Experimental and computational analysis of bubble generation combining oscillating fields and microfluidics

Microbubbles generated by microfluidic techniques have gained substantial interest in various fields such as food engineering, biosensors and the biomedical field. Recently, T-Junction geometries have been utilised for this purpose due to the exquisite control they offer over the processing parameters. However, this only relies on pressure driven flows; therefore bubble size reduction is limited, especially for very viscous solutions. The idea of combining microfluidics with electrohydrodynamics has recently been investigated using DC fields, however corona discharge was recorded at very high voltages with detrimental effects on the bubble size and stability. In order to overcome the aforementioned limitation, a novel set-up to superimpose an AC oscillation on a DC field is presented in this work with the aim of introducing additional parameters such as frequency, AC voltage and waveform type to further control bubble size, capitalising on well documented bubble resonance phenomena and properties. Firstly, the effect of applied AC voltage magnitude and the applied frequency were investigated. This was followed by investigating the effect of the mixing region and electric field strength on the microbubble diameter. A capillary embedded T-junction microfluidic device fitted with a stainless steel capillary was utilised for microbubble formation. A numerical model of the T-Junction was developed using a computational fluid dynamics-based multiphysics technique, combining the solution of transport equations for mass and momentum (Navier-Stokes Equations), a Volume of Fluid algorithm for tracking the gas-liquid interfaces, and a Maxwell Equations solver, all in a coupled manner. Simulation results were attained for the formation of the microbubbles with particular focus on the flow fields along the detachment of the emerging bubble. Experimental results indicated that frequencies between 2-10 kHz have a pronounced effect on the bubble size, whereas elevated AC voltages of 3-4 〖kV〗_(P-P) promoted bubble elongation and growth. It was observed that reducing the mixing region gap to 100 μm facilitated the formation of smaller bubbles due to the reduction of surface area, which increases the shear stresses experienced at the junction. Reducing the tip-to-collector distance causes a further reduction in the bubble size due to an increase in the electric field strength. Computational simulations suggest that there is a uniform velocity field distribution along the bubble upon application of a superimposed field. Microbubble detachment is facilitated by the recirculation of the dispersed phase. A decrease in velocity was observed upstream as the gas column occupies the junction suggesting the build-up in pressure, which corresponds to the widely reported ‘squeezing regime’ before the emerging bubble breaks off from the main stream. The novel set-up described in this work provides a viable processing methodology for preparing microbubbles that offers superior control and precision. In conjunction with optimised processing parameters, microbubbles of specific sizes can be generated to suit specific industrial applications

Novel preparation of monodisperse microbubbles by integrating oscillating electric fields with microfluidics

Microbubbles generated by microfluidic techniques have gained substantial interest in various industries such as cosmetics, food engineering, and the biomedical field. The microfluidic T-junction provides exquisite control over processing parameters, however, it relies on pressure driven flows only; therefore, bubble size variation is limited especially for viscous solutions. A novel set-up to superimpose an alternating current (AC) oscillation onto a direct current (DC) field is invented in this work, capitalising on the possibility to excite bubble resonance phenomenon and properties, and introducing relevant parameters such as frequency, AC voltage, and waveform to further control bubble size. A capillary embedded T-junction microfluidic device fitted with a stainless-steel capillary was utilised for microbubble formation. Furthermore, a numerical model of the T-junction was developed by integrating the volume of fluid (VOF) method with the electric module; simulation results were attained for the formation of the microbubbles with a particular focus on the flow fields along the detachment of the emerging bubble. Two main types of experiments were conducted in this framework: the first was to test the effect of applied AC voltage magnitude and the second was to vary the applied frequency. Experimental results indicated that higher frequencies have a pronounced effect on the bubble diameter within the 100 Hz and 2.2 kHz range, whereas elevated AC voltages tend to promote bubble elongation and growth. Computational results suggest there is a uniform velocity field distribution along the bubble upon application of a superimposed field and that microbubble detachment is facilitated by the recirculation of the dispersed phase. Furthermore, an ideal range of parameters exists to tailor monodisperse bubble size for specific applications

Water chemistry of the Illinois Waterway

Cover title.Includes bibliographical references (p. 23)."ISWS/CIR-147/81.

Practical considerations for assessing the waste assimilative capacity of Illinois streams

Cover title.Includes bibliographical references

A Remotely Operable Facility for Fabrication of Fuel Pins for test Irradiation

AbstractA laboratory scale facility has been set up for fabrication of test fuel pins through sol-gel route for irradiation in FBTR, Kalpakkam. The facility is a train of glove boxes fitted with master slave manipulators for carrying out various operations involved in the fuel fabricat ion process. The paper describes the design features of the equipment and mechanisms for automation, developed for microsphere production and other processes. The design features include control system and vision systems for man- machine interface

Mechanistic insights to drive catalytic hydrogenation of formamide intermediates to methanol via deaminative hydrogenation

Amine-promoted hydrogenation of CO2 to methanol typically proceeds via a formamide intermediate when amines are used as additives or if the hydrogenation is performed in carbon capture solvents. The catalysts used for the hydrogenation of the formamide intermediate dictate the selectivity of the products formed: 1) Deoxygenative hydrogenation (C–O bond cleavage) resulting in N-methylation of amine and deactivation of the solvent, 2) Deaminative hydrogenation (C–N bond cleavage) resulting in formation of methanol and regeneration of the solvent. To date, catalytic reductions of CO2 with amine promoters suffer from poor selectively for methanol which we attribute to the limiting formamide intermediate, though to date, the conditions that favor C–N cleavage have yet to be fully understood. To better understand the reactivity of the formamide intermediates, a range of heterogenous catalysts were used to study the hydrogenation of formamide. Well-known gas phase CO2 hydrogenation catalysts catalyze the hydrogenation of formamide to N-methyl product via C–O bond cleavage. However, the selectivity can be readily shifted to selective C–N bond cleavage by addition of an additive with sufficient basicity for both homogenous and heterogeneous catalytic systems. The base additive shifts the selectivity by deprotonating a hemiaminal intermediate formed in situ during the formamide hydrogenation. This prevents dehydration process leading to N-methylated product, which is a key capture solvent deactivation pathway that hinders amine use in carbon capture, utilization, and storage (CCUS). The findings from this study provide a roadmap on how to improve the selectivity of known heterogenous catalysts, enabling catalytic reduction of captured CO2 to methanol

Process simulation and analysis of carbon capture with an aqueous mixture of ionic liquid and monoethanolamine solvent

This study investigated the prospect of using aqueous mixture of 1-butylpyridinium tetrafluoroborate ([Bpy][BF4]) ionic liquid (IL) and monoethanolamine (MEA) as solvent in post-combustion CO2 capture (PCC) process. This is done by analysis of the process through modelling and simulation. In literature, reported PCC models with a mixture of IL and MEA solvent were developed using equilibrium-based mass transfer approach. In contrast, the model in this study is developed using rate-based mass transfer approach in Aspen Plus®. From the results, the mixed aqueous solvent with 5–30 wt% IL and 30 wt% MEA showed 7%–9% and 12%–27% less specific regeneration energy and solvent circulation rate respectively compared to commonly used 30 wt% MEA solvent. It is concluded that the IL concentration (wt%) in the solvent blend have significant impact on specific regeneration energy and solvent circulation rate. This study is a starting point for further research on technical and economic analysis of PCC process with aqueous blend of IL and MEA as solvent

Marketing and public policy: Transformative research in developing markets

Developing markets are a challenge for researchers who study them and for governments, business leaders, and citizens who strive to improve the quality of life in them. The limitations of the dominant development paradigm coupled with the need to focus on consumers provide tremendous opportunities to engage in truly transformative research. Toward this outcome, several interactive forces must be understood and addressed during research design, management, and implementation. The purpose of this essay is to provide a synthesis-that is, a framework in the form of a conceptual model-with practical applications to transformative research in developing markets and, ultimately, with the broader objective to stimulate new conceptualizations, research, and best practices to transform consumer well-being. © 2012, American Marketing Association

cTULIP: application of a human-based RNA-seq primary tumor classification tool for cross-species primary tumor classification in canine

IntroductionThe domestic dog, Canis familiaris, is quickly gaining traction as an advantageous model for use in the study of cancer, one of the leading causes of death worldwide. Naturally occurring canine cancers share clinical, histological, and molecular characteristics with the corresponding human diseases.MethodsIn this study, we take a deep-learning approach to test how similar the gene expression profile of canine glioma and bladder cancer (BLCA) tumors are to the corresponding human tumors. We likewise develop a tool for identifying misclassified or outlier samples in large canine oncological datasets, analogous to that which was developed for human datasets.ResultsWe test a number of machine learning algorithms and found that a convolutional neural network outperformed logistic regression and random forest approaches. We use a recently developed RNA-seq-based convolutional neural network, TULIP, to test the robustness of a human-data-trained primary tumor classification tool on cross-species primary tumor prediction. Our study ultimately highlights the molecular similarities between canine and human BLCA and glioma tumors, showing that protein-coding one-to-one homologs shared between humans and canines, are sufficient to distinguish between BLCA and gliomas.DiscussionThe results of this study indicate that using protein-coding one-to-one homologs as the features in the input layer of TULIP performs good primary tumor prediction in both humans and canines. Furthermore, our analysis shows that our selected features also contain the majority of features with known clinical relevance in BLCA and gliomas. Our success in using a human-data-trained model for cross-species primary tumor prediction also sheds light on the conservation of oncological pathways in humans and canines, further underscoring the importance of the canine model system in the study of human disease