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Description

In recent years, a substantial amount of research has been focused on identifying suitable interfacial layers in organic light-emitting diodes and organic solar cells which has efficient charge transport properties. In this work, a very thin layer of AgOx is deposited on top of the ITO layer along with PEDOT:PSS

In recent years, a substantial amount of research has been focused on identifying suitable interfacial layers in organic light-emitting diodes and organic solar cells which has efficient charge transport properties. In this work, a very thin layer of AgOx is deposited on top of the ITO layer along with PEDOT:PSS and is observed that the solar cells having the AgOx interfacial layer showed a 28% increase in power conversion efficiency in comparison to that of the control cell. The enhancement in efficiency has been ascribed to improvements in fill factor as well as the increase in shunt resistance and decrease in the series resistance of the solar cells. An equivalent circuit model is also provided to understand the changes in the series and shunt resistances in the AgOx modified devices.

ContributorsDas, Sayantan (Author) / Alford, Terry (Author) / Department of Chemistry and Biochemistry (Contributor)
Created2014-07-28
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Description

S-cysteinylated albumin and methionine-oxidized apolipoprotein A-I (apoA-I) have been posed as candidate markers of diseases associated with oxidative stress. Here, a dilute-and-shoot form of LC–electrospray ionization–MS requiring half a microliter of blood plasma was employed to simultaneously quantify the relative abundance of these oxidized proteoforms in samples stored at −80

S-cysteinylated albumin and methionine-oxidized apolipoprotein A-I (apoA-I) have been posed as candidate markers of diseases associated with oxidative stress. Here, a dilute-and-shoot form of LC–electrospray ionization–MS requiring half a microliter of blood plasma was employed to simultaneously quantify the relative abundance of these oxidized proteoforms in samples stored at −80 °C, −20 °C, and room temperature and exposed to multiple freeze-thaw cycles and other adverse conditions in order to assess the possibility that protein oxidation may occur as a result of poor sample storage or handling. Samples from a healthy donor and a participant with poorly controlled type 2 diabetes started at the same low level of protein oxidation and behaved similarly; significant increases in albumin oxidation via S-cysteinylation were found to occur within hours at room temperature and days at −20 °C. Methionine oxidation of apoA-I took place on a longer time scale, setting in after albumin oxidation reached a plateau. Freeze–thaw cycles had a minimal effect on protein oxidation. In matched collections, protein oxidation in serum was the same as that in plasma. Albumin and apoA-I oxidation were not affected by sample headspace or the degree to which vials were sealed. ApoA-I, however, was unexpectedly found to oxidize faster in samples with lower surface-area-to-volume ratios. An initial survey of samples from patients with inflammatory conditions normally associated with elevated oxidative stress-including acute myocardial infarction and prostate cancer—demonstrated a lack of detectable apoA-I oxidation. Albumin S-cysteinylation in these samples was consistent with known but relatively brief exposures to temperatures above −30 °C (the freezing point of blood plasma). Given their properties and ease of analysis, these oxidized proteoforms, once fully validated, may represent the first markers of blood plasma specimen integrity based on direct measurement of oxidative molecular damage that can occur under suboptimal storage conditions.

ContributorsBorges, Chad (Author) / Rehder, Douglas (Author) / Jensen, Sally (Author) / Schaab, Matthew (Author) / Sherma, Nisha (Author) / Yassine, Hussein (Author) / Nikolova, Boriana (Author) / Breburda, Christian (Author) / Department of Chemistry and Biochemistry (Contributor)
Created2014-07-01
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Description

Our ability to uncover complex network structure and dynamics from data is fundamental to understanding and controlling collective dynamics in complex systems. Despite recent progress in this area, reconstructing networks with stochastic dynamical processes from limited time series remains to be an outstanding problem. Here we develop a framework based

Our ability to uncover complex network structure and dynamics from data is fundamental to understanding and controlling collective dynamics in complex systems. Despite recent progress in this area, reconstructing networks with stochastic dynamical processes from limited time series remains to be an outstanding problem. Here we develop a framework based on compressed sensing to reconstruct complex networks on which stochastic spreading dynamics take place. We apply the methodology to a large number of model and real networks, finding that a full reconstruction of inhomogeneous interactions can be achieved from small amounts of polarized (binary) data, a virtue of compressed sensing. Further, we demonstrate that a hidden source that triggers the spreading process but is externally inaccessible can be ascertained and located with high confidence in the absence of direct routes of propagation from it. Our approach thus establishes a paradigm for tracing and controlling epidemic invasion and information diffusion in complex networked systems.

ContributorsShen, Zhesi (Author) / Wang, Wen-Xu (Author) / Fan, Ying (Author) / Di, Zengru (Author) / Lai, Ying-Cheng (Author) / Ira A. Fulton Schools of Engineering (Contributor)
Created2014-07-01
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Description

A brief review of manganese-catalyzed hydrosilylation is presented along with a personal account of how the design for the highly active catalyst, (Ph2PPrPDI)Mn, was conceived. The reductive transformations achieved using this catalyst are described and put into further context by comparing the observed activities with those attained for leading late

A brief review of manganese-catalyzed hydrosilylation is presented along with a personal account of how the design for the highly active catalyst, (Ph2PPrPDI)Mn, was conceived. The reductive transformations achieved using this catalyst are described and put into further context by comparing the observed activities with those attained for leading late first-row transition-metal catalysts.

ContributorsTrovitch, Ryan (Author) / Department of Chemistry and Biochemistry (Contributor)
Created2014-07-01
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Description

Evolutionary games model a common type of interactions in a variety of complex, networked, natural systems and social systems. Given such a system, uncovering the interacting structure of the underlying network is key to understanding its collective dynamics. Based on compressive sensing, we develop an efficient approach to reconstructing complex

Evolutionary games model a common type of interactions in a variety of complex, networked, natural systems and social systems. Given such a system, uncovering the interacting structure of the underlying network is key to understanding its collective dynamics. Based on compressive sensing, we develop an efficient approach to reconstructing complex networks under game-based interactions from small amounts of data. The method is validated by using a variety of model networks and by conducting an actual experiment to reconstruct a social network. While most existing methods in this area assume oscillator networks that generate continuous-time data, our work successfully demonstrates that the extremely challenging problem of reverse engineering of complex networks can also be addressed even when the underlying dynamical processes are governed by realistic, evolutionary-game type of interactions in discrete time.

ContributorsWang, Wen-Xu (Author) / Lai, Ying-Cheng (Author) / Grebogi, Celso (Author) / Ye, Jieping (Author) / Ira A. Fulton Schools of Engineering (Contributor)
Created2011-12-21
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Description

Locating sources of diffusion and spreading from minimum data is a significant problem in network science with great applied values to the society. However, a general theoretical framework dealing with optimal source localization is lacking. Combining the controllability theory for complex networks and compressive sensing, we develop a framework with

Locating sources of diffusion and spreading from minimum data is a significant problem in network science with great applied values to the society. However, a general theoretical framework dealing with optimal source localization is lacking. Combining the controllability theory for complex networks and compressive sensing, we develop a framework with high efficiency and robustness for optimal source localization in arbitrary weighted networks with arbitrary distribution of sources. We offer a minimum output analysis to quantify the source locatability through a minimal number of messenger nodes that produce sufficient measurement for fully locating the sources. When the minimum messenger nodes are discerned, the problem of optimal source localization becomes one of sparse signal reconstruction, which can be solved using compressive sensing. Application of our framework to model and empirical networks demonstrates that sources in homogeneous and denser networks are more readily to be located. A surprising finding is that, for a connected undirected network with random link weights and weak noise, a single messenger node is sufficient for locating any number of sources. The framework deepens our understanding of the network source localization problem and offers efficient tools with broad applications.

ContributorsHu, Zhao-Long (Author) / Han, Xiao (Author) / Lai, Ying-Cheng (Author) / Wang, Wen-Xu (Author) / Ira A. Fulton Schools of Engineering (Contributor)
Created2017-04-12
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Description

Combustion-derived aerosols in the marine boundary layer have been poorly studied, especially in remote environments such as the open Atlantic Ocean. The tropical Atlantic has the potential to contain a high concentration of aerosols, such as black carbon, due to the African emission plume of biomass and agricultural burning products.

Combustion-derived aerosols in the marine boundary layer have been poorly studied, especially in remote environments such as the open Atlantic Ocean. The tropical Atlantic has the potential to contain a high concentration of aerosols, such as black carbon, due to the African emission plume of biomass and agricultural burning products. Atmospheric particulate matter samples across the tropical Atlantic boundary layer were collected in the summer of 2010 during the southern hemispheric dry season when open fire events were frequent in Africa and South America. The highest black carbon concentrations were detected in the Caribbean Sea and within the African plume, with a regional average of 0.6 μg m-3 for both. The lowest average concentrations were measured off the coast of South America at 0.2 to 0.3 μg m-3. Samples were quantified for black carbon using multiple methods to provide insights into the form and stability of the carbonaceous aerosols (i.e., thermally unstable organic carbon, soot like, and charcoal like). Soot-like aerosols composed up to 45% of the carbonaceous aerosols in the Caribbean Sea to as little as 4% within the African plume. Charcoal-like aerosols composed up to 29% of the carbonaceous aerosols over the oligotrophic Sargasso Sea, suggesting that non-soot-like particles could be present in significant concentrations in remote environments. To better apportion concentrations and forms of black carbon, multiple detection methods should be used, particularly in regions impacted by biomass burning emissions.

ContributorsPohl, K. (Author) / Cantwell, M. (Author) / Herckes, Pierre (Author) / Lohmann, R. (Author) / Department of Chemistry and Biochemistry (Contributor)
Created2014-07-18
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Description

Dynamical processes occurring on the edges in complex networks are relevant to a variety of real-world situations. Despite recent advances, a framework for edge controllability is still required for complex networks of arbitrary structure and interaction strength. Generalizing a previously introduced class of processes for edge dynamics, the switchboard dynamics,

Dynamical processes occurring on the edges in complex networks are relevant to a variety of real-world situations. Despite recent advances, a framework for edge controllability is still required for complex networks of arbitrary structure and interaction strength. Generalizing a previously introduced class of processes for edge dynamics, the switchboard dynamics, and exploit- ing the exact controllability theory, we develop a universal framework in which the controllability of any node is exclusively determined by its local weighted structure. This framework enables us to identify a unique set of critical nodes for control, to derive analytic formulas and articulate efficient algorithms to determine the exact upper and lower controllability bounds, and to evaluate strongly structural controllability of any given network. Applying our framework to a large number of model and real-world networks, we find that the interaction strength plays a more significant role in edge controllability than the network structure does, due to a vast range between the bounds determined mainly by the interaction strength. Moreover, transcriptional regulatory networks and electronic circuits are much more strongly structurally controllable (SSC) than other types of real-world networks, directed networks are more SSC than undirected networks, and sparse networks are typically more SSC than dense networks.

ContributorsPang, Shao-Peng (Author) / Wang, Wen-Xu (Author) / Hao, Fei (Author) / Lai, Ying-Cheng (Author) / Ira A. Fulton Schools of Engineering (Contributor)
Created2017-06-26
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Description

The notable increase in biofuel usage by the road transportation sector in Brazil during recent years has significantly altered the vehicular fuel composition. Consequently, many uncertainties are currently found in particulate matter vehicular emission profiles. In an effort to better characterise the emitted particulate matter, measurements of aerosol physical and

The notable increase in biofuel usage by the road transportation sector in Brazil during recent years has significantly altered the vehicular fuel composition. Consequently, many uncertainties are currently found in particulate matter vehicular emission profiles. In an effort to better characterise the emitted particulate matter, measurements of aerosol physical and chemical properties were undertaken inside two tunnels located in the São Paulo Metropolitan Area (SPMA). The tunnels show very distinct fleet profiles: in the Jânio Quadros (JQ) tunnel, the vast majority of the circulating fleet are light duty vehicles (LDVs), fuelled on average with the same amount of ethanol as gasoline. In the Rodoanel (RA) tunnel, the particulate emission is dominated by heavy duty vehicles (HDVs) fuelled with diesel (5% biodiesel). In the JQ tunnel, PM2.5 concentration was on average 52 μg m-3, with the largest contribution of organic mass (OM, 42%), followed by elemental carbon (EC, 17%) and crustal elements (13%). Sulphate accounted for 7% of PM2.5 and the sum of other trace elements was 10%. In the RA tunnel, PM2.5 was on average 233 μg m-3, mostly composed of EC (52%) and OM (39%). Sulphate, crustal and the trace elements showed a minor contribution with 5%, 1%, and 1%, respectively. The average OC : EC ratio in the JQ tunnel was 1.59 ± 0.09, indicating an important contribution of EC despite the high ethanol fraction in the fuel composition. In the RA tunnel, the OC : EC ratio was 0.49 ± 0.12, consistent with previous measurements of diesel-fuelled HDVs. Besides bulk carbonaceous aerosol measurement, polycyclic aromatic hydrocarbons (PAHs) were quantified. The sum of the PAHs concentration was 56 ± 5 ng m-3 and 45 ± 9 ng m-3 in the RA and JQ tunnel, respectively. In the JQ tunnel, benzo(a)pyrene (BaP) ranged from 0.9 to 6.7 ng m-3 (0.02–0.1‰ of PM2.5)] whereas in the RA tunnel BaP ranged from 0.9 to 4.9 ng m-3 (0.004–0. 02‰ of PM2.5), indicating an important relative contribution of LDVs emission to atmospheric BaP.

ContributorsBrito, J. (Author) / Rizzo, L. V. (Author) / Herckes, Pierre (Author) / Vasconcellos, P. C. (Author) / Caumo, S. E. S. (Author) / Fornaro, A. (Author) / Ynoue, R. Y. (Author) / Artaxo, P. (Author) / Andrade, M. F. (Author) / Department of Chemistry and Biochemistry (Contributor)
Created2013-12-17
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Description

About 2.5 × 106 snapshots on microcrystals of photoactive yellow protein (PYP) from a recent serial femtosecond crystallographic (SFX) experiment were reanalyzed to maximum resolution. The resolution is pushed to 1.46 Å, and a PYP structural model is refined at that resolution. The result is compared to other PYP models determined

About 2.5 × 106 snapshots on microcrystals of photoactive yellow protein (PYP) from a recent serial femtosecond crystallographic (SFX) experiment were reanalyzed to maximum resolution. The resolution is pushed to 1.46 Å, and a PYP structural model is refined at that resolution. The result is compared to other PYP models determined at atomic resolution around 1 Å and better at the synchrotron. By comparing subtleties such as individual isotropic temperature factors and hydrogen bond lengths, we were able to assess the quality of the SFX data at that resolution. We also show that the determination of anisotropic temperature factor ellipsoids starts to become feasible with the SFX data at resolutions better than 1.5 Å.

ContributorsSchmidt, Marius (Author) / Pande, Kanupriya (Author) / Basu, Shibom (Author) / Tenboer, Jason (Author) / Department of Chemistry and Biochemistry (Contributor)
Created2015-05-15