In-situ measurement and characterization of cloud particles using digital in-line holography

Satellite measurement validations, climate models, atmospheric radiative transfer models and cloud models, all depend on accurate measurements of cloud particle size distributions, number densities, spatial distributions, and other parameters relevant to cloud microphysical processes. And many airborne instruments designed to measure size distributions and concentrations of cloud particles have large uncertainties in measuring number densities and size distributions of small ice crystals. HOLODEC (Holographic Detector for Clouds) is a new instrument that does not have many of these uncertainties and makes possible measurements that other probes have never made. The advantages of HOLODEC are inherent to the holographic method. In this dissertation, I describe HOLODEC, its in-situ measurements of cloud particles, and the results of its test flights. I present a hologram reconstruction algorithm that has a sample spacing that does not vary with reconstruction distance. This reconstruction algorithm accurately reconstructs the field to all distances inside a typical holographic measurement volume as proven by comparison with analytical solutions to the Huygens-Fresnel diffraction integral. It is fast to compute, and has diffraction limited resolution. Further, described herein is an algorithm that can find the position along the optical axis of small particles as well as large complex-shaped particles. I explain an implementation of these algorithms that is an efficient, robust, automated program that allows us to process holograms on a computer cluster in a reasonable time. I show size distributions and number densities of cloud particles, and show that they are within the uncertainty of independent measurements made with another measurement method. The feasibility of another cloud particle instrument that has advantages over new standard instruments is proven. These advantages include a unique ability to detect shattered particles using three-dimensional positions, and a sample volume size that does not vary with particle size or airspeed. It also is able to yield two-dimensional particle profiles using the same measurements.

SOLUTE-DERIVED THERMAL STABILITY OF NANOCRYSTALLINE ALUMINUM AND PROCESSING FACTOR INFLUENCE ON THE FORMATION OF AL6MN QUASICRYSTALS IN MELT-SPINNING

Thermal stability of nanograined metals can be difficult to attain due to the large driving force for grain growth that arises from the significant boundary area constituted by the nanostructure. Kinetic approaches for stabilization of the nanostructure effective at low homologous temperatures often fail at higher homologous temperatures. Thermodynamic approaches for thermal stabilization may offer higher temperature stability. In this research, modest alloying of aluminum with solute (1 at.% Sc, Yb, or Sr) was examined as a means to thermodynamically stabilize a bulk nanostructure at elevated temperatures. After using melt-spinning and ball-milling to create an extended solid-solution and nanostructure with average grain size on the order of 30-45 nm, 1 h annealing treatments at 673 K (0.72 Tm) , 773 K (0.83 Tm) , and 873 K (0.94 Tm) were applied. The alloys remain nanocrystalline (<100 nm) as measured by Warren-Averbach Fourier analysis of x-ray diffraction peaks and direct observation of TEM dark field micrographs, with the efficacy of stabilization: Sr>Yb>Sc. Disappearance of intermetallic phases in the Sr and Yb alloys in the x-ray diffraction spectra are observed to occur coincident with the stabilization after annealing, suggesting that precipitates dissolve and the boundaries are enriched with solute. Melt-spinning has also been shown to be an effective process to produce a class of ordered, but non-periodic crystals called quasicrystals. However, many of the factors related to the creation of the quasicrystals through melt-spinning are not optimized for specific chemistries and alloy systems. In a related but separate aspect of this research, meltspinning was utilized to create metastable quasicrystalline Al6Mn in an α-Al matrix through rapid solidification of Al-8Mn (by mol) and Al-10Mn (by mol) alloys. Wheel speed of the melt-spinning wheel and orifice diameter of the tube reservoir were varied to determine their effect on the resulting volume proportions of the resultant phases using integrated areas of collected x-ray diffraction spectra. The data were then used to extrapolate parameters for the Al-10Mn alloy which consistently produced Al6Mn quasicrystal with almost complete suppression of the equilibrium Al6Mn orthorhombic phase.

INTEGRATION OF INSTRUMENTATION AND PROCESSING SOFTWARE OF A LASER SPECKLE CONTRAST IMAGING SYSTEM

Laser speckle contrast imaging (LSCI) has the potential to be a powerful tool in medicine, but more research in the field is required so it can be used properly. To help in the progression of Michigan Tech's research in the field, a graphical user interface (GUI) was designed in Matlab to control the instrumentation of the experiments as well as process the raw speckle images into contrast images while they are being acquired. The design of the system was successful and is currently being used by Michigan Tech's Biomedical Engineering department. This thesis describes the development of the LSCI GUI as well as offering a full introduction into the history, theory and applications of LSCI.

Development of measurement and modeling techniques to quantify atmospheric deposition of persistent, bioaccumulative and toxic chemicals in the Great Lakes

Measurement and modeling techniques were developed to improve over-water gaseous air-water exchange measurements for persistent bioaccumulative and toxic chemicals (PBTs). Analytical methods were applied to atmospheric measurements of hexachlorobenzene (HCB), polychlorinated biphenyls (PCBs), and polybrominated diphenyl ethers (PBDEs). Additionally, the sampling and analytical methods are well suited to study semivolatile organic compounds (SOCs) in air with applications related to secondary organic aerosol formation, urban, and indoor air quality. A novel gas-phase cleanup method is described for use with thermal desorption methods for analysis of atmospheric SOCs using multicapillary denuders. The cleanup selectively removed hydrogen-bonding chemicals from samples, including much of the background matrix of oxidized organic compounds in ambient air, and thereby improved precision and method detection limits for nonpolar analytes. A model is presented that predicts gas collection efficiency and particle collection artifact for SOCs in multicapillary denuders using polydimethylsiloxane (PDMS) sorbent. An approach is presented to estimate the equilibrium PDMS-gas partition coefficient (Kpdms) from an Abraham solvation parameter model for any SOC. A high flow rate (300 L min-1) multicapillary denuder was designed for measurement of trace atmospheric SOCs. Overall method precision and detection limits were determined using field duplicates and compared to the conventional high-volume sampler method. The high-flow denuder is an alternative to high-volume or passive samplers when separation of gas and particle-associated SOCs upstream of a filter and short sample collection time are advantageous. A Lagrangian internal boundary layer transport exchange (IBLTE) Model is described. The model predicts the near-surface variation in several quantities with fetch in coastal, offshore flow: 1) modification in potential temperature and gas mixing ratio, 2) surface fluxes of sensible heat, water vapor, and trace gases using the NOAA COARE Bulk Algorithm and Gas Transfer Model, 3) vertical gradients in potential temperature and mixing ratio. The model was applied to interpret micrometeorological measurements of air-water exchange flux of HCB and several PCB congeners in Lake Superior. The IBLTE Model can be applied to any scalar, including water vapor, carbon dioxide, dimethyl sulfide, and other scalar quantities of interest with respect to hydrology, climate, and ecosystem science.

Estimation of the degree of polarization through computational sensing

The degree of polarization of a refected field from active laser illumination can be used for object identifcation and classifcation. The goal of this study is to investigate methods for estimating the degree of polarization for refected fields with active laser illumination, which involves the measurement and processing of two orthogonal field components (complex amplitudes), two orthogonal intensity components, and the total field intensity. We propose to replace interferometric optical apparatuses with a computational approach for estimating the degree of polarization from two orthogonal intensity data and total intensity data. Cramer-Rao bounds for each of the three sensing modalities with various noise models are computed. Algebraic estimators and maximum-likelihood (ML) estimators are proposed. Active-set algorithm and expectation-maximization (EM) algorithm are used to compute ML estimates. The performances of the estimators are compared with each other and with their corresponding Cramer-Rao bounds. Estimators for four-channel polarimeter (intensity interferometer) sensing have a better performance than orthogonal intensities estimators and total intensity estimators. Processing the four intensities data from polarimeter, however, requires complicated optical devices, alignment, and four CCD detectors. It only requires one or two detectors and a computer to process orthogonal intensities data and total intensity data, and the bounds and estimator performances demonstrate that reasonable estimates may still be obtained from orthogonal intensities or total intensity data. Computational sensing is a promising way to estimate the degree of polarization.

Nanomechanics of cellulose crystals and cellulose-based polymer composites

Cellulose-polymer composites have potential applications in aerospace and transportation areas where lightweight materials with high mechanical properties are needed. In addition, these economical and biodegradable composites have been shown to be useful as polymer electrolytes, packaging structures, optoelectronic devices, and medical implants such as wound dressing and bone scaffolds. In spite of the above mentioned advantages and potential applications, due to the difficulties associated with synthesis and processing techniques, application of cellulose crystals (micro and nano sized) for preparation of new composite systems is limited. Cellulose is hydrophilic and polar as opposed to most of common thermoplastics, which are non-polar. This results in complications in addition of cellulose crystals to polymer matrices, and as a result in achieving sufficient dispersion levels, which directly affects the mechanical properties of the composites. As in other composite materials, the properties of cellulose-polymer composites depend on the volume fraction and the properties of individual phases (the reinforcement and the polymer matrix), the dispersion quality of the reinforcement through the matrix and the interaction between CNCs themselves and CNC and the matrix (interphase). In order to develop economical cellulose-polymer composites with superior qualities, the properties of individual cellulose crystals, as well as the effect of dispersion of reinforcements and the interphase on the properties of the final composites should be understood. In this research, the mechanical properties of CNC polymer composites were characterized at the macro and nano scales. A direct correlation was made between: Dispersion quality and macro-mechanical properties Nanomechanical properties at the surface and tensile properties CNC diameter and interphase thickness Lastly, individual CNCs from different sources were characterized and for the first time size-scale effect on their nanomechanical properties were reported. Then the effect of CNC surface modification on the mechanical properties was studied and correlated to the crystalline structure of these materials.

DYNAMICS AND CONTROL OF REACTIVE DISTILLATION PROCESS FOR MONOMER SYNTHESIS OF POLYCARBONATE PLANTS

Polycarbonate (PC) is an important engineering thermoplastic that is currently produced in large industrial scale using bisphenol A and monomers such as phosgene. Since phosgene is highly toxic, a non-phosgene approach using diphenyl carbonate (DPC) as an alternative monomer, as developed by Asahi Corporation of Japan, is a significantly more environmentally friendly alternative. Other advantages include the use of CO2 instead of CO as raw material and the elimination of major waste water production. However, for the production of DPC to be economically viable, reactive-distillation units are needed to obtain the necessary yields by shifting the reaction-equilibrium to the desired products and separating the products at the point where the equilibrium reaction occurs. In the field of chemical reaction engineering, there are many reactions that are suffering from the low equilibrium constant. The main goal of this research is to determine the optimal process needed to shift the reactions by using appropriate control strategies of the reactive distillation system. An extensive dynamic mathematical model has been developed to help us investigate different control and processing strategies of the reactive distillation units to increase the production of DPC. The high-fidelity dynamic models include extensive thermodynamic and reaction-kinetics models while incorporating the necessary mass and energy balance of the various stages of the reactive distillation units. The study presented in this document shows the possibility of producing DPC via one reactive distillation instead of the conventional two-column, with a production rate of 16.75 tons/h corresponding to start reactants materials of 74.69 tons/h of Phenol and 35.75 tons/h of Dimethyl Carbonate. This represents a threefold increase over the projected production rate given in the literature based on a two-column configuration. In addition, the purity of the DPC produced could reach levels as high as 99.5% with the effective use of controls. These studies are based on simulation done using high-fidelity dynamic models.