Search results for: N. C. Kothiyal

Authors: Ramanjit Kaur, N. C. Kothiyal

Abstract:

The present study compares the improved mechanical strength of cement mortar nanocomposites (CNCs) using polycarboxylate superplasticizer (PCE-SP) stabilized graphene oxide or functionalized carbon nanotubes (SP-GO and SP-FCNT) as reinforcing agents. So, in the present study, GO, and FCNT have been sterically stabilized via superplasticizer. The obtained results have shown that a dosage of 0.02 wt% of SP-GO and 0.08 wt% of SP-FCNTs showed an improvement in compressive strength by 23.2% and 16.5%, respectively. On the other hand, incorporation of 0.04% SP-GO and SP-FCNT resulted in an enhanced split tensile strength of 38.5% and 35.8%, respectively, as compared to the control sample at 90 days of curing. Mercury Intrusion Porosimetry (MIP) observations presented a decline in the porosity of 0.02% SP-GO-CNCs and 0.08% SP-FCNT-CNCs by 25% and 31% in comparison to the control sample. The improved hydration of CNCs contributing to the enhancement of physicomechanical strength has also been shown by SEM and XRD studies.

Keywords: graphene oxide, functionalized CNTs, steric stabilization, microstructure, crystalline behavior, pore structure refinement

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Authors: Aasheesh Raturi, Vimal Kothiyal, P. D. Semalty

Abstract:

We studied mechanical properties of Eucalyptus tereticornis using FT-NIR spectroscopy. Firstly, spectra were pre-processed to eliminate useless information. Then, prediction model was constructed by partial least squares regression. To study the influence of pre-processing on prediction of mechanical properties for NIR analysis of wood samples, we applied various pretreatment methods like straight line subtraction, constant offset elimination, vector-normalization, min-max normalization, multiple scattering. Correction, first derivative, second derivatives and their combination with other treatment such as First derivative + straight line subtraction, First derivative+ vector normalization and First derivative+ multiplicative scattering correction. The data processing methods in combination of preprocessing with different NIR regions, RMSECV, RMSEP and optimum factors/rank were obtained by optimization process of model development. More than 350 combinations were obtained during optimization process. More than one pre-processing method gave good calibration/cross-validation and prediction/test models, but only the best calibration/cross-validation and prediction/test models are reported here. The results show that one can safely use NIR region between 4000 to 7500 cm-1 with straight line subtraction, constant offset elimination, first derivative and second derivative preprocessing method which were found to be most appropriate for models development.

Keywords: FT-NIR, mechanical properties, pre-processing, PLS

Procedia PDF Downloads 308