LFP Cells Research Articles

Multipoint Anionic Bridge: Asymmetric Solvation Structure Improves the Stability of Lithium-Ion Batteries.

In this study, a novel concept of multipoint anionic bridge (MAB) is proposed and proved, which utilizes anions with different sites to connect with the asymmetric solvation structure (ASS). Compared to usual solvation structures, this study utilizes the multifunctional groups of difluoro(oxalate)borate anion (ODFB-), which can connect with Li+. By tailoring the concentration, the anion serves as a bridge between different solvated structures. The electrolyte is investigated through in situ techniques and simulations to draw correlations between different solvation structures and reaction pathways. The proposed design demonstrates remarkable high-temperature performance on both the anode and cathode sides, enabling stable cycling of LCO||graphite (0.5 Ah, 1.0 C) pouch cell for over 200 cycles at 80°C and facilitating Li||MCMB and Li||LFP cells to deliver stable performance for 200 cycles at 100°C. This work paves the way for the development of high-performance electrolyte systems by designing and using new multipoint anions to construct ASSs.

Characterization of Lithium-Ion Battery Fire Emissions—Part 2: Particle Size Distributions and Emission Factors

The lithium-ion battery (LIB) thermal runaway (TR) emits a wide size range of particles with diverse chemical compositions. When inhaled, these particles can cause serious adverse health effects. This study measured the size distributions of particles with diameters less than 10 µm released throughout the TR-driven combustion of cylindrical lithium iron phosphate (LFP) and pouch-style lithium cobalt oxide (LCO) LIB cells. The chemical composition of fine particles (PM2.5) and some acidic gases were also characterized from filter samples. The emission factors of particle number and mass as well as chemical components were calculated. Particle number concentrations were dominated by those smaller than 500 nm with geometric number mean diameters below 130 nm. Mass concentrations were also dominated by smaller particles, with PM1 particles making up 81–95% of the measured PM10 mass. A significant amount of organic and elemental carbon, phosphate, and fluoride was released as PM2.5 constituents. The emission factor of gaseous hydrogen fluoride was 10–81 mg/Wh, posing the most immediate danger to human health. The tested LFP cells had higher emission factors of particles and HF than the LCO cells.

An oxygen-defective framework with intensified Lewis acidity reinforcing composite electrolyte for all-solid-state lithium metal batteries

Composite solid electrolytes (CSEs) are considered a key component of all-solid-state lithium metal batteries, regarded as the next generation of energy storage devices with high energy density and long operating life. Numerous studies have shown that the performance of CSEs is closely related to the structure of the fillers and the interactions between fillers and other components, including polymer matrices and lithium salts. To create more abundant interaction sites in CSEs, we designed a nanostructured framework with intensified Lewis acidity (PVDF-HFP/Ov-CeO2) for poly(ethylene) oxide (PEO) electrolyte (denoted as Ov-CeO2-CSE). The mystery concerning the nanostructured framework adsorbs with PEO polymer and dissociates TFSI− and its influence on the electrochemical lithium ions storage performance is meticulously revealed by coupling experimental with theoretical results. Impressively, the prepared Ov-CeO2-CSE shows improved ionic conductivity (1.76 × 10−4 S cm−1 at 30 °C) and a good lithium-ion transference number (0.49). The Li||Ov-CeO2-CSE||Li cell exhibits great cyclability over 3,500 h at a current density of 0.1 mA cm−2 (areal capacity: 0.1 mAh cm−2, 60 °C). Furthermore, the Li||Ov-CeO2-CSE||LFP cell delivers a high specific capacity of 154.6 mAh g−1 at a current density of 0.5 C, stably maintained over 500 cycles. This work provides a potential strategy for designing multifunctional frameworks by efficient interfaces to build advanced all-solid-state lithium metal batteries.

Effect of fast charging on degradation and safety characteristics of lithium-ion batteries with LiFePO4 cathodes

Fast charging compatibility is a desirable feature for batteries to shape a promising future in our rechargeable world. Enabling fast charging of advanced energy-dense Li-ion batteries for growing electric vehicle (EV) markets depends on the breakthrough of material chemistry and optimization of charging strategy. Lithium iron phosphate (LiFePO4, or LFP) is a pivotal cathode material in state-of-the-art EV batteries due to the merits of high thermal stability, long cycle lifetime, and high-temperature performance. However, degradation-safety interactions of LFP-based Li-ion batteries under fast charging conditions and low temperatures remain elusive. In this study, we cycle LFP cells under different fast charging strategies and thermal environments to understand their effects on degradation pathways, where the capacity, voltage, temperature, coulombic inefficiency, internal resistance, and impedance spectroscopy are evaluated. Half-cell studies are implemented to assess electrode-level capacity retentions. Post-mortem analyses are conducted to reveal physicochemical changes in electrodes. Accelerating rate calorimeter tests are carried out to measure evolutions of cell-level thermal instabilities after fast charging tests. This research article highlights the significant roles of graphite-centric lithium plating and LFP-centric transition metal dissolution in driving substantial electrochemical degradations, suggesting that a mild low temperature does not necessarily reduce the LFP cell lifetime.

Highly Tough Slide‐Crosslinked Gel Polymer Electrolyte for Stable Lithium Metal Batteries

AbstractGel polymer electrolytes (GPEs) hold great promise for the practical application of lithium metal batteries. However, conventional GPEs hardly resists lithium dendrites growth and maintains long‐term cycling stability of the battery due to its poor mechanical performance. Inspired by the slide‐ring structure of polyrotaxanes (PRs), herein we developed a dynamic slide‐crosslinked gel polymer electrolyte (SCGPE) with extraordinary stretchability of 970.93 % and mechanical strength of 1.15 MPa, which is helpful to buffer the volume change of electrodes and maintain mechanical integrity of the battery structure during cycling. Notably, the PRs structures can provide fast ion transport channels to obtain high ionic conductivity of 1.73×10−3 S cm−1 at 30 °C. Additionally, the strong polar groups in SCGPE restrict the free movement of anions to achieve high lithium‐ion transference number of 0.71, which is favorable to enhance Li+ transport dynamics and induce uniform Li+ deposition. Benefiting from these features, the constructed Li|SCGPE‐3|LFP cells exhibit ultra‐long and stable cycle life over 1000 cycles and high‐capacity retention (89.6 % after 1000 cycles). Even at a high rate of 16 C, the cells deliver a high capacity of 79.2 mAh g−1. The slide‐crosslinking strategy in this work provides a new perspective on the design of advanced GPEs for LMBs.

Characterization of Lithium-Ion Battery Fire Emissions—Part 1: Chemical Composition of Fine Particles (PM2.5)

Lithium-ion batteries (LIB) pose a safety risk due to their high specific energy density and toxic ingredients. Fire caused by LIB thermal runaway (TR) can be catastrophic within enclosed spaces where emission ventilation or occupant evacuation is challenging or impossible. The fine smoke particles (PM2.5) produced during a fire can deposit in deep parts of the lung and trigger various adverse health effects. This study characterizes the chemical composition of PM2.5 released from TR-driven combustion of cylindrical lithium iron phosphate (LFP) and pouch-style lithium cobalt oxide (LCO) LIB cells. Emissions from cell venting and flaming combustion were measured in real time and captured by filter assemblies for subsequent analyses of organic and elemental carbon (OC and EC), elements, and water-soluble ions. The most abundant PM2.5 constituents were OC, EC, phosphate (PO43−), and fluoride (F−), contributing 7–91%, 0.2–40%, 1–44%, and 0.7–3% to the PM2.5 mass, respectively. While OC was more abundant during cell venting, EC and PO43− were more abundant when flaming combustion occurred. These freshly emitted particles were acidic. Overall, particles from LFP tests had higher OM but lower EC compared to LCO tests, consistent with the higher thermal stability of LFP cells.

The MOFs derived Co, Zn co-doping porous carbon framework as the collector for stable Li metal anodes

The Li metal anode is regarded as the most potential electrode material in the next-generation energy storage system, because of the high energy density and specific capacity. However, the advancement of Li metal anode is restricted by the volume changing and dendrite growth. In this paper, the Co and Zn co-doped porous carbon framework (CF-CZ) derived from MOF structure was designed and produced to realize the dendrite-free Li metal anode. The porous structure could accommodate the deposited Li metal, which relaxes the pressure of electrode structure and relieves the volume changes. Meanwhile, the Co, Zn co-doping effectively improves the lithiophilicity of framework, which attracts Li+ and decreases the nucleation barrier. Besides, numerous micropores of MOF structure could divide the Li+ flux to reduce the local current density for dense sedimentation. With the synergies of co-doping and porous structure, the symmetric cell of CF-CZ shows better electrochemical performance (the overvoltage can be stable at 14 mV after 1200 cycles) than pure Cu foil, and the LFP cells deliver 116.4 mAh g−1 at 1 C after 200 cycles. As a consequence, the CF-CZ possesses the potential to be applied in Li metal anodes.

Accurate Battery Life Prediction Using Early-Cycle Features

Data-driven machine learning (ML) applications on battery prognosis are thriving with compatible accuracy owing to advancements in computing and data storage technologies. Unfortunately, several experimental obstacles including sparse operating conditions and time cost affect the data quality which restricts the ML model generalizability and applicability given the nonlinear degradation pattern for lithium-ion batteries (LIBs). From a broader perspective, multiple electrochemical attributes have not been investigated thoroughly and therefore, we proposed to build an early-cycle lifetime prediction model by exploring the capability of features extracted from the battery’s extrinsic properties (ex: temperature, dis/-charge time) using cycling data taken from only up to the first 10 cycles. A simple linear model is employed and validated on datasets amounting about 200 cells in total with various environmental temperature settings, cycling protocols, and lithium-based cathode chemistries such as lithium - iron phosphate (LFP), nickel cobalt aluminium oxide (LNCA), and nickel manganese cobalt oxide (LNMC) with mean absolute percentage error (MAPE) cycle life prediction less than 17.3%. Integrating the short-listed explored features together with state-of-the-art features on a fast-charging dataset of 124 LFP cells, the model achieved a satisfying 11.8% overall MAPE using data from the first 10 cycles. This work provides an impactful insight into simple feature engineering on early-cycle prediction applications. Details on the methodology, data-standard challenges, and wider applications will be discussed to explore further derivation of potent early-cycle features.

Characterization of Particulate Emissions From Thermal Runaway of Lithium-Ion Cells

Abstract Over the past decade, there has been a significant acceleration in the adoption of lithium-ion (Li-ion) batteries for various applications, ranging from portable electronics to automotive, defense, and aerospace applications. Lithium-ion batteries are the most used energy storage technologies due to their high energy densities and capacities. However, this battery technology is a potential safety hazard under off-nominal conditions, which may result in thermal runaway events. Such events can release toxic gaseous and particulate emissions, posing a severe risk to human health and the environment. Particulate emissions from the failure of two different cell chemistries—lithium iron phosphate (LFP) and nickel manganese cobalt oxide (NMC)—were studied. Experiments were conducted at multiple states of charge (SOC), and three repeats were performed at each SOC for each cell chemistry to examine the repeatability/variability of these events. Particulate emissions were characterized in terms of particulate matter mass (PM2.5), black carbon, and particle number (PN)/size. Failure of a single cell led to a significant release of particulate emissions, with peak emission levels being higher at the higher SOCs. A high level of variability was observed for a specific SOC for LFP cells, while NMCs exhibited relatively less variability. In general, much higher particulate emissions were observed for NMCs compared to LFPs at each SOC. For NMCs at 100% SOC, peak PN levels were ∼2.5 × 10+09 particles/cc (part/cc), and black carbon levels were ∼60 mg/m3. For LFPs at 100% SOC, peak PN levels were ∼9.0 × 10+08 part/cc, and black carbon levels were 2.5 mg/m3.

Testing of NMC and LFP Li-ION cells for surface temperature at various conditions

Battery electric vehicles (BEVs) are being considered as a replacement technology for diesel vehicles in underground mining of mineral resources. However, many issues related to BEVs in industrial applications still require more detailed research. One significant topic is the heat load—BEVs' heat emission into the working environment during regular operation. This paper provides an overview of the thermal behavior of NMC and LFP Li-ion cells tested under various conditions, which is an important step in determining the overall heat load of BEVs. The surface temperature of three NMC and one LFP 18650 Li-ion cells was monitored during charging and discharging at four different rates, at constant ambient temperatures of 30 °C and 40 °C. The main results pertain to the cell's thermal behavior during charging and discharging, highlighting the distinctive temperature profiles of NMC and LFP cells.

The Operation Window of Lithium Iron Phosphate/Graphite Cells Affects their Lifetime

Lithium iron phosphate (LFP) battery cells are ubiquitous in electric vehicles and stationary energy storage because they are cheap and have a long lifetime. This work compares LFP/graphite pouch cells undergoing charge-discharge cycles over five state of charge (SOC) windows (0%–25%, 0%–60%, 0%–80%, 0%–100%, and 75%–100%). Cycling LFP cells across a lower average SOC results in less capacity fade than cycling across a higher average SOC, regardless of depth of discharge. The primary capacity fade mechanism is lithium inventory loss due to: lithiated graphite reactivity with electrolyte, which increases incrementally with SOC, and lithium alkoxide species causing iron dissolution and deposition on the negative electrode at high SOC which further accelerates lithium inventory loss. Our results show that even low voltage LFP systems (3.65 V) have a tradeoff between average SOC and lifetime. Operating LFP cells at lower average SOC can extend their lifetime substantially in both EV and grid storage applications.

Highly Tough Slide-Crosslinked Gel Polymer Electrolyte for Stable Lithium Metal Batteries.

Gel polymer electrolytes (GPEs) hold great promise for the practical application of lithium metal batteries. However, conventional GPEs hardly resists lithium dendrites growth and maintains long-term cycling stability of the battery due to its poor mechanical performance. Inspired by the slide-ring structure of polyrotaxanes (PRs), herein we developed a dynamic slide-crosslinked gel polymer electrolyte (SCGPE) with extraordinary stretchability of 970.93 % and mechanical strength of 1.15 MPa, which is helpful to buffer the volume change of electrodes and maintain mechanical integrity of the battery structure during cycling. Notably, the PRs structures can provide fast ion transport channels to obtain high ionic conductivity of 1.73×10-3 S cm-1 at 30 °C. Additionally, the strong polar groups in SCGPE restrict the free movement of anions to achieve high lithium-ion transference number of 0.71, which is favorable to enhance Li+ transport dynamics and induce uniform Li+ deposition. Benefiting from these features, the constructed Li|SCGPE-3|LFP cells exhibit ultra-long and stable cycle life over 1000 cycles and high-capacity retention (89.6 % after 1000 cycles). Even at a high rate of 16 C, the cells deliver a high capacity of 79.2 mAh g-1. The slide-crosslinking strategy in this work provides a new perspective on the design of advanced GPEs for LMBs.

Control-oriented multiphysics model of a lithium-ion battery for thermal runaway estimation under operational and abuse conditions

This study proposes a control-oriented multiphysics model for lithium-ion batteries (LIBs) that can estimate electrochemical-thermal responses in real time under normal operation and abuse conditions. The proposed model integrates the simplified electrochemical model, the thermal resistance network, and the adaptive time-stepping method to ensure computational efficiency without sacrificing the accuracy. Specifically, the diffusion equation of the electrochemical model is simplified by addressing Padé approximation. The thermal resistance network estimates 3D temperature distribution through simple matrix multiplication to account for the entropic, ohmic, and chemical reaction during thermal runaway. The adaptive time-stepping method further secures accurate yet fast explicit calculation. Quantitative experimental validation reveals the high accuracy and robustness, and fast inference time of the proposed model to estimate the electrochemical-thermal responses with the average inference time of 0.0047 s per step. The application of the proposed model on the 26650 LFP cell also demonstrates the versatility on various shapes and types of LIBs. The systematic analysis on the 3D temperature distribution in the LIB of interest not only confirms the effectiveness of the internal temperature monitoring but also ensures the virtual sensing capability. The versatility of the proposed model underscores both design- and control- enabling solutions for battery thermal management.

Sizing up sustainability: Influence of battery size and cell chemistry on battery-electric trucks’ life-cycle carbon emissions

Customers and legislators will increasingly demand monitoring and reducing the carbon footprint of logistic companies in the coming years. Besides the fundamental decision for a battery-electric truck, the choice of battery size and cell chemistry should be approached with the goal of minimizing the carbon footprint of the supply chain. Therefore, this paper analyzes the impact of battery size and cell chemistry on the carbon footprint and which factors influence this the most. To quantify this footprint, emissions from production, potential replacements based on battery aging, energy generation, and reuse in second-life applications for both LFP and NMC cell chemistries are considered. The results show that use phase emissions from energy generation have the largest leverage on life-cycle emissions, whereas production emissions play a minor role. If electricity with lower emissions at the home depot compared to the public electricity is available, oversizing the battery capacity tends to be the emission optimal choice. If more than 8% additional renewable energy at the home base for NMC and more than 38% for LFP is available, the largest possible battery is emission-optimal. For smaller shares, the smallest possible battery should be selected. Significant dependence on purchase year and share of second-life usage can be observed.

A Comparatively Low Cost, Easy-To-Fabricate, and Environmentally Friendly PVDF/Garnet Composite Solid Electrolyte for Use in Lithium Metal Cells Paired with Lithium Iron Phosphate and Silicon.

Solid electrolytes may be the answer to overcome many obstacles in developing the next generation of renewable batteries. A novel composite solid electrolyte (CSE) composed of a poly(vinylidene fluoride) (PVDF) base with an active nanofiber filler of aluminum-doped garnet Li ceramic, Li salt lithium bis-(trifluoromethanesulfonyl)imide (LiTFSI), Li fluoride (LiF) stabilizing additive, and plasticizer sulfolane was fabricated. In a Li|CSE|LFP cell with this CSE, a high capacity of 168 mAh g-1 with a retention of 98% after 200 cycles was obtained, representing the best performance to date of a solid electrolyte with a PVDF base and a garnet inorganic filler. In a Li metal cell with Si and Li, it yielded a discharge capacity of 2867 mAh g-1 and was cycled 60 times at a current density of 100 mAh g-1, a significant step forward in utilizing a solid electrolyte of any kind with the desirable Si anode. In producing this CSE, the components and fabrication process were chosen to have a lower cost and improved safety and environmental impact compared with the current state-of-the-art Li-ion battery.

Long-Term Stable Cycling of Dendrite-Free Lithium Metal Batteries Using ZIF-90@PP Composite Separator.

Lithium metal batteries (LMBs) are anticipated to meet the demand for high energy density, but the growth of lithium dendrites seriously hinders its practical application. Herein, we constructed a kind of composite separator (ZIF-90@PP) consisting of zeolite imidazole framework-90 (ZIF-90) and polypropylene (PP) to promote the uniform deposition of Li+ and inhibit the growth of lithium dendrites. The aldehyde groups interacting with TFSI- and the nitrogen-containing negative groups attracting Li+ of ZIF-90 can facilitate the dissociation of LiTFSI to release more Li+, thus alleviating the influence of space charge near the electrode surface and accelerating the transfer of Li+. Not only does the excellent electrolyte wettability of ZIF-90 enhance the electrolyte retention capacity of the separator, but the orderly nano-channels in ZIF-90 also restrict the free migration of anions and homogenize the distribution of Li+. Consequently, the functional separator achieves a long-term stable Li plating/stripping cycling for over 780 h at 2 mA cm-2. Moreover, an impressive average coulombic efficiency of 98.67% at 0.5 C after 300 cycles is realized by Li || LFP full cells based on ZIF-90@PP with a capacity retention rate of 71.22%. The high-rate and long cycling performance of the modified Li || LFP cells further demonstrates the advantages of the ZIF-90@PP composite separator.

Catalytic Growth of Ionic Conductive Lithium Nitride Nanowire Array for Dendrite‐Free Lithium Metal Anode

AbstractThe development of an artificial solid‐electrolyte interphase (SEI) has been recognized as the most efficient strategy to overcome the safety concerns associated with the lithium metal anode (LMA). Inorganic‐rich SEIs on the LMA are crucial for suppressing Li dendrites. Among the prevalent SEI inorganic compounds observed for LMA, lithium nitride (Li3N) is often found in the SEIs of high‐performance LMA. Herein, the Li3N nanowire array is successfully synthesized and the catalytic base‐growth mechanism is thoroughly investigated. The fast ionic conductor Li3N nanowires act as pillars to control the nucleation and growth of lithium metal along the vertical direction of the nanowire by bottom‐up self‐lubrication, which fundamentally prevents the dendrite growth. The Li3N is characterized by abundant lithiophilic nucleation sites, which effectively reduces the local current density, and facilitates homogeneous Li+ flux. Symmetric cells utilizing the Li3N@Li anode have demonstrated excellent stability, featuring uniform deposition without dendrite formation. Additionally, high‐capacity retentions of 98% at 0.5 C after 400 cycles and impressive high‐rate performance at 31.1 mA cm−2 have been realized in high‐loading Li3N@Li||LFP cells. The universal preparation of the Li3N nanowires with various precursors and substrates is further explored, which is expected to be applied in solid‐state batteries and hydrogen storage.

Branch-Chain-Rich Diisopropyl Ether with Steric Hindrance Facilitates Stable Cycling of Lithium Batteries at - 20°C.

Li metal batteries (LMBs) offer significant potential as high energy density alternatives; nevertheless, their performance is hindered by the slow desolvation process of electrolytes, particularly at low temperatures (LT), leading to low coulombic efficiency and limited cycle stability. Thus, it is essential to optimize the solvation structure thereby achieving a rapid desolvation process in LMBs at LT. Herein, we introduce branch chain-rich diisopropyl ether (DIPE) into a 2.5M Li bis(fluorosulfonyl)imide dipropyl ether (DPE) electrolyte as a co-solvent for high-performance LMBs at - 20°C. The incorporation of DIPE not only enhances the disorder within the electrolyte, but also induces a steric hindrance effect form DIPE's branch chain, excluding other solvent molecules from Li+ solvation sheath. Both of these factors contribute to the weak interactions between Li+ and solvent molecules, effectively reducing the desolvation energy of the electrolyte. Consequently, Li (50μm)||LFP (mass loading ~ 10mgcm-2) cells in DPE/DIPE based electrolyte demonstrate stable performance over 650 cycles at - 20°C, delivering 87.2 mAh g-1, and over 255 cycles at 25°C with 124.8 mAh g-1. DIPE broadens the electrolyte design from molecular structure considerations, offering a promising avenue for highly stable LMBs at LT.

Prediction of thermal runaway for a lithium-ion battery through multiphysics-informed DeepONet with virtual data

A surrogate model that predicts thermal runaway (TR) of lithium-ion batteries (LIBs) fast and accurately is essential, yet complex phenomena of TR present significant challenges to achieving adequate performance in both aspects, particularly as traditional finite element models (FEMs) incur significant time and cost. This study proposes a multiphysics-informed deep operator network (MPI-DeepONet) with encoders to address these issues. This proposed neural network aims to predict TR under various thermal abuse conditions, offering a fast and accurate TR prediction surrogate model. In this study, MPI-DeepONet with encoders is trained with virtual data from a multiphysics FEM to overcome the scarcity of actual TR data. The architecture of DeepONet solves interpolation and extrapolation problems, allowing predictions across multiple thermal abuse conditions once trained. The neural network is further enhanced by the supervision of energy balance and chemical reaction equations, ensuring accurate and robust predictions despite limited data by effectively capturing the complex phenomena of TR. Quantitative analysis, compared against actual experiments and ablation studies, confirms the effectiveness of the proposed neural network. Notably, MPI-DeepONet achieves a mean RMSE of 13.2 °C for temperature predictions in the test set, significantly outperforming the 25.4 °C RMSE of purely data-driven DeepONet. This improvement highlights the importance of integrating multiphysics constraints into the neural network. The generality of the proposed neural network is further evidenced by accurate TR prediction in both LFP and NMC cells. The features deployed on the proposed neural network enable real-time quantification of internal temperature distribution and dimensionless concentration of the key components in LIBs, which are challenging to measure directly, achieving speeds at least 10,000 times faster than FEM. The proposed neural network provides comprehensive information for advanced battery management systems to ensure safety and reliability in LIBs, accelerating the digital twin of electric transportation systems through artificial intelligence transformation.

Towards Routine 7Li In Situ Solid-State NMR Studies of Electrochemical Processes in Li|LiPF6|LFP Cells

AbstractIn this study, electrochemical processes in a Li|LiPF6|LFP cell have been explored applying advanced solid-state NMR technologies. In situ solid-state NMR allows to monitor structural changes in local environments in commercially available cell components during galvanostatic cycling. In collaboration with Dragonfly Energy, ePROBE GmbH and Bruker BioSpin GmbH & Co. KG, we have demonstrated an experimental procedure for routine application of in situ solid-state NMR for battery research. This points out the high potential of this approach for use in the energy storage industry.