Charge State Research Articles

Experimental determination of the entropic heat coefficient of a lithium-ion cell through immersion in a dielectric fluid

The heat generation of a lithium-ion cell is predominantly comprised of irreversible and reversible heating, with the latter term dictated by the entropic heat coefficient which describes the variation of the cell’s open circuit voltage with respect to temperature. The entropic heat coefficient is also dependent upon the cell’s state of charge, and the correct description of its behaviour is required to implement numerical and analytical models which accurately describe the heat generation rate of lithium-ion cells. In this study, the entropic heat coefficient of a single 26,650 LiFePO4 cylindrical lithium-ion cell is determined through a novel liquid immersion experimental set-up, offering greater thermal uniformity and control in comparison to the environmental chambers typically utilised. The arrangement is more cost effective and easily implemented in a laboratory setting, with a thermal non-uniformity of 0.2 °C and setpoint stability of ± 0.1 °C achieved. The entropic heat coefficient is determined for six setpoint temperatures in the range of 15 °C to 40 °C across the cell’s entire state of charge, which is adjusted in increments of 10 %. This work also details the influence of open circuit voltage instability arising from cell self-discharge and relaxation, and a method to adjust for its effect is proposed and implemented. The entropic heat coefficient is subsequently utilised to determine the heat generation rate of the cell under two-phase liquid immersion cooling conditions.

Multi-temperature capable enhanced bidirectional long short term memory-multilayer perceptron hybrid model for lithium-ion battery SOC estimation

In this study, we propose a novel hybrid modeling framework for State of Charge (SOC) estimation across a broad temperature spectrum. First, we build a hybrid model to optimize stacked layers of stacked bidirectional long short term memory networks by introducing dropout mechanisms. At the same time, we also optimize the traditional multi-layer perceptron model to ResMLP, which is improved by introducing residual linkage, and then integrate the two optimization models. Finally, the synergistic effect and attention mechanism of genetic algorithm and particle swarm optimization are used to optimize its parameters. We then rigorously tested the model on nine datasets, including HPPC, DST and BBDST, at different temperatures of 5 °C, 15 °C and 35 °C. Using MAE, RMSE and MAXE benchmarks, our research results show that the proposed hybrid model outperforms the benchmark algorithm, achieving significantly enhanced performance and higher accuracy, and the maximum SOC estimation error is kept below 4.53 %. In addition, experimental evaluation at different temperatures shows the robustness and adaptability of the proposed algorithm.

Effect of ionic bonding on luminescence properties of histidine maleic anhydride derivatives

Polymeric materials exhibiting room-temperature phosphorescent (RTP) have attracted wide attention for their easy synthesis, low toxicity, and applications in various fields such as data encryption, cell imaging, information security and other fields. Nevertheless, the conventional ways of preparing such materials are mainly focused on doping, which may suffer from phase separation, poor compatibility, and lack of effective methods to promote intersystem crossing and suppress the nonradiative deactivation rates. Herein, a series of polymers with fluorescence and phosphorescence dual emission were prepared by simple radical solution copolymerization. Through rigid ion-bonded cross-linked networks and cross-linked hydrogen-bonded networks between the polymer chains, the non-radiative jumps and achieve ultra-long phosphorescence lifetimes were able to suppress. By suppressing non-radiative transitions through rigid ion-bonded cross-linked networks and intermolecular hydrogen-bonding networks between polymer chains, ultra-long phosphorescence is achieved. Impressively, a LRTP lifetime of up to 815.38 ms in polymers under ambientconditions is set up. Moreover, in this study, phosphorescence emission can be easily tuned by balancing ion radius and charge states. These results outline the construction of polymeric materials, endowing traditional polymers with new characteristics and promising potential applications.

An Electro-Chemo-Mechanic Model Resolving Delamination between Components in Complex Microstructures of Solid-State Batteries

A novel approach is presented to model delamination and recontacting at internal interfaces of three-dimensional resolved microstructures of solid-state batteries. To resolve the effect of delaminations, we incorporate the consistent enforcement of contact constraints at those interfaces using Nitsche’s method. The model incorporates charge, mass, and momentum conservation to consider electrochemistry, solid mechanics, and their interaction. After introducing and verifying the model, we examine various scenarios to quantify the effect of delaminations at the electrode-solid electrolyte interface on cell performance. The simulations show that increased mechanical stack pressure during cycling mitigates delamination tendencies at the electrode-solid electrolyte interface. Consistent with existing literature, the simulations demonstrate that delaminations increase the internal resistance and reduce the amount of transferred charge. In contrast to experimental analyses, the presented model allows quantitative and in-depth investigations of delamination effects. Furthermore, our analysis of two cell concepts—one assembled in the discharged state and another assembled in the charged state—indicates that half-cells assembled in an initial state from which the active material shrinks in volume upon first charge or discharge show a higher delamination risk at the electrode-solid electrolyte interface. The study highlights the critical relationship between solid mechanics and electrochemistry in consideration of delamination phenomena in solid-state batteries, offering valuable insights for optimizing battery design and performance.

The charge states in polypropylene doped with ZrO2 nanoparticles and their changes at heat treatment

The charge states in polypropylene doped with ZrO2 nanoparticles and their changes at heat treatment

Optimal hydrogen-battery energy storage system operation in microgrid with zero-carbon emission

To meet the greenhouse gas reduction targets and address the uncertainty introduced by the surging penetration of stochastic renewable energy sources, energy storage systems are being deployed in microgrids. Relying solely on short-term uncertainty forecasts can result in substantial costs when making dispatch decisions for a storage system over an entire day. To mitigate this challenge, an adaptive robust optimization approach tailored for a hybrid hydrogen battery energy storage system (HBESS) operating within a microgrid is proposed, with a focus on efficient state-of-charge (SoC) planning to minimize microgrid expenses. The SoC ranges of the battery energy storage (BES) are determined in the day- ahead stage. Concurrently, the power generated by fuel cells and consumed by electrolysis device are optimized. This is followed by the intraday stage, where BES dispatch decisions are made within a predetermined SoC range to accommodate the uncertainties realized. To address this uncertainty and solve the adaptive optimization problem with integer recourse variables in the intraday stage, we proposed an outer-inner column-and-constraint generation algorithm (outer-inner-CCG). Numerical analyses underscored the high effectiveness and efficiency of the proposed adaptive robust operation model in making decisions for HBESS dispatch.

Lithium-ion battery future degradation trajectory early description amid data-driven end-of-life point and knee point co-prediction

This study develops a novel lithium-ion battery future degradation trajectory early description method amid data-driven end-of-life (EOL) point and knee point (KP) co-prediction. Inspired by the concept of KP, the proposed method firstly employs two-stage curve fitting to offline locate KP with minimization total absolute error between the original trajectory and fitted secants as object. Secondly, from partial multi-step fast-charging curves lying in high state-of-charge (SOC) level with only approximately 0.09 SOC interval, our method mines three new aging-dependent features for EOL and knee cycle co-prediction via two optimized Gaussian process regression models. Afterwards, considering the highly linear characteristics of slow degradation stage, knee capacity is further calculated by the linear function fitted via early capacity degradation sequence. Finally, with early capacity degradation sequence, predicted KP and predicted EOL point, the developed method adopts piece-wise cubic Hermite interpolating polynomial to directly generate future degradation trajectory. The verification results using a 140-cell aging dataset demonstrate that the proposed method is powerful for future degradation trajectory early prediction with high accuracy and extremely low real-time computational cost, where most root-mean-square-error and mean-absolute-percentage-error of trajectory prediction results are below 0.03 Ah and 3%, respectively. Our work, for the first time, reveals the possibility of feature extraction from partial multi-step fast-charging curves, and also provides a low-complexity universal framework for accurate future degradation trajectory early prediction.

Rectification of high-frequency artifacts in EIS data of three-electrode Li-ion cells

The use of a reference electrode and the analysis of Electrochemical Impedance Spectroscopy (EIS) data recorded in three-electrode configuration are beneficial for understanding the underlying electrochemical reaction mechanisms in Li-ion batteries. However, analysis of EIS data recorded both in two-electrode and especially three-electrode configurations is prone to misinterpretation due to presence of unidentified artifacts. Using the commercially available instrument (Biologic VMP3), EIS data is recorded simultaneously for both working and counter electrodes in three-electrode five-wire configuration and are algebraically summed to obtain the data for two-electrode configuration. This data is then compared to that recorded in two-electrode configuration. This arrangement of instrument helps in identifying the otherwise hidden and anomalous features, such as a high-frequency arc and extended solid electrolyte interphase (SEI) region, in the three-electrode configuration and the reason for their absence in the two-electrode configuration. Moreover, these additional features are found State-of-Charge (SoC) i.e., cell-electrochemistry dependent and can be highly influenced by the resistance of current/potential measuring leads. Additionally, a new methodology is established to rectify the EIS data and obtain ‘artifact-free’ electrochemical data.

Dynamic effective charge in the continuum final state in the CDW-EIS model: ionisation of molecules by bare-ion impact

Dynamic effective charge in the continuum final state in the CDW-EIS model: ionisation of molecules by bare-ion impact

A DFT study of gas molecules adsorption on TM-doped PtS2 gas nanosensors

In this study, we examined the adsorption and sensing capabilities of transition metal doped PtS2 monolayers (TM = Co, Cu, Fe, Ni) towards three industrially relevant toxic and hazardous gases: CO, NO, and H2S, using density functional theory (DFT) calculations. The interaction between the gases and the TM-doped PtS2 monolayer substrates was thoroughly investigated, taking into account various adsorption configurations, charge transfer phenomena, band structures, and state densities. Results indicate that the TM dopants markedly enhances the conductivity and gas adsorption capacity of PtS2 monolayer. Specifically, the TM-doped PtS2 monolayers exhibit strong adsorption properties towards CO, NO, and H2S, with the adsorption process identified as chemisorption. By analyzing the alterations in conductivity subsequent to gas adsorption, we discerned that Ni-PtS2 could potentially serve as an effective sensor for CO, NO, and H2S. Consequently, our results furnish a solid theoretical foundation for the development of PtS2-based sensors aimed at detecting these gases. Furthermore, the findings of this research offer valuable insights into the design of gas nanosensors.

The effects of hydrogen on the bonding properties of SiC/Cu interface via first-principles calculations

Ceramic/metal interfaces own great importance of technology, but the weak interface bond limits their applications. In this work, the effects of doping H element on the stability and bonding properties of SiC/Cu interface are studied by first principles calculations. In order to study the stability of interface, the potential surfaces were firstly studied for the C and Si terminated SiC/Cu interfaces. The C terminated interface is more stable than the Si terminated interface, which contributes the largest work of adhesion of 3.998 J/m2. The effects of hydrogen on the interface bonding properties were further studied. The occupation properties of hydrogen atoms were then studied, the hydrogen tends to occupy the octahedral position with negative formation energy. To reveal the bonding strength of SiC/Cu interface, the tensile simulations were carried out. The hydrogen owns obvious effects on the tensile strength depends on its occupation site. The movement and diffusion properties of hydrogen atoms in the interface zone were studied combining molecular dynamics and climbing image nudged elastic band method. Finally, the bonding mechanisms were analyzed by combining charge density, state density, differential charge and bader charge. Based on the above calculation results, it is found that for SiC(001)/Cu(111) interface, the H element generally has a negative impact on the bonding properties of SiC/Cu interface.

Electron-electron-ion triple-coincidence experiment of electron-initiated valence ionization of small water clusters

The ionization and fragmentation of small water clusters induced by electron impact (80 eV) is investigated. Using a multiparticle coincidence spectrometer (reaction microscope), all three charged final state particles—two outgoing electrons and one fragment ion—are detected. Nonprotonated (H2O)2+ and protonated water clusters H3O+, [H2O]2H+, [H2O]4H+, and [H2O]5H+ are identified in the measured ion spectrum. The ionization channels for formation of these species are investigated by measuring the kinetic energy distributions and the electronic states of the ions. Only a single state can lead to (H2O)2+, which is identified as ionization of water dimer with a 1b1 hole at the hydrogen bonding donor molecule, while for the protonated water species three major electronic states corresponding to the ionization of 1b1, 3a1, and 1b2 type orbitals are observed. Published by the American Physical Society 2024

Modeling of a metal hydride energy storage tank dynamics using hybrid numerical, experimental, and machine learning methods

This study presents an integrated analysis combining numerical simulations, experimental investigations, and machine learning models to simulate the performance of metal hydride systems for hydrogen storage under various conditions by using a LaNi5 metal hydride cylindrical tank of 500 NL capacity, with a focus on PCM thermal enhancements and surface water heating and cooling. Numerical simulations offer insights into thermal and reaction dynamics, while experimental data are used for model validation and supplemented with additional numerical data for training a FFNN model to predict dynamic hydrogen flow, surface temperature, and surface heat flux. The obtained mean RMSEs for charging/discharging experimental data is 2.8 SOC% for the state of charge and 0.3 °C for surface temperatures. The study compares the effectiveness of water cooling and heating in metal hydride surface across different temperatures, highlighting their impact on the efficiency of hydrogen absorption and desorption processes. Energy consumption is shown to be non-linear; during charging, heat flux peaks before decreases rapidly within around 0.2 h. During discharging, heat flux rises steadily. The study also explores the impact of adding copper fins to the PCM covering metal hydride system, revealing significant improvements in charging and discharging efficiency, specifically, the integration of 16 copper fins led to a notable decrease in complete charging time from approximately 6.5 h to just over 5.2 h, and in complete discharging time from around 4.5 h to under 3.96 h. Using PCM, the highest heat flux is 5 times less during charge and 2 times less during discharge than that for water cooling mode.

Benchmarking the Performance of Lithium and Sodium‐Ion Batteries With Different Electrode and Electrolyte Materials

ABSTRACTSodium‐ion (Na‐ion) batteries are considered a promising alternative to lithium‐ion (Li‐ion) batteries due to the abundant availability of sodium, which helps mitigate supply chain risks associated with Li‐ion batteries. Many studies have focused on the design of Li‐ion batteries, exploring their energy, power, and cost aspects. However, there is still a lack of similar research conducted on Na‐ion batteries. A comparison of the cell voltage characteristics and rate capability of sodium and lithium‐ion batteries using different types of electrodes and electrolytes. For sodium‐ion batteries electrolytes used are NaPF6 and NaClO4 and electrodes used are NaCoO2, NaNiO2, NaFePO4, (Na3V2(PO4)3), graphite, hard carbon, sodium metal, and sodium titanate. For lithium‐ion batteries with LiPF6 and KOH electrolytes and electrodes as LiCoO2, NMC, LVP, Li2MnSiO4, graphite, silicon, lithium titanate (LTO), lithium metal. A thorough analysis of six important performance metrics is part of the investigation: Ragone plots, Electrolyte salt concentration versus spatial coordinate, electrolyte potential versus spatial coordinate, Cell voltage versus battery cell state of charge, Cell voltage versus time, and state variable versus time. Comparing operating voltage and rated capacity NMC and graphite is selected for lithium‐ion batteries as this combination provides operating voltage up to 4.2 V and a rated capacity of 275 Wh/kg, for sodium‐ion for NaCoO2 and hard carbon which has an operating voltage of 2.5–3.8 V and rated capacity around 200 Wh/kg and another combination of electrode as NaFePO4 and sodium metal with NaClO4 electrolyte has a maximum operating voltage of 2.8–3.8 V and rated capacity around 200 Wh/kg. This paper shows significant influence of electrolyte selection on battery performance. The Ragone plots demonstrate that LiPF6 electrolytes in lithium‐ion batteries and NaPF6 electrolytes in sodium‐ion batteries both exhibit superior specific energy densities compared to their KOH and NaClO4 counterparts, respectively. The work presented in this paper encourages researchers to select alternate electrolytes and electrodes for lithium‐ion and sodium‐ion batteries in order to obtain optimal device performance.

Enhancing grid-connected PV-EV charging station performance through a real-time dynamic power management using model predictive control

This paper presents a novel station manager algorithm for grid-connected PV-EV charging stations, designed to address key challenges in current systems. Existing charging stations often encounter issues such as unstable PV power generation and dependence on grid stability, which can interrupt the EV charging process during grid faults. Additionally, PV arrays are typically designed to extract maximum power, leading to over-current or over-voltage situations that compromise the safety of the charging infrastructure and the EV. Furthermore, these systems often require multiple power electronics converters, increasing complexity and costs while reducing overall system efficiency. To overcome these limitations, the proposed algorithm dynamically switches between on-grid and off-grid modes based on real-time weather conditions, grid availability, and the state of charge of the battery electric vehicle (BEV). This approach maximizes PV power utilization, minimizes grid dependency, and enhances BEV charging performance while prioritizing EV safety and ensuring an uninterrupted power supply. It also provides flexibility in BEV power sizing, optimizing the use of power electronics converters to reduce costs and complexity. Two distinct operating modes, adaptive charging and fast charging, are introduced, each integrated with dedicated model predictive controllers (MPC) to achieve specific control objectives. Semi-experimental simulations using a process-in-the-loop (PIL) test approach with the embedded board eZdsp TMS320F28335 demonstrate that the station manager significantly improves performance over conventional methods under various irradiance levels. Moreover, numerical results demonstrate the superiority of the proposed MPC-based approach over traditional controllers such as Proportional-Integral-Derivative (PID) and Sliding Mode Control (SMC) in different charging modes. For instance, the MPC controller achieved an Integral Absolute Error (IAE) of 11.45%, lower than that of the PID controller, and 4.3% lower than the SMC controller.

Effect of surface corrosion on the zeta potential of copper in acidic solutions

The comprehensive investigation was conducted to analyze the corrosion behavior and surface potential of pure copper surfaces in various acidic solutions. We carried out Zeta potential measurement, electrochemical measurement and in situ Raman spectroscopy to investigate the corrosion process and surface potential of copper in acidic solutions with different pH. It was found that the variation in zeta potential with pH corresponds to the corrosion behavior of copper during this process. In 1mmol / L aqueous chloride media, when the pH is greater than 3.5, unalloyed copper is oxidized to monovalent copper. At this stage, as the pH decreases, the zeta potential gradually increases. When the pH reaches 3.5, the Zeta potential reaches the highest, and the rate of cuprous oxide formation reaches the maximum. When the pH continues decrease, unalloyed copper begins to be oxidized to divalent copper, and the zeta potential will also decrease, the surface charge state shifts to the positive direction. Furthermore, our experimental findings are complemented by Density Functional Theory (DFT) calculations.

3D-Mapping and Manipulation of Photocurrent in an Optoelectronic Diamond Device.

Establishing connections between material impurities and charge transport properties in emerging electronic and quantum materials, such as wide-bandgap semiconductors, demands new diagnostic methods tailored to these unique systems. Many such materials host optically-active defect centers which offer a powerful in situ characterization system, but one that typically relies on the weak spin-electric field coupling to measure electronic phenomena. In this work, charge-state sensitive optical microscopy is combined with photoelectric detection of an array of nitrogen-vacancy (NV) centers to directly image the flow of charge carriers inside a diamond optoelectronic device, in 3D and with temporal resolution. Optical control is used to change the charge state of background impurities inside the diamond on-demand, resulting in drastically different current flow such as filamentary channels nucleating from specific, defective regions of the device. Conducting channels that control carrier flow, key steps toward optically reconfigurable, wide-bandgap optoelectronics are then engineered using light. This work might be extended to probe other wide-bandgap semiconductors (SiC, GaN) relevant to present and emerging electronic and quantumtechnologies.

First SOLEDGE3X-EIRENE simulations of the ITER Neon seeded burning plasma boundary up to the first wall

Boundary plasma simulations are essential to estimate expected divertor and first wall (FW) heat and particle loads on ITER during burning plasma operation. A key missing feature of existing SOLPS simulations (Pitts et al., 2019) is the absence of a plasma solution out to the main chamber walls, essential to self-consistently estimate the gross sputtering of wall material. Here, SOLEDGE3X is applied for the first time to obtain up-to-the wall burning plasma solutions of the ITER boundary plasma at the nominal PSOL = 100 MW of the main SOLPS database simulations, including He ash, Ne seeding but without fluid drifts. Compared with the most recent SOLPS-ITER simulations, our simulations show differences in the exact impurity distribution, but the key results for divertor and wall heat flux remain consistent. In the context of the ITER re-baselining exercise (Pitts, 2024), in which the Be FW armour is proposed to be exchanged for tungsten (W), estimates of W wall sources are key to the assessment of likely core contamination and hence impact on fusion gain. We compare the W gross erosion rates due to the different species excluding W self-sputtering. For the cases simulated spanning 0.27%–0.47% separatrix-averaged Ne concentration and 7.5×1022s−1−1.95×1023s−1 D fuelling, Ne8+ remains the largest contributor to the sputtering flux with the largest source being the outer divertor and baffle. The species-wise contribution to W sputtering changes with fuelling with sputtering due to lower Ne charge states being significant at low D fuelling. In general, the gross W sputtering source is found to decrease with increase in D fuelling and increase with increased Ne seeding.

Advancing Protein Analysis: A Low-Pressure Drift Tube Orbitrap Mass Spectrometer for Ultraviolet Photodissociation-Based Structural Characterization.

Owing to its ability to generate extensive fragmentation of proteins, ultraviolet photodissociation (UVPD) mass spectrometry (MS) has emerged as a versatile ion activation technique for the structural characterization of native proteins and protein complexes. Interpreting these fragmentation patterns provides insight into the secondary and tertiary structures of protein ions. However, the inherent complexity and diversity of proteins often pose challenges in resolving their numerous conformations. To address this limitation, we combined UVPD-MS with drift tube ion mobility, offering potential to acquire conformationally selective MS/MS information. A low-pressure drift tube (LPDT) Orbitrap mass spectrometer equipped with 193 nm UVPD capabilities enables the analysis of protein conformers through the analysis of arrival time distributions (ATDs) of individual fragment ions. ATDs of fragment ions are compared for different backbone cleavage sites of the protein or different precursor charge states to give information about regions of potential folding or elongation. This integrated platform offers promise for advancing our understanding of protein structures in the gas phase.

Ultrafast X-ray laser-induced explosion: How the depth influences the direction of the ion trajectory

Single particle imaging using X-ray lasers is a technique aiming to capture atomic resolution structures of biomolecules in their native state. Knowing the particle's orientation during exposure is crucial for method enhancement. It has been shown that the trajectories of sulfur atoms in a Coulomb exploding lysozyme are reproducible, providing orientation information. This study explores if sulfur atom depth influences explosion trajectory. Employing a hybrid collisional-radiative/molecular dynamics model, we analyze the X-ray laser-induced dynamics of a single sulfur ion at varying depths in water. Our findings indicate that the ion spread-depth relationship depends on pulse parameters. At a photon energy of 2 keV, high-charge states are obtained, resulting in an increase of the spread with depth. However, at 8 keV photon energy, where lower charge states are obtained, the spread is essentially independent with depth. Finally, lower ion mass results in less reproducible trajectories, opening a promising route for determining protein orientation through the introduction of heavy atoms.