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Lead-free potassium titanium halide (K2TiI6) perovskite is considered a substantial alternative for highly efficient perovskite solar cells. This research consists of a computational study of Pb-free K2TiI6-based perovskite solar cell using SCAPS 1D. Primarily, the TiO2 and PEDOT:PSS are considered as ETL and HTL exhibit a device efficiency of 5.70%. Further, the impact of various ETL and HTL is explored. The optimization is mainly focused on considering its built-in potential relation with the open circuit voltage and its device efficiency. It is obtained from the numerical simulation, that to circumvent the VOC loss, the CB minimum of the PVSK(CBmin_PVSK) layer should be higher than the CB minimum of the ETL (CBmin_ETL), and the CB minimum of the ETL (CBmin_ETL) should either align or lie above than the FTO contact. In order to have proper hole transport from the perovskite, the VB maximum of the perovskite (PVSK) layer should be lower than the VB maximum of HTL and should either align or lie below the back contact. It is obtained from the simulation that the optimized ETL and HTLs are found as PCBM and Sr2Cu2O2 improve the device efficiency. Further, the impact of perovskite thickness is also investigated, which enhances the device efficiency up to 23.75%. The proposed structure shows remarkable PV parameters VOC = 1.32 V, JSC = 22.30 mA/cm2, FF = 81.07%, and ƞ = 24.01% which indicates that the K2TiI6-based perovskite solar cell is considered a remarkable candidate for Pb-free perovskite solar cell development. [ABSTRACT FROM AUTHOR]

The world is witnessing the fast replacement of fossil-fuelled vehicles by environment-friendly electric vehicles (EVs). This unprecedented growth of EVs is expected to burden the material resource consumption of batteries constituting metals from the earth. However, circular economy in the electric vehicle battery (EVB) ecosystem can provide a sustainable solution to resource management. This has triggered the need to understand and analyse the EVB ecosystem players. Long-term analyses of behaviours of the different variables under dynamic and complex systems are best carried out by the application of system dynamics (SD)—a continuous simulation methodology. This research paper has contributed in developing an interactive SD-based model for the circular production and consumption flow of EVBs to analyse the behavioural dynamics of the different variables involved. Five scenarios have been simulated for the analyses. The behaviour trends of the variables obtained from the SD-based simulation model have provided useful insights and five recommendations for resource sustainability. The recommendations are: the necessity for adopting Industry-4.0 in EVB manufacturing, awareness creation of circular thinking amongst all stakeholders, enhanced end-of-life (EOL) period of EVB, compelling need for high EVB recollection efficiency after EOL, and improvement in the reprocessing technology of EOL batteries. [ABSTRACT FROM AUTHOR]

An analytical model for gate tunneling current in a nanoscale double gate (DG) metal oxide semiconductor field effect transistor (MOSFET) has been developed. The model is simple and generalized one and is based on our earlier work on gate tunneling current in single gate MOSFET, i.e., treating the band profile in the channel as a triangular potential well. The potential distribution in the silicon body is determined through a perturbation approach which facilitates analytical solution to Poisson's equation considering the contributions from both inversion and depletion charges. Looking at the dimension of the MOSFET apart from electrical confinement the effect of structural confinement has also been taken into account. The estimated tunneling current density in the present model compares well with the results of L. Chang et al. [ABSTRACT FROM AUTHOR]

In this article, a transient-enhanced fully synthesizable digital low dropout regulator (FS-DLDO) is proposed for ultra-low-power applications. The FS-DLDO uses a fully synthesizable comparator (FS-Com) to sense load variations. A digital logic controller (D-CTRL) tunes the output voltage (VO) through a quad-loop architecture. The quad-loop architecture uses short bidirectional shift registers (BSR) to achieve fast-transient response and reduce leakage current. In addition, the FS-DLDO supports freeze-mode to regulate a ripple-free VO and minimize power consumption at a steady state. To demonstrate this entire design using standard-cells, the P-MOSFET array (PTA) used in traditional digital low dropout regulator (DLDO) is replaced with an array of three-state buffers (TSA). The layout is created using digital design flow in TSMC CMOS 45 nm process, which occupies a 6708 µm2 area. For a power supply (VSUP) range of 0.5–1 V, the FS-DLDO can provide regulated VO with a 50 mV dropout voltage. At VSUP = 500 mV and clock frequency (fCLK) of 10 MHz, the proposed regulator achieves a transient response time of 0.91 µs. This prototype achieves a peak current efficiency of 99.90% and produces a ripple-free VO at a steady state. [ABSTRACT FROM AUTHOR]

This work presents a PVT robust machine learning-based Voltage-controlled Oscillator (VCO) with an enhanced linearity range. The machine learning algorithm with PVT robustness is implemented digitally. Different from conventional methods, the proposed scheme does not require the VCO to be in working mode every time one needs the prediction of frequency. The proposed scheme uses the frequency to digital converter (FDC) output data as an input learning vector and uses a prediction block to predict the future frequencies. An 11-stage voltage-controlled oscillator with a machine learning algorithm is implemented in SCL 180 nm CMOS technology. The measurement results show that the proposed architecture is robust against PVT variations with an enhanced linearity range. Without a machine learning algorithm, the VCO's control voltage linearity range is 0.28 V to 0.40 V that increases to the range from 0.1 to 1.8 V after applying the proposed machine learning algorithm. The maximum gain variation of 3.71% is observed at FF with respect to the TT corner after applying the proposed machine learning algorithm. [ABSTRACT FROM AUTHOR]

In this work, a dual loop all-digital phase locked loop (ADPLL) is designed to obtain a fast locking, low power and low jitter for SoC and battery-operated applications. The high speed and high-resolution 4-bit flash time to digital converter (TDC) is also proposed to achieve low jitter and fast locking in ADPLL. The flash TDC uses a foreground calibration to make the ADPLL work robustly over PVT variations. In present work, fasting settling time of 1 μs and low power is achieved for proposed ADPLL owing to flash-based TDC and dual loop architecture. The proposed 4-bit flash TDC achieves a resolution of 6 ps. A low-phase noise voltage-controlled oscillator based on inverters is designed to obtain a reduced jitter in ADPLL. The ADPLL is implemented in a 180-nm SCL digital CMOS technology. The achieved phase noise of proposed ADPLL is − 128.2 dBc/Hz at an offset of 100 MHz. At an output frequency of 1.6 GHz, the periodic jitter of ADPLL is 7.8 ps, and power consumption is 6.5 mW. [ABSTRACT FROM AUTHOR]

High electrical conductivity and superior redox properties of metal sulfide-based supercapacitors have attracted much attention in recent years. The simple and cost-effective method in the fabrication of high-performance supercapacitors is currently in high demand. In this paper, low-cost one-dimensional copper sulfide (Cu2S) electrodes are synthesized on glass as well as on flexible substrates such as polyethylene terephthalate (PET) and polypropylene (PP). The effect of the deposition quantity of Cu2S-1:1 on the glass substrate is also discussed. The synthesis of copper sulfide was done at room temperature by reducing copper sulphate pentahydrate using ascorbic acid as a reducing agent in sodium thiosulphate with 2 h of total reaction time. Scanning electron microscopy and x-ray diffraction characterizations are performed to validate the formation of Cu2S hollow rods. Electrochemical measurements such as cyclic voltammetry, galvanostatic charge-discharge, and electrochemical impedance spectroscopy are performed using a Metrohm Autolab workstation. Cyclic voltammetry is performed to measure the capacitance of Cu2S-based supercapacitors in which the ratio of copper sulphate and sodium thiosulphate was varied from 1:0.5 to 1:1.5 with a step size of 0.5, and the deposition quantity of Cu2S-1:1 film was also varied on glass substrate from 1 mg to 2 mg. The results show that the device with a 1:1 ratio shows the highest capacitance, i.e., 587 mF/cm2 as compared to the devices fabricated with a 1:0.5 ratio, 1:1.5 ratio, and 1:1 ratio with greater deposition. This is mainly because the 1:1 ratio has less resistance and has a hollow rod structure which allows the electrolyte ions to penetrate in Cu2S active material and thus, facilitates fast electron transport resulting in high-performance supercapacitors. Further, to understand the increased capacitive properties of a copper sulfide-based supercapacitor, processes involving charge transfer and mass transport are investigated by performing electrochemical impedance spectroscopy (EIS). The radius on the EIS plot of Cu2S-1:1 is smaller as compared to the other three samples on the glass substrate. Also, the resistance of Cu2S-1:1 with greater deposition is more than the Cu2S-1:1 sample because the increased amount of electrode material leads to increased paths for the electrolyte ions to interact with the electrode material. Further, this paper also discusses the successful fabrication of the supercapacitor devices on flexible PP substrate using 1-D Cu2S for the first time. The results show that the capacitance value on the flexible substrate is on par with that of glass substrates. Also, the synthesized copper sulfide 1:1 sample exhibits excellent stability with the capacitance retention of 85.7%, 91.1%, 86.18%, and 92.8%, respectively, on PP, glass, PET, and Cu2S-1:1 with more deposition on glass substrate after 3500 cycles. [ABSTRACT FROM AUTHOR]

The contemporary unsupervised word representation methods have been successful in capturing semantic statistics on various Natural Language Processing tasks. However, these methods proved to be futile in addressing tasks like polysemy or homonymy, which prevail in such tasks. There has been a rise in the number of state-of-the-art transfer learning techniques bringing into play the language models pre-trained on large inclusive corpus. Motivated by these techniques, the present paper proposes an efficacious transfer learning based ensemble model. This model is inspired by ULMFit and presents results on challenging sentiment analysis tasks such as contextualization and regularization. We have empirically validated the efficiency of our proposed model by applying it to three conventional datasets for sentiment classification task. Our model accomplished the state-of-the-art outcomes remarkably when compared to acknowledged baselines in terms of classification accuracy. [ABSTRACT FROM AUTHOR]

Clinically, electrocardiogram (ECG) is a powerful tool for determining the health and functioning of the human heart. Faster detection and diagnosis of heart functioning would aid cardiologists to provide appropriate treatment to the patients (subjects). In this paper, the concept of fractional-order calculus is employed for noise cancellation and artifacts removal in ECG signal as fractional-order differentiator proved to provide more peculiar details about signals than an integer-order differentiator. In the proposed method, R-peaks are detected using Riesz fractional-order digital differentiator (RFODD) based on the differencing method. The differentiation operation enhances the high-frequency components of the signal. So, QRS complex which is a high-frequency component in ECG is accentuated and the R-peaks are detected using appropriate threshold technique. The proposed method is tested on Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) arrhythmia database, and the experimental results of the proposed method have achieved a sensitivity of 99.95%, positive predictivity of 99.949% and an error rate of 0.095%. ECG waveforms are analyzed on various fractional orders of RFODD, and their performance parameters, i.e., sensitivity, positive predictivity and error rate, are also calculated. [ABSTRACT FROM AUTHOR]

Electrocardiogram (ECG) signal processing and analysis is becoming more and more popular as it is useful in diagnosis and prognosis of human heart and clinically automatic machine estimation is based upon it. R-peak is the most important component in ECG beat and is widely used to investigate normal and abnormal subjects (patients). From the last few decades, R-peak detection in ECG has been the most challenging topic in the biomedical research. As QRS complex has high frequency in ECG as compared to other waves (P, T, U-wave), so majority of algorithms estimate QRS complex by either filtering or suppressing the lower frequency waves, including various artifacts like baseline wander, power line interference, and electromyograph noises. This paper demonstrates a new kind of ECG denoising algorithm based on self-convolution window (SCW) concept. The SCW based on Hamming window, herein referred to as Hamming self-convolution window, is used to design a new kind of filter which possesses negligible ripples in the stop band, as compared to the conventional window-based filters. This algorithm is validated on MIT-BIH arrhythmia database and the results outperform in terms of sensitivity, positive predictivity, and error rate obtained as 99.93%, 99.95%, and 0.117%, respectively, as compared to the other well-established works. The approach has also outperformed the results of well-established window-based filters (Hamming and Kaiser) in terms of reduced false negative, false positive, and error rate. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to identify the enablers for organizational excellence inspired by human body; based on which a generally applicable framework that establishes relationships among these enablers can be developed. In the first part of the paper, human body systems and sub-systems are analyzed from organizational perspective operating in dynamically changing environment. The examination of human body organization subsystems has revealed nine attributes that enable human body to become an optimally managed organization. The nine attributes are: quick responsiveness to external stimuli, coordination, communication, control, optimal supply chain management, adaptability, reliability, innovativeness, and self regulation. In the second part of the paper, these nine enablers are modeled using TISM. The model developed clearly demonstrates the driving and dependence of the enabler in human body organization. It is expected that the proposed model can inspire and provide insight to businesses in improving their design and function which will help in achieving organizational excellence. [ABSTRACT FROM AUTHOR]

Cryogenic two-phase flow with phase change heat transfer, consisting of a saturated liquid slug translating in its own superheated vapor in a circular pipe, was numerically simulated. The cryogenic chill down process was simplified by assuming ideal inverted annular flow regime. The method used is based on a sharp interface concept and developed on an Eulerian Cartesian fixed-grid with a cut-cell scheme and marker points to track the moving interface. The unsteady, axisymmetric Navier-Stokes equations in both liquid and vapor phases are solved separately and used to compute the velocity, pressure, and temperature fields and the deformation of the liquid core very accurately. Three most common cryogenic fluids, viz. nitrogen, oxygen, and argon were included in the study. The influence of non-dimensional parameters like Reynolds number $$Re,$$ Weber number $$We$$ , and Jakob number $$Ja$$ on flow characteristics was studied by systematically varying only one at a time. $$Re$$ was found to affect the mass flow rates, but did not have a significant influence on the wall cooling or the Nusselt number. $$We$$ affected the interface shape at the leading edge of the liquid slug, also influencing the heat transfer and velocity field there. $$Ja$$ affects all three quantities of interest, i.e., mass flow rate, wall cooling, and the Nusselt number. [ABSTRACT FROM AUTHOR]

This paper aims at bringing out an analogy between human body and corporate organizations for classical managerial functions, viz. Planning, Organizing, Directing, and Controlling. In human body, every action and response to each stimulus are well planned. It has eleven subsystems, organized into a well structured design and a central directing brain that influences and guides these subsystems to perform in accordance with the plan. A control mechanism in human body minimizes deviations and maintains dynamic equilibrium. This way present analogy visualizes human body as a perfectly planned, organized, directed and controlled system created and sustained by Nature. A SAP-LAP framework of human body organization is also developed to understand the principles and processes behind its perfections. Based on this SAP-LAP model, a number of actions are proposed in this paper that can provide valuable insights for organizations. These insights perhaps can help them in significantly improving their structure and operating procedures, which will enhance the performance of individuals and organizations as a whole. Perhaps the human body is also a perfect example of optimal degree of flexibility in its sub-systems contingent upon their roles and functions. [ABSTRACT FROM AUTHOR]