217 research outputs found
Droplet evaporation dynamics on surfaces
No full textDroplet evaporation governs many man-made and natural processes. Hence, it has been widely studied by many scientists over the past century. With the recent advancements in nanotechnology, many surfaces for two phase heat transfer have been developed including hydrophobic, biphilic and lubricantinfused surfaces. However, evaporation of droplets on these surfaces have not been explored in depth. Traditionally, evaporation on surfaces was characterized by observing the temporal size changes of a droplet. Yet, the transient nature coupled with the significant mass transfer governed gas dynamics occurring at the droplet three-phase contact line make the classical method crude. To accurately investigate evaporation dynamics on surfaces, we present a novel steady measurement technique. By utilizing a piezoelectric dispenser to feed microscale droplets (20 ≤ ≤ 400 μm) to a larger evaporating droplet at a prescribed frequency, we can create variable-sized droplets on any surface and study their evaporation rates by modulating the droplet addition frequency. Using our steady method, we studied evaporation of water and low surface tension fluids on surfaces including functional, biphilic, biconductive and lubricant-infused surfaces. We elucidated the physics governing the droplet evaporation process for each studied surface and working fluid. Furthermore, we developed an original high-speed focal-shift imaging technique to study droplet mobility on the interface. Our results not only shed light into the evaporation physics of droplets on different surfaces but also provides new avenues and strong experimental platforms for the study of phase change heat transfer processes that enable the decoupling of the intricate and length-scale dependent balance played by internal and external flows and binary-mixture dynamics, and the visualization of the interfacial dynamics.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2021-05-01The student, Ahmet Gunay, accepted the attached license on 2019-04-12 at 18:06.The student, Ahmet Gunay, submitted this Dissertation for approval on 2019-04-12 at 18:10.This Dissertation was approved for publication on 2019-04-15 at 13:19.DSpace SAF Submission Ingestion Package generated from Vireo submission #13602 on 2019-08-22 at 16:21:14Made available in DSpace on 2019-08-23T20:47:22Z (GMT). No. of bitstreams: 2
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Previous issue date: 2019-04-15Embargo set by: Seth Robbins for item 112310
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Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 112310
Lift date: 2021-08-23T20:48:32Z
Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemLimited Restriction Lifted for Item 112310 on 2021-08-24T09:15:20Z
Modeling, fabrication and optimization of optically transparent - thermally insulating silica aerogels for solar thermal applications
No full textSolar thermal energy conversion has the potential to reduce greenhouse gas emissions via the offset of fossil fuel burning power generation methods. By capturing the suns energy and using it to heat steam as part of a Rankine cycle, electrical energy can be renewably produced. Furthermore, solar thermal collectors have high potential for domestic heating when deployed at the rooftop scale, reducing fossil fuel consumption used for home heating needs. The efficiency of these solar applications is highly dependent on the ability of the collecting device to absorb the incoming solar energy, and minimize thermal losses to the environment. Current techniques utilize vacuum tubes to eliminate convective losses, in combination with selective surfaces (high absorptivity in the solar spectrum, and low emissivity in the infra-red (IR)) to minimize thermal re-radiation. Here, we present an alternate approach that operates at atmospheric pressures with simple, black, absorbing surfaces. An Optically Transparent Thermally Insulating (OTTI) layer was assumed to be coated on the back side of the black, broadband absorber. This absorber was assumed to have perfect transparency and opacity in the solar spectrum and Infra-Red (IR), respectively. In order to provide a deeper understanding of the link between the optimum OTTI layer material properties and the overall solar thermal efficiency, we developed a coupled radiative-conduction heat transfer (HT) model used to predict how the investigated OTTI layers will behave when they are used as solar thermal absorbers. The optimum properties that were obtain were then incorporated into the HT model to study the thermal performance under various optical concentrations (1 – 20 suns), solar thermal absorber temperatures (20 – 200°C), and external heat transfer coefficients (10 – 100 W/m2K). The results showed potential solar thermal conversion efficiencies of ≈90% can be attained by utilizing OTTI layers as insulators in the solar thermal absorbers. To check if a material to have the assumed material properties can be fabricated, silica aerogels were procured, synthesized and characterized. Due to their naturally high and low transmissivities in the solar and IR spectrums, respectively, silica based aerogels coated on the back with highly absorbing (black) surfaces offer a potential solution to create simple and inexpensive solar thermal absorbers. To test our hypothesis, we fabricated tetramethyl orthosilicate (TMOS) and tetraethyl orthosilicate (TEOS) based silica aerogels. The formed gels were aged for 3 weeks and dried using a carbon dioxide supercritical point dryer. The obtained aerogel optical properties were characterized using ultraviolet-visible (UV-Vis) and Fourier Transform Infrared (FTIR) spectroscopy, showing spectrally averaged (0 < λ < 2.7 µm) transmissions of ≈87% for a sample thickness of 4mm. To minimize the effect the O-H group transmission reduction occurring in the solar spectrum, we modified the baseline aerogels to be hydrophobic with a silane treatment to shield the exposed hydroxyl groups on the surface. Hydrophobic modification resulted in an increase of the spectrally averaged transmissions to ≈ 94%. This study sheds light on the applicability of silica aerogels on black coatings as ideal solar thermal absorbers and offers insights into new avenues for performance improvement of solar thermal energy systems.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2018-05-01The student, Ahmet Gunay, accepted the attached license on 2016-04-25 at 15:18.The student, Ahmet Gunay, submitted this Thesis for approval on 2016-04-25 at 15:31.This Thesis was approved for publication on 2016-04-27 at 09:14.DSpace SAF Submission Ingestion Package generated from Vireo submission #9484 on 2016-07-07 at 13:50:50Made available in DSpace on 2016-07-07T20:28:01Z (GMT). No. of bitstreams: 3
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Previous issue date: 2016-04-27Embargo set by: Seth Robbins for item 93178
Lift date: 2018-07-07T20:28:14Z
Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 93178
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A fast regularized least-squares method for retinal vascular oxygen tension estimation using a phosphorescence lifetime imaging model
No full textClosed Form Solution and Statistical Performance Analyses for Regularized Least Squares Estimation of Retinal Oxygen Tension
No full textMicroRNA target recognition from compositional features of aligned microRNA-mRNA duplexes
No full textThe discovery of microRNAs (miRNAs), small
non-coding RNAs that regulate gene expression at
the post-transcriptional level, has led to a shift in
our understanding of the complexity in gene
regulatory networks. One key question in
understanding the effect of an individual miRNA is
to identify its potential targets in a local or
genome-wide regulation process. We define here a
novel algorithm for computational prediction of
miRNA target genes using solely the sequence
information for mature miRNA and potential
target mRNAs. Our method considers the aligned
miRNA-mRNA duplex as a new sequence and
extracts compositional features from newly
constructed sequence to be fed into a Naive Bayes
Classifier. A rigorous analysis in a common
benchmark set reveals that, in terms of prediction
accuracy, the new algorithm outperforms most of
the available methods, while being competitive
with more complex and relatively inefficient
methods
Simultaneous modeling of enzyme production and biomass growth in recombinant Escherichia coli using artificial neural networks
No full textIn this work, the biomass growth and the TaqI endonuclease production by recombinant Esherichia coli were studied using artificial neural networks. The effects of the medium components on biomass growth and enzyme yield were modeled by various networks. After the most successful networks were statistically determined, they were used to extract additional knowledge such as the possible correlations between the biomass growth and the enzyme yield, and the relative significance of the medium components. It was found that the change of the biomass growth and the enzyme yield with the change of KH2PO4 concentration was strongly correlated with an R-value of -0.954. Some mild correlations were also observed for the other components. It was also found that the relative significances of the medium components were in the same order for both outputs: (NH4)(2)HPO4 Concentration was determined as the most important parameter followed by the glucose, KH2PO4 and MgSO4 concentrations. (C) 2008 Elsevier B.V. All rights reserved
Developing global reaction rate model for CO oxidation over Au catalysts from past data in literature using artificial neural networks
No full textIn this work, the literature for CO oxidation kinetics over Au based catalysts was analyzed using artificial neural networks to test the possibility of developing global reaction rate models representing the entire literature. A database was constructed using the data obtained from nineteen papers published between the years 1997 and 2011; then, the reaction rate was modeled as a function of catalyst preparation and operational variables by using neural networks. Next, global reaction rate equations in the form of power law were developed for each support type by the help of the neural network model, and the order of reaction with respect to each reactant and the parameters of Arrhenius relation were estimated. These power law models were successfully validated by using the information reported in the literature; hence, it was concluded that they can be used for the initial estimation of the reaction rates in the absence of more specific rate equations. (C) 2013 Elsevier B.V. All rights reserved.Scientific and Technical Research Council of Turkey [109M207]; Bogazici University [12A05M1]The financial supports provided by the Scientific and Technical Research Council of Turkey through Project 109M207 and Bogazici University Research Fund Project 12A05M1 are gratefully acknowledged
Recent advances in knowledge discovery for heterogeneous catalysis using machine learning
No full textThe use of machine learning (ML) in catalysis has been significantly increased in recent years due to the astonishing developments in data processing technologies and the accumulation of a large amount of data in published literature and databases. The data generated in house or extracted from external sources have been analyzed using various ML techniques to see patterns, develop models for prediction and deduce heuristic rules for the future. This communication aims to review the works involving knowledge discovery in catalysis using ML techniques; the basic principles, common tools and implementation of ML in catalysis are also summarized
Dark matter and dark energy solutions using by observational evidence
No full text33rd International Physics Congress of the Turkish-Physical-Society (TPS) -- SEP 06-10, 2017 -- Bodrum, TURKEYIn this study, we examine dark energy, dark matter and baryonic matter in FRW by observational evidences. Also we study our model by considering possible dark energy candidates such as Phantom energy. Obtained solutions show that dark energy candidate may be phantom energy depending on accuracy of today's observation.Turkish Phys So
CREATION OF THE GEOINFORMATION MAP OF HISTORICAL AND NATURAL MONUMENTS IN THE TERRITORY OF THE NORTHEAST SLOPE OF CAUCASUS WITHIN THE AZERBAIJAN TERRITORY
No full textIn this report the author describes the geographical information system of historical monuments and natural conditions aimed at promotion of innovative planning of the tourist sector of the economy
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