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This study addresses the research gap regarding using natural fibre-reinforced polymers (FRPs) to construct hybrid Double-Skin Tubular Columns (DSTCs). Experimental testing on twelve rectangular specimens revealed critical failure mechanisms primarily due to the rupture of FRP tubes under excessive stress. This rupture led to the loss of lateral support for the concrete, resulting in severe crushing and localized buckling of the inner steel tube. The experimental results also showed an 18% increase in axial stress and 18 times enhancement in axial strain within confined concrete specimens compared to unconfined concrete specimens because of the effective confinement provided by the outer natural FRP tube (hemp fibre). By integrating experimental and nonlinear finite element simulations, this study highlights the structural performance of these hybrid DSTCs under axial compression, with an average deviation of 1% at the peak axial load, demonstrating the effectiveness of the numerical simulation model. Additionally, a parametric study using validated nonlinear finite element analysis (NLFEA) models to investigate the influence of outer tube cross-sectional aspect ratio, inner steel tube shape, and outer FRP tube thickness on the confined concrete in rectangular DSTCs has been carried out. The finding highlighted that rectangular DSTCs with thicker FRP tubes exhibit higher ultimate axial stress and strain in the confined concrete. Moreover, rectangular DSTCs with square inner steel tubes showed notably lower ultimate axial stress and strain in the confined concrete than rectangular DSTCs with circular inner steel tubes. This comprehensive study emphasizes the importance of stress–strain models, offering valuable insights for the design and construction of hybrid rectangular DSTCs.

Understanding the relationship between a polypeptide sequence and its phase separation has important implications for analysing cellular function, treating disease and designing novel biomaterials. Several sequence features have been identified as drivers for protein liquid–liquid phase separation (LLPS), schematized as a ‘molecular grammar’ for LLPS. Here we further probe how sequence modulates phase separation and the material properties of the resulting condensates, targeting sequence features previously overlooked in the literature. We generate sequence variants of a repeat polypeptide with either no charged residues, high net charge, no glycine residues or devoid of aromatic or arginine residues. All but one of 12 variants exhibited LLPS, albeit to different extents, despite substantial differences in composition. Furthermore, we find that all the condensates formed behaved like viscous fluids, despite large differences in their viscosities. Our results support the model of multiple interactions between diverse residue pairs—not just a handful of residues—working in tandem to drive the phase separation and dynamics of condensates.

The last decade has witnessed significant progress towards zero-emission electric aviation. Lithium-ion batteries are at the centre of this technological transformation. However, electric flight requires suitable considerations for safety concerns associated with Lithium-ion batteries. Fault diagnostic approaches aimed at validating the safety of batteries before every flight have emerged as an attractive prospect. In this pursuit, a three-paper series proposing a novel fault diagnosis algorithm is presented. The algorithm is capable of diagnosing faults in an aircraft battery using the data collected during charging and was previously validated for a particular cell type under steady charging conditions. In this paper, two extensional aspects of the algorithm are investigated: cell-to-cell transferability and disparate charging conditions. While crucial for practical implementation, these aspects were overlooked in previous literature. Through experiments conducted at module-level, it was revealed that the algorithm could diagnose faults for a different cell type with minimal preliminary cell-level characterisation, thus demonstrating its ease of transferability. Moreover, modifications introduced in the algorithm enabled it to perform fault diagnosis under unsteady charging conditions for an aerospace module despite significant internal temperature gradients. Thus, the successful working of the algorithm in the considered aspects, which are unprecedented in literature, prove its feasibility for real-life application.

Solid-state batteries with lithium metal anodes present the highest energy density batteries for applications in electric vehicles, leading to massive R&D investments over the past decade. Although most research focuses on preventing lithium metal dendrites that eventually short the battery, the nature of these shorts remains elusive. Soft-shorts, in particular, receive little attention or are not recognized, even in published data. Here, we present a comprehensive outline of the detection and analysis of soft-shorts in solid-state lithium metal cells with composite polymer electrolytes as well as a fundamental understanding of the dynamics of soft-shorts. Transient un-shorting of soft-shorts that occurs on the micro-to-millisecond timescale—driven by joule heating, chemical reactivity, and other processes—limits one’s ability to determine whether the cell was or is still shorted. We provide numerous experimental methods to detect and analyze soft-shorts in any battery type as a resource to all battery researchers.

Challenged networks (CNs) contain resource-constrained nodes deployed in regions where human intervention is difficult. Opportunistic networks (OppNets) are CNs with no predefined source-to-destination paths. Due to their inherent properties, CNs and OppNets are highly susceptible to black-hole (BH) attacks, resulting in degraded packet-delivery ratio. In this work, an ML-based trust prediction model (MLTPM) is proposed to identify potential BH nodes in OppNets. MLTPMuses a novel function to calculate the total-trust-value (TTV) of each node. Intelligent TrustBoxesare introduced in the network to identify possible BH nodes, using TTV, along with five more node-behaviour features. TrustBoxesreduce the computational overhead of the resource-constrained nodes. Three simulated scenarios are compared - no detection, non-ML-based detection, and MLTPM, each using epidemic, prophet, and spray-and-wait routing protocols. MLTPMperforms best with spray-and-wait, exhibiting about 25.21% and 80% mean improvement in delivery-ratio and dropped-message numbers respectively, compared to non-ML-based detection. An overall 12.62% improvement in delivery-ratio and 26.7% improvement in dropped messages is observed using MLTPM, compared to the above-mentioned scenarios.

Introduction: Osteoarthritis of the knee is a leading cause of disability and is a multi-factorial disease. Moreover, it is partly considered a mechanically driven disease in which higher abnormally disbursed forces play a prime role. With the progression of the disease, the gait function declines, so a comprehensive and objective evaluation of gait function would help in prognostic evaluation and management. Materials and Methods: This study included two groups: patients with primary knee osteoarthritis and a control group of healthy volunteers. Gait analysis and functional knee scores were evaluated for all the subjects. The KOOS score, temporal parameters excluding the step length, and spatial parameters excluding the stance phase percentage were evaluated for an individual as a whole. The KSS score, kinetic parameters, kinematic parameters, step length, and stance phase percentage were calculated for each knee separately. Each knee of the patient and controls was taken as 1 sample and categorized as per Kellgren–Lawrence score. An asymptomatic control group of subjects were included in group A. Symptomatic patients with KL grades 1, 2 were included in group M, and those with KL grades 3, 4 were included in group S. The kinetic and kinematic parameters and KSS score were compared among the three groups. Results: A total of 60 subjects were included of which 40 were patients and 20 were controls. In the control group, the age ranged from 22 to 48 years with a mean age of 28.6 years. In the patient group, the mean age was 60.3 years. Patients with knee osteoarthritis were significantly obese with slower walking speed, short stride length, longer stride time, and decreased cadence compared to the asymptomatic group. There was a significant difference in spatiotemporal parameters, functional scores, and kinetic and kinematic parameters among the groups. Conclusion: Various spatiotemporal, kinetic, and kinematic parameters like peak knee flexion angle, abduction/adduction angle, peak knee adduction moment, range of knee flexion, peak knee flexion, and gait deviation index along with functional scores varied significantly with the progression of the disease.

The new Coronavirus, commonly known as Covid-19 or SARS-CoV-2, was identified first in Wuhan, China, in 2019. However, it became a global pandemic within the first few months of 2020. Covid-19 has undergone numerous mutations between then and now, resulting in millions of infections and deaths worldwide. At the same time, the pandemic has created unprecedented global upheavals in every sphere of life. Sadly, any hopes of fully containing Covid-19 have remained uncertain since the pandemic has resurfaced in waves in most countries, demonstrating extreme resilience. As a result, Covid-19s economic burden has grown with each passing day.

Erucic acid, a nano-sized long-chain ω-9-cis-mono-unsaturated 22C fatty acid, is isolable from various plants, especially from the seeds of Brassicaceae (e.g., rape seed or mustard seed). Isolation of erucic acid has recently been reported by us from the pseudobulb of Crepidium acuminatum.Herein, we report the first self-assembly of erucic acid in different aqueous binary liquids yielding vesicles. Several microscopic techniques such as scanning electron microscopy, high-resolution transmission electron microscopy, atomic force microscopy, optical microscopy, and X-ray diffraction studies were carried out to characterize the vesicular morphology. Encapsulation of various fluorophores as guests inside the self-assemblies of erucic acid was also demonstrated. The examples of the guests include cationic fluorophores rhodamine B, anionic fluorophore carboxyfluorescein, and cationic fluorescence active anticancer drug doxorubicin. Release of the entrapped fluorophores was demonstrated by treating with a vesicle-rupturing agent Triton X-100. On treatment with a composite of self-assembled erucic acid and curcumin, antibacterial activity was observed for both Gram-positive as well as Gram-negative bacteria. Therefore the vesicular self-assemblies generated from the renewable nano-sized erucic acid are useful for drug delivery applications as well as antibacterial activities with poorly water-soluble drugs.

The current research work is based upon the experimental study of the effect of the use of nano-sized particles of colloidal nano-silica (NS) on various properties of concrete. The concrete mixes are designed by substituting cement with 0.75%, 1.5% and 3% of colloidal NS. The analysis of experimental outcomes of this investigation illustrates that the compressive and tensile strength is enhanced with the increasing NS (%). Moreover, increase in density and decline in volume of voids and water absorption have been found due to the introduction of NS in concrete. Increase in mechanical properties and improved non-destructive test results indicates the qualitative improvement in concrete owing to the incorporation of NS. However, the inclusion of NS has no substantial impact on modulus of elasticity of concrete.

Accurate positioning of the flexible links is a major challenge for a flexible link manipulator because of the presence of vibration, model uncertainty, and external disturbances. In this work a popular robust controller, i.e., sliding mode controller (SMC) has been developed for joint trajectory tracking and vibration reduction of the two-link flexible manipulator. Due to the payload's variability, which makes the issue even more challenging, the mass of the payload has been treated as uncertain. Proof of the matching condition of the uncertain parameter has also been provided. The system's dynamics have been modelled using the Assumed mode method. Closed-loop stability has been verified using the Lyapunov method. Lyapunov-based controller (LBC) has also been developed for comparison purposes. Payload has been varied to show the effectiveness of the developed controller. The simulation results have exhibited better performance of the SMC over the LBC.

The successful integration of Li-ion batteries in the automotive industry paved the way for their integration into a new generation of aircraft with zero emission. However, potential hazards associated with Li-on batteries are a major concern for the safety-critical aerospace sector. Removing or reducing the hazards from Li-ion batteries while preferable, requires fundamental changes to the battery chemistry. Another way to address this is the implementation of fault diagnostics and prognostics for forecasting or detecting the presence of faults before an aircraft is airborne. This article, part of a three-part series, presents a novel algorithm exploiting the data collected while charging a battery pack for diagnosing faults. The algorithm works off-board, thus not adding any computational burden or weight to the aircraft while minimising aircraft turn-around time, which is crucial for commercial flight operation. This paper presents the underlying method of the algorithm involving the computation of resistance, charge energy and incremental capacity curve using the charging data followed by a combined horizontal and vertical comparative scheme for diagnosis of faults. The performance of the proposed algorithm was validated via module-level experiments considering three cell inactivation faults. Results indicated that the algorithm successfully segregated faulty and unfaulty cells in multiple test scenarios with different number of faults in a laboratory-assembled module. Upon testing the algorithm in experiments conducted using a real-life aerospace battery module, there was a slight reduction in the performance, attributed to greater thermal variation. Nevertheless, the results indicated promising prospects for practical implementation in eVTOL batteries.

This paper presents the design of the Two-Degree-of-Freedom (2DOF) based Model Reference Adaptive Control (MRAC) as a tracking control system for the Non-minimum Phase (NMP) system. Perfect set point tracking is possible by using a cascade-connected inverse and non-inverse transfer function model of the dynamic system. But this method is restricted to the minimum phase system only, whereas, NMP system produces unbounded output response using this inverse model technique. Though, adaptive inverse feed-forward control technique is an effective tracking control system, it also requires an inverse model of the system. To overcome this problem, a novel feed-forward MRAC scheme for the inverse NMP model and the State feedback controller of the non-inverse model has been proposed, and both the controller are decoupled in a 2DOF framework. The feed-forward control technique guaranteed the tracking performance using the Lyapunov stability theory, and the feedback counterpart enhances the steady-state performance of the NMP plant. The robustness of the asymptotic stability as well as tracking performance of the closed-loop NMP system has been ensured by the proposed 2DOF control based MRAC technique. The effectiveness of the proposed control structure initially has been verified by the MATLAB Simulink toolbox and, then the demand has been strengthened by the implementation of the same control logic in the real-time environment using analog simulation with Op-amp based hardware model.

In the present study, we evaluate spatial cost of living and welfare indices for various states of India based on linear as well as price-independent generalised logarithmic cost functions. We compare the values of the indices as well as examine their correlations and find that there is significant difference among them and, hence, are not substitutable. We implement cluster analysis on constructed indices to club states and Union territories of India. We find that such clusters are closely linked to their per capita output.JEL Codes:C43, C50, R11, R12, D12, D63, D61, D65

Composite polymer electrolytes (CPEs) are attractive materials for solid-state lithium metal batteries, owing to their high ionic conductivity from ceramic ionic conductors and flexibility from polymer components. As with all lithium metal batteries, however, CPEs face the challenge of dendrite formation and propagation. Not only does this lower the critical current density (CCD) before cell shorting, but the uncontrolled growth of lithium deposits may limit Coulombic efficiency (CE) by creating dead lithium. Here, we present a fundamental study on how the ceramic components of CPEs influence these characteristics. CPE membranes based on poly(ethylene oxide) and lithium bis(trifluoromethanesulfonyl)imide (PEO-LiTFSI) with Li7La3Zr2O12(LLZO) nanofibers were fabricated with industrially relevant roll-to-roll manufacturing techniques. Galvanostatic cycling with lithium symmetric cells shows that the CCD can be tripled by including 50 wt % LLZO, but half-cell cycling reveals that this comes at the cost of CE. Varying the LLZO loading shows that even a small amount of LLZO drastically lowers the CE, from 88% at 0 wt % LLZO to 77% at just 2 wt % LLZO. Mesoscale modeling reveals that the increase in CCD cannot be explained by an increase in the macroscopic or microscopic stiffness of the electrolyte; only the microstructure of the LLZO nanofibers in the PEO-LiTFSI matrix slows dendrite growth by presenting physical barriers that the dendrites must push or grow around. This tortuous lithium growth mechanism around the LLZO is corroborated with mass spectrometry imaging. This work highlights important elements to consider in the design of CPEs for high-efficiency lithium metal batteries.

The lithium metal–solid-state electrolyte interface plays a critical role in the performance of solid-state batteries. However, operando characterization of the buried interface morphology in solid-state cells is particularly difficult because of the lack of direct optical access. Destructive techniques that require isolating the interface inadvertently modify the interface and cannot be used for operando monitoring. In this work, we introduce the concept of thermal wave sensing using modified 3ω sensors that are attached to the outside of the lithium metal–solid-state cells to noninvasively probe the morphology of the lithium metal–electrolyte interface. We show that the thermal interface resistance measured by the 3ω sensors relates directly to the physical morphology of the interface and demonstrates that 3ω thermal wave sensing can be used for noninvasive operando monitoring the morphology evolution of the lithium metal–solid-state electrolyte interface.

We report here the hot carrier (HC) cooling time scales within polyhedral CsPbBr3nanocrystals (NCs) characterized by different numbers of facets (6 to 26) utilizing a femtosecond upconversion setup. Interestingly, the observed cooling time scale slows many-fold (>10 times) upon opening the new facets on the NC surface. Furthermore, a temperature-dependent study reveals that cooling in multifaceted NCs is polaron mediated, where newly opened polar facets and the soft lattice of CsPbBr3NCs play pivotal roles. Our hallmark result of slow cooling in polyhedral NCs renders an excellent opportunity for harvesting high-energy carriers by a carefully chosen molecular system. To this end, employing the hole scavenger molecule aniline, we successfully extracted hot holes from optically pumped NCs. We believe that several intriguing properties of the polyhedral NCs, including rapid polaron formation, defect-tolerant nature, and the capability of soft lattice to support slow diffusion of charge carriers, resulted in decelerated cooling.

In this study, the internal temperature of commercially available 21,700-format cylindrical lithium-ion cells is in-situ monitored during three different abuse test conditions. Three typical abuse conditions, namely, nail penetration, over-temperature, and overcharge, were adopted to trigger the cells to thermal runaway. In the nail penetration and over-temperature tests, where the cells underwent thermal runaway, the peak difference between the cell core and surface temperature reached up to 186.6 °C and 331.8 °C respectively. Temperature differences up to 36.7 °C were observed in the overcharge tests, where the cell's internal protection devices prevented thermal runaway. After the abuse tests, post-mortem X-ray CT scans were used to investigate the cell structural integrity, including sidewall ruptures, active material ejection and jelly roll deformation. This study highlights that the core temperatures measured by embedded sensors are significantly higher than the cell surface during thermal runaway. In addition, the core-surface temperature difference is dependent on the triggering mechanisms and propagation of thermal runaway.

•Rectangular zigzag-shaped double lid-driven cavity with hot circular cylinders insertion improves heat dissipation efficiency by approximately 60.4 %.•To enhance dissipate heat effectively for preventing overheating of components like data centers, CPUs, GPUs, and power electronics.•Thermal efficiency can be improved increasing the value of Riand Reinserting hot obstacles.

•Nanoparticles improve heat transfer by up to 7 % in specific conditions.•Higher magnetic forces reduce heat transfer by nearly 30 %.•Nanofluids help reduce energy loss, making the system more efficient.•Adding nanoparticles to fluids can make heat flow more evenly and reduce disturbances.•The study identifies key factors that optimize energy efficiency in heat systems.

The efficiency of electric vehicle battery packs is dependent upon the quality of the lithium-ion cell to busbar connection. The busbars of battery packs are increasingly being constructed using aluminium alloys. Laser welding method is gaining popularity to weld busbars to cell terminals, but it requires a comprehensive evaluation. In literature, weld resistance and thermal behaviour are assessed separately from mechanical strength to evaluate joint performance. However, joint resistance and temperature in the absence of external mechanical loading are not representative of in-service loading which may promote failure of the weld between the busbar and terminal. This paper presents a novel evaluation system (real-time) that simultaneously measures resistance, temperature and mechanical strength for lap-shear and torsion joint configurations. In this approach, the weld is subjected to a continuous loading and resistance and temperature are measured. The real-time change in resistance and temperature was monitored continuously from zero to until the load dropped to 80 % of the peak value at different current amplitudes (i.e. 100 A, 150 A, and 200 A). A resistance increase of approximately 51 %, 62 %, and 71 % was observed at the end of the test for 100 A, 150 A and 200 A currents in lap joint samples, while a resistance change of 28 %, 45 %, and 60 % was observed in torsion test samples. In addition, the temperature captured at peak load for 200 A was around 146 % higher than the initial value for the lap shear sample and 139 % higher for the torsion test sample.

•Identification of biomarkers: Thymol and N-acetylglutamate downregulation, and Betaine and histamine upregulation, serve as indicative biomarkers of susceptibility and potential defense mechanisms in rice against M. graminicolainfection.•Pathway analysis: phenylpropanoid biosynthesis and nicotine/nicotinamide biosynthesis pathways emerge as crucial regulators of susceptibility, shedding light on metabolic pathways essential for modulating rice response to nematode invasion.•Implications for breeding programs: insights from this study provide promising targets for enhancing rice resistance through breeding programs, emphasizing the significance of targeted metabolomic approaches in developing resistant rice varieties against biotic stressors.

Jute retting is a process of bio-degradation of non-cellulosic materials primarily pectin and xylan by the enzymatic action of microbes present in retting water to get the jute fibre. The present study focused on the assessment of three improved retting methods comparing with the conventional retting method of jute for identification of the appropriate retting method which can be acceptable to the majority of the jute growers facing water scarcity and irregular rainfall pattern during the retting period. The jute retting with free-flowing water and conventional retting method of jute required 7135 and 25,840 L of water, respectively, for per quintal dry jute fibre production indicating the superiority of the former. The fibre recovery of the jute retting method with free-flowing water was significantly higher by 6.0, 7.5 and 22.4%, respectively, over in situ retting, retting in concrete retting tank using stagnant water and conventional retting methods. The post-retting water quality characteristics like EC (0.54 dS/m), Ca2++ Mg2+(35.8 mg/L), BOD (biological oxygen demand) (45.1 mg/L), COD (chemical oxygen demand) (157.6 mg/L), chloride (4.2 mg/L) and hardness (65 mg/L) content recorded in the jute retting method with free-flowing water were significantly lower compared to other retting methods. The use of microbial retting consortium “CRIJAF SONA” accelerated the biodegradation process of jute by reducing the retting time of 6 to 10 days under improved retting methods besides fibre quality improvement. The higher fibre strength of 26.5 g/tex, the minimum root content (2.3%) and defect content (0.55%) of jute fibre obtained under jute retting method using free-flowing water reflect its supremacy over other retting methods under study. Hence, the jute retting method with free-flowing water may be implemented for the production of superior quality jute fibre considering the non-availability of water or irregular rainfall pattern of the jute-producing belts of South East Asia.

Background: Piston rings are one of the most vital and critical components of ICEs. The purpose of the piston rings is to provide effective sealing so that the heat from the piston can be transferred to the cylinder wall and oil from the crankcase should be kept away from the combustion chamber. The wear of piston rings directly affects the efficiency and performance of the engine. As a result, to diagnose piston rings faults, an effective condition monitoring and fault diagnosis methodology must be adopted. Purpose: In this study, an attempt has been carried out to diagnose piston ring scuffing faults using vibration signature analysis. Methods: An accelerometer sensor was used to collect time domain vibration signals from the healthy and all faulty engine operating conditions. Spectral feature analysis techniques such as the fast Fourier transform (FFT), power spectrum density (PSD), and empirical mode decomposition (EMD) were used to post-process the acquired signals. Further, a neural network technique known as multi-layer perceptron (MLP) was employed to develop the model for the classification of piston ring scuffing faults. In the end, the outcomes of signal processing and machine learning techniques were evaluated for both engine operating conditions. Results: The results showed clear shreds of fault diagnostic information using FFT, PSD, and EMD analyses whereas the MLP technique provided the best neural network architecture with the least mean squared error value. Conclusion: The results obtained using the signal processing techniques can be considered as a reference for the diagnosis of various engine component faults viz. gudgeon pin, gears, bearings, camshaft, etc. Further, the classification models created with these signals may be utilized in the automobile sector to forecast faults in the previously stated engine components.

ABSTRACTThis paper presents a systematic control-oriented uncertainty modelling approach in the Linear Fractional Transformation (LFT) framework of a Multi-Input-Multi-Output (MIMO) mechanical system for designing an H∞controller. A compact modelling structure has been formulated by considering the parametric uncertainties and disturbances to implement robust control law to achieve certain performance specifications. A popular mechanical system, namely, Two-Degree-of-Freedom (2DOF) Mass-Spring-Dashpot (MSD) dynamics system, which is highly oscillatory and implements in many classical control techniques have been considered as a candidate system to formulate proposed control-oriented LFT modelling framework and design H∞controller to verify the effectiveness of the derived modelling structure in a real-time environment. This modelling methodology has been illustrated in the simulation environment and indicating satisfactory robust stability and performance margin of the designed H∞controller. The proposed control strategy is compared with the standard Model Reference Adaptive Control (MRAC) law to express the effectiveness of the controller.

Ti-doped SrCu2O2(TSCO) is prepared using a solid-state chemical reaction and applied as electrochemical pseudocapacitors. Different characterization techniques have been applied to confirm the crystallinity of the prepared TSCO, including an electrochemical test of the synthesized electrode material; TSCO demonstrates specific capacities (Cs) of ca. 1167.6 and 661.8 F/g at a 5 mV s–1scan rate and 0.02 A/g applied current density, respectively, which is greater than those of the undopped SCO. The increment of the specific capacity value can be explained by the insertion of Ti as doped material in the SCO, which simultaneously intensifies the rate of ion intercalation/deintercalation at the time of charging/discharging (CD). Even the cycling establishment for the TSCO is found to be excellent, and there is only a 4.4% decrease after 10 000 CD cycles. Therefore, TSCO will be highly useful to prepare an electrode able to achieve an immense performance for super capacitance energy storage applications.

Zero-dimensional (0D) carbonaceous materials, such as graphene quantum dots (GQDs) and fluorescent carbon dots (FCDs), are in the limelight for their intriguing optical and material properties. Excellent results of initial photophysical studies with these emergent nanodots garnered intense interest among the researchers that suggested an immediate opportunity of replacing cytotoxic fluorescent dyes with carbonaceous dots (CDs) in bioimaging and related applications. Several exciting properties of CDs, including the excitation-dependent multicolor emission, slow carrier cooling, subpicosecond (subps) interfacial charge transfer, and quantum emission, are of paramount importance for various real applications. Despite the initial success, their large-scale implementations in daily life remained challenging, mainly because of several serious issues, including elusive structures (especially for FCDs), the controversial origin of their emissions, and a lack of proper knowledge while correlating an unusual photophysical property to an intrinsic phenomenon. Such limitations not only present hurdles to their practical utilizations but also call into question their real potential. Recent reports have suggested that many of these exciting properties stemmed from external factors like the presence of a molecular impurity, sample heterogeneity (i.e., a mixture of CD subsets with different spectral identities), and the adopted synthesis methodology (i.e., top-down vs bottom-up). Hence, only a rigorous sample purification cannot help in realizing the actual merit of these emergent materials unless a sample-specific synthesis procedure is followed. A combination of both renders the maximum integrity to the CD samples. This review highlights several exciting properties of these coveted materials and how they are disturbed by the parameters discussed above. We further emphasize the actual promises of these materials, as shown by the recent fluorescence-based temporal and spectral studies. The results of these studies are even more fascinating compared to that of inadequately purified samples. Finally, we propose a standard sample purification methodology applicable to all types of carbonaceous materials.

The ASTRI (Astrofisica con Specchi a Tecnologia Replicante Italiana) Project led by the Italian National Institute for Astrophysics (INAF) is developing and will deploy at the Observatorio del Teidea mini-array (ASTRI Mini-Array) composed of nine telescopes similar to the small-size dual-mirror Schwarzschild-Couder telescope (ASTRI-Horn) currently operating on the slopes of Mt. Etna in Sicily. The ASTRI Mini-Array will surpass the current Cherenkov telescope array differential sensitivity above a few tera-electronvolt (TeV), extending the energy band well above hundreds of TeV. This will allow us to explore a new window of the electromagnetic spectrum, by convolving the sensitivity performance with excellent angular and energy resolution figures. In this paper we describe the Core Science that we will address during the first four years of operation, providing examples of the breakthrough results that we will obtain when dealing with current open questions, such as the acceleration of cosmic rays, cosmology and fundamental physics and the new window, for the TeV energy band, of the time-domain astrophysics.

High altitude platform stations (HAPSs) can be installed as flying super macro base stations (SMBSs) to serve the existing terrestrial infrastructure as a flying ad hoc network (FANET) keeping enhanced and continuous wireless network connections in normal and disaster scenarios. This dynamic process becomes inefficient if the mobility and locations of the user equipment (UE) are unknown and uncertain. Although increasing the number of HAPSs provides more user connectivity, it is too expensive and impractical. Hence, installations of the available HAPSs in the optimum positions can solve the problem in cost effective manner. This paper proposes a novel combinational scheme consisting of the two following stages, i.e., the deep learning (DL)-based forecasting of the ground user (GU) locations and the weighted combinatorial optimisation problem (WCOP)-based HAPS-SMBS positioning to optimise the 5G FANET performances in both normal and disaster scenarios.

The wide integration of all battery electric buses (BEB) in the operation of public transit services is identified as one of the most promising means toward decarbonizing public transport systems. In response, public bus transit (PBT) and utility grid operators are currently in need of developing analytical techniques that enable them to conduct tradeoff analyses for the many available options of BEBs, charging infrastructure, and their associated system impacts. To that end, this article proposes a systematic and effective technique for feasibility check and configuration design of electrified PBT fleets without the need for the sophisticated optimization toolbox and high performance computing. The configuration design aims at determining the number of BEBs and their on-board battery capacities to meet the PBT prespecified schedule under different sizes of chargers. The proposed model is tailored for BEBs designed to either boost their batteries on-route at intermediate bus stations using fast chargers (opportunity charging) or charge while parked at the depot (in-depot charging). The developed model is also utilized to generate the aggregated power demand profiles of electrified PBT fleets under different charging practices. Based on the generated power demand profile, a lifecycle cost analysis is conducted to compare BEB-based PBT options to their diesel counterparts.

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Next generation lithium ion batteries are expected to demonstrate superior energy and power density with longer cycle life for successful electrification of the automobile, aviation, and marine industries. Adoption of lithium metal anodes with solid electrolytes can help to achieve that goal given that the dendrite related issues are solved eventually. Another possibility is to use Ni-rich high capacity NMC cathode materials with liquid and/or solid electrolytes, which presently experiences rapid capacity fade while charged to higher voltages. Several mechanical and chemical degradation mechanisms are active within these NMC based cathode particles. Recent experimental research activities attempted to correlate the mechanical damage with the capacity fade experienced by Ni-rich NMC cathodes. A computational framework is developed in this study capable of quantifying the evolution of inter primary particle and cathode/electrolyte interfacial fracture experienced by the poly and single crystalline NMC cathodes during charge/discharge operation. Influence of mechanical degradation on the overall cell capacity, while operating with liquid and/or solid electrolytes, are successfully characterized. Decreasing the size of the cathode primary particles, or the size of the single crystalline cathodes, can mitigate the overall mechanical degradation, and subsequent capacity fade, experienced by NMC cathodes. The developed theoretical methodology can help the engineers and scientists to better understand the mechanical degradation mechanism prevalent in Ni-rich NMC cathodes and build superior lithium ion based energy storage devices for application in next generation devices.

In this work, ultrasound-assisted synthesis of TiO2nanoparticles in a water-in-oil emulsion in a minireactor has been introduced. For this, a lab-scale ultrasound-assisted minireactor system was developed. Experiments were carried out at different precursor solution flow rates, precursor and surfactant concentrations, and minireactor geometries. Lowering the precursor concentration and flow rate significantly decreases the average particle size of TiO2nanoparticles. However, increasing the surfactant concentration decreases the average particle size up to a certain extent after which it increases due to an increase in viscosity of the microemulsion. Also, the use of a spiral tube and straight tube minireactor leads to a lesser average particle size due to efficient mixing characteristics. Results show that these parameters influence the particle size of TiO2nanoparticles. Moreover, ultrasound-assisted synthesis (at an ultrasound frequency of 22 kHz) is able to produce TiO2nanoparticles of significantly reduced size compared to those produced without using ultrasound. This is achieved by intensified dispersion of aqueous droplets in the oil phase and prevention of droplet coalescence, nucleate grouping, and nanoparticle agglomeration due to the cavitational effect of ultrasonication. The lowest average particle size of 20.9 nm of TiO2nanoparticles was obtained at a precursor concentration of 4 vol %, a precursor solution flow rate of 150 mL/h, and a surfactant concentration of 0.006 g/mL using the minireactor of spiral geometry.

Accurate battery modelling requires precise measurements of key battery characteristics, including their surface temperature during fast charging and discharging states. Battery surface temperature measurements are also used to mitigate thermal events such as thermal runaway, which can cause fires. Established literature has shown that there are significant variations in temperature measurements of the surface of lithium-ion cells between various thermocouple sensors, including common K and T-Type thermocouples. In this paper, these variations in temperature measurements are investigated for the first time in the context of battery characterisation. The surface temperatures of two lithium-ion cells, a 21700-model Lithium Nickel Cobalt Aluminium Oxide (NCA) cylindrical cell and a Lithium Titanate Oxide (LTO) pouch cell, are measured during high current cycling using a variety of different thermocouples and an infrared camera to study the variations and response times in the temperature measurements recorded. The impact of electromagnetic fields emitted by the lithium-ion cells on the temperature measurements is also investigated. Results reported indicate a trend in the size of the temperature sensor with the response time of the cell surface temperature measurements. The recommendations of temperature sensors based on these findings allow for improved response time and accuracy of cell surface temperature measurements.

The growing interest in solid-state batteries has resulted in increased focus on the issue of delamination at the cathode/solid-state electrolyte (SSE) interface. The extent of delamination, and its impact on impedance rise and capacity fade, is determined by a number of material properties, including cathode molar volume change and state-of-charge dependence, mechanical properties of the cathode and SSE, SSE grain boundary microstructure, fracture threshold of the interface, and interfacial exchange current density. The goal of this paper is to develop multiscale mathematical models to link these material properties to performance and provide guidance on possible approaches to minimize delamination, impedance rise, and capacity fade. We examine two cathodes, namely, LiNi0.8Mn0.1Co0.1O2with a positive molar volume change and LiCoO2with a negative molar volume change against a Li7La3Zr2O12(LLZO) SSE. Density functional theory (DFT) is used to determine fundamental material properties at the interface, while mesoscale models are used to link these properties to macroscopic performance. Model results suggest that SSEs with smaller grains and low Young’s modulus and cathodes with low molar volume changes provide opportunities for minimizing delamination.

The crystallographic structure and microstructure of solid electrolytes, such as Li7La3Zr2O12(LLZO), have a profound impact on their reactivity, conductivity, and stability toward dendrites in solid-state batteries. Controlling the material’s structure and morphology requires fine control during the synthesis process, where multiple conditions (precursor particle size/distribution, calcination/sintering temperature, ramp rate, etc.) influence performance. This paper describes, for the first time, the operando characterization of the calcination process using synchrotron X-ray diffraction combined with a mesoscale model of grain growth during the calcination and densification of LLZO. The model is then used to guide synthesis conditions to enhance the densification process. The X-ray data reveal significant coarsening of the initial nanophase lanthanum zirconate precursors during conversion to LLZO. The mesoscale model shows that the activation energy for diffusion during calcination is lower than that during sintering, indicating the inherent coupling between the chemical reaction and grain growth processes. Simulations suggest that particles with small and bimodal size distribution experience better densification, as does precise grading (smaller particles near the surface and larger particles at the center) of different-sized particles. The approach described here can be adapted to understand and guide the synthesis of other materials that undergo calcination and sintering (e.g., transition metal oxide cathodes).

This study focuses on tracing the early economic impacts of COVID-19. The pandemic has unleashed a global shock impacting all economies in several ways. The lockdowns have brought economic activity to a standstill, with the closure of businesses and halting of travel, trade and commerce. Even as the impact on sensitive sectors as trade, tourism and remittances are already becoming visible, it is imperative to understand how these are impacting economies in Asia. This article studies these impacts on Thailand and Sri Lanka, both of which being wired to the globalised world, are witnessing adverse impacts on earnings through exports and tourism as well as a huge decline in inward remittances. Even as countries beef up their health infrastructure, they also seek to restart international travel and trade. Hence, the role of the state is critical to pull the economies out of the de-globalisation trends that are expected to gain pace in and beyond 2020.

This study examines the impact of COVID-19 on the migrant workers and remittances flow to Bangladesh, the fastest growing South Asian country. Migrant workers have been playing an important role in propelling the economic activities of the country for a vast majority of the low-income population. Bangladesh is one of the major remittance recipient countries and earned US$21.8 billion in 2020. Over half a million workers from Bangladesh are employed in foreign countries annually, which eases the pressure on the domestic labour market considerably. However, the inflow of these enormous remittances has been encountered by various challenges including the ongoing COVID-19 pandemic, which has brought numerous adverse socio-economic impacts on the migrant workers. Policy recommendations suggest designing and implementing well-coordinated public–private migrant workers’ inclusive policies and creating a supportive environment for the returnee migrant workers to overcome this crisis. Initiating dialogues and negotiation with the employing countries to protect the jobs and workers’ rights can restore the employment and remittances during and after the pandemic, facilitate the expansion of the labour market across borders, and harness the valuable remittances for the overall welfare of the country.

The global spread of the COVID-19 pandemic has had a devastating impact on women: female care workers are at the forefront of the crisis and are facing increased health risks; women are disproportionately affected by the employment drop related to COVID-19 lockdowns and social distancing measures; they are exposed to an alarming increase in domestic violence and are shouldering heavier burdens at home in times of restricted movement. In other words, the COVID-19 pandemic has exacerbated existing gender inequalities and vulnerabilities. While available reports and research crystallise the challenges faced by other vulnerable groups in general, there is a lack of insights to the unique challenges faced by formally employed women while negotiating the dynamics of home during full lockdowns. This lacuna is especially applicable to the Global South, given that the overwhelming majority of available research focuses on Western societies. In this backdrop, this article explores how formally employed women navigated the COVID-19 lockdown in Sri Lanka. A feminist reading of data gathered through a structured online questionnaire from 50 formally employed women as well as 15 men for the purpose of a comparative analysis sheds light on how far and in what ways employed women were able to balance their professional and personal commitments in a time of increased uncertainty and anxiety, while adopting new practices and deploying new skills. The article concludes that in spite of gendered expectations and challenges, employed women have been able to straddle both professional and domestic duties largely due to the unique resources available to them within the South Asian household. In addition, the article observes that the COVID-19 lockdown in Sri Lanka has opened up new spaces and practices that encourage both employers and employees to enable the better reconciliation of personal and professional spheres.

South Asia has emerged as a major challenge in dealing with COVID-19 virus in terms of its demographics, economy, social values, political ambition and geographical location. The pandemic viewed through the prism of non-traditional security (NTS) threat presents new challenges and demands reworking of conventional governance mechanisms. India is the South Asian hegemon, and China is the single largest immediate neighbour with expansionist ambition in the region. Two most populous countries—one has been the epicentre of the virus, while the other is one of the most widely affected. Their public health and governance trajectory during the pandemic and their health diplomacy in the region have overtures for security architecture of South Asia in post-COVID-19 world. A lone statist approach and legal–institutional officialdom fail to appreciate the instrumentalities of an unconventional security threat like COVID-19. This calls for a more inclusive and comprehensive approach to deal with NTS threat, in general, and epidemiological disease, in particular. This by no means indicating a retreat of the state rather a proactive role in articulating interests of more inclusive categories and, in doing so, the state consolidates its role of governance and becomes a significant point of integration.