Enhanced energy density and fast-charging ability via directional particle configuration

The limited energy density of lithium-ion capacitors poses a significant obstacle to their widespread application,primarily stemming from the inability of the electrodes to simultaneously fulfill both high energy density and rapid charging requirements.Experimental data demonstrate that a directional particle configuration can enhance charging speed while maintaining high-capacity density,but it is rarely discussed.Here,we have developed a particle-level electrochemical model capable of reconstructing an electrode with a directional particle configuration.By employing this method,an investigation was conducted to explore how the spatial morphology characteristics of particle configuration impact the energy storage characteristics of electrodes.Results demonstrate that rational particle configuration can effectively enhance the transport of lithium ions and create additional space for lithium-ion storage.With the same particle size distribution,the best electrode can increase the discharge capacity by up to132.4% and increase the charging SOC by 11.3% compared to the ordinary electrode under the condition of 6 C.These findings provide a further understanding of the energy storage mechanism inside the anisotropic particle distribution electrode,which is important for developing high-performance lithium-ion capacitors.

A comparative study of data-driven battery capacity estimation based on partial charging curves

With its generality and practicality, the combination of partial charging curves and machine learning(ML) for battery capacity estimation has attracted widespread attention. However, a clear classification,fair comparison, and performance rationalization of these methods are lacking, due to the scattered existing studies. To address these issues, we develop 20 capacity estimation methods from three perspectives:charging sequence construction, input forms, and ML models. 22,582 charging curves are generated from 44 cells with different battery chemistry and operating conditions to validate the performance. Through comprehensive and unbiased comparison, the long short-term memory(LSTM) based neural network exhibits the best accuracy and robustness. Across all 6503 tested samples, the mean absolute percentage error(MAPE) for capacity estimation using LSTM is 0.61%, with a maximum error of only 3.94%. Even with the addition of 3 m V voltage noise or the extension of sampling intervals to 60 s, the average MAPE remains below 2%. Furthermore, the charging sequences are provided with physical explanations related to battery degradation to enhance confidence in their application. Recommendations for using other competitive methods are also presented. This work provides valuable insights and guidance for estimating battery capacity based on partial charging curves.

A novel integrated microfluidic chip for on-demand electrostatic droplet charging and sorting

On-demand droplet sorting is extensively applied for the efficient manipulation and genome-wide analysis of individual cells.However,state-of-the-art microfluidic chips for droplet sorting still suffer from low sorting speeds,sample loss,and labor-intensive preparation procedures.Here,we demonstrate the development of a novel microfluidic chip that integrates droplet generation,on-demand electrostatic droplet charging,and high-throughput sorting.The charging electrode is a copper wire buried above the nozzle of the microchannel,and the deflecting electrode is the phosphate buffered saline in the microchannel,which greatly simplifies the structure and fabrication process of the chip.Moreover,this chip is capable of high-frequency droplet generation and sorting,with a frequency of 11.757 kHz in the drop state.The chip completes the selective charging process via electrostatic induction during droplet generation.On-demand charged microdroplets can arbitrarilymove to specific exit channels in a three-dimensional(3D)-deflected electric field,which can be controlled according to user requirements,and the flux of droplet deflection is thereby significantly enhanced.Furthermore,a lossless modification strategy is presented to improve the accuracy of droplet deflection or harvest rate from 97.49% to 99.38% by monitoring the frequency of droplet generation in real time and feeding it back to the charging signal.This chip has great potential for quantitative processing and analysis of single cells for elucidating cell-to-cell variations.

Unraveling the Fundamental Mechanism of Interface Conductive Network Influence on the Fast‑Charging Performance of SiO‑Based Anode for Lithium‑Ion Batteries

Progress in the fast charging of high-capacity silicon monoxide(SiO)-based anode is currently hindered by insufficient conductivity and notable volume expansion.The construction of an interface conductive network effectively addresses the aforementioned problems;however,the impact of its quality on lithium-ion transfer and structure durability is yet to be explored.Herein,the influence of an interface conductive network on ionic transport and mechanical stability under fast charging is explored for the first time.2D modeling simulation and Cryo-transmission electron microscopy precisely reveal the mitigation of interface polarization owing to a higher fraction of conductive inorganic species formation in bilayer solid electrolyte interphase is mainly responsible for a linear decrease in ionic diffusion energy barrier.Furthermore,atomic force microscopy and Raman shift exhibit substantial stress dissipation generated by a complete conductive network,which is critical to the linear reduction of electrode residual stress.This study provides insights into the rational design of optimized interface SiO-based anodes with reinforced fast-charging performance.

Strategic Placement of Charging Stations for Enhanced Electric Vehicle Adoption in San Diego, California

California mandated that 100% of vehicles sold must be electric by 2035. As electric vehicles (EVs) reach a higher penetration of the car sector, cities will need to provide publicly accessible charging stations to meet the charging demand of people who do not have access to a private charging spot like a personal garage. We have chosen to limit our scope to San Diego County due to its non-trivial size, well-defined shape, and dependence on personal vehicles;this project models 100% of current vehicles as electric, roughly 2.5 million. By planning for the future, our model becomes more useful as well as more equitable. We anticipate that our model will find locations that can service multiple population centers, while also maximizing distance to other stations. Sensitivity analysis and testing of our algorithms are conducted for Coronado Island, an island with 24,697 residents. Our formulation is then scaled to set the parameters for the whole county.

Ultraconformable Integrated Wireless Charging Micro-Supercapacitor Skin

Conformable and wire-less charging energy storage devices play important roles in enabling the fast development of wearable,non-contact soft electronics.However,current wire-less charging power sources are still restricted by limited flexural angles and fragile connection of components,resulting in the failure expression of performance and constraining their fur-ther applications in health monitoring wearables and moveable artificial limbs.Herein,we present an ultracompatible skin-like integrated wireless charging micro-supercapacitor,which building blocks(including electrolyte,electrode and substrate)are all evaporated by liquid precursor.Owing to the infiltration and permeation of the liquid,each part of the integrated device attached firmly with each other,forming a compact and all-in-one configuration.In addition,benefitting from the controllable volume of electrode solution precursor,the electrode thickness is easily regulated varying from 11.7 to 112.5μm.This prepared thin IWC-MSC skin can fit well with curving human body,and could be wireless charged to store electricity into high capacitive micro-supercapacitors(11.39 F cm-3)of the integrated device.We believe this work will shed light on the construction of skin-attachable electronics and irregular sensing microrobots.

ZnO Additive Boosts Charging Speed and Cycling Stability of Electrolytic Zn–Mn Batteries

Electrolytic aqueous zinc-manganese(Zn–Mn) batteries have the advantage of high discharge voltage and high capacity due to two-electron reactions. However, the pitfall of electrolytic Zn–Mn batteries is the sluggish deposition reaction kinetics of manganese oxide during the charge process and short cycle life. We show that, incorporating ZnO electrolyte additive can form a neutral and highly viscous gel-like electrolyte and render a new form of electrolytic Zn–Mn batteries with significantly improved charging capabilities. Specifically, the ZnO gel-like electrolyte activates the zinc sulfate hydroxide hydrate assisted Mn^(2+) deposition reaction and induces phase and structure change of the deposited manganese oxide(Zn_(2)Mn_(3)O_8·H_(2)O nanorods array), resulting in a significant enhancement of the charge capability and discharge efficiency. The charge capacity increases to 2.5 mAh cm^(-2) after 1 h constant-voltage charging at 2.0 V vs. Zn/Zn^(2+), and the capacity can retain for up to 2000 cycles with negligible attenuation. This research lays the foundation for the advancement of electrolytic Zn–Mn batteries with enhanced charging capability.

Multilevel carbon architecture of subnanoscopic silicon for fast‐charging high‐energy‐density lithium‐ion batteries

Silicon(Si)is widely used as a lithium‐ion‐battery anode owing to its high capacity and abundant crustal reserves.However,large volume change upon cycling and poor conductivity of Si cause rapid capacity decay and poor fast‐charging capability limiting its commercial applications.Here,we propose a multilevel carbon architecture with vertical graphene sheets(VGSs)grown on surfaces of subnanoscopically and homogeneously dispersed Si–C composite nanospheres,which are subsequently embedded into a carbon matrix(C/VGSs@Si–C).Subnanoscopic C in the Si–C nanospheres,VGSs,and carbon matrix form a three‐dimensional conductive and robust network,which significantly improves the conductivity and suppresses the volume expansion of Si,thereby boosting charge transport and improving electrode stability.The VGSs with vast exposed edges considerably increase the contact area with the carbon matrix and supply directional transport channels through the entire material,which boosts charge transport.The carbon matrix encapsulates VGSs@Si–C to decrease the specific surface area and increase tap density,thus yielding high first Coulombic efficiency and electrode compaction density.Consequently,C/VGSs@Si–C delivers excellent Li‐ion storage performances under industrial electrode conditions.In particular,the full cells show high energy densities of 603.5 Wh kg^(−1)and 1685.5 Wh L^(−1)at 0.1 C and maintain 80.7%of the energy density at 3 C.

Optimizing Average Electric Power During the Charging of Lithium-Ion Batteries Through the Taguchi Method

In recent times, lithium-ion batteries have been widely used owing to their high energy density, extended cycle lifespan, and minimal self-discharge rate. The design of high-speed rechargeable lithium-ion batteries faces a significant challenge owing to the need to increase average electric power during charging. This challenge results from the direct influence of the power level on the rate of chemical reactions occurring in the battery electrodes. In this study, the Taguchi optimization method was used to enhance the average electric power during the charging process of lithium-ion batteries. The Taguchi technique is a statistical strategy that facilitates the systematic and efficient evaluation of numerous experimental variables. The proposed method involved varying seven input factors, including positive electrode thickness, positive electrode material, positive electrode active material volume fraction, negative electrode active material volume fraction, separator thickness, positive current collector thickness, and negative current collector thickness. Three levels were assigned to each control factor to identify the optimal conditions and maximize the average electric power during charging. Moreover, a variance assessment analysis was conducted to validate the results obtained from the Taguchi analysis. The results revealed that the Taguchi method was an eff ective approach for optimizing the average electric power during the charging of lithium-ion batteries. This indicates that the positive electrode material, followed by the separator thickness and the negative electrode active material volume fraction, was key factors significantly infl uencing the average electric power during the charging of lithium-ion batteries response. The identification of optimal conditions resulted in the improved performance of lithium-ion batteries, extending their potential in various applications. Particularly, lithium-ion batteries with average electric power of 16 W and 17 W during charging were designed and simulated in the range of 0-12000 s using COMSOL Multiphysics software. This study efficiently employs the Taguchi optimization technique to develop lithium-ion batteries capable of storing a predetermined average electric power during the charging phase. Therefore, this method enables the battery to achieve complete charging within a specific timeframe tailored to a specificapplication. The implementation of this method can save costs, time, and materials compared with other alternative methods, such as the trial-and-error approach.

Study on site selection planning of urban electric vehicle charging station

The large-scale development of electric vehicles(EVs)requires numerous charging stations to serve them,and the charging stations should be reasonably laid out and planned according to the charging demand of electric vehicles.Considering the costs of both operators and users,a site selection model for optimal layout planning of charging stations is constructed,and a queuing theory approach is used to determine the charging pile configuration to meet the charging demand in the planning area.To solve the difficulties of particle swarm global optimization search,the improved random drift particle swarm optimization(IRDPSO)and Voronoi diagram are used to jointly solve for the optimal layout of electric vehicles.The final arithmetic analysis verifies the feasibility and practicality of the model and algorithm,and the results show that the total social cost is minimized when the charging station is 9,the location of the charging station is close to the center of gravity and the layout is reasonable.

Designing an Effective Method for Automatic Electric Vehicle Charging Stations in a Static Environment

This article outlines an Effective Method for Automatic Electric Vehicle Charging Stations in a Static Environment. It consists of investigated wireless transformer structures with various ferrite forms. WPT technology has rapidly advanced in the last few years. At kilowatt power levels, the transmission distance grows from a few millimeters to several hundred millimeters with a grid to load efficiency greater than 90%. The improvements have made the WPT more appealing for electric vehicle (EV) charging applications in both static and dynamic charging scenarios. Static and dynamic WEVCS, two of the main applications, are described, and current developments with features from research facilities, academic institutions, and businesses are noted. Additionally, forthcoming concepts based WEVCS are analyzed and examined, including “dynamic” wireless charging systems (WCS). A dynamic wireless power transfer (DWPT) system, which can supply electricity to moving EVs, is one of the feasible alternatives. The moving secondary coil is part of the dynamic WPT system, which also comprises of many fixed groundside (primary) coils. An equivalent circuit between the stationary system and the dynamic WPT system that results from the stationary system is demonstrated by theoretical investigations. The dynamic WPT system’s solenoid coils outperform circular coils in terms of flux distribution and misalignment. The WPT-related EV wireless charging technologies were examined in this study. WPT can assist EVs in overcoming their restrictions on cost, range, and charging time.

Overview of multi-stage charging strategies for Li-ion batteries

To reduce the carbon footprint in the transportation sector and improve overall vehicle efficiency,a large number of electric vehicles are being manufactured.This is due to the fact that environmental concerns and the depletion of fossil fuels have become significant global problems.Lithium-ion batteries(LIBs)have been distinguished themselves from alternative energy storage technologies for electric vehicles(EVs) due to superior qualities like high energy and power density,extended cycle life,and low maintenance cost to a competitive price.However,there are still certain challenges to be solved,like EV fast charging,longer lifetime,and reduced weight.For fast charging,the multi-stage constant current(MSCC) charging technique is an emerging solution to improve charging efficiency,reduce temperature rise during charging,increase charging/discharging capacities,shorten charging time,and extend the cycle life.However,there are large variations in the implementation of the number of stages,stage transition criterion,and C-rate selection for each stage.This paper provides a review of these problems by compiling information from the literature.An overview of the impact of different design parameters(number of stages,stage transition,and C-rate) that the MSCC charging techniques have had on the LIB performance and cycle life is described in detail and analyzed.The impact of design parameters on lifetime,charging efficiency,charging and discharging capacity,charging speed,and rising temperature during charging is presented,and this review provides guidelines for designing advanced fast charging strategies and determining future research gaps.

Deep Learning Based Automatic Charging Identification and Positioning Method for Electric Vehicle

Electric vehicle charging identification and positioning is critically important to achieving automatic charging.In terms of the problem of automatic charging for electric vehicles,a dual recognition and positioning method based on deep learning is proposed.The method is divided into two parts:global recognition and localization and local recognition and localization.In the specific implementation process,the collected pictures of electric vehicle charging attitude are classified and labeled.It is trained with the improved YOLOv4 networkmodel and the corresponding detectionmodel is obtained.The contour of the electric vehicle is extracted by the BiSeNet semantic segmentation algorithm.The minimum external rectangle is used for positioning of the electric vehicle.Based on the location relationship between the charging port and the electric vehicle,the rough location information of the charging port is obtained.The automatic charging equipment moves to the vicinity of the charging port,and the camera near the charging gun collects pictures of the charging port.The model is detected by the Hough circle,the KM algorithmis used for featurematching,and the homography matrix is used to solve the attitude.The results show that the dual identification and location method based on the improved YOLOv4 algorithm proposed in this paper can accurately locate the charging port.The accuracy of the charging connection can reach 80%.It provides an effective way to solve the problems of automatic charging identification and positioning of electric vehicles and has strong engineering practical value.

The acceleration of a high-charge electron bunch to 10 GeV in a 10-cm nanoparticle-assisted wakefield accelerator

An intense laser pulse focused onto a plasma can excite nonlinear plasma waves.Under appropriate conditions,electrons from the background plasma are trapped in the plasma wave and accelerated to ultra-relativistic velocities.This scheme is called a laser wakefield accelerator.In this work,we present results from a laser wakefield acceleration experiment using a petawatt-class laser to excite the wakefields as well as nanoparticles to assist the injection of electrons into the accelerating phase of the wakefields.We find that a 10-cm-long,nanoparticle-assisted laser wakefield accelerator can generate 340 pC,10±1.86 GeV electron bunches with a 3.4 GeV rms convolved energy spread and a 0.9 mrad rms divergence.It can also produce bunches with lower energies in the 4–6 GeV range.

Solar wind ion charge state distributions and compound cross sections for solar wind charge exchange X-ray emission

Solar Wind Charge eXchange X-ray(SWCX) emission in the heliosphere and Ea rth’s exosphere is a hard to avoid signal in soft Xray obse rvations of astrophysical targets.On the other hand,the X-ray imaging possibilities offered by the SWCX process has led to an increasing number of future dedicated space missions for investigating the solar wind-terrestrial inte ractions and magnetospheric interfaces.In both cases,accurate modelling of the SWCX emission is key to correctly interpret its signal,and remove it from obse rvations,when needed.In this paper,we compile solar wind abundance measurements from ACE for different solar wind types,and atomic data from literature,including charge exchange cross-sections and emission probabilities,used fo r calculating the compound cross-section a for the SWCX X-ray emission.We calculate a values for charge-exchange with H and He,relevant to soft X-ray energy bands(0.1-2.0 keV)for various solar wind types and solar cycle conditions.

Intelligent Electric Vehicle Charging Scheduling in Transportation-Energy Nexus With Distributional Reinforcement Learning

Dear Editor,This letter is concerned with electric vehicle(EV) charging scheduling problem in transportation-energy nexus using an intelligent decision-making strategy with probabilistic self-adaptability features.

Electric Vehicle Charging Capacity of Distribution Network Considering Conventional Load Composition

At present,the large-scale access to electric vehicles(EVs)is exerting considerable pressure on the distribution network.Hence,it is particularly important to analyze the capacity of the distribution network to accommodate EVs.To this end,we propose a method for analyzing the EV capacity of the distribution network by considering the composition of the conventional load.First,the analysis and pretreatment methods for the distribution network architecture and conventional load are proposed.Second,the charging behavior of an EVis simulated by combining the Monte Carlo method and the trip chain theory.After obtaining the temporal and spatial distribution of the EV charging load,themethod of distribution according to the proportion of the same type of conventional load among the nodes is adopted to integrate the EV charging load with the conventional load of the distribution network.By adjusting the EV ownership,the EV capacity in the distribution network is analyzed and solved on the basis of the following indices:node voltage,branch current,and transformer capacity.Finally,by considering the 10-kV distribution network in some areas of an actual city as an example,we show that the proposed analysis method can obtain a more reasonable number of EVs to be accommodated in the distribution network.

Weight Gain from Static Charging

This paper announces the discovery that a statically charged object gains weight, equal to approximately 7 × 10-11 grams per excess electron when the object is negatively charged and 5 × 10-11 grams per excess proton when positively charged. The weight gain is not instantaneous but increases to a maximum and then decays with the excess charge.

Fluid Charging and Paleo-pressure Evolution in the Ledong Slope Zone of the Yinggehai Basin,South China Sea

Large numbers of gas reservoirs have been discovered in overpressure basins.Fluid charging has a close relationship with paleo-pressure evolution,affecting the migration of gas reservoirs.To study fluid charging and the related pressure system,we analyzed burial histories and fluid inclusion(PVTx)simulations and conducted basin modeling of the Ledong Slope Zone in the Yinggehai Basin as an example.On the basis of fluid-inclusion assemblages(FIAs),homogenization temperature(Th),final melting temperature(Tm,ice)and Raman spectroscopy in fluid inclusions,there are three stages of fluid charging:during the first and second stage,methane-dominated fluid was charged at 2.2–1.7 Ma and 1.7–0.9 Ma,respectively.In the third stage,CO_(2)-rich hydrothermal fluid was charged since 0.9 Ma.It could be concluded from the well-logging data that the disequilibrium compaction in the Yinggehai Fm.,along with the fluid expansion and clay diagenesis in the Huangliu and Meishan formations,resulted in the overpressure in the Ledong slope zone.The evolution of paleo-pressure was affected by the sedimentation rate of the Yinggehai Fm.,as well as the hydrocarbon generation rate.Additionally,the Ledong Slope Zone is less affected by diapir activity than the nearby diapir area.Based on fluid inclusions,paleo-pressure,basin modeling and geological background,the gas migration history of the Ledong Slope Zone can be divided into four stages:in the first stage,excess pressure was formed around 5 Ma;from 2.2 to 1.7 Ma,there was a reduction in the charging of hydrocarbon fluid and steadily increasing excess pressure;during the 1.7–0.9 Ma period a large amount of hydrocarbon was generated,excess pressure increasing significantly and hydraulic fractures forming in mudstones,With gas reservoirs developing in structural highs;since 0.9 Ma,CO_(2)-rich hydrothermal fluid accumulated in reservoirs adjacent to faults and the pressure coefficient remained stable.The research results are helpful in the study of fluid migration and accumulation mechanisms in overpressure basins.

Microporous Cyclodextrin Film with Funnel-type Channel Polymerized on Electrospun Cellulose Acetate Membrane as Separators for Strong Trapping Polysulfides and Boosting Charging in Lithium-Sulfur Batteries

The“shuttle effect”of polysulfides hampers the commercialization of lithium-sulfur(Li-S)batteries.Here,a thin molecular sieve film was decorated on the surface of an electrospun cellulose acetate(CA)membrane derived from recycled cigarette filters,where the truncated cone structureβ-cyclodextrin(β-CD)was selected as the building block to physically block and chemically trap polysulfides while simultaneously dramatically speeding up ion transport.Furthermore,on theβ-CD free side of the separator facing the cathode,graphite carbon(C)was sputtered as an upper current collector,which barely increases the thickness.These benefits result in an initial discharge performance of 1378.24 mAh g^(−1) and long-term cycling stability of 863.78 mAh g^(−1) after 1000 cycles at 0.2 C for the battery with theβ-CD/CA/C separator,which is more than three times that of the PP separator after 500 cycles.Surprisingly,the funnel-type channel ofβ-CD generates a differential ionic fluid pressure on both sides,speeding up ion transport by up to 69%,and a 65.3%faster charging rate of 9484 mA g^(−1) was achieved.The“funnel effect”of a separator is regarded as a novel and high-efficiency solution for fast charging of Li-S and other lithium secondary batteries.