Module Configuration Research Articles

Effect of module configurations on the performance of parallel-connected lithium-ion battery modules

To meet the power and energy of battery storage systems, lithium-ion batteries have to be connected in parallel to form various battery modules. However, different single module collector configurations (SCCs) and unavoidable interconnect resistances lead to inhomogeneous currents and state-of-charge (SoC) within the module, thereby significantly reducing the module lifetime and safety. Therefore, the correlation of SCCs to module inhomogeneous currents and SoC are worth investigating. Based on mathematical permutations and combinations calculations, all SCCs are firstly defined and obtained in this paper. Then, two parallel modules are developed in Matlab/Simscape based on fresh cell and degradation cell separately, which are used to quantify the influence of all SCCs. Furthermore, multiple module collector configurations (MCCs) and Urban Dynamometer Driving Schedule (UDDS) working condition are considered in the analysis. Results indicate that both module collectors connected to same edge cell of module cause the most inhomogeneity. The maximum SoC difference under the UDDS is only 46 % of the 0.5C. Moreover, MCCs can reduce inhomogeneous currents and SoC within the parallel module, while not all MCCs perform better homogeneous performance than SCCs. Finally, the effect of changes in SCCs on degradation module inhomogeneous currents and SoC is verified as same as for fresh cells parallel module. Based on the above results, the optimal single module collector configuration of the N cells parallel module is obtained through mathematical analysis, which can greatly improve the currents and SoC homogeneity of the module.

Cobalt Ditelluride Meets Tellurium Vacancy: An Efficient Catalyst as a Multifunctional Polysulfide Mediator toward Robust Lithium-Sulfur Batteries.

The commercialization of lithium-sulfur batteries (LSBs) faces significant challenges due to persistent issues, such as the shuttle effect of lithium polysulfides (LiPSs) and the slow kinetics of cathodic reactions. To address these limitations, this study proposes a vacancy-engineered cobalt ditelluride catalyst (v-CoTe2) supported on nitrogen-doped carbon as a sulfur host at the cathode. Density functional theory calculations and experimental results indicate that the electron configuration modulation of v-CoTe2 enhances the chemical affinity and catalytic activity toward LiPS. Specifically, v-CoTe2 can strongly interact with PSs through multisite coordination, effectively facilitating the kinetics of the LiPS redox reaction. Furthermore, the introduction of Te vacancies generates a large number of spin-polarized electrons, further enhancing the reaction kinetics of LiPS. As a result, the v-CoTe2@S cathode demonstrates high initial capacity and excellent cyclic stability, maintaining 80.4% capacity after 500 cycles at a high current rate of 3 C. Even under a high sulfur load of 6.7 mg cm-2, a high areal capacity of 6.1 mA h cm-2 is retained after 50 cycles. These findings highlight the significant potential of Te vacancies in CoTe2 as a sulfur host material for LSBs.

Enhancing the Performance of Photovoltaic Solar Cells using a Hybrid Cooling Technique of Thermoelectric Generator and Heat Sink

Abstract This study aims to enhance the performance of photovoltaic (PV) solar cells by employing a hybrid cooling technique involving a thermoelectric generator (TEG) and heat sink. Three configuration modules are investigated both experimentally and numerically: module 01: PV only (PV), module 02: PV with TEG (PV-TEG), and module 03: PV with TEG and heat sink (PV-TEG-HS). These modules have been examined numerically under various weather conditions, including solar radiation, wind speed, and ambient temperature. The experimental and numerical results indicate that as solar radiation increases from 500 to 1000 W/m2, the temperature of the PV back sheet and PV solar cell also increases. Specifically, for module PV, module PV-TEG, and module PV-TEG-HS, the temperature increases by 57.3%, 56.1%, and 32% respectively. Additionally, the percentage output power (Pout) of the PV increases with rising solar radiation for the three modules, reaching 60.5%, 62.0%, and 87.39% respectively. Moreover, the percentage Pout of the TEG also increases with the increasing solar radiation for the three modules, with percentages of 0%, 299.25%, and 311.96% respectively. Furthermore, increasing wind speed leads to a decrease in the temperatures of the back sheet and solar cell, while simultaneously increasing the Pout of the PV for all three modules. However, the Pout of the TEG in module PV-TEG-HS decreases. The impact of increasing ambient temperatures on module PV-TEG-HS is relatively small compared to the other modules.

Ring-assisted, racetrack, and Mach-Zehnder modulator: which one offers the lowest voltages and chirp-free operation?

This study presents a comparison between resonant and non-resonant electro-optical modulator configurations. The focus lies on finding the configuration with the highest modulation amplitude at the lowest drive voltage while achieving a large electro-optical bandwidth. It is found that the ring-assisted Mach-Zehnder modulator (RaMZM) offers chirp-free and resonantly enhanced modulation without bandwidth limitations imposed by the ring. In contrast, a racetrack modulator (RTM) offers resonant enhancement at the cost of a chirped modulated signal and with a bandwidth limitation. The traditional non-resonant Mach-Zehnder modulator (MZM) configuration requires higher modulation voltages while offering chirp-free operation with a flat frequency response. The RaMZM, therefore, looks like an ideal candidate for encoding information in backbone networks where small modulation voltages and perfect control over the phase of a signal are needed. The results are supported by experiments that show driverless plasmonic modulation at 220 GBaud 2PAM, 160 GBaud 4PAM and 100 GBaud 8PAM with record low peak voltages of 0.5 V.

Fabrication and performance evaluation of large–scale luminescent and plasmonic luminescent solar concentrator modules

This study presents the detailed fabrication and performance evaluation of large–scale luminescent solar concentrator (LSC) and plasmonic luminescent solar concentrator (PLSC) modules. Individual LSC, PLSC, and reference devices have been fabricated with dimensions of 10 x 10 x 0.5 cm. Five devices of each type were connected in series, ensuring correct photovoltaic cell polarity, to form cohesive modular groups with minimal mismatch. These solar concentrators were subsequently integrated into an outdoor panel designed to accommodate the modules for outdoor performance evaluations. Outputs of 240 mW, 213 mW, and 46 mW were observed for the individual PLSC, LSC and reference devices respectively from an indoor solar simulator test outputting 900 W/m2. Outdoor performance analysis has highlighted that the inclusion of metal nanoparticles within the PLSCs enhanced the outputs by 65% on average with a maximum enhancement of 88.6% observed over the course of a single day. The series connection within the LSC modules demonstrated enhanced scalability and potential for practical application in solar energy systems. This innovative module configuration provides valuable insights into the advancement of luminescent solar concentrators through plasmonic enhancement, contributing to the broader goal of optimising solar energy harvesting.

Membrane fouling in integrated forward osmosis and membrane distillation systems – A review

With the increase in water consumption, especially by the industrial and agricultural sectors, more strategies capable of increasing the recovery and reuse of water resources have been sought. An example of technology that assists in this challenge is membrane separation processes. However, systems that use this type of separation may be limited by the phenomenon of fouling. Integrated systems such as forward osmosis (FO) with membrane distillation (MD) have several advantages, such as obtaining a high-quality permeate from raw wastewater, the constant regeneration of the draw solution, which assists in continuous operation, and the possibility of association with biological tanks that enable nutrients recovery. However, these systems face limitations related to low flux values caused by membrane fouling. Therefore, the present review seeks to study fouling in integrated FO-MD systems to understand the main challenges of applying this technology and achieving higher permeate flux values. From the most recent studies, many strategies are being evaluated, such as different membrane materials, deposition of antifouling materials on membrane surface, feed temperature, draw solution substances, concentration and temperature, use of spacers and new modules configurations. That way, the low flux from those systems may be bypassed, enabling FO-MD systems scale up.

Energy management of residential buildings using innovative passive techniques

Abstract Recently, efforts on sustainability and energy savings in buildings have increased due to the growing global awareness of the energy use of buildings and the negative impacts of carbon dioxide emissions on climate change. As a result, it is critical to propose effective strategies to reduce such energy consumption. The goal of this project is to advance the idea of net-zero energy buildings as a worldwide mitigation method for climate change. Thus, a numerical model was developed and validated to investigate the passive cooling capabilities of an innovative phase change material (PCM)-based phase cube in residential buildings. The proposed phase cube includes six various PCM-compact storage module (PCM-CSM) configurations including Rubitherm’s SP-24E plates (Horizontal), Half Circular Inline, Half Circular Staggered, Vertical plates, Inline Cylindrical and Staggered Cylindrical compact storage modules. All the proposed designs were numerically simulated, and the obtained results were compared and analysed at an inlet air temperature and velocity of 35°C, and 4m/s, respectively and each phase cube contained the same mass of Rubitherm’s SP-24E PCM, which was 30.326 kg. The results showed that the Horizontal, Half Circular Inline and Vertical phase cubes can absorb heat at a higher rate from fresh air at nearly 496.19w, 465.9w and 458.16w, respectively translating the lowest outlet air temperature of about 25°C from the cube. Integrating such phase cubes into residential buildings for indoor passive air cooling substantially decreased the building cooling loads, resulting in reduced electric energy consumption by the air conditioning system.

Preliminary study of the thermoelectric cooler and heat pipe application for the cooling system in cabin pickup car

Abstract Car cooling systems are essential equipment to make passengers comfortable, but their energy consumption is very high. Thermoelectric technology has been widely applied as a cooler in many applications, but its use as a car cooler has not been widely used. This research aims to conduct a preliminary study using thermoelectric coolers (TEC) as alternative coolers in pickup cars and to investigate the effect of thermoelectric module and heat exchanger configurations on cooling systems performance. A-TEC cooling system usually uses conventional heat sinks on the cold side and hot side of the TEC. In this study, heat pipes are used as heat exchangers on the hot side of TEC to improve its performance. The cooling system consists of 2 units installed at the rear of the pickup car cabin. Tests were varied using 2 TEC modules arranged in series and 4 TECs arranged in parallel thermal and electrical series. The results showed that using two cooling system units consisting of four TEC modules equipped with heat pipes was able to cool the temperature of the pickup car cabin at 27.4 °C and obtained the highest COP value of 1.16. It shows heat pipes can enhance TEC cooling system performance, producing lower cabin temperatures than conventional heat sinks.

Evaluation of the Mechanical Properties of PLA Material Used For 3D Printing Solar E-Hub Component

The advent of additive manufacturing (AM) technologies revolutionized design and production processes across various industries. In renewable energy, AM enabled new possibilities for optimizing solar e-hub (solar energy harvesting module) configurations, enhancing efficiency and performance. This study examined critical considerations such as material selection, durability, and cost-effectiveness in solar hub development. This fast-prototyping technique was controlled by computer-aided design (CAD) software like CREO Parametric 7.0 and Creality Slicer 4.8. Experimental results indicated that PLA (Polylactic acid) materials exhibited superior strength, with an impact energy of 4.8 Joules. The deformation study revealed that the maximum load of 22 MPa aligned with the ultimate tensile strength of PLA, and a hardness test result of 83.1 HRF featured its exemplary hardness properties. These findings advanced the understanding of using AM to investigate mechanical behaviours of PLA materials and optimize solar e-hub configurations for portable device applications, promoting sustainable energy solutions and the adoption of renewable energy technologies. In addition, the successful implementation of this approach will enable the renewable energy sectors to minimize the carbon foot-prints towards helping the global net-zero emissions by aligning the circular economy approach.

Investigating the impact of battery arrangements on thermal management performance of lithium-ion battery pack design

The working temperature is one of the key factors affecting the efficiency and safety performance of automotive power batteries. Current battery pack design primarily focuses on single layout configurations, overlooking the potential impact of mixed arrangements on thermal management performance. This study presents a module-based optimization methodology for comprehensive concept design of Lithium-ion (Li-ion) battery pack. Firstly, the arrangement modules is optimized and performed using particle swarm optimization algorithms considering various arrangement layout (i.e. rectangular, diamond, and staggered arrangements) by taking the intercell spacing and maximum temperature of the modules as design objectives. Secondly, the battery pack configuration design is performed employing a neural network model reflect diverse battery module configurations within the pack, exploring their impact on thermal management performance. The hybrid battery arrangement effectively improves thermal management, and the module spacing helps to enhance heat dissipation. The staggered arrangement has a greater impact on the heat dissipation performance of the battery pack, but the spacing between different modules varies with the position of the modules. When all configuration schemes are staggered modules, the optimal range of the spacing between modules is between 6 and 7 mm. However, the study observes a non-linear relationship between module spacing and the maximum temperature difference within the battery pack. While increasing module spacing initially decreases temperature differences, it eventually reverses, suggesting that spacing alone may not consistently enhance thermal management. Validation with a lithium-ion battery pack case study demonstrates the method’s effectiveness, providing valuable knowledge for future cell and pack designs that employ different battery cell arrangements and diverse cooling strategies.

Jet-assisted membrane filtration and design application: A model for fouling removal area estimation

Membrane fouling remains a significant challenge in desalination and other membrane-based filtration processes. This study presents a novel force-balance model to accurately estimate the de-fouling area in jet-assisted filtration for in-situ fouling control. The model includes various design parameters, such as initial jet velocity, nozzle diameter, impinging angle, membrane pore size, membrane resistance, and permeate flux. The validation showed a strong correlation between theoretical predictions and experimental observations, with an R2 value of 0.97, indicating high predictive accuracy. Additionally, an empirical formula and design automation tools were developed to facilitate the configuration of jet filtration modules, enabling practical application of the findings. As a demonstration, the arrangement of multiple jets in a hollow fiber membrane module was optimized using the model, significantly improving microalgae filtration performance. The optimized jet configuration enhanced permeate flux by 236 % and reduced the specific energy consumption by 67 % compared to conventional setups. This research offers a framework for extending the application of jet-based fouling mitigation and cleaning in various membrane filtration systems, providing substantial improvements in efficiency and operational sustainability.

Investigation of static and dynamic mechanical loads on light-weight PV modules for offshore floating applications

Photovoltaic (PV) systems are significant for the transition towards renewable energy. However, their expansion is constrained by the scarcity of suitable land in proximity to electric grids. To address this issue, floating PV is a promising solution. Ensuring the robustness of floating PV installations remains a major concern, particularly regarding the mechanical load due to strong winds in open water. This study aims to assess the impact of wind on floating PV modules, by considering real wind speed values occurring at the North Sea. To achieve this objective, the influence of PV module configuration, such as inclination, is examined. Moreover, different thicknesses of PV glass are considered to find an optimum between mechanical stability and material consumption. Lastly, a resonance vibration test is performed and compared to simulations to estimate the effects of vibration on PV module stress. The findings indicate that a low inclination installation is preferable, and a glass-glass PV module with a 2.5 mm glass thickness can withstand static and dynamic mechanical loads, although long-term durability requires further investigation. Additionally, it is crucial for the standard Dynamic Mechanical Load (DML) test to include higher pressure values and an extended vibration test at the resonance frequency with the highest measured acceleration, identified after a frequency sweep.

How does module tracking for agrivoltaics differ from standard photovoltaics? Food, energy, and technoeconomic implications

Module tracking can be an effective approach for spatial-temporal sharing of sunlight between solar modules and crops in agrivoltaics (AV). For desired food-energy yield across various seasons and crops, tracking needs to be customized based on factors including crop type, module array density, economics and social preferences, and policy. Here, we explore customized tracking (CT) along single axis for AV to meet the desired food-energy yield and economic performance for a variety of module configurations and crop types. CT is implemented through a time multiplexing of standard tracking and anti-tracking along the day to balance sunlight between modules and crops, respectively. Module energy and spatial-temporal shading are modeled using the view factor approach while the crop response to shading is modeled empirically. Economic factors including module hardware/soft costs and crop profit are explored to model the economic performance using price-performance ratio. A case study done at Punjab, Pakistan shows that 5 hours of daily standard tracking around noon can ensure 80 % of the typical energy yield targets while maintaining 40 % and 80 % relative biomass yield for crops having high and moderate shade sensitivity, respectively. When module row spacing is increased 2–3 times relative to a typical ground mounted photovoltaic (GMPV) system, biomass yield for crops having high shade sensitivity can be substantially recovered while also improving economic performance. Due to a higher capital cost, 30–40 % increase in feed-in-tariff could be required to make the tracking AV economically competitive to a typical GMPV. The proposed approach can be highly effective for customized module tracking design and economic analysis for AV.

Induced Anion Redox before Full Oxidation of Ru4+/Ru5+ through Local Configuration Modulation in P2-Na0.67[Mg0.33Ru0.67]O2

The study of anionic redox in layered-oxide cathodes for Na-ion batteries (NIBs) has been extensive, aiming to attain high-energy density. The involvement of Mn4+ or Ru5+ oxidation states is known to be crucial for the anionic O2 −/O− reaction during Na+ de/intercalation. Nevertheless, our findings indicate that anionic redox can activate in Ru-based layered-oxide cathodes prior to complete Ru4+/Ru5+ oxidation. By employing first-principles calculation and experimental techniques, we disclose that additional Na+ deintercalation from P2-Na0.33[Mg0.33Ru0.67]O2 relies on anionic oxidation after extracting 0.33 mol Na+ from P2-Na0.67[Mg0.33Ru0.67]O2, concomitant with cationic oxidation of Ru4+/Ru4.5+. Specifically, only the oxygen adjacent to 2Mg/1Ru is implicated in anionic redox during Na+ de/intercalation, indicating that the Na–O–Mg arrangement in the P2-Na0.33[Mg0.33Ru0.67]O2 structure significantly reduces the thermodynamic stability of anionic redox compared to cationic redox. Through O anionic and Ru cationic reactions, P2-Na0.67[Mg0.33Ru0.67]O2 demonstrates a substantial specific capacity of ∼172 mA h g− 1 and exceptional power capability, facilitated by facile Na+ diffusion and reversible structural changes during charge/discharge. These findings propose an innovative strategy to enhance anionic redox activity by modifying the local oxygen environment, paving the way for high-energy-density cathode materials in NIBs.

Using Machine Learning Methods to Assess Module Performance Contribution in Modular Optimization Frameworks.

Modular algorithm frameworks not only allow for combinations never tested in manually selected algorithm portfolios, but they also provide a structured approach to assess which algorithmic ideas are crucial for the observed performance of algorithms. In this study, we propose a methodology for analyzing the impact of the different modules on the overall performance. We consider modular frameworks for two widely used families of derivative-free black-box optimization algorithms, the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) and differential evolution (DE). More specifically, we use performance data of 324 modCMA-ES and 576 modDE algorithm variants (with each variant corresponding to a specific configuration of modules) obtained on the 24 BBOB problems for 6 different runtime budgets in 2 dimensions. Our analysis of these data reveals that the impact of individual modules on overall algorithm performance varies significantly. Notably, among the examined modules, the elitism module in CMA-ES and the linear population size reduction module in DE exhibit the most significant impact on performance. Furthermore, our exploratory data analysis of problem landscape data suggests that the most relevant landscape features remain consistent regardless of the configuration of individual modules, but the influence that these features have on regression accuracy varies. In addition, we apply classifiers that exploit feature importance with respect to the trained models for performance prediction and performance data, to predict the modular configurations of CMA-ES and DE algorithm variants. The results show that the predicted configurations do not exhibit a statistically significant difference in performance compared to the true configurations, with the percentage varying depending on the setup (from 49.1% to 95.5% for mod-CMA and 21.7% to 77.1% for DE).

A real-time and energy-efficient SRAM with mixed-signal in-memory computing near CMOS sensors

In-memory computing (IMC) represents a promising approach to reducing latency and enhancing the energy efficiency of operations required for calculating convolution products of images. This study proposes a fully differential current-mode architecture for computing image convolutions across all four quadrants, intended for deep learning applications within CMOS imagers utilizing IMC near the CMOS sensor. This architecture processes analog signals provided by a CMOS sensor without the need for analog-to-digital conversion. Furthermore, it eliminates the necessity for data transfer between memory and analog operators as convolutions are computed within modified SRAM memory. The paper suggests modifying the structure of a CMOS SRAM cell by incorporating transistors capable of performing multiplications between binary (−1 or +1) weights and analog signals. Modified SRAM cells can be interconnected to sum the multiplication results obtained from individual cells. This approach facilitates connecting current inputs to different SRAM cells, offering highly scalable and parallelized calculations. For this study, a configurable module comprising nine modified SRAM cells with peripheral circuitry has been designed to calculate the convolution product on each pixel of an image using a 3×3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$3 \ imes 3$$\\end{document} mask with binary values (−1 or 1). Subsequently, an IMC module has been designed to perform 16 convolution operations in parallel, with input currents shared among the 16 modules. This configuration enables the computation of 16 convolutions simultaneously, processing a column per cycle. A digital control circuit manages both the readout or memorization of digital weights, as well as the multiply and add operations in real-time. The architecture underwent testing by performing convolutions between binary masks of 3 × 3 values and images of 32 × 32 pixels to assess accuracy and scalability when two IMC modules are vertically integrated. Convolution weights are stored locally as 1-bit digital values. The circuit was synthesized in 180 nm CMOS technology, and simulation results indicate its capability to perform a complete convolution in 3.2 ms, achieving an efficiency of 11,522 1-b TOPS/W (1-b tera-operations per second per watt) with a similarity to ideal processing of 96%.

Development and first implementation of a novel multi-modality cardiac motion and dosimetry phantom for radiotherapy applications.

Cardiac applications in radiation therapy are rapidly expanding including magnetic resonance guided radiation therapy (MRgRT) for real-time gating for targeting and avoidance near the heart or treating ventricular tachycardia (VT). This work describes the development and implementation of a novel multi-modality and magnetic resonance (MR)-compatible cardiac phantom. The patient-informed 3D model was derived from manual contouring of a contrast-enhanced Coronary Computed Tomography Angiography scan, exported as a Stereolithography model, then post-processed to simulate female heart with an average volume. The model was 3D-printed using Elastic50A to provide MR contrast to water background. Two rigid acrylic modules containing cardiac structures were designed and assembled, retrofitting to an MR-safe programmable motor to supply cardiac and respiratory motion in superior-inferior directions. One module contained a cavity for an ion chamber (IC), and the other was equipped with multiple interchangeable cavities for plastic scintillation detectors (PSDs). Images were acquired on a 0.35 T MR-linac for validation of phantom geometry, motion, and simulated online treatment planning and delivery. Three motion profiles were prescribed: patient-derived cardiac (sine waveform, 4.3mm peak-to-peak, 60 beats/min), respiratory (cos4 waveform, 30mm peak-to-peak, 12 breaths/min), and a superposition of cardiac (sine waveform, 4mm peak-to-peak, 70 beats/min) and respiratory (cos4 waveform, 24mm peak-to-peak, 12 breaths/min). The amplitude of the motion profiles was evaluated from sagittal cine images at eight frames/s with a resolution of 2.4mm × 2.4mm. Gated dosimetry experiments were performed using the two module configurations for calculating dose relative to stationary. A CT-based VT treatment plan was delivered twice under cone-beam CT guidance and cumulative stationary doses to multi-point PSDs were evaluated. No artifacts were observed on any images acquired during phantom operation. Phantom excursions measured 49.3±25.8%/66.9±14.0%, 97.0±2.2%/96.4±1.7%, and 90.4±4.8%/89.3±3.5% of prescription for cardiac, respiratory, and cardio-respiratory motion profiles for the 2-chamber (PSD) and 12-substructure (IC) phantom modules respectively. In the gated experiments, the cumulative dose was<2% from expected using the IC module. Real-time dose measured for the PSDs at 10Hz acquisition rate demonstrated the ability to detect the dosimetric consequences of cardiac, respiratory, and cardio-respiratory motion when sampling of different locations during a single delivery, and the stability of our phantom dosimetric results over repeated cycles for the high dose and high gradient regions. For the VT delivery, high dose PSD was<1% from expected (5-6 cGy deviation of 5.9Gy/fraction) and high gradient/low dose regions had deviations<3.6% (6.3 cGy less than expected 1.73Gy/fraction). A novel multi-modality modular heart phantom was designed, constructed, and used for gated radiotherapy experiments on a 0.35 T MR-linac. Our phantom was capable of mimicking cardiac, cardio-respiratory, and respiratory motion while performing dosimetric evaluations of gated procedures using IC and PSD configurations. Time-resolved PSDs with small sensitive volumes appear promising for low-amplitude/high-frequency motion and multi-point data acquisition for advanced dosimetric capabilities. Illustrating VT planning and delivery further expands our phantom to address the unmet needs of cardiac applications in radiotherapy.

Origins of High Air Sensitivity and Treatment Strategies in O3-Type NaMn1/3 Fe1/3Ni1/3O2.

Sodium-ion layered oxides are one of the most highly regarded sodium-ion cathode materials and are expected to be used in electric vehicles and large-scale grid-level energy storage systems. However, highly air-sensitive issues limit sodium-ion layered oxide cathode materials to maximize cost advantages. Industrial and scientific researchers have been developing cost-effective air sensitivity treatment strategies with little success because the impurity formation mechanism is still unclear. Using density functional theory calculations and ab initio molecular dynamics simulations, this work shows that the poor air stability of O3-type NaMn1/3Fe1/3Ni1/3O2 (NMFNO) may be as follows: (1) low percentage of nonreactive (003) surface; (2) strong surface adsorption capacity and high surface reactivity; and (3) instability of the surface sodium ions. Our physical images point out that the high reactivity of the NMFNO surface originates from the increase in electron loss and unpaired electrons (magnetic moments) of the surface oxygen active site as well as the enhanced metal coactivation effect due to the large radius of the sodium ion. We also found that the hydrolysis reaction requires a higher reactivity of the surface oxygen active site, while the carbon hybridization mode transformation in carbonate formation depends mainly on metal activation and does not even require the involvement of surface oxygen active sites. Based on the calculation results and our proposed physical images, we discuss the feasibility of these treatment strategies (including surface morphology modulation, cation/anion substitution, and surface configuration design) for air-sensitive issues.

Digital Twin System of Substation Equipment

This paper adopts the following technical solutions to achieve: a digital twin system for substation, including: database, database configuration module, data warehousing module, background data processing module and front-end browsing module; The front-end browsing module is used to display the data sent by the background data processing module in the corresponding form according to the user's selection; The form includes building the three-dimensional model of the substation based on BIM technology, and displaying the corresponding real-time data and status in the three-dimensional components of the three-dimensional model. Compared with the existing technology, it organically integrates the three-dimensional model and panoramic monitoring data of the substation, realizes the three-dimensional panoramic display of substation assets and the acquisition of substation monitoring data, improves the spatial experience of daily operation and maintenance comprehensive monitoring, and provides a solid data platform for the subsequent in-depth mining and intelligent analysis of multidimensional data of the substation.

Optimizing spiral‐wound pervaporation membrane modules through simulation: Unraveling the permeate spacer structure

AbstractFor low‐pressure pervaporation, the performance of spiral wound pervaporation membrane (SWM‐PV) module is significantly influenced by permeate spacer structure. This study addresses mass transport challenges in SWM‐PV modules, focusing on increased gas flow resistance and vacuum attenuation due to membrane envelope deformation in the permeate side channel. Employing fluid and structural simulation models to evaluate phase change and membrane deformation, we successfully optimized SWM‐PV module configurations for improved ethanol recovery. Our strategies included a mass transfer‐enhanced feed spacer to mitigate concentration polarization, a high‐strength permeate spacer to alleviate membrane deformation, and tailored membrane envelopes to balance packing density and mass transfer efficiency. These synergistic optimizations led to a 22.1% improvement in ethanol mass transfer coefficient and a 78.5% reduction in module's specific energy consumption. Our work reveals the importance of permeate spacer structure in optimizing SWM‐PV modules, offering clear guidance for the development of mass transfer‐enhanced SWM‐PV modules.