On the Ageing of High Energy Lithium-Ion Batteries-Comprehensive Electrochemical Diffusivity Studies of Harvested Nickel Manganese Cobalt Electrodes

Path ahead: Tackling the Challenge of Computationally Estimating Lithium Diffusion in Cathode Materials

In the roadmap toward designing new and improved materials for Lithium ion batteries, the ability to estimate the diffusion coefficient of Li atoms in electrodes, and eventually solid-state electrolytes, is key. Nevertheless, as of today, accurate prediction through computational tools remains challenging. Its experimental measurement does not appear to be much easier. In this work, we devise a computational protocol for the determination of the Li-migration energy barrier and diffusion coefficient, focusing on a common cathode material such as LiNiO2, which represents a prototype of the widely adopted NMC (LiNi1-x-y Mn x Co y O2) class of materials. Different methodologies are exploited, combining ab initio metadynamics, path sampling, and density functional theory. Furthermore, we propose a novel, fast, and simple 1D approximation for the estimation of the effective frequency. The outlined computational protocol aims to be generally applicable to Lithium diffusion in other materials and components for batteries, including anodes and solid electrolytes.

Understanding Interfaces at the Positive and Negative Electrodes on Sulfide-Based Solid-State Batteries

Despite the high ionic conductivity and attractive mechanical properties of sulfide-based solid-state batteries, this chemistry still faces key challenges to encompass fast rate and long cycling performance, mainly arising from dynamic and complex solid-solid interfaces. This work provides a comprehensive assessment of the cell performance-determining factors ascribed to the multiple sources of impedance from the individual processes taking place at the composite cathode with high-voltage LiNi0.6Mn0.2Co0.2O2, the sulfide argyrodite Li6PS5Cl separator, and the Li metal anode. From a multiconfigurational approach and an advanced deconvolution of electrochemical impedance signals into distribution of relaxation times, we disentangle intricate underlying interfacial processes taking place at the battery components that play a major role on the overall performance. For the Li metal solid-state batteries, the cycling performance is highly sensitive to the chemomechanical properties of the cathode active material, formation of the SEI, and processes ascribed to Li diffusion in the cathode composite and in the space-charge layer. The outcomes of this work aim to facilitate the design of sulfide solid-state batteries and provide methodological inputs for battery aging assessment.

An Efficient Methodology Combining K-Means Machine Learning and Electrochemical Modelling for the Determination of Ionic Diffusivity and Kinetic Properties in Battery Electrodes

This paper presents an innovative and efficient methodology for the determination of the solid-state diffusion coefficient in electrode materials with phase transitions for which the assumption of applying the well-known formula from the work of Weppner et al. is not satisfied. This methodology includes a k-means machine learning screening of Galvanostatic Intermittent Titration Technique (GITT) steps, whose outcomes feed a physics-informed algorithm, the latter involving a pseudo-two-dimensional (P2D) electrochemical model for carrying out the numerical simulations. This methodology enables determining, for all of the 47 steps of the GITT characterization, the dependency of the Na⁺ diffusion coefficient as well as the reaction rate constant during the sodiation of an NVPF electrode to vary between 9 × 10-18 and 6.8 × 10-16 m²·s^-1 and between 2.7 × 10-14 and 1.5 × 10-12 m^2.5·mol^-0.5·s^-1, respectively. This methodology, also validated in this paper, is (a) innovative since it presents for the first time the successful application of unsupervised machine learning via k-means clustering for the categorization of GITT steps according to their characteristics in terms of voltage; (b) efficient given the considerable reduction in the number of iterations required with an average number of iterations equal to 8, and given the fact the entire experimental duration of each step should not be simulated anymore and hence can be simply restricted to the part with current and a small part of the rest period; (c) generically applicable since the methodology and its physics-informed algorithm only rely on "if" and "else" statements, i.e., no particular module/toolbox is required, which enables its replication and implementation for electrochemical models written in any programming language.

Characteristics of Open Circuit Voltage Relaxation in Lithium-Ion Batteries for the Purpose of State of Charge and State of Health Analysis

Open circuit voltage relaxation to a steady state value occurs, and is measured, at the terminals of a lithium-ion battery when current stops flowing. It is of interest for use in determining state of charge and state of health. As voltage relaxation can take several hours, a representative model and curve fitting is necessary for practical usage. Previous studies of lithium-ion voltage relaxation investigate four characteristics: relationship between voltage relaxation magnitude and state of charge; length of relaxation required; model complexity for state of charge estimation; and model complexity for state of health evaluation. However, previous studies have inconsistent methodology or use only one type of lithium-ion cell, making comparison and generalization difficult. To address this, we conducted 3 h and 24 h voltage relaxation experiments over a range of states of charge on three different lithium ion chemistries (nickel cobalt aluminum NCA; nickel manganese cobalt NMC532; lithium iron phosphate LFP) and fitted them with a new voltage relaxation equivalent circuit model. It was found that a 3 h relaxation period was sufficient for NMC and LFP for state of charge and state of health investigations. Voltage relaxation of the NCA cell continued to evolve past 24 h. It was shown that voltage relaxation shape and magnitude changes as a function of state of charge, and the accuracy of estimating state of charge was explored. Strategically choosing a state of charge for state of health assessment can be optimized to accentuate voltage relaxation magnitude and this differs by chemistry. This suggested technique and experimental findings can be paired with battery degradation studies to determine accuracy of assessing state of health.

Small hollow nanostructures as a new morphology to improve stability of LiMn2O4cathodes in Li-ion batteries

Spinel LiMn₂O₄is a promising cathode material for lithium-ion batteries. However, bulk LiMn₂O₄commonly suffers from capacity fading due to the dissolution of Mn into the electrolyte during cycling. Moreover, bulk LiMn₂O₄exhibits a low Li⁺diffusion coefficient that limits the volume available to Li⁺storage. Herein, we report the synthesis of small hollow porous LiMn₂O₄nanostructures with a mean size of 51 nm exhibiting exposed (111) planes, assembled by nanoparticles of about 6 nm in size. The morphological features of these nanostructures ensure a large contact area between the material and the electrolyte, shorten the pathways for Li⁺diffusion and provide effective accommodation of the volume change during cycling. Therefore, these hollow nanostructures exhibit improved discharge capacity retention (nearly 82% after 200 cycles) and a greater Li⁺diffusion coefficient (3.46 × 10^-7cm s^-1) compared with that of bulk LiMn₂O_4.

Comparative Study of Equivalent Circuit Models Performance in Four Common Lithium-Ion Batteries: LFP, NMC, LMO, NCA

Lithium-ion (Li-ion) batteries are an important component of energy storage systems used in various applications such as electric vehicles and portable electronics. There are many chemistries of Li-ion battery, but LFP, NMC, LMO, and NCA are four commonly used types. In order for the battery applications to operate safely and effectively, battery modeling is very important. The equivalent circuit model (ECM) is a battery model often used in the battery management system (BMS) to monitor and control Li-ion batteries. In this study, experiments were performed to investigate the performance of three different ECMs (1RC, 2RC, and 1RC with hysteresis) on four Li-ion battery chemistries (LFP, NMC, LMO, and NCA). The results indicated that all three models are usable for the four types of Li-ion chemistries, with low errors. It was also found that the ECMs tend to perform better in dynamic current profiles compared to non-dynamic ones. Overall, the best-performed model for LFP and NCA was the 1RC with hysteresis ECM, while the most suited model for NMC and LMO was the 1RC ECM. The results from this study showed that different ECMs would be suited for different Li-ion battery chemistries, which should be an important factor to be considered in real-world battery and BMS applications.

Epitaxial Nickel Ferrocyanide Stabilizes Jahn-Teller Distortions of Manganese Ferrocyanide for Sodium-Ion Batteries

Manganese-based Prussian Blue, Na_2-δ Mn[Fe(CN)₆ ] (MnPB), is a good candidate for sodium-ion battery cathode materials due to its high capacity. However, it suffers from severe capacity decay during battery cycling due to the destabilizing Jahn-Teller distortions it undergoes as Mn²⁺ is oxidized to Mn³⁺ . Herein, the structure is stabilized by a thin epitaxial surface layer of nickel-based Prussian Blue (Na_2-δ Ni[Fe(CN)₆ ]). The one-pot synthesis relies on a chelating agent with an unequal affinity for Mn²⁺ and Ni²⁺ ions, which prevents Ni²⁺ from reacting until the Mn²⁺ is consumed. This is a new and simpler synthesis of core-shell materials, which usually needs several steps. The material has an electrochemical capacity of 93 mA h g^-1 , of which it retains 96 % after 500 charge-discharge cycles (vs. 37 % for MnPB). Its rate capability is also remarkable: at 4 A g^-1 (ca. 55 C) it can reversibly store 70 mA h g^-1 , which is also reflected in its diffusion coefficient of ca. 10^-8  cm²  s^-1 . The epitaxial outer layer appears to exert an anisotropic strain on the inner layer, preventing the Jahn-Teller distortions it normally undergoes during de-sodiation.

Closed Loop Recycling of Electric Vehicle Batteries to Enable Ultra-high Quality Cathode Powder

The lithium-ion battery (LIB) recycling market is becoming increasingly important because of the widespread use of LIBs in every aspect of our lives. Mobile devices and electric cars represent the largest application areas for LIBs. Vigorous innovation in these sectors is spurring continuous deployment of LIB powered devices, and consequently more and more LIBs will become waste as they approach end of life. Considering the significant economic and environmental impacts, recycling is not only necessary, but also urgent. The WPI group has successfully developed a closed-loop recycling process, and has previously demonstrated it on a relatively small scale 1 kg spent batteries per experiment. Here, we show that the closed-loop recycling process can be successfully scaled up to 30 kg of spent LIBs from electric vehicle recycling streams, and the recovered cathode powder shows similar (or better) performance to equivalent commercial powder when evaluated in both coin cells and single layer pouch cells. All of these results demonstrate the closed-loop recycling process has great adaptability and can be further developed into industrial scale.

Impact of the Temperature in the Evaluation of Battery Performances During Long-Term Cycling—Characterisation and Modelling

This paper presents the results regarding the thermal characterisation and modelling of high energy lithium-ion battery cells at both room (25 °C) and cycling (35 °C) temperatures. In this work two types of Nickel Manganese Cobalt (NMC) batteries are studied: a fresh (or uncycled) and an aged (or cycled) battery cells. The ageing of the studied NMC battery cells is achieved by means of accelerated ageing tests (i.e., repetition of numerous charge and discharge cycles) at 35 °C cycling temperature. Temperature at the surface of the battery cells is characterised, with a set of three discharge current rates 0.3C (i.e., 6 A), 1C (i.e., 20 A) and 2C (i.e., 40 A), and the evolutions at three different locations on the surface of the battery cells namely, at the top, in the center and at the bottom regions are measured. In addition, temperature and ageing dependent electrochemical-thermal modelling of the uncycled and cycled battery cells is also successfully accomplished in case of both room and cycling temperatures. Numerical simulations were carried out in case of high 2C constant current rate, and the assessment of the modelling accuracy by comparison of the predicted battery cells voltage and temperature with respect to the experimental data is further presented. With this paper, thermal performances of battery cells prior and after long-term cycling are evaluated at the cycling temperature, next to the ambient temperature. Hence, thermal characterisation and modelling results are more closely reflecting that encountered by the battery cells in real cycling conditions, so that their performances are believed in this way to be more objectively evaluated.