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Synthesis and Optical Properties of Organic‐Inorganic Hybrid [(18‐Crown‐6)K][MoOCl<sub>4</sub>(H<sub>2</sub>O)]
No full textCrown ether anchored organic-inorganic hybrid halides have been recently reported as interesting luminescent materials in the visible region of electromagnetic spectrum. Is it possible to develop such crown ether anchored hybrid materials for near infrared emission? Motivated by this question, we designed a new hybrid material, namely, [(18-Crown-6)K][MoOCl4 (H2O)]. 18-Crown-6 ether bound with K+ form the cationic part [(18-Crown-6)K]+. The K+ of [(18-Crown-6)K]+ electrostatically interacts with Cl− of the anionic part [MoOCl4 (H2O)] -, forming the hybrid crystal [(18-Crown-6)K][MoOCl4 (H2O)]. It crystallizes in orthorhombic crystal system with Pnma space group. The Mo(V) possesses one d-electron (d1) in C4v point group symmetry in the [MoOCl4 (H2O)]− polyhedra. This electronic configuration leads to multiple spin-allowed d – d transitions along with a ligand to metal charge transfer (LMCT) resulting into multiple optical absorption bands in the near UV-visible-near infrared (NIR) region. The lowest energy d -d transition via 2E ( dxz, d1yz )/2E (dxz, d1yz ) → 2B2 ( d1xy ) leads to NIR PL with peak at 952 nm, but with a poor intensity at room temperature
Emerging collective quantum phenomena of excitons in metal-halide perovskites
No full textMetal-halide perovskites (MHPs) with unique electronic and optical properties have emerged as promising materials with a broad spectrum of applications in photovoltaics, optoelectronic, and photonic devices. The distinct properties and tremendous potential of MHPs are intricately defined by excitons and collective quantum states. This article reviews the excitonic states and coordinated interplay of charge, spin, and lattice. We discuss the recent experimental and theoretical discoveries of excitonic phenomena, as well as correlated states involving condensation and cooperative emission. Additionally, our exploration extends to the structural properties of MHPs that facilitate the emergence of robust quantum states, even at room temperatures. Finally, an overview of the remaining challenges and potential applications of MHPs in quantum optics, coherent light sources, electrically driven amplified spontaneous emission, and superfluorescent lasing is provided
Drivers of Widespread Floods in Indian River Basins
No full textWidespread floods affecting multiple subbasins in a river basin have implications for infrastructure, agriculture, environment, and groundwater recharge. However, the crucial linkage between widespread floods and their drivers remains unexplored for Indian subcontinental river basins. Here, we examine the occurrence and drivers of widespread flooding in seven Indian subcontinental river basins during the observed climate (1959–2020). The peninsular river basins have a high probability of widespread flooding, compared to the transboundary basins of the Ganga and Brahmaputra. Favorable antecedent baseflow and soil moisture conditions, uniform precipitation distribution, and precipitation seasonality determine the probability of widespread floods in Indian river basins. The widespread floods are associated with large atmospheric circulations that cause precipitation in a large part of a river basin. Our findings highlight the prominent drivers and mechanisms of widespread floods with implications for flood mitigation in India
Sub-seasonal to seasonal (S2S) prediction of dry and wet extremes for climate adaptation in India
No full textExtreme climatic events have considerable impacts on society, and their prediction is an essential tool for climate change adaptation. A reliable forecast of dry and wet extremes is crucial for developing an early warning system and decision-making in agriculture and water resources. Sub-seasonal to seasonal (S2S) forecasts can be valuable for climate adaptation in water resource and agriculture sectors due to their extended range forecast ability and accessibility of different hydrometeorological products. However, the utility of these S2S models’ forecasting capabilities is limited to a certain lead time, rendering them unsuitable for decision-making. We comprehensively examined the prediction skill of nine global S2S prediction models for precipitation and dry and wet extremes over India during the summer monsoon season (June to September). We find that ECCC, NCEP, and UKMO perform better than the other S2S models in predicting dry and wet extremes during the summer monsoon (June-September) in India. Our findings show that the better-performing S2S forecast models can be used to predict wet and dry extreme events several weeks ahead during the summer monsoon season. The extended range forecast system (ERFS), which is currently operational in India, provides better forecast skills for dry and wet extremes than most of the S2S models. However, S2S models provide an extended lead time forecast compared to ERFS. Therefore, a combination of ERFS and better-performing S2S models can be utilized in the early warning of dry and wet extremes at longer lead times. Practical Implications
India has witnessed climate-related catastrophes over the past few decades that, include flooding and droughts. There is a strong need to develop tools that can provide early warning of weather and climate extremes and help in climate adaptation. Climate services and climate change adaptation need reliable forecast products at seasonal to sub-seasonal scales. Recently, sub-seasonal forecasts bridged the gap between short-range and long-range forecasts and are critical for informed decision-making in India's agricultural and disaster risk reduction sectors. We utilized S2S precipitation forecasts from various forecasting centers around the world to comprehensively examine their utility in India.
Several critical implications are associated with the findings. First, we evaluated the forecasting skill of S2S models in predicting rainfall at different regions and months of the summer monsoon season. The forecast skill of meteorological forecast varies substantially in different regions and lead times. The forecast skill weakens with the increase in forecast lead time. An improved forecast skill during the summer monsoon onset and cessation could be valuable for planning agricultural activities and water resources. In addition, we identify the regions and times where these models do not perform well and where steps can be taken to improve the model’s performances in the future. Second, there is a difference in the forecast skills of S2S models for dry and wet extremes for different regions over India. We identify a set of S2S models that provide better forecast skill for both dry and wet extremes and can be successfully employed in India's S2S operational forecast system as an early warning.
Third, we highlight the advantage of using S2S models over ERFS in forecasting dry and wet extremes in India. ERFS provide good forecast skills for both wet and dry extremes for the Indian region, but a few S2S models provide extended lead forecasts that are currently unavailable in ERFS. Therefore, we demonstrate the potential of S2S forecast information to provide early warning systems. As a result, S2S forecast information can be integrated into a “ready-set-go” framework to provide an early warning of an extreme event a few weeks in advance
Probing the surface of oxide nanoparticles using DNP-enhanced high-resolution NMR of quadrupolar nuclei
No full textThe surfaces of nanomaterials with applications in optoelectronics and catalysis control their physicochemical properties. NMR spectroscopy, enhanced by dynamic nuclear polarization (DNP), is a powerful approach to probe the local environment of spin-1/2 nuclei near surfaces. However, this technique often lacks robustness and resolution for half-integer quadrupolar nuclei, which represent more than 66% of the NMR-active isotopes. A novel pulse sequence is introduced here to circumvent these issues. This method is applied to observe with high-resolution 27Al and 17O spin-5/2 nuclei on the surface of γ-alumina. Moreover, we report high-resolution 17O spectra of ZnO nanoparticles used in optoelectronics. Their assignment using DFT calculations allows the first NMR observation of vacancies near the surfaces. Finally, we employ the introduced NMR technique to observe 11B spin-3/2 nuclei on the surface of partially oxidized boron nitride supported on silica and to distinguish its different BO2OH active sites
Holed up, but thriving: Impact of multitrophic cryoconite communities on glacier elemental cycles
No full textCryoconite holes (water and sediment-filled depressions), found on glacier surfaces worldwide, serve as reservoirs of microbes, carbon, trace elements, and nutrients, transferring these components downstream via glacier hydrological networks. Through targeted amplicon sequencing of carbon and nitrogen cycling genes, coupled with functional inference-based methods, we explore the functional diversity of these mini-ecosystems within Antarctica and the Himalayas. These regions showcase distinct environmental gradients and experience varying rates of environmental change influenced by global climatic shifts. Analysis revealed a diverse array of photosynthetic microorganisms, including Stramenopiles, Cyanobacteria, Rhizobiales, Burkholderiales, and photosynthetic purple sulfur Proteobacteria. Functional inference highlighted the high potential for carbohydrate, amino acid, and lipid metabolism in the Himalayan region, where organic carbon concentrations surpassed those in Antarctica by up to 2 orders of magnitude. Nitrogen cycling processes, including fixation, nitrification, and denitrification, are evident, with Antarctic cryoconite exhibiting a pronounced capacity for nitrogen fixation, potentially compensating for the limited nitrate concentrations in this region. Processes associated with the respiration of elemental sulfur and inorganic sulfur compounds such as sulfate, sulfite, thiosulfate, and sulfide suggest the presence of a complete sulfur cycle. The Himalayan region exhibits a higher potential for sulfur cycling, likely due to the abundant sulfate ions and sulfur-bearing minerals in this region. The capability for complete iron cycling through iron oxidation and reduction reactions was also predicted. Methanogenic archaea that produce methane during organic matter decomposition and methanotrophic bacteria that utilize methane as carbon and energy sources co-exist in the cryoconite, suggesting that these niches support the complete cycling of methane. Additionally, the presence of various microfauna suggests the existence of a complex food web. Collectively, these results indicate that cryoconite holes are self-sustaining ecosystems that drive elemental cycles on glaciers and potentially control carbon, nitrogen, sulfur, and iron exports downstream
Pairs of inner projections and two applications
No full textOrthogonal projections onto closed subspaces of H2 (Dn) of the form H2 (Dn) for inner functions φ on (Dn) are referred to as inner projections, where H2 (Dn) denotes the Hardy space over the open unit polydisc Dn. In this paper, we classify pairs of commuting inner projections. We also present two seemingly independent applications: the first is an answer to a question posed by R. G. Douglas, and the second is a complete classification of partially isometric truncated Toeplitz operators with inner symbols on Dn</SUP
An exactly solvable asymmetric K-exclusion process
No full textWe study an interacting particle process on a finite ring with L sites with at most K particles per site, in which particles hop to nearest neighbors with rates given in terms of t-deformed integers and asymmetry parameter q, where t > 0 and q≥ are parameters. This model, which we call the (q, t) asymmetric simple K-exclusion process (ASEP), reduces to the usual ASEP on the ring when K = 1 and to a model studied by Schütz and Sandow (Phys. Rev. E, 1994) when
. This is a special case of the misanthrope process and as a consequence, the steady state does not depend on q and is of product form, generalizing the same phenomena for the ASEP. What is interesting here is the steady state weights are given by explicit formulas involving t-binomial coefficients, and are palindromic polynomials in t. Interestingly, although the (q, t) K-ASEP does not satisfy particle-hole symmetry, its steady state does. We analyze the density and calculate the most probable number of particles at a site in the steady state in various regimes of t. Lastly, we construct a two-dimensional exclusion process on a discrete cylinder with height K and circumference L which projects to the (q, t) K-ASEP and whose steady state distribution is also of product form. We believe this model will serve as an illustrative example in constructing two-dimensional analogues of misanthrope processes
Data-driven simulation-assisted-Physics learned AI (DPAI) for heat diffusion in large grain polycrystalline materials
No full textIn this paper, we propose Data-driven simulation-assisted Physics-learned Artificial Intelligence (DPAI), a deep-learning algorithm to simulate heat diffusion in large-grain polycrystalline materials. The DPAI model captures the spatio-temporal representation of heat diffusion in the material from input sequences from the training dataset. The training dataset consists of various temperature plots of polycrystalline materials taken from Finite Element (FE) simulations having varying numbers of grains oriented in random directions with a single-point heat source at the center. The arbitrary plane of the 3D microstructure of these materials is represented using 2D Voronoi tessellations. Voronoi configurations are used to model the geometry of the 2D Computer-Aided Design (CAD) model. Each cell of the Voronoi tessellation represents one grain of the microstructure. This CAD model is used as an input to the FE for solving heat diffusion equations. To model the near-realistic material anisotropy and accurately measure temperature differences at cell boundaries, a smaller mesh size is required in FE modeling, which takes considerable solver time. Therefore, the proposed Deep learning model significantly reduces the computational time while maintaining accuracy as compared to conventional numerical techniques. After training, the effectiveness of the trained DPAI model is examined by modeling larger domain problems involving a greater number of grains and varying material properties. The simulation result is qualitatively compared with the experiment. A scaled-up version of the microstructure is represented using Unidirectional Carbon Fiber laminate. The laminate is heated with a point heat source and the temperature plots are captured using Infrared Camera
Significant role of permafrost in regional hydrology of the Upper Indus Basin, India
No full textUpper Indus Basin (UIB), being climatologically sensitive and socio-economically important, has emerged as a hotspot for eco-hydrological studies. Permafrost, one of the essential components of the regional hydrological cycle with a critical role in microclimate, is also an important water resource in the UIB. Despite being an important component of the cryospheric system, permafrost is least studied in the UIB. In present study, we used stable oxygen and hydrogen isotopic composition in supra-permafrost water (SPFW) and aufeis along with precipitation, snowpack, glacier and other groundwaters to assess their variability and estimate their contribution to regional hydrology. The sources are evolving isotopically, depending on physiographic and hydrometeorological factors, with each source attaining different (if not distinct) isotopic signatures. The isotopic signatures (with different ranges) of sources help in estimating the contribution from these sources. A significant altitude gradient of δ18O is observed in stream water, SPFW and other groundwaters. Isotopic composition in SPFW is differentially modulated by fractionation, resulting in isotopic variability from the source waters. The results suggest snowmelt and/or glacier melt as the source of SPFW. To stream flow, SPFW is the dominant contributor (43 ± 18 %) at higher elevations (> 4300 m a.m.s.l.) in July, followed by snowmelt (26 ± 10 %). In September, SPFW contribution decreases (14 ± 8 %), but the contribution from other groundwaters becomes dominant (39 ± 11 %) to stream flow. The results indicate the significant role of seasonal thawing and freezing of active layer on the contribution from SPFW. This study highlights the significant role of permafrost in the hydrological system of the basin. The study also emphasizes the need to understand the dynamics of permafrost, taliks of various types (e.g., supra-permafrost subaerial talik) and active layer under changing climate to define the subsequent implications to regional hydrology, eco-hydrological systems and micro-climate of permafrost regions