Low Charge States Research Articles

Oligonucleotide Anion Adduct Formation Using Negative Ion Electrospray Ion-Mobility Mass Spectrometry.

Improving the mobile phase of electrospray oligonucleotides has been a major focus in the field of oligonucleotides. These improved mobile phases should reduce the charge state envelope of oligonucleotides coupled with electrospray ionization, which is key to reducing spectral complexity and increasing sensitivity. Traditional mobile phase compositions with fluorinated alcohol and alkylamine, like hexafluoroisopropanol (HFIP) and triethylamine (TEA), have a large amount of cationic adduction and many charge states. Utilizing different fluorinated alcohol and alkylamine combinations, like nonafluoro-tert-butyl alcohol (NFTB) and octylamine (OA), can selectively reduce the charge states analyzed. Other classes of biomolecules have been analyzed with anionic salts to stabilize complexes, increase the molecular peak detection, and even provide unique structural information about these molecules; however, there have been no studies using anionic salts with oligonucleotides. Our experiments systematically study the stability and binding of ammonium anionic salt. We show that anions selectively bind low charge states of these oligonucleotides. Ion-mobility measurements are made to determine the collision cross section (CCS) of these oligonucleotides with anion adduction. We utilize both a nucleic acid exact hard sphere simulation (EHSS) calibration and a protein calibration. We are able to show that NFTB/OA is a good choice for the study of oligonucleotides with reduced charge states for the binding of anionic salts and the determination of CCS using ion mobility.

On the efficacy of SoC-preconditioning on the utilization of battery packs in Electric Vehicles

During the last decade Electric Vehicles (EVs) surged in popularity. However, their mass adoption is slowed by the limited capacity of their Energy Storage System (ESS). Lithium Ion (Li-Ion) technology has established itself as the de-facto standard for mobile applications, though its energy density and cost put a hard limit on the maximum size of viable EV battery packs. Maximizing its utilization therefore becomes of central importance. To efficiently use a battery pack over its entire lifetime, the State of Health (SoH) of the cells needs to be taken into account. In this paper, we propose a novel preconditioning algorithm to minimize the time an EV is connected to the charging station. Our proposed approach uses existing Active Cell Balancing (ACB) hardware of the battery pack to precondition the State of Charge (SoC) of cells such that all cells reach the top SoC threshold at the same time without requiring an additional balancing phase during charging. This is done by considering the individual cells’ SoH to precondition them for achieving an equal time to charge fully. Applying the same approach for discharging, we can extend the driving range of an EV, which otherwise is limited by the cell with the lowest SoC in the pack. Our analysis of various usage scenarios shows that our proposed preconditioning algorithm increases the usable energy of the battery pack by up to 1.8% compared to conventional balancing algorithms while effectively halving the time connected to a charging station, all without requiring any additional hardware components.

Investigation of capacity fade for 18650-type lithium-ion batteries cycled in different state of charge (SoC) ranges

18650-type cells comprising of LiNi0.5Co0.2Mn0.3O2 and LiNi0.9Co0.05Al0.05O2 as cathode blend and graphite as anode are cycled in various SoC ranges. Differing capacity fade is found, indicating that cycling in a medium SoC range results in lower capacity loss and behaves better than including high or low SoC in the cycling ranges. Cycling to low SoC tends to have nonlinear capacity fade (sudden capacity drop). Non-destructive methods, i.e. in situ neutron powder diffraction (NPD) and alternating current (AC) impedance, are employed to study the degradation mechanisms. Lithiated cathode loss and loss of lithium inventory (LLI) are calculated from crystal structure parameters refined from the in situ NPD. LLI is the dominating degradation factor for the differing capacity fade of cells. Lithiated cathode loss and solid electrolyte interphase (SEI) growth are deemed to be main fatigue reasons behind the LLI. By investigating the sensitivity of impedance parameters concerning the change in battery capacity, both ohmic resistance (R0) and SEI resistance (R1) present a linear relationship with the change of capacity for both, linear and nonlinear degradation, i.e. R0 and R1 follow the sudden capacity drop, which is ascribed to the formation of new SEI as evidenced by scanning electron microscopy (SEM) images.

A Fully Filter-Based Decentralized Control With State of Charge Balancing Strategy for Battery Energy Storage Systems in Autonomous DC Microgrid Applications

State of charge (SoC) imbalance and dc bus voltage deviations are significant issues for distributed battery energy storage systems in autonomous dc microgrid applications. Accordingly, a high-pass filter (HPF) based SoC balancing method is proposed to achieve SoC balance by considering different SoCs and capacities; A band-pass filter (BPF) based power droop control is used to accomplish power-sharing and voltage compensation. Through this approach, battery storage units (BSUs) with higher SoC and capacity deliver more power during discharging mode than those with lower SoC and capacity. During charging mode, those BSUs with higher SoC and lower capacity are controlled to absorb less power than those with higher capacity and lower SoC. Therefore, SoC balance can be achieved between distributed BSUs. Further, the dc bus voltage is maintained within the desired range by adopting the proposed method. In addition, the control method employed also considers the impact of line resistance. The proposed control strategy is implemented in a fully decentralized way which does not require any communication link, while maintaining system stability. MATLAB/Simulink and processor-in-the loop (PIL) simulation results verify that the proposed control strategy is effective and feasible.

Dynamic Electrochemical Impedance Spectroscopy of Lithium-ion Batteries: Revealing Underlying Physics through Efficient Joint Time-Frequency Modeling

The value and interpretation of dynamic electrochemical impedance spectroscopy (DEIS) during the charging and discharging of lithium-ion batteries is examined using the Doyle-Fuller-Newman pseudo-two-dimensional (P2D) lithium-ion battery model with parameters for a lithium-cobalt-oxide/graphite cell. Two computational approaches are explored to balance accuracy, speed, and interpretability: (i) A brute force time domain calculation of the full nonlinear equation set subject to direct current (DC) plus superimposed sinusoidal modulation of frequency ω 1, followed by post-processing with short-time Fourier transforms to track the dynamic impedance signal at the modulation frequency during charge and discharge; (ii) A fast-computing time-separated method that solves the C-rate dependent P2D equations for the DC charge/discharge transients occurring on the slow time-scales, t b ∼ O(3600 s/C), followed by solutions to linearized frequency domain equations derived for direct computation of the dynamic impedance signal. The time-separated method is rigorously correct in the limit 1/(t b ω 1) → 0. Key physics that drives differences between stationary and dynamic EIS signals is easily explored with the time-separated method. C-rate dependent studies show that DEIS signals are selectively sensitive to interfacial processes in ways that may be promising for real-time diagnostics and control of the negative electrode at high states-of-charge (SOC) and the positive electrode at low SOCs.

Influence of protein ion charge state on 213 nm top-down UVPD.

Ultraviolet photodissociation (UVPD) is a powerful and rapidly developing method in top-down proteomics. Sequence coverages can exceed those obtained with collision- and electron-induced fragmentation methods. Because of the recent interest in UVPD, factors that influence protein fragmentation and sequence coverage are actively debated in the literature. Here, we performed top-down 213 nm UVPD experiments on a 7 T Fourier-transform ion cyclotron resonance mass spectrometer (FT-ICR MS) for the model proteins ubiquitin, myoglobin and cytochrome c that were electrosprayed from native, denaturing and supercharging solutions in order to investigate the effect of protein charge states on UVPD fragments. By performing UVPD in ultrahigh vacuum, factors associated with collisional cooling and any ion activation during transfer between mass analyzers can be largely eliminated. Sequence coverage increased from <10% for low charge states to >60% for high charge states for all three proteins. This trend is influenced by the overall charge state, i.e., charges per number of amino acid residues, and to a lesser degree by associated structural changes of protein ions of different charge states based on comparisons to published collision-cross section measurements. To rationalize this finding, and correlate sequence ion formation and identity with the number and location of protons, UVPD results were compared to protonation sites predicted based on electrostatic modelling. Assuming confined protonation sites, these results indicate the presence of two general fragmentation types; i.e., charge remote and charge directed. For moderately high protein charge states, fragment ions mostly originate in regions between likely protonation sites (charge remote), whereas sequence ions of highly charge protein ions occur either near backbone amide protonation sites at low-basicity residues (charge directed) or at charge remote sites (i.e., high-basicity residues). Overall, our results suggest that top-down 213 UVPD performance in the zero-pressure limit depends strongly on protein charge states and protonation sites can influence the location of backbone cleavages.

Harnessing Interfacial Electron Transfer in Redox Flow Batteries

Summary Redox flow batteries (RFBs) have garnered increasing attention for their potential to enable the widespread adoption of renewable electricity. However, a critical need associated with the continued development of this technology involves designing electrode-electrolyte interfaces that exhibit rapid, stable electron transfer kinetics. This targeted review outlines key challenges associated with measuring and enhancing the electron transfer kinetics of established and emerging flow battery active materials. We discuss several promising opportunities for advancing flow battery science and technology using the tools of applied electroanalysis and catalysis science. These challenges and opportunities are broadly relevant for future research directed at advancing the commercial adoption of RFBs for grid-scale energy storage.

Combining Acid Titration and Mass Spectrometry to Decouple Mixed Redox Processes in Cation-Disordered Li-Excess Cathodes

In recent years, cation-disordered rock-salt transition-metal oxides (DRX) have emerged as promising cathode materials for Li-ion batteries. With sufficient extent of lithium excess in DRX, lithium ions can diffuse and percolate through lattice tetrahedral holes having low energy barriers. In certain compositions, over 0.7 Li per unit formula (Li1+ x TM1 − x O2, where TM represents transition metal ions) are electrochemically accessible, which leads to exceptionally high capacity that can surpass 300 mAh g − 1. In addition, the limitation of having specific transition metal ions (Mn, Co, and Ni) to form a stable layered structure is relaxed for DRX materials.1 Accommodating various transition metal ions into the DRX lattice enlarges the domain of design and optimization. Thus, DRX material’s potential in reaching a high energy density and increasing the design flexibility makes it a prominent candidate for next-generation cathodes in Li-ion batteries.However, the diverse metal-oxide (or even metal-oxyfluoride) chemistry in DRX also leads to its complex local coordination environment. The inherent cation-mixing and Li-excess nature of the DRX cathode has been argued as the major cause of oxygen redox, which is an atypical redox process in Li-stoichiometric layered materials. Overlapped TM-dominated orbitals and unhybridized O-dominated orbitals in the DRX electronic configuration result in parallel mechanisms of transition-metal redox and oxygen redox.1,2 While X-ray spectroscopic research has elucidated oxygen redox process in Li-excess layered oxides, few studies can successfully resolve and quantify each redox process’s contribution to capacity individually.3 Without quantitative information of the interwoven transition-metal and oxygen redox processes, designing and optimizing DRX materials could be impeded. For example, understanding which redox process dominates the capacity loss may be critical to rationally-design a DRX with a long cycle life. Therefore, the aim of this study is to develop a chemical approach to deconvolute the mixed redox processes in the DRX.In this research, a DRX material, Li1 . 15Ni0 . 45Ti0 . 3Mo0 . 1O1 . 85F0 . 15 (NTMF-DRX), was first isotopically enriched with 18O. Electrodes comprising the 18O-enriched DRX were charged to various cut-off voltages. Meanwhile, the O2 loss from the DRX lattice was monitored and quantified by differential electrochemical mass spectrometry (DEMS). Furthermore, each extracted electrode was then titrated by a concentrated acid solution. When the DRX was etched and dissolved by the acid, O2 evolved from two reactions: 1) disproportionation of oxidized oxygen dissolved from the 18O-enriched DRX lattice; 2) water splitting by oxidized nickel ions (Ni3+ or Ni4+). With the known 18O enrichment (%) in DRX, two sources of O2 can be distinguished and quantified individually via mass spectrometry. Finally, the amount of O2 evolution from two reactions can be used to backcalculate the electrochemical capacity contributed from the nickel redox and the oxygen redox, respectively.The results of this research generally agree with the predictions from ab initio calculations.2 Within the NTMF-DRX material, the nickel redox predominates the charge transfer at low states of charge (below 4.1 V vs. Li/Li+). The oxygen redox occurs and competes with the nickel redox between 4.1 V and 4.5 V, where 39.5% of the charge capacity is supplied by oxidizing oxygen. Moreover, the DEMS analysis provides quantitative outgassing information that is usually not captured by other approaches. At the high voltage ranging from 4.5 V to 4.7 V, the activated formation and further oxidation of dimerized lattice oxygen atoms results in irreversible gaseous O2 loss, which is accounted for 77.7% of the net oxygen redox capacity. On the whole, adding up each component capacity of various redox processes measured using our analytical techniques matches the net charge transfer measured by the potentiostat, with a difference of ≤10 mAh g − 1 at any given potential. To conclude, this study presents a new route to characterize the intermixed redox mechanisms in the DRX. The deconvoluted redox capacity can be useful in developing DRX cathode materials for Li-ion batteries with the supreme performance. References (1) Clément, R. J.; Lun, Z.; Ceder, G. Cation-disordered rocksalt transition metal oxides and oxyfluorides for high energy lithium-ion cathodes. Energy & Environmental Science 2020, 345–373.(2) Seo, D. H.; Lee, J.; Urban, A.; Malik, R.; Kang, S.; Ceder, G. The structural and chemical origin of the oxygen redox activity in layered and cation-disordered Li-excess cathode materials. Nature Chemistry 2016, 8, 692–697.(3) Assat, G.; Tarascon, J. M. Fundamental understanding and practical challenges of anionic redox activity in Li-ion batteries. Nature Energy 2018, 3, 373–386.

Density Functional Tight Binding Modelling of Lithium Intercalated Graphite with Machine-Learned Repulsive Potential

Lithium ion batteries have been a central part of consumer electronics for decades. More recently, they have also become critical components in the quickly arising technological fields of electric mobility and intermittent renewable energy storage. However, many fundamental principles and mechanisms are not yet understood to a sufficient extent to fully realize the potential of the incorporated materials.The vast majority of concurrent lithium ion batteries make use of graphite anodes. Their working principle is based on intercalation–the embedding and ordering of (lithium-) ions in the two-dimensional spaces between the graphene sheets. This important process–it yields the upper bound to a battery's charging speed and plays a decisive role for its longevity–is characterized by multiple phase transitions, ordered and disordered domains, as well as non-equilibrium phenomena, and therefore quite complex. Such complexity emerges particularly at low states of charge (SOC), and complicates both the interpretation of experiments and the computational modelling.From a computational standpoint, targeted system sizes compatible with the SOC range of interest are inaccessible to first-principles calculations, yet require first-principles treatment of key effects such as dispersion and long-range electrostatics. Density Functional Tight Binding (DFTB), a semi-empirical approximation to DFT, offers a high-quality trade-off between accuracy and speed. However, this advantage comes at the cost–or rather initial investment–of pairwise parametrization.As no Li-C DFTB parameters were publicly available yet, we produced a parameter set specifically tailored to this system, employing a parametrization strategy [1] that combines global optimization of electronic parameters via Particle Swarm Optimization (PSO) [2] with our recently developed approach that uses Gaussian Process Regression (GPR) [3] to machine-learn the repulsive potential.Using the resulting parametrization, we are able to reproduce experimental reference structures at a level of accuracy which is in no way inferior to much more costly ab initio methods. We present structural properties and diffusion barriers for some exemplary system states. Additionally, we are able for the first time to resolve the full Potential Energy Surface (PES) of Li motion in stage-I and stage-II LiC108 (SOC 5%). The PES contains information that enables us to implement, and in perspective discuss, both kinetic Monte Carlo (kMC) models of Li-ion mobility in the graphite host, and free-energy sampling which ultimately yields the computed voltage profile of the anode.[1] Panosetti et al., https://arxiv.org/abs/1904.13351 [2] Chou et al., J. Chem. Theory Comput. 2016, 12, 1, 53–64[3] Panosetti et al., J. Chem. Theory Comput. 2020, 16, 4, 2181–2191 Figure 1

Investigating Diffusion of Lithium Intercalated in Graphite By a Combination of Multiscale Modeling and NMR

Lithium ion batteries play a key role in the implementation of fully sustainable electrical mobility. Long lifetime, fast recharging and safety are required for the acceptance of any battery powered vehicle. Graphite is still the state of art as negative electrode. Despite decades of investigation into the mechanism of lithium intercalation, the ion mobility and the underlying microscopic processes are still not fully understood, limiting progress in performance and lifetime prediction of a battery. In particular, improvements in fast charging of batteries mandates a deeper understanding of the lower states of charge (SoC), bellow or around 20 %. We propose a combination of advanced NMR experiments, i.e spin alignment echo (SAE), with a theoretical multi scale modelling approach to investigate relevant phenomena such as lithium ion diffusion in graphite. Here, we present a novel multi-level accelerated first-principles kinetic Monte Carlo (1p-kMC) model to assess in detail the mobility at a low SoC, i.e LiC108. In particular, an external potential is applied in order to mimic the driving force causing (dis)charge of the battery.

Mechanistic Role of Thermal Gradients on Lithium Plating in Li-Ion Batteries

Unwanted lithium deposition on the surface of graphite particles tends to occur during charging of Li-ion batteries at low temperatures, high rates, and high states of charge. However, the intricacies of the coupled thermal-electrochemical interactions that govern Li plating behavior are yet to be fully uncovered. Thermal inhomogeneity naturally develops during the high rate operation of large-format cells, particularly when active cooling systems are employed; hence, a deeper investigation of the relationship between thermal gradients and Li plating is merited. This study employs a microstructure-aware modeling approach to probe the influences of both in-plane and inter-electrode thermal gradients on Li plating. Both types of thermal gradient were found to cause inhomogeneous current distribution within the electrodes. While inter-electrode gradients resulted in a variation in the Li plating onset point and severity, the Li plating induced by in-plane gradients was nearly the same as for isothermal cases at the same mean temperature. The sensitivity of charging performance to mean temperature and thermal gradient magnitude was analyzed across a range of practical conditions. Electrochemical experiments were performed under applied external thermal gradients to study the effect on plating and cell lifespan in various cell formats, and the electrode degradation was characterized post-mortem. By gaining a fundamental understanding of the Li plating phenomenon, this study aims to assist in the design of electrode structures and cell formats that will reduce the propensity for this mode of degradation.

Prolonged Cycle Life for Ultrafast Li4Ti5O12//Li3V2(PO4)3 Superredox Capacitor

1. Introduction One promising strategy of increasing the energy density of electric double layer capacitors (EDLCs) is the design of hybrid supercapacitors, which combine an activated carbon (AC) electrode with an electrode made from a high-capacity faradic (or pseudocapacitive) material such as lithium titanate (Li4Ti5O12, LTO). We have previously reported the LTO//AC hybrid capacitor system—called Nanohybrid Capacitor—shows the 3-fold energy density (30 Wh L-1) of EDLC, while attaining the high power (6,000 W L-1) comparative to EDLC.1) To achieve further increase of energy density from Nanohybrid Capacitor, replacement of the AC positive electrode is required by alternatives with higher capacity as well as ultrafast electrochemical characteristics and excellent cycle capability. Lithium vanadium phosphate [Li3V2(PO4)3, LVP] is promising candidate for positive electrodes due to its relatively high reaction potentials (3.9 V vs. Li/Li+), high reversible capacity (131.5 mAh g-1), and a large value of the Li+ diffusion coefficient (10-9 -10-11 cm2 s-1). In particular, we have successfully synthesized LVP/multiwalled carbon nanotubes (MWCNTs) composites which enable high C-rate operation of 96 mAh g-1 at 300C—more than twice the rate possible with AC electrodes—via our unique technique of ultracentrifugation (UC) treatment.2) Beyond the challenge of improving power performance, a more serious drawback is that the cycle performance of previous LVP-based cells has been limited to 500-4,000 cycles.3,4) In this study, we designed LVP-based full cells consisting of positive electrodes made from the uc-LVP/MWCNT composite paired with negative electrodes made from standard commercially available LTO—which we call SuperRedox Capacitors—that simultaneously achieve high energy, high power density, and long cycle life. We also successfully identify the mechanism of capacity degradation during full cell cycling and devise a strategy for minimizing its effect on the cycling performance.2. Experimental LTO/LVP full-cells were assembled using negative LTO and positive uc-LVP/MWCNT composite electrodes in laminate-type cells. The electrolyte was 1.0 M LiPF6/EC:DEC (1:1, volume ratio). Charge-discharge tests for LTO//LVP full cells were performed in constant-current charge and discharge modes between 1.5-2.8 V. Current densities for the full cells were 10C-rate for cycling tests and ranged from 1 to 480C-rate in rate tests, assuming that 1C-rate equals 131.5 mA g-1.3. Results and Discussion Ragone plots of LTO//LVP full cells calculated based on the total volume of two electrodes are shown in Fig. 1. LTO//LVP full-cells exhibit high volumetric energy density of 63.5 Wh L-1 within the region of low power requirement (100 W L-1) which corresponds to the 5-folds of EDLC. Even at a higher power (10,000 W L-1), 63% of the energy density (40 Wh L-1) can be maintained. Accordingly, the obtained Ragone characteristics for our LTO//LVP full cells demonstrated that this system can be operated at high power comparative to the EDLC, while showing the merit of this system in terms of volumetric capacity compared to EDLC and even Nanohybrid Capacitor. Our LTO//LVP full cells also demonstrated outstanding cyclability: capacity retention of 77% over 10,000 cycles (Fig. 2). Such stable cycle performance was achieved thanks to the electrochemical preconditioning [=Li preconditioning of LTO, state of charge (SOC)=25%] conducted prior to the full cell assembling. In the process of elucidation of the Li-preconditioning effects on cycle performances, it was found that minimization of the vanadium elution from the LVP and the subsequent deposition on the LTO surface play an important role for the stable cycling. Combined results of XPS, ICP-MS and SEM observation suggest that the deposited vanadium species on the LTO surface induces the decomposition of electrolytes and production of HF. The irreversible electrolyte decomposition leads to a decrease in the coulombic efficiency of Li+ intercalation/deintercalation into LTO crystals, resulted in the gradual shift between two electrodes: higher SOC for uc-LVP/MWCNT positive and lower SOC for LTO negative electrodes. Additionally, the produced HF is considered to induce further elution of vanadium from the uc-LVP/MWCNT, accelerating the SOC shifts and degradation in the full cell capacity. Li preconditioning of LTO was found to be effective as a countermeasure, because of the given capacity margin to minimize the effect of SOC shifts, and the formation of the protective coverture on the LTO surface—composed of such as LiF and Li2CO3—from the undesirable vanadium deposition. References 1) K. Naoi et al., Energy Environ. Sci., 5, 9363 (2012).2) K. Naoi et al., J. Electrochem. Soc., 162, A827 (2015).3) M. Secchiaroli et al., J. Mater. Chem. A, 3, 11807 (2015).4) C. Liu et al., Energy Storage Mater., 5, 93 (2016). Figure 1

Coulomb explosion imaging for gas-phase molecular structure determination: An ab initio trajectory simulation study.

Coulomb explosion velocity-map imaging is a new and potentially universal probe for gas-phase chemical dynamics studies, capable of yielding direct information on (time-evolving) molecular structure. The approach relies on a detailed understanding of the mapping between the initial atomic positions within the molecular structure of interest and the final velocities of the fragments formed via Coulomb explosion. Comprehensive on-the-fly ab initio trajectory studies of the Coulomb explosion dynamics are presented for two prototypical small molecules, formyl chloride and cis-1,2-dichloroethene, in order to explore conditions under which reliable structural information can be extracted from fragment velocity-map images. It is shown that for low parent ion charge states, the mapping from initial atomic positions to final fragment velocities is complex and very sensitive to the parent ion charge state as well as many other experimental and simulation parameters. For high-charge states, however, the mapping is much more straightforward and dominated by Coulombic interactions (moderated, if appropriate, by the requirements of overall spin conservation). This study proposes minimum requirements for the high-charge regime, highlights the need to work in this regime in order to obtain robust structural information from fragment velocity-map images, and suggests how quantitative structural information may be extracted from experimental data.

Prediction of compression force evolution over degradation for a lithium-ion battery

This study proposes a method to predict the evolution of compression force during the degradation of a lithium-ion battery under packed conditions. The total compression force comprises irreversible and reversible forces. The former is estimated using a multivariate machine learning method, whereas the latter is estimated by combining machine learning and phenomenological modeling. For predicting the irreversible force, impedance-related features are extracted and their correlations with the evolution of the irreversible force are quantitatively analyzed using Grey relational analysis. Subsequently, features with high Grey relational grades are employed as representative health indicators for multivariate inputs of Gaussian process regression. For predicting the reversible force, the force evolution during the charge/discharge period is predicted using a phenomenological force model. The equivalent stiffness used in this model is separately estimated depending on the state of charge (SOC) to account for the inherent characteristics of phase transition and different degradation behaviors. The evolution of equivalent stiffness under high SOC shows nonlinearity but weak evolution characteristics, whereas those under low and medium SOCs show linearity but strong evolution characteristics. Finally, the proposed method is used to enable control and design for two potential applications: estimations of the state of health-dependent SOC and separator compression.

Economic Impacts of the Demand Response of Electric Vehicles Considering Battery Degradation

The increase in the number of electric vehicles (EVs) has led to increased global expectations that the application of this technology may result in the reduction of CO2 emissions through the replacement of conventional petrol vehicles and ensure the flexibility of power systems such as batteries. In this paper, we propose a residential demand response (DR) evaluation model that considers the degradation mechanism of the EV battery and examines the effective battery operation. We adopted the already-proposed NiMnCo battery degradation model to develop an EV DR evaluation model. In this model, the battery operation is optimized to minimize the electricity and degradation costs affected by ambient temperature, battery state of charge (SOC), and depth of discharge. In this study, we evaluated the impact of the relevant parameters on the economics of the DR of EV batteries for 10 all-electric detached houses with photovoltaic system assuming multiple EV driving patterns and battery (dis)charging constraints. The results indicated that the degradation costs are greatly affected by the SOC condition. If a low SOC can be managed with a DR strategy, the total cost can be reduced. This is because the sum of the reduction of purchased cost from the utility and calendar degradation costs are higher than the increase of the cycle degradation cost. In addition, an analysis was conducted considering different driving patterns. The results showed that the cost reduction was highest when a driving pattern was employed in which the mileage was low and the staying at home time was large. When degradation costs are included, the value of optimized charging and discharging operations is more apparent than when degradation costs are not considered.

Influence of Freezing Treatment on the Thermal Runaway Characteristics of Lithium-Ion Batteries

Owing to increasing applications of lithium-ion batteries (LIBs), it is worth investigating the thermal runaway (TR) behaviors of LIBs under extreme conditions such as flash freezing, which has been proposed as a feasible way for LIB transportation or storage. In this study, a series of experiments was conducted to explore and compare the TR behaviors of batteries with and without freezing treatment. According to the results, the batteries after freezing treatment exhibited a faster temperature rise, and the onset time of TR (t) was shortened. For example, t was 277.2 s in the blank test, whereas for the battery after 72 h freezing, t was 250.2 s. Moreover, the microstructure comparison on the internal electrode materials after TR showed that freezing treatment aggravated the agglomeration and clustering of them. Additionally, we recommend storing LIBs with a lower state of charge (SOC) even in freezing or extreme-cold conditions.

Editors’ Choice—Mechanistic Elucidation of Anion Intercalation into Graphite from Binary-Mixed Highly Concentrated Electrolytes via Complementary 19F MAS NMR and XRD Studies

Dual-graphite batteries have emerged as promising candidate for sustainable energy storage due to their potentially low costs and absence of toxic materials. However, the mechanism of anion intercalation and the structures of the resulting graphite intercalation compounds (GICs) are still not well understood. Here, we systematically evaluate the anion intercalation characteristics into graphite for three highly concentrated electrolytes containing LiPF6, LiTFSI and their equimolar binary mixture. The binary mixture exhibits a significantly enhanced capacity retention and improved intercalation kinetics compared to the single-salt electrolytes in graphite ∣∣ Li metal cells. In situ X-ray diffraction studies prove the formation of stage 1-GICs and a homogeneous distribution of anions within graphite. From ex situ solid-state 19F magic-angle spinning (MAS) nuclear magnetic resonance (NMR) measurements, GICs can be identified at various states-of-charge (SOCs). The 19F chemical shifts of intercalated anions indicate no significant charge transfer between anion and graphite. The observed narrow 19F linewidths of the GIC-signals are most likely caused by a high translational and/or rotational mobility of the intercalates. Furthermore, the 19F MAS NMR studies allow the identification of the molar ratios for PF6− and TFSI− anions intercalated into graphite, suggesting a preferred intercalation of PF6− anions, especially at lower SOCs.

Molecular dynamics modeling of lithium ion intercalation induced change in the mechanical properties of LixMn2O4.

The objective of this study is to understand the fracture mechanisms in the lithium manganese oxide (LiMn2O4) electrode at the molecular level by studying mechanical properties of the material at different values of the State of Charge (SOC) using the principles of molecular dynamics (MD). A 2 × 2 × 2 cubic structure of the LiMn2O4 unit cell containing eight lithium ions, eight trivalent manganese ions, eight tetravalent manganese ions, and 32 oxygen ions is studied using a large-scale atomic/molecular massively parallel simulator. As part of the model validation, the lattice parameter and volume changes of LixMn2O4 as a function of SOC (0 < x < 1) have been studied and validated with respect to the experimental data. This validated model has been used for a parametric study involving the SOC value, strain rate (charge and discharge rate), and temperature. The MD simulations suggest that the lattice constant varies from 8.042 Å to 8.235 Å during a full discharging cycle, in agreement with the experimental data. The material at higher SOC shows more ductile behavior compared to low SOC values. Furthermore, yield and ultimate stresses are less at lower SOC values except when SOC values are within 0.125 and 0.375, verifying the phase transformation theory in this range. The strain rate does not affect the fully intercalated material significantly but seems to influence the material properties of the partially charged electrode. Finally, a study of the effect of temperature suggests that diffusion coefficient values for both high and low-temperature zones follow an Arrhenius profile, and the results are successfully explained using the vacancy diffusion mechanism.

Dynamic charge state distributions of 5 MeV Xe20+ ions penetrating through gaseous argon target

Dynamic distribution of charge state of highly charged 131Xe20+ (Z = 54) ions penetrating through the different areal density of gaseous argon target are measured, with the energy of 5 MeV (38.2 keV/u). Two individual stages of charge state are observed: pre-equilibrium stage, where the distribution moves toward the lower charge state with increasing the density of target; equilibrium stage, where the average charge state remains constant as 3.5. The experimental average charge states are compared with the theoretical predictions by the semi-empirical formulas and the classical-trajectory Monte Carlo (CTMC) respectively. A strong dependence of the average charge on energy loss of projectiles is observed too.

Hard Carbon Composite Electrodes for Sodium‐Ion Batteries with Nano‐Zeolite and Carbon Black Additives

AbstractTo enable fast charging of sodium‐ion batteries and eliminate metallic dendrite growth on the electrodes an improvement in electrode design is required. In this work, we show the benefit of a mixed composite electrode containing ionic and electronic conducting additives for a sodium‐ion battery negative electrode. Hard carbon electrodes with 5 % additive containing different proportions of zeolite and carbon black are coated. The performance of the electrodes is elucidated through electrochemical and physical characterization methods; fast sodiation, electrochemical impedance spectroscopy (EIS), galvanostatic intermittent titration techniques (GITT) and electron microscopy. The addition of zeolite improves the sodium‐ion transport diffusivity within the composite electrode by an order of magnitude at low voltages and high states of charge. EIS shows significantly lower series and solid‐electrolyte interphase (SEI) resistances in the zeolite containing electrode after cycling. The capacity retention at higher rates is improved and a significant reduction of sodium dendrite growth was observed after cycling. SEM images confirm that porosity is still present in the zeolite containing electrode samples, enabling a pore network for sodium ion transport. These results emphasize the importance and limitations of ionic transport within hard carbon electrodes, and the required optimisation between electronic and ionic conductivity for sodium ion transport in these electrodes.