Indian Institute of Technology Guwahati

About: Indian Institute of Technology Guwahati is a education organization based out in Guwahati, Assam, India. It is known for research contribution in the topics: Catalysis & Computer science. The organization has 6933 authors who have published 17102 publications receiving 257351 citations.

Optically active single-walled carbon nanotubes.

Abstract: The optical, electrical and mechanical properties of single-walled carbon nanotubes (SWNTs) are largely determined by their structures, and bulk availability of uniform materials is vital for extending their technological applications. Since they were first prepared, much effort has been directed toward selective synthesis and separation of SWNTs with specific structures. As-prepared samples of chiral SWNTs contain equal amounts of left- and right-handed helical structures, but little attention has been paid to the separation of these non-superimposable mirror image forms, known as optical isomers. Here, we show that optically active SWNT samples can be obtained by preferentially extracting either right- or left-handed SWNTs from a commercial sample. Chiral 'gable-type' diporphyrin molecules bind with different affinities to the left- and right-handed helical nanotube isomers to form complexes with unequal stabilities that can be readily separated. Significantly, the diporphyrins can be liberated from the complexes afterwards, to provide optically enriched SWNTs.

Modeling of daily pan evaporation in sub tropical climates using ANN, LS-SVR, Fuzzy Logic, and ANFIS

Abstract: This paper investigates the abilities of Artificial Neural Networks (ANN), Least Squares – Support Vector Regression (LS-SVR), Fuzzy Logic, and Adaptive Neuro-Fuzzy Inference System (ANFIS) techniques to improve the accuracy of daily pan evaporation estimation in sub-tropical climates. Meteorological data from the Karso watershed in India (consisting of 3801 daily records from the year 2000 to 2010) were used to develop and test the models for daily pan evaporation estimation. The measured meteorological variables include daily observations of rainfall, minimum and maximum air temperatures, minimum and maximum humidity, and sunshine hours. Prior to model development, the Gamma Test (GT) was used to derive estimates of the noise variance for each input–output set in order to identify the most useful predictors for use in the machine learning approaches used in this study. The ANN models consisted of feed forward backpropagation (FFBP) models with Bayesian Regularization (BR), along with the Levenberg–Marquardt (LM) algorithm. A comparison was made between the estimates provided by the ANN, LS-SVR, Fuzzy Logic, and ANFIS models. The empirical Hargreaves and Samani method (HGS), as well as the Stephens–Stewart (SS) method, were also considered for comparison with the newer machine learning methods. The Root Mean Square Error (RMSE) and Correlation Coefficient (CORR) were the statistical performance indices that were used to evaluate the accuracy of the various models. Based on the comparison, it was found that the Fuzzy Logic and LS-SVR approaches can be employed successfully in modeling the daily evaporation process from the available climatic data. In addition, results showed that the machine learning models outperform the traditional HGS and SS empirical methods.

Gas Adsorption Properties of the Chromium-Based Metal Organic Framework MIL-101

Abstract: MIL-101, a chromium-based metal organic framework, is known to adsorb large amounts of green house gases such as CO2 and CH4. Measurement, analysis, and modeling of the pure gas adsorption isotherms of desired gases are necessary for any attempt to use this framework for separation/storage applications. In an attempt to understand adsorption characteristics of this framework, pure gas adsorption properties of CO2 and CH4 along with C3H8, SF6, and Ar were measured at three temperatures 283, 319, and 351 K using a standard gravimetric method. The adsorbates were chosen based on their physical characteristics such as polarizability and quadrupole moment. Dual site Langmuir (DSL) isotherm proved to be useful for modeling adsorption of gases on this type of materials that are known to have heterogeneity. Active metal centers and sites inside the pores of supertetrahedra act as major locations for adsorption. Analysis of enthalpy of adsorption using the DSL model revealed that, for all gases, it initially decre...

Functional oligosaccharides: production, properties and applications

Abstract: Worldwide interest in oligosaccharides has been increasing ever since they were accorded the prebiotic status. The oligosaccharides of various origin like, bacteria, algae, fungi and higher plants have been used extensively both as food ingredients and pharmacological supplements. The non-digestible oligosaccharides have been implicated as dietary fibre, sweetener, weight controlling agent and humectant in confectioneries, bakeries and breweries. Functional oligosaccharides have been found effective in gastrointestinal normal flora proliferation and pathogen suppression, dental caries prevention, enhancement of immunity, facilitation of mineral absorption, source of antioxidant, antibiotic alternative, regulators of blood glucose in diabetics and serum lipids in hyperlipidemics. Apart from the pharmacological applications, oligosaccharides have found use in drug delivery, cosmetics, animal and fishery feed, agriculture, etc. Keeping in view the importance of the functional oligosaccharides, we present an overview of their natural sources, types, structures, physiological properties. Conventional as well as novel synthesis, purification and analysis methods are summarized. Recent promising developments in this area are presented to facilitate their further exploitation.