Single polymer dynamics in semi-dilute solutions: linear and ring polymers

Synthetic and biological polymers are ubiquitous in nature and modern technologies. Traditional characterization methods of polymeric materials rely on bulk level measurements that can provide useful information on material properties. However, these methods generally cannot access underlying molecular information, such as polymer conformation, distributions in molecular behavior, and the role of intermolecular interactions in non-equilibrium flows. Over the past two decades, single molecule techniques have been established to investigate molecular-level dynamics, thereby allowing direct access to polymer chain relaxation mechanisms and polymer non-linear response under a variety of flows. Despite recent progress in the field of single polymer dynamics, however, the vast majority of single molecule studies has focused on dilute solutions of linear polymers. In this thesis, we effectively extend single molecule imaging to increasingly complex polymeric systems of increasing polymer concentration and more complex chain architectures. In this way, we aim to address several fundamental questions, including how do polymer concentration and chain architecture affect dynamics at the single chain level? We address these questions using a combination of single molecule experiments and Brownian dynamics simulations. In one project, we performed a series of single molecule experiments by systematically increasing polymer concentration to the semi-dilute untangled regime. Based on these results, we obtained a scaling relation for longest polymer relaxation time as a function of concentration, and these results are compared to blob scaling theories. We further studied single polymer dynamics upon a step-strain deformation in planar extensional flow, including both transient and steady state polymer extension. Experimental data are compared to results from large-scale Brownian dynamics simulations that include intra- and intermolecular hydrodynamic interactions and excluded volume interactions, work performed in collaboration with the Prakash group at Monash University. In this way, we obtain parameter-free predictions of polymer dynamics in non-dilute flows using the method successive fine-graining. Remarkably, our results show a close comparison between experiments and simulation, which provides a solid understanding of polymer dynamics in the semi-dilute concentration regime, both near equilibrium under strong flow. In the second project, we studied the impact of circular polymer or ring polymer topology on single chain dynamics in extensional flows. Single molecule experiments revealed that ring polymers stretch differently compared to linear polymers in extensional flows in the context of the coil-stretch transition. Interestingly, we found that the ring structure exhibits a strong hydrodynamic coupling between the two strands of a stretched ring, which leads to a "slow-down" of the coil-stretch transition and a looping effect of rings under strong extensional flow. Moving beyond our work on single chain dynamics in dilute and semi-dilute solutions, we further sought to identify how molecular-scale interactions are translated into collective non-Newtonian fluid properties. In particular, we developed a new technique to directly measure normal stresses or extensional viscosity in microfluidic devices by coupling the Stokes trap with particle tracking. Here, we study the phenomenon of flow-induced particle migration to measure polymer-induced solution stresses and extensional viscosity in semi-dilute solutions of DNA and synthetic polymers. We combined the automated hydrodynamic trap, which is a home-built microfluidic hydro- dynamic trap, and a piezo-nano positioning stage to directly observe particle migration in polymer solution undergoing planar extensional flow. Experimental data was analyzed in the context of a second-order fluid model in order to determine normal stress. Finally, extensional viscosity was deduced from particle migration experiments, and these results showed favorable comparison to extensional viscosity measurements determined with the optically-detected elastocapillary self-thinning dripping-onto-substrate (ODES-DOS) extensional rheometer. Overall, this thesis aims to provide a fundamental molecular picture of polymer dynamics in the semi-dilute concentration regime and for different polymer architectures. Combining single molecule fluorescence microscopy, Brownian dynamics simulation, 3D particle tracking, and continuum-level constitutive equations, we are able to provide an informative physical picture of polymers in non-Newtonian semi-dilute polymer solutions. From a broad view, this work provides a starting point to relate macroscopic stress response to a microscopic or molecular-level interactions, thereby providing a new perspective to understand non-linear polymer properties

Effects of surface properties on solder bump formation by direct droplet deposition

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2004.Includes bibliographical references (leaves 158-162).Recent advances in microdroplet generation and deposition processes have made it possible to directly form solder bumps on integrated circuits using micron-sized molten metal droplets. The direct droplet deposition bumping process can potentially produce uniform-sized bumps more economically than the existing processes such as plating and stencil printing. However, the development of this new bumping method is still in its infancy, particularly because of a lack of understanding about the post-impact deposition behavior of molten droplets on solid targets. A deposited molten on the deposition efficiency, as well as on the final bump size and shape. The present study investigates the effects of wetting and surface roughness on droplet bouncing during solder bump formation. The potential for droplet bouncing is modeled based on the energy difference between the maximum spreading and equilibrium sessile stages of a deposited droplet. Validated by experimental results, the model shows that strong droplet-surface wetting can significantly reduce the tendency for a deposited droplet to bounce. The effect of surface droplet can sometimes recoil violently after the initial spreading and rebound off the target surface. Such behavior, known as bouncing, has a strong influence roughness on the bouncing potential is represented by the roughness-induced incomplete wetting during droplet deposition, a phenomenon quantified by a change in the effective contact area under the deposited droplet. An idealized surface model is used to represent the real surface and to describe the relationship between various roughness parameters to changes in the effective contact area. The theoretical analysis, validated by empirical data, shows that surface effective(cont.) contact area. The theoretical analysis, validated by empirical data, shows that surface roughness promotes bouncing during solder bump formation. The results from this study suggest that droplet bouncing during solder bump formation may be effectively controlled by improving the surface wetting and minimizing the substrate surface roughness. The knowledge gained is also relevant to other droplet-based manufacturing processes such as spray forming, coating, and rapid prototyping.by Wen-Kai Hsiao.Ph.D

Printing stable liquid tracks on a surface with finite receding contact angle.

We have used high-speed imaging to study the formation of liquid tracks on a surface with nonzero receding contact angle, by the sequential deposition of liquid drops. For small drop spacing we found good agreement with the track morphology predicted by an existing line stability model. In addition, we confirmed definitively the preferential drop-to-bead fluid flow and the predicted drop spreading variation in the scalloped line and paired bead formation regimes. However, we found that without accounting for drop impact inertia, the model underestimated the maximum drop spreading radii and, hence, the instantaneous track width. In addition, the printed track became stable at larger drop spacing, in contrast to the expected behavior. We believe that the destabilizing effect of a receding contact line may be minimized when track radii, as predicted by volume conservation and drop-bead coalescence dynamics, converge as the drop spacing increases. An increase in viscous dissipation and a reduction of the capillary-driven flow may be the additional stabilization mechanisms. The latter may also be responsible for achieving a stable and symmetrical track when printing with a shorter interval (higher print frequency) at a given drop spacing.This project was supported by the UK Engineering and Physical Sciences Research Council and industrial partners in the Programme Grant number EP/H018913/1 ‘Innovation in Industrial Inkjet Technology’.This is the final published version. It first appeared at http://pubs.acs.org/doi/abs/10.1021/la502490p

A New Paradigm for Device-free Indoor Localization: Deep Learning with Error Vector Spectrum in Wi-Fi Systems

The demand for device-free indoor localization using commercial Wi-Fi devices has rapidly increased in various fields due to its convenience and versatile applications. However, random frequency offset (RFO) in wireless channels poses challenges to the accuracy of indoor localization when using fluctuating channel state information (CSI). To mitigate the RFO problem, an error vector spectrum (EVS) is conceived thanks to its higher resolution of signal and robustness to RFO. To address these challenges, this paper proposed a novel error vector assisted learning (EVAL) for device-free indoor localization. The proposed EVAL scheme employs deep neural networks to classify the location of a person in the indoor environment by extracting ample channel features from the physical layer signals. We conducted realistic experiments based on OpenWiFi project to extract both EVS and CSI to examine the performance of different device-free localization techniques. Experimental results show that our proposed EVAL scheme outperforms conventional machine learning methods and benchmarks utilizing either CSI amplitude or phase information. Compared to most existing CSI-based localization schemes, a new paradigm with higher positioning accuracy by adopting EVS is revealed by our proposed EVAL system

Adult rat retinal ganglion cells and glia can be printed by piezoelectric inkjet printing.

We have investigated whether inkjet printing technology can be extended to print cells of the adult rat central nervous system (CNS), retinal ganglion cells (RGC) and glia, and the effects on survival and growth of these cells in culture, which is an important step in the development of tissue grafts for regenerative medicine, and may aid in the cure of blindness. We observed that RGC and glia can be successfully printed using a piezoelectric printer. Whilst inkjet printing reduced the cell population due to sedimentation within the printing system, imaging of the printhead nozzle, which is the area where the cells experience the greatest shear stress and rate, confirmed that there was no evidence of destruction or even significant distortion of the cells during jet ejection and drop formation. Importantly, the viability of the cells was not affected by the printing process. When we cultured the same number of printed and non-printed RGC/glial cells, there was no significant difference in cell survival and RGC neurite outgrowth. In addition, use of a glial substrate significantly increased RGC neurite outgrowth, and this effect was retained when the cells had been printed. In conclusion, printing of RGC and glia using a piezoelectric printhead does not adversely affect viability and survival/growth of the cells in culture. Importantly, printed glial cells retain their growth-promoting properties when used as a substrate, opening new avenues for printed CNS grafts in regenerative medicine

Sampling Neural Radiance Fields for Refractive Objects

Recently, differentiable volume rendering in neural radiance fields (NeRF) has gained a lot of popularity, and its variants have attained many impressive results. However, existing methods usually assume the scene is a homogeneous volume so that a ray is cast along the straight path. In this work, the scene is instead a heterogeneous volume with a piecewise-constant refractive index, where the path will be curved if it intersects the different refractive indices. For novel view synthesis of refractive objects, our NeRF-based framework aims to optimize the radiance fields of bounded volume and boundary from multi-view posed images with refractive object silhouettes. To tackle this challenging problem, the refractive index of a scene is reconstructed from silhouettes. Given the refractive index, we extend the stratified and hierarchical sampling techniques in NeRF to allow drawing samples along a curved path tracked by the Eikonal equation. The results indicate that our framework outperforms the state-of-the-art method both quantitatively and qualitatively, demonstrating better performance on the perceptual similarity metric and an apparent improvement in the rendering quality on several synthetic and real scenes.Comment: SIGGRAPH Asia 2022 Technical Communications. 4 pages, 4 figures, 1 table. Project: https://alexkeroro86.github.io/SampleNeRFRO/ Code: https://github.com/alexkeroro86/SampleNeRFR

Img2Logo:Generating Golden Ratio Logos from Images

Logos are one of the most important graphic design forms that use an abstracted shape to clearly represent the spirit of a community. Among various styles of abstraction, a particular golden-ratio design is frequently employed by designers to create a concise and regular logo. In this context, designers utilize a set of circular arcs with golden ratios (i.e., all arcs are taken from circles whose radii form a geometric series based on the golden ratio) as the design elements to manually approximate a target shape. This error-prone process requires a large amount of time and effort, posing a significant challenge for design space exploration. In this work, we present a novel computational framework that can automatically generate golden ratio logo abstractions from an input image. Our framework is based on a set of carefully identified design principles and a constrained optimization formulation respecting these principles. We also propose a progressive approach that can efficiently solve the optimization problem, resulting in a sequence of abstractions that approximate the input at decreasing levels of detail. We evaluate our work by testing on images with different formats including real photos, clip arts, and line drawings. We also extensively validate the key components and compare our results with manual results by designers to demonstrate the effectiveness of our framework. Moreover, our framework can largely benefit design space exploration via easy specification of design parameters such as abstraction levels, golden circle sizes, etc

Near-Surface Attenuation and Velocity Structures in Taiwan from Wellhead and Borehole Recordings Comparisons

By analyzing the data from 28 seismic borehole stations deployed by the Central Weather Bureau Seismic Network throughout Taiwan from 2007 to 2014, we estimated the near-surface velocity (Vp and Vs) and attenuation (Qp and Qs) structures from surface to depths of approximately 300 m. To ensure that the deeper recordings were on the ray path between the seismic source and upper receiver, only events with an incidence angle of less than 35° were selected. Local magnitudes of analyzed events were between 1.1 and 6.6. The subsurface Qp and Qs were well modeled in the 5 - 40 Hz frequency band using the spectral ratio of direct P- and S-waves, respectively, at each station, under frequency-independent Q and ω2 source model assumptions. The estimated Vp in the Coastal Plain, the Western Foothills, the Longitudinal Valley, and the Yilan Plain were approximately 1000 - 2000 m s-1, which was lower than the Vp of 2500 - 4000 m s-1 in the Central Mountain Range. In addition, the Vs in the plain areas were lower than that in the Central Mountain Range. The low Vp and Vs and high Vp/Vs ratio in the Coastal Plain and the Western Foothills can be attributed to the unconsolidated soil and high pore-fluid content of subsurface sediments in the plain areas. In contrast to the velocity distribution, low Qp and Qs were observed in the Central Mountain Range. The low Qp and Qs with low Vp/Vs and low Qs/Qp ratios in the Central Mountain Range was consistent with the high thermal temperature observed in the field investigation. The obtained velocity and attenuation structures near surface could also provide important constraints in validation of the crustal structure of Taiwan