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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Theory of Cation Solvation in the Helmholtz Layer of Li-Ion Battery Electrolytes

The solvation environments of Li + in conventional nonaqueous battery electrolytes, such as LiPF 6 in mixtures of ethylene carbaronate (EC) and ethyl methyl carbonate (EMC), are often used to rationalize transport properties and solid electrolyte interphase (SEI) formation. Solvation environments in the compact electrical double layer (EDL) next to the electrode, also known as the Helmholtz layer, determine (partially) what species can react to form the SEI, with bulk solvation environments often being used as a proxy. Here, we develop and test a theory of cation solvation in the Helmholtz layer of nonaqueous Li-ion battery electrolytes. First, we validate the theory against bulk and diffuse EDL atomistic molecular dynamics (MD) simulations of LiPF 6 EC/EMC mixtures as a function of surface charge, where we find the theory can qualitatively capture the solvation environments. Next, we turn to the Helmholtz layer, where we find the main effect of the solvation structures next to the electrode is an apparent reduction in the number of binding sites between Li + and the solvents, again where we find reasonable agreement with our developed theory. Finally, by solving a simplified version of the theory, we find that the probability of Li + binding to each solvent remains equal to the bulk probability, suggesting that the bulk solvation environments are a reasonable place to start when understanding battery electrolytes. Our developed formalism can be parametrized from bulk MD simulations and used to predict the solvation environments in the Helmholtz layer through reducing the number of available coordination sites, which can be used to determine what could react and form the SEI.

Helmholtz↗
DOE OSTI2022

Oxidation of glucose to glycolic acid using oxygen and pyrolyzed spent Li-ion battery electrode material as catalyst

A search for non-noble catalysts for biomass processing led to the discovery that pyrolyzed electrode coating of spent Li-ion batteries can be used as an excellent catalyst for oxidation of D-glucose to glycolic acid. New no/low-cost catalyst was prepared by pyrolyzing black electrode coatings of 18,650 Li-ion cells from a spent DELL 1525 laptop battery at 600 ºC. Catalyst was characterized using SEM, EDX and X-ray and was shown to contain lithium nickel manganese cobalt oxide (Li a Ni b Mn c Co d O e ) on carbon with Ni: Mn: Co 4.12: 2.10: 1.50. Here, the catalytic activity of this material was evaluated for oxidation of D-glucose in aq. NaOH and water; glycolic, tartaric, malic, succinic and 2-hydroxybutaric acid were identified as key degradation products. The highest glycolic acid yield of 94% was obtained for oxidation of D-glucose under 3.4 Atm. oxygen, 120 °C, 2.0 h in 0.5 M aq. NaOH using 10 g catalyst/mol glucose.

25 ENERGY STORAGE↗
DOE OSTI2024

Entropy-Stabilized Multication Fluorides as a Conversion-Type Cathode for Li-Ion Batteries–Impact of Element Selection

Metal fluorides (e.g., FeF 2 and FeF 3 ) have received attention as conversion-type cathode materials for Li-ion batteries due to their higher theoretical capacity compared to that of common intercalation materials. However, their practical use has been hindered by low round-trip efficiency, voltage hysteresis, and capacity fading. Cation substitution has been proposed to address these challenges, and recent advancements in battery performance involve the introduction of entropy stabilization in an attempt to facilitate reversible conversion reactions by increasing configurational entropy. Building on this concept, high entropy fluorides with five cations were synthesized by using a simple mechanochemical route. In order to examine the impact of element selection, Co 0.2 Cu 0.2 Ni 0.2 Zn 0.2 Fe 0.2 F 2 (HEF-Fe) was compared with Co 0.2 Cu 0.2 Ni 0.2 Zn 0.2 Mg 0.2 F 2 (HEF-Mg), replacing electrochemically inactive Mg with Fe as an active participant in the conversion reaction. Combining electrochemical measurements with first-principles calculations, high-resolution electron microscopy, and synchrotron X-ray analysis, HEFs’ battery performances and conversion reaction mechanisms were investigated in detail. The results highlighted that replacement of Mg with Fe was beneficial, with enhanced capacity, rate capability, and surface stability. In addition, it was found that HEF-Fe showed similar cycle stability without an electrochemically inactive element. In conclusion, these findings provide valuable insights for the design of high entropy multielement fluorides for improved Li-ion battery performance.

25 ENERGY STORAGE↗
DOE OSTI2026

Long cycle and calendar life of Si-based Li-ion batteries enabled by localized high-concentration electrolytes and their surprising water tolerance

Silicon-based anodes promise an increase in energy density for Li-ion batteries, yet they suffer from a poor calendar life. Researchers have posited that fluorinated lithium salt forms reactive side products that destroy the solid electrolyte interphase (SEI), even without cycling. HF is one such reactive side product formed from trace water contamination in the electrolyte. Some electrolytes, such as localized high concentration electrolytes (LHCEs) may improve cell stability in highly reactive systems, such as Li metal and Si. In the present study, LHCEs containing 200-300 ppm of water retained up to 8% greater capacity (1200-1300 mAh/g Si) in calendar life tests over 200 days compared to dried electrolytes (< 20 ppm water). Calendar aging took place at 100% state of charge. Cells with 200-300 ppm water performed comparably to cells with 20 ppm water in cycle life tests (900-1000 mAh/g Si) . Even adding 1000 ppm water did not lead to rapid capacity fade in cells undergoing cycle life tests. Nano-FTIR spectroscopy revealed chemical and structural differences in the SEI for cells with 1000 ppm water compared to 200-300 ppm water. The SEI differences, including increased Li2O concentration, may have contributed to improved calendar life. This research reveals the capabilities of LHCEs to improve the calendar and cycle life of Si-based Li-ion batteries, despite the presence of a highly reactive contaminant.

25 ENERGY STORAGE↗
DOE OSTI2020

Autonomous Strategies for Improved Performance and Reliability of Li‐Ion Batteries

Abstract The battery community has devoted significant effort to improve the performance and reliability of Li‐ion batteries through the development of new materials. The integration of autonomous function provides an alternative strategy to further extend performance. Autonomous material systems mimic the ability of biological systems to self‐protect, sense, regulate, and heal in response to damage and other environmental changes. When incorporated in batteries, these materials enable autonomic restoration of battery performance upon degradation, as well as autonomic shutdown or extinguishment in response to thermal runaway. Successful strategies for improving Li‐ion battery performance include controlled release of microencapsulated functional additives and the integration of self‐healing or adaptive interlayers and binders. These methods have been effective for stabilizing the solid electrolyte interface, preventing battery fires, restoring electrode conductivity, and suppressing Li dendrite growth. Challenges and opportunities exist in the further application of autonomous strategies in the battery environment. A greater variety of encapsulated additives with precise triggered‐release are needed to address specific battery degradation mechanisms. Incorporation of self‐healing polymers in solid‐state batteries facilitates improvement in interfacial and mechanical stability. The integration of autonomous strategies with battery management systems potentially enables enhanced control over multiple battery cycling parameters.

Zhao, Lihong↗
DOE OSTI2020

Heat of Mixing During Fast Charge/Discharge of a Li-Ion Cell: A Study on NMC523 Cathode

Predicting temperature rise accurately during fast charge/discharge of a Li-ion cell is essential to avoid thermal runaway and extend battery life. While modeling the temperature rise, it is necessary to model the heat generation correctly. Heat of mixing, one of the four main sources of heat generation in a Li-ion battery, has often been considered insignificant and therefore excluded from modeling. When included, it is modeled using the expression from a Taylor expansion approximation. In this work, we have shown the conditions when including the heat of mixing becomes important and quantified the error associated with using the Taylor expansion, especially under high charge/discharge conditions. Consequently, we carry out the calculation of the rate of enthalpy change and the heat generation rate from the most fundamental equation for the rate of the total enthalpy change without simplifying assumptions or approximations. The heat generation rate calculated doing so naturally includes irreversible, reversible and mixing heat. We then exclusively separate out the heat of mixing by subtracting the rate of enthalpy change by reaction from the rate of the total enthalpy change. Results show that the contribution of heat of mixing in the total heat generated increases with the charge/discharge rate and is as large as 23% for a 6 C discharge. This result suggests that while modeling heat generation for fast charge/discharge, it is necessary to include the heat of mixing and avoid calculating it using the Taylor expansion approximation.

25 ENERGY STORAGE↗
DOE OSTI2023

Constructing “Li-rich Ni-rich” oxide cathodes for high-energy-density Li-ion batteries

The current exploration of high-energy-density cathode materials for Li-ion batteries is mainly concentrated on either so-called “Li-rich” or “Ni-rich” oxides. However, both are suffering from formidable practical challenges. Here, we combine these two concepts to obtain “Li-rich Ni-rich” oxides in pursuit of more practical high-energy-density cathodes. As a proof of concept, we synthesized an array of Li 1+y Ni( 3-5y)/3 Mo 2y/3 O 2 oxides, whose structures were identified to be the coexistence of LiNiO 2 -rich and Li 4 MoO 5 -rich domains with the aid of XRD, TEM, and NMR techniques. Such an intergrowth structure of 5–20 nm size enables excellent mechanical and structural reversibility for the layered rock-salt LiNiO 2 -rich domain upon cycling thanks to the robust cubic rock-salt Li 4 MoO 5 -rich domain enabling an “epitaxial stabilization” effect. As a result, we achieved high capacities (>220 mA h g -1 ) with Ni contents as low as 80%; the Li 1.09 Ni 0.85 Mo 0.06 O 2 member (y = 0.09) shows much improved cycling performances (91% capacity retention for 100 cycles at C/10) compared with pure LiNiO 2 . Further, this work validates the feasibility of constructing Li-rich Ni-rich compounds in the form of intergrowing domains and hence unlocks vast possibilities for future cathode design.

25 ENERGY STORAGE↗
DOE OSTI2021

Prospects for Employing Lithium Copper Phosphates as High-Voltage Li-Ion Cathodes

Three compositions of lithium copper phosphates: Li 2 CuPO 4 , Li 2 Cu 5 (PO 4 ) 4 , and Li 2 CuP 2 O 7 have been studied as potential high-voltage cathode materials for Li-ion batteries, following computational predictions of high operating voltages. An assisted-microwave preparation of Li 2 CuPO 4 , which is otherwise difficult to prepare in nearly pure form, has been developed. The electrochemical performance of all three compounds has been investigated. Additionally, the cyclability of these materials is found to be poor due to structural changes, irreversible reduction to metallic copper at potentials as high as 2.5 V, and the possibility of dissolution into the electrolyte. Some general understanding in regard to the use of Cu compounds in redox electrodes is presented.

25 ENERGY STORAGE↗
DOE OSTI2024

Predicting Li-ion Battery Performance for Impurity-doped NMC Cathodes Using Deep Learning

With the electric vehicle (EV) market expansion and the energy sector's shift towards electrification, the demand for battery metals, including lithium (Li), cobalt (Co), and nickel (Ni), is set to surpass supply. A critical knowledge gap exists in the purity standards for battery precursors and the impact of impurities on battery performance. Addressing this, our study employs a Deep Machine Learning (DL) based multi-objective optimization approach to interpret the relationship between metal impurities in domestic battery resources and their effects on battery performance. We analyze experimental data from Li-ion batteries with NMC (Nickel-Manganese-Cobalt oxide) cathodes over 1000 cycles, representing approximately ~6-8 months of operation, to establish a baseline of performance without impurities. Leveraging this data, we develop a Physics-Informed Deep Learning (PIDL) framework to extend our findings to cases that include metal impurities (e.g., Fe, Cu, Al) ranging from (0.001 - 0.01) %, respectively. By incorporating physics-based features, our PIDL model can accurately estimate the performance of NMC cathodes doped with various metal impurities to provide rapid design decisions. This research paves the way for informed decisions in Li-ion battery material design and optimization, ensuring the sustainable growth of the EV market and the broader energy sector.

25 ENERGY STORAGE↗
DOE OSTI2021

Quantitative Measurement of Li-Ion Concentration and Diffusivity in Solid-State Electrolyte

Here, we present a quantitative method to measure the concentration and diffusivity of Li ion in a solid-state electrolyte with nanoscale depth resolution. We designed a standard sample with different depths of trenches and used time-of-flight secondary ion mass spectroscopy, inductively coupled plasma optical emission spectroscopy, three-dimensional (3D) optical microscopy, and electrochemical strain microscopy to obtain effective Li-ion concentration and the corresponding diffusivity as a function of depth. As a result, we verified the dependence of electromechanical strain induced by ionic oscillation on mobile-ion concentration. We also showed the diffusivity change as a function of effective concentration and discussed the difference in diffusivity near the surface and inside the bulk. Our method can be widely used for electromechanical strain in various ionic conductors, rendering our technique universal for quantitative analysis of ionic dynamics at a multiscale.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Li-Ion Battery Electrode Contact Resistance Estimation by Mechanical Peel Test

Li-ion battery electrode electronic properties, including bulk conductivity and contact resistance, are critical parameters affecting cell performance and fast-charge capability. Contact resistance between the coating and current collector is often the largest electronic resistance in an electrode and is affected by chemical, microstructural, and interfacial variations. Direct measurements of contact resistance and bulk conductivity have proven to be challenging. In their absence, a mechanical electrode peel test is often used to compare adhesion and electrical contact resistance. However, using a micro-flexible-surface probe, contact resistance can be directly determined. Here, this work compares contact resistance and mechanical peel strength of multiple commercial-grade HE5050 and NCM523 cathodes and graphite and silicon anodes. It was found that peel strength correlates well with contact resistance in a carefully curated data set (p < 0.05) and in some situations may be a good metric to estimate electrical properties. However, there were distinct outliers in the data set, indicating that peel strength may not accurately reflect electrical properties when there is significant variation in electrode composition. These results illustrate the value of the micro-flexible-surface probe in quantifying contact resistance and bulk conductivity to better understand how battery composition and processing steps affect microstructure and resulting cell performance.

25 ENERGY STORAGE↗
DOE OSTI2023

Sustainable Li-ion anode material from Fe-catalyzed graphitization of paper waste

We report a novel method for the conversion of paper towel waste to biographite anode material is developed and optimized for use in Li-ion batteries. The surge in demand for Li-ion battery anode materials coupled with the unsustainable and inefficient methods of producing battery-grade graphite necessitate alternative carbon feedstocks and graphitization technologies. Paper waste (PW) is identified as a suitable carbon feedstock for iron-catalyzed graphitization due to its sustainability, low cost, low ash content, and ample supply for the intended end use. A Box Behnken experimental design for statistical optimization is pursued for untreated and pre-carbonized PW with factors of temperature (1100-1300 °C), hold time (1-5 h), and iron catalyst loading (0.5-1.5x fixed carbon content) with biographite crystal size as the primary response variable. Temperature and iron catalyst loading are found to be significant factors, whereas hold time is found to be insignificant. Reversible capacities of the biographite anodes are found to be 340-355 mAh g-1 with 99% capacity retention over 100 cycles, indicating good electrochemical performance relative to commercial graphite anodes. The initial Coulombic efficiency of untreated and pre-carbonized biographites, however, are 77% and 75%, respectively, suggesting parasitic reactions including electrolyte decomposition.

25 ENERGY STORAGE↗
DOE OSTI2020

Fully Exploited Oxygen Redox Reaction by the Inter-Diffused Cations in Co-Free Li-Rich Materials for High Performance Li-Ion Batteries

To meet the growing demand for global electrical energy storage, high-energy-density electrode materials are required for Li-ion batteries. To overcome the limit of the theoretical energy density in conventional electrode materials based solely on the transition metal redox reaction, the oxygen redox reaction in electrode materials has become an essential component because it can further increase the energy density by providing additional available electrons. However, the increase in the contribution of the oxygen redox reaction in a material is still limited due to the lack of understanding its controlled parameters. Here, it is first proposed that Li-transition metals (TMs) inter-diffusion between the phases in Li-rich materials can be a key parameter for controlling the oxygen redox reaction in Li-rich materials. The resulting Li-rich materials can achieve fully exploited oxygen redox reaction and thereby can deliver the highest reversible capacity leading to the highest energy density, ≈1100 Wh kg -1 among Co-free Li-rich materials. The strategy of controlling Li/transition metals (TMs) inter-diffusion between the phases in Li-rich materials will provide feasible way for further achieving high-energy-density electrode materials via enhancing the oxygen redox reaction for high-performance Li-ion batteries.

25 ENERGY STORAGE↗
DOE OSTI2022

3D LiMn 2 O 4 nThin Film Deposited by ALD: A Road toward High-Capacity Electrode for 3D Li-Ion Microbatteries

Miniaturized electronics suffer from a lack of energy autonomy. In that context, the fabrication of lithium-ion solid-state microbatteries with high performance is mandatory for powering the next generation of portable electronic devices. Here, the fabrication of a thin film positive electrode for 3D Li-ion microbatteries made by the atomic layer deposition (ALD) method and in situ lithiation step is demonstrated. The 3D electrodes based on spinel LiMn 2 O 4 films operate at high working potential (4.1 V vs Li/Li + ) and are capable of delivering a remarkable surface capacity (approximate to 180 mu Ah cm -2 ) at low C-rate while maintaining more than 40 mu Ah cm -2 at C/2 (time constant = 2 h). Both the thickness of the electrode material and the 3D gain of the template are carefully tuned to maximize the electrode performance. Further, advanced characterization techniques such as transmission electron and X-ray transmission microscopies are proposed as perfect tools to study the conformality of the deposited films and the interfaces between each layer: no interdiffusion or segregation are observed. This work represents a major issue towards the fabrication of 3D-lithiated electrode by ALD-without any prelithiation step by electrochemical technique-making it an attractive solution for the fabrication of 3D Li-ion solid-state microbatteries with semiconductor processing methods.

3D Li-ion micro-batteries↗
DOE OSTI2022

MatPhase: Material phase prediction for Li-ion Battery Reconstruction using Hierarchical Curriculum Learning

Li-ion Batteries (LIB), one of the most efficient energy storage devices, are used extensively in many industrial applications. These batteries consist of electrodes that are put together with heterogeneous material compositions. Imaging data of these battery electrodes obtained from X-ray tomography can explain the distribution of material constituents and allow reconstructions to study electron transport pathways. Such reconstructions of material constituents help quantify various associated properties of electrodes (e.g., volume-specific surface area, porosity) which determine the performance of batteries. These images often suffer from low image contrast between multiple material constituents, hence making it difficult for humans to distinguish and characterize these constituents through visual inspection. A minor error in detecting distributions of the material constituents can lead to magnified errors in the calculated parameters of material properties (e.g., porosity). We present MatPhase, a novel hierarchical curriculum learning technique to address the complex task of estimating material constituent distribution in battery electrodes. MatPhase comprises three modules: (i) an uncertainty-aware global model trained to yield inferences conditioned upon global knowledge of material distribution, (ii) a local model to capture relatively more fine-grained (local) distributional signals, (iii) an aggregator model to appropriately fuse the local and global effects towards obtaining the final distribution. On average, MatPhase improves prediction up to 8.5% relative to other sophisticated modeling pipelines and state-of-the-arts (SOTA) object detection models employed in the performance comparison.

Tabassum, Anika↗
DOE OSTI2023

Dynamic Monkey Bar Mechanism of Superionic Li‐ion Transport in LiTaCl 6

Abstract The LiTaCl 6 solid electrolyte has the lowest activation energy of ionic conduction at ambient conditions (0.165 eV), with a record high ionic conductivity for a ternary compound (11 mS cm −1 ). However, the mechanism has been unclear. We train machine‐learning force fields (MLFF) on ab initio molecular dynamics (AIMD) data on‐the‐fly and perform MLFF MD simulations of AIMD quality up to the nanosecond scale at the experimental temperatures, which allows us to predict accurate activation energy for Li‐ion diffusion (at 0.164 eV). Detailed analyses of trajectories and vibrational density of states show that the large‐amplitude vibrations of Cl − ions in TaCl 6 − enable the fast Li‐ion transport by allowing dynamic breaking and reforming of Li−Cl bonds across the space in between the TaCl 6 − octahedra. We term this process the dynamic‐monkey‐bar mechanism of superionic Li + transport which could aid the development of new solid electrolytes for all‐solid‐state lithium batteries.

Lei, Ming↗
DOE OSTI2022

Meshfree Methods for Modeling Chemo-Mechanical Cathode Cracking in Li-Ion Batteries

Through repeated charging and discharging, the electrodes of a Li-ion battery experience cyclic loading causing swelling and contraction due to the movement of lithium, also known as intercalation. This research focuses specifically on the chemo-mechanical cracking in the cathode. Because cathode particles are comprised of many randomly-oriented grains, which have highly anisotropic material properties, the expansion and contraction is very non-uniform. As a result, stress concentrations tend to form between grains, which necessitates the modeling of crack propagation largely along grain boundaries. Chemo-mechanical models are simulated mainly by two methods: the cohesive zone model (CZM) and the continuous damage model (CDM). The CZM is more accurate at capturing the sharp discontinuities of a crack but is very computationally expensive and intractable for large-scale models as a result. Conversely, the CDM is easily computed but not well-suited to easily allow for discontinuous field variables, which are inherent across a crack. This study aims to improve the CDM's ability to capture discontinuous cracks. Current versions of the CDM use the finite element method (FEM), which is one of the most widely used approaches for spatial discretization. This research investigates the use of the Reproducing Kernel Particle Method (RKPM), a meshfree method, for spatial discretization and aims to achieve a chemo-mechanical crack propagation model that achieves both intermediate accuracy and computational time between a CDM and CZM. To gain a better understanding of how the meshfree model compares to the current FEM model in capturing cathode crack propagation, further investigation is needed.

cathode cracking↗
DOE OSTI2021

In Situ Measurement of Temperature Distributions in a Li-ion Cell during Internal Short Circuit and Thermal Runaway

Here we report in situ measurement of temperature distributions in a 2.5-Ah pouch format Li-ion cell during internal short circuit (ISC) and thermal runaway. The ISC and thermal runaway were triggered by nail penetration. The local temperatures were measured by embedded K type micro thermocouples in the middle layer of the experimental Li-ion cell. Highly non-uniform temperature distributions were observed during ISC and thermal runaway as compared with those during constant current discharging and external short circuit. The in situ measurement also captured details of how thermal runaway started from the ISC location and spread to the entire cell in a few seconds. Moreover, the comparison between ISC without thermal runaway and ISC with thermal runaway suggests that internal short circuit resistance plays a critical role in the risk of thermal runaway.

Huang, Shan↗