Indian Institute of Technology Madras

About: Indian Institute of Technology Madras is a facility organization based out in Chennai, Tamil Nadu, India. It is known for research contribution in the topics: Catalysis & Heat transfer. The organization has 20118 authors who have published 36499 publications receiving 590447 citations.

On the formation of protected gold nanoparticles from AuCl 4 − by the reduction using aromatic amines

Abstract: Amines are used extensively as reductants and subsequent capping agents in the synthesis of metal nanoparticles, especially gold, due to its affinity to nitrogen. Taking 2-methyl aniline as an example, we show that metal reduction is followed by polymerization of the amine, while part of it covers the nanoparticle surface another fraction deposits in the solution. It is found that the oxidative polymerization of the amine goes in step with the formation of gold nanoparticles. The gold nanoparticles thus formed have a mean diameter of 20 nm. The polymerized amine encapsulates the gold nanoparticle forming a robust shell of about 5 nm thickness, making the gold core inert towards mineralizing agents such as chloroform, bromoform, sodium cyanide, benzylchloride, etc. which react with the naked gold nanoparticles. The deposited polymer is largely protonated, taking up protons from the medium during its formation. Similar results have been observed in the case of aniline also. The materials have been fully characterized by spectroscopy and microscopy.

Regularization in Hilbert scales under general smoothing conditions

Abstract: For solving linear ill-posed problems regularization methods are required when the available data include some noise. In the present paper regularized approximations are obtained by a general regularization scheme in Hilbert scales which include well-known regularization methods such as the method of Tikhonov regularization and its higher-order forms, spectral methods, asymptotical regularization and iterative regularization methods. For both the cases of high- and low-order regularization, we study a priori and a posteriori rules for choosing the regularization parameter and provide order optimal error bounds that characterize the accuracy of the regularized approximations. These error bounds have been obtained under general smoothing conditions. The results extend earlier results and cover the case of finitely and infinitely smoothing operators. The theory is illustrated by a special ill-posed deconvolution problem arising in geoscience.

Search for Narrow Resonances in Dijet Final States at sqrt[s]=8 TeV with the Novel CMS Technique of Data Scouting.

Abstract: A search for narrow resonances decaying into dijet final states is performed on data from proton-proton collisions at a center-of-mass energy of 8 TeV, corresponding to an integrated luminosity of 18.8 fb(-1). The data were collected with the CMS detector using a novel technique called data scouting, in which the information associated with these selected events is much reduced, permitting collection of larger data samples. This technique enables CMS to record events containing jets at a rate of 1 kHz, by collecting the data from the high-level-trigger system. In this way, the sensitivity to low-mass resonances is increased significantly, allowing previously inaccessible couplings of new resonances to quarks and gluons to be probed. The resulting dijet mass distribution yields no evidence of narrow resonances. Upper limits are presented on the resonance cross sections as a function of mass, and compared with a variety of models predicting narrow resonances. The limits are translated into upper limits on the coupling of a leptophobic resonance Z'(B) to quarks, improving on the results obtained by previous experiments for the mass range from 500 to 800 GeV.

Long-term observations of cloud condensation nuclei in the Amazon rain forest – Part 1: Aerosol size distribution, hygroscopicity, and new model parametrizations for CCN prediction

Abstract: . Size-resolved long-term measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a 1-year period and full seasonal cycle (March 2014–February 2015). The measurements provide a climatology of CCN properties characteristic of a remote central Amazonian rain forest site. The CCN measurements were continuously cycled through 10 levels of supersaturation (S = 0.11 to 1.10 %) and span the aerosol particle size range from 20 to 245 nm. The mean critical diameters of CCN activation range from 43 nm at S = 1.10 % to 172 nm at S = 0.11 %. The particle hygroscopicity exhibits a pronounced size dependence with lower values for the Aitken mode (κAit = 0.14 ± 0.03), higher values for the accumulation mode (κAcc = 0.22 ± 0.05), and an overall mean value of κmean = 0.17 ± 0.06, consistent with high fractions of organic aerosol. The hygroscopicity parameter, κ, exhibits remarkably little temporal variability: no pronounced diurnal cycles, only weak seasonal trends, and few short-term variations during long-range transport events. In contrast, the CCN number concentrations exhibit a pronounced seasonal cycle, tracking the pollution-related seasonality in total aerosol concentration. We find that the variability in the CCN concentrations in the central Amazon is mostly driven by aerosol particle number concentration and size distribution, while variations in aerosol hygroscopicity and chemical composition matter only during a few episodes. For modeling purposes, we compare different approaches of predicting CCN number concentration and present a novel parametrization, which allows accurate CCN predictions based on a small set of input data.