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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Accurate Prediction of Voltage of Battery Electrode Materials Using Attention-Based Graph Neural Networks

Performing first-principles calculations to discover electrodes’ properties in the large chemical space is a challenging task. While machine learning (ML) has been applied to effectively accelerate those discoveries, most of the applied methods ignore the materials’ spatial information and only use predefined features: based only on chemical compositions. Here, we propose two attention-based graph convolutional neural network techniques to learn the average voltage of electrodes. Our proposed methods, which combine both atomic composition and atomic coordinates in 3D-space, improve the accuracy in voltage prediction significantly when compared to composition-based ML models. The first model directly learns the chemical reaction of electrodes and metal ions to predict their average voltage, whereas the second model combines electrodes’ ML predicted formation energy (E form ) to compute their average voltage. Our E form -based model demonstrates improved accuracy in transferability from our subset of learned Li ions to Na ions. Moreover, we predicted the theoretical voltage of 10 Na x MPO 4 F (M = Ti, Cr, Fe, Cu, Mn, Co, and Ni) fluorophosphate battery frameworks, which are unavailable in the Material Project database. It could be shown that we can expect average voltages higher than 3.1 V from those Na battery frameworks except from the NaTiPO 4 F and TiPO 4 F pair of electrodes, which offer an average voltage of 1.32 V.

25 ENERGY STORAGE↗
DOE OSTI2020

A mechanistic study of mesoporous TiO 2 nanoparticle negative electrode materials with varying crystallinity for lithium ion batteries

Nanoscale oxide-based negative electrodes are of great interest for lithium ion batteries due to their high energy density, power density and enhanced safety. In this work, we conducted a case study on mesoporous TiO 2 nanoparticle negative electrodes with uniform size and varying crystallinity in order to investigate the trend in the electrochemical properties of oxide-based nanoscale negative electrodes with varying crystallinity. Furthermore, mesoporous solid spherical TiO 2 nanoparticles with a uniform particle size and varying crystallinity, i.e. , amorphous TiO 2 (A-TiO 2 ), partially crystalline TiO 2 (PC-TiO 2 ) and fully crystalline TiO 2 (FC-TiO 2 ) nanoparticles were studied. At low current rate (quasi steady-state), the specific capacity of the samples drops with the decrease of crystallinity. Ex situ synchrotron pair distribution function analysis reveals that the 1D zigzag Li ion diffusion pathway becomes expanded with the increase of crystallinity, which promotes ion mobility and charge storage. At high current rates (away from equilibrium states), however, the A-TiO 2 sample demonstrates slightly larger capacity than the FC-TiO 2 sample, both of which show larger capacities than that of the PC-TiO 2 sample. Both A-TiO 2 and FC-TiO 2 samples exhibit higher capacitive contribution to the charge storage and larger Li + diffusivity than those of the PC-TiO 2 sample, which explains their better rate capability. Moreover, the larger Li + diffusivity of the A-TiO 2 sample leads to the slightly larger specific capacity than the FC-TiO 2 sample at the highest current rate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2012

Evaluation of Niobium as Candidate Electrode Material for DC High Voltage Photoelectron Guns

The field emission characteristics of niobium electrodes were compared to those of stainless steel electrodes using a DC high voltage field emission test apparatus. A total of eight electrodes were evaluated: two 304 stainless steel electrodes polished to mirror-like finish with diamond grit and six niobium electrodes (two single-crystal, two large-grain, and two fine-grain) that were chemically polished using a buffered-chemical acid solution. Upon the first application of high voltage, the best large-grain and single-crystal niobium electrodes performed better than the best stainless steel electrodes, exhibiting less field emission at comparable voltage and field strength. In all cases, field emission from electrodes (stainless steel and/or niobium) could be significantly reduced and sometimes completely eliminated, by introducing krypton gas into the vacuum chamber while the electrode was biased at high voltage. Of all the electrodes tested, a large-grain niobium electrode performed the best, exhibiting no measurable field emission (< 10 pA) at 225 kV with 20 mm cathode/anode gap, corresponding to a field strength of 18:7 MV/m.

BastaniNejad, M.↗
DOE OSTI2024

Process Optimization of Carbon Electrode Materials Manufacturing by Experimental Study and Machine Learning Techniques

Electrospun carbon fibers from coal have been investigated as electrodes for batteries and supercapacitors. Despite the excellent properties of coal-derived carbon fibers (CCNF) for energy storage devices, there still lacks systematic understanding on how various process parameters affect final electrode performances, which poses challenges to scale from pilot to high volume manufacturing. The goals of this project are twofold. First, we focuse on process optimization for converting a new precursor from powder river basin (PRB) coal, referred to as coal-based polyurethane (CPU) to CCNF using electrospinning. Second, different machine learning techniques will be examined using experimental data from this work and open literature. Specifically, for CPU the following process parameters need to be characterized and optimized in order to produce CCNFs with desirable mechanical integrity and physiochemical properties: precursor composition and viscosity, operating voltage and distance, oxidation and carbonization temperature and duration. Consequently, physiochemical properties of the fibers were characterized to correlate these process parameters with desirable electrochemical performance. Given the complex nature of the fiber production process, ML models are assessed for their ability to capture the nonlinear relationship between process parameters and the electrochemical properties in applications including supercapacitors. As such, we applied various machine learning techniques, to determine which technique produces a model that best predicts device function.

Cincotta, Robert E.F.↗
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 OSTI2021

Machine Learning Screening of Metal-Ion Battery Electrode Materials

Here, in this work we present deep neural network regression machine learning models (ML) for predicting the average voltage and the percentage change in volume of battery electrodes upon charging and discharging with metal ions. Our models exhibit good performance as measured by the average mean absolute error obtained from a 10-fold cross-validation as well as on independent test sets. We further assess the robustness our ML models by investigating their screening potential beyond the training database. We produce novel Na-ion electrodes by systematically replacing Li-ions in the original database by Na-ions, and then selecting a set of 22 electrodes that exhibit a good performance in energy density as well as small volume variations upon charging and discharging, as predicted by the machine learning model. The ML predictions for these new materials are then compared to quantum-mechanics based calculations. Our results reaffirm the significant role of machine learning techniques in the exploration of materials for battery applications.

,electrode volume change↗
NASA NTRS2005

Nickel-Tin Electrode Materials for Nonaqueous Li-Ion Cells

Experimental materials made from mixtures of nickel and tin powders have shown promise for use as the negative electrodes of rechargeable lithium-ion electrochemical power cells. During charging (or discharging) of a lithium-ion cell, lithium ions are absorbed into (or desorbed from, respectively) the negative electrode, typically through an intercalation or alloying process. The negative electrodes (for this purpose, designated as anodes) in state-of-the-art Li-ion cells are made of graphite, in which intercalation occurs. Alternatively, the anodes can be made from metals, in which alloying can occur. For reasons having to do with the electrochemical potential of intercalated lithium, metallic anode materials (especially materials containing tin) are regarded as safer than graphite ones; in addition, such metallic anode materials have been investigated in the hope of obtaining reversible charge/discharge capacities greater than those of graphite anodes. However, until now, each of the tin-containing metallic anode formulations tested has been found to be inadequate in some respect.

Ehrlich, Grant M.↗
DOE OSTI2022

Additive manufacturing of LiNi 1/3 Mn 1/3 Co 1/3 O 2 battery electrode material via vat photopolymerization precursor approach

Additive manufacturing, also called 3D printing, has the potential to enable the development of flexible, wearable and customizable batteries of any shape, maximizing energy storage while also reducing dead-weight and volume. In this work, for the first time, three-dimensional complex electrode structures of high-energy density LiNi 1/3 Mn 1/3 Co 1/3 O 2 (NMC 111) material are developed by means of a vat photopolymerization (VPP) process combined with an innovative precursor approach. This innovative approach involves the solubilization of metal precursor salts into a UV-photopolymerizable resin, so that detrimental light scattering and increased viscosity are minimized, followed by the in-situ synthesis of NMC 111 during thermal post-processing of the printed item. The absence of solid particles within the initial resin allows the production of smaller printed features that are crucial for 3D battery design. The formulation of the UV-photopolymerizable composite resin and 3D printing of complex structures, followed by an optimization of the thermal post-processing yielding NMC 111 is thoroughly described in this study. Based on these results, this work addresses one of the key aspects for 3D printed batteries via a precursor approach: the need for a compromise between electrochemical and mechanical performance in order to obtain fully functional 3D printed electrodes. In addition, it discusses the gaps that limit the multi-material 3D printing of batteries via the VPP process.

25 ENERGY STORAGE↗
DOE OSTI2023

Improving charge transport in integrated MoO 3 /C electrode materials for water-in-salt energy storage systems by incorporating oxygen vacancies

Improvements in the charge storage properties of α-MoO 3 used as an electrode with a 30m ZnCl 2 water-in-salt electrolyte have been achieved by enhancements in electron and ion transport enabled by an inventive synthesis route. Electron transport was improved through the integration of MoO 3 with dopamine-derived carbon via a chemical preintercalation route, and enhanced ion transport was achieved by incorporating oxygen vacancies in MoO 3 structure through ethanol 2 reduction under hydrothermal conditions. Here, the presence of carbon was confirmed by corresponding D and G bands observed in Raman spectroscopy measurements. The presence of oxygen vacancies was proven through correlated XPS, TGA, Raman spectroscopy and XRD analyses, with the introduction of oxygen vacancies leading to an expanded interlayer region. Four-point probe measurements provided evidence of increased electronic conductivity due to the incorporation of carbon, and cyclic voltammetry-based charge storage mechanism analyses revealed increases in ion transport kinetics due to oxygen vacancy formation. Tuning the oxygen vacancy concentration is critical, as excessive concentrations of these point defects leads to structural instability and poor capacity retention. This work demonstrates the combined potential of carbon and oxygen vacancies in moderate concentrations to enhance the charge storage properties of transition metal oxides. The strategies developed in this study offer a path to the development of promising materials for high-rate, high-capacity, and long-duration electrochemical energy storage technologies.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
NASA NTRS1985

Influence of the temperature of electrode material on its disintegration under the action of an arc discharge in hydrogen

An analysis is made of the electrophysical processes occurring at the end surface of rod electrodes during constant and alternating arc discharge in hydrogen. Experiments are reported on the effect of surface temperature of tungsten electrodes on their erosion. The influence of activating additions of thorium oxide, the structure of the tungsten, and the gas surrounding the electrode on the specific thermal loading and the erosion of the electrodes is discussed.

Bolotov, A. V.↗
DOE OSTI2025

Unraveling the origin of air-stability in single-crystalline layered oxide positive electrode materials

Single-crystalline Ni-rich layered oxides present compelling advantages over conventional polycrystalline counterparts toward large-scale applications, including enhanced mechanical stability and higher energy density. Nevertheless, the deleterious effects of air exposure, which is inevitable in industrial processing, on their structure and electrochemical performance remain poorly understood. Herein, we reveal that air exposure is more detrimental to the electrochemical performance of single-crystalline layered oxide positive electrodes than polycrystalline counterparts. It is found that air-induced surface structural distortions are primarily responsible for the electrochemical performance decay of single-crystalline samples rather than the generally believed surface residual lithium. Leveraging multiscale diffraction and imaging techniques, we identify an undesirable structural transition to a metastable O1* phase, which introduces substantial lattice defects and localized strain concentrations within the layered structure. These adverse structural evolutions compromise structural integrity and promote crack initiation during electrochemical cycling, ultimately accelerating capacity fade. Our findings provide critical insights into the air-induced degradation mechanisms and emphasize the urgent need for developing effective stabilization strategies to facilitate the commercial implementation of single-crystalline Ni-rich positive electrodes.

36 MATERIALS SCIENCE↗