation, Parameter Estimation, and Uncertainty Quantification for Nanoelectrode Array Biosensors / Cossettini, Andrea; Scarbolo, Paolo; Morales Escalante, Jose A.; Stadlbauer, Benjamin; Muhammad, Naseer; Taghizadeh, Leila; Heitzinger, Clemens; Selmi, Luca. - (2018), pp. 81-81. ((Intervento presentato al convegno SIAM Conference on Uncertainty Quantification (UQ18) tenutosi a Garden Grove, California, USA nel April 16-19, 2018.

Calibration, Compensation, Parameter Estimation, and Uncertainty Quantification for Nanoelectrode Array Biosensors

Luca Selmi
2018

Abstract

This paper presents the use of a statistical approach to estimate physical/electrochemical parameters of impedance spectroscopy experiments performed with a realistic nanoelectrodes array biosensor platform. The Bayesian estimation methodology is based on the combination of nanobiosensor simulations, performed with the ENBIOS tool, with Markov-Chain Monte Carlo (MCMC) analyses. A simple 1D electrode-electrolyte geometry is first considered as a validation test case, allowing the accurate estimation of Stern layer permittivity and salt concentration, as set by a reference analytical model. Then, full 3D analyses of the nanoelectrodes’ array system are performed in order to estimate a number of relevant parameters for measurements in electrolyte. Furthermore, moving to more challenging test cases, size/permittivity of microparticles suspended in electrolyte will also be discussed. This methodology allows for the determination of impedance spectroscopy data parameters, and quantification of parameter uncertainties in these multi-variable detection problems. It is thus a very promising approach in order to improve the precision of biosensor measurement predictions, which are intrinsically affected by many parameters.
SIAM Conference on Uncertainty Quantification (UQ18)
Garden Grove, California, USA
April 16-19, 2018
Cossettini, Andrea; Scarbolo, Paolo; Morales Escalante, Jose A.; Stadlbauer, Benjamin; Muhammad, Naseer; Taghizadeh, Leila; Heitzinger, Clemens; Selmi, Luca
Calibration, Compensation, Parameter Estimation, and Uncertainty Quantification for Nanoelectrode Array Biosensors / Cossettini, Andrea; Scarbolo, Paolo; Morales Escalante, Jose A.; Stadlbauer, Benjamin; Muhammad, Naseer; Taghizadeh, Leila; Heitzinger, Clemens; Selmi, Luca. - (2018), pp. 81-81. ((Intervento presentato al convegno SIAM Conference on Uncertainty Quantification (UQ18) tenutosi a Garden Grove, California, USA nel April 16-19, 2018.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11380/1162732
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