Modeling and control of probe-on-probe dynamics in dual-probe atomic force microscopy

“The atomic force microscope (AFM) is a widely used instrument for imaging and direct manipulation of materials and particles at the nanoscale. The AFM uses a probe, which is a microcantilever with a sharp point at the end. Typically, the AFM is constructed with a single probe. The disadvantage of this construction is that it can only be used either for imaging or manipulation in one implementation. An AFM was constructed using two probes, permitting simultaneous imaging and manipulation. A dual-probe AFM (DP-AFM) provides a foundation for feedback controlled manipulation. Paper I investigates probe-on-probe contact stability and examines the dynamics of probe-on-probe contact. Evaluation of these interactions leads to study the stability of state-dependent switched systems. Uniform ultimate boundedness theorem and sequence nonincreasing condition corollary were employed to show stability of proposed state dependent switched model with DP-AFM application. Paper II is extending approach-retract curve to characterize probe-on-probe interaction. Universal sensitivity model for probe-on-probe interaction was found. During the retract phase, adhesion occurs between probes. Jump-off-contact deflection between probes was employed for adhesion force calculation. Paper III represents implementation of Iterative Learning Control on Z-axis nanostage with stochastic and deterministic noise. The nano stage model was identified using frequency response of the stage. Deterministic and stochastic noise spectrum was identified experimentally. Optimal Q filter and learning filter (L-filter) were designed depending on the deterministic and stochastic noise spectrum. The error norm was experimentally found to be converging for all four ILC algorithms”--Abstract, page iv

Predicting Trajectory Paths For Collision Avoidance Systems

This work was motivated by the idea of developing a more encompassing collision avoidance system that supported vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communications. Current systems are mostly based on line of sight sensors that are used to prevent a collision, but these systems would prevent even more accidents if they could detect possible collisions before both vehicles were in line of sight. For this research we concentrated mostly on the aspect of improving the prediction of a vehicle\u27s future trajectory, particularly on non-straight paths. Having an accurate prediction of where the vehicle is heading is crucial for the system to reliably determine possible path intersections of more than one vehicle at the same time. We first evaluated the benefits of merging Global Positioning System (GPS) data with the Geographical Information System (GIS) data to correct improbable predicted positions. We then created a new algorithm called the Dead Reckoning with Dynamic Errors (DRWDE) sensor fusion, which can predict future positions at the rate of its fastest sensor, while improving the handling of accumulated error while some of the sensors are offline for a given period of time. The last part of out research consisted in the evaluation of the use of smartphones\u27 built-in sensors to predict a vehicle\u27s trajectory, as a possible intermediate solution for a vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communications, until all vehicles have all the necessary sensors and communication infrastructure to fully populate this new system. For the first part of our research, the actual experimental results validated our proposed system, which reduced the position prediction errors during curves to around half of what it would be without the use of GIS data for prediction corrections. The next improvement we worked on was the ability to handle change in noise, depending on unavailable sensor measurements, permitting a flexibility to use any type of sensor and still have the system run at the fastest frequency available. Compared to a more common KF implementation that run at the rate of its slowest sensor (1Hz in our setup), our experimental results showed that our DRWDE (running at 10Hz) yielded more accurate predictions (25-50% improvement) during abrupt changes in the heading of the vehicle. The last part of our research showed that, comparing to results obtained with the vehicle-mounted sensors, some smartphones yield similar prediction errors and can be used to predict a future position

Control of single- and dual-probe atomic force microscopy

“Atomic force microscope (AFM) is one of the important and versatile tools available in the field of nanotechnology. It is a type of probe-based microscopy wherein an atomically sharp tip, mounted on the free end of a microcantilever, probes the surface of interest to generate 3D topographical images with nanoscale resolution. An integral part of the AFM is the feedback controller that regulates the probe deflection in the presence of surface height changes, enabling the control action to be used for generating topographical image of the sample. Besides sensing, the probe can also be used as a mechanical actuator to manipulate nanoparticles and fabricate nanoscale structures. Despite its capabilities, AFM is not considered user-friendly because imaging is slow, and fabrication operations are laborious and often performed in open-loop, i.e. without any monitoring mechanism. This dissertation is composed of two journal articles which aim to address prominent AFM challenges using feedback control strategies. First article proposes a novel control design methodology based on repetitive control technique to accurately track AFM samples. Theoretical and experimental results demonstrate that incorporating a model of the general sample topography in the control design leads to superior tracking in AFM. Second article introduces a novel dual-probe AFM (DP-AFM) design that has two independent probes. Such a setup provides an opportunity to implement process control strategies where one probe can be used to perform one of the many AFM operations while the other probe can provide feedback by imaging the process. To demonstrate this capability, an application involving real-time plowing depth control where plow depth is controlled with nanometer-level accuracy is also presented”--Abstract, page iv

Adhäsions- und Reibungsverhalten von Nano- und Mikropartikeln auf Siliziumwafern

In der vorliegenden Arbeit wurde das Reibungsverhalten auf Siliziumwafern von Polystyrol-Nanopartikeln mit einem Durchmesser von 100 nm bestimmt. Dazu wurden Manipulationsexperimente mit Hilfe eines Rasterkraftmikroskopes im Peak-Force-Tapping Modus durchgeführt. Durch ein Kräftemodell wurde, unter Verwendung der zusätzlich gemessenen Adhäsionskraft, die Gleitreibungskraft zwischen den Nanopartikeln und der Oberfläche in wäsrigen Medien mit pH 2, pH 6 und pH 9 bestimmt. Darüber hinaus wurden teilweise fluoreszierende Mikropartikel mit einem Durchmesser von 2 µm erzeugt und ein Versuchsaufbau erstellt, der eine Beobachtung der Fluoreszenzpartikel während der Manipulation erlaubte. Damit war es möglich eine Rollbewegung von Mikropartikeln direkt zu beobachten und nachzuweisen

A study of protein-DNA interactions using atomic force microscopy and DNA origami

The development and application of genome editing tools has accelerated in recent years. However, their widespread application, especially in the medical field, is delayed for various issues with the safety of the tools being one of the top concerns. Much of the detail of how proteins find their target sites and how they cleave at the sites remains unclear. Despite much progress in lab environments, where the tolerance for imprecise cutting is relatively high, in vivo treatment remains difficult. Most genome editing tools are derived from naturally occurring regulatory proteins. Better understanding of the mechanisms used by these natural proteins should facilitate the use of genome editing tools. In nature, gene regulation is usually sparked by a change in the cellular environment, such as viruses invading a bacterium. Restriction enzymes defend the host bacteria by recognising specific sites on the viral DNA and cutting invading viruses at those sites. We aim first to understand how these proteins translocate along the viral DNA molecules toward their recognition sites, and then to see how their accuracy of cleavage can be increased. Protein translocation along DNA molecules has been studied for more than 40 years. Atomic force microscopy in fluid mode allows direct observation of protein/DNA interactions. This application is about twenty years old but most of the images taken, lack the spatial and temporal resolution for quantitative studies of protein translocation dynamics. Here we achieve second-level and nanometre-scale tracking of the translocation of EcoRV, a Type IIP restriction enzyme, using fast-scan atomic force microscopy (AFM) and DNA origami techniques. We find that EcoRV tends to jump toward its recognition site from afar and then switch to slow sliding mode when it is within about 20 base pairs of its recognition site. Our methods demonstrate how BcgI, a type IIB restriction enzyme, brings together two recognition sites both in cis and in trans before cleavage, minimising mis-cleavage at a single recognition site. We show that the collision looping model is valid but not the sliding model. The two restriction enzymes were chosen as they represent different model systems of typical restriction enzymes. Our methods will be useful in studies of other types of restriction enzymes and other proteins or protein complexes that interact with DNA. We expect that these methods will see broader applications in studies of protein-DNA interactions. We also hope that our studies will contribute to the safe application of the genome-editing tools in medical contexts.Cambridge Trus