4:30 PM - 4:45 PM
▼ [18p-F306-11] Potentiometric Biosensor Response Calculation via Molecular Dynamics: Effect of Nanomorphology and Molecular Analyte Binding
Keywords:Molecular Dynamics, Biosensor, Nanostructure
Improved understanding of the electrostatic properties of the oxide-water interface is crucial for rational design in a large range of technological applications such as fuel cells, water desalination and potentiometric biosensors. For example, it is currently unclear what the effect of nanomorphology such as nanopores and nanotexturing is on the pH response of potentiometric sensors such as ion-sensitive field-effect transistors (IS-FETs). Some experiments have shown increased surface area being correlated with increased pH sensitivity, and others have shown no relationship.
In this work, we present the most extensive molecular dynamics simulation of the electric field and potential properties of the silica-water interface to-date; investigating the effects of surface morphology explicitly by comparing the potentiometric pH response of a crystalline to that of an amorphous model of silica with the same silanol density and surface charge density. Validation is performed by direct comparison to experimental data and analytical models. The simulations results show that the increased surface area of amorphous oxide surfaces can provide increased counter-ion binding, thus resulting in enhanced potentiometric pH response. We also present evidence that this novel approach to potentiometric-sensor response modelling can be applied to a wide variety important problems in the field such as (bio)molecular response modelling.
In this work, we present the most extensive molecular dynamics simulation of the electric field and potential properties of the silica-water interface to-date; investigating the effects of surface morphology explicitly by comparing the potentiometric pH response of a crystalline to that of an amorphous model of silica with the same silanol density and surface charge density. Validation is performed by direct comparison to experimental data and analytical models. The simulations results show that the increased surface area of amorphous oxide surfaces can provide increased counter-ion binding, thus resulting in enhanced potentiometric pH response. We also present evidence that this novel approach to potentiometric-sensor response modelling can be applied to a wide variety important problems in the field such as (bio)molecular response modelling.