Estimation of tip-sample force in tapping mode atomic force microscopy using neural-network and repetitive control approaches

Atomic Force Microscopy is one of the most powerful tools for imaging, measuring and manipulating materials at nanometer scale. Among different modes of AFM, tapping mode, in which the oscillating tip touches the sample periodically, is most common mode. During the tip approach and retract, the tip interacts with sample and experiences different force regimes. This tip-sample interaction force contains information about the sample topology, material properties and tip geometry. However, quantitative measurement of the time-varying tip-sample interaction forcing function is challenging in the tapping mode because of the combined dynamic complexities of the cantilever and nonlinear complexity of the tip-sample force. In first part of this research, an initial investigation of a neural-network approach to tip-sample interaction force estimation is studied. The tip-sample interaction is treated as an unknown force and a neural-network is used in a dynamic observer framework to approximate the unknown forcing function. Simulations are used to demonstrate plausibility of the approach and accuracy of the force model is evaluated for several scenarios. In second part, an approach based on repetitive control is used to design a filter for execrating tip-sample force signal from noisy tip displacement measurements. Design of the filter parts and their parameters are explained and effect of each parameter on force estimation performance is discussed using simulations. Improvement in filter performance by using torsional harmonic cantilevers as the sensor is demonstrated --Abstract, page iv

Data acquisition and imaging using wavelet transform: a new path for high speed transient force microscopy

The unique ability of Atomic Force Microscopy (AFM) to image, manipulate and characterize materials at the nanoscale has made it a remarkable tool in nanotechnology. In dynamic AFM, acquisition and processing of the photodetector signal originating from probe–sample interaction is a critical step in data analysis and measurements. However, details of such interaction including its nonlinearity and dynamics of the sample surface are limited due to the ultimately bounded bandwidth and limited time scales of data processing electronics of standard AFM. Similarly, transient details of the AFM probe's cantilever signal are lost due to averaging of data by techniques which correlate the frequency spectrum of the captured data with a temporally invariant physical system. Here, we introduce a fundamentally new approach for dynamic AFM data acquisition and imaging based on applying the wavelet transform on the data stream from the photodetector. This approach provides the opportunity for exploration of the transient response of the cantilever, analysis and imaging of the dynamics of amplitude and phase of the signals captured from the photodetector. Furthermore, it can be used for the control of AFM which would yield increased imaging speed. Hence the proposed method opens a pathway for high-speed transient force microscopy

Synaptic Elasticity

Synapses play a critical role in neural circuits, and their highly specialized structures and biochemical characteristics have been widely studied in learning and memory. Along with their role in signal transmission, synapses also serve as adhesion structures, yet their mechanical characteristics have not received much attention. Given the important role of mechanics in cell adhesion, mechanical studies of synapses could offer insights into synaptic development, maintenance, and function. Here, I investigated synaptic elasticity in cultured rat hippocampal neurons and suggest that mechanical elasticity may be related to synaptic plasticity. I used torsional harmonic atomic force microscopy (TH-AFM) to measure the nanomechanical properties of functional mature excitatory synapses, whose identity and activity was verified by fluorescence microscopy. I combined TH-AFM with transmission electron microscopy and found that high stiffness of synapses originated from postsynaptic spines, not presynaptic boutons. I observed that spines at functional mature excitatory synapses were on average 10 times stiffer than dendritic shafts and that the distribution of spine stiffness exhibited a lognormal-like pattern. Importantly, I found that spine stiffness was correlated with spine size, and it is well established that spine size is correlated with synaptic strength. Based on the stiffness measurements and theoretical modelling of cell adhesion stability, I suggest that stiffness not only helps maintain spine morphology in the presence of synapse adhesion, but also helps stabilize synaptic adhesion. I propose a mechanical synaptic plasticity model. According to this model, mechanical strength leads to functional strength, which could provide a potential causal link between structural plasticity and functional plasticity of synapses

Image processing techniques for high-speed atomic force microscopy

Atomic force microscopy (AFM) is a powerful tool for imaging topography or other characteristics of sample surfaces at nanometer-scale spatial resolution by recording the interaction of a sharp probe with the surface. Dispute its excellent spatial resolution, one of the enduring challenges in AFM imaging is its poor temporal resolution relative to the rate of dynamics in many systems of interest. This has led to a large research effort on the development of high-speed AFM (HS-AFM). Most of these efforts focus on mechanical improvement and control algorithm design. This dissertation investigates a complementary HS-AFM approach based on the idea of undersampling which aims at increasing the imaging rate of the instrument by reducing the number of pixels in the sample surface that need to be acquired to create a high-quality image. The first part of this work focuses on the reconstruction of images sub-sampled according to a scheme known as μ path patterns. These patterns consist of randomly placed short and disjoint scans and are designed specifically for fast, efficient, and consistent data acquisition in AFM. We compare compressive sensing (CS) reconstruction methods with inpainting methods on recovering μ-path undersampled images. The results illustrate that the reconstruction quality depends on the choice of reconstruction methods and the sample under study, with CS generally producing a superior result for samples with sparse frequency content and inpainting performing better for samples with information limited to low frequencies. Motivated by the comparison, a basis pursuit vertical variation (BPVV) method, combing CS and inpainting, is proposed. Based on single image reconstruction results, we also extend our analysis to the problem of multiple AFM frames, in which higher overall video reconstruction quality is achieved by pixel sharing among different frames. The second part of the thesis considers patterns for sub-sampling in AFM. The allocation of measurements plays an important role in producing accurate reconstructions of the sample surface. We analyze the expected image reconstruction error using a greedy CS algorithm of our design, termed simplified matching pursuit (SMP), and propose a Monte Carlo-based strategy to create μ-path patterns that minimize the expected error. Because these μ path patterns involve a collection of disjoint scan paths, they require the tip of the instrument to be repeatedly lifted from and re-engaged to the surface. In many cases, the re-engagements make up a significant portion of the total data acquisition time. We therefore extend our Monte Carlo design strategy to find continuous scan patterns that minimize the reconstruction error without requiring the tip to be lifted from the surface. For the final part of the work, we provide a hardware demonstration on a commercial AFM. We describe hardware implementation details and image a calibration grating using the proposed μ-path and continuous scan patterns. The sample surface is reconstructed from acquired data using CS and inpainting methods. The recovered image quality and achievable imaging rate are compared to full raster-scans of the sample. The experimental results show that the proposed scanning combining with reconstruction methods can produce higher image quality with less imaging time

Hybrid structures for molecular level sensing

With substantial molecular mobility and segment dynamics relative to metals and ceramics, all polymeric materials, to some extent, are stimuli-responsive by exhibiting pronounced chemical and physical changes in the backbone, side chains, segments, or end groups induced by changes in the local environment. Thus, the push to incorporate polymeric materials as sensing/responsive nanoscale layers into next-generation miniaturized sensor applications is a natural progression. The significance and impact of this research is wide-ranging because it offers design considerations and presents results in perhaps two of the most critical broad areas of nanotechnology: ultrathin multifunctional polymer coatings and miniaturized sensors. In this work, direct evidence is given showing that polymer coatings comprised of deliberately selected molecular segments with very different chemistry can have switchable properties, and that the surface composition can be precisely controlled, and thus properties can be tuned: all in films on the order of 20 nm and less. Furthermore, active sensing layers in the form of plasma-polymerized polymers are successfully incorporated into actual silicon based microsensors resulting in a novel hybrid organic/inorganic materials platform for microfabricated MEMS sensors with record performance far beyond contemporary sensors in terms of detection sensitivity to various environments. The results produced in this research show thermal sensors with more than two orders of magnitude better sensitivity than what is attainable currently. In addition, a humidity response on the order of parts per trillion, which is four orders of magnitude more sensitive than current designs is achieved. Molecular interactions and forces for organic molecules are characterized at the picoscale to optimize polymeric nanoscale layer design that in turn optimize and lead to microscale hybrid sensors with unprecedented sensitivities

Nonlinear Dynamics

This volume covers a diverse collection of topics dealing with some of the fundamental concepts and applications embodied in the study of nonlinear dynamics. Each of the 15 chapters contained in this compendium generally fit into one of five topical areas: physics applications, nonlinear oscillators, electrical and mechanical systems, biological and behavioral applications or random processes. The authors of these chapters have contributed a stimulating cross section of new results, which provide a fertile spectrum of ideas that will inspire both seasoned researches and students

Fabrication and characterization of shape memory polymers at small scales

The objective of this research is to thoroughly investigate the shape memory effect in polymers, characterize, and optimize these polymers for applications in information storage systems. Previous research effort in this field concentrated on shape memory metals for biomedical applications such as stents. Minimal work has been done on shape memory poly- mers; and the available work on shape memory polymers has not characterized the behaviors of this category of polymers fully. Copolymer shape memory materials based on diethylene glycol dimethacrylate (DEGDMA) crosslinker, and tert butyl acrylate (tBA) monomer are designed. The design encompasses a careful control of the backbone chemistry of the materials. Characterization methods such as dynamic mechanical analysis (DMA), differential scanning calorimetry (DSC); and novel nanoscale techniques such as atomic force microscopy (AFM), and nanoindentation are applied to this system of materials. Designed experiments are conducted on the materials to optimize spin coating conditions for thin films. Furthermore, the recovery, a key for the use of these polymeric materials for information storage, is examined in detail with respect to temperature. In sum, the overarching objectives of the proposed research are to: (i) design shape memory polymers based on polyethylene glycol dimethacrylate (PEGDMA) and diethylene glycol dimethacrylate (DEGDMA) crosslinkers, 2-hydroxyethyl methacrylate (HEMA) and tert-butyl acrylate monomer (tBA). (ii) utilize dynamic mechanical analysis (DMA) to comprehend the thermomechanical properties of shape memory polymers based on DEGDMA and tBA. (iii) utilize nanoindentation and atomic force microscopy (AFM) to understand the nanoscale behavior of these SMPs, and explore the strain storage and recovery of the polymers from a deformed state. (iv) study spin coating conditions on thin film quality with designed experiments. (iv) apply neural networks and genetic algorithms to optimize these systems.Ph.D.Committee Chair: Gall, Ken; Committee Chair: May, Gary S; Committee Member: Brand, Oliver; Committee Member: Degertekin, F Levent; Committee Member: Milor, Linda

STRUCTURES AND REACTIONS OF BIOMOLECULES AT INTERFACES

This dissertation serves to study a protein\u27s conformation-function relationship since immobilized proteins often behave differently from their solution-state counterparts. Therefore, this study is important to the application of protein-based biodevices. Another aim of this dissertation is to explore a new approach to realize low voltage electrowetting without the help of oil bath. Utilizing this approach, a protein micro-separation was realized. Additionally, the interfacial properties of ionic liquid (IL) solid-like layer, which played a key role in electrowetting, was studied for further developments of IL-based applications. Atomic Force Microscopy (AFM) was utilized in the study and played multiple roles in this dissertation. First, AFM was used as a fabrication tool. In the contact mode, conductive AFM tip was used to conduct the electrochemical oxidation to create a chemical pattern or to conduct an electrowetting experiment. Subsequently, AFM was used as a characterization tool in the tapping mode to characterize the surface structure, the thickness, and the surface potential. Furthermore, AFM in the contact mode was used as a measurement tool to measure the tribological force properties of sample. The results of the study concerning the conformational change in immobilized calmodulin showed that the immobilized CaM retained its activity. Additionally, the immobilization of CaM on a solid support did not interfere with the ability of the protein to bind calcium, as well as CaM kinase binding domain. For the electrowetting experiment, our data suggested that the ultra-high capacitance density of the IL dielectric layer leads to the low voltage electrowetting. We also successfully demonstrated the streptavidin and GFP proteins separation by Electrowetting-on-Dielectric (EWOD) force. The results of the surface properties study indicated that the charge and dipole of the substrate can influence the structures and properties of the IL interfacial layer. Our study would be beneficial in research and assay work involving engineered proteins, as well as the study and development of electrowetting applications