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Citations since 2017
8 Research Items
I am studying the properties of Multiple Stellar Populations in Globular Clusters. The star clusters were thought to be simple stellar populations which essentially means that these stars are of the same age, of same chemical composition and have the same evolutionary journey. However, observations of these star clusters over time prove otherwise. I am trying to study these clusters which are chemically enriched primarily with Helium and Nitrogen, and understand their properties through their evolution. Prior to that I was studying the feldspars, which are abundant in Earth's crust and her interior.
May 2019 - present
- PhD Student
- I am working on the young, intermediate-age and massive star clusters residing in the Magellanic Clouds. I get my data from the HST data archival system and using a few photometric techniques, I try to analyze how many of these clusters might have multiple stellar populations.
Multiple stellar populations (MPs) representing star-to-star light-element abundance variations are common in nearly all ancient Galactic globular clusters (GCs). Here we provide the strongest evidence yet that the populous, ∼1.7 Gyr old Large Magellanic Cloud cluster NGC 2173 also exhibits light-element abundance variations. Thus, our results sugg...
Multiple stellar populations (MPs) representing star-to-star light-element abundance variations are common in nearly all ancient Galactic globular clusters. Here we provide the strongest evidence yet that the populous, ~ 1.7 Gyr-old Large Magellanic Cloud cluster NGC 2173 also exhibits light-element abundance variations. Thus, our results suggest t...
The conventional picture of coeval, chemically homogeneous, populous star clusters – known as ‘simple stellar populations’ (SSPs) – is a view of the past. Photometric and spectroscopic studies reveal that almost all ancient globular clusters in the Milky Way and our neighbouring galaxies exhibit star-to-star light-element abundance variations, typi...
The conventional picture of coeval, chemically homogeneous, populous star clusters -- known as `simple stellar populations' (SSPs) -- is a view of the past. Photometric and spectroscopic studies reveal that almost all ancient globular clusters in the Milky Way and our neighbouring galaxies exhibit star-to-star light-element abundance variations, ty...
The traditional picture of the star clusters being simple 9 (known as Simple Stellar Populations, SSPs) is long gone as the new evidences have been 10 put forward by various photometric and spectroscopic studies showing that star clusters 11 (especially, ancient globular clusters) might have chemical abundance variations in them. 12 Thus,it is know...
Rocks and minerals are formed under the extreme conditions of temperature and pressure in interior of a planet. It is a very difficult task to know the surface and core-mantle activities of a planet experimentally since simulating such systems in the laboratory is practically impossible. Therefore, applying the method of evolutionary algorithm coup...
I have drawn a bandstructure using Quantum espresso (plotband.x). I am getting some vertical lines in the picture. I know it's a glitch with QE, but I don't know how to get rid of these unwanted lines. Does anyone have any idea as to how to erase these lines ? I have attached an example.
I have a spin polarized system for which I need a separate band-structure for spin up and spin down system. I have used the band-prog routine (PWSCF band plotting routine) developed by J. Yates. However, there is a discrepancy of calculation of K-Points done by the said routine and the PW of quantum espresso because of which it fails to draw the separate bands for the given structure.
Can anyone suggest a way to draw the separate band-structures for a spin polarized system? Thanks in advance!
N.B. The normal way (using plotband.x in QE) of bandplotting works. This question is specifically for the band-structure of spin polarized system. Please let me know if anyone has done this already &/ has an idea about this.
I am using the quantum espresso V.6.1. After doing plotband.x calculations, I am getting multiple .xmgr files. Why does this happen? I have provided K-points appropriately in my bands-input file. And when I did an example of Silicon from the tutorial, I got single .xmgr file. Is it a software issue or am I doing something wrong in my input details?
Please let me know if you need additional information than the details I already provided above.
Thanks in advance.
If the equilibrium crystallization takes place, there is a change in temperature (or in volume) over the time at some pressure. However, in fractional crystallization process, a chemical equilibrium is not achieved. So, if I am keeping pressure constant, does temperature change in fractional crystallization method for 1 run in simulation?
Thanks in advance.
To study the properties of the young and intermediate age star clusters in the Magellanic Clouds. My main aim is to detect if any cluster which is young (1-2 Gyr)/intermediate age (2-5 Gyr) has multiple populations in it.
I am studying the end members of a ternary Feldspars namely Albite (NaAlSi3O8), Anorthite(CaAl2Si2O8) and Orthoclase(KAlSi3O8). These are the Aluminosillicates which occupy large portion of the Earth's crust. I am studying their electronic, optical and thermodynamical properties. I am also interested in understanding their behavior at high pressure. In this regard, I am particularly interested in Albite since albite goes through a series of phase transition as a function of pressure. It would be an interesting phenomenon to look whether this transition leads to the formation of the hollandite structure (of course, at high pressure and temperature).
High entropy alloys are the multicomponent systems, generally, made of four or five elements and in comparison with alloys, these have properties such as good creep strength, high hardness, good magnetic properties and superior thermal stability. High hardness with low density of HEA is of a particular interest in aerospace engineering where controlling the weight of various components is essential for reducing energy demands.