Charge State Research Articles

Impact of external heating and state of charge on discharge performance and thermal runaway risk in 21700 Li-ion batteries

This study investigates the combined effects of external heating and State of Charge (SOC) on the discharge performance and thermal runaway risk of 21700 Li-ion batteries. Experiments subject commercially available 21700 cylindrical cells to various external heating conditions at different SOC levels (20, 40, 60, 80, and 100 %) while measuring discharge performance and thermal behavior at different discharge rates (0.2, 0.5, 1, and 1.5C). The study emphasizes the significance of Li-ions' spatial arrangement and maintaining electrical charge in the electrolyte to evaluate battery performance. Numerical simulations are then conducted to complement the experimental data and provide deeper insights. The results reveal a significant degradation in discharge performance with increasing external heat, characterized by voltage drops and reduced capacity. Cells with higher SOC levels exhibit more severe exothermic reactions during external heating, leading to a higher likelihood of thermal runaway. Cells operated at a moderate SOC of 40 % demonstrate a significantly lower risk of thermal runaway under similar heating conditions. The rapid rise in temperature at 100 % SOC of batteries showed a sharp increase of over 20 °C per second. Temperature spikes were noted at specific time intervals corresponding to different SOC levels: 100, 80, 60, 40, and 20. At this critical point, temperatures ranged from 135 to 182 °C, indicating potential thermal issues from internal short circuits causing separator melting. These findings highlight the critical role of SOC management in ensuring the safe and reliable operation of 21700 Li-ion batteries, particularly in applications involving elevated temperatures.

Centralised Control and Energy Management of Multiple Interconnected Standalone AC Microgrids

When microgrids operate autonomously, they must curtail the surplus of renewable energy sources (RES) while minimising reliance on gas. However, when interconnected, microgrids can collaboratively minimise RES curtailment and gas consumption due to the ability of exchanging power. This paper presents a centralised controller and energy management of multiple standalone AC microgrids interconnected to a common AC bus using back-to-back converters. Each microgrid consists of RES, a battery, a gas-powered auxiliary unit, and a load. The battery’s state of charge (SOC) is controlled and is used in the AC bus frequency to indicate whether the microgrid has a surplus or shortage of power. High-level global droop control exchanges power between the microgrids. The optimisation problem for this interconnected system is modelled cooperatively to determine the optimal dispatch solution that minimises the energy cost from the auxiliary unit. The optimal dispatch is solved in three cases using the Nelder–Mead simplex algorithm under different settings: one-variable optimisation, three-variable optimisation with the standard droop equation, and three-variable optimisation with a modified droop equation. The optimised performance results are compared with those of the non-optimised benchmark to determine the percentage of optimal performance. The simulation results show that the total energy cost from the auxiliary unit is minimised by 8.98%.

Novel state of charge estimation method of containerized Lithium–Ion battery energy storage system based on deep learning

State of charge (SOC) is a critical indicator for lithium–ion battery energy storage system. However, model-driven SOC estimation is challenging due to the coupling of internal charging and discharging processes, ion diffusion, and chemical reactions in the electrode materials. These factors result in frequent changes in their internal characteristics. Therefore, we devise a novel deep learning SOC estimation method based on the attention mechanism (A) and convolutional neural networks-long short term memory (CNN–LSTM) network model. The CNN layers are employed to extract the critical features of the battery dataset. The LSTM layers are utilized to capture the long-term dependencies in the time series data. The attention mechanism can assign attention weights to different features within the output of the convolution layer. The A–CNN–LSTM method not only amplifies the positive influence of critical knowledge but also provides a global reference. The comparative experiments of three datasets and ablation study are carried out. The root mean square error, mean absolute error, and mean absolute percentage error obtained from the A–CNN–LSTM model decreased by 32.75 %, 45.88 %, and 53.36 %, respectively, compared with the best results obtained from the existing CNN, LSTM, gate recurrent unit (GRU), CNN–LSTM, and CNN–GRU models. The proposed model demonstrates greater stability and consistency than other models, underscoring its efficacy in SOC estimation.

Observation of Discrete Charge States of a Coherent Two-Level System in a Superconducting Qubit.

We report observations of discrete charge states of a coherent two-level system (TLS) that is strongly coupled to an offset-charge-sensitive superconducting transmon qubit. We measure an offset charge of 0.072e associated with the two TLS eigenstates, which have a transition frequency of 2.9GHz and a relaxation time exceeding 3ms. Combining measurements in the strong dispersive and resonant regime, we quantify both transverse and longitudinal coupling of the TLS-qubit interaction. We further perform joint tracking of TLS transitions and quasiparticle tunneling dynamics but find no intrinsic correlations. This Letter demonstrates microwave-frequency TLS as a source of low-frequency charge noise.

Aging Retardation of Lead-Acid Batteries by Adjusting Charge Controller Threshold Values in Off-grid Photovoltaic System

Hybrid systems or coupled power plants with energy storage are becoming more and more popular due to the rising need for energy. Researchers have been conducting several experiments to assure longer-lasting battery use due to the increasing widespread use of energy storage and the depletion of resources such as silicon and precious metals. In this study, a simulation study is carried out in PVSyst software on lead-acid batteries, which have a low cycle and a very traditional electrochemical structure. The simulation is realized by scaling Spain’s consumption curve in 2023, taken from the European Network of Transmission System Operators for Electricity (ENTSO-E), together with lead acid batteries and off-grid photovoltaic (PV) modules. After the off-grid system design is created and consumption data is imported, it is aimed to extend battery life by changing the charge-discharge threshold values of the charge controllers. Threshold values are in two categories, high and low, and seventeen different cases are simulated. According to the results of the simulation, the state of charge (SOC) levels of the batteries decreases significantly due to radiation and cloudiness in the winter months and remain high in the spring and summer months. When charge controllers are set to high thresholds levels, they cause gassing currents that rise to an average of 20 amps, while battery life extends up to 5.3 years. When low threshold values are used, negligible levels of oxygen and hydrogen gasses are formed in the battery, but battery life decreases to 4.1 years.

Mechanistic Studies of Small Molecule Ligands Selective to RNA Single G Bulges.

Small-molecule RNA binders have emerged as an important pharmacological modality. A profound understanding of the ligand selectivity, binding mode, and influential factors governing ligand engagement with RNA targets is the foundation for rational ligand design. Here, we report a novel class of coumarin derivatives exhibiting selective binding affinity towards single G RNA bulges. Harnessing the computational power of all-atom Gaussian accelerated Molecular Dynamics (GaMD) simulations, we unveiled a rare minor groove binding mode of the ligand with a key interaction between the coumarin moiety and the G bulge. This predicted binding mode is consistent with results obtained from structure-activity-relationship (SAR) studies and transverse relaxation measurements by NMR spectroscopy. We further generated 444 molecular descriptors from 69 coumarin derivatives and identified key contributors to the binding events, such as charge state and planarity, by lasso (least absolute shrinkage and selection operator) regression. Strikingly, small structure perturbations on these key contributors, such as the addition of a methyl group that disrupts the planarity of the ligand resulted in > 100-fold reduction in the binding affinity. Our work deepened the understanding of RNA-small molecule interactions and integrated a new generalizable platform for the rational design of selective small-molecule RNA binders.

Charging of DNA Complexes in Positive-Mode Native Electrospray Ionization Mass Spectrometry.

Native mass spectrometry (nMS) provides insights into the structures and dynamics of biomacromolecules in their native-like states by preserving noncovalent interactions through "soft" electrospray ionization (ESI). For native proteins, the number of charges that are acquired scales with the surface area and mass. Here, we explore the effect of highly negatively charged DNA on the ESI charge of protein complexes and find a reduction of the mass-to-charge ratio as well as a greater variation. The charge state distributions of pure DNA assemblies show a lower mass-to-charge ratio than proteins due to their greater density in the gas phase, whereas the charge of protein-DNA complexes can additionally be influenced by the distribution of the ESI charges, ion pairing events, and collapse of the DNA components. Our findings suggest that structural features of protein-DNA complexes can result in lower charge states than expected for proteins.

A Universal Plug-and-Play Approach to In Situ Multinuclear Magnetic Resonance Analysis of Electrochemical Phenomena in Commercial Battery Cells.

Advancing electrochemical energy storage devices relies on versatile analytical tools capable of revealing the molecular mechanisms behind the function and degradation of battery materials in situ. The nuclear magnetic resonance phenomenon plays a pivotal role in fundamental studies of energy materials and devices because of its exceptional sensitivity to local environments and the dynamics of many electrochemically relevant elements. The jelly roll architecture is one of the most energy-dense and, therefore, most popular concepts implemented in pouch, prismatic, and cylindrical Li- and Na-ion cells. Such widely commercialized designs, however, represent a significant obstacle for a range of powerful in situ magnetic resonance-based methodologies due to negligible radio frequency electromagnetic field penetration through conductive metal casings and current collectors. In this work, we introduce an experimental setup that enables direct RF wave transmission through the cell terminals and current collectors, and provides efficient excitation and detection of NMR signals. An RF adapter designed as a plug-and-play device effectively turns the battery cell into an NMR probe that can be tuned to a broad range of Larmor frequencies. Due to its exceptional sensitivity, versatility, and multinuclear capability, the proposed methodology is suitable for fundamental research and industrial high-throughput screening applications. In situ NMR lineshapes provide a direct quantitative description of the chemical environments of electrochemically active elements and enable new metrics for the accurate assessment of state-of-charge (SoC) and state-of-health (SoH). Specifically, in commercial pouch cells based on lithium cobalt oxide, lithium nickel manganese cobalt oxide, and sodium nickel iron manganese oxide chemistries, 7Li and 23Na NMR data unambiguously show electrochemical transformations between intercalated and metallic forms of charge carrier ions, and reveal anisotropic magnetic properties of the electrode coating.

Substantial oxygen loss and chemical expansion in lithium-rich layered oxides at moderate delithiation.

Delithiation of layered oxide electrodes triggers irreversible oxygen loss, one of the primary degradation modes in lithium-ion batteries. However, the delithiation-dependent mechanisms of oxygen loss remain poorly understood. Here we investigate the oxygen non-stoichiometry in Li1.18-xNi0.21Mn0.53Co0.08O2-δ electrodes as a function of Li content by using cycling protocols with long open-circuit voltage steps at varying states of charge. Surprisingly, we observe substantial oxygen loss even at moderate delithiation, corresponding to 2.5, 4.0 and 7.6 ml O2 per gram of Li1.18-xNi0.21Mn0.53Co0.08O2-δ after resting at upper capacity cut-offs of 135, 200 and 265 mAh g-1 for 100 h. Our observations suggest an intrinsic oxygen instability consistent with predictions of high oxygen activity at intermediate potentials versus Li/Li+. In addition, we observe a large chemical expansion coefficient with respect to oxygen non-stoichiometry, which is about three times greater than those of classical oxygen-deficient materials such as fluorite and perovskite oxides. Our work challenges the conventional wisdom that deep delithiation is a necessary condition for oxygen loss in layered oxide electrodes and highlights the importance of calendar ageing for investigating oxygen stability.

Energy management strategy and operation strategy of hybrid energy storage system to improve AGC performance of thermal power units

With the continuous increase of the renewable energy power generation penetration, the intermittency and fluctuation of renewable energy power generation make the traditional thermal power units (TPU) which play the main role of regulation need to undertake more frequent and more severe regulation tasks. In order to improve the automatic generation control (AGC) command response capability of TPU, an operation strategy of hybrid energy storage system (HESS) is proposed in this paper. While assisting TPU to complete the regulation tasks, it gives full play to the advantages of power-type and energy-type energy storage. Moreover, an energy management strategy of energy storage array (ESA) is proposed to improve the overall operation efficiency of ESA while making the state of charge (SOC) of all energy storage subunits consistent. Finally, the effectiveness of the proposed strategy is verified by simulation experiments. The results show that after using HESS to assist TPU operation, the comprehensive regulation performance index of TPU increased from 4.0198 to 7.8112, which significantly improved the operational flexibility of TPU. Meanwhile, the strategy proposed in this paper makes different types of energy storage systems in HESS operate in a relatively healthy SOC range, and the SOC of the flywheel energy storage system (FESS) reaches the limitation value decrease from 6 times to once, ensuring the overall charge and discharge capacity of HESS.

Inverse Open Circuit Voltage Curve Model for LiCoO2 Battery at Different Temperatures

Lithium-ion batteries are widely used in a variety of applications. For effective battery management, accurate estimation of the state of charge (SOC) is essential. One of the most commonly employed methods for SOC estimation relies on the open circuit voltage (OCV) curve with respect to SOC. However, inverting the OCV-SOC function is not always straightforward. This paper proposes a novel analytical function that directly models the inverse OCV-SOC function, providing a more efficient and reliable method for SOC estimation. Moreover, the dependency of the proposed function on battery temperature is also being investigated, allowing for a wider application of the method under different OCV measuring conditions.

Gábor Transform-Based Antibody Quantitation in Serum: An Interlaboratory Liquid Chromatography/High-Resolution Mass Spectrometry Investigation.

Therapeutic monoclonal antibodies (t-mAbs) are crucial for treating various conditions, including cancers and autoimmune disorders. Accurate quantitation and pharmacokinetic monitoring of t-mAbs in serum are essential, but current methods like ligand binding assays (LBAs) and bottom-up peptide liquid chromatography-tandem mass spectrometry (LC-MS/MS) can lack the sensitivity and specificity needed to meet clinical demands. Emerging techniques using high-resolution mass spectrometry (HRMS) in top-down and middle-up approaches offer improved ability to accurately quantify mAb proteoforms apart from degradation products by keeping the sample proteins intact or minimizing digestion. This study describes the first use of Gábor transform (GT)-based iFAMS Quant+ software to quantify a t-mAb (vedolizumab) from ∼400 samples using an Agilent 6545XT AdvanceBio Q-TOF at the University of Oregon. These results are compared to a previously validated laboratory-developed test (LDT) from Mayo Clinic utilizing a Thermo Q Exactive Plus Orbitrap. The Mayo method used conventional extracted ion chromatograms (XICs) of select charge states for quantitation, while the iFAMS Quant+ method utilized GT-based charge state deconvolution, background subtraction, and signal integration. Calibration and quality control (QC) analyses and Passing-Bablok regression of 351 subject samples demonstrated excellent agreement between the two methods. The iFAMS Quant+ workflow exhibited unique advantages for characterizing interferents and analyte signal anomalies due to its deconvolution-based approach.

Electrolyte‐free solid‐state batteries demonstrated with bifunctional Li2VCl4

All‐solid‐state batteries have attracted much attention because of the expected high energy density and inherent safety stemming from their nonflammable property. While improving the energy density of the cathode poses a significant challenge, here we introduce a novel battery design strategy to enhance energy density by employing bifunctional cathode material, allowing the weight ratio of the active material to be increased without using an electrolyte for the cathode. By employing lithium‐containing vanadium halide Li2VCl4, serving as both active material and electrolyte, the all‐solid‐state battery cell with no electrolyte for the cathode with a capacity approaching the theoretical limit is demonstrated. In addition, we present a guideline for improving capacity retention from the perspective of interfacial stability. Notably, thermodynamic analysis revealed interfacial instability between Li2VCl4 and sulfide material. A double‐layer separator, incorporating halide materials for the cathode side, was implemented to enhance the interfacial stability and mitigate the capacity degradation. Furthermore, it was found that the rate capability depends on the lithium content in synthesized Li2‐xVCl4 and does not change with the state of charge significantly. This study will contribute to designing the bifunctional cathode material for an all‐solid‐state battery and describe its unique properties.

A fusion algorithm of multidimensional element space mapping architecture for SOC estimation of lithium-ion batteries under dynamic operating conditions

Accurate estimation of the state of charge (SOC) is pivotal for ensuring the reliable operation of lithium-ion batteries in electric vehicles, particularly under complex real-world conditions. This paper introduces a novel SOC estimation method named Multidimensional Elemental Space Mapping Architecture (MESMA), which integrates the battery equivalent circuit model with a data-driven approach to tackle adaptability under intricate conditions and high-dimensional input data correlation. Initially, a least squares method incorporating a forgetting factor is employed to identify the battery circuit model parameters and analyze their correlation with SOC. Subsequently, a feature fusion algorithm is introduced to discern spatial variables highly correlated with SOC by leveraging both original voltage and current data and circuit model parameters as inputs to a Convolutional Neural Network (CNN) model, and an eight-input and one-output spatially mapped feature CNN model is established. Finally, the XGBoost model is harnessed for battery SOC estimation. The effectiveness and adaptability of MESMA are validated using experimental data from both public single condition and mixed condition datasets, including FUDS, Mixed-1, etc. The results unequivocally demonstrate that MESMA accurately estimates the SOC of lithium-ion batteries under varying operating conditions. Furthermore, it exhibits remarkable adaptability and stability across different temperatures, effectively capturing SOC trends.

Operando lateral state-of-charge inhomogeneity mapping via wavelength-resolved neutron imaging

The continuous advancement in battery technology requires the development of robust and more precise diagnostic tools for the characterization of commercial-scale battery cells. In this work, operando Bragg edge imaging (BEI), based on a time-of-flight approach, provides spatially resolved state-of-charge (SoC) mapping of a commercial-size pouch cell. The changes in the position and intensity of Bragg edges are used to track the Li intercalation into the graphite, thereby identifying the spatial distribution of various lithiation stages and the corresponding SoC. The operando wavelength-resolved BEI assessment revealed an inhomogeneous Li+ intercalation, dependent on the distance to the electrical tabs, effectively identifying features that contribute to the overall loss of performance and the accelerated degradation of battery materials. The presented results demonstrate the potential of advanced wavelength-resolved neutron imaging to be used as a diagnostic tool for commercial battery cells in a configuration without special casings or isotopes for enhancement of imaging contrast. It thus highlights its applicability for operando characterization of future batteries for portable and automotive applications.

Detection of Impedance Inhomogeneity in Lithium-Ion Battery Packs Based on Local Outlier Factor

The inhomogeneity between cells is the main cause of failure and thermal runaway in Lithium-ion battery packs. Electrochemical Impedance Spectroscopy (EIS) is a non-destructive testing technique that can map the complex reaction processes inside the battery. It can detect and characterise battery anomalies and inconsistencies. This study proposes a method for detecting impedance inconsistencies in Lithium-ion batteries. The method involves conducting a battery EIS test and Distribution of Relaxation Times (DRT) analysis to extract characteristic frequency points in the full frequency band. These points are less affected by the State of Charge (SOC) and have a strong correlation with temperature, charge/discharge rate, and cycles. An anomaly detection characteristic impedance frequency of 136.2644 Hz was determined for a cell in a Lithium-ion battery pack. Single-frequency point impedance acquisition solves the problem of lengthy measurements and identification of anomalies throughout the frequency band. The experiment demonstrates a significant reduction in impedance measurement time, from 1.05 h to just 54 s. The LOF was used to identify anomalies in the EIS data at this characteristic frequency. The detection results were consistent with the actual conditions of the battery pack in the laboratory, which verifies the feasibility of this detection method. The LOF algorithm was chosen due to its superior performance in terms of FAR (False Alarm Rate), MAR (Missing Alarm Rate), and its fast anomaly identification time of only 0.1518 ms. The method does not involve complex mathematical models or parameter identification. This helps to achieve efficient anomaly identification and timely warning of single cells in the battery pack.

Hydrogenation‐Driven Metal Dispersion and Catalytic Enhancement of Borophane‐Supported Single‐Atom Catalysts for Electrochemical Nitrogen Reduction

AbstractThe present study delves into electrochemical nitrogen reduction reaction (NRR) for ammonia synthesis using borophane‐supported single‐atom catalysts (SACs) through density functional theory (DFT) calculations. In comparison to previously reported borophene, which serves as a potential substrate for SACs in NRR, hydrogenated borophane, especially borophane‐2H(B5H2), not only prevents metal aggregation, resulting in stable atomically dispersed metal centers, but also enhances catalytic activity by modulating the metal's charge state. Among all candidates, atomic tungsten anchored on W1/borophane‐2H(B5H2) displays the most favorable NRR activity and product selectivity.

Confined mass transport in two-dimensional capillary

Abstract Over the past decade, nanofluidics has undergone significant expansion, propelled by advances in crafting artificial channels at nanometric and sub-nanometric scales with diverse geometries. Central to this domain, two-dimensional capillaries have risen as a pivotal research platform, marked by their angstrom-level precision, unparalleled wall surface smoothness, and clearly defined surface charge states. Their advent has profoundly deepened our understanding of mass transport dynamics, spanning gases, water molecules, and ions, shedding light on the complex interactions among various influencing factors and revealing a range of previously undiscovered physical phenomena. This review delves into the development of 2D capillaries, the principal fluid transport phenomena observed within, and the critical elements that affect these processes. We also touch on a fascinating discovery - the quantum liquid friction seen in water moving over carbon surfaces. In anticipation of future explorations in nanofluidics, we envision a trajectory aimed at emulating the efficiency levels of biological protein channels, setting the stage for a new era of scientific inquiry and technological innovation.

Spiro-Buckybowls: Synthesis and Selective Transformations Toward Chiral and Nonlinear Optical Polycycles.

Integration of spirocycles with buckybowls is a promising strategy to construct three-dimensional (3D) curved π-systems and to endow distinctive physicochemical features arising from buckybowls. Herein, a series of carbon-bridged spiro-type heterosumanenes (spiro-HSEs) were synthesized by combining 9,9'-spirobifluorene and dichalcogenasumanenes (DCSs). It is found that spiro-conjugation plays an important role in the geometric and electronic structures of spiro-HSEs. The bowl depth of DCSs moiety becomes larger in the spiro-HSEs. Owing to the Jahn-Teller (J-T) effect, two DCSs segments of spiro-HSEs have different bowl depths accompanied with the unequal distribution of charge in radical cation state. Taking advantage of the typical reactions of DCSs, selective transformations of spiro-HSEs have been adopted in accordance to the nature of chalcogen atoms (S, Se, Te) to bestow the value-added functionalities. The emissive property is enhanced by converting the thiophene rings of S-doped spiro-HSE into thiophene S,S-dioxides. A chiroptical polycycle could be produced by ring-opening of the edge benzene of Se-doped spiro-HSE. The covalent adduct of Te-doped spiro-HSE with Br2 forms non-centrosymmetric halogen-bonded networks, resulting in the high performance second-order nonlinear optics (NLO).

Spiro‐Buckybowls: Synthesis and Selective Transformations Toward Chiral and Nonlinear Optical Polycycles

AbstractIntegration of spirocycles with buckybowls is a promising strategy to construct three‐dimensional (3D) curved π‐systems and to endow distinctive physicochemical features arising from buckybowls. Herein, a series of carbon‐bridged spiro‐type heterosumanenes (spiro‐HSEs) were synthesized by combining 9,9′‐spirobifluorene and dichalcogenasumanenes (DCSs). It is found that spiro‐conjugation plays an important role in the geometric and electronic structures of spiro‐HSEs. The bowl depth of DCSs moiety becomes larger in the spiro‐HSEs. Owing to the Jahn‐Teller (J‐T) effect, two DCSs segments of spiro‐HSEs have different bowl depths accompanied with the unequal distribution of charge in radical cation state. Taking advantage of the typical reactions of DCSs, selective transformations of spiro‐HSEs have been adopted in accordance to the nature of chalcogen atoms (S, Se, Te) to bestow the value‐added functionalities. The emissive property is enhanced by converting the thiophene rings of S‐doped spiro‐HSE into thiophene S,S‐dioxides. A chiroptical polycycle could be produced by ring‐opening of the edge benzene of Se‐doped spiro‐HSE. The covalent adduct of Te‐doped spiro‐HSE with Br2 forms non‐centrosymmetric halogen‐bonded networks, resulting in the high performance second‐order nonlinear optics (NLO).