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Luminescence characteristics of terrestrial Jarosite from Kachchh, India: A Martian analogue
No full textIn this study, naturally occurring jarosite samples from Kachchh, India (considered to be Martian analogue) were characterized using Fourier Transform Infrared Spectroscopy (FTIR), Cathodoluminescence–Energy Dispersive X-ray Spectroscopy (CL-EDXS), and Luminescence (thermoluminescence [TL], blue and infrared stimulated luminescence [BSL and IRSL]) methods. FTIR and CL-EDXS studies suggested that jarosite preserves its luminescence characteristics even after annealing the samples to 450°C. This facilitated luminescence studies (TL/BSL/IRSL) to assess the potential use of luminescence-dating methods to establish the chronology of jarosite formation or its transport. Jarosite exhibited TL, BSL, and IRSL signals with varied sensitivities. The TL glow curve of jarosite comprised glow peaks at 100, 150, 300, and 350°C, reproducible over multiple readout cycles. The least bleachable TL glow peak at 350°C is reduced to (1/e)th of its glow peak intensity (i.e., 36%) with ~100 min of light exposure under a sunlamp. BSL and IRSL optical decay signals comprised three components. These signals exhibited athermal fading of g ~ 6%/decade, but pIRIR signal at 225°C showed a near zero fading. The saturation doses (2D0) ranged from 700 Gy to 2600 Gy for different signals, which suggests a dating range of ~25 ka using a reported Martian total dose rate of 65 Gy/ka, primarily due to cosmic rays. Multiple TL glow peaks and their widely differing stability also offer promise to discern changes in cosmic ray fluxes over a century to millennia time scale through inverse modeling and laboratory experiments
Constraining scalars of 16H through proton decays in non-renormalisable SO(10) models
No full textNon-renormalisable versions of SO(10) based on irreducible representations with lesser degrees of freedom, are free of running into the catastrophe of non-perturbativity of standard model gauge couplings in contrast to the renormalisable versions having tensors with many degrees of freedom. 16H is the smallest representation, participates in Yukawa Lagrangian at the non-renormalisable level, contributing to the charged and neutral fermion masses, and has six distinct scalars with different B−L charges. We computed the leptoquark and diquark couplings of different pairs of scalars stemming from all possible decomposition of the term resulting from the coupling of 16H with the 16 dimensional fermion multiplet of SO(10), i.e. [Formula presented]. Computing the tree and loop level contribution of different pairs to the effective dimension six, B−L conserving operators, it turns out only three pairs, viz [Formula presented], and [Formula presented], and H−T can induce proton decay at tree level. Assuming that the Yukawa couplings of the 16H are comparable to those of the 126‾H of a realistic SO(10) model and setting the cutoff scale to the Planck scale typically constrains the B−L breaking scale to be 4∼5 orders of magnitude less than the cutoff scale (Λ). Moreover, analysing the branching pattern of the leading two-body decay modes of the proton, we observed a preference for the proton to decay into second-generation mesons due to the hierarchical nature of Yukawa couplings. In a realistic SO(10) scenario, we find that MT>108 TeV, while MΔ could be as light as a few TeVs
Operator growth and Krylov complexity in Bose-Hubbard model
No full textWe study Krylov complexity of a one-dimensional Bosonic system, the celebrated Bose-Hubbard Model. The Bose-Hubbard Hamiltonian consists of interacting bosons on a lattice, describing ultra-cold atoms. Apart from showing superfluid-Mott insulator phase transition, the model also exhibits both chaotic and integrable (mixed) dynamics depending on the value of the interaction parameter. We focus on the three-site Bose Hubbard Model (with different particle numbers), which is known to be highly mixed. We use the Lanczos algorithm to find the Lanczos coefficients and the Krylov basis. The orthonormal Krylov basis captures the operator growth for a system with a given Hamiltonian. However, the Lanczos algorithm needs to be modified for our case due to the instabilities instilled by the piling up of computational errors. Next, we compute the Krylov complexity and its early and late-time behaviour. Our results capture the chaotic and integrable nature of the system. Our paper takes the first step to use the Lanczos algorithm non-perturbatively for a discrete quartic bosonic Hamiltonian without depending on the auto-correlation method. � 2023 Elsevier B.V., All rights reserved
Determination of electron heat flux in the topside ionosphere and its impact on the vertical profile of OI 630.0 nm emission rate during nighttime SAR arcs for different solar activity conditions
No full textElectron heat flux in the ionosphere plays a crucial role in altering the electron temperature and thermal balance of the electron population, especially over subauroral- and high-latitudes. The downward flow of electron heat flux in the subauroral-latitude ionosphere through magnetosphere-ionosphere coupling causes an enhancement in the electron temperature, thereby leading to the formation of Stable Auroral Red (SAR) arcs. Understanding the relationship between heat flux and electron temperature is critical, as no technique exists to measure heat flux directly in the SAR arc region. This study primarily reports the characteristics of thermal electron heat flux of SAR arcs in the sub-auroral ionosphere and its influence on the plasma densities in the inner-magnetosphere and the SAR arc peak emission altitude. The downward electron heat flux has been characterized by using measured atomic oxygen red line emission intensity in conjunction with simultaneous enhancements of electron temperature by in-situ measurements for several nighttime SAR arc events reported in the literature for the period of 2012–2020 of solar cycle-24, and by using GLOW, a physics-based model. The present investigation reveals considerable variation in the estimated heat flux and SAR arc emission altitudes due to the influence of solar activity. This study, thus, quantifies the electron heat flux, averaging 2.89 × 1011 eV-cm−2-sec-1 near solar minimum and 8.05 × 1012 eV-cm−2-sec-1 during solar maximum, associated with ionospheric heating during observations of nighttime SAR arcs and their relevance to space weather phenomena
Inversion of generalized Radon transform over symmetric m-tensor fields in Rn
No full textIn this work, we study a set of generalized Radon transforms over symmetric m-tensor fields in Rn. The longitudinal/transversal Radon transform and corresponding weighted integral transforms for symmetric m-tensor field are introduced. We give the kernel descriptions for the longitudinal and transversal Radon transform. Further, we also prove that a symmetric m-tensor field can be recovered uniquely from certain combinations of these integral transforms of the unknown tensor field. This generalizes a recent study done for the recovery of vector fields from its weighted Radon transform data to recovery of a symmetric m-tensor field from analogously defined weighted Radon transforms
Exploring the complex structure-property landscape in nacre-inspired biomimetic composites
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Liquid-Liquid Phase Separation to Fabricate Microgels of Recombinantly Expressed Proteins
No full textMicrogels, a microscale variant of hydrogels (1–100 µm), exhibit high surface area and responsiveness to external stimuli while retaining the soft, viscoelastic nature of their macroscale counterparts. While microgels can be derived from both synthetic and natural polymers, protein-based microgels offer significant advantages due to their diverse function and activities. However, traditional fabrication methods, such as microfluidics and emulsion-based techniques, often involve trade-offs between scalability, structural integrity, and functionality. To overcome these limitations, liquid-liquid phase separation is leveraged to fabricate microgels using globular supercharged fluorescent protein and a terminal epoxy derivative of PEG polymer – poly(ethylene glycol)diglycidyl ether (PEGDE). The presence of terminal epoxy groups on PEGDE facilitates internal crosslinking with lysine residues of supercharged proteins, resulting in stable microgels. The microgels are characterized with fluorescence microscopy, SEM, and FTIR. Fluorescence recovery after photobleaching experiments suggest the encapsulation of the polymers within the dense phase and are dependent on the polymer chain length. The results are further supported by coarse-grained MD simulations providing mechanistic insights. Finally, the utility of the microgels in dye and nanoparticle adsorption, along with biomineralization of fluorinated calcium phosphate, is shown. These highlight the ability of microgels to potentially open avenues for biomimetic material synthesis
Predicting spatiotemporal concentrations in a multizonal residential apartment using conventional and Physics-informed deep learning approach
No full textMost indoor air pollution studies focusing on modeling and material balance assume well-mixed conditions, which is usually not true in larger and multizonal spaces. Spatially nonhomogenous concentrations can lead to considerably different personal exposure of occupants within the same indoor space. Studying the interzonal transport of pollutants and their governing factors provides critical insights into the fate and transport of pollutants. The current work focuses on predicting PM2.5 and CO2 concentrations in different zones of a residential apartment using measured concentrations in one zone using conventional and physics-informed long short-term memory (PI-LSTM) models for different internal door configurations. Model predictions were validated using experimentally obtained spatiotemporal data sets using the exposure and maximum concentration (relative to measured) as key performance metrics. The PI-LSTM model performed better in most cases for PM2.5, while the LSTM model exhibited better predictive accuracy for CO2 concentrations. As more internal doors were opened and the number of zones increased, PI-LSTM’s predictive accuracy declined. PM2.5 predictions were more accurate for zones near the emission source than those farther away