A new Linear RFQ Ion Trap/Axial Time-of-Flight mass spectrometer was developed and tested. A segmented quadrupole rod system was used to create a static axially confining field that could trap and cool an ion cloud from a DC ion source. In addition, an adjustable extraction field was applied, after sufficient ion collection, by pulsing the trapping rod segments to send the cooled ion cloud into a collinear Time-of-Flight spectrometer. Two chevron stacked multichannel plates, with a measured charge amplification of 3.75 x 107, were used as a detector at the end of the flight tube. / The purpose of this work was to investigate ion dynamics in the linear trap (LTRAP) so as to determine the suitability of this system as a source for TOFMS. The trap was therefore designed to be relatively weak so that the ion collection volume would be large enough to obtain a detailed picture of the cloud. The system was tested using a Cs+ (m/ z =133) ion source. Optimal parameters were found to be an applied well depth of -5V to -15V with a q value between 0.3 and 0.6 in a buffer gas environment of N2 at pressures of 10 -4 Torr or greater. Under these conditions and a cooling/collection time of 50ms the trap was observed to contain about 2500 ions. This translated to a detection efficiency of about 26.7% of the ions entering LTRAP. / Computer simulations based on a thermodynamic model were created to analyze the experimental data. The ion ensemble was found to reach an equilibrium temperature of 0.0353 +/- 0.0025eV in less than 10ms. Another computer program was used to reconstruct the phase space density of the LTRAP collection from the detector signals. The results of this reconstruction agreed with the results obtained from the model fitting procedure thereby confirming the thermodynamic model. / The phase space density distribution in LTRAP showed that with a time-focusing reflectron even this weak trap would have a m/Delta m = 250. This has led to guidelines for the construction of a high-resolution hybrid mass spectrometer using a linear ion trap. Based on these current results, a mass resolution of almost 10,000 is predicted as an upper limit of this type of mass spectrometer.

This thesis consists of two papers, dealing with complementary applications of the Feynman-Vernon influence functional formalism to describe different thermal effects in quantum fields. In the first paper, a black body of finite extent is treated as an unobserved environment in the course of a microscopic derivation of black body radiation. In the second paper, a quantum field is treated as an environment probed by a pointlike accelerating detector, which experiences the thermal Unruh effect (apparent heating of the vacuum). Issues of locality and directionality in quantum field theory are treated in both papers.

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Two active topics in radiation therapy treatment verification, portal image segmentation and correlation, are addressed, and a robust algorithm for automatic segmentation of portal images and portal image registration with respect to a reference image is developed. Morphological techniques have been intensively applied in all stages of the segmentation part of this algorithm, from edge detection to feature extraction. An important issue, edge enhancement, is discussed particularly in detail. The performance of the morphological edge detection technique on portal images is compared with that of local gradient operators and optimal edge detectors, while the advantage of the morphological edge detection and segmentation techniques is justified. The treatment field mask is proposed as the landmark for portal-simulator image correlation achieved by matching inertia moments of landmarks. The effect of two different landmarks, the treatment field mask and the treatment field contour, is examined with this correlation method, and the superiority of using the treatment field mask is shown.

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Colloidal clusters, aggregates of a few micrometer-sized spherical particles, are a model experimental system for understanding the physics of self-assembly and processes such as nucleation. Colloidal clusters are well suited for studies on these topics because they are the simplest colloidal system with internal degrees of freedom. Clusters made from particles that weakly attract one another continually rearrange between different structures. By characterizing these internal dynamics and the structures connected by the rearrangement pathways, we seek to understand the statistical physics underlying self-assembly and equilibration. In this thesis, we examine the rearrangement dynamics of colloidal clusters and analyze the equilibrium distributions of ground and excited states. We prepare clusters of up to ten microspheres bound by short-range depletion interactions that are tuned to allow equilibration between multiple isostatic arrangements. To study these clusters, we use bright-field and digital holographic microscopy paired with computational post-processing to amass ensemble-averaged and time-averaged probabilities. We study both two-dimensional (2D) and three-dimensional (3D) clusters composed of either one or two species of particles. To learn about geometrical nucleation barriers, we track rearrangements of particles within freely rotating and translating 3D clusters. We show that rearrangements occur on a timescale of seconds, consistent with diffusion-dominated internal dynamics. To better understand excited states and transition pathways, we track hundreds of rearrangements between degenerate ground states in 2D clusters. We show that the rearrangement rates can be understood using a model with two parameters, which account for the diffusion coefficient along the excited-state rearrangement pathways and the interaction potential. To explore new methods to control self-assembly, we analyze clusters of two species with different masses and different interactions. We find that the interactions allow for control over the intracluster placement of each species, while the masses have no influence. To provide a theoretical framework for understanding these observations, we derive the classical partition function of colloidal clusters in terms of translational, rotational, and vibrational degrees of freedom. We show that the masses of the particles enter the partition function through the kinetic energy but have no effect on the probabilities of states that differ only in where the masses are placed. This result is consistent with our experiments. Overall, this work shows that the equilibrium distribution of self-assembled colloidal clusters is well-modeled by classical statistical physics, and that the rearrangement dynamics of colloidal clusters can be understood by incorporating diffusion and the effect of the interaction potential. Because both the structures and dynamics can be accurately predicted, these clusters are a promising system for self-assembling novel materials and for studying the emergence of phase transitions. / Engineering and Applied Sciences - Applied Physics

It is widely assumed that when colloidal particles adsorb to a fluid-fluid interface, they reach equilibrium rapidly. Recently, however, Kaz et al. [Nature Materials, 11, 138-142 (2012)] found that a variety of functionalised latex microspheres breaching an aqueous phase-oil interface relax logarithmically with time toward equilibrium. The relaxation is so slow that the time projected for the particles to reach the equilibrium contact angle of 110◦ is months – far longer than typical experimental timescales. In this thesis, we seek to understand the out-of-equilibrium behaviour of particles near interfaces. Because contact line pinning is likely an extra source of dissipation at interfaces, we start with experiments to elucidate the origins of contact-line pinning and find that polymer hairs on aqueous dispersed polymer particles strongly pin the contact-line. For particles without polymer hairs, nanoscale surface roughness can also pin the contact-line, though with a lower energy. We then extend our digital holography capabilities to track non-spherical particles. We demonstrate that we can track the centre-of-mass of a colloidal spherocylinder to a precision of 35 nm in all three dimensions and its orientation to a precision of 1.5◦ . Furthermore, the measured translational and rotational diffusion coefficients for the spherocylinders agree with hydrodynamic predictions to within 0.3%. This new functionality enables us to track colloidal ellipsoids and spherocylinders as they breach interfaces. By comparing the adsorption trajectories of the non-spherical particles to what is predicted from energy minimisation, we learn that contact-line pinning affects not just the timescales of breaching, but also the pathway to equilibrium. In fact, a particle’s path to equilibrium can have complications even before the particle breaches the interface. Some particles are attracted to the interface, but stay within a few nanometers without ever breaching. We refer to this binding-mode as ‘non-capillary binding’, and we investigate when this binding mode is present, what causes it, and how interparticle interactions depend on the binding mode. The last few chapters in this thesis are extensions of ideas developed in the first part. We track the run and tumble of E.coli to demonstrate the potential of digital holographic microscopy as an imaging tool for active particles. Taking all of the particle-interface literature into account, we also outline some simple design principles for making particle-stabilised Pickering emulsions. / Engineering and Applied Sciences - Applied Physics

We study four systems where individual units come together to display a range of collective behavior. First, we consider a physical system of phase oscillators on a network that expands the Kuramoto model to include oscillator-network interactions and the presence of noise: using a Hebbian-like learning rule, oscillators that synchronize in turn strengthen their connections to each other. We find that the average degree of connectivity strongly affects rates of flipping between aligned and anti-aligned states, and that this result persists to the case of complex networks. Turning to a fully multi-player, multi-strategy evolutionary dynamics model of cooperating bacteria that change who they give resources to and take resources from, we find several regimes that give rise to high levels of collective structure in the resulting networks. In this setting, we also explore the conditions in which an intervention that affects cooperation itself (e.g. “seeding the network with defectors”) can lead to wiping out an infection. We find a non-monotonic connection between the percent of disabled cooperation and cure rate, suggesting that in some regimes a limited perturbation can lead to total population collapse. At a larger scale, we study how the locomotor system recovers after amputation in fruit flies. Through experiment and a theoretical model of multi-legged motion controlled by neural oscillators, we find that proprioception plays a role in the ability of flies to control leg forces appropriately to recover from a large initial turning bias induced by the injury. Finally, at the human scale, we consider a social network in a traditional society in Africa to understand how social ties lead to group formation for collective action (stealth raids). We identify critical and distinct roles for both leadership (important for catalyzing a group) and friendship (important for final composition). We conclude with prospects for future work. / Physics

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