Large area quantitative analysis of nanostructured thin-films

Proposed and verified method offers an unique quantitative large scale nanostructures' evaluation.This is the accepted manuscript. The final version is available at http://pubs.rsc.org/en/Content/ArticleLanding/2015/RA/c4ra16018e#!divAbstract

Kinetic and DFT Studies on the Mechanism of C−S Bond Formation by Alkyne Addition to the [Mo3S4(H2O)9]4+ Cluster

Reaction of [Mo3(μ3-S)(μ-S)3] clusters with alkynes usually leads to formation of two C−S bonds between the alkyne and two of the bridging sulfides. The resulting compounds contain a bridging alkenedithiolate ligand, and the metal centers appear to play a passive role despite reactions at those sites being well illustrated for this kind of cluster. A detailed study including kinetic measurements and DFT calculations has been carried out to understand the mechanism of reaction of the [Mo3(μ3-S)(μ-S)3(H2O)9]4+ (1) cluster with two different alkynes, 2-butyne-1,4-diol and acetylenedicarboxylic acid. Stoppedflow experiments indicate that the reaction involves the appearance in a single kinetic step of a band at 855 or 875 nm, depending on the alkyne used, a position typical of clusters with two C−S bonds. The effects of the concentrations of the reagents, the acidity, and the reaction medium on the rate of reaction have been analyzed. DFT and TD-DFT calculations provide information on the nature of the product formed, its electronic spectrum and the energy profile for the reaction. The structure of the transition state indicates that the alkyne approaches the cluster in a lateral way and both C−S bonds are formed simultaneously

Seeing it my way: a case of a selective deficit in inhibiting self-perspective

Little is known about the functional and neural architecture of social reasoning, one major obstacle being that we crucially lack the relevant tools to test potentially different social reasoning components. In the case of belief reasoning, previous studies tried to separate the processes involved in belief reasoning per se from those involved in the processing of the high incidental demands such as the working memory demands of typical belief tasks (e.g., Stone et al., 1998; Samson et al., 2004). In this study, we developed new belief tasks in order to disentangle, for the first time, two perspective taking components involved in belief reasoning: (1) the ability to inhibit one’s own perspective (self-perspective inhibition) and (2) the ability to infer someone else’s perspective as such (other-perspective taking). The two tasks had similar demands in other-perspective taking as they both required the participant to infer that a character has a false belief about an object’s location. However, the tasks varied in the self-perspective inhibition demands. In the task with the lowest self-perspective inhibition demands, at the time the participant had to infer the character’s false belief, he or she had no idea what the new object’s location was. In contrast, in the task with the highest self-perspective inhibition demands, at the time the participant had to infer the character’s false belief, he or she knew where the object was actually located (and this knowledge had thus to be inhibited). The two tasks were presented to a stroke patient, WBA, with right prefrontal and temporal damage. WBA performed well in the low-inhibition false belief task but showed striking difficulty in the task placing high self-perspective inhibition demands, showing a selective deficit in inhibiting self-perspective. WBA also made egocentric errors in other social and visual perspective taking tasks, indicating a difficulty with belief attribution extending to the attribution of emotions, desires and visual experiences to other people. The case of WBA, together with the recent report of three patients impaired in belief reasoning even when self-perspective inhibition demands were reduced (Samson et al., 2004), provide the first neuropsychological evidence that (a) the inhibition of one’s own point of view and (b) the ability to infer someone else’ s point of view, rely on distinct neural and functional processes

ZnO nanorods: Production and characterisation of the nanocrystals grown by potentiostatic and galvanostatic electrocrystallisation

ZnO nanorods (ZnO-nR) were grown electrochemically under potentiostatic (PS) and galvanostatic conditions (GS) in an undivided three electrodes (PS) or two electrodes (GS) cell arrangement onto ITO/glass and ITO/Polyester. Their physical properties were examined using SEM, absorption spectroscopy and XRD. It was found that the galvanostatic growth induces higher hydroxyl content than the potentiostatic growth. Conditions for the production of consistent quality of ZnO-nR have been established

Investigating the photoelectrochemistry of transparent ZnO grown on ITO/plastic for flexible photoelectrochemical cell and photovoltaic application

ZnO was electrochemically grown on ITO coated polyethylene (PET) substrate. By sandwiching the electrolyte (sodium para-toluene sulfonate) with so grown ZnO/ITO/PET substrate with another ITO/Plastic substrate, a transparent ZnO based flexible PV cells was fabricated. The efficiency of 0.3% was obtained when shined under UV light. It was concluded that there will be a significant trade-off between with its performance although the optical transparency is very attractive. © 2012 Materials Research Society

Enhancing energy management in grid-interactive buildings: A comparison among cooperative and coordinated architectures

The increasing penetration of renewable energy sources has the potential to contribute towards the decarbonisation of the building energy sector. However, this transition brings its own challenges including that of energy integration and potential grid instability issues arising due the stochastic nature of variable renewable energy sources. One potential approach to address these issues is demand side management, which is increasingly seen as a promising solution to improve grid stability. This is achieved by exploiting demand flexibility and shifting peak demand towards periods of peak renewable energy generation. However, the energy flexibility of a single building needs to be coordinated with other buildings to be used in a flexibility market. In this context, multi-agent systems represent a promising tool for improving the energy management of buildings at the district and grid scale. The present research formulates the energy management of four buildings equipped with thermal energy storage and PV systems as a multi-agent problem. Two multi-agent reinforcement learning methods are explored: a centralised (coordinated) controller and a decentralised (cooperative) controller, which are benchmarked against a rule-based controller. The two controllers were tested for three different climates, outperforming the rule-based controller by 3% and 7% respectively for cost, and 10% and 14% respectively for peak demand. The study shows that the multi-agent cooperative approach may be more suitable for districts with heterogeneous objectives within the individual buildings

Electrical characterization of electrochemically grown ZnO nanorods using STM

ZnO nanorods were grown homogenously and vertically on ITO using electrochemical techniques. The physical properties of the nanorods were characterized using SEM and optical absorption. The electrical conductivity, deduced using STM at different tip heights, and was found to be 20 Ω-cm with a carrier concentration of 3×1015 cm-3. The results show that electrochemically grown ZnO nanorods have electrical properties suitable for use in electronic devices such as solar cells and transistors. A-Si:H p-i-n solar cells were then deposited after the fabrication on the ZnO on ITO-coated substrates. The results show that the textured solar cell performance was 30% higher than the planar solar cell. © 2012 Materials Research Society

Data-driven predictive control for unlocking building energy flexibility: A review

Managing supply and demand in the electricity grid is becoming more challenging due to the increasing penetration of variable renewable energy sources. As significant end-use consumers, and through better grid integration, buildings are expected to play an expanding role in the future smart grid. Predictive control allows buildings to better harness available energy flexibility from the building passive thermal mass. However, due to the heterogeneous nature of the building stock, developing computationally tractable control-oriented models, which adequately represent the complex and nonlinear thermal-dynamics of individual buildings, is proving to be a major hurdle. Data-driven predictive control, coupled with the “Internet of Things”, holds the promise for a scalable and transferrable approach, with data-driven models replacing traditional physics-based models. This review examines recent work utilising data-driven predictive control for demand side management application with a special focus on the nexus of model development and control integration, which to date, previous reviews have not addressed. Further topics examined include the practical requirements for harnessing passive thermal mass and the issue of feature selection. Current research gaps are outlined and future research pathways are suggested to identify the most promising data-driven predictive control techniques for grid integration of buildings

Evaluation of 18 isolates of basidiomycetes for Lignocellulose degrading enzymes

Since fossil fuel resources are limited there is a necessity to produce alternative types of fuel that are renewable and eco-friendly. Basidiomycetes are potential sources of enzymes that can be used for biofuel production. The current study aimed to isolate basidiomycetes from Sri Lanka, screen them for lignocellulose degrading enzymes, namely cellulase, xylanase, laccase, Mn peroxidase and lignin peroxidase and study the effect of potential inducers of laccase production. Among the eighteen basidiomycetes isolated, Pycnoporus sp. produced the highest cellulase activity (0.23 FPU/ml) whereas Phlebiopsis sp. produced the highest xylanase activity (5.4 U/ml). Earliella scabrosa produced the highest laccase (91.2 U/l) and Mn peroxidase (17.5 U/l) activities. Lignin peroxidase activity was not detected from the isolates. Effect of alkali lignin, Cu2+ and rice bran, three potential inducers, on laccase production by E. scabrosa, Pycnoporus sp. and Trametes hirsuta (M40) was studied. Results indicated that alkali lignin (2 g/l) significantly increased laccase production from Pycnoporus sp. and T. hirsuta (M40) while Cu2+ increased laccase production from E. scabrosa and T. hirsuta at 200 μM. Use of rice bran (10 g/l) resulted in higher laccase production from E. scabrosa and Pycnoporus sp. High laccase activity (79600 U/l) was obtained from E. scabrosa by using 50 g/l of rice bran and by extending the incubation period to 18 days. The study concluded that some of the basidiomycetes isolated can produce significant lignocellulose degrading enzyme activities