Showing papers by "Indian Institute of Technology Bombay published in 2021"

Population Properties of Compact Objects from the Second LIGO-Virgo Gravitational-Wave Transient Catalog

Abstract: We report on the population of 47 compact binary mergers detected with a false-alarm rate of 0.01 are dynamically assembled. Third, we estimate merger rates, finding RBBH = 23.9-+8.614.3 Gpc-3 yr-1 for BBHs and RBNS = 320-+240490 Gpc-3 yr-1 for binary neutron stars. We find that the BBH rate likely increases with redshift (85% credibility) but not faster than the star formation rate (86% credibility). Additionally, we examine recent exceptional events in the context of our population models, finding that the asymmetric masses of GW190412 and the high component masses of GW190521 are consistent with our models, but the low secondary mass of GW190814 makes it an outlier.

Observation of Gravitational Waves from Two Neutron Star–Black Hole Coalescences

Abstract: We report the observation of gravitational waves from two compact binary coalescences in LIGO’s and Virgo’s third observing run with properties consistent with neutron star–black hole (NSBH) binaries. The two events are named GW200105_162426 and GW200115_042309, abbreviated as GW200105 and GW200115; the first was observed by LIGO Livingston and Virgo and the second by all three LIGO–Virgo detectors. The source of GW200105 has component masses 8.9−1.5+1.2 and 1.9−0.2+0.3M⊙ , whereas the source of GW200115 has component masses 5.7−2.1+1.8 and 1.5−0.3+0.7M⊙ (all measurements quoted at the 90% credible level). The probability that the secondary’s mass is below the maximal mass of a neutron star is 89%–96% and 87%–98%, respectively, for GW200105 and GW200115, with the ranges arising from different astrophysical assumptions. The source luminosity distances are 280−110+110 and 300−100+150Mpc , respectively. The magnitude of the primary spin of GW200105 is less than 0.23 at the 90% credible level, and its orientation is unconstrained. For GW200115, the primary spin has a negative spin projection onto the orbital angular momentum at 88% probability. We are unable to constrain the spin or tidal deformation of the secondary component for either event. We infer an NSBH merger rate density of 45−33+75Gpc−3yr−1 when assuming that GW200105 and GW200115 are representative of the NSBH population or 130−69+112Gpc−3yr−1 under the assumption of a broader distribution of component masses.

Targeting SARS-CoV-2 spike protein of COVID-19 with naturally occurring phytochemicals: an in silico study for drug development.

Abstract: Spike glycoprotein, a class I fusion protein harboring the surface of SARS-CoV-2 (SARS-CoV-2S), plays a seminal role in the viral infection starting from recognition of the host cell surface receptor, attachment to the fusion of the viral envelope with the host cells. Spike glycoprotein engages host Angiotensin-converting enzyme 2 (ACE2) receptors for entry into host cells, where the receptor recognition and attachment of spike glycoprotein to the ACE2 receptors is a prerequisite step and key determinant of the host cell and tissue tropism. Binding of spike glycoprotein to the ACE2 receptor triggers a cascade of structural transitions, including transition from a metastable pre-fusion to a post-fusion form, thereby allowing membrane fusion and internalization of the virus. From ancient times people have relied on naturally occurring substances like phytochemicals to fight against diseases and infection. Among these phytochemicals, flavonoids and non-flavonoids have been the active sources of different anti-microbial agents. We performed molecular docking studies using 10 potential naturally occurring compounds (flavonoids/non-flavonoids) against the SARS-CoV-2 spike protein and compared their affinity with an FDA approved repurposed drug hydroxychloroquine (HCQ). Further, our molecular dynamics (MD) simulation and energy landscape studies with fisetin, quercetin, and kamferol revealed that these molecules bind with the hACE2-S complex with low binding free energy. The study provided an indication that these molecules might have the potential to perturb the binding of hACE2-S complex. In addition, ADME analysis also suggested that these molecules consist of drug-likeness property, which may be further explored as anti-SARS-CoV-2 agents. Communicated by Ramaswamy H. Sarma.

Arene diversification through distal C(sp2)-H functionalization.

Abstract: Transition metal-catalyzed aryl C-H activation is a powerful synthetic tool as it offers step and atom-economical routes to site-selective functionalization. Compared with proximal ortho-C-H activation, distal (meta- and/or para-) C-H activation remains more challenging due to the inaccessibility of these sites in the formation of energetically favorable organometallic pretransition states. Directing the catalyst toward the distal C-H bonds requires judicious template engineering and catalyst design, as well as prudent choice of ligands. This review aims to summarize the recent elegant discoveries exploiting directing group assistance, transient mediators or traceless directors, noncovalent interactions, and catalyst and/or ligand selection to control distal C-H activation.

A gravitational-wave measurement of the Hubble constant following the second observing run of Advanced LIGO and Virgo

Abstract: This paper presents the gravitational-wave measurement of the Hubble constant (H 0) using the detections from the first and second observing runs of the Advanced LIGO and Virgo detector network. The presence of the transient electromagnetic counterpart of the binary neutron star GW170817 led to the first standard-siren measurement of H 0. Here we additionally use binary black hole detections in conjunction with galaxy catalogs and report a joint measurement. Our updated measurement is H 0 = km s−1 Mpc−1 (68.3% of the highest density posterior interval with a flat-in-log prior) which is an improvement by a factor of 1.04 (about 4%) over the GW170817-only value of km s−1 Mpc−1. A significant additional contribution currently comes from GW170814, a loud and well-localized detection from a part of the sky thoroughly covered by the Dark Energy Survey. With numerous detections anticipated over the upcoming years, an exhaustive understanding of other systematic effects are also going to become increasingly important. These results establish the path to cosmology using gravitational-wave observations with and without transient electromagnetic counterparts.

Upper limits on the isotropic gravitational-wave background from Advanced LIGO and Advanced Virgo’s third observing run

Abstract: We report results of a search for an isotropic gravitational-wave background (GWB) using data from Advanced LIGO’s and Advanced Virgo’s third observing run (O3) combined with upper limits from the earlier O1 and O2 runs. Unlike in previous observing runs in the advanced detector era, we include Virgo in the search for the GWB. The results of the search are consistent with uncorrelated noise, and therefore we place upper limits on the strength of the GWB. We find that the dimensionless energy density Ω GW ≤ 5.8 × 10 − 9 at the 95% credible level for a flat (frequency-independent) GWB, using a prior which is uniform in the log of the strength of the GWB, with 99% of the sensitivity coming from the band 20–76.6 Hz; Ω GW ( f ) ≤ 3.4 × 10 − 9 at 25 Hz for a power-law GWB with a spectral index of 2 / 3 (consistent with expectations for compact binary coalescences), in the band 20–90.6 Hz; and Ω GW ( f ) ≤ 3.9 × 10 − 10 at 25 Hz for a spectral index of 3, in the band 20–291.6 Hz. These upper limits improve over our previous results by a factor of 6.0 for a flat GWB, 8.8 for a spectral index of 2 / 3 , and 13.1 for a spectral index of 3. We also search for a GWB arising from scalar and vector modes, which are predicted by alternative theories of gravity; we do not find evidence of these, and place upper limits on the strength of GWBs with these polarizations. We demonstrate that there is no evidence of correlated noise of magnetic origin by performing a Bayesian analysis that allows for the presence of both a GWB and an effective magnetic background arising from geophysical Schumann resonances. We compare our upper limits to a fiducial model for the GWB from the merger of compact binaries, updating the model to use the most recent data-driven population inference from the systems detected during O3a. Finally, we combine our results with observations of individual mergers and show that, at design sensitivity, this joint approach may yield stronger constraints on the merger rate of binary black holes at z ≳ 2 than can be achieved with individually resolved mergers alone.

Toolbox for Distal C-H Bond Functionalizations in Organic Molecules.

Abstract: Transition metal catalyzed C-H activation has developed a contemporary approach to the omnipresent area of retrosynthetic disconnection. Scientific researchers have been tempted to take the help of this methodology to plan their synthetic discourses. This paradigm shift has helped in the development of industrial units as well, making the synthesis of natural products and pharmaceutical drugs step-economical. In the vast zone of C-H bond activation, the functionalization of proximal C-H bonds has gained utmost popularity. Unlike the activation of proximal C-H bonds, the distal C-H functionalization is more strenuous and requires distinctly specialized techniques. In this review, we have compiled various methods adopted to functionalize distal C-H bonds, mechanistic insights within each of these procedures, and the scope of the methodology. With this review, we give a complete overview of the expeditious progress the distal C-H activation has made in the field of synthetic organic chemistry while also highlighting its pitfalls, thus leaving the field open for further synthetic modifications.

A deep learning framework for building energy consumption forecast

Abstract: Increasing global building energy demand, with the related economic and environmental impact, upsurges the need for the design of reliable energy demand forecast models. This work presents k CNN-LSTM, a deep learning framework that operates on the energy consumption data recorded at predefined intervals to provide accurate building energy consumption forecasts. k CNN-LSTM employs (i) k − means clustering – to perform cluster analysis to understand the energy consumption pattern/trend; (ii) Convolutional Neural Networks (CNN) – to extract complex features with non-linear interactions that affect energy consumption; and (iii) Long Short Term Memory (LSTM) neural networks – to handle long-term dependencies through modeling temporal information in the time series data. The efficiency and applicability of k CNN-LSTM were demonstrated using a real time building energy consumption data acquired from a four-storeyed building in IIT-Bombay, India. The performance of k CNN-LSTM was compared with the k -means variant of the state-of-the-art energy demand forecast models in terms of well-known quality metrics. It is also observed that the accurate energy demand forecast provided by k CNN-LSTM due to its ability to learn the spatio-temporal dependencies in the energy consumption data makes it a suitable deep learning model for energy consumption forecast problems.

Evaluation of 18 satellite- and model-based soil moisture products using in situ measurements from 826 sensors

Abstract: . Information about the spatiotemporal variability of soil moisture is critical for many purposes, including monitoring of hydrologic extremes, irrigation scheduling, and prediction of agricultural yields. We evaluated the temporal dynamics of 18 state-of-the-art (quasi-)global near-surface soil moisture products, including six based on satellite retrievals, six based on models without satellite data assimilation (referred to hereafter as open-loop models), and six based on models that assimilate satellite soil moisture or brightness temperature data. Seven of the products are introduced for the first time in this study: one multi-sensor merged satellite product called MeMo and six estimates from the HBV model with three precipitation inputs (ERA5, IMERG, and MSWEP) and with and without assimilation of SMAPL3E satellite retrievals, respectively. As reference, we used in situ soil moisture measurements between 2015 and 2019 at 5-cm depth from 826 sensors, located primarily in the USA and Europe. The 3-hourly Pearson correlation (R) was chosen as the primary performance metric. The median R ± interquartile range across all sites and products in each category was 0.66 ± 0.30 for the satellite products, 0.69 ± 0.25 for the open-loop models, and 0.72 ± 0.22 for the models with satellite data assimilation. The best-to-worst performance ranking of the four single-sensor satellite products was SMAPL3E, SMOS, AMSR2, and ASCAT, with the L-band-based SMAPL3E (median R of 0.72) outperforming the others at 50 % of the sites. Among the two multi-sensor satellite products (MeMo and ESA-CCI), MeMo performed better on average (median R of 0.72 versus 0.67), mainly due to the inclusion of SMAPL3E. The best-to-worst performance ranking of the six open-loop models was HBV-MSWEP, HBV-ERA5, ERA5-Land, HBV-IMERG, VIC-PGF, and GLDAS-Noah. This ranking largely reflects the quality of the precipitation forcing. HBV-MSWEP (median R of 0.78) performed best not just among the open-loop models but among all products. The calibration of HBV improved the median R by +0.12 on average compared to random parameters, highlighting the importance of model calibration. The best-to-worst performance ranking of the six models with satellite data assimilation was HBV-MSWEP+SMAPL3E, HBV-ERA5+SMAPL3E, GLEAM, SMAPL4, HBV-IMERG+SMAPL3E, and ERA5. The assimilation of SMAPL3E retrievals into HBV-IMERG improved the median R by +0.06, suggesting that data assimilation yields significant benefits at the global scale.

Organic synthesis with the most abundant transition metal–iron: from rust to multitasking catalysts

Abstract: In industries and academic laboratories, several late transition metal-catalyzed prerequisite reactions are widely performed during single and multistep synthesis. However, besides the desired products, these reactions lead to the generation of numerous chemical waste materials, by-products, hazardous gases, and other poisonous materials, which are discarded in the environment. This is partly responsible for the creation of global warming, resulting in climate adversities. Thus, the development of environmentally benign, cheap, easily accessible, and earth-abundant metal catalysts is desirable to minimize these issues. Certainly, iron is one of the most important metals belonging to this family. The field of iron catalysis has been explored in the last two-three decades out of its rich chemistry depending on its oxidation states and ligand cooperation. Moreover, this field has been enriched by the promising development of iron-catalyzed reactions namely, C–H bond activation, including organometallic C–H activation and C–H functionalization via outer-sphere pathway, cross-dehydrogenative couplings, insertion reactions, cross-coupling reactions, hydrogenations including hydrogen borrowing reactions, hydrosilylation and hydroboration, addition reactions and substitution reactions. Thus, herein an inclusive overview of these reaction have been well documented.

Electron and photon reconstruction and identification with the CMS experiment at the CERN LHC

Abstract: The performance is presented of the reconstruction and identification algorithms for electrons and photons with the CMS experiment at the LHC. The reported results are based on proton-proton collision data collected at a center-of-mass energy of 13 TeV and recorded in 2016-2018, corresponding to an integrated luminosity of 136 fb$^{-1}$. Results obtained from lead-lead collision data collected at $\sqrt{s_\mathrm{NN}}=$ 5.02 TeV are also presented. Innovative techniques are used to reconstruct the electron and photon signals in the detector and to optimize the energy resolution. Events with electrons and photons in the final state are used to measure the energy resolution and energy scale uncertainty in the recorded events. The measured energy resolution for electrons produced in Z boson decays in proton-proton collision data ranges from 2 to 5%, depending on electron pseudorapidity and energy loss through bremsstrahlung in the detector material. The energy scale in the same range of energies is measured with an uncertainty smaller than 0.1 (0.3)% in the barrel (endcap) region in proton-proton collisions and better than 1 (3)% in the barrel (endcap) region in heavy ion collisions. The timing resolution for electrons from Z boson decays with the full 2016-2018 proton-proton collision data set is measured to be 200 ps.

Z-scheme photocatalysts for visible-light-driven pollutants degradation: A review on recent advancements

Abstract: Harvesting solar energy for energy and environmental applications is an ever-fascinating field of research. Although semiconductor photocatalysis is the potential tool for recalcitrant degradation, it still suffers from rapid recombination, inability to utilize visible light, and lower photocatalytic performance. Recently, the Z-scheme photocatalysts are becoming research hotspots for their strong redox ability, charge carrier separation, and ability to exploit visible light. This review provides insights into the fundamental mechanism, synthesis strategies, and characterization techniques of Z-scheme photocatalysts. The recent advancements in their applications in visible-light-driven pollutants degradation are also reviewed.

Recent development in transition metal-catalysed C–H olefination

Abstract: Transition metal-catalysed functionalizations of inert C–H bonds to construct C–C bonds represent an ideal route in the synthesis of valuable organic molecules. Fine tuning of directing groups, catalysts and ligands has played a crucial role in selective C–H bond (sp2 or sp3) activation. Recent developments in these areas have assured a high level of regioselectivity in C–H olefination reactions. In this review, we have summarized the recent progress in the oxidative olefination of sp2 and sp3 C–H bonds with special emphasis on distal, atroposelective, non-directed sp2 and directed sp3 C–H olefination. The scope, limitation, and mechanism of various transition metal-catalysed olefination reactions have been described briefly.

LIGO Detector Characterization in the Second and Third Observing Runs

Abstract: The characterization of the Advanced LIGO detectors in the second and third observing runs has increased the sensitivity of the instruments, allowing for a higher number of detectable gravitational-wave signals, and provided confirmation of all observed gravitational-wave events. In this work, we present the methods used to characterize the LIGO detectors and curate the publicly available datasets, including the LIGO strain data and data quality products. We describe the essential role of these datasets in LIGO–Virgo Collaboration analyses of gravitational-waves from both transient and persistent sources and include details on the provenance of these datasets in order to support analyses of LIGO data by the broader community. Finally, we explain anticipated changes in the role of detector characterization and current efforts to prepare for the high rate of gravitational-wave alerts and events in future observing runs.

The 2021 quantum materials roadmap

Abstract: In recent years, the notion of "Quantum Materials" has emerged as a powerful unifying concept across diverse fields of science and engineering, from condensed-matter and cold-atom physics to materials science and quantum computing. Beyond traditional quantum materials such as unconventional superconductors, heavy fermions, and multiferroics, the field has significantly expanded to encompass topological quantum matter, two-dimensional materials and their van der Waals heterostructures, Moire materials, Floquet time crystals, as well as materials and devices for quantum computation with Majorana fermions. In this Roadmap collection we aim to capture a snapshot of the most recent developments in the field, and to identify outstanding challenges and emerging opportunities. The format of the Roadmap, whereby experts in each discipline share their viewpoint and articulate their vision for quantum materials, reflects the dynamic and multifaceted nature of this research area, and is meant to encourage exchanges and discussions across traditional disciplinary boundaries. It is our hope that this collective vision will contribute to sparking new fascinating questions and activities at the intersection of materials science, condensed matter physics, device engineering, and quantum information, and to shaping a clearer landscape of quantum materials science as a new frontier of interdisciplinary scientific inquiry.

Hexafluoroisopropanol: the magical solvent for Pd-catalyzed C-H activation.

Abstract: Among numerous solvents available for chemical transformations, 1,1,1,3,3,3-hexafluoro-2-propanol (popularly known as HFIP) has attracted enough attention of the scientific community in recent years. Several unique features of HFIP compared to its non-fluoro analogue isopropanol have helped this solvent to make a difference in various subdomains of organic chemistry. One such area is transition metal-catalyzed C-H bond functionalization reactions. While, on one side, HFIP is emerging as a green and sustainable deep eutectic solvent (DES), on the other side, a major proportion of Pd-catalyzed C-H functionalization is heavily relying on this solvent. In particular, for distal aromatic C-H functionalizations, the exceptional impact of HFIP to elevate the yield and selectivity has made this solvent irreplaceable. Recent research studies have also highlighted the H-bond-donating ability of HFIP to enhance the chiral induction in Pd-catalyzed atroposelective C-H activation. This perspective aims to portray different shades of HFIP as a magical solvent in Pd-catalyzed C-H functionalization reactions.

Rethinking the study of human–wildlife coexistence

Abstract: Although coexistence with wildlife is a key goal of conservation, little is known about it or how to study it. By coexistence we mean a sustainable though dynamic state in which humans and wildlife coadapt to sharing landscapes, where human interactions with wildlife are effectively governed to ensure wildlife populations persist in socially legitimate ways that ensure tolerable risk levels. Problems that arise from current conflict-oriented framing of human-wildlife interactions include reinforcing a human-nature dichotomy as fundamentally oppositional, suggesting coexistence requires the absence of conflict, and skewing research and management toward direct negative impacts over indirect impacts and positive aspects of living with wildlife. Human behavior toward wildlife is framed as rational calculus of costs and benefits, sidelining emotional and cultural dimensions of these interactions. Coexistence is less studied due to unfamiliarity with relevant methodologies, including qualitative methods, self-reflexivity and ethical rigor, and constraints on funding and time. These challenges are illustrated with examples from fieldwork in India and Africa. We recommend a basic approach to case studies aimed at expanding the scope of inquiries into human-wildlife relations beyond studies of rational behavior and quantification of costs and benefits of wildlife to humans.

A review of thermal management for Li-ion batteries: Prospects, challenges, and issues

Abstract: Li-ion batteries are essential component in the current generation of electric vehicles. However, further pushing electric vehicles are concerned with battery life. Since the temperature dictates battery lifetime, it is crucial to manage the heat and keep the temperature at an acceptable range within the battery pack. The benefit of a cooling system is to prevent the premature degradation of battery life. This paper provides a critical review of the so far thermal management strategy dealing with temperature within the cells, module, and packs. This paper reviews the advantages and disadvantages of state of the art (traditional) thermal cooling system. In this paper, we have reviewed separately cell, module, and pack level cooling system. The battery thermal modeling techniques and cooling system design challenges are also reviewed. This paper also reviews the future cooling system for future vehicles with rising fast charge rate and these techniques can improve the limitations of the traditional cooling system. This paper also suggests the best suitable and economically viable technology for the upcoming EVs issues.