Loss Of Efficiency Research Articles

In planta transformation in wheat: an improved protocol to develop wheat transformants.

Lack of efficient transformation protocol continues to be a major bottleneck for successful genome editing or transgenic development in wheat. An in planta transformation method was developed in Indian bread wheat in earlier study (Vasil et al. in Nat Biotechnol 10:667-674, 1992) which was labour-intensive and time-consuming. In the present study, in planta transformation method was improved to make it simple, efficient, less labour-intensive and time-saving. PCR-based screening for generated transformants at T0 stage was introduced in this method. Shoot apical meristem of two days old wheat seedling was inoculated with the routine active culture of Agrobacterium tumefaciens harboring plasmid pCAMBIA1300-Ubi-GFP having gene GFP under the control of Zea mays ubiquitin promoter. PCR analysis at T0 stage confirmed 27 plants to be transgene positive. These 27 plants were only taken to the next generation (T1) and the rest were discarded. At T1 generation 6 plants were analyzed to be PCR positive. Out of them, 4 plants were confirmed to have stable integration of transgene (GFP). Fluorescent microscopy at T1 stage confirmed the 4 Southern hybridization positive plants to be expressing reporter gene GFP. Screening at T0 stage, reduced the load of plants to be taken to T1 generation and their screening thereof at T1 with no overall loss in transformation efficiency. We successfully transformed wheat genotype HD2894 with 3.33% transformation efficiency using a simple, effective method which was less labour-intensive and less time-consuming. This method may be utilized to develop wheat transgenic as well as genome edited lines for desirable traits.

Coaxial Electrospun Porous Core-Shell Nanofibrous Membranes for Photodegradation of Organic Dyes.

In this study, a series of AgCl/ZnO-loaded nanofibrous membranes were prepared using coaxial electrospinning. Their physical and chemical characteristics were evaluated by SEM, TEM, XRD, XPS, IR, PL, and UV-visible spectrometer, and the photocatalytic experiments using methylene blue (MB) as a model pollutant. The formation of AgCl/ZnO heterojunction and the structure of core-shell nanofibers with porous shell layer were confirmed. AgCl/ZnO photocatalysts were also effectively loaded onto the surfaces of the porous core-shell nanofibers. The results of photocatalytic experiments revealed that the AgCl/ZnO (MAgCl:MZnO = 5:5)-loaded nanofibrous membrane achieved a degradation efficiency of 98% in just 70 min and maintained a photocatalytic efficiency exceeding 95% over the first five experimental cycles, which successfully addressed the issues of photocatalytic efficiency loss during the photodegradation of MB with AgCl/ZnO nanoparticles as photocatalyst. The photodegradation mechanism was also researched and proposed.

Revealing and optimizing the design of cover installation for outdoor units of air conditioners through CFD simulations and thermodynamic modeling

When renewing building facades in most Chinese cities, covers are often designed and installed to conceal the outdoor units of residential split air conditioners for congruousness of building facades. However, how those covers impact airflow and energy efficiency should be thoroughly examined. This study investigates two popular designs of cover (louver and circular-hole) and selects Nanjing, renowned for its hot summers, as the case city. This study employs Computational Fluid Dynamics models to simulate airflow obstruction caused by the covers surrounding the outdoor units. Grey Model, trained from the CFD results, quantifies interactions between design of cover and inlet air temperature. Additionally, a thermodynamic model assesses the covers' impact on the coefficient of performance of air conditioners. The findings reveal that the primary cause of outdoor unit overheating is warm air backflow from the outlet to the inlet. A mere 1 °C increase in inlet air temperature can reduce COP by 4.1%–8.7%. The maximum temperature differences caused by different designs of cover are 4.5 °C for the louver type and 4.4 °C for the circular-hole type. To mitigate these negative impacts, optimal design recommendations are provided: a minimum distance between the cover and outdoor unit of 0.29 m for louver type and 0.1 m for circular-hole type, both feasible in most installations. These findings can help designers, manufacturers, installers and policymakers, to facilitate the design and installation of optimal covers for outdoor air-conditioning units, thus minimizing energy efficiency losses.

Novel nano-fertilizers derived from drinking water industry waste for sustained release of macronutrients: performance, kinetics and sorption mechanisms

Nanotechnology has emerged as a promising approach for the controlled release of nutrients, particularly phosphorus and potassium. These essential plant nutrients are often applied in excess, leading to environmental pollution and loss of efficiency in crop production. Innovative economic and highly efficient fertilizers are urgently needed to achieve the targeted crop production worldwide in the presence of limited land and water resources. Therefore, in this study, novel, eco-friendly, cost-effective and enhanced efficiency nano-enabled fertilizers, NEF (nWTF1and nWTF2) were synthesized by impregnation of nanostructured water treatment residuals (nWTR) with (KH2PO4 + MgO) at 1:1 and 3:1 (w/w) ratios respectively using a planetary ball mill. The nWTR, nWTF1 and nWTF2 were extensively characterized. The water retention behavior and the sustained release of nutrients from the fabricated nano-enabled fertilizers (nWTF1 and nWTF2) in distilled water and sandy soil were investigated and monitored over time. The water retention capacity of the soil treated with nWTF2 after 26 days was 9.3 times higher than that of soil treated with conventional fertilizer. In addition, the nWTF2 exhibited lower release rates of P, K and Mg nutrients for longer release periods in comparison with the conventional fertilizers. This is a significant advantage over traditional fertilizers, which release nutrients quickly and can lead to leaching and nutrient loss. The main interaction mechanisms of PO4–K–Mg ions with nWTR surface were suggested. The results of the kinetics study revealed that power function was the best suitable model to describe the kinetics of P, K and Mg release data from NEF in water and soil. The produced NEF were applied to Zea maize plants and compared to commercial chemical fertilizer control plants. The obtained results revealed that the nano-enabled fertilizers (nWTF1 and nWTF2) significantly promoted growth, and P content compared with the commercial chemical fertilizer treated plants. The present work demonstrated the power of nano enabled fertilizers as efficient and sustained release nano-fertilizers for sustainable agriculture and pollution free environment.

The Role of Efficiency in Beverage Packaging Industry

In fact, the performance of an organization is reflected in its efficiency and best resource utilization. For manufacturing companies, efficient production is a major element of operational efficiency. The main purpose of this study is to identify the factors that affect the efficiency of the beverage Can industry at Ball Egypt, including the availability and quality of raw materials, good conditions for the work environment, planning, high machine capability, and purchasing power, in addition to the contributions of communication, on-the-job training, and intellectual capital to boost the efficiency of the plant. The study used the scale method by using surveys distributed individually to employees as the main tool for data collection. Discovering that the work environment and planning are core functions has an impact on plant efficiency and makes the best use of available resources. High-quality raw materials and machine capability drive the entity to increase productivity and minimize downtime while increasing efficiency. Purchasing power helps to keep lines stable and machine durability high, but it had a negative impact on efficiency. To maximize the outcome of any activity, communication is required to share ideas and handle tasks between departments, as well as to resolve conflicts that may arise. Intellectual capital involved in each department reinforced a good environment and continuously boost incremental development, especially for a fast-changing industry and emerging new entrants. On-the-job training prepares employees to improve their skills and work hard to meet efficiency goals. Through the study, it appeared that missing intentions from top management will cause high losses in efficiency. High-speed lines for beverage Can manufacturing are in dire need of all of these variables to scale up efficiency significantly. Efficiency and effectiveness are inextricably linked and have an impact on the output of any process. Creating a framework for critical factors that affect efficiency will aid the organization's efforts to improve the efficiency of its operations.

Causal Selection of Covariates in Regression Calibration for Mismeasured Continuous Exposure.

Regression calibration as developed by Rosner, Spiegelman, and Willett is used to adjust the bias in effect estimates due to measurement error in continuous exposures. The method involves two models: a measurement error model relating the mismeasured exposure to the true (or gold-standard) exposure and an outcome model relating the mismeasured exposure to the outcome. However, no comprehensive guidance exists for determining which covariates should be included in each model. In this article, we investigate the selection of the minimal and most efficient covariate adjustment sets under a causal inference framework. We show that to address the measurement error, researchers must adjust for, in both measurement error and outcome models, any common causes (1) of true exposure and the outcome and (2) of measurement error and the outcome. We also show that adjusting for so-called prognostic variables that are independent of true exposure and measurement error in the outcome model, may increase efficiency, while adjusting for any covariates that are associated only with true exposure generally results in efficiency loss in realistic settings. We apply the proposed covariate selection approach to the Health Professional Follow-up Study dataset to study the effect of fiber intake on cardiovascular disease. Finally, we extend the originally proposed estimators to a nonparametric setting where effect modification by covariates is allowed.

The role of fines in espresso extraction dynamics

The impact of particle size distribution of coffee grounds on espresso extraction was explored. Finely ground coffee for espresso has a characteristically bimodal particle size distribution. For a given median grind size, different grinding technologies can yield a different share of fines (particles < 100 µm). We performed espresso extractions for a range of median particle sizes and systematically varying the share of fines by adding sieved fines to the coffee grounds. Dynamic beverage weights, extraction percentage, extraction time and dynamic headspace PTR-MS (proton-transfer mass spectrometer) analysis and sensory evaluation of the resulting brews were measured. We show that the share of fines plays a key role in the espresso extraction flow rate. An increase of share of fines decreases coffee bed permeability, leads to reduced flow rates and longer extraction times. A statistical model using partial least squares regression of the particle size distributions of coffee grounds confirms that fines decrease the coffee bed permeability. The PTR-MS analysis shows a non-linear increase of aroma compounds in the cup with increasing extraction yield. Our hypothesis is that both extraction efficiency and post-extraction evaporative losses of aroma compounds influence the final aroma compound concentrations in the cup.

Two-in-one strategy for optimizing chemical and structural properties of carbon felt electrodes for vanadium redox flow batteries

ABSTRACT Vanadium redox flow batteries (VRFBs) have received significant attention for use in large-scale energy storage systems (ESSs) because of their long cycle life, flexible capacity, power design, and safety. However, the poor electrochemical activity of the conventionally used carbon felt electrode results in low energy efficiency of the VRFBs and consequently impedes their commercialization. In this study, a carbon felt (CF) electrode with numerous nanopores and robust oxygen-containing functional groups at its edge sites is designed to improve the electrochemical activity of a carbon felt electrode. To achieve this, Ni metal nanoparticles were initially precipitated on the surface of the CF electrode, followed by etching of the precipitated Ni nanoparticles on the CF electrode using sulfuric acid. The resulting CF electrode had a specific surface area eight times larger than that of the pristine CF electrode. In addition, the oxygen-containing functional groups anchored at the graphite edge sites of the nanopores can act as robust electrocatalysts for VO2+/VO2 + and V2+/V3+ redox reactions. Consequently, the VRFB cell with the resulting carbon felt electrode can deliver a high energy efficiency of 86.2% at the current density of 60 mA cm−2, which is 20% higher than that of the VRFB cell with the conventionally heat-treated CF electrode. Furthermore, the VRFB cell with the resultant carbon felt electrodes showed stable cycling performance with no considerable energy efficiency loss over 200 charge-discharge cycles. In addition, even at a high current density of 160 mA cm−2 , the developed carbon felt electrode can achieve an energy efficiency of 70.1%.

SiO2/WO3/ZnO based self-cleaning coatings for solar cells

The accumulation of pollution and any kinds of contamination on the glass cover of the solar cell affects the efficiency of the photovoltaic (PV) systems. The contamination on the glass cover can absorb and reflect a certain part of the sunlight irradiation, which can decrease the intensity of the light coming in through the glass cover. With the study, it was planned to develop self-cleaning coatings for the PV systems. It was aimed to prevent or reduce the contamination-induced efficiency loss of the existing PV systems. In the scope of the project, SiO2/WO3 and SiO2/WO3/ZnO composites were coated from their solutions on the glass substrates using a dip-coating technique. WO3 was selected as a photocatalyst semiconductor. Under the UV light irradiation, WO3 could absorb the photons of the UV light, generating the photoinduced charge carriers. The photoexcited charge carriers provide both the photoinduced hydrophilicity on the surface of the coating and the photocatalytic degradation of the organic contaminants accumulated on the surface of the coating, which allows water droplets to spread and flow on the surface of the cover glass to remove the contaminations. However, the recombination rate of the photoexcited charge carriers on the WO3 film was high. In order to suppress the recombination of the photoinduced charge carriers, WO3 was coupled with SiO2 and ZnO. Both of these semiconductors improved the photocatalytic activity of the WO3 film. Although SiO2 has superior features in terms of the light transmission, it was not very effective under UV light as a photocatalyst alone. The widely preferred photocatalyst ZnO was added into the composite film structure to enhance the photocatalytic activity. The self-cleaning mechanism of the film coatings on a solar cell was investigated through the photocatalytic dye removal efficiency on the as-prepared film samples. There was a slight decrease in the light transparency and the solar cell efficiency because of the WO3 content of the composite film. On the other hand, coupling the SiO2/WO3 film with ZnO enhanced the photocatalytic activity, and it suppressed the reduction effect of the WO3 phase on both the light transparency and the solar cell efficiency. The photocatalytic dye removal efficiency was increased to over 90% after 240 min of UVA light irradiation. In addition, the solar cell coated with the SiO2/WO3/ZnO film provided almost the same solar cell efficiency as the uncoated solar cell. The water contact angle measurement also exhibited the photocatalytic degradation of the model contamination on the glass cover of the solar cell under the UVA light irradiation.Graphical

The Effect of Different Orchard Ground Conditions on the Performance of A Mechanical Hazelnut Harvesting Machine

In this study, the values of harvesting efficiency, field productivity, kernel productivity, kernel losses, and foreign material separation efficiency of hazelnut harvesting machine with mechanical harvesting unit were determined under different orchard ground conditions (ground preparation before harvesting (OG1) and without ground preparation (OG2)). Also, it was observed how these conditions affect the operation of the hazelnut harvesting machine. For this purpose, the harvesting efficiency, field productivity, kernel productivity and kernel losses of the hazelnut harvesting machine in OG1 and OG2 plots at 265.50 kg ha-1 orchard yield, 1600 mm working width and 1.60 m s-1 working velocity in two different orchard grounds were 96.05%, 90.15%; 8.624 h ha-1, 9.839 h ha-1; 0.116 ha h-1, 0.102 ha h-1; 778.72 kg h-1, 739.76 kg h-1; 3.95%, 9.85%, respectively. The hazelnut harvesting machine with a mechanical harvesting unit can work independently from the ground conditions and we can say that it is an alternative to other hazelnut harvesting machines. The data obtained from the study will help the decision-making process for the best selection and use by providing the necessary technical information about the functional aspects of the machine. Complete mechanization of hazelnut harvesting will lead to a decrease in labor requirements, thus increasing product profitability through a decrease in production cost. The presence of machines with high-performance characteristics in hazelnut harvesting mechanization will shorten the time the product stays on the ground and increase the quality of the harvested product.

Impact of DC-DC Converters on the Energy Performance of a Dense Concentrator PV Array under Nonuniform Irradiance and Temperature Profiles

Efficiency losses resulting from electrical mismatching in densely packed photovoltaic arrays present a significant challenge, particularly exacerbated in nonuniformly illuminated receivers and under varying temperatures. Serial configurations are particularly susceptible to radiation nonuniformities, while parallel systems are negatively affected by temperature variations. Various authors have recommended the incorporation of electrical voltage and current sources to mitigate these losses. This study explores different electrical connection configurations utilizing concentrated photovoltaic (CPV) cells and DC-DC electrical current converters. A self-adaptive microfluidic cell matrix cooling system is employed to mitigate thermal dispersion caused by the highly nonuniform illumination profile. The obtained results for each configuration are compared with the total electrical power produced by individual cells, operating under identical radiation and temperature conditions to those of the entire array. The results reveal a noteworthy increase in production across all studied configurations, with the parallel–series arrangement demonstrating the most promising practical utility. This configuration exhibited a remarkable 50.75% increase in power production compared with the standard series connection.

Loss of efficiency in flat belt quarter-turn drive system

In the flat belt quarter-turn drive systems, the drive efficiency loss is a noteworthy problem. However, many factors can lead to a loss of efficiency, such as large load, insufficient tension, and belt misalignment, but in the flat belt quarter-turn drive system, because of its special design principles, the belt misalignment becomes a very important factor. To address this issue, a set of flat belt quarter-turn drive devices and test systems are designed and built. To further study the causes of efficiency loss, a series of tests are carried out with the slip rate as the index and the belt misalignment, braking torque, motor speed, and pre-tension as the experimental factors. In the process of research, the OFAT experimental method and quaternary quadratic rotation orthogonal test are adopted. Through response surface analysis and variance analysis, the significance of these four factors on slip rate and the complex association is proved. Using the response surface plots, it is possible to estimate the extent of the speed loss of the flat belt quarter-turn drive under the range of operating conditions considered in this study.

A new methodology to robustify an experimental design: Application to the Baranyi model

A robust experimental design is a desired object for practitioners when there is uncertainty about any of the assumptions necessary to compute the optimal design. For instance, when they use non-linear models, which requires having nominal values of the parameters. Several alternatives have been developed in the literature to obtain robust experimental designs such as adaptive or Bayesian designs, among others. Here a new methodology is proposed to robustify the optimal experimental design. Based on the maximin idea, the method adds support points to the optimal design, to obtain designs that are robust. It is applied to the Baranyi model, one of the most used mathematical models in predictive microbiology to describe the behaviour of microorganisms in food products, an essential issue for human health. Previously, D-optimal designs are provided for the model, considering 4 and 6 parameters to be estimated. A sensitivity analysis is carried out regarding the deviations in the nominal values of the parameters, which shows a greater loss of efficiency for two of them. Given these results, the new methodology is applied to the D-optimal design, checking the robustness of the augmented designs through the efficiency achieved. Finally, c-, A- and I-optimal designs are calculated to provide accurate estimation of the model parameters and the predictions.

Transferable Energy Storage Bidder

Energy storage resources must consider both price uncertainties and their physical operating characteristics when participating in wholesale electricity markets. This is a challeng-ing problem as electricity prices are highly volatile, and energy storage has efficiency losses, power, and energy constraints. This paper presents a novel, versatile, and transferable approach combining model-based optimization with a convolutional long short-term memory network for energy storage to respond to or bid into wholesale electricity markets. We test our proposed approach using historical prices from New York State, showing it achieves state-of-the-art results, achieving between 70% to near 90% profit ratio compared to perfect foresight cases, in both price response and wholesale market bidding setting with various energy storage durations. We also test a transfer learning approach by pre-training the bidding model using New York data and applying it to arbitrage in Queensland, Australia. The result shows transfer learning achieves exceptional arbitrage profitability with as little as three days of local training data, demonstrating its significant advantage over training from scratch in scenarios with very limited data availability.

Novel differential power processing technique for uneven partial shading mitigation in PV systems

Photovoltaic (PV) system output power greatly depends on environmental operating conditions. Partial shaded condition (PSC) operates PV string under mismatch. PV module mismatch has been one of the major causes for reduced amount of output power. Maximizing the amount of energy extraction from PV system under mismatch greatly influenced by conversion efficiency as well as the mismatch mitigation topology used. Differential power processing (DPP) is one of the advanced techniques to deal with mismatch conditions and enhance power output from a PV system. In this paper hybrid modular DPP topology is presented. The proposed technique mitigates the effect of mismatches at submodule and enhance power extraction from PV string. Since in majority shading on a PV module is nonuniform. The conversion efficiency of module level DPP shading mitigation techniques enhanced using submodule level DPP architecture. To demonstrate its applicability simulation study is carried out in MATLAB Simulink and results are compared with traditional bypass method and module level DPP. Simulation results showed the reduction in mismatch loss and improvement in efficiency and power output.

Long term aging studies of the new PMTs used for the HL-LHC ATLAS hadron calorimeter upgrade

The central hadron calorimeter (TileCal) of the ATLAS experiment at the Large Hadron Collider (LHC) is a sampling calorimeter read out by about 10,000 photomultipliers(PMTs). Earlier studies of performance showed a degradation in PMTs response as a function of theintegrated anode charge. At the end of the High-Luminosity LHC (HL-LHC) program, the expectedintegrated anode charge for PMTs reading out the most exposed cells is 600 C, and theirprojected response loss is 25%.These PMTs (≈ 8% of the total TileCal PMTs) willbe replaced with a newer version PMT with the same geometry.A test set-up is being used in the Pisa laboratory to study thelong term response of this new PMT modeland compare it to theold PMT model currently installed in TileCal. For the first time thisnew PMT has been tested after integrating more than 800 C of anode charge. Preliminaryresults obtained from data collected in Pisa over a period exceeding two years areshown in this paper. We also introduce a preliminary study aimed to disentangle the contribution tothe PMT response degradation due to the loss of quantum efficiency and to the change in absolutegain.

Intra-class deep learning object detection on embedded computer system

&lt;span lang="EN-US"&gt;Implementation of artificial intelligence tends to be portable, mobile and embeds in embedded computer system (EBD). EBD is a special-purpose computer with limited capacity in a small-form size. Deep learning (DL) had known as cutting edges for object recognition. With DL, object feature extraction analysis is omitted. DL requires large computing resources and capacity. Implement DL algorithm on EBD goal to achieves high detection accuracy and high-efficiency resources. Hence, be able to cope with intra-class variations, and image disturbances. By those challenges and limitations, this study reports the performance of EBD to recognize an object which has high variations in their class, through an optimal raw-input dataset. The raw-input dataset performed optimization process with a supervisor. Yield is the proper optimal input dataset in size. The performance results observed begin from training dataset until evaluation stage of DL. The comparison performs in efficiency resources, loss, validation-loss, timesteps, and detection accuracy by multiclass confusion matrix analysis. This study shows through this purpose method efficient resources are highly archived. Shorter timesteps ensure training stage is successful, and detection accuracy is perfectly archived. In addition, this study proves DL method archived great performances in classifying object that has identical structure.&lt;/span&gt;

Privacy-Preserving Network Embedding Against Private Link Inference Attacks

Network embedding represents network nodes by a low-dimensional informative vector. While it is generally effective for various downstream tasks, it may leak some private information of networks, such as hidden private links. In this work, we address a novel problem of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">privacy-preserving network embedding against private link inference attacks</i> . Basically, we propose to perturb the original network by adding or removing links, and expect the embedding generated on the perturbed network can leak little information about private links but hold high utility for various downstream tasks. Towards this goal, we first propose general measurements to quantify privacy gain and utility loss incurred by candidate network perturbations; we then design a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P</i> rivacy- <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P</i> reserving <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</i> etwork <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">E</i> mbedding ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e.</i> , PPNE) framework to identify the optimal perturbation solution with the best privacy-utility trade-off in an iterative way. Furthermore, we propose many techniques to accelerate PPNE and ensure its scalability. For instance, as the skip-gram embedding methods including DeepWalk and LINE can be seen as matrix factorization with closed-form embedding results, we devise efficient privacy gain and utility loss approximation methods to avoid the repetitive time-consuming embedding training for every candidate network perturbation in each iteration. Experiments on real-life network datasets (with up to millions of nodes) verify that PPNE outperforms baselines by sacrificing less utility and obtaining higher privacy protection.

Impact of Climate Change on the Performance of Household-Scale Photovoltaic Systems

The objective of this article was to investigate the impacts of climate change on photovoltaic systems among renewable energies by the end of the 21st century. One hypothesis posited that due to decreased cloud cover as a result of changing climate, the geographical region under examination would receive more solar irradiation—usable by photovoltaic panels—which would in turn increase the annual electrical energy production of these systems. Another hypothesis suggested that the average temperature increase, associated with changing climate conditions, would detrimentally affect the efficiency of electricity production in photovoltaic systems. The study was based on the simulation of a household-scale photovoltaic model. This simulation calculated the system's performance on an hourly basis depending on inputs and summed these to produce an annual value. Input values were derived from climate scenario databases. These variables included global horizontal irradiance, direct horizontal irradiance, temperature, and wind speed. The output was the aforementioned quantity of annual electrical energy production. An analysis occurred between the annual average global horizontal irradiance and the annual average air temperature in relation to the quantities of annual electrical energy production. Pearson and partial correlation examinations among the variables demonstrated that unfavorable scenarios resulted in reduced efficiency of photovoltaic electrical energy production, primarily due to rising temperatures. Among other contributions, this article can support research into the active cooling of photovoltaic systems and the examination of their viability to mitigate efficiency losses caused by current and future temperature increases. Doi: 10.28991/HIJ-2024-05-01-01 Full Text: PDF

A new path towards ultra-high efficient laser power converters: Silicon carbide-based multijunction devices

Current high power laser transmission technology faces two major limitations to improve the efficiency of the photovoltaic receivers: the intrinsic entropic losses associated to low bandgap materials (such as GaAs) and the series resistance losses that degrade the device performance at high power densities. The use of high bandgap materials and new architectures for laser power converters (LPC) have been pointed out as alternatives to overcome these limitations. In this work, three silicon carbide polytypes (3C, 4H and 6H) are proposed as base materials for the standard horizontal laser power converter (hLPC) architecture and the Vertical Epitaxial Hetero-Structure Architecture (VEHSA). 3C SiC based hLPCs outperform the power converters based on the other two polytypes, achieving a maximum efficiency of 84.6% at ▪, but suffer from series resistance losses, that deteriorate their efficiency, at higher laser power densities. This issue is solved with 3C SiC 4 cells VEHSAs that demonstrated increasing efficiency with the input power, reaching a maximum of 87.4% at ▪. The VEHSA reduced number of cells minimize the risks of efficiency losses due to current mismatch between cells. These results support the feasibility of a new generation of LPCs capable of efficiently convert ultra-high laser power densities.