175 research outputs found
Heat transfer through a condensate droplet on hydrophobic and nanostructured superhydrophobic surfaces
Get PDFUnderstanding the fundamental mechanisms governing vapor condensation on non-wetting surfaces is crucial to a wide range of energy and water applications. In this thesis, we reconcile classical droplet growth modeling barriers by utilizing two-dimensional axisymmetric numerical simulations to study individual droplet heat transfer on non-wetting surfaces (90° < θ_a < 170°). Incorporation of an appropriate convective boundary condition at the liquid vapor interface reveals that the majority of heat transfer occurs at the three phase contact line, where the local heat flux can be up to 4 orders of magnitude higher than at the droplet top. Droplet distribution theory is incorporated to show that previous modeling approaches under predict the overall heat transfer by as much as 300% for dropwise and jumping-droplet condensation. To verify our simulation results, we study condensed water droplet growth using optical and ESEM microscopy on bi-philic samples consisting of hydrophobic and nanostructured superhydrophobic regions, showing excellent agreement with the simulations for both constant base area and constant contact angle growth regimes. Our results demonstrate the importance of resolving local heat transfer effects for the fundamental understanding and high fidelity modeling of phase change heat transfer on non-wetting surfaces.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2018-05-01The student, Shreyas Chavan, accepted the attached license on 2016-04-25 at 17:05.The student, Shreyas Chavan, submitted this Thesis for approval on 2016-04-25 at 17:16.This Thesis was approved for publication on 2016-04-27 at 09:11.DSpace SAF Submission Ingestion Package generated from Vireo submission #9489 on 2016-07-07 at 13:50:52Made available in DSpace on 2016-07-07T20:35:15Z (GMT). No. of bitstreams: 2
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Characterization of surface sulfate species on mixed metal oxide catalysts: insights from spectroscopic studies
No full textSolid acid and super acid catalysts are promising alternatives for very important reactions usually catalyzed industrially by homogeneous acid reactions. Sulfated metal oxides are among many examples of solid super acids which work well for acid catalyzed reactions. These catalysts have applications in isomerization, alkylation, acylation and oxidative dehydrogenation reaction. A characteristic example encompasses products from tert-butylation of phenol which have tremendous importance in chemical, petrochemical as well as pharmaceutical industry. In spite of significant amount of work devoted in this area, the catalysts being commercially used have low yields. Hence we channel our efforts in enhancing the productivity of the alkylation of phenol reaction by using sulfated metal oxides as it has shown in our preliminary work improved catalytic activity. In this work, we focus on the preparation and characterization of sulfated mixed metal oxides. Specifically, sulfated-Tin-Zirconium oxides (STZ) are produced by coprecipitation method using hydrated Zirconium Oxychloride(ZrOCl2.8H2O) and Tin Chloride(SnCl4.5H2O) as metal precursors and ammonia as the precipitating agent. Different proportions of hydrous tin and zirconium oxides (molar ratios of 1:10,1:1 and 10:1) are synthesized. Sulfation of the prepared hydrous oxides is performed using wet impregnation method with 1M and 0.5M sulfuric acid solution. Calcination of the prepared sulfate mixed hydroxides follows at 600oC. Our work focuses on the incorporation of vibrational spectroscopic teqniques at the individual steps of the synthesis procedure. To that end, first we utilize Raman spectroscopy to study the speciation of the metal salts precursors in water and at various pH range. The broad spectral envelope is assigned to specific vibational modes of the various species. XRD analysis is done to understand the crystalline phases of the catalyst. Additionally, we study the temperature evolution of the deposited sulfated species by means of in-situ Attenuated Total Reflection (ATR-FTIR) and in-situ Raman spectroscopy using high temperature reaction chamber. The results show that the molecular structure of the surface sulfate species varies significantly with increasing temperature as underscored by the changes of S=O vibrational bands. It was found that the sulfated species getting attached to the catalyst support can majorly be present as bidentate, tridentate and polymeric species and are a function of the temperature as well as the Sn:Zr ratio. Tuning the molecular structure of the sulfated species could potentially alter the acidic properties of the catalysts as indicated by the Lewis/Bronsted acid sites. Lastly, it was found that the crystalline phases of the the regenerated catalyst remain unaffected along with the sulfated groups.M.S.Includes bibliographical referencesby Shreyas Achary
IDENTIFICATION OF NOVEL SLEEP RELATED GENES FROM LARGE SCALE PHENOTYPING EXPERIMENTS IN MICE
Get PDFHumans spend a third of their lives sleeping but very little is known about the physiological and genetic mechanisms controlling sleep. Increased data from sleep phenotyping studies in mouse and other species, genetic crosses, and gene expression databases can all help improve our understanding of the process. Here, we present analysis of our own sleep data from the large-scale phenotyping program at The Jackson Laboratory (JAX), to identify the best gene candidates and phenotype predictors for influencing sleep traits.
The original knockout mouse project (KOMP) was a worldwide collaborative effort to produce embryonic stem (ES) cell lines with one of mouse’s 21,000 protein coding genes knocked out. The objective of KOMP2 is to phenotype as many as of these lines as feasible, with each mouse studied over a ten-week period (www.mousephenotype.org). The phenotyping for sleep behavior is done using our non-invasive Piezo system for mouse activity monitoring. Thus far, sleep behavior has been recorded in more than 6000 mice representing 343 knockout lines and nearly 2000 control mice. Control and KO mice have been compared using multivariate statistical approaches to identify genes that exhibit significant effects on sleep variables from Piezo data. Using these statistical approaches, significant genes affecting sleep have been identified. Genes affecting sleep in a specific sex and that specifically affect sleep during daytime and/or night have also been identified and reported.
The KOMP2 consists of a broad-based phenotyping pipeline that consists of collection of physiological and biochemical parameters through a variety of assays. Mice enter the pipeline at 4 weeks of age and leave at 18 weeks. Currently, the IMPC (International Mouse Phenotyping Consortium) database consists of more than 33 million observations. Our final dataset prepared by extracting biological sample data for whom sleep recordings are available consists of nearly 1.5 million observations from multitude of phenotyping assays. Through big data analytics and sophisticated machine learning approaches, we have been able to identify predictor phenotypes that affect sleep in mice. The phenotypes thus identified can play a key role in developing our understanding of mechanism of sleep regulation
A Framework for Implementing Predictive Analytics in the High Frequency Trading Realm
No full textIn this paper, we explore a framework for applying machine learning techniques at the high frequency trading level. In particular, we explore how machine learning algorithms such as recurrent neural networks and elastic-nets can be useful in the high frequency domain for predicting bid and ask movements. Specifically, we focus on analyzing the performance of such models during a high volatility scenario, namely the flash crash of 2010 - we find that elastic nets can be powerful for predicting the volatile price movements that begin to occur soon after the start of a flash crash. We also discover specific features which can warn us about upcoming volatile price movements. Finally, we propose and test a prototype policy for setting off alarms before potential flash crashes, and also discuss the limitations and potential extensions of our methodology
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Synthesis of Hybrid Inorganic-Organic Microparticles
No full textThe self-assembly of isotropic and anisotropic colloidal particles into higher-ordered structures has been of great interest recently due to the promise of creating metamaterials with novel macroscopic properties. The physicochemical properties of these metamaterials can be tailored to achieve composites with tunable functionalities. The formation of these metamaterials can be used as a pathway to emulating advanced biological systems. In particular, synthetically mimicking the surface of a moth’s eye, which consists of arrays of ellipsoidal protuberances, can be used as a strategy for fabricating antireflective coatings. To enable this technology, it is necessary to design a synthesis scheme that produces micron-sized composite particles with tunable refractive index. In the future, the resulting composite microparticles can then undergo geometric and spatial modifications to form self-assemblies that have unique macroscopic material properties. This research work delineates a strategy of developing microparticles with a hybrid configuration that constitutes an inorganic and an organic part. The inorganic part comprises ~30 nm diameter titania (TiO2) nanoparticles, which are embedded within an organic polymer particle comprised of diethyl methylene malonate polymer [p(DEMM)]. Anionic polymerization is modified to controllably incorporate TiO2 nanoparticles into the polymer matrix. A design of experiments was identified and carried out to identify the major process variables that influence the final particle size. In particular, since DEMM polymerization may be initiated entirely by the presence of hydroxyl anions, pH was found to control the final overall particle diameter between 300 nm and 1 micrometer. The overall inorganic particle loading can be readily modified and is confirmed by thermogravimetric analysis, allowing for the desired macroscopic refractive index to be controlled. Light scattering, scanning electron microscopy and zeta potential analysis reveals that the colloidal stability of the hybrid microparticles is dependent on the ligand coating the inorganic constituent. In addition, this synthetic scheme is applied to different inorganic constituents that have interesting functionalities, such as fluorescent CdTe quantum dots, in order to show the methods versatility method to produce composite particles for a wide spectrum of applications. These initial investigations provide a the synthetic groundwork to evaluating the coating properties of the microparticles and their self-assembly into novel materials in the future.Master of Science in Chemical Engineering (MSChE
Phase change phenomena on water repelling and biphilic surfaces
Get PDFThis Dissertation was approved for publication on 2019-04-10 at 09:54.Water-repelling surfaces have been studied for many decades. Hydrophobic and superhydrophobic surfaces are beneficial in phase change heat transfer applications, specifically during condensation because of the enhanced heat transfer and during freezing because of the anti-freezing properties. The current study is focused on enhanced phase change phenomena on superhydrophobic and biphilic surfaces. Hydrophobic surfaces that enable dropwise condensation exhibit 5-10X higher heat transfer. Coalescence induced droplet jumping on superhydrophobic surfaces further increases the heat transfer by 30%. Here, biphilic surfaces consisting of hydrophilic spots on a superhydrophobic background are studied for enhanced condensation. Water droplets nucleating at the hydrophilic spots grow to sizes defined by the biphilic geometry, followed by coalescence and departure. A high fidelity model that captures departure dynamics during droplet jumping on biphilic surfaces and predict the overall condensation heat transfer has been developed. By controlling the spatial geometry and length scale of the hydrophilic spots, enhanced (10X) jumping-droplet condensation heat transfer is obtained.
In terms of freezing and frost formation, understanding the mechanisms of frost formation is essential to a variety of Heating, Ventilating, Air Conditioning and Refrigeration (HVAC&R) applications. When water vapor in the ambient condenses on a chilled substrate in the form of liquid water and then freezes, it is known as condensation frosting. The dominant mechanism governing the spread of condensation frosting is inter-droplet ice bridge frost wave propagation. When a subcooled condensate water droplet freezes on a hydrophobic or superhydrophobic surface, neighboring droplets still in the liquid phase begin to evaporate. The evaporated water molecules deposit on the frozen droplet and initiate the growth of ice bridges directed toward the water droplets being depleted. Neighboring liquid droplets freeze as soon as the ice bridge connects. In this study, the significance of individual droplet freezing on frost wave propagation is studied. 10X slower frost wave propagation speeds on superhydrophobic surfaces are observed. Furthermore, at larger length scales, during bulk freezing of water, it has been shown that superhydrophobic surfaces offer no delay in freezing.
Although frosting delay has been shown with superhydrophobic surfaces, complete elimination of frosting has not been achieved. Given enough time, frosting will initiate and spread to cover the entire surface. In the HVAC&R sectors, the most common approach to remove frost from a surface (defrost) is to reverse the system cycle direction and heat the working fluid. However, water retention on the heat exchanger surface during defrosting decreases the long term heat transfer performance. In this study, the defrosting behavior of superhydrophobic and biphilic surfaces comprising of spatially distinct superhydrophobic and hydrophilic domains is used to accelerate defrosting. During defrosting, biphilic surfaces are shown to exhibit enhanced surface cleaning with no water retention. Furthermore, an ultra-efficient method to defrost a surface covered with ice/frost by focusing energy at the substrate-ice interface is studied. To remove ice/frost efficiently, only the interfacial layer adhering the ice/frost to the solid surface is melted by using a localized ‘pulse’ of heat, allowing gravity or gas shear in conjunction with the ultra-thin lubricating melt water layer to remove the ice/frost. A high fidelity numerical model is developed to simulate pulse defrosting. This work not only provides a fundamental understanding of phase change processes on superhydrophobic and biphilic surfaces, but also elucidates its applications for a plethora of energy industries.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2021-05-01The student, Shreyas Chavan, accepted the attached license on 2019-04-09 at 16:13.The student, Shreyas Chavan, submitted this Dissertation for approval on 2019-04-09 at 16:16.DSpace SAF Submission Ingestion Package generated from Vireo submission #13540 on 2019-08-22 at 16:20:55Made available in DSpace on 2019-08-23T20:44:41Z (GMT). No. of bitstreams: 2
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Identifying candidate genes for variation in sleep-related quantitative traits
Get PDFBackground
Humans spend approximately one third of their lives sleeping, but compared with other biological processes, most of the molecular and genetic aspects of sleep have not been elucidated. A non-existent gene ontology and lack of a dedicated database containing a comprehensive list of sleep-related genes and their function presents a hurdle for sleep researchers. Materials and methods
Using a two-pronged approach to solve this problem, publicly available microarray data from NCBI GEO (National Center for Biotechnology Information – Gene Expression Omnibus) database was used to develop a list of sleep-related genes for traits of interest. The data were analyzed using R Bioconductor and custom Perl scripts. The genes from this list were then matched with the genes in QTL (Quantitative Trait Loci) for the trait. The genes within the QTL chromosomal region matching any in the list of sleep-related genes were considered as potential candidates for causing variations in the quantitative trait. Results
Here we present the results for our study conducted for sleep deprivation (SD) using this approach. 227 genes were identified which showed significant differential expression after 3, 6, 9 and 12 hours of sleep deprivation in three mouse strains. We were able to identify 4 candidate genes in Dps1 QTL, 2 in Dps2, and 9 genes in Dps3. Dps loci are the QTL associated with delta power in slow wave sleep. The list also contains Homer1 which has already been established as a molecular correlate of sleep loss. The advantage with this approach is that it provides more information and cross support than a simple list of sleep-related candidate genes. The association of information about genes with their function and role in sleep can help in forming sleep-specific gene ontologies, which would be useful for sleep researchers
Nanomaterial-based approaches for advancing neurotechnologies
No full textThe human brain is a phenomenal ‘organic machine’, comprised of an intricate network of tens of billions of neurons dispersed in a milieu of chemical and biochemical constituents. While remarkable advances have been made to better understand how the brain works and how to overcome neural deficits resulting from degenerative diseases, traumatic injuries and cancer, the inherent complexity makes it difficult to fully comprehend, modulate and repair. This is partly due to challenges in developing advanced tools to effectively probe and interface with neural cells and tissue. Yet, given that the biomolecular interactions and chemical communication in the brain occur at the nanoscale, there is great potential in leveraging advances in nanoscience and nanotechnology to address pertinent challenges in neuroscience. This doctoral dissertation will focus on the rational design and characterization of nanomaterial-based approaches for applications in neural regeneration, neural drug delivery and neural modulation. The reproducible control of chemical reactions and advanced nanochemistry can enable the generation of a variety of nanomaterials and nanostructures with well-defined compositions, shapes and properties. The first portion of this dissertation describes the control of neural cell fate by the delivery of chemical factors through the soluble microenvironment. This was achieved by the synthesis of a multifunctional polymeric nanocarrier, designed to facilitate the simultaneous delivery of distinct functional factors in the form of small molecules and RNA-based biomolecules. Moving from the soluble microenvironment in which cells are immersed to the underlying substrate, cells can sense and consequently respond to the physical microenvironment in which they reside. The next part of the dissertation describes the control of neural cell shape and behavior by modifying the surface chemistry on two-dimensional surfaces. These surfaces, consisting of immobilized extracellular matrix proteins and/or nanomaterials, were observed to direct neuronal differentiation and extension. The final portion of the dissertation describes how the abovementioned approaches were further advanced to generate three-dimensional nano-scaffolds. By introducing specialized synthetic nanomaterials into biomaterial scaffolds, these multifunctional hybrid nano-scaffolds were utilized to selectively guide neural cell fate, to achieve remotely-controlled drug release and to modulate neural activity. Overall, nanomaterial-based approaches offer the precise physical and chemical control to design tools suitable for advancing neuroscience research.Ph.D.Includes bibliographical referencesby Shreyas Sha
Data from: Immunoreactive peptide maps of SARS-CoV-2
No full textSerodiagnosis of SARS-CoV-2 infection is impeded by immunological cross-reactivity among the human coronaviruses (HCoVs) SARS-CoV-2, SARS-CoV-1, MERS-CoV, OC43, 229E, HKU1, and NL63. To study humoral immune responses specific to SARS-CoV-2, it is imperative to identify peptides that may enable discrimination between exposure to SARS-CoV-2 and other HCoVs. We used a high-density peptide microarray and plasma samples collected at two time points from 50 subjects with SARS-CoV-2 infection confirmed by qPCR, samples collected in 2004-2005 from 11 subjects with IgG antibodies to SARS-CoV-1, 11 subjects with IgG antibodies to other seasonal human coronaviruses (HCoV), and 10 healthy human subjects. The peptide microarrays consist of ~172000 12-mer peptide probes spanning whole viral genomes. This dataset consists of reactivity values for individual peptides from all 132 plasma samples for both IgG and IgM. Also made available is the correspondence key that provides a reference for all viral genome sequences that a peptide originated from.Aggregate data for all samples:
In peptide microarray, text files containing peptide probe reactivity values for individual samples are generated as tab-delimited text files. Data from these files was aggregated into CSV files for IgG and IgM. Each row contains probe sequences and their unique identifiers that can be matched with their reference in correspondence key for its source, followed by reactivity values for all 132 samples.
IgG_aggregate_file_covid_pub.csv
IgM_aggregate_file_covid_pub.csv
Correspondence key and header map:
The cross-reactivity among human coronaviruses is because of the highly conserved nature of their genomes. Because of this, it is imperative to map 12-mer peptides to their source for proper epitope reassembly. Correspondence key file containing probes sequences, their unique identifiers and the source makes it possible to detect the longest epitope sequence. The header map file acts as an additional layer of information with details of protein names and their locations in the genome.
NTX-127_all_11_files_correspondence_key.txt
Corona_chip_header_map_no_seq.txt
Epitope re-assembly
The software for epitope re-assembly is an R script that takes either IgG or IgM as an argument and makes separate epitope files for all coronaviruses.
epitope_reassembler.REach peptide array is divided in 12 subarrays, with each subarray comprising ~172,000 twelve-amino acid (aa) nonredundant linear peptides that tile the proteomes of known HCoVs with 11 amino acid overlap. A total of 132 plasma samples were tested using eleven 12-plex peptide arrays. If there are three or more continuous reactive peptides (with reactivity values above the threshold of 10000) in samples, then those peptide sequences are reassembled to constitute an epitope. The length of an epitope depends on the number of such continuous reactive peptides
Effects of tumor size and location on survival in upper tract urothelial carcinoma after nephroureterectomy
Get PDFIntroduction: Upper Tract Urothelial Carcinoma (UTUC) is a rare disease with few prognostic determinants. We sought to evaluate the impact of tumor size and location on patient survival following nephroureterectomy for UTUC.
Materials and Methods: Data on 8284 patients treated with radical nephroureterectomy for UTUC in the United States between 1998 and 2011 were analyzed from the National Cancer Data Base. Univariable survivorship curves were generated based on pT stage, pN stage, grade, tumor size, and tumor site (renal pelvis vs. ureter). A Cox proportional hazards model was used to evaluate the effect of age, comorbidity, T stage, lymph node involvement, tumor site, and tumor size on survival.
Results: The median follow-up time was 46 months. A majority of the patients were male (55.4%) with a tumor size of ≥3.5 cm (52.0%) and pT stage <T2 (47.8%). The overall 5 years survival overall survival (OS) for the entire cohort was 51.6%. When stratified by tumor size <3.5 cm or ≥3.5 cm the 5-year OS was 45.9% and 58.5%, respectively. On multivariable analysis controlling for age, Charlson comorbidity index, grade, and tumor stage, tumor size ≥3.5 cm was independently predictive of worse OS (odds ratio: 1.13 [95% confidence interval: 1.02–1.26], P = 0.023).
Conclusions: Using the largest series of patients with UTUC undergoing nephroureterectomy, we demonstrated a worse survival in patients with larger tumor sizes (≥3.5 cm) but no difference in survival based on tumor location while controlling for other pathologic characteristics. Incorporation of tumor size into perioperative risk modeling may help with patient stratification and provide further prognostic information for patient counseling
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