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A Scalable Physics-Based Compact Model for Terminal Charge, Intrinsic Capacitance and Drain Current in Nanosheet Field Effect Transistors
No full textThis study introduces a physics-based, SPICE-compatible model for Nanosheet Field-Effect Transistors (NsFETs) that offers explicit expressions for the drain current, terminal charges, and intrinsic capacitances applicable to both p-type and n-type devices. The carrier transport is modeled using the drift-diffusion formalism, while the terminal charges are calculated using the Ward-Dutton linear charge partition scheme, ensuring charge conservation. Employing a bottom-up approach, the model effectively captures quantum mechanical confinement-induced effects with minimal reliance on empirical parameters, thus preserving the simplicity characteristic of traditional bulk MOSFET models. Short channel effects are modeled in a self-consistent way. This model has been extensively validated against both experimental data and simulations across varying device dimensions and bias conditions, demonstrating exceptional scalability across all device dimensions. The proposed model has also been implemented in Verilog-A and integrated in a commercial SPICE simulator to simulate NsFETs based circuits, underscoring the model’s practical applicability in contemporary semiconductor design
Green synthesis of 1,4-benzodiazepines over La2O3 and La( OH)3 catalysts: possibility of Langmuir-Hinshelwood adsorption (vol 6, pg 103455, 2016)
No full textEnergy and power characteristics of nanocatalyzed Belousov-Zhabotinsky reactions via bifurcation analyses
No full textActive stimuli-responsive materials, intrinsically powered by chemical reactions, have immense capabilities that can be harnessed for designing synthetic systems for a variety of biomimetic applications. It goes without saying that the key aspect involved in the designing of such systems is to accurately estimate the amount of energy and power available for transduction through various mechanisms. Belousov-Zhabotinsky (BZ) reactions are dynamical systems, which exhibit self-sustained nonlinear chemical oscillations, as their catalyst undergoes periodic redox cycles in the presence of reagents. The unique feature of BZ reaction based active systems is that they can continuously perform mechanical work by transducing energy from sustained chemical oscillations. The objective of our work is to use bifurcation analyses to identify oscillatory regimes and quantify energy-power characteristics of the BZ reaction based on nanocatalyst activity and BZ reaction formulations. Our approach involves not only the computation of higher order Lyapunov and frequency coefficients but also Hamiltonian functions, through normal form reduction of the kinetic model of the BZ reaction. Ultimately, using these calculations, we determine amplitude, frequency, and energy-power densities, as a function of the nanocatalysts' activity and BZ formulations. As normal form representations are applicable to any dynamical system, we believe that our framework can be extended to other self-sustained active systems, including systems based on stimuli-responsive materials. � 2023 Elsevier B.V., All rights reserved
Variational diffusion unlearning: a variational inference framework for unlearning in diffusion models under data constraints
No full textFor a responsible and safe deployment of diffusion models in various domains, regulating the generated outputs from these models is desirable because such models could generate undesired, violent, and obscene outputs. To tackle this problem, recent works use machine unlearning methodology to forget training data points containing these undesired features from pre-trained generative models. However, these methods proved to be ineffective in data-constrained settings where the whole training dataset is inaccessible. Thus, the principal objective of this work is to propose a machine unlearning methodology that can prevent the generation of outputs containing undesired features from a pre-trained diffusion model in such a data-constrained setting. Our proposed method, termed as Variational Diffusion Unlearning (VDU), is a computationally efficient method that only requires access to a subset of training data containing undesired features. Our approach is inspired by the variational inference framework with the objective of minimizing a loss function consisting of two terms: plasticity inducer and stability regularizer. Plasticity inducer reduces the log-likelihood of the undesired training data points, while the stability regularizer, essential for preventing loss of image generation quality, regularizes the model in parameter space. We validate the effectiveness of our method through comprehensive experiments for both class unlearning and feature unlearning. For class unlearning, we unlearn some user-identified classes from MNIST, CIFAR-10, and tinyImageNet datasets from a pre-trained unconditional denoising diffusion probabilistic model (DDPM). Similarly, for feature unlearning, we unlearn the generation of certain high-level features from a pre-trained Stable Diffusion mode
Web Privacy Perceptions Amongst Indian Users
No full textWhile personalized content in the digital world is necessary for a better browsing experience, users knowingly or unknowingly share a lot of data with third-party advertising networks, market analysts, and trackers. Although India is the second largest online market in the world, the privacy perceptions of Indian users is not well understood. The focus of this work is to investigate the understanding of privacy on the web amongst Indians, and to provide a basis for making web privacy features more usable among Indian users. Through this user study, we want to understand how different attributes affect privacy choices of the users when they are accessing the web. We also investigate if the users are aware of various ways in which websites and web applications collect information, their implications, different options to handle their privacy, and if the usability of privacy settings affects their decision-making. This study sheds light on the prevalence of various privacy violations or information leaks, if and how they target a group of people, and why they succeed. The survey also acts as an informative revision of the different aspects regarding privacy for the users from India
Nanoscale non-biochar formulations of banana peel layers for comparison of in vitro adsorption and release of ammonium with demonstration of fertilizing action
No full textThe convergent ability of non-biochar biomass-formulations to adsorb and release NH4+ has not been extensively investigated. In this work, we have prepared nanoscale non-biochar formulations of banana peel sections and studied their ability to adsorb and release NH4+. A combination of FTIR, XRD, FESEM, EDX, TGA, DTG, BET and DLS highlight the distinctive nanoscale structural, surface and thermal properties of the banana peel formulations. The inner and outer sections of banana peel display attractive surface porosity and superlative adsorption efficiencies towards NH4+ that are superior compared to reported biomass-derived NH4+ adsorbents. The nanoscale banana peel adsorbents display quantitative in vitro release of adsorbed NH4+. The direct treatment of Arabidopsis thaliana with NH4+ loaded banana peel adsorbents result in significant and distinctive enhancements in leaf area, root number, and root length. The nanoscale non-biochar banana peel formulations reported in this work hold promise as eco-friendly and cost-effective adsorbents and fertilizers
On the Utility of Soil Moisture for Monitoring and Prediction of Compound Hot and Dry Extremes in India
No full textThe increasing frequency of compound hot and dry extremes (CHDEs) across India poses serious risks to agriculture and ecosystems. However, real-time monitoring and prediction of CHDEs in India have been lacking. Here, we examine the effectiveness of soil moisture (SM) and evaporative stress ratio (ESR) in capturing dry extremes during the summer monsoon (June–September) and non-monsoon (October–May) seasons. Indicators solely based on soil moisture or ESR fail to capture dry extremes across the seasons and regions in India. However, a joint indicator based on soil moisture and (ESR) effectively captures dry extremes during the monsoon and non-monsoon seasons. We developed a catalog of CHDEs in India using the Standardized Hot and Drought Index (SHDI) for the 1979–2020 period. Most CHDEs in India occur during the summer monsoon season, driven by precipitation deficit and increased vapor pressure deficit (VPD). CHDEs cause vegetation stress as captured by solar-induced fluorescence (SIF) and the normalized difference vegetation index (NDVI). However, SIF responds more quickly to CHDEs than NDVI during the summer monsoon and non-monsoon seasons. We used SHDI and NDVI to examine their utility for near-real-time monitoring and predicting CHDEs in India. CHDEs in India can be predicted 2 weeks in advance using soil moisture, ESR, and temperature based on the Extended Range Forecasting System (ERFS), highlighting the potential of integrating observations and forecasts for monitoring and prediction
Millennial-Scale Slip Rates Along Blind Himalayan Frontal Thrust: Findings From Chalsa-Gorubathan Recess in East-Central Himalaya
No full textThe Himalayan Frontal Thrust (HFT) is seismotectonically the most active orogen-scale structure of the Himalaya at least since Quaternary. However, in the eastern Himalaya, HFT is multiply segmented by orogen-scale transfer faults and often blind. We present new insights on fault-driven landscape evolution in the Chalsa-Gorubathan Recess in the east-central Himalaya, where the Sub-Himalaya is missing and a blind frontal fault system has deformed the late Pleistocene piedmont fan. We provide new and alternative constraints on the minimum fault displacement rates using luminescence dating of the displaced fan-surface (27.4 ± 4.5 kyr). Fault-propagation folding of piedmont fan surface record 6 ± 2 mm/year. Slip rate on the blind fault-splay. This suggests that the HFT accommodates one-third of the total Himalayan shortening along this transect since late Pleistocene. The minimum accumulated slip deficit ranges between 4 and 8 m since the ~1100 ad Nepal Earthquake which could lead to a Mw 6.8 seismic event anytime
Cohen–Macaulay weighted oriented edge ideals and its Alexander dual
No full textThe study of the edge ideal I(DG) of a weighted oriented graph DG with underlying graph G started in the context of Reed–Muller type codes. We generalize some Cohen–Macaulay constructions for I(DG), which Villarreal gave for edge ideals of simple graphs. Our constructions can be used to produce large classes of Cohen–Macaulay weighted oriented edge ideals. We use these constructions to classify all the Cohen–Macaulay weighted oriented edge ideals, whose underlying graph is a cycle. We also show that I(DCn) is Cohen–Macaulay if and only if I(DCn) is unmixed and I(Cn) is Cohen–Macaulay, where Cn denotes the cycle of length n. Miller generalized the concept of Alexander dual ideals of square-free monomial ideals to arbitrary monomial ideals, and in that direction, we study the Alexander dual of I(DG) and its conditions to be Cohen–Macaulay
First principle investigation and substrate temperature dependent structural and electrical transport characterizations of pulsed laser deposited (PLD) cadmium indium Selenide (α-CdIn2Se4) ternary semiconducting compound thin films
No full textThe theoretical investigations on CdIn2Se4, a ternary semiconducting compound belonging to the II-III2-VI4 family, were accomplished using the SIESTA code. Using density functional theory, the band structure of the CdIn₂Se₄ was proposed. Its semiconducting nature was highlighted by the direct band gap of ≃1.6700 eV. The values of the Fermi energy, the highest occupied molecular orbital, the lowest unoccupied molecular orbital, and Mulliken atomic charges of individual atoms in CdIn₂Se₄ were inferred. A pulsed laser deposition technique deposited CdIn2Se4 thin films on various substrates at different substrate temperatures (Ts). Electron microscopy and an X-ray diffractometer were used to study the morphology and/or crystal structure of CdIn2Se4 films. The CdIn2Se4 films were found to be amorphous when synthesized at lower Ts (s s (> 550 K). The additional reflection observed in CdIn2Se4 films at higher Ts (> 550 K) is identified due to the characteristic peak of the hexagonal β-phase In2Se3. The ICDD card 01-089-2388 was used to index the electron diffraction and X-ray diffraction results of the tetragonally structured and P-42 m (1 1 1) crystallographic space group α-phase CdIn2Se4 films. The lattice constant and unit cell volume for the (1 1 1) reflection of CdIn2Se4 films have been inferred. For the most substantial (1 1 1) reflection, the stacking fault (5.7992 × 10−3) and unity value of the texture coefficient for the CdIn2Se4 film are extracted. No element/s other than Cd, In, and Se are evident in the CdIn2Se4 thin films’ energy dispersive analysis of X-ray spectra, which revealed the purity of the CdIn2Se4 films. The Raman investigation demonstrates the effective formation of nanocrystalline, strain-influenced CdIn2Se4 films with a prominent Raman mode at 137 cm−1. The DC electrical resistivity, thermal activation energies, band gap energies, Hall coefficient, carrier concentration, and Hall mobility were deduced for CdIn2Se4 films. The implications are addressed