Phenylamine Analogous Adducts of C60

Abstract

Reaction conditions leading to efficient nitration of the C₆₀ molecules for the production of nearly pure hexanitro[60]fullerenes using gaseous nitrogen dioxide as the nitration agent were developed. Approach of utilizing hexanitrofullerene as a reactive precursor molecule in the preparation of organic derivatives of C₆₀ demonstrated a versatile alternative synthetic method for indirect fullerene functionalization. Fullerenic nitro functions were found to be excellent leaving groups opt for replacement by nucleophilic substituents, such as phenylamine and oligophenylamines.     

Thermodynamic properties of 1‐ETHYL‐3‐methylimidazolium methanesulphonate with aromatic sulphur,nitrogen compounds at T = 298.15–323.15 K and P = 1 bar

This work investigates the ability of 1‐ethyl‐3‐methylimidazolium methanesulphate ([EMIM][MeSO₃]) as a green and tuneable solvent for denitrification and desulphurisation studies. Experimental density, surface tension and refractive index data have been measured for the following systems: [EMIM][MeSO₃] (1) + pyridine (2), [EMIM][MeSO₃] (1) + pyrrole (2), [EMIM][MeSO₃] (1) + quinoline (2), [EMIM][MeSO₃] (1) + indoline (2), [EMIM][MeSO₃] (1) + thiophene (2) and [EMIM][MeSO₃] (1) + water (2) over the entire mole fraction of [EMIM][MeSO₃] at T = 298.15–323.15 K and P = 1 bar. Further from experimental density, surface tension and refractive index, coefficient of thermal expansivity, excess molar volume, deviation of surface tension and refractive index deviation were also calculated. It was found that the heteroaromatic nitrogen/sulphur compounds are completely miscible in [EMIM][MeSO₃]. The surface tension values were found to increase while the refractive index decreases with increasing mole fraction of [EMIM][MeSO₃]. The experimental values for surface tension increased in the order: pyridine > thiophene > pyrrole > indoline > quinoline > water and for refractive index: pyridine > pyrrole > indoline > quinoline > thiophene > water. It was found that the composition of [EMIM][MeSO₃] has a greater influence than temperature in deciding the surface, optical and thermodynamic properties for similar molecular interaction such as IL–thiophene and IL–pyrrole than dissimilar molecules such as IL–water. Further quantum chemical‐based COSMO‐RS tool was used to estimate the activity coefficient at different composition. © 2012 Canadian Society for Chemical Engineering     

Augmenting satellite precipitation estimation with lightning information

We have used lightning information to augment the precipitation estimation from remotely sensed imagery using an artificial neural network cloud classification system (PERSIANN-CCS). Co-located lightning data are used to segregate cloud patches, segmented from Geostationary Operational Environmental Satellite (GOES)-12 infrared (IR) data, into either electrified patches (ECPs) or nonelectrified patches (NECPs). A set of features is extracted separately for the ECPs and NECPs. Features for the ECPs include a new feature corresponding to the number of flashes that occur within a 15 minute window around the time of the nominal scan of the satellite IR images of the cloud patches. The cloud patches are classified and clustered using a self-organizing maps (SOM) neural network. Then, brightness temperature and rain rate (T–R) relationships are derived for different clusters. Rain rates are estimated for the cloud patches based on their representative (T–R) relationship. The equitable threat scores (ETS) of the daily and hourly precipitation estimates at a range of rain rate thresholds show that incorporating lightning information can improve categorical precipitation estimation in the winter and fall seasons. In the winter, the ETS improvement is almost 15% for the daily and 12% for the hourly rainfall estimates (at thresholds below 15 mm hour^?1). During the same period, there is also a drop in the false alarm ratio (FAR) and a corresponding increase in the probability of detection (POD) at most threshold levels. During the summer and spring seasons, no categorical significant improvements have been noted, except for the BIAS scores for the hourly rainfall estimates at higher thresholds (above 5 mm hour^?1) in the summer months. A quantitative evaluation in terms of the root mean squared error (RMSE) and correlation coefficient (CORR) shows that the incorporation of lightning data does improve rainfall estimation over all seasons with the most improvement (around 11–13% CORR improvement) occurring during the winter. We speculate that during the winter, more of the ice processes are packed into a thinner stratiform layer with lower cloud tops and freezing levels. Hence, more of the ice contributes to precipitation on the ground. We also expect that information from lightning, related to the ice microphysics processes, provides surrogate information about the rain rate.     

Interpretation of the relationship between skin temperature and vegetation fraction: Effect of subpixel soil temperature variability

Both land surface/skin temperature and vegetation indices data provided routinely and globally by NASA MODIS sensors at 1‐km grid resolution represent an important piece of information assimilated into various environmental applications/models. Previous studies based on these and similar remotely data sets and on two‐component pixel representation (accounting for pixel‐aggregated vegetation and bare soil temperatures only) have shown a rather strong linear relationship between the pixel's skin temperature and the vegetation index/fraction. Deviations (Δ₀) from this relationship are frequently used for soil moisture content estimates at a pixel scale. As the two‐component pixel model does not account for subpixel heterogeneity (associated, for example, with bare soil temperature variability within the pixel), its role in controlling a magnitude of Δ₀ has been examined. A simple tri‐component pixel model describing vegetation and wet and dry bare soil temperatures was suggested to analyse an impact of this heterogeneity on Δ₀ estimates. This model was considered to provide a ‘true’ estimate of Δ₀ as compared with Δ₀ evaluated from the two‐component pixel model. A comparison between the models shows that a substantial underestimation of Δ₀ was likely to occur at a level of individual pixels when the two‐component approach was applied for interpretation of the observed relationship between the skin temperature and the vegetation index. Depending on the fraction of pixel occupied by the dry soil, this underestimation might be as much as 100%.     

Amorphous Catalysts and Electrochemical Water Splitting: An Untold Story of Harmony

In the near future, sustainable energy conversion and storage will largely depend on the electrochemical splitting of water into hydrogen and oxygen. Perceiving this, countless research works focussing on the fundamentals of electrocatalysis of water splitting and on performance improvements are being reported everyday around the globe. Electrocatalysts of high activity, selectivity, and stability are anticipated as they directly determine energy‐ and cost efficiency of water electrolyzers. Amorphous electrocatalysts with several advantages over crystalline counterparts are found to perform better in electrocatalytic water splitting. There are plenty of studies witnessing performance enhancements in electrocatalysis of water splitting while employing amorphous materials as catalysts. The harmony between the flexibility of amorphous electrocatalysts and electrocatalysis of water splitting (both the oxygen evolution reaction [OER] and the hydrogen evolution reaction [HER]) is one of the untold and unsummarized stories in the field of electrocatalytic water splitting. This Review is devoted to comprehensively discussing the upsurge of amorphous electrocatalysts in electrochemical water splitting. In addition to that, the basics of electrocatalysis of water splitting are also elaborately introduced and the characteristics of a good electrocatalyst for OER and HER are discussed.     

Aromatic sulfur‐nitrogen extraction using ionic liquids: Experiments and predictions using an a priori model

The tie‐line composition of three quaternary system namely 1‐ethyl‐3‐methylimidazolium acetate ([EMIM][OAc]) ([EMIM][OAc]) (1) + thiophene (2) + pyridine (3) + toluene (4), 1‐ethyl‐3‐methylimidazolium ethylsulphate ([EMIM][EtSO₄]) (1) + thiophene (2) + pyridine (3) + toluene (4), 1‐ethyl‐3‐methylimidazolium methylsulphonate ([EMIM][MeSO₃]) (1) + thiophene (2) + pyridine (3) + toluene (4) were experimentally determined at 298.15 K. The measured tie‐line data were successfully correlated with the nonrandom two liquid and UNIversal QUAsiChemical model prediction which gave less than 1% root mean square deviation (RMSD). [EMIM][MeSO₃] looks to be a promising solvent for the simultaneous separation having distribution ratios less than unity for both thiophene and pyridine. The quantum chemical‐based conductor like screening model for real solvent (COSMO‐RS) model was then used to predict the tie‐line composition of quaternary systems. COSMO‐RS gave the RMSD for the studied systems to be 8.41, 8.74, and 6.53% for the ionic liquids, respectively. © 2013 American Institute of Chemical Engineers AIChE J, 59: 4806–4815, 2013     

Phase behavior of catalytic deactivated compounds and water with 1-ethyl-3-methylimidazolium acetate [EMIM][OAc] ionic liquid at T = 298.15–323.15 K and p = 1 bar

Density, surface tension and refractive index of the binary mixture of catalytic deactivated compounds with 1-ethyl-3-methylimidazolium acetate {[EMIM][OAc]} ionic liquid were measured at temperature of 298.15–323.15 K from which the derived thermodynamic properties including excess molar volume and deviation of surface tension and refractive index were calculated. The derived thermodynamic properties could be explained well by the interaction between similar and dissimilar aromatic structure of the molecules over the entire mole fraction of ILs. It was observed that all the catalytic deactivated compounds and water molecules have significant structural interaction with [EMIM][OAc] via CH?π bond interaction, π?π stacking and n?π interaction over the entire mole fraction of IL at T = 298.15 K. Further the composition of ionic liquid have significant influence on the interaction between dissimilar aromatic structure of molecules like pyridine, indoline and quinoline in liquid phase as compared to temperature. The surface tension increases in the order of: hiophene > pyridine > quinoline > pyrrole > indoline > water; while the refractive index increases in the order: pyridine < water < pyrrole < thiophene < indoline < quinoline. The deviation of surface tension was found to be inversely proportional to the deviation of refractive index at T = 298.15 K. From these results it was concluded that the structure of the ionic liquids is very important for extraction processes on catalytic deactivated compounds, especially for pyridine, indoline and quinoline as compared to water molecules.     

Phenylamine Analogous Adducts of C60

Reaction conditions leading to efficient nitration of the C₆₀ molecules for the production of nearly pure hexanitro[60]fullerenes using gaseous nitrogen dioxide as the nitration agent were developed. Approach of utilizing hexanitrofullerene as a reactive precursor molecule in the preparation of organic derivatives of C₆₀ demonstrated a versatile alternative synthetic method for indirect fullerene functionalization. Fullerenic nitro functions were found to be excellent leaving groups opt for replacement by nucleophilic substituents, such as phenylamine and oligophenylamines.     

Quantum chemical studies on the simultaneous interaction of thiophene and pyridine with ionic liquid

The simultaneous interaction of thiophene and pyridine with different ionic liquids:1‐butyl‐1‐methylpyrrolidinium tetrafluoroborate([BPYRO][BF₄]),1‐butyl‐1‐methylpyrrolidinium hexafluoro‐phosphate ([BPYRO][PF₆]), 1‐butyl‐4‐methylpyridinium tetrafluoroborate ([BPY][BF₄]), 1‐butyl‐4‐methylpyridinium hexafluorophosphate ([BPY][PF₆]) and 1‐benzyl‐3‐methylimidazolium tetrafluoroborate ([BeMIM][BF₄]) were investigated using quantum chemical calculations. A three‐tier approach comprising of partial charges, interaction energies and sigma profile generation using conductor‐like screening model for real solvents (COSMO‐RS) was chosen to study the systems. A quantitative attempt based on the CH‐π interaction in ionic liquid; thiophene–pyridine complexes gave the interaction energies of ILs in the order: [BPY][BF₄] > [BPYRO][PF₆] > [BeMIM][BF₄] > [BPY][PF₆] > [BPYRO][BF₄]. An inverse relation was observed between the activity coefficient at infinite dilution predicted via COSMO‐RS–based model and interaction energies. The dominance of CH‐π interaction was evident from the sigma profiles of ionic liquid together with thiophene and pyridine. © 2010 American Institute of Chemical Engineers AIChE J, 2011     

A linear merging methodology for high-resolution precipitation products using spatiotemporal regression

Currently, the only viable option for a global precipitation product is the merger of several precipitation products from different modalities. In this article, we develop a linear merging methodology based on spatiotemporal regression. Four highresolution precipitation products (HRPPs), obtained through methods including the Climate Prediction Center's Morphing (CMORPH), Geostationary Operational Environmental Satellite-Based Auto-Estimator (GOES-AE), GOES-Based Hydro-Estimator (GOES-HE) and Self-Calibrating Multivariate Precipitation Retrieval (SCAMPR) algorithms, are used in this study. The merged data are evaluated against the Arkansas Red Basin River Forecast Center's (ABRFC's) ground-based rainfall product. The evaluation is performed using the Heidke skill score (HSS) for four seasons, from summer 2007 to spring 2008, and for two different rainfall detection thresholds. It is shown that the merged data outperform all the other products in seven out of eight cases. A key innovation of this machine learning method is that only 6% of the validation data are used for the initial training. The sensitivity of the algorithm to location, distribution of training data, selection of input data sets and seasons is also analysed and presented.