Development of advanced capillary electrophoresis techniques with UV and mass spectrometry detection for forensic, pharmaceutical and environmental applications

Capillary electrophoresis (CE) is a modern analytical technique, which is electrokinetic separation generated by high voltage and taken place inside the small capillaries. In this dissertation, several advanced capillary electrophoresis methods are presented using different approaches of CE and UV and mass spectrometry are utilized as the detection methods. ^ Capillary electrochromatography (CEC), as one of the CE modes, is a recent developed technique which is a hybrid of capillary electrophoresis and high performance liquid chromatography (HPLC). Capillary electrochromatography exhibits advantages of both techniques. In Chapter 2, monolithic capillary column are fabricated using in situ photoinitiation polymerization method. The column was then applied for the separation of six antidepressant compounds. ^ Meanwhile, a simple chiral separation method is developed and presented in Chapter 3. Beta cycodextrin was utilized to achieve the goal of chiral separation. Not only twelve cathinone analytes were separated, but also isomers of several analytes were enantiomerically separated. To better understand the molecular information on the analytes, the TOF-MS system was coupled with the CE. A sheath liquid and a partial filling technique (PFT) were employed to reduce the contamination of MS ionization source. Accurate molecular information was obtained. ^ It is necessary to propose, develop, and optimize new techniques that are suitable for trace-level analysis of samples in forensic, pharmaceutical, and environmental applications. Capillary electrophoresis (CE) was selected for this task, as it requires lower amounts of samples, it simplifies sample preparation, and it has the flexibility to perform separations of neutral and charged molecules as well as enantiomers. ^ Overall, the study demonstrates the versatility of capillary electrophoresis methods in forensic, pharmaceutical, and environmental applications.^

The Use of Hyphenated Spectrometric Techniques for the Environmental Forensic Assessment of Non-Traditional Pollutants and Degradates in the Greater Florida Everglades

A comprehensive investigation of sensitive ecosystems in South Florida with the main goal of determining the identity, spatial distribution, and sources of both organic biocides and trace elements in different environmental compartments is reported. This study presents the development and validation of a fractionation and isolation method of twelve polar acidic herbicides commonly applied in the vicinity of the study areas, including e.g. 2,4-D, MCPA, dichlorprop, mecroprop, picloram in surface water. Solid phase extraction (SPE) was used to isolate the analytes from abiotic matrices containing large amounts of dissolved organic material. Atmospheric-pressure ionization (API) with electrospray ionization in negative mode (ESP-) in a Quadrupole Ion Trap mass spectrometer was used to perform the characterization of the herbicides of interest. The application of Laser Ablation-ICP-MS methodology in the analysis of soils and sediments is reported in this study. The analytical performance of the method was evaluated on certified standards and real soil and sediment samples. Residential soils were analyzed to evaluate feasibility of using the powerful technique as a routine and rapid method to monitor potential contaminated sites. Forty eight sediments were also collected from semi pristine areas in South Florida to conduct screening of baseline levels of bioavailable elements in support of risk evaluation. The LA-ICP-MS data were used to perform a statistical evaluation of the elemental composition as a tool for environmental forensics. A LA-ICP-MS protocol was also developed and optimized for the elemental analysis of a wide range of elements in polymeric filters containing atmospheric dust. A quantitative strategy based on internal and external standards allowed for a rapid determination of airborne trace elements in filters containing both contemporary African dust and local dust emissions. These distributions were used to qualitative and quantitative assess differences of composition and to establish provenance and fluxes to protected regional ecosystems such as coral reefs and national parks.

Advanced Techniques for Image Quality Assessment of Modern X-ray Computed Tomography Systems

X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.

A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.

Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.

The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).

First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.

Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.

Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.

The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.

To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.

The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.

The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.

Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.

The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.

In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.

Acoustic and Magnetic Techniques for the Isolation and Analysis of Cells in Microfluidic Platforms

Cancer comprises a collection of diseases, all of which begin with abnormal tissue growth from various stimuli, including (but not limited to): heredity, genetic mutation, exposure to harmful substances, radiation as well as poor dieting and lack of exercise. The early detection of cancer is vital to providing life-saving, therapeutic intervention. However, current methods for detection (e.g., tissue biopsy, endoscopy and medical imaging) often suffer from low patient compliance and an elevated risk of complications in elderly patients. As such, many are looking to “liquid biopsies” for clues into presence and status of cancer due to its minimal invasiveness and ability to provide rich information about the native tumor. In such liquid biopsies, peripheral blood is drawn from patients and is screened for key biomarkers, chiefly circulating tumor cells (CTCs). Capturing, enumerating and analyzing the genetic and metabolomic characteristics of these CTCs may hold the key for guiding doctors to better understand the source of cancer at an earlier stage for more efficacious disease management.

The isolation of CTCs from whole blood, however, remains a significant challenge due to their (i) low abundance, (ii) lack of a universal surface marker and (iii) epithelial-mesenchymal transition that down-regulates common surface markers (e.g., EpCAM), reducing their likelihood of detection via positive selection assays. These factors potentiate the need for an improved cell isolation strategy that can collect CTCs via both positive and negative selection modalities as to avoid the reliance on a single marker, or set of markers, for more accurate enumeration and diagnosis.

The technologies proposed herein offer a unique set of strategies to focus, sort and template cells in three independent microfluidic modules. The first module exploits ultrasonic standing waves and a class of elastomeric particles for the rapid and discriminate sequestration of cells. This type of cell handling holds promise not only in sorting, but also in the isolation of soluble markers from biofluids. The second module contains components to focus (i.e., arrange) cells via forces from acoustic standing waves and separate cells in a high throughput fashion via free-flow magnetophoresis. The third module uses a printed array of micromagnets to capture magnetically labeled cells into well-defined compartments, enabling on-chip staining and single cell analysis. These technologies can operate in standalone formats, or can be adapted to operate with established analytical technologies, such as flow cytometry. A key advantage of these innovations is their ability to process erythrocyte-lysed blood in a rapid (and thus high throughput) fashion. They can process fluids at a variety of concentrations and flow rates, target cells with various immunophenotypes and sort cells via positive (and potentially negative) selection. These technologies are chip-based, fabricated using standard clean room equipment, towards a disposable clinical tool. With further optimization in design and performance, these technologies might aid in the early detection, and potentially treatment, of cancer and various other physical ailments.

Development of Advanced Capillary Electrophoresis Techniques with UV and Mass Spectrometry Detection for Forensic, Pharmaceutical and Environmental Applications

Capillary electrophoresis (CE) is a modern analytical technique, which is electrokinetic separation generated by high voltage and taken place inside the small capillaries. In this dissertation, several advanced capillary electrophoresis methods are presented using different approaches of CE and UV and mass spectrometry are utilized as the detection methods. Capillary electrochromatography (CEC), as one of the CE modes, is a recent developed technique which is a hybrid of capillary electrophoresis and high performance liquid chromatography (HPLC). Capillary electrochromatography exhibits advantages of both techniques. In Chapter 2, monolithic capillary column are fabricated using in situ photoinitiation polymerization method. The column was then applied for the separation of six antidepressant compounds. Meanwhile, a simple chiral separation method is developed and presented in Chapter 3. Beta cycodextrin was utilized to achieve the goal of chiral separation. Not only twelve cathinone analytes were separated, but also isomers of several analytes were enantiomerically separated. To better understand the molecular information on the analytes, the TOF-MS system was coupled with the CE. A sheath liquid and a partial filling technique (PFT) were employed to reduce the contamination of MS ionization source. Accurate molecular information was obtained. It is necessary to propose, develop, and optimize new techniques that are suitable for trace-level analysis of samples in forensic, pharmaceutical, and environmental applications. Capillary electrophoresis (CE) was selected for this task, as it requires lower amounts of samples, it simplifies sample preparation, and it has the flexibility to perform separations of neutral and charged molecules as well as enantiomers. Overall, the study demonstrates the versatility of capillary electrophoresis methods in forensic, pharmaceutical, and environmental applications.

UTILIZATION OF GIS AND SPATIAL ANALYSIS TECHNIQUES IN ARTISANAL AND SMALL SCALE MINING TO LOCATE A CENTRALIZED PROCESSING CENTRE

One of the global phenomena with threats to environmental health and safety is artisanal mining. There are ambiguities in the manner in which an ore-processing facility operates which hinders the mining capacity of these miners in Ghana. These problems are reviewed on the basis of current socio-economic, health and safety, environmental, and use of rudimentary technologies which limits fair-trade deals to miners. This research sought to use an established data-driven, geographic information (GIS)-based system employing the spatial analysis approach for locating a centralized processing facility within the Wassa Amenfi-Prestea Mining Area (WAPMA) in the Western region of Ghana. A spatial analysis technique that utilizes ModelBuilder within the ArcGIS geoprocessing environment through suitability modeling will systematically and simultaneously analyze a geographical dataset of selected criteria. The spatial overlay analysis methodology and the multi-criteria decision analysis approach were selected to identify the most preferred locations to site a processing facility. For an optimal site selection, seven major criteria including proximity to settlements, water resources, artisanal mining sites, roads, railways, tectonic zones, and slopes were considered to establish a suitable location for a processing facility. Site characterizations and environmental considerations, incorporating identified constraints such as proximity to large scale mines, forest reserves and state lands to site an appropriate position were selected. The analysis was limited to criteria that were selected and relevant to the area under investigation. Saaty’s analytical hierarchy process was utilized to derive relative importance weights of the criteria and then a weighted linear combination technique was applied to combine the factors for determination of the degree of potential site suitability. The final map output indicates estimated potential sites identified for the establishment of a facility centre. The results obtained provide intuitive areas suitable for consideration

Analytical strategies for the early quality and safety assurance in the global feed chain. Approaches for nitrogen adulterants in soybean meal and mineral and transformer oils in vegetable oils.

In the past decade, several major food safety crises originated from problems with feed. Consequently, there is an urgent need for early detection of fraudulent adulteration and contamination in the feed chain. Strategies are presented for two specific cases, viz. adulterations of (i) soybean meal with melamine and other types of adulterants/contaminants and (ii) vegetable oils with mineral oil, transformer oil or other oils. These strategies comprise screening at the feed mill or port of entry with non-destructive spectroscopic methods (NIRS and Raman), followed by post-screening and confirmation in the laboratory with MS-based methods. The spectroscopic techniques are suitable for on-site and on-line applications. Currently they are suited to detect fraudulent adulteration at relatively high levels but not to detect low level contamination. The potential use of the strategies for non-targeted analysis is demonstrated.

Position paper on passive sampling techniques for the monitoring of contaminants in the aquatic environment - Achievements to date and perspectives

This paper, based on the outcome of discussions at a NORMAN Network-supported workshop in Lyon (France) in November 2014 aims to provide a common position of passive sampling community experts regarding concrete actions required to foster the use of passive sampling techniques in support of contaminant risk assessment and management and for routine monitoring of contaminants in aquatic systems. The brief roadmap presented here focusses on the identification of robust passive sampling methodology, technology that requires further development or that has yet to be developed, our current knowledge of the evaluation of uncertainties when calculating a freely dissolved concentration, the relationship between data from PS and that obtained through biomonitoring. A tiered approach to identifying areas of potential environmental quality standard (EQS) exceedances is also shown. Finally, we propose a list of recommended actions to improve the acceptance of passive sampling by policy-makers. These include the drafting of guidelines, quality assurance and control procedures, developing demonstration projects where biomonitoring and passive sampling are undertaken alongside, organising proficiency testing schemes and interlaboratory comparison and, finally, establishing passive sampler-based assessment criteria in relation to existing EQS.

Experimental and analytical investigation of refrigerant and lubricant migration

The off-cycle refrigerant mass migration has a direct influence on the on-cycle performance since compressor energy is necessary to redistribute the refrigerant mass. No studies, as of today, are available in the open literature which experimentally measured the lubricant migration within a refrigeration system during cycling or stop/start transients. Therefore, experimental procedures measuring the refrigerant and lubricant migration through the major components of a refrigeration system during stop/start transients were developed and implemented. Results identifying the underlying physics are presented. The refrigerant and lubricant migration of an R134a automotive A/C system-utilizing a fixed orifice tube, minichannel condenser, plate and fin evaporator, U-tube type accumulator and fixed displacement compressor-was measured across five sections divided by ball valves. Using the Quick-Closing Valve Technique (QCVT) combined with the Remove and Weigh Technique (RWT) using liquid nitrogen as the condensing agent resulted in a measurement uncertainty of 0.4 percent regarding the total refrigerant mass in the system. The determination of the lubricant mass distribution was achieved by employing three different techniques-Remove and Weigh, Mix and Sample, and Flushing. To employ the Mix and Sample Technique a device-called the Mix and Sample Device-was built. A method to separate the refrigerant and lubricant was developed with an accuracy-after separation-of 0.04 grams of refrigerant left in the lubricant. When applying the three techniques, the total amount of lubricant mass in the system was determined to within two percent. The combination of measurement results-infrared photography and high speed and real time videography-provide unprecedented insight into the mechanisms of refrigerant and lubricant migration during stop-start operation. During the compressor stop period, the primary refrigerant mass migration is caused by, and follows, the diminishing pressure difference across the expansion device. The secondary refrigerant migration is caused by a pressure gradient as a result of thermal nonequilibrium within the system and causes only vapor phase refrigerant migration. Lubricant migration is proportional to the refrigerant mass during the primary refrigerant mass migration. During the secondary refrigerant mass migration lubricant is not migrating. The start-up refrigerant mass migration is caused by an imbalance of the refrigerant mass flow rates across the compressor and expansion device. The higher compressor refrigerant mass flow rate was a result of the entrainment of foam into the U-tube of the accumulator. The lubricant mass migration during the start-up was not proportional to the refrigerant mass migration. The presence of water condensate on the evaporator affected the refrigerant mass migration during the compressor stop period. Caused by an evaporative cooling effect the evaporator held 56 percent of the total refrigerant mass in the system after three minutes of compressor stop time-compared to 25 percent when no water condensate was present on the evaporator coil. Foam entrainment led to a faster lubricant and refrigerant mass migration out of the accumulator than liquid entrainment through the hole at the bottom of the U-tube. The latter was observed for when water condensate was present on the evaporator coil because-as a result of the higher amount of refrigerant mass in the evaporator before start-up-the entrainment of foam into the U-tube of the accumulator ceased before the steady state refrigerant mass distribution was reached.

Development of new analytical procedures of isotope geochemistry by mass spectrometry. Application to the study of high-pressure metamorphic rocks from the Iberian Massif

319 p.

Advanced Analytical Microscopy at the Nanoscale: Applications in Wide Bandgap and Solid Oxide Fuel Cell Materials

The atomic-level structure and chemistry of materials ultimately dictate their observed macroscopic properties and behavior. As such, an intimate understanding of these characteristics allows for better materials engineering and improvements in the resulting devices. In our work, two material systems were investigated using advanced electron and ion microscopy techniques, relating the measured nanoscale traits to overall device performance. First, transmission electron microscopy and electron energy loss spectroscopy (TEM-EELS) were used to analyze interfacial states at the semiconductor/oxide interface in wide bandgap SiC microelectronics. This interface contains defects that significantly diminish SiC device performance, and their fundamental nature remains generally unresolved. The impacts of various microfabrication techniques were explored, examining both current commercial and next-generation processing strategies. In further investigations, machine learning techniques were applied to the EELS data, revealing previously hidden Si, C, and O bonding states at the interface, which help explain the origins of mobility enhancement in SiC devices. Finally, the impacts of SiC bias temperature stressing on the interfacial region were explored. In the second system, focused ion beam/scanning electron microscopy (FIB/SEM) was used to reconstruct 3D models of solid oxide fuel cell (SOFC) cathodes. Since the specific degradation mechanisms of SOFC cathodes are poorly understood, FIB/SEM and TEM were used to analyze and quantify changes in the microstructure during performance degradation. Novel strategies for microstructure calculation from FIB-nanotomography data were developed and applied to LSM-YSZ and LSCF-GDC composite cathodes, aged with environmental contaminants to promote degradation. In LSM-YSZ, migration of both La and Mn cations to the grain boundaries of YSZ was observed using TEM-EELS. Few substantial changes however, were observed in the overall microstructure of the cells, correlating with a lack of performance degradation induced by the H2O. Using similar strategies, a series of LSCF-GDC cathodes were analyzed, aged in H2O, CO2, and Cr-vapor environments. FIB/SEM observation revealed considerable formation of secondary phases within these cathodes, and quantifiable modifications of the microstructure. In particular, Cr-poisoning was observed to cause substantial byproduct formation, which was correlated with drastic reductions in cell performance.

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.

MATERIAL CHARACTERIZATION OF GILDING AND PAINTING TECHNIQUES OF A POST-BYZANTINE ICON

This study aims to identify the materials used in the production of a post-byzantine icon from the Museum of Évora’s collection. The icon, representing the “Emperor Constantine and his mother Helen holding the Holy Cross” was once dated as being from the 10th century. Throughout a multi-analytical approach, combining area exams with spectroscopic techniques, this study tried to confirm its actual chronology. The results obtained revealed that it is most likely an icon from the late 17th or 18th century.

New insight on the underdrawing of 16th Flemish-Portuguese easel paintings by combined surface analysis and microanalytical techniques

This paper focusses on the study of the underdrawings of 16th century easel paintings attributed to the workshop of the Portuguese-Flemish Master Frei Carlos. This investigation encompasses multidisciplinary research that relates the results of surface exams (infrared reflectography, standard light photography and infrared photography) with analytical investigations. The surface analysis of Frei Carlos’ underdrawings by infrared reflectography has shown heterogeneous work, revealing two different situations: (1) an abundant and expressive underdrawing, revealing a Flemish influence and (2) a simple and outlined underdrawing. This preliminary research raised an important question related to this Portuguese-Flemish workshop and to the analytical approach: Is the underdrawing's heterogeneity, as observed in the reflectograms, related to different artists or is this rather an effect that is produced due to the use of different materials in the underdrawing's execution? Consequently, if different materials were used, how can we have access to the hidden underdrawings? In order to understand the reasons for this dissemblance, chemical analysis of micro-samples collected in underdrawing areas and representing both situations were carried out by optical microscopy, micro Fourier transform infrared spectroscopy (μ-FTIR), scanning electron microscopy coupled with energy dispersive X-ray spectrometry (SEM-EDX) and micro-Raman spectroscopy (μ-Raman). Taking into account the different possibilities and practical and theoretical limitations of surface and punctual examinations in the study of easel painting underdrawings, the methodology of research was adjusted, sometimes resulting in a re-analysis of experimental results. This research shows the importance of combining multispectral surface exams and chemical analysis in the understanding of the artistic creative processes of 16th century easel paintings.