Scanning probe microscopy from the perspective of the sensor
The class of instruments considered in this thesis, scanning probe microscopes (SPM), raster scan a sensory probe over a surface to form both high resolution images and quantitative interaction measurements. Understanding and extracting information from SPM data has been considered extensively in th...
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| Format: | Thesis (University of Nottingham only) |
| Language: | English |
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2014
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| Online Access: | http://eprints.nottingham.ac.uk/14000/ http://eprints.nottingham.ac.uk/14000/1/Thesis.pdf |
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nottingham-14000 |
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nottingham-140002017-12-17T09:15:50Z http://eprints.nottingham.ac.uk/14000/ Scanning probe microscopy from the perspective of the sensor Stirling, Julian The class of instruments considered in this thesis, scanning probe microscopes (SPM), raster scan a sensory probe over a surface to form both high resolution images and quantitative interaction measurements. Understanding and extracting information from SPM data has been considered extensively in the three decades since the first SPM. Major developments tend to be greeted with their own theory and data analysis techniques. The more gradual evolution of equipment has not, however, attracted the same level of theoretical consideration. In this thesis we consider the SPM from an instrumentation perspective, concentrating on two specific types of microscope: the scanning tunnelling microscope (STM) and the atomic force microscope (AFM). Both of these microscopes rely on a sensory probe or sensor to induce and measure the desired interaction. We have carefully considered a range of experiments from a `sensor-eye-view', both theoretically and experimentally. We first consider the effect of the geometry of AFM sensors on quantitative force measurements, identifying that the length of tips that the length of tips can induce an unwanted coupling of lateral and normal forces. We go further by developing methods to experimentally correct these force measurements along with designing a sensor which exploits symmetry to separate lateral and normal forces. We also consider the ways to automatically optimise the apex of the sensory probe of an STM to give the desired imaging resolution using a combination of prescribed routines and genetic algorithms. Image analysis techniques developed for this work have been developed into an open-source toolbox to automatically process and analyse SPM images. Finally, we use control theory to analyse the feedback controlling the SPM probe. We find that the methods used in the literature do not fully consider the method with which the control loop is implemented in SPM. We employ a modified approach which results in more realistic simulated SPM operation. 2014-03-15 Thesis (University of Nottingham only) NonPeerReviewed application/pdf en http://eprints.nottingham.ac.uk/14000/1/Thesis.pdf Stirling, Julian (2014) Scanning probe microscopy from the perspective of the sensor. PhD thesis, University of Nottingham. |
| repository_type |
Digital Repository |
| institution_category |
Local University |
| institution |
University of Nottingham Malaysia Campus |
| building |
Nottingham Research Data Repository |
| collection |
Online Access |
| language |
English |
| description |
The class of instruments considered in this thesis, scanning probe microscopes (SPM), raster scan a sensory probe over a surface to form both high resolution images and quantitative interaction measurements. Understanding and extracting information from SPM data has been considered extensively in the three decades since the first SPM. Major developments tend to be greeted with their own theory and data analysis techniques. The more gradual evolution of equipment has not, however, attracted the same level of theoretical consideration.
In this thesis we consider the SPM from an instrumentation perspective, concentrating on two specific types of microscope: the scanning tunnelling microscope (STM) and the atomic force microscope (AFM). Both of these microscopes rely on a sensory probe or sensor to induce and measure the desired interaction. We have carefully considered a range of experiments from a `sensor-eye-view', both theoretically and experimentally.
We first consider the effect of the geometry of AFM sensors on quantitative force measurements, identifying that the length of tips that the length of tips can induce an unwanted coupling of lateral and normal forces. We go further by developing methods to experimentally correct these force measurements along with designing a sensor which exploits symmetry to separate lateral and normal forces.
We also consider the ways to automatically optimise the apex of the sensory probe of an STM to give the desired imaging resolution using a combination of prescribed routines and genetic algorithms. Image analysis techniques developed for this work have been developed into an open-source toolbox to automatically process and analyse SPM images.
Finally, we use control theory to analyse the feedback controlling the SPM probe. We find that the methods used in the literature do not fully consider the method with which the control loop is implemented in SPM. We employ a modified approach which results in more realistic simulated SPM operation. |
| format |
Thesis (University of Nottingham only) |
| author |
Stirling, Julian |
| spellingShingle |
Stirling, Julian Scanning probe microscopy from the perspective of the sensor |
| author_facet |
Stirling, Julian |
| author_sort |
Stirling, Julian |
| title |
Scanning probe microscopy from the perspective of the sensor |
| title_short |
Scanning probe microscopy from the perspective of the sensor |
| title_full |
Scanning probe microscopy from the perspective of the sensor |
| title_fullStr |
Scanning probe microscopy from the perspective of the sensor |
| title_full_unstemmed |
Scanning probe microscopy from the perspective of the sensor |
| title_sort |
scanning probe microscopy from the perspective of the sensor |
| publishDate |
2014 |
| url |
http://eprints.nottingham.ac.uk/14000/ http://eprints.nottingham.ac.uk/14000/1/Thesis.pdf |
| first_indexed |
2018-09-06T10:56:47Z |
| last_indexed |
2018-09-06T10:56:47Z |
| _version_ |
1610855384901222400 |