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Solar cells have become the centre of academic research in recent times, primarily owing to their ability to generate cost-effective and environmentally friendly sustainable energy on a commercial and industrial level. In this study, we propose the initiation of a research attempt focused on polymer solar cells that employ PBDB-T/ITIC as the active material. To facilitate this investigation, we have employed SCAPS-1D, a robust simulation program widely recognized for its effectiveness in the field. The objective of this study is to enhance the efficiency of a polymer solar cell composed of PBDB-T/ITIC as the absorber, P3HT as the Hole Transport Layer (HTL), and WS2 as the Electron Transport Layer (ETL) through the utilization of SCAPS simulation techniques. By systematically manipulating various parameters within the SCAPS device simulator, we have successfully incorporated the impact of temperature, thickness, defect density, and metal contacts on key performance parameters such as Open Circuit Voltage (Voc), Short Circuit Current density (Jsc), Fill Factor (FF), and Power Conversion Efficiency (PCE). We have developed a novel polymer-based solar cell utilizing the PBDB-T/ITIC material, which exhibits enhanced efficiency, improved temperature stability, and reduced environmental impact. The findings of our study may have the potential to assist the thin-film photovoltaic industry in the development of economically feasible and highly efficient polymer based solar cells.

This paper introduces the EGTL (extract, generate, transfer, load) model, a theoretical framework designed to enhance the traditional ETL processes by integrating a novel ‘generate’ step utilizing generative artificial intelligence (GenAI). This enhancement optimizes data extraction and processing, presenting a high-level solution architecture that includes innovative data storage concepts: the Fusion and Alliance stores. The Fusion store acts as a virtual space for immediate data cleaning and profiling post-extraction, facilitated by GenAI, while the Alliance store serves as a collaborative data warehouse for both business users and AI processes. EGTL was developed to facilitate advanced data handling and integration within digital ecosystems. This study defines the EGTL solution design, setting the groundwork for future practical implementations and exploring the integration of best practices from data engineering, including DataOps principles and data mesh architecture. This research underscores how EGTL can improve the data engineering pipeline, illustrating the interactions between its components. The EGTL model was tested in the prototype web-based Hyperloop Decision-Making Ecosystem with tasks ranging from data extraction to code generation. Experiments demonstrated an overall success rate of 93% across five difficulty levels. Additionally, the study highlights key risks associated with EGTL implementation and offers comprehensive mitigation strategies.

The perovskite solar cells, founded on lead halides, have garnered significant attention from the photovoltaic industry owing to their superior efficiency, ease of production, lightweight characteristics, and affordability. However, due to the hazardous nature of lead-based compounds, these solar cells are currently unsuitable for commercial production. In this context, a lead-free perovskite, cesium-bismuth iodide (Cs3Bi2I9) is considered as a potential alternative to the lead halide-based cell due to their non-toxicity and stability, but this perovskite cannot be matched with random hole transport layer (HTL) and electron transport layer (ETL) materials compared to lead halide-based perovskite because of their crystal structure and band gap. Therefore, in this study, performance comparison of different ideal HTL and ETL materials for Cs3Bi2I9 perovskite layer were studied using SCAPS-1D device simulation on the basis of open circuit voltage, short circuit current, power conversion efficiency (PCE) and fill factor (FF) as well as several novel PSC configuration models were designed that can direct for further experimental research for PSC device commercialization. Results from this investigation reveals that the maximum efficiency of 20.96 % is obtained for the configuration ITO/WS2/Cs3Bi2I9/NiO/Au with optimized parameters such as thickness 400 nm, band gap 2.1eV, absorber layer defect density 1012 cm−3, donor density of ETL 1018 cm−3 and the acceptor density of HTL 1020 cm−3.

In this work, our aim was to design and numerical simulation of a solar cell using the SCAPS-1D simulation program. The studied solar cell has an N-I-P type structure, with its active layer based on a hybrid (organic–inorganic) semiconductor called "methylammonium tin triiodide perovskite", CH3NH3SnI3, which is known as MASnI3. This semiconductor is known for its efficiency in the field of photovoltaic thanks to its good properties such as high absorption, direct bang-gap, and facilities of elaboration. The objective of this study was primarily focused on improving the performance of the perovskite solar cells, specifically enhancing their reproducibility and stability, as they tend to degrade rapidly. To achieve this, we proposed the use of ZnO and Spiro-OMeTAD as charge transport layers (ETL and HTL, respectively) and varying the thickness of the active layer to obtain the optimal parameters that ensure the proper functioning of the cell. [ABSTRACT FROM AUTHOR]

In this study, we introduced the weak electron-accepting oxazole derivative 4,5-diphenyl-2-(4-(4,4,5,5-tetramethyl-1,3,2-dioxaborolan-2-yl)phenyl)oxazole (TPO) into both anthracene and pyrene moieties of a dual core structure. Ultimately, we developed 2-(4-(6-(anthracen-9-yl)pyren-1-yl)phenyl)-4,5-diphenyloxazole (AP-TPO) as the substitution on the second core, pyrene, and 4,5-diphenyl-2-(4-(10-(pyren-1-yl)anthracen-9-yl)phenyl)oxazole (TPO-AP) as the substitution on the first core, anthracene. Both materials exhibited maximum photoluminescence wavelengths at 433 and 443 nm in solution and emitted deep blue light with high photoluminescence quantum yields of 82% and 88%, respectively. When used as the emitting layer in non-doped devices, TPO-AP outperformed AP-TPO, achieving a current efficiency of 5.49 cd/A and an external quantum efficiency of 4.26% in electroluminescence. These materials introduce a new category of deep blue emitters in the organic light-emitting diodes field, combining characteristics related to the electron transport layer. [ABSTRACT FROM AUTHOR]

We synthesized zinc oxide nanoparticles (ZnO NPs) by meticulously controlling both temperature and reaction times, allowing us to fine-tune their crystalline properties, morphology, and particle dimensions. This analysis confirmed the existence of a mixture of rod and sphere shapes (ZnO-I), including rod-shaped NPs with an average size of 14.8 nm × 5.2 nm and spherical NPs with an average diameter of 5.27 nm. We subsequently incorporated these synthesized ZnO NPs into organic light-emitting diode (OLED) devices for red, green, and blue colors, utilizing them as the electron injection layer through a solution-based process. The green OLED device using ZnO-I exhibited a promising current efficiency of 4.02 cd/A and an external quantum efficiency of 1.47%. [ABSTRACT FROM AUTHOR]

The results of gene expression analysis based on p-value can be extracted and sorted by their absolute statistical significance and then applied to multiple similarity scores of their gene ontology (GO) terms to promote the combination and adjustment of these scores as essential predictive tasks for understanding biological/clinical pathways. The latter allows the possibility to assess whether certain aspects of gene function may be associated with other varieties of genes, to evaluate regulation, and to link them into networks that prioritize candidate genes for classification by applying machine learning techniques. We then detect significant genetic interactions based on our algorithm to validate the results. Finally, based on specifically selected tissues according to their normalized gene expression and frequencies of occurrence from their different biological and clinical inputs, a reported classification of genes under the subject category has validated the abstract (glomerular diseases) as a case study. [ABSTRACT FROM AUTHOR]

Business intelligence (BI) refers to technologies, tools, and practices for collecting, integrating, analyzing, and presenting large volumes of information to enable improved decision-making. A modern BI architecture typically consists of a data warehouse made up of one or more data marts that consolidate data from several operational databases. BI further incorporates a combination of analytics, data management, and reporting tools, together with associated methodologies for managing and analyzing data. An important goal of BI initiatives is to improve business decision-making for organizations to increase revenue, improve operational efficiency, and gain a competitive advantage. In this article, we analyze qualitatively various prominent business intelligence (BI) frameworks in the literature and develop a comprehensive BI framework from these. Through the technique of qualitative propositions, we identify the properties, respective advantages, and possible disadvantages of the said BI frameworks to develop a comprehensive framework aimed mainly at data management, incorporating the advantages and eliminating the disadvantages of the individual frameworks. The BI landscape is vast, so as a limitation, we note that the new framework is conceptual; hence, no implementation or any quantitative measurement is performed at this stage. That said, our work exhibits originality since it combines numerous BI frameworks into a comprehensive framework, thereby contributing to conceptual BI framework development. As part of future work, the new framework will be formally specified, followed by a practical phase, namely, conducting case studies in the industry to assist companies in their BI applications. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer Sciences Institute is the property of Lublin University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Recent breakthroughs based on lead (Pb) halide perovskites have inspired extensive study into low-cost photovoltaics to overcome the major challenges that come in this space: stability and toxicity. This work undertook the device configuration of a lead-free perovskite solar cell (PSC) to adopt (CH3NH3SnBr3) methylammonium tin bromide perovskite as an absorber layer. The perovskite solar cell was built with the perovskite CH3NH3SnBr3 as the light absorber layer, Spiro-OMeTAD as the hole transport layer, and a comparative evaluation of various electron transport layers (ETLs) was performed depending on conduction band offsets. CdZnS excelled the other suggested ETLs, with a 24.05% power conversion efficiency. The efficiency of the solar cell was also improved by modifying the doping density in the ETL, the perovskite light absorber layer's thickness, and the HTL layer. The ETL based doping concentrations for the CdZnS (1021 cm−3) and Spiro-OMeTAD (1020 cm−3) were discovered to be the most effective for displaying increased efficiency. 600 nm thick perovskite layer was acceptable for the efficient design. These findings represent the photovoltaic device's best performance; it will be employed to design PSC with high efficiency. [ABSTRACT FROM AUTHOR]

Perovskite solar cells have become a popular alternative to traditional silicon solar cells due to their potential to provide high-efficiency, low-cost, and lightweight solar energy harvesting solutions. However, the multilayer architecture of perovskite solar cells demands careful investigation of the interaction and interfacing between the various layers, as they play a crucial role in determining the overall performance of the cell. In this context, the present work aims at analyzing the coupling between a spongy transparent electron-transporting layer (ETL) and perovskite in a formulation CsPbI3:EuI2. The ETL used in this work is a transparent mesoporous TiO2 layer called “gig-lox” (grazing incidence angle geometry–local oxidation), which has been optimized to boost the interfacing with the perovskite for achieving a highly interconnected blend of materials. The gig-lox TiO2 ETL shows a high surface wettability with respect to the perovskite solution, especially after pre-annealing at 500 °C, and this enables the perovskite material to deeply infiltrate throughout it. The surface wettability of the gig-lox TiO2 has been estimated by contact angle measurements, while the deep infiltration of the perovskite material has been demonstrated through X-ray diffraction and transmission electron microscopy analyses. Thanks to the achieved deep infiltration, the photo-generated charge injection from the perovskite into the mesoporous oxide is enhanced with respect to the use of a planar compact oxide, as shown by the photoluminescence measurements. The mainstay of the approach resides in the ETL that is deposited by a solvent-free sputtering method and is up-scalable for high industrial throughput.

Perovskite solar cells (PSCs) have attracted increasing research interest, but their performance depends on both the choice of materials and the process used. The materials can typically be treated in solution, which makes them well suited for roll-to-roll processing methods, but their deposition under ambient conditions requires overcoming some challenges to improve stability and efficiency. In this review, we highlight the latest advancements in photonic curing (PC) for perovskite materials, as well as for hole transport layer (HTL) and electron transport layer (ETL) materials. We present how PC parameters can be used to control the optical, electrical, morphological, and structural properties of perovskite HTL and ETL layers. Emphasizing the significance of these advancements for perovskite solar cells could further highlight the importance of this research and underline its essential role in creating more efficient and sustainable solar technology.

Solar energy has emerged as an effective renewable source of electricity that reduces carbon emissions and global warming. Conventional solar panels comprise silicon wafers and are vastly used on a commercial basis; however, they do have some drawbacks. Silicon is an indirect band gap material (Eg = 1.12 eV), that lowers its overall absorption and affects the efficiency of the solar cells. Increasing the thickness of existing cells can result in better absorption, but this increases manufacturing cost and complexity. Recently, Perovskite materials have proven to be an effective alternative, as they have better light absorption capability, are readily crystallized as a thin film, and have low cost and higher efficiencies compared to the existing solar technology. Organic/inorganic halide perovskite solar cells are declared the game changer as an alternate energy solution in a concise period claiming efficiencies >20 %. This remarkable progress further highlights the possibility of realizing the potential even deeper. In the Perovskite solar cell structure, Electron Transport Layer (ETL) and Hole transport layer (HTL) is also added to avoid recombination of charge, and maximize absorption. In this paper, we implemented a novel solar cell design on SCAPS-1D, having an optimized parameter composition of FTO/TiO2/CH3NH3SnI3/CuI/Au. The simulation results demonstrated an open circuit voltage (Voc) =1.06 V, Jsc= 32.15 mA/cm2, for FF= 80.43 % and PCE= 27.33 %. We also analyzed the effect of absorber layer thickness and temperature on the performance of the proposed design. The optimized design can not only be useful for the development of a cost-effective and efficient solar cell but also has the potential to advance the field of Perovskite solar cells. Furthermore, we present the mathematical modeling of the proposed solar cell on MATLAB Simulink by mapping the characteristics onto the solar array. Through this modeling, we have developed a solar panel design that can give an output power of 130 W.

The results of gene expression analysis based on p-value can be extracted and sorted by their absolute statistical significance and then applied to multiple similarity scores of their gene ontology (GO) terms to promote the combination and adjustment of these scores as essential predictive tasks for understanding biological/clinical pathways. The latter allows the possibility to assess whether certain aspects of gene function may be associated with other varieties of genes, to evaluate regulation, and to link them into networks that prioritize candidate genes for classification by applying machine learning techniques. We then detect significant genetic interactions based on our algorithm to validate the results. Finally, based on specifically selected tissues according to their normalized gene expression and frequencies of occurrence from their different biological and clinical inputs, a reported classification of genes under the subject category has validated the abstract (glomerular diseases) as a case study.

An all-inorganic lead-free tandem PV cell consisting of two sub-cells CsSn0.5Ge0.5I3 (perovskite) based top cell/CIGS-based bottom cell has been designed, simulated, and optimized by varying the thickness of pertinent layers utilizing the SCAPS-1D simulator. In the top sub-cell, a wide bandgap lead-free inorganic CsSn0.5Ge0.5I3 perovskite is inserted as the primary absorber layer because of its distinctive characteristics with an ETL of ZnO, which is recognized for its high electron mobility & absorption coefficient, and an HTL of NiO to offer increased hole mobility with good chemical-durability. For the bottom sub-cell, we have selected p-type CIGS as the absorber with Spiro-OMeTAD as the apposite HTL to provide suitable offsets of valence and conduction band distribution and TiO2 as ETL to offer low-cost, low-ecotoxicity, excellent optical properties, and chemical-stability and thus offers improved efficiency of the overall tandem structure. In the beginning, the two sub-cells were simulated independently; the top sub-cell was simulated under the standard spectrum of AM1.5G, while the bottom sub-cell was optimized using a filtered spectrum. Thereafter, the current matching point of both cells was attained by optimizing the absorber layer thicknesses. Finally, our computational modeling and simulation results offer the optimized cell structure revealing an outstanding overall 38.39% power conversion efficiency (PCE), Fill Factor (FF) of 83.4%, open-circuit voltage (VOC) of 2.48 V, and short-circuit current density (Jsc) of 18.64 mA cm−2. The proposed tandem structure's performance matrices outperform those stated in the most recent literature. These outcomes of the proposed structure are expected to facilitate the development and production of a low-cost and highly effective inorganic perovskite Tandem PV cell in the future.

Perovskite solar cells have become a popular alternative to traditional silicon solar cells due to their potential to provide high-efficiency, low-cost, and lightweight solar energy harvesting solutions. However, the multilayer architecture of perovskite solar cells demands careful investigation of the interaction and interfacing between the various layers, as they play a crucial role in determining the overall performance of the cell. In this context, the present work aims at analyzing the coupling between a spongy transparent electron-transporting layer (ETL) and perovskite in a formulation CsPbI 3 :EuI 2 . The ETL used in this work is a transparent mesoporous TiO 2 layer called "gig-lox" (grazing incidence angle geometry–local oxidation), which has been optimized to boost the interfacing with the perovskite for achieving a highly interconnected blend of materials. The gig-lox TiO 2 ETL shows a high surface wettability with respect to the perovskite solution, especially after pre-annealing at 500 ° C, and this enables the perovskite material to deeply infiltrate throughout it. The surface wettability of the gig-lox TiO 2 has been estimated by contact angle measurements, while the deep infiltration of the perovskite material has been demonstrated through X-ray diffraction and transmission electron microscopy analyses. Thanks to the achieved deep infiltration, the photo-generated charge injection from the perovskite into the mesoporous oxide is enhanced with respect to the use of a planar compact oxide, as shown by the photoluminescence measurements. The mainstay of the approach resides in the ETL that is deposited by a solvent-free sputtering method and is up-scalable for high industrial throughput. [ABSTRACT FROM AUTHOR]

The most important obstacles in industrialization of the perovskite solar cell are presence of lead toxicity and stability. In this article, a theoretical analysis of eco-friendly and stable CsSn0.5Ge0.5I3 based PSC has been presented. Different factors influencing the cell performance such as operating temperature, defect concentration, back contact of work function, parasitic resistance and thickness of perovskite layer have been investigated. In the present work, cesium tin germanium triiodide has been used as a cost-effective light absorber layer in place of counterpart of lead. After optimizing thickness of CsSn0.5Ge0.5I3 at 700 nm, the parameters such as fill factor, short current density, efficiency, and open-circuit voltage are 64.98%, 26.872 mA/cm2, 16.12% and 0.923 V, respectively. The proposed result will open a remarkable way for research community to develop lead-free perovskite solar cells. [ABSTRACT FROM AUTHOR]

Information Technology (IT) and its advancements change the education environment. Conventional classroom education has been transformed into a modernized form. Education field decision-makers are always searching for new technologies that provide fast solutions to support Education Decision Support Systems (EDSS). There is a significant need for an effective decision support system to utilize student data which helps the university in making the right decisions. The Electronic learning system (e-learning) provides a live forum for faculties and students to connect with learning portals and virtually execute educational activities. Even though these modern approaches support the education system, active student participation still needs to be improved. Moreover, accurately measuring student performance using collected attributes remains difficult for parents and teachers. Therefore, this paper seeks to understand and predict student performance using effective data processing and a deep learning-based decision model. The implementation of EDSS starts with data preprocessing, Extraction-Transformation-Load (ETL), a data mart area to store the extracted data with Online Analytical Processing (OLAP) processing, and decision-making using Deep Graph Convolutional Neural Network (DGCNN). The statistical evaluation is based on the student dataset from the Kaggle repository. The analyzed results depict that the proposed EDSS model on an independent data mart with efficient decision support and OLAP provides a better platform to make academic decisions and help educators to make necessary decisions notified to the students. [ABSTRACT FROM AUTHOR]

Formamidinium (NH2CHNH2+) lead-based perovskite materials are becoming one of the suitable materials for planar heterojunction solar cell due to its wide bandgap tunability feature. In this work, simulation of formamidinium lead-based perovskite solar cell device is performed using SCAPS-1D software where bandgap of the absorber layer has been varied along with the other parameters like electron affinity, conduction & valence band effective density of states and thickness. With those variations, photovoltaic performance parameters e.g., open circuit voltage ( V OC ), current density ( J SC ), efficiency (η ), fill factor ( FF ), and Quantum efficiency ( QE ) have been investigated. The effect of thickness variation of absorber layer, SnO2 and ZnO as a different ETL material and effect of gold (Au)/2-D MXenes Ti 3 C 2 T x as a rear electrode have been explored and depicted its effects on overall photovoltaic performance parameters. Further, the effects of series/shunt resistance ( R Series and R Shunt ) have also been simulated using SCAPS-1D software. [ABSTRACT FROM AUTHOR]

Motivated form the performance and utilization of organic light emitting diodes (OLEDs) in advanced flexible optoelectronic devices, this research article reports the structure optimization of ITO/NPD/Alq3/TPBi/Bphen/LiF/Al based OLED. For the designed OLED, the computational investigation of its electrical properties (charge densities, I–V and J–V characteristics), recombination rates along the growth direction and optical parameters with the help of Shockley–Read–Hall recombination model, Poisson equations, drift and diffusion equations and carrier continuity equation have been studied. As per the data taken from the I–V and J–V characteristics, the operating (threshold) voltage of designed OLED was found as ~ 3.5 V. From the calculation, it was confirmed that the e–h recombination rate is highest (~ 4.5 × 1028/m3) in emissive (EML) region (~ 260 nm–275 nm). In optical parameters, the study has been made on input emission spectrum of the emissive (EML) layer (Alq3) which demonstrates the maximum intensity corresponding to wavelength of ~ 475 nm (visible region). Further, the external quantum efficiency with variable applied voltage has also been studied with the information on the mechanism of efficiency drop on a particular voltage. The behaviours of the recombination prefactors β1 and β2 for the designed OLED have also been studied with the variable applied range of voltages. The outcomes of the study suggest the usage of optimized OLED structure in the advanced and flexible optoelectronics in the visible region. [ABSTRACT FROM AUTHOR]

Copyright of Techno.com is the property of Universitas Dian Nuswantoro, Fakultas Ilmu Komputer and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Business Intelligence plays a vital role in helping organizations to extract meaningful insights from their data and make informed decisions. However, choosing the right data modeling approach can be challenging, as different methodologies have unique advantages and limitations. The focus of the current paper is to provide an insight into the Data Vault architecture, which is an emerging approach to data modeling, compared to the established methods of Kimball and Inmon. The paper conducted a comparative analysis of these methodologies, with a particular emphasis on the benefits of Data Vault. This study highlights the advantages of the Data Vault model in managing data from multiple sources and its compatibility with agile implementation practices. Overall, this paper sheds light on the relevance of Data Vault in contemporary data management practices.

Heterogeneity is the key aspect of complex networks and smart devices for using it as nature of live streams. The heterogeneous stream-disk join is a significant research topic in real-time processing applications because it can directly affect the data analytics. Multiple issues, including stream loss, scalability, disk access cost, and data accuracy, should be considered during heterogeneous stream-disk join transformation. In this work we overcome these issues by introducing a distributed heterogeneous stream-disk join architecture (DHSDJArch) which can prevent stream data loss as well as maintaining balance between heterogeneous distributed data sources and accuracy of stream-disk join. A four phased distributed architecture is proposed for the multi-objective optimization to transform heterogeneous incomplete stream. To prevent stream loss, configuration of log retention is proposed based on the characteristics of distributed event streaming platform (DESP). Specifically, two transformations are proposed to pre-process heterogeneous streams and to join pre-processed stream with distributed disk data by performing real-time disk access while compensating the differences between data sources and streaming application, respectively. We conduct comprehensive experimental study on real datasets to verify the performance of proposed architecture in terms of accuracy, log retention policy, scaling, stability and cloud data storage.