74 research outputs found
Finding maximal k-edge-connected subgraphs from a large graph
No full textIn this paper, we study how to find maximal k-edge-connected subgraphs from a large graph. k-edge-connected subgraphs can be used to capture closely related vertices, and finding such vertex clusters is interesting in many applications, e.g., social network analysis, bioinformatics, web link research. Compared with other explicit structures for modeling vertex clusters, such as quasi-clique, k-core, which only set the requirement on vertex degrees, k-edge-connected subgraph further requires high connectivity within a subgraph (a stronger requirement), and hence defines a more closely related vertex cluster. To find maximal k-edge-connected subgraphs from a graph, a basic approach is to repeatedly apply minimum cut algorithm to the connected components of the input graph until all connected components are k-connected. However, the basic approach is very expensive if the input graph is large. To tackle the problem, we propose three major techniques: vertex reduction, edge reduction and cut pruning. These speed-up techniques are applied on top of the basic approach. We conduct extensive experiments and show that the speed-up techniques are very effective.Rui Zhou, Chengfei Liu, Jeffrey Xu Yu, Weifa Liang, Baichen Chen, Jianxin L
Engineering Porous Electrodes for Advanced Redox Flow Batteries
No full textThe escalating adoption of renewable energy sources underscores the pressing need for efficient and scalable energy storage systems to ensure consistent energy supply and grid stability. Within energy storage technologies, redox flow batteries have been regarded as promising solutions for stationary grid-scale energy storage. However, the path to their widespread commercialization has been restricted due to the high capital costs, and one of the key solutions to cost reduction lies in enhancing the battery performance.Porous electrodes are crucial components of redox flow battery system, which are closely related to the reactor internal resistance and battery performance. The main focus of this thesis is the development of engineering porous electrodes with a balance between the active surface area and effective electrolyte transport pathways for advanced redox flow batteries. Efforts are devoted to three aspects: i) unveiling the relationship between the morphological properties and electrochemical performance of three distinct carbon-fiber electrodes, including carbon felt, carbon paper, and carbon cloth. Investigating the optimal compression condition for the three electrode in redox flow battery system; ii) developing a dual-layer electrode configuration to simultaneously meet the requirement of high active surface area and low mass transfer resistance; iii) Tailoring the electrode microstructure using non-solvent induced phase separation as well as integrating a micro-flow field into the electrode architecture for improved mass transfer performance.First, the 3D electrode morphology of the three commercially available carbon-fiber electrodes was characterized through X-ray computed tomography at 0-50% compression ratios. The electrochemical performance was evaluated at the same compression range in a lab-scale full-cell vanadium redox flow battery. It was found that the cloth possessed a bimodal pore size distribution. However, its distinct microstructure and the associated advantageous mass transfer properties were deteriorated significantly at applied high compression (e.g., >30% compression ratios). The optimal trade-off between the pressure drop and the electrochemical performance occurs at the compression ratios of 30%, 20%, and 20% for the felt, paper, and cloth, respectively.Secondly, the carbon cloth electrode was combined with a sub-layer consisting of carbon paper to assemble a dual-layer electrode configuration. Quantitative analysis of contributions from each type of polarization was investigated under both V2+/V3+ and VO2+/VO2+ redox couples in one-container symmetric cells with flow-through flow fields. The results showed that the proposed strategy was effective to obtain decreased overall kinetic and mass transport resistances. At the current density of 100 mA/cm2, a decrease of ~35% and ~17% of the overall cell overpotential was achieved compared to single-layer carbon cloth and paper, respectively.Finally, the non-solvent induced phase separation technique was used to fabricate tailored non-fibrous porous electrodes. Inspired by the flow field designs in redox flow batteries for low pressure drop and uniform electrolyte distribution, a strategy to imprint micropatterned flow fields directly into the electrode architecture during the phase exchange process was explored. Two micro-patterned designs (i.e., groove and pillar patterns) were selected and the electrochemical measurements were conducted using the Fe2+/Fe3+ redox couple in a symmetric cell. It was found that the pillar-patterned electrodes combined with an external interdigitated flow field showed the best performance. At an electrolyte velocity of 10 cm/s, the total resistances for kinetic and mass transfer are less than 0.1 Ω·cm2 in symmetric iron cell tests, corresponding to a reduction of ~60% when comparing to the activated carbon paper electrode
Time-dependent fiber spinning equations. 2. Analysis of the stability of numerical approximations
No full textPerspiration Compensated Transdermal Alcohol Sensor for Personalized Medicine
No full textNon-invasive continuous alcohol (ethanol) monitoring has potential applications in both population research and in clinical management of acute alcohol intoxication or chronic alcoholism. Current wearable monitors based on transdermal alcohol content (TAC) sensing have limited accessibility and blood alcohol content (BAC) quantification accuracy. In the first half of this work, we demonstrated a self-contained discreet wearable transdermal alcohol (TAC) sensor in the form of a wristband or armband. This sensor can detect vapor-phase alcohol in perspiration from 0.09 ppm (equivalent to 0.09 mg/dL sweat alcohol concentration at 25 °C under Henry’s Law equilibrium) to over 500 ppm at one-minute time resolution. Additionally, a digital sensor was employed to monitor the temperature and humidity levels inside the sensing chamber. Two male human subjects were recruited to conduct studies with alcohol consumption using calibrated prototype TAC sensors to validate the performance. Our preliminary data showed that, under well-controlled conditions, this sensor can acquire TAC curves at low doses (1-2 standard drinks). Moreover, TAC data for different doses can be easily distinguished. However, substantial interpersonal and intrapersonal variabilities in measurement data were also observed in experiments under less controlled conditions. Our observations suggest that perspiration rate might be an important contributing factor to these variabilities, which inspired us to develop a perspiration compensated TAC sensor. In the second half of this thesis, we carefully analyzed the mass transport process of ethanol and water vapors inside the sensing chamber to identify the root causes of sensor variabilities observed from our device. A mathematical model was developed to better understand the relationship between sensing current and ethanol concentration in liquid sweat. The resulted equation suggests that perspiration rate-induced sensor variabilities can potentially be compensated by two humidity measurements. Therefore, we updated the wearable TAC sensor design, integrating two additional digital temperature and humidity sensors. Internal components of the device were rearranged, reducing its overall size to 42 mm x 46 mm x 13 mm. Prototypes of the new TAC sensor were fabricated and characterized in our lab. Next, 10 repeated trials with alcohol administration (1 standard drink) were conducted by one subject to test the hypothesis on that individual. Normalized area under curve (AUC) and peak values were utilized to compare the sensor variabilities before and after compensation. Compared to TAC data without compensation, the variabilities of AUC and peak values were reduced by 45% and 64%, respectively. ANOVA f-tests were applied to test the hypothesis on this individual. The null hypothesis of the peak values has been rejected with an f statistic of 7.89 (p-value = 0.004). However, the test on AUC data yielded an f statistic of 3.35 (p-value = 0.054), indicating the null hypothesis of the AUC values was not rejected. Based on power analysis, 20 samples in total are required to draw a conclusion for AUC. Further studies with sufficient sample sizes are required to validate and characterize the impact of different perspiration rates on TAC sensors, which may inform more reproducible and accurate sensor designs in the future. In addition, the author also contributed to several other sensors and portable systems for personalized medicine and research. Two selected projects with major contributions were included in Chapter 9
Spectral methods for the viscoelastic time‐dependent flow equations with applications to Taylor–Couette flow
No full textComparison of two different carbon nanotubes-based hybrid multiscale composites with respect to mechanical and electrical properties
No full textMorphological Properties and Electrochemical Performance for Compressed Carbon-fiber Electrodes in Redox Flow Batteries
No full textImproving reactor performance of redox flow batteries is critical to reduce capital cost, and one of the main contributions to the internal resistance is generated by the electrodes, which also impact the pressure drop of the stack. Porous electrodes with optimized microstructure and physiochemical properties play a key role in enhancing electrochemical and fluid dynamic performance. Electrode compression significantly impacts morphology and battery behavior, but the relationship between microstructure and performance remains unclear. In the present study, three representative, commercially available, carbon-fiber electrodes (i.e., paper, felt, and cloth) with distinct microstructures were investigated, and a comprehensive study was conducted to compare morphology, hydraulic permeability, mechanical behavior, electrochemical performance in a lab-scale vanadium redox flow battery at compression ratios of 0%-50%. The 3D electrode morphology was characterized through X-ray computed tomography and the extracted microstructure parameters (e.g., surface area and tortuosity) were compared with corresponding electrochemically determined parameters. The optimal trade-off between fluid dynamics and electrochemical performance occurred at the compression ratios of 30%, 20%, and 20% for the felt, paper, and cloth, respectively. Owing to the bi-modal porosity of the woven microstructure, the cloth showed a better trade-off between the electrochemical performance and pressure drop than the other electrodes
Morphological Properties and Electrochemical Performance for Compressed Carbon-fiber Electrodes in Redox Flow Batteries
No full textRecognizing the urgent need for further cost reduction to drive deep penetration of redox flow batteries as grid-scale stationary energy storage systems in the global energy mix, it is critical to improve reactor performance to bring down the high capital cost. As one of the main contributors to the overall internal resistance, porous electrodes with properly designed microstructure and optimized physiochemical properties are preferable for boosting electrochemical and fluid dynamic performance. The present study aims to unveil the relationship between electrode morphology and electrochemical performance under varying electrode compression. Three representative, commercially available, carbon-fiber electrodes (i.e., paper, felt, and cloth) with distinct microstructures were selected here, and a comprehensive study was conducted to compare morphology, hydraulic permeability, mechanical behavior, electrochemical properties including decoupled kinetic and mass transfer resistances, and overall battery performance in a lab-scale vanadium redox flow battery at 0-50% compression ratios. The 3D electrode morphology was characterized through X-ray computed tomography and the extracted key microstructure parameters (e.g., surface area and tortuosity) were compared with corresponding electrochemically determined parameters. It was found that the cloth possessed a bimodal pore size distribution due to its distinct woven microstructure and that it was sensitive to the applied compression. The large pores formed at the intersections between fiber bundles collapsed under excessive compression, which greatly reduced the advantageous high permeability and low mass transfer resistances characteristic of the uncompressed cloth. The paper electrodes exhibited a strongly growing compression force accompanied by increased in-plane tortuosity and mass transfer resistance even at low compression (<20%). During battery operation, the cloth maintains a good balance between performance and pressure drop at moderate compression. The optimal trade-off between fluid dynamics and electrochemical performance occurred at the compression ratios of 30%, 20%, and 20% for the felt, paper, and cloth, respectively
Large-scale analysis of protein phosphorylation in Populus leaves
No full textProtein phosphorylation is a key regulatory factor in all aspects of plant biology; most regulatory pathways are governed by the reversible phosphorylation of proteins. To better understand the role that phosphorylated proteins play in a woody model plant, we performed a systemic analysis of the phosphoproteome from Populus leaves using high accuracy NanoLC-MS/MS in combination with biochemical enrichments using strong cation exchange chromatography and titanium dioxide chromatography. We identified 104 phosphopeptides from 94 phosphoproteins and determined 111 phosphorylation sites including 93 occurring on serine residues and 18 on threonine residues. The identified phosphoproteins are involved in a wide variety of metabolic processes. Among these identified phosphoproteins, 68 phosphorylation sites (72 %) were located outside of conserved domains. The identified phosphopeptides share a common phosphorylation motif of pS/pT-P/D-S/A. These data suggest that the Populus metabolism and gene regulation machinery are major targets of phosphorylation. To our knowledge, this is the first gel-free, large-scale phosphoproteomics analysis in woody plants. The identified phosphorylation sites will be a valuable resource for many fields of plant biology, and information gained from the study will provide a better understanding of protein phosphorylation
Low-rank decomposition on transformed feature maps domain for image denoising
No full textLow-rank based models are proved outstanding for denoising on the data with strong repetitive or redundant property. However, for natural images with complex structures or rich details, the performance drops down because of the weak low-rankness of the data. A feasible solution is to transform the data into a suitable domain to further explore the underlying low-rank information. In this paper, we present a novel approach to create such a domain via a fully replicated linear autoencoder network. By applying various low-rank models to the feature maps generated by the encoder rather than the original data, and then performing inverse transformation by the decoder, their denoising performances all get enhanced. In addition, feature maps also show good sparsity, hence we introduce a new measure combining sparse and low-rank regularity, and further propose corresponding single image denoising model. Extensive experiments show the superiority of our work
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