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36 result(s) for "sub‐modules"
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Accomplishing High‐Performance Organic Solar Sub‐Modules (≈55 cm2) with >16% Efficiency by Controlling the Aggregation of an Engineered Non‐Fullerene Acceptor
The fabrication of environmentally benign, solvent‐processed, efficient, organic photovoltaic sub‐modules remains challenging due to the rapid aggregation of the current high performance non‐fullerene acceptors (NFAs). In this regard, design of new NFAs capable of achieving optimal aggregation in large‐area organic photovoltaic modules has not been realized. Here, an NFA named BTA‐HD‐Rh is synthesized with longer (hexyl‐decyl) side chains that exhibit good solubility and optimal aggregation. Interestingly, integrating a minute amount of new NFA (BTA‐HD‐Rh) into the PM6:L8‐BO system enables the improved solubility in halogen‐free solvents (o‐xylene:carbon disulfide (O‐XY:CS2)) with controlled aggregation is found. Then solar sub‐modules are fabricated at ambient condition (temperature at 25 ± 3 °C and humidity: 30–45%). Ultimately, the champion 55 cm2 sub‐modules achieve exciting efficiency of >16% in O‐XY:CS2 solvents, which is the highest PCE reported for sub‐modules. Notably, the highest efficiency of BTA‐HD‐Rh doped PM6:L8‐BO is very well correlated with high miscibility with low Flory‐Huggins parameter (0.372), well‐defined nanoscale morphology, and high charge transport. This study demonstrates that a careful choice of side chain engineering for an NFA offers fascinating features that control the overall aggregation of active layer, which results in superior sub‐module performance with environmental‐friendly solvents. A remarkable PCE of >16% is accomplished through enhanced morphology in 55 cm2 sub‐modules fabricated using environmentally benign non‐halogen solvents (O‐XY:CS2) and longer side‐chains (hexyl‐decyl) assisted new NFA (BTA‐HD‐Rh). This notable performance is attributed to an improved nano‐scale morphology, intra‐ and intermolecular interactions, lesser recombinations, and film aggregations. In addition, optimized devices have operational stabilities.
Halogen‐free solvent processed organic solar sub‐modules (≈55 cm2) with 14.70% efficiency by controlling the morphology of alkyl chain engineered polymer donor
Goals of high efficiency, morphological analysis, and the ability to produce organic solar cell (OSC) sub‐modules using halogen‐free solvents are demanding. In this study, a robust conjugated polymer with thienothiophene π‐spacer with pendant alkyl side chain (NapBDT‐C12) was synthesized and used to fabricate sub‐modules. Excellent efficiencies were demonstrated by a NapBDT‐C12 integrated ternary blend, which was used to produce stable small‐area‐to‐sub‐module devices using O‐xylene. The efficiency of the NapBDT‐C12 added small‐area ternary devices (PM6:NapBDT‐C12:L8‐BO) was 18.71%. Owing to the controlled homogeneity of the blend with favorable nanoscale film morphology, enhanced carrier mobilities, and exciton dissociation/splitting properties, contributed to the efficiencies of small‐area‐to‐sub‐module OSCs. Moreover, a 55 cm2 sub‐module with an efficiency of 14.69% was accomplished by bar coating using O‐xylene under ambient conditions. This study displays the potential of a ternary blend based OSC device to produce high efficiency scalable sub‐modules at ambient conditions. A remarkable PCE of 14.69% was achieved by enhancing the morphology of air‐processed sub‐modules (55 cm2) fabricated using halogen‐free solvents (O‐xylene). This performance was achieved by regulating surface morphology, intra‐ and intermolecular interactions, and film optimal aggregation.
Medium-Voltage DC-DC Converter Topologies for Electric Bus Fast Charging Stations: State-of-the-Art Review
With the expansion of E-mobility technology, the demand for Medium-Voltage (MV) Electric Buses (E-buses) charging infrastructure has significantly increased. In this regard, the effective connection of E-bus chargers to a medium voltage power grid is essential to provide fast charging and carry out multiple charging processes simultaneously. One of the main building blocks for E-bus charging is the DC-DC converter stage responsible for regulating the power flow and matching the different voltage and power levels. Accordingly, this paper presents a comprehensive review of DC-DC converter topologies applicable to MV E-bus fast charging. This review discusses and compares the basic isolated DC-DC converter topologies. In addition, the DC-DC converters are classified based on their conversion stages. Moreover, isolated DC-DC converter topologies applicable for MV E-bus fast charging applications, including Dual Active Bridge (DAB) modular-based structure converter and Modular Multilevel Converter (MMC)-based DAB, are discussed where the merits and demerits of each topology are highlighted. Moreover, this review illustrates how DAB converters are employed in different power level applications through the multimodule converter or the MMC-based DAB structure. Furthermore, the challenges and required features for MV DC-DC converter topologies are discussed.
Implementation of Graphic Plugin Loading Platform Based on Python
With the scripting language getting more and more mature, individual developers can also develop script programs according to their own needs based on the existing software library. In order to help individual developers to quickly and simply complete the software graphical problems, a graphical plugin loading platform is developed based on Python language. Through the specified plugin class standard, developers can quickly convert existing scripts or develop scripts according to plugin class, and easily realize the software graphical.
Prediction of new candidate proteins and analysis of sub-modules and protein hubs associated with seed development in rice (Oryza sativa) using an ensemble network-based systems biology approach
Background Rice is a critical global food source, but it faces challenges due to nutritional deficiencies and the pressures of a growing population. Understanding the molecular mechanisms and protein functions in rice seed development is essential to improve yield and grain quality. However, there is still a significant knowledge gap regarding the key proteins and their interactions that govern rice seed development. Protein–protein interaction (PPI) analysis is a powerful tool for studying developmental processes like seed development, though its potential in rice research is yet to be fully realized. With the aim of unraveling the protein interaction landscape associated with rice seed development, this systems biology study conducted a PPI network-based analysis. Using a list of known seed development proteins from the Gene Ontology (GO) knowledgebase and literature, novel candidate proteins for seed development were predicted using an ensemble of network-based algorithms, including Majority Voting, Hishigaki Algorithm, Functional Flow, and Random Walk with Restart, which were selected based on their popularity and usability. The predictions were validated using enrichment analysis and cross-checked with independent transcriptomic analysis results. The rice seed development sub-network was further analyzed for community and hub detection. Results The study predicted 196 new proteins linked to rice seed development and identified 14 sub-modules within the network, each representing different developmental pathways, such as endosperm development and seed growth regulation. Of these, 17 proteins were identified as intra-modular hubs and 6 as inter-modular hubs. Notably, the protein SDH1 emerged as a dual hub, acting as both an intra-modular and inter-modular hub, highlighting its importance in seed development PPI network stability. Conclusions These findings, including the identified hub proteins and sub-modules, provide a better understanding of the PPI interaction landscape governing seed development in rice. This information is useful for achieving a systems biology understanding of seed development. This study implements an ensemble of algorithms for the analysis and showcases how systems biology techniques can be applied in developmental biology.
Experiment on nearest level modulation algorithm for FPGA based Modular Multilevel Converters
Modular Multilevel Converter (MMC) has been applied to medium and high - voltage power systems recently because it has many advantages over other multilevel converters. This paper will present the algorithms of Nearest Level Modulation (NLM) and capacitor voltage balancing to greatly reduce the switching frequency as well as producing an output voltage at the AC side with very low harmonic distortion. The experimental system for the MMC converter requires a large amount of I/O signals ports. However, Digital Signal Processor (DSP) only provides up to 24 I/O signals ports while the experimental system of the MMC converter needs more than that. In this paper, the experimental system used FPGA to embed the proposed methods and applied to an MMC with 12 Sub-Modules (SM) to generate a 13-level AC voltage waveform. In this case, FPGA is the most suitable choice to develop the control circuit for the experimental system of MMC. The effectiveness of the proposed algorithm was verified by simulations and tested using a laboratory – scale prototype.
Protein-protein interaction (PPI) network analysis reveals important hub proteins and sub-network modules for root development in rice (Oryza sativa)
BackgroundThe root system is vital to plant growth and survival. Therefore, genetic improvement of the root system is beneficial for developing stress-tolerant and improved plant varieties. This requires the identification of proteins that significantly contribute to root development. Analyzing protein-protein interaction (PPI) networks is vastly beneficial in studying developmental phenotypes, such as root development, because a phenotype is an outcome of several interacting proteins. PPI networks can be analyzed to identify modules and get a global understanding of important proteins governing the phenotypes. PPI network analysis for root development in rice has not been performed before and has the potential to yield new findings to improve stress tolerance.ResultsHere, the network module for root development was extracted from the global Oryza sativa PPI network retrieved from the STRING database. Novel protein candidates were predicted, and hub proteins and sub-modules were identified from the extracted module. The validation of the predictions yielded 75 novel candidate proteins, 6 sub-modules, 20 intramodular hubs, and 2 intermodular hubs.ConclusionsThese results show how the PPI network module is organized for root development and can be used for future wet-lab studies for producing improved rice varieties.
A DC Short-Circuit Fault Ride Through Strategy of MMC-HVDC Based on the Cascaded Star Converter
A modular multilevel converter based high voltage direct current (MMC-HVDC) with DC fault self-clearing is adopted to deal with the DC short-circuit fault. However, the constant power load characteristic of the sub-modules causes capacitor voltages to diverge and the converter to go out of hot standby. To address this problem, a novel DC short-circuit fault ride through strategy is proposed. According to the polarities of grid voltages, the working or blockage of the upper and lower bridge arms is chosen according to six sections to obtain a cascaded star converter. The capacitor voltages of MMC sub-modules are maintained and balanced through the control similar to the cascaded star converter. Moreover, in order not to change zero crossing, a cluster balancing control method by scaling the amplitudes of the modulated waves is proposed to balance the capacitor voltages between phase clusters. The strategy also achieves the DC Bus line-to-line equipotential and no fault current generated. With the switches of two modes (normal operation and fault ride through operation) after the fault is cleared, the power transfer of MMC-HVDC can be recovered quickly. Finally, the effectiveness of the proposed fault ride through strategy is demonstrated on the 21-level MMC-HVDC simulation model in PSCAD/EMTDC.
Circulating current mitigation for renewable-based modular seven-level converter using deep learning-optimized fractional-order proportional resonant controller
Modular multi-level converters (MMCs) are often used for high and medium voltage applications. However, to reduce losses and costs, many researchers prefer a half-bridge converter. In addition, the half-bridge-based MMC is vulnerable in the event of an error, so the full-bridge MMC is used here to work with faulty network states. The losses and harmonics in the system could be reduced by using an appropriate arm voltage and circulating current control model. In order to operate the MMC in a grid-tied renewable system, both outer and inner loop control were performed. In order to realize outer-loop control, a fractional-order proportional–integral–derivative controller using a deep learning technique is proposed. An active power filter-based fractional-order proportional resonant controller with improved pulse width modulation achieves arm balancing with harmonic mitigated circulating current regulation. The simulation shows that the proposed method reduced the current and voltage harmonics to 71.56% and 10.42% through an improved control strategy based on pulse width modulation.
Block Triangular Decoupling for Linear Systems over Principal Ideal Domains
This paper studies in the framework of the so-called geometric approach the block triangular decoupling problem with state feedback for linear systems defined over a principal ideal domain with identity. First, various properties of feedback reachability submodules are discussed, and then under certain assumptions necessary and sufficient conditions for its solvability are obtained. Further, the pole assignability for decoupled systems is investigated. Finally, a simple example is given to illustrate the results.