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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Effect of Welding Processes on the Microstructure, Mechanical Properties and Residual Stresses of Plain 9Cr-1Mo Steel Weld Joints

9Cr-1Mo steel designated as P9 is widely used in the construction of power plants and high-temperature applications. It is chosen for fabricating hexcan fuel subassembly wrapper components of fast breeder reactors. Arc welding processes are generally used for fabricating 9Cr-1Mo steel weld joints. A-TIG welding process is increasingly being adopted by the industries. In the present study, shielded metal arc (SMA), tungsten inert gas (TIG) and A-TIG welding processes are used for fabricating the 9Cr-1Mo steel weld joints of 10 mm thickness. Effect of the above welding processes on the microstructure evolution, mechanical properties and residual stresses of the weld joints has been studied in detail. All the three weld joints exhibited comparable strength and ductility values. 9Cr-1Mo steel weld joint fabricated by SMAW process exhibited lower impact toughness values caused by coarser grain size and inclusions. 9Cr-1Mo steel weld joint fabricated by TIG welding exhibited higher toughness due to finer grain size, while the weld joint fabricated by A-TIG welding process exhibited adequate toughness values. SMA steel weld joint exhibited compressive residual stresses in the weld metal and HAZ, while TIG and A-TIG weld joint exhibited tensile residual stresses in the weld metal and HAZ.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Processing Parameter Effects on Residual Stress and Mechanical Properties of Selective Laser Melted Ti6Al4V

Selective laser melting (SLM) process is characterized by large temperature gradients resulting in high levels of residual stress within the additively manufactured metallic structure. SLM-processed Ti6Al4V yields a martensitic microstructure due to the rapid solidification and results in a ductility generally lower than a hot working equivalent. Post-process heat treatments can be applied to SLM components to remove in-built residual stress and improve ductility. Residual stress buildup and the mechanical properties of SLM parts can be controlled by varying the SLM process parameters. This investigation studies the effect of layer thickness on residual stress and mechanical properties of SLM Ti6Al4V parts. This is the first-of-its kind study on the effect of varying power and exposure in conjunction with keeping the energy density constant on residual stress and mechanical properties of SLM Ti6Al4V components. It was found that decreasing power and increasing exposure for the same energy density lowered the residual stress and improved the % elongation of SLM Ti6Al4V parts. Increasing layer thickness resulted in lowering the residual stress at the detriment of mechanical properties. The study is based on detailed experimental analysis along with finite element simulation of the process using ABAQUS to understand the underlying physics of the process.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Techno-Economic Analysis of Magnesium Extraction from Seawater via a Catalyzed Organo-Metathetical Process

Magnesium (Mg) has many useful applications especially in various Mg alloys which can decrease weight while increasing strength. To increase the affordability and minimize environment consequence, a novel catalyzed organo-metathetical (COMET) process was proposed to extract Mg from seawater aiming to achieve significant reduction in total energy and production cost comparing with the melting salt electrolysis method currently adopted by US Mg LLC. A process flowsheet for a reference COMET process was set-up using Aspen Plus which included five key steps, anhydrous MgCl2 production, transmetallation, dibutyl Mg decomposition, n-BuLi regeneration, and LiCL electrolysis. The energy and production cost and CO2 emission were estimated based on the Aspen modeling using Aspen economic analyzer. Our results showed that it is possible to produce Mg from seawater with a production cost of $2.0/kg-Mg while consuming about 35.3 kWh/kg-Mg and releasing 7.0 kg CO2/kg-Mg. A simplified US Mg manufacturing process was also generated using Aspen and the cost and emission results were estimated for comparison purpose. Under our simulation conditions, the reference COMET process maintain a comparable CO2 emission rate and can save about 40% in production cost and save about 15% energy compared to the simplified US Mg process.

Liu, Jian (ORCID:0000000153297408)↗
DOE OSTI2025

Mechanical Characteristics of Additively Manufactured ODS 316L and 316H Alloys with and Without Post-build Processing

This research aims to explore an accelerated development path for oxide dispersion-strengthened (ODS) alloys by integrating additive manufacturing (AM) technologies with recent advances in ODS materials and traditional manufacturing methods. Novel AM and post-build processing routes have been developed for ODS austenitic alloys, specifically Fe-Cr-Ni alloys like 316L and 316H. Electron microscopy and mechanical characterizations were conducted to evaluate the effects of process variables on microstructure and properties, aiming for an economically feasible route property optimization. Traditionally, ODS alloy production involves multi-day high-energy mechanical milling of alloy powder with yttria (Y 2 O 3 ) followed by powder consolidation via extrusion or other methods and additional thermomechanical processing (TMP) for property control. Here, to address these challenges associated with this complex and costly approach, we propose exploring alternative, cost-effective processing routes focusing on AM and traditional TMP methods. The new ODS alloy processing routes have achieved up to a 400% increase in yield strength and a 60% increase in ultimate tensile strength compared to wrought stainless steels while still maintaining significant ductility and fracture toughness. This paper details the novel and economical AM-based processing routes for ODS austenitic alloys, combined with post-build TMPs, and discusses the mechanical and microstructural characteristics of the developed materials.

Byun, Thak Sang [Oak Ridge National Laboratory (OR↗
DOE OSTI2025

Utilization of Hemp Processing Waste for 3D Printing of Biocomposites

Unlike stem biomass, the residues after the extraction of cannabidiol (CBD) oil from hemp flower are challenging to utilize because of their high extractive content (~ 40%, mainly lipids) and are typically considered waste and landfilled. This study presented a novel approach to effectively valorize this underutilized hemp processing waste via chemical processing for three-dimensional (3D) printing applications. Hemp processing waste was processed with sodium hydroxide (NaOH) to control extractives for solving nozzle clogging and then applied as a biofiller in polylactic acid (PLA) composites to improve the mechanical strength. The novelty of this work lies in demonstrating that controlled extractive removal via NaOH treatment not only improves processability but also enhances mechanical performance in 3D-printed biocomposites. We systematically investigated the effect of the processed biofiller content (2.5–10 wt%) on the mechanical and thermal properties of the biocomposites. The decrease in the content of extractives reduced the non-structural components and improved the surface compatibility of the hemp waste with the PLA matrix, thereby enhancing the polymer-biofiller interactions. The best performance was achieved at 2.5 wt% loading, where Young’s modulus increased from 2.3 GPa to 2.6 GPa and tensile strength from 42.7 MPa to 48.8 MPa. Interestingly, the complete removal of extractives also reduced the mechanical strength of their biocomposites, indicating the interfacial adhesion effects of extractives. Furthermore, this study provides new insights into balancing extractive content for optimal mechanical properties, offering a sustainable solution for waste valorization in additive manufacturing.

Additive manufacturing↗
DOE OSTI2017

Process-Structure Linkages Using a Data Science Approach: Application to Simulated Additive Manufacturing Data

A novel data science workflow is developed and demonstrated to extract process-structure linkages (i.e., reduced-order model) for microstructure evolution problems when the final microstructure depends on (simulation or experimental) processing parameters. Our workflow consists of four main steps: data pre-processing, microstructure quantification, dimensionality reduction, and extraction/validation of process-structure linkages. These methods that can be employed within each step vary based on the type and amount of available data. In this paper, this data-driven workflow is applied to a set of synthetic additive manufacturing microstructures obtained using the Potts-kinetic Monte Carlo (kMC) approach. Additive manufacturing techniques inherently produce complex microstructures that can vary significantly with processing conditions. Using the developed workflow, a low-dimensional data-driven model was established to correlate process parameters with the predicted final microstructure. In addition, the modular workflows developed and presented in this work facilitate easy dissemination and curation by the broader community.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Parameters, Properties, and Process: Conditional Neural Generation of Realistic SEM Imagery Toward ML-Assisted Advanced Manufacturing

Abstract The research and development cycle of advanced manufacturing processes traditionally requires a large investment of time and resources. Experiments can be expensive and are hence conducted on relatively small scales. This poses problems for typically data-hungry machine learning tools which could otherwise expedite the development cycle. We build upon prior work by applying conditional generative adversarial networks (GANs) to scanning electron microscope (SEM) imagery from an emerging advanced manufacturing process, shear-assisted processing and extrusion (ShAPE). We generate realistic images conditioned on temper and either experimental parameters or material properties. In doing so, we are able to integrate machine learning into the development cycle, by allowing a user to immediately visualize the microstructure that would arise from particular process parameters or properties. This work forms a technical backbone for a fundamentally new approach for understanding manufacturing processes in the absence of first-principle models. By characterizing microstructure from a topological perspective, we are able to evaluate our models’ ability to capture the breadth and diversity of experimental scanning electron microscope (SEM) samples. Our method is successful in capturing the visual and general microstructural features arising from the considered process, with analysis highlighting directions to further improve the topological realism of our synthetic imagery.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Image Processing Pipeline for Fluoroelastomer Crystallite Detection in Atomic Force Microscopy Images

Phase transformations in materials systems can be tracked using atomic force microscopy (AFM), enabling the examination of surface properties and macroscale morphologies. In situ measurements investigating phase transformations generate large datasets of time-lapse image sequences. The interpretation of the resulting image sequences, guided by domain-knowledge, requires manual image processing using handcrafted masks. Here this approach is time-consuming and restricts the number of images that can be processed. Her in this study, we developed an automated image processing pipeline which integrates image detection and segmentation methods. We examine five time-series AFM videos of various fluoroelastomer phase transformations. The number of image sequences per video ranges from a hundred to a thousand image sequences. The resulting image processing pipeline aims to automatically classify and analyze images to enable batch processing. Using this pipeline, the growth of each individual fluoroelastomer crystallite can be tracked through time. We incorporated statistical analysis into the pipeline to investigate trends in phase transformations between different fluoroelastomer batches. Understanding these phase transformations is crucial, as it can provide valuable insights into manufacturing processes, improve product quality, and possibly lead to the development of more advanced fluoroelastomer formulations.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Life cycle greenhouse gas emissions of hydrogen fuel production from chlor-alkali processes in the United States

By-product hydrogen from chlor-alkali processes can help meet the increasing demand for hydrogen fuel in early fuel cell electric vehicle markets (e.g., California) in the U.S. Hydrogen produced from chlor-alkali plants is typically combusted for process heat on site, vented to the atmosphere (i.e., wasted), or sold to the external merchant hydrogen market. Whether it is combusted, vented, or sold as a commodity, relevant information is lacking as to the life-cycle environmental benefits or trade-offs of using by-product hydrogen from chlor-alkali plants. A life-cycle analysis framework was employed to evaluate well-to-gate greenhouse gas (GHG) emissions associated with by-product hydrogen from chlor-alkali processes in comparison with hydrogen from the conventional centralized natural gas steam methane reforming (central SMR) pathway. U.S.-specific, plant-by-plant, and up-to-date chlor-alkali production characteristics were incorporated into the analysis. In addition to the venting and combustion scenarios, to deal with the multi-functionality of the chlor-alkali processes that simultaneously produce chlorine, sodium hydroxide, and hydrogen, two different co-product allocation strategies were adopted mass allocation and market value allocation. It was estimated that by-product hydrogen production from chlor-alkali processes creates 1.3-9.8 kg CO 2 e/kg H 2 of life-cycle GHG emissions on average, which is 20-90% less than the conventional central SMR pathway. The results vary with co-product treatment scenarios, regional electric grid characteristics, on-site power generation, product prices, and hydrogen yield. Despite the variations in the results, it was concluded that the life-cycle GHG emission reduction benefits of using by-product hydrogen from chlor-alkali processes are robust. In conclusion, with a diverse set of scenario analyses, the study developed a comprehensive and detailed life-cycle GHG emissions inventory of the chlor-alkali by-product hydrogen pathway and quantified sensitivity indices in the context of different assumptions and input parameter values.

08 HYDROGEN↗
DOE OSTI2019

Bioalcohol production from acidogenic products via a two-step process: A case study of butyric acid to butanol

This article presents the full study (lab-scale experimental study and large-scale techno-economic analysis) results of a two-step catalytic process for the conversion of organic waste–derived butyric acid to butanol. Butanol from biomass resources like organic waste promise to become an attractive and sustainable fuel and industrial precursor due to an increase in greenhouse gas content in the atmosphere. Therefore, research in this field is important for energy applications and reduction in greenhouse gas emissions. In this regard, a two-step process was applied in this study to produce butanol from butyric acid that can potentially be derived from organic waste. The two-step process consists of the (1) esterification of butyric acid to methyl butyrate and (2) hydrogenolysis of this methyl butyrate to butanol. The first reaction, esterification of butyric acid, was optimized using carbon-based catalysts. The production of butanol from methyl butyrate via hydrogenolysis was investigated using bimetallic Pt–Co catalysts. The hydrogenolysis of methyl butyrate on these catalysts under optimal conditions of 250 °C, 5 MPa H 2 , and a feed/catalyst weight ratio of 11.2 led to 54.1% selectivity toward 1-butanol. Based on the experimental results, an integrated process simulation model was developed to determine the economic potential of the two-step production of butanol from butyric acid. Using this model, the techno-economic feasibility of the two-step process was analyzed. Here, the minimum selling price (MSP) of 1-butanol produced from butyric acid using this process was US dollars 3.388 per gallon of gasoline equivalent (GGE). This MSP is in the range of recent biofuel market prices of US dollars 2.03/GGE to US dollars 3.83/GGE.

09 BIOMASS FUELS↗
DOE OSTI2019

Friction stir processing of dual certified 304/304L austenitic stainless steel for improved cavitation erosion resistance

Cavitation phenomenon is known to be prevalent in equipment in hydraulic environments. Understanding cavitation and improving the cavitation resistance of commonly used materials is of interest for both scientific and economic reasons. In this study, friction stir processing was employed to modify commercial dual certified AISI 304/304L austenitic stainless steel plates. The cavitation erosion resistance of the processed plates was evaluated and compared to that of the unprocessed steel. A temperature control algorithm was employed to maintain a target tool temperature during the processing. The cross sections of the processed nuggets were evaluated using optical microscopy, scanning electron microscopy and Vickers hardness testing. Cavitation testing was performed conforming to ASTM G134 on specimens cut out of the nuggets of the commercially unprocessed and the processed 304/304L steel. The tool temperature was found to affect the microstructure and the cavitation performance. Friction stir processed steel showed 3 times better cavitation resistance than the unprocessed 304/304L. Surface cavitation patterns and cavitation rates were characterized and the mechanisms of material removal were discussed.

Jiang, Xiujuan↗
DOE OSTI2018

Weighted gene co-expression network analysis reveals potential genes involved in early metamorphosis process in sea cucumber Apostichopus japonicus

Highlights: • Gene expression profiles of sea cucumber were systematically examined. • Gene co-expression modules of sea cucumber were analyzed for the first time. • The module MEdarkmagenta is highly related to the early metamorphosis process. • Genes associated with the early metamorphosis process were identified. Sea cucumbers, one main class of Echinoderms, have a very fast and drastic metamorphosis process during their development. However, the molecular basis under this process remains largely unknown. Here we systematically examined the gene expression profiles of Japanese common sea cucumber (Apostichopus japonicus) for the first time by RNA sequencing across 16 developmental time points from fertilized egg to juvenile stage. Based on the weighted gene co-expression network analysis (WGCNA), we identified 21 modules. Among them, MEdarkmagenta was highly expressed and correlated with the early metamorphosis process from late auricularia to doliolaria larva. Furthermore, gene enrichment and differentially expressed gene analysis identified several genes in the module that may play key roles in the metamorphosis process. Our results not only provide a molecular basis for experimentally studying the development and morphological complexity of sea cucumber, but also lay a foundation for improving its emergence rate.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Increasing ethanol yield through fiber conversion in corn dry grind process

Conversion of corn fiber to ethanol in the dry grind process could increase ethanol yields, reduce downstream processing costs and improve overall process profitability. In this work, we investigate the in-situ conversion of corn fiber into ethanol (cellulase addition during simultaneous saccharification and fermentation) during dry grind process. Addition of 30 FPU/g fiber cellulase resulted in 4.6% increase in ethanol yield compared to the conventional process. Use of excess cellulase (120 FPU/g fiber) resulted in incomplete fermentation and lower ethanol yield compared to the conventional process. Lastly, multiple factors including high concentrations of ethanol and phenolic compounds were responsible for yeast stress and incomplete fermentation in excess cellulase experiments.

09 BIOMASS FUELS↗
DOE OSTI2022

Model quantification of the effect of coproducts and refinery co-hydrotreating on the economics and greenhouse gas emissions of a conceptual biomass catalytic fast pyrolysis process

Here we present model results for a scaled-up conceptual process informed by bench scale biomass catalytic fast pyrolysis (CFP) and hydrotreating experimental data. This process uses a Pt/TiO 2 catalyst during CFP, which produces a partially deoxygenated organic biocrude intermediate that is then hydroprocessed to a hydrocarbon fuel blendstock; the catalyst also enables high yields of acetone and methyl-ethyl-ketone (MEK) coproducts. Two options for hydroprocessing were modeled: (A) co-hydrotreating at a petroleum refinery using hydrogen sourced from steam reforming of natural gas and (B) standalone hydrotreating at a biorefinery using hydrogen sourced from CFP off gases. The results revealed that Case A was economically advantageous with a modeled minimum fuel selling price (MFSP) of $\$$2.83/GGE or gallon gasoline equivalent (in 2016 US dollars), while the additional cost of standalone hydrotreating facilities in Case B increased the MFSP to $3.13/GGE. Conversely, greenhouse gas (GHG) emissions were lower for Case B (3.9 g CO 2 e/MJ) compared to Case A (21.5 g CO 2 e/MJ) due to the use of biogenic (Case B) and fossil-derived (Case A) hydrogen. In a third option (Case C), the requirements for separation and purification of acetone and MEK were removed from the refinery co-processing scenario (Case A) to evaluate the impacts of this process simplification. Elimination of these coproducts increased the MFSP to $3.21/GGE and GHG emissions to 35 g CO 2 e/MJ. These comparisons based on our detailed conceptual models provide economic and sustainability guidance regarding processing choices for future biorefineries. While refinery coprocessing using existing equipment and the production of relatively valuable coproducts can benefit the economics, the hydrogen-source and biogenic coproducts can have significant impacts on the sustainability of the process, and feasibility to use CFP off-gases or other renewable sources for hydrogen production can help lower GHG emissions.

09 BIOMASS FUELS↗
DOE OSTI2023

Pore-scale simulation of multiphase flow and reactive transport processes involved in geologic carbon sequestration

Multiphase flow and reactive transport are two essential physicochemical processes that govern the effectiveness of geological carbon sequestration (GCS). The interaction and feedback among different phases and components during intricate physicochemical processes hold great significance in understanding CO 2 sequestration. Pore-scale simulations can account for multiphase flow and reactive transport processes in porous media and obtain spatial distributions of parameters (density, velocity, concentration, etc.) in the pore space as well as their temporal evolutions. This proves especially valuable considering that experiments can be hindered by constraints in spatial and temporal resolution. The comprehensive insights garnered from pore-scale research can be leveraged for continuum modeling using the representative elementary volume (REV) concept. In this contribution, four sequential mechanisms of CO 2 -brine-rock interaction in three zones delineated by CO 2 saturation are elaborated to elucidate complicated physicochemical processes involved in GCS, which are followed by general descriptions of mathematical equations and pore-scale numerical methods. In addition, as interested and commonly encountered processes, leakage risks during GCS and CO 2 -enhanced oil recovery (CO 2 -EOR) processes are presented. The existing challenges and future directions are discussed for both the performance of the pore-scale models and the current gaps in the field of GCS. Importantly, we expect that this review will prove beneficial for researchers interested in pore-scale simulations, GCS, and related disciplines.

58 GEOSCIENCES↗
DOE OSTI2017

Co-optimization of CO 2 -EOR and Storage Processes under Geological Uncertainty

This paper presents an integrated numerical framework to co-optimize EOR and CO 2 storage performance in the Farnsworth field unit (FWU), Ochiltree County, Texas. The framework includes a field-scale compositional reservoir flow model, an uncertainty quantification model and a neural network optimization process. The reservoir flow model has been constructed based on the field geophysical, geological, and engineering data. A laboratory fluid analysis was tuned to an equation of state and subsequently used to predict the thermodynamic minimum miscible pressure (MMP). A history match of primary and secondary recovery processes was conducted to estimate the reservoir and multiphase flow parameters as the baseline case for analyzing the effect of recycling produced gas, infill drilling and water alternating gas (WAG) cycles on oil recovery and CO 2 storage. A multi-objective optimization model was defined for maximizing both oil recovery and CO 2 storage. The uncertainty quantification model comprising the Latin Hypercube sampling, Monte Carlo simulation, and sensitivity analysis, was used to study the effects of uncertain variables on the defined objective functions. Uncertain variables such as bottom hole injection pressure, WAG cycle, injection and production group rates, and gas-oil ratio among others were selected. The most significant variables were selected as control variables to be used for the optimization process. A neural network optimization algorithm was utilized to optimize the objective function both with and without geological uncertainty. The vertical permeability anisotropy (Kv/Kh) was selected as one of the uncertain parameters in the optimization process. The simulation results were compared to a scenario baseline case that predicted CO 2 storage of 74%. The results showed an improved approach for optimizing oil recovery and CO 2 storage in the FWU. The optimization process predicted more than 94% of CO 2 storage and most importantly about 28% of incremental oil recovery. The sensitivity analysis reduced the number of control variables to decrease computational time. A risk aversion factor was used to represent results at various confidence levels to assist management in the decision-making process. The defined objective functions were proved to be a robust approach to co-optimize oil recovery and CO 2 storage. The Farnsworth CO 2 project will serve as a benchmark for future CO 2 –EOR or CCUS projects in the Anadarko basin or geologically similar basins throughout the world.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

A screening-level life cycle greenhouse gas analysis of CO 2 enhanced oil recovery with CO 2 sourced from the Shute Creek natural gas-processing facility

This life cycle analysis (LCA) evaluates life cycle greenhouse gas (GHG) emissions associated with a system that produces both natural gas and crude oil. Two systems are defined: System 1, which independently produces natural gas and oil, and System 2, which captures carbon dioxide (CO 2 ) from the natural gas-processing plant and utilizes this captured CO 2 for enhanced oil recovery (EOR). The LCA uses customized spreadsheet models with emission factors from peer-reviewed literature and publications of the National Energy Technology Laboratory of the U.S. Department of Energy. The modeling results show that the CO 2 EOR scenario using captured CO 2 produces both natural gas and oil with lower life cycle GHG emissions than alternative systems producing natural gas and oil independently. Sensitivity analyses show that the model results are most sensitive to the fraction of CO 2 captured (or equivalently, the fraction of CO 2 vented) at the natural gas-processing facility and the incremental oil recovery factor and net CO 2 utilization factor of the EOR operations. The input variable driving the relative difference in life cycle GHG emissions between these two systems is the fraction of CO 2 captured at the natural gas-processing facility (i.e., the capture rate). Here, the results of this study highlight the necessity of linking processes in the life cycle modeling, as a change to one process can affect other processes within the coupled energy system comprised of natural gas and oil. In addition, this analysis shows, as prior work has also suggested, that CO 2 EOR using captured anthropogenic CO 2 provides a viable means for offsetting carbon emissions from oil production and combustion via the associated storage of CO 2 that occurs incidentally during this tertiary method of oil recovery.

02 PETROLEUM↗
DOE OSTI2019

Nanoscale MnO 2 cathodes for Li-ion batteries: effect of thermal and mechanical processing

This study investigates the effect of thermal and mechanical processing of MnO 2 nanoparticle cathodes on the electrochemical performance, ion intercalation mechanism and structural changes upon cycling. Specifically, thermal processing at different temperatures is utilized to tune the sub-nanoparticle polymorph composition, while mechanical processing (high energy ball-milling) is used to change the particle size and create a better contact between active material and conductive graphite additive. The combination of thermal and mechanical processing is also investigated for possible synergistic effects. The structural changes due to processing suggest that thermal treatment of the MnO 2 nanoparticles at 400 °C forms a high concentration of pyrolusite domains (1 $\times$ 1 channels) leading to improved reversibility of lithium intercalation/de-intercalation and capacity retention. It is also found that ball-milling for a short time (20 min) leads to some amorphization and decrease of the crystallite sizes resulting in improved capacity. The structural changes and ion intercalation mechanism of the pristine and processed electrode materials during cycling are investigated by ex situ synchrotron x-ray diffraction (XRD) and ex situ and in situ x-ray absorption near edge structure (XANES) studies.

25 ENERGY STORAGE↗