IITB-Monash Research Academy

This paper surveys current literature on modeling methods, control techniques, protection schemes, applications, and real-world implementations pertaining to grid forming inverters (GFMIs). Electric power systems are increasingly being augmented with inverter-based resources (IBRs). While having a growing share of IBRs, conventional synchronous generator-based voltage and frequency control mechanisms are still prevalent in the power industry. Therefore, IBRs are experiencing a growing demand for mimicking the behavior of synchronous generators, which is not possible with conventional grid following inverters (GFLIs). As a solution, the concept of GFMIs is currently emerging, which is drawing increased attention from academia and the industry. This paper presents a comprehensive review of GFMIs covering recent advancements in control technologies, fault ride-through capabilities, stability enhancement measures, and practical implementations. Moreover, the challenges in adding GFMIs into existing power systems, including a seamless transition from grid-connected mode to the standalone mode and vice versa, are also discussed in detail. Recently commissioned projects in Australia, the UK, and the US are taken as examples to highlight the trend in the power industry in adding GFMIs to address issues related to weak grid scenarios. Research directions in terms of voltage control, frequency control, system strength improvement, and regulatory framework are also discussed. This paper serves as a resource for researchers and power system engineers exploring solutions to the emerging problems with high penetration of IBRs, focusing on GFMIs.

Neurological disorders such as Alzheimer's disease, stroke, and brain cancers are difficult to treat with current drugs as their delivery efficacy to the brain is severely hampered by the presence of the blood-brain barrier (BBB). Drug delivery systems have been extensively explored in recent decades aiming to circumvent this barrier. In particular, polymeric nanoparticles have shown enormous potentials owing to their unique properties, such as high tunability, ease of synthesis, and control over drug release profile. However, careful analysis of their performance in effective drug transport across the BBB should be performed using clinically relevant testing models. In this review, polymeric nanoparticle systems for drug delivery to the central nervous system are discussed with an emphasis on the effects of particle size, shape, and surface modifications on BBB penetration. Moreover, the authors critically analyze the current in vitro and in vivo models used to evaluate BBB penetration efficacy, including the latest developments in the BBB-on-a-chip models. Finally, the challenges and future perspectives for the development of polymeric nanoparticles to combat neurological disorders are discussed.

Automatic sarcasm detection is the task of predicting sarcasm in text. This is a crucial step to sentiment analysis, considering prevalence and challenges of sarcasm in sentiment-bearing text. Beginning with an approach that used speech-based features, automatic sarcasm detection has witnessed great interest from the sentiment analysis community. This article is a compilation of past work in automatic sarcasm detection. We observe three milestones in the research so far: semi-supervised pattern extraction to identify implicit sentiment, use of hashtag-based supervision, and incorporation of context beyond target text. In this article, we describe datasets, approaches, trends, and issues in sarcasm detection. We also discuss representative performance values, describe shared tasks, and provide pointers to future work, as given in prior works. In terms of resources to understand the state-of-the-art, the survey presents several useful illustrations—most prominently, a table that summarizes past papers along different dimensions such as the types of features, annotation techniques, and datasets used.

Aditya Joshi, Vinita Sharma, Pushpak Bhattacharyya. Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers). 2015.

heterostructure diode technologically promising for next-generation optoelectronics.

One-dimensional noble metal nanostructures are important components in modern nanoscience and nanotechnology due to their unique optical, electrical, mechanical, and thermal properties. However, their cost and scalability may become a major bottleneck for real-world applications. Copper, being an earth-abundant metallic element, is an ideal candidate for commercial applications. It is critical to develop technologies to produce 1D copper nanostructures with high monodispersity, stability and oxygen-resistance for future low-cost nano-enabled materials and devices. This article covers comprehensively the current progress in 1D copper nanostructures, most predominantly nanorods and nanowires. First, various synthetic methodologies developed so far to generate 1D copper nanostructures are thoroughly described; the methodologies are in conjunction with the discussion of microscopic, spectrophotometric, crystallographic and morphological characterizations. Next, striking electrical, optical, mechanical and thermal properties of 1D copper nanostructures are highlighted. Additionally, the emerging applications of 1D copper nanostructures in flexible electronics, transparent electrodes, low cost solar cells, field emission devices are covered, amongst others. Finally, there is a brief discussion of the remaining challenges and opportunities.

The incoherence between measurement and sparsifying transform matrices and the restricted isometry property (RIP) of measurement matrix are two of the key factors in determining the performance of compressive sensing (CS). In CS-MRI, the randomly under-sampled Fourier matrix is used as the measurement matrix and the wavelet transform is usually used as sparsifying transform matrix. However, the incoherence between the randomly under-sampled Fourier matrix and the wavelet matrix is not optimal, which can deteriorate the performance of CS-MRI. Using the mathematical result that noiselets are maximally incoherent with wavelets, this paper introduces the noiselet unitary bases as the measurement matrix to improve the incoherence and RIP in CS-MRI. Based on an empirical RIP analysis that compares the multichannel noiselet and multichannel Fourier measurement matrices in CS-MRI, we propose a multichannel compressive sensing (MCS) framework to take the advantage of multichannel data acquisition used in MRI scanners. Simulations are presented in the MCS framework to compare the performance of noiselet encoding reconstructions and Fourier encoding reconstructions at different acceleration factors. The comparisons indicate that multichannel noiselet measurement matrix has better RIP than that of its Fourier counterpart, and that noiselet encoded MCS-MRI outperforms Fourier encoded MCS-MRI in preserving image resolution and can achieve higher acceleration factors. To demonstrate the feasibility of the proposed noiselet encoding scheme, a pulse sequences with tailored spatially selective RF excitation pulses was designed and implemented on a 3T scanner to acquire the data in the noiselet domain from a phantom and a human brain. The results indicate that noislet encoding preserves image resolution better than Fouirer encoding.

Abstract The tremendous impact of UV radiation on every individual has resulted in massive interest in development of new sensor technologies to effectively monitor the solar exposure. However, there is no comprehensive review that critically discusses the advances made in the field of wearable UV sensor technologies and to position them as next‐generation mass‐deployable wearable devices. Herein, this gap is addressed by first classifying UV detection technologies into photoelectric and photochromic systems and summarizing their unique strengths and drawbacks. This is followed by a discussion on the integration of novel materials and design concepts with these technologies to develop wearable UV sensors. Then, the commercially available wearable UV sensors are examined thoroughly together with their limitations. Toward the end, a highly critical future outlook is provided, wherein the role of technological and regulatory interventions in assisting the development and integration of wearable UV sensors in the day‐to‐day activities is discussed. More importantly, the purpose of this review is not only to provide an in‐depth understanding of the underlying UV detection mechanism, design principles, and wearable technologies but also to act as a roadmap for those interested in the development and regulation of commercially deployable wearable UV sensors.

There is a pressing need for high-rate cycling and cost-effective stationary energy storage systems in concomitance with the fast development of solar, wind, and other types of renewable sources of energy. Aqueous rechargeable Ca-ion batteries have the potential to meet the growing demands of stationary energy storage devices because they are abundant and safe; they can also be manufactured at a low-cost and have a higher volumetric capacity. In this study, we have demonstrated a low-cost, safe, aqueous Ca-ion battery that is based on a low potential, lower specific weight, in situ polymerized polyaniline as an anode, and a high redox-potential open-framework structured potassium copper hexacyanoferrate as a cathode. The charge–discharge mechanism of this battery includes doping/dedoping of NO3– at the anode, and intercalation and deintercalation of Ca-ion at the cathode. This Ca-ion battery works successfully in a 2.5 M Ca(NO3)2 aqueous electrolyte that exhibits 70 Wh kg–1 specific energy at 250 W kg–1 and even maintains a high energy density of 53 Wh kg–1 at a higher rate of 950 W kg–1; this indicates a good rate capability (calculation based on anode active mass). At 0.8 A g–1, the battery provides an average specific capacity of 130 mA h g–1, exhibiting high Coulombic efficiency (∼96%), with 95% capacity retention of over 200 cycles across its life span, which is a new achievement in the electrochemical performance of aqueous Ca-ion batteries. Furthermore, the calcium-ion storage mechanism is investigated using high-end X-ray absorption near edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) measurements. Thus, this significant electrochemical performance of the anode and the cathode renders the battery a promising candidate in grid-scale storage applications.

This paper presents an improved method to estimate the available inertia in an islanded AC microgrid. Inertia estimation is carried out based on measured frequency response for any arbitrary disturbance that occurs in the system. Modifications are made to the conventional swing equation-based curve-fitting method to obtain an accurate estimate for a system with high penetration of renewable generations. A polynomial curve fit over the total power generation is introduced to estimate the size of the disturbance accurately. Additionally, a variable order polynomial fit is carried out over the measured frequency, which not only improves the estimate of inertia but also helps to refrain the influence of network topology and size/location of the disturbance. The test microgrid system considered is a modified Standard IEEE distribution network, which consists of radial feeders and distributed generations. Firstly, the proposed method is tested on a system with only synchronous generations to assess the accuracy of the estimate. This is followed by the integration of Type 3 and Type 4 wind turbines, and a PV array within the microgrid system. Virtual inertia control is then implemented in the wind turbines to obtain inertial support. Estimation study of the microgrid system with virtual inertia is then carried out. The developed estimation method can accurately estimate the inertia provided by the synchronous sources within the generation mix. Finally, from all the results and observations, the inertia estimation process in a microgrid system is segregated into synchronous and nonsynchronous inertia estimation.

This work examines the potential of PbZr_0.53Ti_0.47O₃/CoFe₂O₄ (PZT/CFO) multi-layered nanostructures (MLNs) to achieve a giant electrocaloric effect (ECE) and enhanced pyroelectric energy harvesting.

Abstract Layered transition metal dichalcogenides have shown tremendous potential for photodetection due to their non-zero direct bandgaps, high light absorption coefficients and carrier mobilities, and ability to form atomically sharp and defect-free heterointerfaces. A critical and fundamental bottleneck in the realization of high performance detectors is their trap-dependent photoresponse that trades off responsivity with speed. This work demonstrates a facile method of attenuating this trade-off by nearly 2x through integration of a lateral, in-plane, electrostatically tunable p-n homojunction with a conventional WSe 2 phototransistor. The tunable p-n junction allows modulation of the photocarrier population and width of the conducting channel independently from the phototransistor. Increased illumination current with the lateral p-n junction helps achieve responsivity enhancement upto 2.4x at nearly the same switching speed (14–16 µs) over a wide range of laser power (300 pW–33 nW). The added benefit of reduced dark current enhances specific detectivity ( D* ) by nearly 25x to yield a maximum measured flicker noise-limited D* of 1.1×10 12 Jones. High responsivity of 170 A/W at 300 pW laser power along with the ability to detect sub-1 pW laser switching are demonstrated.

Synthesis of shape-controlled nanoparticles of precious metals with defined size is well-established in the literature and the control over shape and size is achieved using surfactants and capping agents. However, a clean surface without impurities is required for realistic applications. In the present investigation, palladium nanocubes are synthesized using poly(vinylpyrrolidone) and potassium bromide. A novel method for cleaning the nanoparticle surface, i.e., treatment with tert-butylamine is reported. For comparison, a part of the untreated sample is subjected to the commonly used method of heat-treatment in an oxygen atmosphere for surface cleaning. The XPS and FTIR spectra of the heat-treated sample show incomplete removal of PVP and complete removal of Br− and the XRD pattern suggests oxide formation on the Pd surface. Treatment with tert-butylamine provides a clean surface free of PVP and Br−. Cleanliness of the surface is further confirmed by the voltammograms and ORR activities in 0.1 M HClO4. We conclude that tert-butylamine can be an effective solvent for the removal of PVP and a reagent for Br− ions because of its ability to form a quaternary ammonium salt.

Ammonia production has traditionally been based on large-scale plants. The thrust toward large-scale production to gain economic advantages has overshadowed the benefits that could be derived from small-scale production plants. Additionally, the ammonia industry consumes a major chunk of global fossil fuels, which also burdens the planet with greenhouse gases. To effectively counter these issues, this study investigates the production of ammonia from biomass. Processes based on biomass plants are usually small-scale and are limited by biomass supply. To ensure sustainable ammonia production, this study tries to highlight the techno-economic advantages that result from small-scale ammonia plants based on biomass feedstock. This paper proposes a new process that takes inputs from a relatively old, natural gas based process (leading concept ammonia) specifically designed for small-scale ammonia manufacture and couples it with a recently developed dual fluidized bed technology for biomass feedstock. Two different flowsheet configurations are simulated rigorously and compared to gain a better understanding of the process. The flowsheets are optimized, and energy integration is performed to provide a wider insight. The life cycle assessment calculations that are carried out using ASPEN Plus simulation results and ecoinvent databases predict a CO2 emissions reduction of 54–68% when compared to conventional ammonia plants.

Two-photon lithography (TPL) is a versatile technology for additive manufacturing of 2D and 3D micro/nanostructures with sub-wavelength resolved features. Recent advancement in laser technology has enabled the application of TPL fabricated structures in several fields such as microelectronics, photonics, optoelectronics, microfluidics, and plasmonic devices. However, the lack of two-photon polymerizable resins (TPPRs) induces bottleneck to the growth of TPL to its true potential, and hence continuous research efforts are focused on developing efficient TPPRs. In this article, we review the recent advancements in PI and TPPR formulation and the impact of process parameters on fabrication of 2D and 3D structures for specific applications. The fundamentals of TPL are described, followed by techniques used for achieving improved resolution and functional micro/nanostructures. Finally, a critical outlook and future prospects of TPPR formulation for specific applications are presented.

The synthesis and magnetic and theoretical studies of three isostructural heterometallic [CoIII2LnIII2(μ3-OH)2(o-tol)4(mdea)2(NO3)2] (Ln = Dy (1), Tb (2), Ho (3)) “butterfly” complexes are reported (o-tol = o-toluate, (mdea)2– = doubly deprotonated N-methyldiethanolamine). The CoIII ions are diamagnetic in these complexes. Analysis of the dc magnetic susceptibility measurements reveal antiferromagnetic exchange coupling between the two LnIII ions for all three complexes. ac magnetic susceptibility measurements reveal single-molecule magnet (SMM) behavior for complex 1, in the absence of an external magnetic field, with an anisotropy barrier Ueff of 81.2 cm–1, while complexes 2 and 3 exhibit field induced SMM behavior, with a Ueff value of 34.2 cm–1 for 2. The barrier height for 3 could not be quantified. To understand the experimental observations, we performed DFT and ab initio CASSCF+RASSI-SO calculations to probe the single-ion properties and the nature and magnitude of the LnIII–LnIII magnetic coupling and to develop an understanding of the role the diamagnetic CoIII ion plays in the magnetization relaxation. The calculations were able to rationalize the experimental relaxation data for all complexes and strongly suggest that the CoIII ion is integral to the observation of SMM behavior in these systems. Thus, we explored further the effect that the diamagnetic CoIII ions have on the magnetization blocking of 1. We did this by modeling a dinuclear {DyIII2} complex (1a), with the removal of the diamagnetic ions, and three complexes of the types {KI2DyIII2} (1b), {ZnII2DyIII2} (1c), and {TiIV2DyIII2} (1d), each containing a different diamagnetic ion. We found that the presence of the diamagnetic ions results in larger negative charges on the bridging hydroxides (1b > 1c > 1 > 1d), in comparison to 1a (no diamagnetic ion), which reduces quantum tunneling of magnetization effects, allowing for more desirable SMM characteristics. The results indicate very strong dependence of diamagnetic ions in the magnetization blocking and the magnitude of the energy barriers. Here we propose a synthetic strategy to enhance the energy barrier in lanthanide-based SMMs by incorporating s- and d-block diamagnetic ions. The presented strategy is likely to have implications beyond the single-molecule magnets studied here.

Automatic sarcasm detection is the task of predicting sarcasm in text. This is a crucial step to sentiment analysis, considering prevalence and challenges of sarcasm in sentiment-bearing text. Beginning with an approach that used speech-based features, sarcasm detection has witnessed great interest from the sentiment analysis community. This paper is the first known compilation of past work in automatic sarcasm detection. We observe three milestones in the research so far: semi-supervised pattern extraction to identify implicit sentiment, use of hashtag-based supervision, and use of context beyond target text. In this paper, we describe datasets, approaches, trends and issues in sarcasm detection. We also discuss representative performance values, shared tasks and pointers to future work, as given in prior works. In terms of resources that could be useful for understanding state-of-the-art, the survey presents several useful illustrations - most prominently, a table that summarizes past papers along different dimensions such as features, annotation techniques, data forms, etc.

Abstract Cations and anions are replaced with Fe, Mn, and Se in CZTS in order to control the formations of the secondary phase, the band gap, and the micro structure of Cu 2 ZnSnS 4 . We demonstrate a simplified synthesis strategy for a range of quaternary chalcogenide nanoparticles such as Cu 2 ZnSnS 4 (CZTS), Cu 2 FeSnS 4 (CFTS), Cu 2 MnSnS 4 (CMTS), Cu 2 ZnSnSe 4 (CZTSe), and Cu 2 ZnSn(S 0.5 Se 0.5 ) 4 (CZTSSe) by thermolysis of metal chloride precursors using long chain amine molecules. It is observed that the crystal structure, band gap and micro structure of the CZTS thin films are affected by the substitution of anion/cations. Moreover, secondary phases are not observed and grain sizes are enhanced significantly with selenium doping (grain size ~1 μm). The earth-abundant Cu 2 MSnS 4 /Se 4 (M = Zn, Mn and Fe) nanoparticles have band gaps in the range of 1.04–1.51 eV with high optical-absorption coefficients (~10 4 cm −1 ) in the visible region. The power conversion efficiency of a CZTS solar cell is enhanced significantly, from 0.4% to 7.4% with selenium doping, within an active area of 1.1 ± 0.1 cm 2 . The observed changes in the device performance parameters might be ascribed to the variation of optical band gap and microstructure of the thin films. The performance of the device is at par with sputtered fabricated films, at similar scales.

In the domain of synthetic chemistry, C-H bond activation has always remained in the spotlight for researchers over the last few decades. Although different strategies have been employed to chemically trigger unactivated C-H bonds, transition metal catalyzed directing group (DG) aided C-H bond activation is the most explored pathway of all because of its ability to perform diverse site selective functional metamorphosis. Despite its popularity, tedious synthetic methodology requiring additional steps for the installation and removal of DGs from the target substrate diminishes its efficacy. However, replacement of directing groups by transient directing groups (tDGs) reduces the hurdle to a greater extent without compromising the product yield and selectivity. In this report we have depicted the intense journey of transient directing groups with three (Rh, Ru, and Pd) prevalent second row transition metals.

Ultrasound (US)-responsive carriers have emerged as promising theranostic candidates because of their ability to enhance US-contrast, promote image-guided drug delivery, cause on-demand pulsatile release of drugs in response to ultrasound stimuli, as well as to enhance the permeability of physiological barriers such as the stratum corneum, the vascular endothelium, and the blood-brain barrier (BBB). US-responsive carriers include microbubbles MBs, liposomes, droplets, hydrogels, and nanobubble-nanoparticle complexes and have been explored for cavitation-mediated US-responsive drug delivery. Recently, a transient increase in the permeability of the BBB by microbubble (MB)-assisted low-frequency US has shown promise in enhancing the delivery of therapeutic agents in the case of neurological disorders. Further, the periodic mechanical stimulus generated by US-responsive MBs have also been explored in tissue engineering and has directly influenced the differentiation of mesenchymal stem cells into cartilage. This Review discusses the various types of US-responsive carriers and explores their emerging roles in therapeutics ranging from drug delivery to tissue engineering.