Thermal Decomposition of Propargyl Alcohol: Single Pulse Shock Tube Experimental and ab Initio Theoretical Study

Thermal decomposition of propargyl alcohol (C3H3OH), a molecule of interest in interstellar chemistry and combustion, was investigated using a single pulse shock tube in the temperature ranging from 953 to 1262 K. The products identified include acetylene, propyne, vinylacetylene, propynal, propenal, and benzene. The experimentally observed overall rate constant for thermal decomposition of propargyl alcohol was found to be k = 10((10.17 +/- 0.36)) exp(-39.70 +/- 1.83)/RT) s(-1) Ab initio theoretical calculations were carried out to understand the potential energy surfaces involved in the primary and secondary steps of propargyl alcohol thermal decomposition. Transition state theory was used to predict the rate constants, which were then used and refined in a kinetic simulation of the product profile. The first step in the decomposition is C-O bond dissociation, leading to the formation of two important radicals in combustion, OH and propargyl. This has been used to study the reverse OH propargyl radical reaction, about which there appears to be no prior work. Depending on the site of attack, this reaction leads to propargyl alcohol or propenal, one of the major products at temperatures below 1200 K. A detailed mechanism has been derived to explain all the observed products.

The irregularities of the sunspot cycle and their theoretical modelling

The 11-year sunspot cycle has many irregularities, the most prominent amongst them being the grand minima when sunspots may not be seen for several cycles. After summarizing the relevant observational data about the irregularities, we introduce the flux transport dynamo model, the currently most successful theoretical model for explaining the 11-year sunspot cycle. Then we analyze the respective roles of nonlinearities and random fluctuations in creating the irregularities. We also discuss how it has recently been realized that the fluctuations in meridional circulation also can be a source of irregularities. We end by pointing out that fluctuations in the poloidal field generation and fluctuations in meridional circulation together can explain the occurrences of grand minima.

TIME VARYING LINEAR PREDICTION USING SPARSITY CONSTRAINTS

Time-varying linear prediction has been studied in the context of speech signals, in which the auto-regressive (AR) coefficients of the system function are modeled as a linear combination of a set of known bases. Traditionally, least squares minimization is used for the estimation of model parameters of the system. Motivated by the sparse nature of the excitation signal for voiced sounds, we explore the time-varying linear prediction modeling of speech signals using sparsity constraints. Parameter estimation is posed as a 0-norm minimization problem. The re-weighted 1-norm minimization technique is used to estimate the model parameters. We show that for sparsely excited time-varying systems, the formulation models the underlying system function better than the least squares error minimization approach. Evaluation with synthetic and real speech examples show that the estimated model parameters track the formant trajectories closer than the least squares approach.

Wind speed prediction using spatio-temporal covariance

High wind poses a number of hazards in different areas such as structural safety, aviation, and wind energy-where low wind speed is also a concern, pollutant transport, to name a few. Therefore, usage of a good prediction tool for wind speed is necessary in these areas. Like many other natural processes, behavior of wind is also associated with considerable uncertainties stemming from different sources. Therefore, to develop a reliable prediction tool for wind speed, these uncertainties should be taken into account. In this work, we propose a probabilistic framework for prediction of wind speed from measured spatio-temporal data. The framework is based on decompositions of spatio-temporal covariance and simulation using these decompositions. A novel simulation method based on a tensor decomposition is used here in this context. The proposed framework is composed of a set of four modules, and the modules have flexibility to accommodate further modifications. This framework is applied on measured data on wind speed in Ireland. Both short-and long-term predictions are addressed.

Holistic Measures for Evaluating Prediction Models in Smart Grids

The performance of prediction models is often based on ``abstract metrics'' that estimate the model's ability to limit residual errors between the observed and predicted values. However, meaningful evaluation and selection of prediction models for end-user domains requires holistic and application-sensitive performance measures. Inspired by energy consumption prediction models used in the emerging ``big data'' domain of Smart Power Grids, we propose a suite of performance measures to rationally compare models along the dimensions of scale independence, reliability, volatility and cost. We include both application independent and dependent measures, the latter parameterized to allow customization by domain experts to fit their scenario. While our measures are generalizable to other domains, we offer an empirical analysis using real energy use data for three Smart Grid applications: planning, customer education and demand response, which are relevant for energy sustainability. Our results underscore the value of the proposed measures to offer a deeper insight into models' behavior and their impact on real applications, which benefit both data mining researchers and practitioners.

Stability of the flow in a soft tube deformed due to an applied pressure gradient

A linear stability analysis is carried out for the flow through a tube with a soft wall in order to resolve the discrepancy of a factor of 10 for the transition Reynolds number between theoretical predictions in a cylindrical tube and the experiments of Verma and Kumaran J. Fluid Mech. 705, 322 (2012)]. Here the effect of tube deformation (due to the applied pressure difference) on the mean velocity profile and pressure gradient is incorporated in the stability analysis. The tube geometry and dimensions are reconstructed from experimental images, where it is found that there is an expansion and then a contraction of the tube in the streamwise direction. The mean velocity profiles at different downstream locations and the pressure gradient, determined using computational fluid dynamics, are found to be substantially modified by the tube deformation. The velocity profiles are then used in a linear stability analysis, where the growth rates of perturbations are calculated for the flow through a tube with the wall modeled as a neo-Hookean elastic solid. The linear stability analysis is carried out for the mean velocity profiles at different downstream locations using the parallel flow approximation. The analysis indicates that the flow first becomes unstable in the downstream converging section of the tube where the flow profile is more pluglike when compared to the parabolic flow in a cylindrical tube. The flow is stable in the upstream diverging section where the deformation is maximum. The prediction for the transition Reynolds number is in good agreement with experiments, indicating that the downstream tube convergence and the consequent modification in the mean velocity profile and pressure gradient could reduce the transition Reynolds number by an order of magnitude.

Crystal Structure and Prediction

The notion of structure is central to the subject of chemistry. This review traces the development of the idea of crystal structure since the time when a crystal structure could be determined from a three-dimensional diffraction pattern and assesses the feasibility of computationally predicting an unknown crystal structure of a given molecule. Crystal structure prediction is of considerable fundamental and applied importance, and its successful execution is by no means a solved problem. The ease of crystal structure determination today has resulted in the availability of large numbers of crystal structures of higher-energy polymorphs and pseudopolymorphs. These structural libraries lead to the concept of a crystal structure landscape. A crystal structure of a compound may accordingly be taken as a data point in such a landscape.

Implication of a sigma-Methane Complex en Route to Elimination of Methane from a Ruthenium Complex: An Experimental and Theoretical Investigation

The five-coordinated 16-electron complex Ru(Me)(dppe)(2)]OTf] (3) undergoes methane elimination at room temperature to afford the ortho-metalated species (dppe){(C6H5)(C6H4)PCH2CH2P(C6H5)(2)}Ru]OTf] (7). Methane elimination, monitored using NMR spectroscopy, revealed no intermediate throughout the reaction. The NOE between Ru-Me protons and ortho phenyl protons and an agostic interaction trans to the methyl group were found in complex 3 by NMR spectroscopy, which form the basis for three plausible pathways for methane elimination and ortho metalation: pathway I (through spatial interaction), pathway II (through oxidative addition and reductive elimination), and pathway III (through agostic interaction). Methane elimination from complex 3 via pathway I was discounted, since it involves interactions through space and not through bonds. Moreover, the calculated energy barrier for the pathway I transition state was quite high (71.3 kcal/mol), which also indicates that this pathway is very unlikely. Furthermore, no spectroscopic evidence for oxidatively added seven-coordinated Ru(IV) species was found and the computed energy barrier of the transition state for pathway II was moderately high (41.1 kcal/mol), which suggests that this cannot be the right pathway for methane elimination and ortho-metalation of complex 3. On the other hand, indirect evidence in the form of chemical reactions point to the most plausible pathway for methane elimination, pathway III, via the intermediacy of a sigma-CH4 complex that could not be found spectroscopically. DFT calculations at several levels on this pathway showed an initial low-barrier rearrangement through TS1 to a square-pyramidal intermediate wherein methyl and agostic C-H are cis to each other. Migration of hydrogen from agostic C-H and elimination of methane proceed through the transition state TS2, which retains a weak metal-H bonding through most parts of the reaction coordinate. Upon comparison of all three pathways, pathway III was found to be the most likely for methane elimination and ortho-metalation of complex 3.

Prediction of Land Surface Temperature under Cloudy Conditions using Microwave Remote Sensing and ANN

Land surface temperature (LST) is an important variable in climate, hydrologic, ecological, biophysical and biochemical studies (Mildrexler et al., 2011). The most effective way to obtain LST measurements is through satellites. Presently, LST from moderate resolution imaging spectroradiometer (MODIS) sensor is applied in various fields due to its high spatial and temporal availability over the globe, but quite difficult to provide observations in cloudy conditions. This study evolves of prediction of LST under clear and cloudy conditions using microwave vegetation indices (MVIs), elevation, latitude, longitude and Julian day as inputs employing an artificial neural network (ANN) model. MVIs can be obtained even under cloudy condition, since microwave radiation has an ability to penetrate through clouds. In this study LST and MVIs data of the year 2010 for the Cauvery basin on a daily basis were obtained from MODIS and advanced microwave scanning radiometer (AMSR-E) sensors of aqua satellite respectively. Separate ANN models were trained and tested for the grid cells for which both LST and MVI were available. The performance of the models was evaluated based on standard evaluation measures. The best performing model was used to predict LST where MVIs were available. Results revealed that predictions of LST using ANN are in good agreement with the observed values. The ANN approach presented in this study promises to be useful for predicting LST using satellite observations even in cloudy conditions. (C) 2015 The Authors. Published by Elsevier B.V.

Experimental determination and theoretical correlation for the solubilities of dicarboxylic acid esters in supercritical carbon dioxide

The synthesis of high molecular weight esters such as bis (2-ethylhexyl) sebacate is of significance for its use as a lubricant. This ester is synthesized by the transesterification of dimethyl sebacate with 2-ethylhexanol. Therefore, the solubilities of bis (2-ethylhexyl) sebacate and dimethyl sebacate were determined at 308-328 K at pressures of 10-18 MPa in supercritical carbon dioxide. The solubility of dimethyl sebacate was always higher than bis (2-ethylhexyl) sebacate at a given temperature and pressure. The Mendez-Teja model was used to verify the self-consistency of data. Further, a new semi-empirical model with three parameters was developed using the solution theory coupled with Wilson activity coefficient. This model was used to correlate the experimental data of this work and solubilities of many high molecular weight esters reported in the literature. (C) 2015 Elsevier B.V. All rights reserved.

Prediction of Queue Waiting Times for Metascheduling on Parallel Batch Systems

Prediction of queue waiting times of jobs submitted to production parallel batch systems is important to provide overall estimates to users and can also help meta-schedulers make scheduling decisions. In this work, we have developed a framework for predicting ranges of queue waiting times for jobs by employing multi-class classification of similar jobs in history. Our hierarchical prediction strategy first predicts the point wait time of a job using dynamic k-Nearest Neighbor (kNN) method. It then performs a multi-class classification using Support Vector Machines (SVMs) among all the classes of the jobs. The probabilities given by the SVM for the class predicted using k-NN and its neighboring classes are used to provide a set of ranges of predicted wait times with probabilities. We have used these predictions and probabilities in a meta-scheduling strategy that distributes jobs to different queues/sites in a multi-queue/grid environment for minimizing wait times of the jobs. Experiments with different production supercomputer job traces show that our prediction strategies can give correct predictions for about 77-87% of the jobs, and also result in about 12% improved accuracy when compared to the next best existing method. Experiments with our meta-scheduling strategy using different production and synthetic job traces for various system sizes, partitioning schemes and different workloads, show that the meta-scheduling strategy gives much improved performance when compared to existing scheduling policies by reducing the overall average queue waiting times of the jobs by about 47%.

Intramolecular hydrogen bonds involving organic fluorine in the derivatives of hydrazides: an NMR investigation substantiated by DFT based theoretical calculations

The rare examples of intramolecular hydrogen bonds (HB) of the type the N-H center dot center dot center dot F-C, detected in a low polarity solvent in the derivatives of hydrazides, by utilizing one and two-dimensional solution state multinuclear NMR techniques, are reported. The observation of through-space couplings, such as, (1h)J(FH), and (1h)J(FN), provides direct evidence for the existence of intra-molecular HB. Solvent induced perturbations and the variable temperature NMR experiments unambiguously establish the presence of intramolecular HB. The existence of multiple conformers in some of the investigated molecules is also revealed by two dimensional HOESY and N-15-H-1 HSQC experiments. The H-1 DOSY experimental results discard any possibility of self or cross dimerization of the molecules. The derived NMR experimental results are further substantiated by Density Function Theory (DFT) based Non Covalent Interaction (NCI), and Quantum Theory of Atom in Molecule (QTAIM) calculations. The NCI calculations served as a very sensitive tool for detection of non-covalent interactions and also confirm the presence of bifurcated HBs.

Theoretical Insights to Niobium-Doped Monolayer MoS2-Gold Contact

We report a first principles study of the electronic properties for a contact formed between Nb-doped monolayer MoS2 and gold for different doping concentrations. We first focus on the shift of energy levels in band structure and the density of states with respect to the Fermi level for a geometrically optimized 5 x 5 MoS2 supercell for both pristine and Nb-doped structures. The doping is achieved by substituting Mo atoms with Nb atoms at random positions. It is observed that for an experimentally reported sheet hole doping concentration of (rho(2D)) 1.8 x 10(14) cm(-2), the pristine MoS2 converts to degenerate p-type semiconductor. Next, we interface this supercell with six layers of < 111 > cleaved surface of gold to investigate the contact nature of MoS2-Au system. By careful examination of projected band structure, projected density of states, effective potential and charge density difference, we demonstrate that the Schottky barrier nature observed for pure MoS2-Au contact can be converted from n-type to p-type by efficient Nb doping.

Composition dependent multiple structural transformations of myoglobin in aqueous ethanol solution: A combined experimental and theoretical study

Experimental studies (circular dichroism and ultra-violet (UV) absorption spectra) and large scale atomistic molecular dynamics simulations (accompanied by order parameter analyses) are combined to establish a number of remarkable (and unforeseen) structural transformations of protein myoglobin in aqueous ethanol mixture at various ethanol concentrations. The following results are particularly striking. (1) Two well-defined structural regimes, one at x(EtOH) similar to 0.05 and the other at x(EtOH) similar to 0.25, characterized by formation of distinct partially folded conformations and separated by a unique partially unfolded intermediate state at x(EtOH) similar to 0.15, are identified. (2) Existence of non-monotonic composition dependence of (i) radius of gyration, (ii) long range contact order, (iii) residue specific solvent accessible surface area of tryptophan, and (iv) circular dichroism spectra and UV-absorption peaks are observed. Interestingly at x(EtOH) similar to 0.15, time averaged value of the contact order parameter of the protein reaches a minimum, implying that this conformational state can be identified as a molten globule state. Multiple structural transformations well known in water-ethanol binary mixture appear to have considerably stronger effects on conformation and dynamics of the protein. We compare the present results with studies in water-dimethyl sulfoxide mixture where also distinct structural transformations are observed along with variation of co-solvent composition. (C) 2015 AIP Publishing LLC.