SEARCH · Search NASA
Results for “battery materials”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Long-life lithium-ion batteries realized by low-Ni, Co-free cathode chemistry
The increasing demand for lithium-ion battery-powered electric vehicles (EVs) has led to a surge in recent prices of strategic battery materials such as cobalt (Co) and nickel (Ni). While all EV makers are eager to eliminate Co usage, Ni has rapidly become another ‘pain point’ for the industry, as its price is nearing half that of Co. The sustainability issue facing both Ni and Co puts forward a grand materials challenge, that is, to reduce Ni content and eliminate Co while maintaining high specific energy and stability. Here in this work, a complex concentrated doping strategy is used to eliminate Co in a commercial NMC-532 cathode. The LiNi 0.5 Mn 0.43 Ti 0.02 Mg 0.02 Nb 0.01 Mo 0.02 O 2 cathode shows potential cost advantage with relatively high specific energy and significantly improved overall performance (~95% capacity retained after 1,000 cycles in pouch-type cells, 2.8–4.3 V vs graphite, at 1 C, 1.5 mA cm -2 ). Combining X-ray techniques and electron microscopy, we uncover the origins of the superior stability.
Thermochemistry of cation disordered Li ion battery cathode materials, (M′ = Nb and Ta, M′′ = Mn and Fe)
Enthalpies of formation from oxides (Δ H f,ox ) of novel disordered Li 1+x Ta x Fe 1−2x O 2 and reported (M′′ = Mn 3+ and Fe 3+ ).
Role of crystallographic orientation in atom probe analysis of Li-ion battery cathode materials
Using air-stable lithium cobalt oxide (LCO) as a prototypical system, we elucidate the role of crystallographic orientation and anisotropic transport in atom probe tomography (APT) for lithium transition metal oxide (LTMO) cathode materials.
Report from: US Muon Workshop 2021: A Road Map for a Future Muon Facility February 1-2, 2021
The workshop titled “US Muon Workshop 2021: A road map for a future Muon Facility” was held virtually on February 1-2, 2021. The workshop aimed to bring together world experts in muon spectroscopy (µSR) and other techniques along with interested stakeholders to evaluate the scientific need to construct a new µSR facility in the United States (US). The more than 200 participants highlighted several key scientific areas for µSR research, including quantum materials, hydrogen chemistry, and battery materials, and how each area could benefit from a new, high flux pulsed muon source. Experts also discussed aspects of the µSR technique, such as low-energy µSR, novel software developments, and beam and detector technologies that could enable revolutionary advances in µSR at a next-generation facility. The workshop concluded with discussion of a concept being developed for a new µSR facility at the Spallation Neutron Source (SNS) of Oak Ridge National Laboratory (ORNL). That novel design concept was first envisioned by many of the same µSR experts at a workshop held previously at ORNL in 2016. The participants expressed that the current design had the potential to be a world-leading µSR facility, and strongly encouraged the principal investigators to continue their work in order to refine the concept and determine instrument parameters that would enable new scientific opportunities
Operando study of mechanical integrity of high-volume expansion Li-ion battery anode materials coated by Al 2 O 3
Group IV elements and their oxides, such as Si, Ge, Sn and SiO have much higher theoretical capacity than commercial graphite anode. However, these materials undergo large volume change during cycling, resulting in severe structural degradation and capacity fading. Al 2 O 3 coating is considered an approach to improve the mechanical stability of high-capacity anode materials. To understand the effect of Al 2 O 3 coating directly, we monitored the morphology change of coated/uncoated Sn particles during cycling using operando focused ion beam–scanning electron microscopy. Here, the results indicate that the Al 2 O 3 coating provides local protection and reduces crack formation at the early stage of volume expansion. The 3 nm Al 2 O 3 coating layer provides better protection than the 10 and 30 nm coating layer. Nevertheless, the Al 2 O 3 coating is unable to prevent the pulverization at the later stage of cycling because of large volume expansion.
US Muon Workshop 2021: A road map for a future Muon Facility
The workshop title “US Muon Workshop 2021: A road map for a future Muon Facility” was held virtually on February 1-2, 2021. The workshop aimed to bring together world experts in muon spectroscopy (µSR) and other techniques along with interested stakeholders to evaluate the scientific need to construct a new µSR facility in the United States (US). The more than 200 participants highlighted several key scientific areas for µSR research, including quantum materials, hydrogen chemistry, and battery materials, and how each area could benefit from a new, high flux pulsed muon source. Experts also discussed aspects of the µSR technique, such as low-energy µSR, novel software developments, alongside beam and detector technologies, that could enable revolutionary advances in µSR at a next-generation facility. The workshop concluded with discussion of a concept being developed for a new µSR facility at the Spallation Neutron Source (SNS) of Oak Ridge National Laboratory (ORNL). That novel design concept was first envisioned by many of the same µSR experts at a workshop held previously at ORNL in 2016. The participants expressed that the current design had the potential to be a world-leading µSR facility, and strongly encouraged the principal investigators to continue their work in order to refine the concept and determine instrument parameters that would enable new scientific opportunities.
Lithium Ion Cathode Materials Prepared Using Glycerol as Solvent and Reactant
Two different types of cathode materials were prepared using glycerol as a solvent and reactant. The LiMn1/3Ni1/3Co1/3O2 layered oxide cathode material was successfully synthesized with a shorter time of heat treatment of 8hr at 900°C. An appreciated capacity retention of 83.7% after 100 cycles with an initial discharge capacity of 177.1 mAh/g at 0.1C (discharge rate) has been achieved. Another cathode material with the formula of Li1.2 Mn0.51Ni0.145+xCo0.145-xO2 (x=0 (LR2), 0.0725 (LR1)), as a Li-rich cathode material, has been also successfully synthesized using glycerol. It was shown that LR1 discharge capacity was increased from 185 to 213 mAh/g after 20 cycles and ended up with 194.9 mAh/g after 60 cycles at 0.1C (discharge rate). This material shows an exceptional discharge capacity retention, lower toxic cobalt component, and lower production cost comparing with other Li-rich cathode materials. Detailed results of powder material synthesis, characterization, and battery testing will be presented to demonstrate that glycerol as a green solvent in the synthesis of battery materials.
Identifying Variability in Differential Scanning Calorimetry for Materials-Level Battery Safety
Explore the source record for details and available documents.
Ultra-Fast Calcination of Lithium Ion Battery Cathode Materials
Explore the source record for details and available documents.
Phosphorus-carbon composites as battery anode materials
An electrochemical device includes an anode containing a phosphorus-carbon composite including a conductive carbon matrix and nano-sized phosphorus particles, wherein the nano-sized phosphorus particles are uniformly dispersed on the surface and/or pores of the carbon matrix.
Gas-mediated defect engineering in earth-abundant Mn-rich layered oxides for non-aqueous sodium-based batteries
Gases are often by-products of battery materials during cell formation and degradation, affecting the cycle life and safety of rechargeable batteries. However, understanding gas-mediated (electro)-chemical reactions and nanoscale structural transformations during the synthesis of battery electrode materials remains challenging because of the lack of suitable characterization routes and the complexity of the interplay between thermodynamics and kinetics. Here, in this study, we use operando synchrotron X-ray diffraction, in situ transmission X-ray microscopy and multiscale modelling to elucidate the reaction pathways and microstructural defect development of earth-abundant Mn-rich layered oxides as positive electrode materials for sodium-based batteries. In particular, we demonstrate the dominant role of CO 2 over O 2 and H 2 O (g) in modulating the competition between entropy and enthalpy during solid-state synthesis. Using Ni 0.25 Mn 0.75 CO 3 as a model precursor, we reveal that CO 2 generation favours the formation of entropy-driven metastable intermediates, suppresses closed pore/nanovoids formation and decreases chemical heterogeneity and residual lattice strain of Mn-rich layered oxides during the synthesis. This result motivates a fast-sintering strategy to promote CO 2 release, which ultimately leads to improved chemo-mechanical and electrochemical stability of the Mn-rich positive electrodes when tested in non-aqueous Na metal coin cells.
Polymers in Lithium‐Ion and Lithium Metal Batteries
Abstract Lithium‐ion batteries play a significant role in modern electronics and electric vehicles. However, current Li‐ion battery chemistries are unable to satisfy the increasingly heightened expectations regarding energy demand and reliability. To boost the overall energy density while ensuring the safety of Li batteries, researchers have focused on alternative battery materials, such as silicon, sulfur, and Li metal. These represent promising avenues, although numerous obstacles (e.g., Si cracking, polysulfide shuttling, Li dendrites, etc.) must be tackled before batteries based on these materials can enter mass production and penetrate the mainstream market. Polymers are a class of materials that are widely used in current battery systems; however, many novel polymer chemistries may offer better performance and reliability than the current ones, and even overcome the issues of the above‐mentioned new battery materials. In this review, selected polymeric materials for solving these issues are categorized into four parts: polymer electrolytes, polymer artificial solid‐electrolyte interphases, binders, and separators. Both the current progress and the characterization methods are included. Potential future directions of energy materials research are pointed out as well.
Deep learning of experimental electrochemistry for battery cathodes across diverse compositions
Artificial intelligence (AI) has emerged as a tool for discovering and optimizing novel battery materials. However, the adoption of AI in battery cathode representation and discovery is still limited due to the complexity of optimizing multiple performance properties and the scarcity of high-fidelity data. Here, we present a machine learning model (DRXNet) for battery informatics and demonstrate the application in the discovery and optimization of disordered rocksalt (DRX) cathode materials. We have compiled the electrochemistry data of DRX cathodes over the past 5 years, resulting in a dataset of more than 19,000 discharge voltage profiles on diverse chemistries spanning 14 different metal species. Learning from this extensive dataset, our DRXNet model can capture critical features in the cycling curves of DRX cathodes under various conditions. Our approach offers a data-driven solution to facilitate the rapid identification of novel cathode materials, accelerating the development of next-generation batteries for carbon neutralization.
Prediction of Li 3 Fe 8 B 8 compound with rapid one-dimensional ion diffusion channels
Using a computational crystal structure search in the Li-Fe-B ternary system, we predict a stable phase of Li 3 Fe 8 B 8 , featuring 1D channels that enable rapid Li-ion transport. Ab initio molecular dynamics simulations show that the Li-ion diffusion coefficient in Li 3 Fe 8 B 8 surpasses that of common electrode and conductive additive materials by several orders of magnitude. The high diffusion in Li 3 Fe 8 B 8 can be explained by the Frenkel–Kontorova model, which describes an incommensurate state between the Li diffusion chain and the periodic potential field caused by the FeB backbone structure. The favorable lithium-ion diffusivity and mechanical properties of Li 3 Fe 8 B 8 make it a promising conductive additive for battery materials. Furthermore, an external magnetic field can further manipulate the properties of this material due to its predicted itinerant ferromagnetism, which also offers a platform for exploring spin-dependent phenomena.
Artifact identification in X-ray diffraction data using machine learning methods
In situ synchrotron high-energy X-ray powder diffraction (XRD) is highly utilized by researchers to analyze the crystallographic structures of materials in functional devices ( e.g. battery materials) or in complex sample environments ( e.g. diamond anvil cells or syntheses reactors). An atomic structure of a material can be identified by its diffraction pattern along with a detailed analysis of the Rietveld refinement which yields rich information on the structure and the material, such as crystallite size, microstrain and defects. For in situ experiments, a series of XRD images is usually collected on the same sample under different conditions ( e.g. adiabatic conditions) yielding different states of matter, or is simply collected continuously as a function of time to track the change of a sample during a chemical or physical process. In situ experiments are usually performed with area detectors and collect images composed of diffraction patterns. For an ideal powder, the diffraction pattern should be a series of concentric Debye–Scherrer rings with evenly distributed intensities in each ring. For a realistic sample, one may observe different characteristics other than the typical ring pattern, such as textures or preferred orientations and single-crystal diffraction spots. Textures or preferred orientations usually have several parts of a ring that are more intense than the rest, whereas single-crystal diffraction spots are localized intense spots owing to diffraction of large crystals, typically >10 µm. In this work, an investigation of machine learning methods is presented for fast and reliable identification and separation of the single-crystal diffraction spots in XRD images. The exclusion of artifacts during an XRD image integration process allows a precise analysis of the powder diffraction rings of interest. When it is trained with small subsets of highly diverse datasets, the gradient boosting method can consistently produce high-accuracy results. The method dramatically decreases the amount of time spent identifying and separating single-crystal diffraction spots in comparison with the conventional method.