Standard Test Conditions Research Articles

Exploring the Limits and Balancing Efficiency, Transparency, and Esthetics in Ultrathin a‐Si:H Transparent Photovoltaic Devices

Transparent photovoltaic (TPV) devices represent a promising advance in photovoltaic technologies, particularly in building‐integrated photovoltaics (BIPV). Unlike conventional photovoltaics, which primarily prioritize efficiency, TPV must balance between efficiency, transparency, and aesthetics. These additional dimensions introduce unique challenges on device architecture. This article reports the development of wide‐bandgap, inorganic‐based TPV devices integrating ultrathin hydrogenated amorphous silicon (a‐Si:H) as a transparent absorber, with carrier selective contacts and transparent electrodes. The article analyzes how absorber thickness influences the electrical, optical, and aesthetic performance of devices, evaluating key parameters in TPV such as light utilization efficiency (LUE), average photopic transmittance (APT), color rendering index (CRI), and electrical properties such as power conversion efficiency (PCE). The device structure is SLG/FTO/AZO/a‐SiCx(n)/a‐Si:H/V2Ox/AZO. This approach results in PCE ranging from 1.7% with an APT of 60% to a PCE of 4.1% with an APT of 28%, yielding LUE values between 0.9% and 1.3%. Device characterization encompasses optical spectrophotometry, J–V measurements under standard test conditions, spectral response analysis, and variable illumination measurements (VIM). Additionally, color characterization is conducted using CIE 1931 color space maps to determine the chromaticity coordinates, CRI, and the variation of color as a function of absorber thickness.

Discrimination of high impedance fault in microgrid power network using semi-supervised machine learning algorithm

This work proposes a semi-supervised classification approach for discriminating high-impedance (HI) faults and other transients in a photovoltaic (PV) interconnected microgrid (MG) network. The suggested classifier combines unsupervised K-means clustering with the supervised multi-layer perceptron neural network algorithm. The K-means clustering technique is utilized in the first phase to detect and remove irrelevant instances from multiple events in the data set. To obtain the final predictions of targeted labels, clustered cases from the first phase are utilized to learn the multi-layer perceptron neural network classifier in the next phase. The suggested method outperforms stand-alone classifiers (K-means clustering and multi-layer perceptron) by providing enhanced accuracy and success rate of discriminating HI fault under standard test conditions and weather intermittency of PV. Furthermore, the results of the performance study clearly show that the suggested model is more resilient and offers superior performance than the stand-alone classifiers under the standard test condition and uncertainty of PV in MG networks.

Experimental validation of an advanced electrical model for lead-acid batteries

Batteries are essential for the transition to sustainable energy sources. While various battery types exist, lead-acid batteries offer the most economical option currently available. The battery model plays an important role in the simulation of renewable energy systems and the estimation of battery condition in the development of the model-based battery management system (BMS). In this paper, we propose a novel approach to develop an innovative electrical model that accurately reflects lead-acid battery behavior. This model, which can be described as an equivalent circuit, reliably represents the lead-acid battery by taking into account all aspects of battery behavior within a dynamic system. It encompasses factors such as internal resistance and capacitance, as well as open circuit voltage (VOC) and state of charge (SOC). Further validation using data from an actual 180 Ah, 2V Tudor C10 battery and comparison with developed models reveals the superior accuracy of the proposed model, particularly during charging and discharging operations. The results show that the proposed electrical model exhibits mean bias error (MBE) and root mean square error (RMSE) values of less than 90 mV/cell and 80 mV/cell, respectively, for charging operations, and less than 160 mV/cell and 70 mV/cell, respectively, for discharging operations. These results highlight the ability of the proposed model to comprehensively capture the dynamic complexities of lead-acid battery behavior, outperforming its counterparts in terms of accuracy under standard test conditions. It serves as a powerful tool in simulation programs such as MATLAB/Simulink, PSIM, PSpice and Labview, facilitating the solution of problems and equations related to electrical circuits.

Quantifying Measurement Uncertainty in Photovoltaic Module Performance at Standard Test Conditions: A Machine-Based Approach

This paper presents an in-depth analysis of measurement uncertainty in the output parameters of photovoltaic (PV) devices, focusing specifically on measurements conducted under standard test conditions (STC). Accurate characterization of module I-V performance is crucial for PV manufacturers, researchers, and investors alike. The study provides a comprehensive overview of the measurement procedures for both performance and temperature coefficient of PV modules, with a strong emphasis on the detailed calculation of associated uncertainties. Notably, the research was conducted under real-world sunlight conditions, with special attention given to reference devices such as reference cells, modules, or pyranometers, which play a pivotal role in determining overall uncertainty components. By utilizing a diverse array of machines from various sources, the results obtained are applicable across a wide range of measurement configurations. Furthermore, adherence to the ISO/IEC 17025 series of standards ensures a standardized and reliable approach. The novelty of this research lies in its comprehensive approach to uncertainty analysis, encompassing both performance and temperature coefficient measurements under real-world conditions. By providing valuable guidelines for PV module characterization and reliability assessment, particularly in uncertainty estimation, this study contributes significantly to the advancement of photovoltaic technology.

NaHCO3 modulates the bla operon and β-lactam susceptibility in borderline oxacillin-resistant Staphylococcus aureus (BORSA).

Methicillin-resistant Staphylococcus aureus (MRSA) are resistant to nearly all β-lactam antibiotics under standard testing conditions. However, a novel phenotype exists wherein certain MRSA strains exhibit β-lactam susceptibility in the presence of bicarbonate (termed 'NaHCO3-responsive'), an abundant ion in mammalian tissues and blood. This suggests that specific MRSA infections may be treatable by β-lactams. NaHCO3 responsiveness appears due to effects of NaHCO3 on the expression mecA/PBP2a and other accessory genes required for PBP functionality. mecA expression can be co-regulated by the bla operon regulatory genes, blaI and blaR1. To elucidate the influence of NaHCO3 specifically on the bla operon via investigations of the impact of NaHCO3 on β-lactamase hyper-producing, mecA-negative, borderline oxacillin-resistant Staphylococcus aureus (BORSA) strains. Evaluate the effect of NaHCO3 on β-lactam susceptibility via minimum inhibitory concentrations (MIC) assay, expression of genes within the bla operon (blaZ, blaI, blaR1) via RT-qPCR, and β-lactamase (BlaZ) activity via nitrocefinase assay in BORSA. NaHCO3 enhanced susceptibility to β-lactamase-susceptible β-lactams penicillin and ampicillin. NaHCO3 had no impact on susceptibility to the anti-staphylococcal β-lactams oxacillin and cefazolin, or the anti-MRSA antibiotics vancomycin and daptomycin. NaHCO3 repressed expression of all genes within the bla operon and reduced β-lactamase production. These data demonstrate that NaHCO3 influences expression of genes within the bla operon, translating to reduced β-lactamase production and enhanced β-lactam susceptibility in BORSA strains. Furthermore, this indicates that the classical blaZ regulators, blaI and blaR1, are the likely mediators of NaHCO3-mediated repression of mecA. However, questions still remain regarding the mechanism via which NaHCO3 regulates the bla operon.

Evaluation of the impact of oleic acid-capped Al2O3 nanoparticles on the tribological performance of conventional lube oil

Purpose This study aims to evaluate the influence of oleic acid (OA)-capped Al2O3 nanoparticles on the tribological performance of conventional lube oil. The goal is to determine the optimal nanoparticle concentration that enhances lubricant efficiency by reducing friction and wear. Design/methodology/approach The research involved preparing nanolubricants with four different concentrations of Al2O3 nanoparticles: 0.05, 0.1, 0.25 and 0.5 wt.%. Tribological performance was assessed using a four-ball tribotester, which measured the coefficient of friction (COF) and wear scar diameter (WSD) under standardized testing conditions. Findings The experimental results revealed that the nanolubricant containing 0.1 wt.% OA-Al2O3 nanoparticles exhibited the most significant improvement in tribological performance. This formulation achieved a 38.84% reduction in COF and a 23.87% reduction in WSD compared to the base lubricant. These findings demonstrate the effectiveness of incorporating OA-capped Al2O3 nanoparticles in reducing friction and wear, thereby enhancing the overall performance of conventional lubricants. Originality/value This study demonstrates the benefits of OA-capped Al2O3 nanoparticles in lubricants, including a 38.84% reduction in COF and a 23.87% reduction in WSD. By systematically analyzing different nanoparticle concentrations, it identified that 0.1% by weight of nanoparticles is the most effective formulation for reducing friction and wear. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0236/

Assessing the drought-tolerance and growth-promoting potential of strawberry (Fragaria × ananassa Duch.) rhizobacteria for consortium bioformulation

Plant growth-promoting rhizobacteria (PGPR) are known to influence plant root cells to regulate and induce specific traits related to growth promotion and survival. In the present study, rhizobacteria from strawberry plants were screened for stress tolerance under osmotic stress in TSB-mediated PEG 6000 (-0.73 MPa) and tested their ability to produce proline, exopolysaccharide, and free amino acids, all of which induce and regulate stress tolerance. The rhizobacteria were also distinguished for the production of 1-aminocyclopropane-1-carboxylate deaminase (ACCd) for the mitigation of drought stress. Among the 111 rhizobacterial isolates, 41 isolates grow above threshold limit in osmotic stress tolerance, 33 of which exhibited stress tolerance. Further characterization screened 27 isolates as capable growth promoters. Among the experimentally screened rhizobacteria, the isolates SBU4 and SDK8 [Pseudomonas fluorescens (OP627557) (PGPR1) and Pseudomonas glycinae (OP627558) (PGPR2)] exhibited the most promising phyto-beneficial potential. Both the isolates grew exponentially well during the log phase, with increased growth in Log CFU ml-1 under experimentally produced osmotic stress. The drought stress tolerance test results of the SBU4 and SDK8 isolates revealed the presence of proline (1.93 μg mL-1, 2.05 μg mL-1), exopolysaccharide (2.19 mg mg-1 protein, 2.58 mg mg-1 protein), and free amino acid (11.47 μmol g-1, 13.32 μmol g-1) and positive growth in ACCd-enriched DF media, an ACCd assay (α-ketobutyrate (0.56 μmol/ml, 0.64 μmol/ml) and ammonia (0.37 μg mL-1, 0.53 μg mL-1)). The isolates SBU4 and SDK8 performed well in qualitative tests for P solubilization, N fixing ability, siderophore chelation, HCN, and ammonia production, as well as in assays involving P producers (94.57 μg mL-1 and 92.86 μg mL-1), siderophore units (52.14% SU and 63.12% SU), and IAA producers (74.63 μg mL-1 and 72.64 μg mL-1). These rhizobacterial isolates were optimized under various growth factors (pH, temperature, incubation) to achieve a relatively high log CFU ml-1. The isolates achieved maximum Log CFU mL-1 when cultured in either a specific range of pH or temperature or growth period (incubation) under standard test conditions. The growth of cultures on cross-streaked nutrient agar plates was tested for an efficient, effective consortium bioformulation that enhances growth and specific traits (drought stress mitigation) in strawberry plants.

Low-voltage DC-DC off-grid PV system: various irradiance studies

The off-grid photovoltaic (OGPV) system, also referred to as a stand-alone power system, generates electricity from solar energy independently of the main electricity grid. However, photovoltaic (PV) modules face limitations in consistently providing the necessary voltage. Thus, a DC-DC converter is employed to adjust the voltage to match the requirements of the load. This paper proposes a detailed analysis of irradiance patterns resembling in-lab and real-world conditions to address the challenge of selecting the optimal DC-DC OGPV system capable of functioning effectively under standard test condition (STC) and dynamic test condition (DTC), respectively. Three proposed irradiance analyses, tailored to different environmental scenarios, aim to identify output performances for DC-DC OGPV system which are aligning with standards set by the International Electrotechnical Commission (IEC) 61727. The DC-DC OGPV system is simulated using MATLAB Simulink. Furthermore, comparative studies involving different PV module types and several switching techniques (pulse generator and maximum power point tracking or MPPT implementations), where findings are instrumental in advancing the development and projection planning for medium to high-voltage OGPV systems, contributing to the global initiative for accessible and sustainable energy solutions aligned with sustainable development goal (SDG 7).

Investigation of Standard Test Condition Requirement in Establishing Alternative Measurement Platform for Photovoltaic Cell

Abstract The output characteristics of any solar modules or solar cells are typically assessed according to the standard requirements known as Standard Test Conditions (STC). To meet the STC requirement before commercializing products, manufacturers must subject every fabricated solar cell or module to various tests. These tests include conducting current-voltage characteristics under specific conditions: a solar irradiance of 1000 W/m², a cell temperature of 25°C, and an air mass (AM) of 1.5. This study investigates this STC requirements for developing an alternative measurement platform for photovoltaic cells, specifically focusing on current-voltage characterization of solar cells. Utilizing calibrated photovoltaic cells, the optimal angles for Air Mass 1.0 and 1.5 was identified to be 48.2° and 41.8° respectively. Main methodology was segregated in three stages: first, correlating solar irradiance and illuminance under different light conditions, both outdoor and indoor; second, designing a system with a cooling device to stabilize cell temperature at 25°C; and third, developing a platform to meet AM 1.0 and 1.5 requirements. Results demonstrated varying irradiance outputs for sunlight, halogen lamps, and LED Grow Lights, with the latter achieving 810.2 W/m² under AM 1.5. The study also established optimal voltage and current settings for temperature stabilization, achieving 25°C in 3 minutes. Although the proposed solar simulator design did not reach the targeted 1000 W/m², it offers a feasible low-cost alternative for small-scale applications. The research underscores the technical viability of developing cost-effective solar simulators that meet STC requirements, despite challenges in achieving high irradiance levels with LEDs.

Stress–strain behaviour of wood in compression: experimental and analytical investigations

This study extensively investigates the compressive performance of two hardwood species (beech and birch) with the aim of developing simple yet efficient mathematical models to represent the stress–strain curves of wood along the different orientations. The proposed relationships were compared with the compressive data presented in this study and those compiled from the literature. Unlike models for cellular material used for wood in literature, the suggested relationships proved to be efficient in representing the complete stress–strain curves of wood by considering the micromechanical effects influencing the transverse behaviour of moderate- and high-density wood species such as beech and birch. The proposed models were shown to accurately capture the behaviour of beech and birch not only at standard testing conditions, but also at different environmental or processing conditions. Additionally, the models can successfully be applied to other hardwood and softwood species. These findings underscore the models' broad applicability and their value in advancing the understanding of wood's mechanical behaviour.

Advanced Performance Prediction of Triple-Junction Solar Cell Structures Using MATLAB/Simulink Under Variable Conditions

Raising the efficiency of triple-junction cells such as (GaInP/GaInAs/Ge) is an important goal for designing high-concentration photovoltaic systems. This purpose can be achieved by facing cell obstacles and acting on their configurations to sustain under highly concentrated sunlight and high operating temperatures. In this paper, a prediction performance study of triple-junction solar cells with four types of structures is proposed under variable conditions. The results show that the series structure is well-validated with experimental data under standard test conditions and is presented against those under variable conditions. Then, the triple-junction cells are compared and discussed in terms of photovoltaic cell open circuit voltage, photovoltaic cell electrical efficiency, fill factor, and temperature coefficients. Consequently, the results show that the cells can be separated into two categories that are useful for Low Concentration Systems and High Concentration Systems. The Low Concentration Systems present high efficiency at 20 suns. For the High Concentration Systems, the Hybrid 2 type demonstrates an optimal efficiency of 38.48% at 118 suns with a high FF (0.873) and shows a lower temperature coefficient than the series type. So, Hybrid 2 presents a good candidate for high-concentration systems with a performance better than the conventional triple-junction cells.

A Room-Level Indoor Localization Using an Energy-Harvesting BLE Tag

Energy-efficient and cost-effective localization systems are attractive for large-scale tracking and localization of goods. In this paper, we propose a room-level localization system using energy-harvesting BLE tags to track the targets. We introduce the Dempster–Shafer (D–S) evidence theory combined with fingerprinting technology for location estimation. To reduce the estimation complexity, we divide the indoor environment into clear areas and fuzzy areas. The D–S algorithm is employed to locate the target in the clear areas when the targets are only detected by the anchor nodes within a single room. Conversely, fuzzy areas are characterized by RSSI signals detected by anchor nodes across multiple rooms. Then, the system integrates fingerprint matching to ensure superior positioning accuracy across the deployment. Extensive experiments demonstrate that the proposed system maintains a room-level positioning accuracy above 99% under standard test conditions within an area of approximately 2000 m2 with lots of rooms.

Device optimization of all-perovskite triple-junction solar cells for realistic irradiation conditions

All-perovskite two-terminal tandem solar cells, comprising two or more junctions, offer high power conversion efficiencies (PCEs) that exceed the limits of single-junction photovoltaics. Realizing high-efficiency SCs requires carefully optimizing the photoactive layer, front electrodes, and functional layers. Here, we first aim to determine the optimal device architecture, i.e., the perovskites bandgaps and optimum layer thicknesses, for standard test conditions (STCs). We then optimize the energy yield (EY) under realistic outdoor conditions (ROCs), i.e., the overall electrical energy to be expected in one year at a specific location. In the first step, we reference our simulation with two terminal all-perovskite triple-junction SCs (2T3J-PSCs) to previously experimentally realized PSC with a PCE of 20.1% as a benchmark to derive the underlying diode parameters and use our in-house energy yield code combined with a hybrid particle swarm optimization and gravitational search algorithm (PSOGSA) to find the optimal bandgap combination and perovskite layer thicknesses. The optimized SCs with the optimal bandgap combination offer a PCE of 25.1% with a current density of 10.1 mA/cm2. Furthermore, the effect of the other functional layers, such as transparent conductive oxide (TCO), hole transport layer (HTL), and recombination junctions (RJs), is also investigated to enhance the cell performance further. The SCs with optimized layers exhibit improved parameters: PCE of 27.1%, with a relative improvement of 34.8% in the PCE compared with the fabricated cell, and a high current matching a of 10.8 mA/cm2. The numerical results showed that the reported cell can potentially achieve a PCE of 36% at an eVoc/EG ratio of 0.72. However, the optimal parameters may vary in real-world operating conditions due to variations in temperature, humidity, and light exposure. As a result, the optimal energy yield (EY) parameters may differ. Therefore, the energy yield optimizing process is also carried out by considering ROCs in Phoenix, AZ, USA, to find the best parameters under these conditions. We found that the optimum top layer bandgap under ROCs is lower than under STCs due to a bluer, more shifted spectrum in ROCs. After that, the optimized cell under ROCs is tested in several locations exhibiting different climatic conditions (Seattle, Honolulu, Los Angeles, Miami, and Milwaukee). The numerical results show that the optimized cell under ROCs offers an increase in energy yield in several locations compared to conventional single-junction crystalline Si-SCs (PCE = 23.6%) with a high energy yield of 648.2 kWh/m2 in Phoenix, with an improvement of 39.9% in the EY compared to the Si-SC counterpart. Our results provide design guidelines for fabricating a highly efficient triple-junction perovskite SC in the lab and outdoor applications and improve the efficiency of 2T3J-PSCs beyond the 30% limit.

Comparative Analysis of Material Efficiency and the Impact of Perforations on Heat Sinks for Monocrystalline Photovoltaic Panel Cooling

In this research, the design and simulation of a heat sink for photovoltaic panels were carried out using aluminum and copper, the most commonly used materials in heat dissipation systems. This heat sink consisted of fins that were tested both perforated and non-perforated to improve heat dissipation efficiency. This research stems from the need to reduce the temperature of photovoltaic panels during operation, as scientific evidence shows that photovoltaic panels experience a decrease in efficiency as the temperature increases, taking as a reference the temperature under standard test conditions. The simulations of photovoltaic panels with aluminum and copper fins, both perforated and non-perforated, followed a rigorous methodology. For validation, the simulation results were compared with field data, yielding a mean absolute percentage error of 1.71%. The findings indicate that copper fins reduced the temperature of the photovoltaic panel by 2.62 K, resulting in a 1.31% increase in efficiency. Similarly, aluminum fins reduced the temperature by 2.10 K, with a 1.05% increase in efficiency. Perforated copper fins achieved a temperature reduction of 3.07 K, increasing efficiency by 1.54%, while perforated aluminum fins reduced the temperature by 2.49 K, contributing to a 1.25% increase in efficiency.

A Low‐Acidity Chloride Electrolyte Enables Exceptional Reversibility and Stability in Aqueous Tin Metal Batteries

AbstractTin (Sn) metal has emerged as a promising anode for aqueous batteries, due to its high capacity, non‐toxicity, and cost‐effectiveness. However, Sn metal has often been coupled with strong and corrosive sulfuric acids (2–3 M), leading to severe electrode corrosion and hydrogen evolution issues. Although high efficiency and long cycling were reported, the results were achieved using high currents to kinetically mask electrode‐electrolyte side reactions. Herein, we introduce a low‐acidity tin chloride electrolyte (pH=1.09) as a more viable option, which eliminates the need of strong acids and enables a reversible dendrite‐free Sn plating chemistry. Remarkably, the plating efficiency approaches unity (99.97 %) under standard testing conditions (1 mA cm−2 for 1 mAh cm−2), which maintains high at 99.23–99.93 % across various aggressive conditions, including low current (0.1–0.25 mA cm−2), high capacity (5–10 mAh cm−2), and extended resting time (24–72 hours). The battery calendar life is further prolonged to 3064 hours, significantly surpassing literature reports. Additionally, we presented an effective method to mitigate the potential Sn2+ oxidization issue on the cathode, demonstrating long‐cycling Sn||LiMn2O4 hybrid batteries. This work offers critical insights for developing highly reversible Sn metal batteries.

Advancing global solar photovoltaic power forecasting with sub-seasonal climate outlooks

Given the high weather dependency of solar photovoltaic energy, accurate weather information ranging from days to weeks in advance are required for stable plant operation and management. This study emphasizes that sub-seasonal climate outlooks can advance global solar power forecasting. We evaluate the capacity factor (CF) for standard test conditions (CFstc), calculated from atmospheric reanalysis of surface solar irradiance and ambient air temperature, by comparing it with actual CF from two solar plants in Korea. Results confirm CFstc as a reliable estimate of actual CF. Application of this methodology to four-week outlooks from two state-of-the-art sub-seasonal climate forecast systems shows a significant anomaly correlation coefficient (ACC) skill for global solar power forecasting at least one week in advance (5–11 forecast days). Regional ACC skills vary at extended lead times, with South Asia, eastern South America and eastern Australia maintaining ACC > 0.6 for up to two weeks (12–18 forecast days). Notably, useful ACC skill persists for up to four weeks (26–32 forecast days) across 70.9 % of global land areas. These findings suggest that sub-seasonal climate outlooks can provide decision-making information in developing more reliable solar energy strategies, highlighting the importance of transdisciplinary collaboration between renewable energy and meteorological sectors.

Innovative materials integrated with PCM for enhancing photovoltaic panel efficiency: An experimental investigation

The electrical power generated by a photovoltaic panel is crucial due to the high demand for electricity. Operating temperatures above the Standard Test Conditions (STC) negatively impact the output power, which is a significant drawback of this technology. Therefore, it is essential to keep the front and back surface temperatures of the photovoltaic panel as low as possible. Phase Change Material (PCM) is a good passive cooling method, but it has low thermal conductivity. This paper introduces a novel material to address this issue. Iron Filling Waste (IFW) is integrated with PCM to cool the photovoltaic panel. This investigation is presented experimentally with three modules. The highest surface temperature of the reference panel, 78 °C, is recorded for the uncooled module, while with PCM- IFW is 70.5 °C. The comparative analysis shows that the PV module cooled by PCM-IFW achieved an efficiency enhancement and power output increase of 39 % and 33 % respectively, compared to the reference panel without cooling. IFW-PCM achieves an average enhancement in efficiency and output power by 23 % and 11 %, respectively, compared with panels that use PCM only. Also, IFW enhances thermal conductivity without any additional economic cost for the cooling systems.

Ray tracing design-optimization & experimental validation of water based optical filter to reduce solar PV module heating

The operating temperature of a photovoltaic (PV) module significantly impacts its efficiency. Increased temperatures reduce the efficiency due to a negative thermal coefficient, which decreases its power above standard test conditions (25 °C, 1000 W/m2). This research targets the reduction of thermal load on PV modules through the incorporation of a water-based optical filter, designed and optimized using ray tracing techniques. The optimal thickness for the glass was determined as 3 mm and 5 mm for the water layers of the filter, providing the best yield. The filter effectively absorbs 92 % of the infrared radiation and 47 % of the ultraviolet spectral flux, significantly reducing heat-induced efficiency losses in the PV module. Water-based optical filter system reduces the module temperature up to 9.80 °C. The optical filter-based PV system achieved a 4.56 % increase in electrical efficiency compared to the reference module, with an average efficiency of 12.19 %. The heated water, reaching up to 48.25 °C, can be reused for various industrial processes, providing both cooling for PV modules and a hot water source, making it versatile and efficient for regions needing both electricity and hot water.

Highly efficient 2D transition metal Dichalcogenides/SnSe solar cells using Sb2S3 as a back surface field and interfacial layer engineering

Boosting the performance of solar cells is crucial for advancing photovoltaic technology. This study investigates the integration of alternative 2D materials to enhance the performance of solar cells. Three solar cell configurations sample 1 with CdS, sample 2 with MoS2, and sample 3 with SnS2 are systematically investigated via numerical simulation. The simulation framework is validated against experimental data, demonstrating good agreement. Alternative 2D materials are explored to replace toxic CdS and improve the Voc through suitable band alignment with the absorber material, SnSe. Additionally, Sb2S3 is introduced as a back surface field (BSF) for the first time, resulting in increased efficiencies across all three samples. Further performance enhancements involve the insertion of 2D interfacial layers between the electron transport layer (ETL) and absorber to mitigate interface defects. Thirteen materials are evaluated as interfacial layers and nine metals as back contacts, revealing Ni as the optimal back contact for all samples, while MoS2, SnS2, and WS2 are identified as suitable interfacial layers for samples 1, 2, and 3, respectively. Analysis of the solar cells reveals that sample 2, incorporating MoS2 and SnS2, achieves the highest efficiency at 13.58 %. This outperforms sample 3 at 13.55 % and sample 1 at 13.13 %. Sample 2′s superior performance is attributed to the effective utilization of 2D transition metal dichalcogenide (TMDC) materials, which enhance charge carrier transport and minimize recombination losses within the cell structure. Optimized solar cell configurations are modeled using a one-diode approach to build corresponding modules. These modules, created by connecting solar cells in series and parallel, are evaluated through simulated I-V characteristics and power output under standard test conditions. Analysis reveals that Module 2 exhibits superior performance, with higher short-circuit current (ISC) and open-circuit voltage (VOC) compared to Modules 1 and 3. Overall, this study demonstrates the significant role of 2D TMC materials in advancing solar cell performance, providing valuable insights for future solar energy applications.

Effect of The Temperature on The Size of Inhibition Zone of the Clindamycin, Levofloxacin, Tetracycline, and Trimethoprim Activity Against Staphylococcus aureus ATCC 25923

Antibiotic sensitivity should be tested. In the sensitivity test, there are technical factors that influence the formation of the inhibition zone diameter. Based on several research one of the technical factors that affect the diameter of the inhibition in the disc diffusion method is the temperature incubation of the media, this must be examined so that it can be controlled to ensure the validity of the sensitivity test results. This study aims to determine the mean, difference, and analyze the diameter of the inhibition zone of the antibiotics namely Clindamycin, Levofloxacin, Tetracycline, and Trimethoprim against Staphylococcus aureus on Mueller-Hinton agar media with incubation temperatures of 33°C, 34°C, 35°C, 36°C and 37°C for 18 hours. This research is observational, with a cross-sectional design. The data used are primary data with 100 data on the diameter of the antibiotic inhibition zone, obtained by measuring the diameter of the inhibition zone with different incubation temperatures. The selection of antibiotics is based on the mechanism of action of antibiotics inhibiting bacteria namely, the cell wall or membranes that surrounds the bacterial cell; the machineries that make the nucleic acids DNA and RNA and the machinery that produce proteins (the ribosome and associated proteins) with a range of inhibition zones based on Internal Quality Control CLSI. The data will be processed univariately and the Repeated Measure statistical test to determine the significance of the difference in the diameter of the formed inhibition zone using the ANOVA test. The results of the measurement of the inhibition zone diameter on the incubation temperature variation showed a significant difference with p-value 0.000 for Levofloxacin, Tetracycline and Trimethoprim, while for p-value Clindamycin is 0.010. Levofloxacin, Tetracycline, and Trimethoprim antibiotics, the higher the incubation temperature, the average diameter of the inhibition zone is smaller, while for Clindamycin the higher the incubation temperature, the higher the average diameter of the inhibition zone is the same. There is an effect of incubation temperature volume on the diameter of the antibiotic inhibition zone in the disc diffusion method antibiotic sensitivity test. The research indicates that incubation temperature affects the diameter of the antibiotic inhibition zone in disc diffusion tests, underscoring the need for standardized and precise testing conditions to ensure accurate and reliable antibiotic sensitivity results.