An experimental investigation of spin-on doping optimization for enhanced electrical characteristics in silicon homojunction solar cells: Proof of concept.

The pursuit of enhancing the performance of silicon-based solar cells is pivotal for the progression of solar photovoltaics as the most potential renewable energy technologies. Despite the existence of sophisticated methods like diffusion and ion implantation for doping phosphorus into p-type silicon wafers in the semiconductor industry, there is a compelling need to research spin-on doping techniques, especially in the context of tandem devices, where fabricating the bottom cell demands meticulous control over conditions. The primary challenge with existing silicon cell fabrication methods lies in their complexity, cost, and environmental concerns.

Predictive analysis of the power spectral irradiance from blackbody radiation source using single pixel detector.

Accurate spectral irradiance measurement in the near-infrared range is significant for the design and characterization of photodetector and photovoltaic cells. Approximation method is commonly used to solve for the input power using estimated spectral irradiance, where the dependency on wavelength and temperature remains uncertain. This study aims to determine the power spectrum at different radiation temperatures using a single pixel photodetector, taking into consideration factors such as transmission spectra of alumina radiator, CaF collimating lens, responsivity, and measured photocurrent information of photodetectors.

Translating conventional wisdom on chicken comb color into automated monitoring of disease-infected chicken using chromaticity-based machine learning models.

Bacteria- or virus-infected chicken is conventionally detected by manual observation and confirmed by a laboratory test, which may lead to late detection, significant economic loss, and threaten human health. This paper reports on the development of an innovative technique to detect bacteria- or virus-infected chickens based on the optical chromaticity of the chicken comb. The chromaticity of the infected and healthy chicken comb was extracted and analyzed with International Commission on Illumination (CIE) XYZ color space.

Quantifying Microalgae Growth by the Optical Detection of Glucose in the NIR Waveband.

Microalgae have become a popular area of research over the past few decades due to their enormous benefits to various sectors, such as pharmaceuticals, biofuels, and food and feed. Nevertheless, the benefits of microalgae cannot be fully exploited without the optimization of their upstream production. The growth of microalgae is commonly measured based on the optical density of the sample.

Prerequisite for COVID-19 Prediction: A Review on Factors Affecting the Infection Rate.

Since the year 2020, coronavirus disease 2019 (COVID-19) has emerged as the dominant topic of discussion in the public and research domains. Intensive research has been carried out on several aspects of COVID-19, including vaccines, its transmission mechanism, detection of COVID-19 infection, and its infection rate and factors. The awareness of the public related to the COVID-19 infection factors enables the public to adhere to the standard operating procedures, while a full elucidation on the correlation of different factors to the infection rate facilitates effective measures to minimize the risk of COVID-19 infection by policy makers and enforcers.

Chemical Composition, Antioxidant, Antibacterial, and Antibiofilm Activities of Essential Oil.

The essential oil of , commonly known as lemon myrtle oil, possesses various beneficial properties due to its richness in bioactive compounds. This study aimed to characterize the chemical profile of the essential oil isolated from leaves of (BCEO) and its biological properties, including antioxidant, antibacterial, and antibiofilm activities. Using gas chromatography-mass spectrometry, 21 compounds were identified in BCEO, representing 98.

Color Index of Transformer Oil: A Low-Cost Measurement Approach Using Ultraviolet-Blue Laser.

The color of transformer oil can be one of the first indicators determining the quality of the transformer oil and the condition of the power transformer. The current method of determining the color index (CI) of transformer oil utilizes a color comparator based on the American Society for Testing and Materials (ASTM) D1500 standard, which requires a human observer, leading to human error and a limited number of samples tested per day. This paper reports on the utilization of ultra violet-blue laser at 405- and 450-nm wavelengths to measure the CI of transformer oil.

The Amber-Colored Liquid: A Review on the Color Standards, Methods of Detection, Issues and Recommendations.

For most natural or naturally-derived liquid products, their color reflects on their quality and occasionally affects customer preferences. To date, there are a few subjective and objective methods for color measurement which are currently utilized by various industries. Researchers are also improving these methods and inventing new methods, as color is proven to have the ability to provide various information on the condition and quality of the liquid.

A Feasible Alternative to FDSOI and FinFET: Optimization of W/LaO/Si Planar PMOS with 14 nm Gate-Length.

At the 90-nm node, the rate of transistor miniaturization slows down due to challenges in overcoming the increased leakage current (). The invention of high-k/metal gate technology at the 45-nm technology node was an enormous step forward in extending Moore's Law. The need to satisfy performance requirements and to overcome the limitations of planar bulk transistor to scales below 22 nm led to the development of fully depleted silicon-on-insulator (FDSOI) and fin field-effect transistor (FinFET) technologies.

Deep learning approach towards accurate state of charge estimation for lithium-ion batteries using self-supervised transformer model.

Accurate state of charge (SOC) estimation of lithium-ion (Li-ion) batteries is crucial in prolonging cell lifespan and ensuring its safe operation for electric vehicle applications. In this article, we propose the deep learning-based transformer model trained with self-supervised learning (SSL) for end-to-end SOC estimation without the requirements of feature engineering or adaptive filtering. We demonstrate that with the SSL framework, the proposed deep learning transformer model achieves the lowest root-mean-square-error (RMSE) of 0.

A Review on Thermophotovoltaic Cell and Its Applications in Energy Conversion: Issues and Recommendations.

Generally, waste heat is redundantly released into the surrounding by anthropogenic activities without strategized planning. Consequently, urban heat islands and global warming chronically increases over time. Thermophotovoltaic (TPV) systems can be potentially deployed to harvest waste heat and recuperate energy to tackle this global issue with supplementary generation of electrical energy.

Corrigendum to "Compatibility of household appliances with DC microgrid for PV systems" [Heliyon 6 (12), (December 2020) Article e05699].

[This corrects the article DOI: 10.1016/j.heliyon.

Multi-dimensional optimization of InGaAs thermophotovoltaic cell using real coded genetic algorithm.

The optimization of thermophotovoltaic (TPV) cell efficiency is essential since it leads to a significant increase in the output power. Typically, the optimization of InGaAs TPV cell has been limited to single variable such as the emitter thickness, while the effects of the variation in other design variables are assumed to be negligible. The reported efficiencies of InGaAs TPV cell mostly remain < 15%.

MoS/h-BN/Graphene Heterostructure and Plasmonic Effect for Self-Powering Photodetector: A Review.

A photodetector converts optical signals to detectable electrical signals. Lately, self-powered photodetectors have been widely studied because of their advantages in device miniaturization and low power consumption, which make them preferable in various applications, especially those related to green technology and flexible electronics. Since self-powered photodetectors do not have an external power supply at zero bias, it is important to ensure that the built-in potential in the device produces a sufficiently thick depletion region that efficiently sweeps the carriers across the junction, resulting in detectable electrical signals even at very low-optical power signals.

Compatibility of household appliances with DC microgrid for PV systems.

DC distribution of PV systems has spread back especially in the residential sector as a variety of electronic appliances became locally available in the market. The compatibility of household appliances with the best voltage-level in a DC environment is the field that still in the research phase and has not yet made a practically extensive appearance. This paper mainly discusses this issue by providing a review of the concerning research efforts, identifying the gaps in the existing knowledge.

Role of optimization algorithms based fuzzy controller in achieving induction motor performance enhancement.

Three-phase induction motors (TIMs) are widely used for machines in industrial operations. As an accurate and robust controller, fuzzy logic controller (FLC) is crucial in designing TIMs control systems. The performance of FLC highly depends on the membership function (MF) variables, which are evaluated by heuristic approaches, leading to a high processing time.

Toward Enhanced State of Charge Estimation of Lithium-ion Batteries Using Optimized Machine Learning Techniques.

State of charge (SOC) is a crucial index used in the assessment of electric vehicle (EV) battery storage systems. Thus, SOC estimation of lithium-ion batteries has been widely investigated because of their fast charging, long-life cycle, and high energy density characteristics. However, precise SOC assessment of lithium-ion batteries remains challenging because of their varying characteristics under different working environments.

Applications of Photonics in Agriculture Sector: A Review.

The agricultural industry has made a tremendous contribution to the foundations of civilization. Basic essentials such as food, beverages, clothes and domestic materials are enriched by the agricultural industry. However, the traditional method in agriculture cultivation is labor-intensive and inadequate to meet the accelerating nature of human demands.

UV-Vis Spectroscopy: A New Approach for Assessing the Color Index of Transformer Insulating Oil.

Monitoring the condition of transformer oil is considered to be one of the preventive maintenance measures and it is very critical in ensuring the safety as well as optimal performance of the equipment. Various oil properties and contents in oil can be monitored such as acidity, furanic compounds and color. The current method is used to determine the color index () of transformer oil produces an error of 0.

Temperature dependence of impact ionization in InAs.

An Analytical Band Monte Carlo model was used to investigate the temperature dependence of impact ionization in InAs. The model produced an excellent agreement with experimental data for both avalanche gain and excess noise factors at all temperatures modeled. The gain exhibits a positive temperature dependence whilst the excess noise shows a very weak negative dependence.

Temperature dependence of gain and excess noise in InAs electron avalanche photodiodes.

Measurement and analysis of the temperature dependence of avalanche gain and excess noise in InAs electron avalanche photodiodes (eAPDs) at 77 to 250 K are reported. The avalanche gain, initiated by pure electron injection, was found to reduce with decreasing temperature. However no significant change in the excess noise was measured as the temperature was varied.

High speed InAs electron avalanche photodiodes overcome the conventional gain-bandwidth product limit.

High bandwidth, uncooled, Indium Arsenide (InAs) electron avalanche photodiodes (e-APDs) with unique and highly desirable characteristics are reported. The e-APDs exhibit a 3dB bandwidth of 3.5 GHz which, unlike that of conventional APDs, is shown not to reduce with increasing avalanche gain.