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COMP6055 - Complex Systems Independent Research Project
No full textThis report was submitted as part of the fulfilment of an integrated MSc-level year as part of the author's PhD program at the University of Southampton Institute for Complex Systems Simulations
Dataset for "Interfacial Physics of Field-Effect Biosensors"
No full textSupporting Data for:
Lowe, Benjamin (2016). Interfacial Physics of Field-Effect Biosensors. University of Southampton, Doctoral Thesis.
See attached README.txt for more details and acknowledgements.
The results of the thesis begin from Chapter 4 onwards and data is included for each Chapter as described below:
Chapter 4: Charging at the Silica-Water Interface.
In the folder "silica_water_DFT" are the results of the convergence study of DFT calculations can be found.
Supplementary Data for these DFT simulations of silica-water interactions can be found with the corresponding paper, or at doi:10.5258/SOTON/401050
Chapter 5: Kinetic Monte Carlo Model of Dynamic Surface Charging.
The folder "KMC": Contains input and output files for the Kinetic Monte Carlo simulations found in Chapter 5 of the thesis. Simulated using the Zacros version 1.01 software.
Chapter 6: Modelling the Net Charge of Proteins
The folder "modelling_net_charges" contains the pH titration results for TNF_alpha and Streptavidin calculated using MOE 2013.8 and PROPKA.
Chapter 7: Electrical Double Layer Dynamics at the Silica-Water Interface
Supplementary Data for these MD simulations of silica-water-biomolecules interactions can be found with the corresponding paper, or at doi:10.5258/SOTON/401018
Chapter 8: Quantitative Analysis of FET-Sensor Literature Data: From pH Sensing to Biosensing
The folder "streptavidin_meta_analysis" contains the summarised quantitative data used to plot the results. The plots were peformed using iPython and can be found in an iPython notebook file "streptavidin_notebook.ipynb"
"Surface Charge Calculations.ipynb" contains general calculations relating to estimating the surface charge density using the Poisson Boltzman equation (linearised vs non linearised). This was used to help choose the surface potential in the Gouy-Chapman-Stern model of Chapter 7.
The archive onetepconv.zip contains the OnetepConv software discussed in Chapter 4, and available online at: https://github.com/holyone2/onetepconv</span
Interfacial physics of field-effect biosensors
No full textField-Effect Transistor-sensors (FET-sensors) are a class of pH and biomolecule sensors that can be produced at a low cost and with high sensitivity, as a result having potential for commercialisation and widespread use. The response of a FET-sensor is generated when the electric field at the sensor surface changes, thereby inducing a measurable change in current through the device. The electric field can be modified by pH or by binding of an analyte to the surface. The solid state counterpart, the Metal Oxide Semiconductor FET, has been extensively studied as it is the basis of modern electronics. FET-sensors are less well understood, mainly due to the inherent complexity introduced by the aqueous media present at the sensor surface. The FET-sensor surface is usually an oxide such as silica and its interaction with aqueous solution introduces many complex effects, such as ion-dynamics and pH dependent ionisation, which make these systems non-trivial to understand and predict. To-date, most models of FET-sensor response have relied upon mean-field assumptions which neglect the multi-scale nature of the system and even qualitative predictions of FET-sensor response remain challenging.In the work presented here, the interfacial physics of FET-sensors were modelled using a variety of simulation techniques at different time- and length-scales. Acid-base surface charging reactions at the oxide surface of the sensor are an important part of FET-sensor response. Density Functional Theory (DFT) simulations revealed a new mechanism of surface charging and also showed that these reactions have no well-defined transition state which can be used to model their kinetics. A Kinetic Monte Carlo (KMC) model was validated that can be used describe the dynamics of surface-charging reactions on a device scale.As FET-sensors operate by detecting changes in the interfacial electric field, the mean net charge density of surface-bound biomolecules is an important parameter in most models of BioFET response. Semi-empirical calculations were performed to estimate the net charge of two different biomolecular systems relevant to biosensing studies. The ion dynamics in the electrical double layer at the silicawater-biomolecule interface were investigated using classical Molecular Dynamics (MD) simulations, which suggested that, in contrast to commonly used net-charge arguments for FET-sensor response, the importance of water polarisation for FET-sensor response has been hitherto underestimated.A quantitative analysis of data extracted from the FET-sensor literature was performed, comparing experimental biosensing data with pH-sensing data. This revealed some frequent problems related to reproducibility and comparability of experimental data in this field, and highlighted that optimisation of surface chemistry is an underappreciated component of sensor optimisation. Despite these limitations, BioFET research is a rapidly advancing field in which novel device design and operation methodologies are constantly being developed which increase the viability of BioFET devices for commercial use
Acid-base dissociation mechanisms at the silica-water interface: A DFT study
No full textOne of the fundamental effects of the hydration of silica surfaces is the production of surface charges. This phenomenon is believed to be primarily a consequence of proton uptake and release at the silica/water interface [1]. Hydrated silica surfaces have been the focus of much experimental and simulation work due to their importance in nanodevices such as Ion-Sensitive Field Effect Transistors (IS-FETs) [2], however the electrostatics and dynamics of these surfaces are not well understood. For example, there is still no consensus on whether the partial charge or unit charge model is more representative of the underlying charging mechanism [3].In this work, Density Functional Theory (DFT) calculations are used to investigate the fundamental protonation/deprotonation reactions at the silica/water interface. The silica surface was modelled as a periodic slab, whereas the solvent was modeled as a hydrated cluster containing hydronium or hydroxide ions. These reactions were found to be highly exothermic and activationless, and showed a rate of reaction limited by reorientation of the nearby water molecules. A new mechanism of surface protonation was demonstrated where hydronium ions protonate the surface without transfer of their protons to the surface, this occurred via stabilising the dissociation of intermediate water molecules. Understanding these kinetics is vital to interpreting signal-to-noise characteristics of chemically sensitive nanodevices such as nano-IS-FETs. [4
Acid-base dissociation mechanisms and energetics at the silica–water interface: an activationless process
No full textHypothesis: Silanol groups at the silica–water interface determine not only the surface charge, but also have an important role in the binding of ions and biomolecules. As the pH is increased above pH 2, the silica surface develops a net negative charge primarily due to deprotonation of the silanol group. An improved understanding of the energetics and mechanisms of this fundamentally important process would further understanding of the relevant dynamics. Simulations: Density Functional Theory ab initio molecular dynamics and geometry optimisations were used to investigate the mechanisms of surface neutralisation and charging in the presence of OH- and H3O+ respectively. This charging mechanism has received little attention in the literature.Findings: The protonation or deprotonation of isolated silanols in the presence of H3O+ or OH-, respectively, was shown to be a highly rapid, exothermic reaction with no significant activation energy. This process occurred via a concerted motion of the protons through ‘water wires’. Geometry optimisations of large water clusters at the silica surface demonstrated proton transfer to the surface occurring via the rarely discussed ‘proton holes’ mechanism. This indicates that surface protonation is possible even when the hydronium ion is distant (at least 4 water molecules separation) from the surface.<br/
Charge dynamics at the silica-electrolyte interface
No full textPresented at the 251st Spring 2016 American Chemical Society National Meetin
Supplementary Data for Paper Entitled "Acid-base dissociation mechanisms and energetics at the silica–water interface: an activationless process"
No full textPublication Submission Contents includes the publication (lyx document) and images in respective subfolders.
XYZ animations includes .xyz file-format trajectories showing the geometry optimisations from the paper
Raw Data archive provides raw data used in simulations (input files and output files <5Mb)</span
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