Thermal characterization of intrinsic and extrinsic InP using photoacoustic technique

An open photoacoustic cell operating in the low range of chopping frequency has been employed to evaluate the thermal diffusivity values of intrinsic InP and InP doped with S, Sn and Fe. The experimental set-up is calibrated by the evaluation of thermal diffusivity value of pure Si and GaAs. The present investigation shows that doped samples show a reduced value for thermal diffusivity compared to intrinsic sample. From the analysis of data it is also seen that nature of dopant clearly influences the thermal diffusivity value of semiconductors. The results are explained in terms of phonon assisted heat transfer mechanism in semiconductors

Thermal characterization of intrinsic and extrinsic InP using photoacoustic technique

An open photoacoustic cell operating in the low range of chopping frequency has been employed to evaluate the thermal diffusivity values of intrinsic InP and InP doped with S, Sn and Fe. The experimental set-up is calibrated by the evaluation of thermal diffusivity value of pure Si and GaAs. The present investigation shows that doped samples show a reduced value for thermal diffusivity compared to intrinsic sample. From the analysis of data it is also seen that nature of dopant clearly influences the thermal diffusivity value of semiconductors. The results are explained in terms of phonon assisted heat transfer mechanism in semiconductors

Thermal characterization of intrinsic and extrinsic InP using photoacoustic technique

An open photoacoustic cell operating in the low range of chopping frequency has been employed to evaluate the thermal diffusivity values of intrinsic InP and InP doped with S, Sn and Fe. The experimental set-up is calibrated by the evaluation of thermal diffusivity value of pure Si and GaAs. The present investigation shows that doped samples show a reduced value for thermal diffusivity compared to intrinsic sample. From the analysis of data it is also seen that nature of dopant clearly influences the thermal diffusivity value of semiconductors. The results are explained in terms of phonon assisted heat transfer mechanism in semiconductors

Photothermal deflection studies on heat transport in intrinsic and extrinsic InP

Laser induced transverse photothermal deflection technique has been employed to determine the thermal parameters of InP doped with Sn, S and Fe as well as intrinsic InP. The thermal diffusivity values of these various samples are evaluated from the slope of the curve plotted between the phase of photothermal deflection signal and pump-probe offset. Analysis of the data shows that heat transport and hence the thermal diffusivity value, is greatly affected by the introduction of dopant. It is also seen that the direction of heat flow with respect to the plane of cleavage of semiconductor wafers influences the thermal diffusivity value. The results are explained in terms of dominating phonon assisted heat transfer mechanism in semiconductors.

Photoacoustic investigation of intrinsic and extrinsic Si

An open-cell configuration of the photoacoustic (PA) technique is employed to determine the thermal and transport properties of intrinsic Si and Si doped with B (p-type) and P (n-type). The experimentally obtained phase of the PA signal under heat transmission configuration is fitted to that of theoretical model by taking thermal and transport properties, namely, thermal diffusivity, diffusion coefficient, and surface recombination velocity, as adjustable parameters. It is seen from the analysis that doping and also the nature of dopant have a strong influence on the thermal and transport properties of semiconductors. The results are interpreted in terms of the carrier-assisted and phonon-assisted heat transfer mechanisms in semiconductors as well as the various scattering processes occurring in the propagation of heat carriers.

Weather and climate of Penisular India modulated by Extrinsic factors- Empirical and Numerical Perspectives

The Doctoral thesis focuses on the factors that influence the weather and climate over Peninsular Indias. The first chapter provides a general introduction about the climatic features over peninsular India, various factors dealt in subsequent chapters, such as solar forcing on climate, SST variability in the northern Indian Ocean and its influence on Indian monsoon, moisture content of the atmosphere and its importance in the climate system, empirical formulation of regression forecast of climate and some aspects of regional climate modeling. Chapter 2 deals with the variability in the vertically integrated moisture (VIM) over Peninsular India on various time scales. The third Chapter discusses the influence of solar activity in the low frequency variability in the rainfall of Peninsular India. The study also investigates the influence of solar activity on the horizontal and vertical components of wind and the difference in the forcing before and after the so-called regime shift in the climate system before and after mid-1970s.In Chapter 4 on Peninsular Indian Rainfall and its association with meteorological and oceanic parameters over adjoining oceanic region, a linear regression model was developed and tested for the seasonal rainfall prediction of Peninsular India.

Study on period search methods of variable stars: Application to ASAS and CRTS databases

Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.