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DOE OSTI2024

High‐Loading Lithium‐Sulfur Batteries with Solvent‐Free Dry‐Electrode Processing

Abstract Lithium‐sulfur (Li‐S) batteries, with their high energy density, nontoxicity, and the natural abundance of sulfur, hold immense potential as the next‐generation energy storage technology. To maximize the actual energy density of the Li‐S batteries for practical applications, it is crucial to escalate the areal capacity of the sulfur cathode by fabricating an electrode with high sulfur loading. Herein, ultra‐high sulfur loading (up to 12 mg cm −2 ) cathodes are fabricated through an industrially viable and sustainable solvent‐free dry‐processing method that utilizes a polytetrafluoroethylene binder fibrillation. Due to its low porosity cathode architecture formed by the binder fibrillation process, the dry‐processed electrodes exhibit a relatively lower initial capacity compared to the slurry‐processed electrode. However, its mechanical stability is well maintained throughout the cycling without the formation of electrode cracking, demonstrating significantly superior cycling stability. Additionally, through the optimization of the dry‐processing, a single‐layer pouch cell with a loading of 9 mg cm −2 and a novel multi‐layer pouch cell that uses an aluminum mesh as its current collector with a total loading of 14 mg cm −2 are introduced. To address the reduced initial capacity of dry‐processed electrodes, strategies such as incorporating electrocatalysts or employing prelithiated active materials are suggested.

Chemistry↗

DOE OSTI2020

An experimental investigation of the effectiveness of Ar-CO 2 shielding gas mixture for the wire arc additive process

Wire arc additive manufacturing (AM) is the process by which a large, metallic structure is built layer-by-layer using a welding arc to melt a wire feedstock. A novel opportunity exists to alter the shielding gas composition to fabricate distinct geometrical features without altering the other AM parameters. In this paper, shielding gases with varied concentrations of Argon (Ar) and CO 2 was used to deposit three distinct geometric shapes (walls, infill, and overhang) using a wire-based additive manufacturing system utilizing the gas metal arc welding (GMAW) surface tension transfer (STT) process. Computer-aided design (CAD) models were sliced with a custom-built slicer, and the sliced algorithm was converted into optimal robotic toolpaths. A custom virtual instrument (VI) was built in LabVIEW to compare the temperature profiles on the surface during each deposition process. After each deposition, the geometric features were scanned, and the surface waviness value was evaluated. Tensile and Charpy impact coupons were extracted from the wall geometries in the longitudinal and transverse directions and tested. The results indicated that a higher CO 2 content produced higher melt pool temperatures to an extent, while lower contents of CO 2 resulted in a dimensionally accurate geometry. The data also indicated that the 2%/98% CO 2 /Ar blend produced scatter in tensile strength and the analysis of variance (ANOVA) shows significant difference. However, the intermediate range of CO 2 (5–10%) resulted in uniform tensile properties. Altogether, these results indicate that a 5%/95% CO 2 /Ar blend is the ideal shielding gas for lowering process temperatures and improving mechanical properties in wire arc additive manufacturing using the gas metal arc welding surface tension transfer process. Additionally, varying concentrations of Ar/CO 2 can be used within the same part in order to modify the local properties or process parameters such as strength, toughness, temperature, or dimensional features. This may improve overall manufacturing quality without sacrificing specific properties.

42 ENGINEERING↗

DOE OSTI2015

Distributed computing strategies for processing of FT-ICR MS imaging datasets for continuous mode data visualization

High-resolution Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry imaging enables the spatial mapping and identification of biomolecules from complex surfaces. The need for long time-domain transients, and thus large raw file sizes, results in a large amount of raw data (“big data”) that must be processed efficiently and rapidly. This can be compounded by largearea imaging and/or high spatial resolution imaging. For FT-ICR, data processing and data reduction must not compromise the high mass resolution afforded by the mass spectrometer. The continuous mode “Mosaic Datacube” approach allows high mass resolution visualization (0.001 Da) of mass spectrometry imaging data, but requires additional processing as compared to featurebased processing. We describe the use of distributed computing for processing of FT-ICR MS imaging datasets with generation of continuous mode Mosaic Datacubes for high mass resolution visualization. An eight-fold improvement in processing time is demonstrated using a Dutch nationally available cloud service.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2015

Building a sustained climate assessment process

The leaders and authors of the Third US National Climate Assessment (NCA3) developed new modes of engaging academia, the private sector, government agencies and civil society to support their needs for usable, rigorous, and timely information and better connect science and decision-making. A strategic vision for assessment activities into the future was built during the NCA3 process, including recommendations on how to establish a sustained assessment process that would integrate evolving scientific understanding into decision making to manage the risks of climate change over time. This vision includes a collaborative assessment process that involves partnerships across a diverse and widely distributed set of non-governmental and governmental entities. The new approach to assessments would produce timely, scientifically sound climate information products and processes, rather than focusing on the production of single quadrennial synthesis reports. If properly implemented, a sustained assessment would be more efficient and cost-effective, avoiding the painful and time-consuming process of beginning the assessment process anew every 4 years. This ongoing assessment would also encourage scientific and social innovations and explore new insights and opportunities, building the capacity to advance the development and delivery of climate information to meet societal requirements and benefit from scientific opportunities.

Buizer, James L.↗

DOE OSTI2018

Single-Grain Bulk YBa{sub 2}Cu{sub 3}O{sub y} Superconductors Grown by Infiltration Growth Process Utilizing the YbBa{sub 2}Cu{sub 3}O{sub y} + Liquid Phase as a Liquid Source

The top-seeded infiltration growth (IG) processed YBa{sub 2}Cu{sub 3}O{sub y} (Y-123) has several advantages compared to the same material produced by other melt process techniques. There is usually no shrinkage, a limited number of pores, and an uniform secondary phase particle dispersion in the Y-123 matrix. These characteristics of the IG process are very attractive for several industrial applications. In this paper, we produced a large single-grain Y-123 by IG and top seeded melt-growth process. Utilizing commercial YbBa{sub 2}Cu{sub 3}O{sub y} (Yb-123) and a homemade Y{sub 2}BaCuO{sub 5} (Y-211), we produced bulk YBa{sub 2}Cu{sub 3}O{sub y} samples using Yb-123 + liquid (1:1) as a liquid source. Four facet lines on the top surfaces of the as-grown samples indicated a uniform growth from the seed up to sample edges. Magnetization measurements by SQUID magnetometer showed a sharp superconducting transition with T{sub c},{sub onset} at 92.1 K. The critical current density at 77 K and self-field was 39,000 A/cm{sup 2}. Trapped field results confirmed that single grain Y-123 samples were produced utilizing the above process. Our results prove that Yb-123 + liquid (1:1) as a liquid source is effective in producing single grain Y-123 material by IG process.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2017

Scaling Limits and Generic Bounds for Exploration Processes

We consider exploration algorithms of the random sequential adsorption type both for homogeneous random graphs and random geometric graphs based on spatial Poisson processes. At each step, a vertex of the graph becomes active and its neighboring nodes become blocked. Given an initial number of vertices N growing to infinity, we study statistical properties of the proportion of explored (active or blocked) nodes in time using scaling limits. We obtain exact limits for homogeneous graphs and prove an explicit central limit theorem for the final proportion of active nodes, known as the jamming constant, through a diffusion approximation for the exploration process which can be described as a unidimensional process. We then focus on bounding the trajectories of such exploration processes on random geometric graphs, i.e., random sequential adsorption. As opposed to exploration processes on homogeneous random graphs, these do not allow for such a dimensional reduction. Instead we derive a fundamental relationship between the number of explored nodes and the discovered volume in the spatial process, and we obtain generic bounds for the fluid limit and jamming constant: bounds that are independent of the dimension of space and the detailed shape of the volume associated to the discovered node. Lastly, using coupling techinques, we give trajectorial interpretations of the generic bounds.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2018

Discrete Approximations of Determinantal Point Processes on Continuous Spaces: Tree Representations and Tail Triviality

We prove tail triviality of determinantal point processes μ on continuous spaces. Tail triviality has been proved for such processes only on discrete spaces, and hence we have generalized the result to continuous spaces. To do this, we construct tree representations, that is, discrete approximations of determinantal point processes enjoying a determinantal structure. There are many interesting examples of determinantal point processes on continuous spaces such as zero points of the hyperbolic Gaussian analytic function with Bergman kernel, and the thermodynamic limit of eigenvalues of Gaussian random matrices for Sine{sub 2},Airy{sub 2},Bessel{sub 2}, and Ginibre point processes. Our main theorem proves all these point processes are tail trivial.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2015

Foreword: Additive Manufacturing: Interrelationships of Fabrication, Constitutive Relationships Targeting Performance, and Feedback to Process Control

Additive manufacturing (AM) offers distinct advantages over conventional manufacturing processes including the capability to both build and repair complex part shapes; to integrate and consolidate parts and thus overcome joining concerns; and to locally tailor material compositions as well as properties. Moreover, a variety of fields such as aerospace, military, automotive, and biomedical are employing this manufacturing technique as a way to decrease costs, increase manufacturing agility, and explore novel geometry/functionalities. In order to increase acceptance of AM as a viable processing method, pathways for qualifying both the material and the process need to be developed and, perhaps, standardized. This symposium was designed to serve as a venue for the international AM community—including government, academia, and industry—to define the fundamental interrelationships between feedstock, processing, microstructure, shape, mechanical behavior/materials properties, and function/performance. Eventually, insight into the connections between processing, microstructure, property, and performance will be achieved through experimental observations, theoretical advances, and computational modeling of physical processes. Finally, once this insight matures, AM will be able to move from the realm of making parts to making qualified materials that are certified for use with minimal need for post-fabrication characterization.

36 MATERIALS SCIENCE↗

DOE OSTI2018

Numerical Investigation of Novel Oxygen Blast Furnace Ironmaking Processes

Oxygen blast furnace (OBF) ironmaking process has the potential to realize “zero carbon footprint” production, but suffers from the “thermal shortage” problem. This paper presents three novel OBF processes, featured by belly injection of reformed coke oven gas, burden hot-charge operation, and their combination, respectively. These processes were studied by a multifluid process model. The applicability of the model was confirmed by comparing the numerical results against the measured key performance indicators of an experimental OBF operated with or without injection of reformed coke oven gas. Then, these different OBF processes together with a pure OBF were numerically examined in aspects of in-furnace states and global performance, assuming that the burden quality can be maintained during the hot-charge operation. The numerical results show that under the present conditions, belly injection and hot charge, as auxiliary measures, are useful for reducing the fuel rate and increasing the productivity for OBFs but in different manners. Hot charge should be more suitable for OBFs of different sizes because it improves the thermochemical states throughout the dry zone rather than within a narrow region in the case of belly injection. The simultaneous application of belly injection and hot charge leads to the best process performance, at the same time, lowering down hot-charge temperature to achieve the same carbon consumption and hot metal temperature as that achieved when applying the hot charge alone. This feature will be practically beneficial in the application of hot-charge operation. In addition, a systematic study of hot-charge temperature reveals that optimal hot-charge temperatures can be identified according to the utilization efficiency of the sensible heat of hot burden.

36 MATERIALS SCIENCE↗

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↗