Manganese Cobalt Oxide Research Articles

Identification of waste lithium-ion battery cell chemistry for recycling.

Battery technology has attained a key position as an energy storage technology in decarbonization of energy systems. Lithium-ion batteries have become the dominant technology currently used in consumer appliances, electric vehicles (EVs), and industrial applications. However, lithium-ion batteries are not alike and can have different cathode chemistries which makes their recycling more complex. In addition, as larger quantities of batteries are starting to enter their end-of-life (EOL) stage, efficient handling and management of batteries with different cathode chemistry types are required. By identifying the cathode chemistry type prior to mechanical treatment, mixing of different cathode chemistries could be decreased, resulting in an increase in overall recycling efficiency. This study investigated the applicability of a non-destructive battery diagnostic methods, namely incremental capacity analysis (ICA), for identifying EOL lithium-ion battery chemistry. The study conducted ICA both on known reference batteries and EOL batteries from the recycling industry. Next, EOL batteries were crushed and the resulting fine active material was analysed to validate the ICA result. In addition, released gaseous and airborne particles were measured during crushing. The ICA results showed reliable identification of lithium iron phosphate (LFP) from other chemistries. In addition, lithium cobalt oxide (LCO), lithium nickel cobalt aluminum oxide (NCA) and lithium nickel manganese cobalt oxide (NMC) could be identified with various degrees. The identification may suffer if the battery is heavily used, and its state of health is low.

Manganese cobalt oxide-polythiophene composite for asymmetric supercapacitor

In this work, the synthesis of manganese cobalt oxide (MCO) and polythiophene (PTh) composite on Ni-foam is carried out using two step chemical methods. The MCO/PTh films are analyzed by various characterization techniques to study its structural, morphological and electrochemical aspects. The polycrystalline nature of MCO in MCO/PTh composite is confirmed from XRD analysis while presence of various functional groups in MCO/PTh is validated by FT-IR study. Oxidation state of manganese, cobalt and sulfur in the MCO/PTh composite are confirmed from EDAX and XPS analysis. The highest specific surface of the MCO/PTh sample is found about 63.3 m2/g from BET analysis. The deposition of fibrous polythiophene on the MCO nanoflakes is revealed by FE-SEM images while it is further validated by TEM analysis. The electrochemical characterizations of the MCO/PTh composite are carried out by different techniques. The specific capacitance of 1643.08F/g (6386.01 mF/cm2) at 20 mA/cm2 is showed by MCO/PTh electrode at optimized conditions. The electrochemical kinetics of the optimized sample is carried out to understand the charge storage dynamics for the MCO/PTh composite. The capacitance retention of 98 % is exhibited by MCO/PTh electrode after 5000 cycles. Additionally, the aqueous asymmetric supercapacitor, having 1.7 V potential window is tested. The device MCO/PTh//AC exhibited a specific capacitance of 133.47F/g with energy and power density of 53.5 Wh/kg, 13.3 kW/kg at 50 mA/cm2. The obtained results showed that utilization of this synergy of metal oxide with polymer composite can be a potential candidate for supercapacitors.

Enhancing the efficiency of a wavelength-dispersive spectrometer based on a slitless design using a single-bounce monocapillary.

This paper introduces a novel slit-less wavelength-dispersive spectrometer design that incorporates a single-bounce monocapillary with the goal of positioning the sample directly on the Rowland circle, thereby eliminating the need for a traditional entrance slit. This configuration enhances photon throughput while preserving energy resolution, demonstrated in comparative measurements on boron nitride and different lithium nickel manganese cobalt oxide cathodes. A common alternative to an entrance slit for limiting the source size on the Rowland circle is a customized design of the beamline involving a focusing optics unit consisting of two Kirkpatrick-Baez mirrors close to the end station. The new slit-less design does not rely on specialized beamlines and can be considered, thanks to the increased efficiency, for spectrometers using laboratory based sources equipped with equivalent optics. The comparative measurements found that the resolving power achieved was E/ΔE = 1085 at 401.5 eV incident energy, and the enhancement in detection efficiency was a factor of 3.7 due to more effective utilization of the X-ray beam.

Pollutant-free pyrolysis strategy for direct upgrading of cathode materials from spent lithium-ion batteries

The recycling of lithium-ion batteries (LIBs) has been dogged by air pollutants containing fluoride (e.g. HF, PF5, POF3). Pyrolysis is a technique that can eliminate polyvinylidene fluoride (PVDF) from the cathode electrode sheets of spent LIBs, effectively separating the cathode material from the aluminum (Al) foil. Nonetheless, the HF gas generated during pyrolysis not only corrodes equipment but also presents serious environmental risks. To address this, a novel, eco-friendly strategy is introduced for the direct upgrading of cathode active materials (CAM). The strategy's cornerstone involves incorporating a minor amount of calcium into the original cathode material's coating, and it leverages mechanical stirring during the waste battery material separation process to ensure the electrode is fully detached from the current collector at a reduced temperature. The pyrolysis mechanism elucidates that fluorine-containing organic pollutants are converted into metal fluorides and deposited on the surface of cathode particles during aerobic pyrolysis, thereby improving the interfacial stability of lithium nickel cobalt manganese oxide (NCM) materials, reducing transition metal dissolution. This strategy not only eliminates the release of fluorine-containing organic pollutants during pyrolysis but also achieves direct regeneration of CAM. This work underscores the importance of the cathode materials' manufacturing process in facilitating the recycling of spent LIBs and provides an environmentally friendly and economically viable solution for the battery recycling industry.

The Selection of Li-Ion Batteries Used in Electric Vehicles (EV)'s Using the TOPSIS Method

This study focuses on choosing lithium-ion cells for electric vehicles in order to increase its functionality and effectiveness. In the selection process, variables including energy density, longevity, cost, or environmental impact are considered. To determine which battery technology is best for EV applications, many different types of batteries and their properties are examined. The research intends to increase EV performance overall, decrease charging time, and increase driving range. The research advances environmentally friendly transport options and broadens the shift to electric mobility. For decision-makers, producers, and other industry participants, the study offers useful insights. Introduction: Lithium-ion battery selection for electrically powered cars is a crucial choice that has an impact on both the individual vehicle's efficiency and overall performance. The selection of battery technology has a direct impact on variables like Distance, charging time, and longevity because batteries are the main source of power for EVs. Power weight, cycle life, safety, price, and environmental effect are important factors to consider when choosing a battery. To achieve optimal performance, a longer driving range, and customer happiness, these aspects must be in balance. The choice of lithium-ion batteries will have a significant impact on how sustainable transportation develops in the future as the EV industry grows. Research significance: The ability of Li-ion batteries to increase overall performance and dependability as an environmentally friendly transport solution underlies the research significance of choosing them for electric vehicles. Effective battery selection can address major issues with EV adoption by increasing driving range, cutting down on charging time, and improving overall energy efficiency. Additionally, improvements in battery technology help to lessen environmental impacts and carbon emissions. The choice of affordable and dependable battery options is also essential to the commercial viability and general acceptance of EVs. The advancement of technology, innovation, and the shift to a more environmentally friendly transportation system can all be sped up by this kind of research. Method: A multi-criteria decision-making process called TOPSIS (process of Prioritisation through Similarity to Ideal Solution) is used to assess and rank alternatives depending on many factors. To evaluate their relative proximity, options are compared with a superior option and a worse solution. a combination of similarity to the most effective answer and closeness to the worst solution, the approach determines an evaluation of performance for each alternative. The option with the greatest score is regarded as the best option. In difficult decision-making scenarios, TOPSIS offers a methodical method for objectively assessing and ranking alternatives. Alternate parameters: Lithium- Cobalt Oxide Battery (LiCoO2) – LCOB, Lithium-Manganese Oxide Battery (LiMn2O4)- LMOB, Lithium-Nickel Manganese Cobalt Oxide Battery (LiNiMnCoO2)-LNMCOB, Lithium Iron Phosphate Battery (LiFePO4)-LFPB, Lithium-Titanate Battery (Li4Ti5O12) LTOB. Evaluation parameters: Reliability, Safety, Specific power, Specific energy density, Price. Result: Lithium- Cobalt Oxide Battery (LiCoO2) – LCOB is in 5th rank, Lithium-Manganese Oxide Battery (LiMn2O4)- LMOB is in 4th rank, Lithium-Nickel Manganese Cobalt Oxide Battery (LiNiMnCoO2)-LNMCOB is in 3rd rank, Lithium Iron Phosphate Battery (LiFePO4)-LFPB is in 1st rank, Lithium-Titanate Battery (Li4Ti5O12) LTOB is in 2nd rank. Conclusion: the selection of li ion batteries used in electric vehicles (ev)'s Lithium- Cobalt Oxide Battery (LiCoO2) – LCOB is in 5th rank, Lithium-Manganese Oxide Battery (LiMn2O4)- LMOB is in 4th rank, Lithium-Nickel Manganese Cobalt Oxide Battery (LiNiMnCoO2)-LNMCOB is in 3rd rank, Lithium Iron Phosphate Battery (LiFePO4)-LFPB is in 1st rank, Lithium-Titanate Battery (Li4Ti5O12) LTOB is in 2nd rank.

Effect of the field strength on the MAS NMR spectra: Comparative study between diamagnetic and paramagnetic systems

AbstractSolid‐state NMR spectroscopy has gained increasing attention as a probe to investigate structures and dynamics of various solid materials, in particular, materials for rechargeable batteries. Cathodes and anodes for rechargeable batteries contain unpaired electrons (paramagnetic), which generate localized magnetic fields at molecules. Owing to this paramagnetic interaction, it is often complicated to measure and interpret the NMR spectra of the paramagnetic systems. Thus, understanding the effect of the interaction between unpaired electrons and nuclei is important. NMR spectroscopy at higher magnetic fields has been perceived as beneficial since this can provide higher sensitivity and resolution. However, the response to the magnetic field strength varies depending on the nuclei of interest and material properties because various factors affect NMR characteristics. In this work, we performed a systematic study of the effect of the field strength on the magic angle spinning (MAS) NMR characteristics by comparing diamagnetic and paramagnetic systems at two different magnetic fields. As diamagnetic materials, LiCoO2 (LCO) and Li2O are examined. As paramagnetic materials, LiFePO4(LFP) and lithium nickel manganese cobalt oxides (LiNixMnyCo1–x–yO2) with different compositions are investigated. We have demonstrated that higher signal intensity and narrower linewidths can be obtained at higher magnetic fields for diamagnetic systems, whereas higher signal intensity and better resolution are obtained at lower magnetic fields for paramagnetic systems. Our research will provide systematic and experimental evidence about the field strength dependence of paramagnetic systems and rationalized grounds for choosing proper NMR spectrometers for each material.

Airway exposure to lithium nickel manganese cobalt oxide particles induces alterations in lung microenvironment and potential kidney and liver damage in mice.

With the increasing use of lithium-ion batteries, the exposure and health effects of lithium nickel manganate cobalt (NMC), a popular cathode material for the battery, have attracted widespread attention. However, the main absorption routes and target organs of NMC are unknown. This study aims to systematically investigate the main absorption routes and target organs of NMC. Male adult C57BL/6J mice were subjected to acute exposure to NMC particles (Ni: Co: Mn = 5: 3: 2, mass median geometric diameter 9.15 μm) by intragastric administration, transdermal drug delivery, and oropharyngeal aspiration (OPA). The OPA group showed a significant increase in NMC metal levels in organs and blood compared to the other exposure routes. After OPA treatment (0.5 or 2mg, once per day, 3 days), significantly increased metal levels were found in the lung, liver and kidney, but there was no dose-response effect. In the lung, obvious inflammation, and significant elevation of white blood cells, neutrophils and eosinophils in bronchoalveolar lavage fluid were observed, all of which showed a dose-response effect. Reduced urine output and renal tubular cell loss, as well as dysregulated metabolic and immune functions as indicated by the hepatic transcriptome, were observed in NMC-exposed mice. Respiratory exposure is the main exposure route of NMC. Short-term respiratory exposure to NMC results in potential damage to the kidney and liver in addition to severe inflammation in the lung.

High Rate Performance of Single‐Crystalline NCM Upcycled from Spent Lithium‐Ion Batteries Via Direct Recovery and Modification

AbstractThe global expansion of spent lithium‐ion batteries (LIBs) presents both an urgent environmental issue and a significant economic opportunity, driving the development of diverse recycling processes worldwide. Direct regeneration is a promising method for recovering materials from spent LIBs. However, most existing direct regeneration methods focus solely on recovering cathodes without addressing further improvements in their performance. Herein, a direct regeneration method is reported to upcycle single‐crystalline lithium nickel manganese cobalt oxides (NCM) from spent polycrystalline NCM based on a facile phosphoric acid etching approach. Moreover, the Li3PO4 coating and PO43− polyanion doping are simultaneously achieved on the surface of single‐crystal NCM during the upcycling single‐crystalline process. The enlarged lattice spacing and fast ionic conductor coating layer enhance Li+ diffusion and mitigate phase transformations during delithiation/lithiation. Benefiting from the synergistic effect of single crystal structure and surface modification, the upcycled single‐crystalline LiNi0.65Co0.2Mn0.15O2 demonstrates excellent electrochemical performances, including large reversible capacity (≈186 mAh g−1 at 0.1C), high‐rate capability (≈142 mAh g−1 at 10C), and excellent cycling stability (≈99% retention for 100 cycles). This approach provides a novel and effective upcycling pathway to transform the spent LIBs into value‐added cathode materials, achieving a win–win situation for environmental protection and resource conservation.

Effect of the Particle Size Averaging Method on the Predicted Behavior of Lithium-ion Batteries According to the Pseudo-2D Model

Abstract The pseudo-2D (P2D) model is widely utilized in the modeling of lithium-ion batteries for product design and state monitoring applications. The P2D model relies on an average electrode particle size as an input parameter, but existing literature has been inconsistent as to how this is obtained. In this work, we examined the effect of the particle size averaging method on the behavior of Li-ion batteries as predicted by the P2D model. We first set up a standard P2D model that only considers representative sizes and a modified P2D model that accounts for the entire size distribution. Number average, volume-surface average, and D50 particle sizes were then obtained for graphite anodes and lithium iron phosphate and nickel manganese cobalt oxide cathodes typically found in commercial lithium-ion cells. Lastly, the results generated by monodisperse and polydisperse models were compared. It was found that the volume-surface average and D50 sizes accurately predict the energy density and cell capacity with respect to the polydisperse model, while the number average particle size may result in notable discrepancies. For this reason, the number average particle size, or getting a simple average particle size from scanning electron microscopy images, should be avoided.

Improving Energy Storage and Nickel Manganese Cobalt Oxide Cathode Lifetime via a Tannic Acid/Iron (III) Metal Phenolic Network Coating

AbstractSurface coating lithium‐ion battery cathodes is a promising strategy to improve performance and mitigate cathode degradation. The coatings studied to date focus on either electronically or ionically conducting layers, which have been introduced to enhance the redox reactions of cathode particles, or oxide‐based physical protection layers limiting surface degradation. Such coatings require high‐temperature, time‐consuming synthesis processes, along with uncertainty in the specific interactions between these coatings and lithium ions. Here, metal‐phenolic network coated LiNi0.6Mn0.2Co0.2O2 (NMC) cathodes are, produced using naturally occurring polyphenols via a rapid one‐step assembly, improve cathode electrochemical performance. The performance improvement arises from the interaction between lithium ions and the coated layer, which enhances the lithium‐ion transport to the cathode. In half‐cell 1C rate cycling conditions, the modified cathode displays a 20% reduction in overpotential and a 54% decrease in interfacial resistance compared to the uncoated cathode. In a full‐cell format, the modified cathode exhibits a 10% increase in capacity and a 54% increase in lifespan for constant current cycling; in addition to a 5% increase in capacity and a 25% increase in lifespan for constant current‐constant voltage (CCCV) cycling. This work paves the way for improving cathode materials via eco‐friendly lithium‐ion attraction strategies.

Tailoring Binder Molecular Weight to Enhance Slurry‐Cast NMC Cathodes for Sulfide Solid‐State Batteries

We demonstrate for the first time the critical influence of binder molecular weight on the performance of slurry‐cast lithium nickel manganese cobalt oxide (NMC) cathodes in sulfide‐based all‐solid‐state batteries (SSBs). SSBs are increasingly recognized as a safer and potentially more efficient alternative to traditional Li‐ion batteries, owing to the superior ionic conductivities and inherent safety features of sulfide solid electrolytes. However, the integration of high‐voltage NMC cathodes with sheet‐type sulfide solid electrolytes presents significant fabrication challenges. Our findings reveal that higher molecular weight binders not only enhance the discharge capacity and cycle life of these cathodes but also ensure robust adhesion and structural integrity. By optimizing binder molecular weights, we effectively shield the active materials from degradation and mechanical stress, significantly boosting the functionality and longevity of SSBs. These results underscore the paramount importance of binder properties in advancing the practical application of high‐performance all‐solid‐state batteries.

Regulating the Intralayer Cation Disorder in Layered Lithium-Rich Cathodes to Improve Cycle Performance.

The Li/Mn ordered structure of lithium-rich (LR) cathodes leads to the heterogeneous Li2MnO3 and LiTMO2 components, readily triggering structural degeneration and performance degradation in long-term cycling. However, the lack of guiding principles for promoting cation disorder within the transition metal (TM) layers has posed a persistent challenge in designing homogeneous layered LR cathodes. Herein, the (Li + Mn)TM content in the TM layer as a criterion for the design of cation-disordered layered LR cathodes is proposed. The intralayer cation disorder can be achieved by tuning the (Li + Mn)TM content less than 0.5 combined with incorporating the solute ions with suitable ionic radii. For a multicomponent LR nickel cobalt manganese (LRNCM) oxides system, multiscale structural analyses reveal that cation-disordered layered Li1.1(Ni0.6Co0.1Mn0.3)0.9O2 (LR613) exhibits enhanced compositional homogeneity and higher R m symmetry. The developed LR613 cathode undergoes a solid-solution reaction during Li+ deintercalation and mitigates voltage decay during cycling. It is elucidated that intralayer cation disorder effectively alleviates microstrain within the cathode structure and enhances overall structural stability. This comprehensive understanding of the composition-structure-electrochemical behavior relationship inspires the development of durable cation-disordered layered LR cathodes through composition tuning.

Robust degradation of tetracycline hydrochloride by electro-assisted activation of peroxymonosulfate over porous cobalt-manganese oxide nanowire array in situ grown on nickel foam

The electro-assisted activation of peroxymonosulfate (PMS) with transition metals for treating antibiotics in water environment has become a research hotspot. In this work, porous cobalt-manganese oxide nanowire array was successfully in situ fabricated on nickel foam (Co2.5Mn0.5O4/NF), and the degradation efficiency of tetracycline hydrochloride (TC) by PMS activation over Co2.5Mn0.5O4/NF in the presence of an electric field (defined as E-Co2.5Mn0.5O4/NF-PMS) was further studied. The E-Co2.5Mn0.5O4/NF-PMS system showed an unexpectedly high catalytic performance for TC degradation, achieving a removal efficiency of 98.71% in 20min with a rate constant of 0.2092min−1. Thereinto, the electric field ensured a rapid redox cycle of Co(II)/Co(III) and Mn(II)/Mn(III)/Mn(IV), which activated PMS continuously and guaranteed the robustness of TC degradation process. Specifically, the catalytic system exhibited outstanding stability after ten consecutive cycles. Electron paramagnetic resonance (EPR) analysis and quenching experiments illuminated that non-radical pathway involved singlet oxygen (1O2) was dominant in TC oxidation degradation in E-Co2.5Mn0.5O4/NF-PMS system, and furthermore possible degradation routes of TC were revealed. Of note, the degradation system exhibited relatively low level of energy consumption (0.51 kWh m−3 order−1), widespread applicability in treating wastewater contaminated with different organic pollutants, and excellent resistance toward the interference from background anions.

Synthesis of urchin-like MnCo2O4 nanospheres as electrode material for supercapacitors

The morphology of MnCo2O4 has a significant effect on the electrochemical performance. In this paper, urchin-like MnCo2O4 nanospheres was successfully fabricated by a simple hydrothermal process and post-annealing treatment. The effects of addition of surfactant (Hexadecy ltrimethyl ammonium bromide) on the crystal structure, surface morphology and electrochemical performance of MnCo2O4 have been investigated. The results show that all the synthesized manganese cobalt oxides are composed of cubic spinel MnCo2O4. The addition of surfactant leads to the change of the morphology of MnCo2O4 from nanoarray to urchin-like nanospheres and increases the specific surface area, which is beneficial to improve the electrochemical performance of the MnCo2O4 electrode. The electrochemical test reveals that the urchin-like MnCo2O4 nanospheres delivered a high specific capacity of 2019 F/g at a 1 A/g and 1144 F/g at 5 A/g, respectively. The specific capacity of MnCo2O4 electrode reaches 512 F/g at 10 A/g and retains 96 % of the initial capacity after 2000 cycles at 10 A/g, which maintains an extraordinary cycling performance. In addition, an asymmetric supercapacitor (MnCo2O4//AC) with urchin-like MnCo2O4 nanospheres as a cathode and activated carbon (AC) as an anode was also assembled. Impressively, the assembled MnCo2O4//AC asymmetric supercapacitor exhibits a high energy density of 69 Wh/kg at a power density of 793 W/kg. The above research shows that the urchin-like MnCo2O4 nanospheres synthesized by adding surfactants are expected to be excellent high-performance energy storage electrode materials, which provides a new strategy for the synthesis of high-capacity nanoelectrode materials.

Unveiling the Particle-Feature Influence of Lithium Nickel Manganese Cobalt Oxide on the High-Rate performances of Practical Lithium-ion Batteries

The commercialized lithium nickel manganese cobalt oxides have been extensively applied for high-rate lithium-ion batteries due to its collective merits of fast kinetics, high specific capacity, and reasonable cost. The optimization on lithium nickel manganese cobalt oxide particles is crucial for high-rate batteries since the rate capability, storage and cycling stability are highly dependent on the chemical and physical properties of the cathode materials. Herein, the particle-feature influence on the high-rate performances is investigated to unveil the structure-property relationship. Through systematic electrochemical analysis and material characterizations, a direct comparison between commercial lithium nickel manganese cobalt oxide cathode materials with different particle size, doping, and crystalline structures has been performed. It is found that for polycrystalline lithium nickel manganese cobalt oxide materials, appropriate Al and Zr doping and small particle size are beneficial to superior rate performance and cycling stability up to 30C. While single-crystalline particles show outstanding storage properties compared to polycrystalline particles with similar size and ion doping. Morphological and structural evolution of the lithium nickel manganese cobalt oxide particles corresponding to their differentiated electrochemical performances has been revealed including the changed mixing degree of Li+/Ni2+, collapsing of primary particles and different parasitic reactions between the electrolyte and the particle surface. This work can provide direct guidance for the subtle design of efficient cathodes for high-rate lithium-ion batteries.

Resource-efficient artificial intelligence for battery capacity estimation using convolutional FlashAttention fusion networks

Accurate battery capacity estimation is crucial for optimizing lifespan and monitoring health conditions. Deep learning has made notable strides in addressing long-standing issues in the artificial intelligence community. However, large AI models often face challenges such as high computational resource consumption, extended training times, and elevated deployment costs. To address these issues, we developed an efficient end-to-end hybrid fusion neural network model. This model combines FlashAttention-2 with local feature extraction through convolutional neural networks (CNNs), significantly reducing memory usage and computational demands while maintaining precise and efficient health estimation. For practical implementation, the model uses only basic parameters, such as voltage and charge, and employs partial charging data (from 80 % SOC to the upper limit voltage) as features, without requiring complex feature engineering. We evaluated the model using three datasets: 77 lithium iron phosphate (LFP) cells, 16 nickel cobalt aluminum (NCA) cells, and 50 nickel cobalt manganese (NCM) oxide cells. For LFP battery health estimation, the model achieved a root mean square error of 0.109 %, a coefficient of determination of 0.99, and a mean absolute percentage error of 0.096 %. Moreover, the proposed convolutional and flash-attention fusion networks deliver an average inference time of 57 milliseconds for health diagnosis across the full battery life cycle (approximately 1898 cycles per cell). The resource-efficient AI (REAI) model operates at an average of 1.36 billion floating point operations per second (FLOPs), with GPU power consumption of 17W and memory usage of 403 MB. This significantly outperforms the Transformer model with vanilla attention. Furthermore, the multi-fusion model proved to be a powerful tool for evaluating capacity in NCA and NCM cells using transfer learning. The results emphasize its ability to reduce computational complexity, energy consumption, and memory usage, while maintaining high accuracy and robust generalization capabilities.

ALD-Imparted Stability on High-Voltage Cathode Materials for Increased Cycle Life and Energy Density in Lithium-Ion Batteries

High-voltage cathode materials such as lithium cobalt oxide (LCO) and nickel manganese cobalt oxide (NMC) are critical for obtaining high energy densities in lithium-ion batteries (LIBs). Although both materials have been implemented in commercially available consumer electronics, the demand for exceedingly higher cell energy densities requires cathodic stability at increased cell potentials. Cycling LIBs to high potentials (≥ 4.4 V) can accelerate degradation modes at the cathode such electrolyte consumption, material phase transitions, transition metal ion dissolution, and oxygen loss. Material engineering strategies such as transition metal doping/alloying or surface coating are often employed to mitigate these failure pathways, however, many of the methods used to realize these solutions are not feasible at industrial scales while also being time, energy, and cost prohibitive.In this work, we demonstrate how atomic layer deposition (ALD) can be used to stabilize both LCO and single-crystalline NMC materials at high cell potentials in LIBs. Using Forge Nano’s ALD technology, we show how we can deposit thin, homogenous coatings on these cathode materials at industrially relevant scales. Electrochemical testing and differential capacity analysis of cathode half cells at progressively wider voltage windows illustrate that ALD protects and stabilizes the cathode against detrimental side reactions that cause capacity fade and increased internal resistance. Post-cycling SEM-EDX characterization from full cells shows that Co dissolution can be significantly reduced when an ALD coating is deposited on the cathode and that this effect becomes more pronounced at elevated cut off voltages. EIS analysis results demonstrate that ALD protects LCO surfaces from detrimental phase transitions above a 4.5 V upper cut off voltage, suppressing the formation of a spinel layer and shielding the surface from harmful reactions with the electrolyte. Together, these enhancements lead to cycling performances that rival the best performing commercial material investigated in this work, showing that ALD can be a viable and affordable technology for cathode materials enhancement.

Understanding Local Structure-Activity Relation in Lithium-Ion Cathodes with Solid State NMR: Effect of Dopants, Synthesis and Electrochemical Cycling

As the need for research and development efforts to enable alternative, sustainable lithium-ion cathode material is increasing, fine-tuning of the cathode composition and local structure has been focused on the use of dopants/ coatings and varying synthesis conditions such as annealing temperature and time. While changing these parameters has been shown to have significant effect on materials performance, the relation of synthesis parameters with local structure and composition and electrochemical activity is an ongoing focus area1. Solid state NMR is an important characterization technique for LIB systems as 6Li and 7Li solid state NMR can directly “see and follow” the Li cations within the structure, providing crucial information on domain structures, lithium local order changes and metal segregation. A multinuclear NMR approach is also crucial to track the dopants and study how/ if the dopants are diffusing into the bulk or remain on the surface as unintended coatings. This work covers an overview of how multinuclear solid-state NMR can be utilized to understand cathode local structure changes with synthesis, and electrochemical cycling, how dopants play a role in transition metal segregation and cathode interphase, and they affect materials performance. The NMR characterization studies focus on lithium-ion cathodes systems including lithium and manganese rich transitional metal oxide cathodes, lithium nickel oxide and nickel manganese cobalt oxides and are assisted by density functional theory calculations in providing a better understanding of the experimental characterization data and therefore local environments, domain structures and dopant effects.

Investigation of the Impact of Different Electrode Inhomogeneities on the Voltage Response of Li-Ion Batteries

Battery degradation is a fundamental concern in battery research, with the biggest challenge being to maintain performance and safety upon usage. From the microstructure of the materials to the design of the electrodes and their assembly in cells, it is impossible to achieve perfect reproducibility. This is problematic because small manufacturing or local variations could have big repercussions on performance and reliability.In this purely theoretical study, we investigated the potential impact of different inhomogeneities on the performance on two typical Li-ion batteries with a graphite negative electrode and either nickel manganese cobalt oxide 111 or lithium iron phosphate as the positive electrode. Our modeling results showed that out of the nine considered inhomogeneities, only three could affect performance, when at a mild level and randomly distributed, with two unlikely to happen in real cells because they would probably disappear during rest. The only one found to be impactful was inhomogeneities of resistance on the negative electrode. In that case, we predicted an impact on the voltage response that is close to the signature that was attributed to inhomogeneities in the literature. Moreover, such inhomogeneities also open the possibility of a snowball effect as it was shown to induce lithiation inhomogeneities at end of charge when the PE is limiting while the NE in the middle of a well define voltage plateau.Our study showed that it is necessary to assess the level at which the paralleling is occurring, electrode or full cell, as the model predicts an impact on how much current is flowing within or in-between the electrodes.While we are well aware of the limitations of this work, we believe it provides a good starting point for discussion with the community.

Proposal of a Data-Driven Surrogate Models with the Aim to Estimate the Mechanical Degradation of Cathodes in Lithium-Ion Batteries

Battery aging, a complex process crucial to the longevity and effectiveness of lithium-ion batteries, relies on the intricate interplay between electrochemical reactions and structural changes within battery electrodes. An essential element of battery aging involves the deterioration of electrode materials, which occurs due to the mechanical stresses induced during the insertion and extraction of ions within the active material particles.Ion intercalation, which governs the charging and discharging behavior of lithium-ion batteries, creates concentration variations within the active material particles. These variations, affected by transport processes and kinetics, lead to mechanical stresses as ions are spatial confined within the particles. These stresses are a cause of electrode degradation, resulting in particle fractures and the deterioration of electrode integrity.Understanding electrode degradation requires considering phase transitions experienced by common cathode materials like Lithium Nickel Manganese Cobalt Oxide (NMC) or Lithium Iron Phosphate (LFP) during ion intercalation. The transition between lithium-poor and lithium-rich phases, especially in the transition zone, creates significant mechanical stresses due to concentration differences. These stresses often exceed the material's resilience, causing particle fractures and impairing electrode functionality.Despite advances in computational techniques, accurately simulating these complex processes remains challenging due to the computational resources required. This has led researchers to explore innovative methods such as data-driven modeling, including physics-informed neural networks (PINNs). Here the PINN integrate the transport equation into the training algorithm to predict concentration profiles within active material particles, which lead to a improved accuracy of the concentration estimation inside the particle without computational bottlenecks. The proposed PINN possess a novel design, to precisely solve the moving boundary Stefan-Problem of the active material in phase transition.Classical neural networks (ANNs) are also valuable for estimating the electrical potential of active material particles, using results from existingmicrostructural simulations to develop models capturing electrochemical-mechanical interactions within batteries.Furthermore, to understand the extent of particle fracture and its impact on electrode performance, a phase-field-like damage model is integrated into the grey-box model. The governing equations are derived from the stationary point of the potential energy functional of the active particle system.The aim is to establish an operational range resilient to battery aging by systematically studying mechanical stresses and degradation under various operating conditions. This approach, combining experimental data, computational simulations, and theoretical frameworks, promises to advance our understanding of battery aging and drive the development of durable battery technologies