Membership analysis and 3D kinematics of the star-forming complex around Trumpler 37 using Gaia-DR3

Identifying and characterizing young populations of star-forming regions is crucial to unravel their properties. In this regard, Gaia-DR3 data and machine learning tools are very useful for studying large star-forming complexes. In this work, we analyze the $\rm \sim7.1degree^2$ area of one of our Galaxy's dominant feedback-driven star-forming complexes, i.e., the region around Trumpler 37. Using the Gaussian mixture and random forest classifier methods, we identify 1243 high-probable members in the complex, of which $\sim60\%$ are new members and are complete down to the mass limit of $\sim$0.1 $-$ 0.2~$\rm M_{\odot}$. The spatial distribution of the stars reveals multiple clusters towards the complex, where the central cluster around the massive star HD 206267 reveals two sub-clusters. Of the 1243 stars, 152 have radial velocity, with a mean value of $\rm -16.41\pm0.72~km/s$. We investigate stars' internal and relative movement within the central cluster. The kinematic analysis shows that the cluster's expansion is relatively slow compared to the whole complex. This slow expansion is possibly due to newly formed young stars within the cluster. We discuss these results in the context of hierarchical collapse and feedback-induced collapse mode of star formation in the complex.Comment: 23 pages, 15 figures, accepted for publication in Ap

Search for brown dwarfs in IC 1396 with Subaru HSC: interpreting the impact of environmental factors on substellar population

© 2024 The Author(s). Published by Oxford University Press on behalf of Royal Astronomical Society. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/Young stellar clusters are predominantly the hub of star formation and hence, ideal to perform comprehensive studies over the least explored substellar regime. Various unanswered questions like the mass distribution in brown dwarf regime and the effect of diverse cluster environment on brown dwarf formation efficiency still plague the scientific community. The nearby young cluster, IC 1396 with its feedback-driven environment, is ideal to conduct such study. In this paper, we adopt a multiwavelength approach, using deep Subaru HSC along with other data sets and machine learning techniques to identify the cluster members complete down to ∼ 0.03 M⊙ in the central 22 arcmin area of IC 1396. We identify 458 cluster members including 62 brown dwarfs which are used to determine mass distribution in the region. We obtain a star-to-brown dwarf ratio of ∼ 6 for a stellar mass range 0.03–1 M⊙ in the studied cluster. The brown dwarf fraction is observed to increase across the cluster as radial distance from the central OB-stars increases. This study also compiles 15 young stellar clusters to check the variation of star-to-brown dwarf ratio relative to stellar density and ultraviolet (UV) flux ranging within 4–2500 stars pc−2 and 0.7–7.3 G0, respectively. The brown dwarf fraction is observed to increase with stellar density but the results about the influence of incident UV flux are inconclusive within this range. This is the deepest study of IC 1396 as of yet and it will pave the way to understand various aspects of brown dwarfs using spectroscopic observations in future.Peer reviewe

Characterization of graphite deposits of Arunachal pradesh

Graphite, being one of the important non-ferrous minerals and having applications in various important industries, will find increased consumption in the coming years. Graphite, a mineral of pure carbon, is one of the most versatile elements in industry, because of its varying physical properties and characteristics. It is a crystalline form of carbon and a good conductor of heat and electricity and a good lubricant. It is also used in nuclear reactor as moderator. India has a large deposition of graphite minerals out of which about 43% are found in Arunachal Pradesh. However, compared to the rest of the country, the North-East Region and particularly Arunachal Pradesh has not attracted attention till date for detail investigation for characterization, beneficiation, prospecting and/or exploitation of the mineral resources including graphite. Bulk graphite sample were collected from different location of Arunachal Pradesh were crushed to all below 12 mm size. A representative sample was obtained by quartering and coning of the entire crushed sample, was subjected to sieving to obtain different size fractions of the graphite sample. The carbon content of the representative graphite sample was found to be 7–16% by CHN analysis of the different locations. The chemical analysis result shows that the fixed carbon content of the graphite sample found to be 5–10%. The chemical analysis, powder XRD and FTIR characterization indicated the presence of the silica, aluminium oxide, iron oxide, Ca, Mg etc in the raw graphite sample collected from Arunachal Pradesh

Characterization and ion specificity of the iron ore beneficiation waste

Low-grade iron ore fines and slime contain ~ 58% iron and high amount of alumina containing gangue minerals. Beneficiation of low-grade iron ore fines and slime using surface-active agent produces a reasonably stable suspension. To recover water from the suspension and to reduce the volume of the tailing pond, flocculation of suspended gangue minerals is essential. The gangue minerals in the dispersed phase were characterized by XRD and FTIR and found to be chlorite, kaolinite, hematite, goethite, aluminosilicate minerals as major phases. The influence of inorganic anions (Cl−, I−, and SO42−) and divalent cations (Ca2+) on the zeta potential and the isoelectric point of dispersed phase of iron ore slime in aqueous medium have been studied. The ion specificity an ubiquitous phenomena has been observed in the beneficiation waste

Testing the role of environmental effects on the initial mass function of low-mass stars

International audienceIn the star-formation process, the vital impact of environmental factors such as feedback from massive stars and stellar density on the form of the initial mass function (IMF) at the low-mass end is yet to be understood. Hence a systematic highly sensitive observational analysis of a sample of regions under diverse environmental conditions is essential. We analyse the IMF of eight young clusters (g) range ~6-12 kpc along with the nearby cluster IC 348 using deep near-IR photometry and Gaia DR2. These clusters are embedded in massive stellar environments of radiation strength $\log(L_\mathrm{FUV}/\mathrm{L}_{\odot })\, \sim 2.6$-6.8, $\log(L_\mathrm{EUV})\, \sim$ 42.2-50.85 photon s-1, with stellar density in the range of ~170-1220 star pc-2. After structural analysis and field decontamination we obtain an unbiased uniformly sensitive sample of pre-main-sequence members of the clusters down to the brown-dwarf regime. The lognormal fit to the IMF of nine clusters gives the mean characteristic mass (mc) and σ of 0.32 ± 0.02 M⊙ and 0.47 ± 0.02, respectively. We compare the IMF with that of low- and high-mass clusters across the Milky Way. We also check for any systematic variation with respect to the radiation field strength and the stellar density as well with Rg. We conclude that there is no strong evidence for an environmental effect in the underlying form of the IMF of these clusters

Testing the role of environmental effects on the Initial Mass Function of low mass stars

In star formation process, the vital role of environmental factors such as feedback from massive stars and stellar density on the form of the Initial Mass Function (IMF) at low-mass end is yet to be understood. Hence a systematic, high sensitive observational analysis of a sample of regions under diverse environmental conditions is essential. We analyse the IMF of eight young clusters ($<$5 Myr) namely IC1848-West, IC1848-East, NGC1893, NGC2244, NGC2362, NGC6611, Stock8 and Cygnus OB2 which are located at the Galactocentric distance ($R_g$) range $\sim$6-12 kpc along with nearby cluster IC348 using deep near-IR photometry and Gaia-DR2. These clusters are embedded in massive stellar environments of radiation strength $log(L_{FUV}/L_{\odot})$ $\sim$2.6 to 6.8, $log(L_{EUV})$ $\sim$42.2 to 50.85 photons/s, with stellar density in the range of $\sim$170 - 1220 stars/pc$^2$. After structural analysis and field decontamination we obtain an unbiased, uniformly sensitive sample of Pre-Main Sequence members of the clusters down to brown-dwarf regime. The log-normal fit to the IMF of nine clusters gives the mean characteristic mass ($m_c$) and $\sigma$ of 0.32$\pm$0.02 $M_\odot$ and 0.47$\pm$0.02, respectively. We compare the IMF with that of low and high mass clusters across the Milky Way. We also check for any systematic variation with respect to the radiation field strength, stellar density as well with $R_g$. We conclude that there is no strong evidence for environmental effect in the underlying form of IMF of these clusters.Comment: Accepted for publication in Monthly Notices of Royal Astronomical Society (MNRAS). 27 pages, 24 figures, 4 table

Kinetics and Adsorption Behavior of the Methyl Blue at the Graphene Oxide/Reduced Graphene Oxide Nanosheet–Water Interface: A Comparative Study

The adsorption behavior of the methyl blue dye molecule, a mutagenic agent onto the graphene oxide (GO) and reduced graphene oxide (rGO) nanosheets, has been investigated at different pH values, adsorption times, temperatures, and also in the presence of different ions like Na⁺, Ca²⁺, Mg²⁺, and SO₄^2–. A green solution chemistry approach has been adopted for the synthesis of rGO where ascorbic acid is used as a reducing agent under ultrasonication. A kinetic investigation has revealed that adsorption of methyl blue at the GO/rGO nanosheets–water interface follows linear pseudo second-order kinetics. The endothermic and spontaneous nature of the adsorption process was ascertained by the thermodynamic parameters such as Gibbs free energy change (Δ<i>G</i>°), enthalpy change (Δ<i>H</i>°), and entropy changes (Δ<i>S</i>°). The adsorption density of methyl blue at the GO nanosheet–water interface increases with increasing pH of the medium, while it decreases at the rGO nanosheet–water interface. Such results indicates that methyl blue interacts with GO nanosheets mainly by its positively charged (N⁺H) group, while with rGO nanosheets interact by its negatively charged SO₃^– groups. The influence of presence of different monovalent and divalent ions like Na⁺, Ca²⁺, Mg²⁺, and SO₄^2– on the adsorption density of the methyl blue onto the GO and rGO nanosheets was also investigated. The mechanism of the adsorption process was finally investigated by diffuse reflectance infrared Fourier transform (DRIFT) spectra of GO and rGO nanosheets before and after adsorption of methyl blue dye molecule

Titania supported bio-derived activated carbon as an electrode material for high-performance supercapacitors

Supercapacitors are promising energy storage devices compared to batteries due to their long cycle life and high-power density. In this work, we report a supercapacitor based on Titania supported bio-derived activated Carbon with high power density. The composite electrode material shows an initial specific capacitance of 214 F g−1 at 1 A g−1 and exhibits 92% of capacitance retention for 5000 cycles in 1 M Na2SO4 solution. The enhanced electrochemical performance is due to the synergistic effect of the electric double-layer capacitance behavior of carbon and the pseudo-capacitive nature of Titania. An energy density of 29.72 and 20 Wh kg−1 can be achieved at a power density of 499 and 4000 W kg−1, respectively. The supercapacitor based on TiO2 based intercalation compounds provides significantly high energy at the expense of power, which may be appropriate for several applications. © 202