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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

System and method for in-process inspection within advanced manufacturing processes

A system and method can include a laser Doppler vibrometer (LDV) in optical communication with a part during manufacturing and a transducer in ultrasonic communication with the part during manufacturing. The system can also include a controller connected to both the LDV and the transducer. The controller may be configured to cause the transducer to vibrate the part during manufacturing at a predetermined frequency and the LDV may be configured to measure one or more mechanical response types of the part during manufacturing based on one or more optical characteristics of a reflected beam. The controller may further be configured to determine whether a defect is present in the part during manufacturing in response to the one or more mechanical response types of the part.

42 ENGINEERING↗
DOE OSTI2022

Active magnetic regenerative processes and systems employing hydrogen as heat transfer fluid and process gas

A system including:an active magnetic regenerative refrigerator apparatus that includes a high magnetic field section in which a hydrogen heat transfer fluid can flow from a cold side to a hot side through at least one magnetized bed of at least one magnetic refrigerant, and a low magnetic field or demagnetized section in which the hydrogen heat transfer fluid can flow from a hot side to a cold side through the demagnetized bed;a first conduit fluidly coupled between the cold side of the low magnetic field or demagnetized section and the cold side of the high magnetic field section; anda second conduit fluid coupled to the first conduit, an expander and at least one liquefied hydrogen storage module.

Holladay, Jamie D.↗
DOE OSTI2020

Multi-Model and Multi-Scale Global Sensitivity Analysis for Identifying Controlling Processes of Complex Systems

An environmental model consists of multiple process level sub-models, and each sub-model represents a process that is key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this project develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods with variance-based global sensitivity analysis to address uncertainty in process models and parameters. The new method yields three process sensitivity indices. The first one is called first-order process sensitivity index, and it is derived as a single summary measure of relative process importance. Evaluating the index is computationally expensive, because it relies in a Monte Carlo scheme that requires thousands and even millions of model executions. To reduce computational cost, this project develops a computationally efficient, quasi Monte Carlo method, and this method is presented in Chapter 2 of this report with and a numerical example for demonstration. The numerical example shows that the results of the quasi Monte Carlo method are substantially close to those of the full Monte Carlo method, but the computational cost of the quasi Monte Carlo method is only 0.7% of that of the full Monte Carlo method. The second index is called total-effect process sensitivity index, and it measures interactions between different processes. Therefore, this sensitivity index includes the first-order process sensitivity index, and can be used to identify influential processes. On the other hand, the total-effect process sensitivity index can also be used to screen non-influential processes. This is demonstrated by two numerical examples using the Sobol-G* functions and groundwater flow models that consider recharge process, geological process, and snowmelt process. The numerical examples shows that the total-effect process sensitivity index is more informative than the first-order process sensitivity. The derivation of the process sensitivity index and the numerical examples are discussed in Chapter 3. Chapter 4 presents two computationally efficient methods for screening non-influential processes to exclude them from further investigation. The two methods are the multi-model difference-based sensitivity (MMDS) analysis method, which can be implemented using the Latin Hypercube Sampling. The second one is the implementation of MMDS method using a binning method. The numerical example for the Sobol-G* function indicates the two methods are capable of identifying non-influential models, and the numerical examples for the groundwater flow and reactive transport show that the two methods are effective for groundwater problems. However, it should be noted that the two methods are numerical approximations, and they can only be used for screening non-influential processes, not for ranking importance of system processes. All the sensitivity analysis methods are implemented by developing python codes, and the codes are in a software called SAMMPY: a python package for process sensitivity analysis under multiple models. The SAMMPY design and structure are discussed in Chapter 5, and the package is released to the public for free download.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

In-situ X-Ray Analysis of Rapid Thermal Processing for Thin-Film Solar Cells: Closing the Gap between Production and Laboratory Efficiency

For materials synthesis, it is well known that the material final state may not reach equilibrium and depends on the synthetic process. In particular, processes that quickly remove the available energy from the material may leave it in a metastable state and the metastability may actually impart desirable functional properties. By its very nature, Rapid thermal processing (RTP) is ideally suited to produce such metastable materials. However, metastability and the dynamics of reaching a metastable state are poorly understood, since this is best accomplished through in situ monitoring. In this regard, RTP is particularly challenging as the processing time are very short (seconds to minutes). As a result, there is only poor understanding, and hence use, of RTP in industry. This is potentially a cost-increasing limitation, because RTP can decrease cost by decreasing processing time, and as such, increase throughput and decrease the total thermal budget of processing - a significant cost. RTP is already being used for key processing steps in PV technologies. With silicon wafer PV, it is used for establishing electrical contact between the Ag metal grid and the silicon (known as firing). In this process, a silicon wafer with deposited metal/frit in a grid pattern is heated rapidly to temperatures between 750 and 800 ºC. The processing time when the temperature is held above 600ºC is short (<5 seconds). This process has historically been optimized empirically and it is unclear how the thermal processing affects formation of the final contact between the metal and the silicon. In the case of thin-film PV, RTP has been demonstrated in the process of making absorber layers, i.e. CIGS and CZTS. Use of RTP can reduce the processing time from 10s of minutes to seconds, reducing the thermal budget and increasing the throughput significantly. The conversion from precursor material to final PV material is not well understood, and most of the process optimization is done empirically. Again, the proposed in situ monitoring will provide insight into the conversion process. We have developed a unique instrument for in situ monitoring of the reaction process during RTP. The most fundamental property to monitor is the atomic arrangement (for solids, crystalline structure) and thus we have focused on this property. The chamber was designed to collect X-ray diffraction (XRD) for crystal phase determination, although it has lent insight in the formation of liquids. We designed and constructed both inert (air) and reactive (S/Se) versions of this chamber. We have applied the RTP-XRD methodology to: silicon solar cell electrical contact formation; the reaction sequence for forming CIGS PV thin films from copper selenide and indium gallium selenide precursors; the phase sequence for forming HC(NH2)2PbI3 (FAPbI3) and CH3NH3PbI3 (MAPbI3) hybrid-perovskite PV thin films. The RTP instrument enables real-time collection of X-ray diffraction data with intervals as short as 100 ms, and while heating at ramp rates as high 100 ºCs-1 up to 1200 ºC. The system is portable and can be installed on a synchrotron beamline. The RTP reactor consists of a metallic body (front cap assembly, central block and end cap assembly) that houses a quartz reaction chamber. The sample is secured inside the reaction chamber on a sample holder connected to the front-cap assembly. Modifications of the chamber were made for safely handling sulfur and selenium vapor environments. A Se/S source holder was added to generate a Se/S over pressure in the chamber on heating and the entrance window is made wider in order to accommodate the detachable additional holder. Se/S are toxic in nature and therefore a proper Se/S trapping is used before releasing the gases to exhaust. Screen-printing provides an economically attractive means for making Ag electrical contacts to Si solar cells, but the use of Ag substantiates a significant manufacturing cost, and the glass frit used in the paste to enable contact formation contains Pb. To achieve optimal electrical performance and to develop pastes with alternative, abundant, and non-toxic materials requires understanding the contact formation process during firing. We use the RTP-XRD chamber during firing of Ag-Si contacts to reveal the reaction sequence for contact formation. The findings show that between 500 ºC and 650 ºC PbO in the frit etches the SiNx antireflective-coating on the solar cell, exposing the Si surface. Then, above 650 ºC, Ag+ dissolves into the molten glass frit – key for enabling deposition of metallic Ag on the emitter surface and precipitation of Ag nanocrystals within the glass. This clarifies contact formation mechanisms and can be used to suggest approaches for development of inexpensive, nontoxic solar cell contacting pastes. We used the RTP/XRD chamber to study the formation of CuInGaS/Se (CIGS) PV films by in-situ selenization of pre-deposited metal stacks and annealing of pre-deposited Cu-In-Ga-Se precursors. During the metal stack selenization, we observed that Se first reacts with the metals and forms selenides. We observed formation of intermetallics such as Cu2In and binary selenides during heating. On further annealing in a Se atmosphere, CuInSe2 and CuGaSe2 forms which on heating up to 550 °C reacts further to form the CIGS phase. On prolonged exposure to 550 °C for more than 5 mins or higher temperature, we see separation into Ga-rich and Ga-depleted CIGS phases. On introducing a holding step at 400 °C for 10 min during the annealing ramp, the CIGS phase (forms between 500-550 °C), appears to be less prone to decomposition into high-Ga and low-Ga phases during holding at peak temperature. Lead halide perovskites have emerged as successful optoelectronic materials with high photovoltaic power conversion efficiencies and low material cost. However, substantial challenges remain in the scalability, stability and fundamental understanding of the materials. We demonstrated the application of radiative thermal annealing, an easily scalable processing method, for synthesizing formamidinium lead iodide (FAPbI3) perovskite solar absorbers. Devices fabricated from films formed via radiative thermal annealing have equivalent efficiencies to those annealed using a conventional hotplate. By coupling results from in situ x-ray diffraction using a radiative thermal annealing system with device performances, we mapped the processing phase space of FAPbI3 and corresponding device efficiencies. Our map of processing-structure-performance space suggests the commonly used FAPbI3 annealing time, 10 min at 170 °C, can be significantly reduced to 40 s at 170 °C without affecting the photovoltaic performance. Applying the Johnson-Mehl-Avrami model to the decomposition into PbI2, the activation energy was determined. We also presented a well-controlled, manufacturing relevant annealing method, radiative thermal annealing, for the methylammonium lead triiodide films formed by solvent engineering process, with dimethylformamide (DMF) and dimethyl sulfoxide as solvent and diethyl ether as the antisolvent. Radiative thermal annealing can produce high quality perovskite films, evidenced by high efficiency solar cell devices, in a shorter time than the widely-used hotplate annealing. Using in-situ x-ray diffraction during the radiative annealing, we show that the role of the antisolvent is not to form an intermediate compound (a methylammonium iodide, lead iodide, and dimethyl sulfoxide compound) by washing of the main solvent (DMF) but to achieve a pin-hole free, uniform film of methylammonium lead iodide. We find that having the intermediate compound does not guarantee a high quality (pin-hole free) perovskite film. Our study was extended to reveal the effect of annealing environment, annealing temperature profile, and deposition substrate.

36 MATERIALS SCIENCE↗
DOE OSTI2022

AI-Enabled Discovery and Physics-Based Optimization of Energy Efficient Processing Strategies for Advanced Turbine Alloys (Final Technical Report)

In this project, the multi-organizational team of academic and industrial researchers from the University of Kentucky an aerospace and energy generation OEM partner has leveraged novel Digital Process Twin (DPT) models of process/structure interactions (i.e., process-induced surface integrity) to advance a paradigm of fully integrated computational materials engineering (ICME). Using efficient process models as the core of a digital process simulator for a reinforcement learning algorithm, the team has integrated industrial data and metrics of structure/performance/energy relationships and manufacturing-related energy metrics to optimize dynamic processing parameters for significantly improved life-cycle energy efficiency of advanced γ-TiAl low-pressure turbine (LPT) alloys, as indicated by a set of design relevant parameters (e.g., residual stresses and scrap rate). The key objective and anticipated outcome of the project was at least a 10% reduction in life-cycle embodied energy for a recently developed, γ-TiAl low-pressure turbine (LPT) alloy and nickel-based superalloy Inconel 718, through the adoption of the proposed AI-enabled process optimization approach. The final project outcomes significantly exceeded this original target, realizing manufacturing-related energy efficiency improvements of more than 130% for TiAl and up to 80% for Inconel 718. Rather than following the prevailing and highly inefficient empirical paradigm, the proposed study demonstrated the feasibility of adopting a digital, physics-based process design and optimization paradigm. The recurring need for manual intervention, rework, reinspection causes significant production bottlenecks and unnecessary expense associated with delivering the requisite component quality. The OEM partner, and turbine industry in general, expect to reap significant cost and resource savings if an AI-optimized set of parameters can be applied to specific machining operations. The technical scope of the proposed project involved the paving of a realistic path towards model-based and AI-enabled Integrated Computational Materials Engineering (ICME), and away from inefficient empirical process optimization and legacy manufacturing practices, which are no longer able to efficiently process novel high-performance turbine alloy materials. The project team will address the fundamental knowledge gap that currently exists within the ICME paradigm with respect to the process/structure/performance/energy impacts of finishing processes. While significant resources have been devoted to the ‘early stages’ of manufacturing, such as alloy design, primary and secondary processing, finishing processes have not been adequately integrated within ICME. To provide an actionable path towards model-based finishing process design (e.g., machining, burnishing, grinding, polishing), we will employ a novel AI-enabled process optimization paradigm, based on a computationally efficient, physics-based process simulator. Through limited experimental work to calibrate and validate our process simulator model via an advanced in-situ characterization technique and process optimization via reinforcement learning, the project will seek to demonstrate a viable alternative to the inefficient ‘legacy’ processing strategies, empirical testing and broad scope machining learning approaches, all of which fail to adequately consider complex process physics. The project team has identified an intermetallic γ-TiAl LPT alloy, which is currently being used as part of the OEM partner’s advanced gas turbine designs. This particular alloy poses significant manufacturing challenges during finishing operations, which limit the degree to which the current turbine design can be manufactured in an energy- and cost-efficient manner. Empirical testing and numerical modeling efforts to optimize processing parameters for γ-TiAl have not been able to resolve these manufacturing challenges, so the proposed physics-based AI-enabled optimization technology would offer a truly novel and transformative capability. The multi-organizational team of academic and industry experts from the UKY and the OEM partner will work together closely to demonstrate the analytical and experimental critical function and characteristic proof of concept of this novel approach.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Carbon Intensities of Refining Products in Petroleum Refineries with Co-Processed Biofeedstocks

Petroleum refineries increasingly seek to generate fuels with lower carbon intensities (CIs; a measure of life cycle greenhouse gas [GHG] emissions per unit of energy of fuel; well-to-wheel [WTW]) to meet growing demand. Co-processing refers to a process that adds biomass-derived feedstocks to the fossil-based feedstocks of existing petroleum refinery process units. With the use of biofeedstocks, it is expected that co-processed fuels would have lower CIs than their petroleum counterparts without requiring changes in the existing infrastructure for producing, transporting, and using fuels. To quantify the GHG emissions reduction benefits of co-processing, this study uses a linear programming model to simulate petroleum refinery conditions with and without co-processing. The co-processing cases include three biofeedstocks (soy oil, tallow, and used cooking oil or UCO) used as 10 vol.% of the feedstock to a hydrotreater or hydrocracker since these lipid-based feedstocks have favorable properties to be treated in a hydrotreater or hydrocracker. In addition, we considered pyrolysis oil used as 10 vol.% of the feedstock to a fluid catalytic cracking (FCC) unit in the modeled refinery due to its higher oxygen content compared to other lipid-based feedstocks. Life cycle analysis (LCA) using two distinct approaches—process-level energy allocation and a refinery-level marginal approach—has been conducted for each case. The LCA results using process-level allocation show that there are no noticeable changes in emissions or energy use impacts at the facility level. The life cycle GHG emission reductions of co-processing cases are mainly related to the fraction of biogenic carbon embedded in each fuel product. For example, co-processed jet fuels (a mixture of fossil and biogenic fuels) made via hydrotreating or hydrocracking have higher biogenic carbon, which results in jet fuel CI reductions of 3.9%–8.6% compared to the CI of baseline petroleum jet fuels on a WTW basis. However, analysis of co-processed pyrolysis oil in an FCC shows that a higher fraction of biofeedstocks (29%) becomes process emissions (i.e., CO and CO 2 ), mainly due to the oxygenates in pyrolysis oil, and so it generates less renewable fuel than biofeedstocks co-processed via hydrotreating or hydrocracking. Using the refinery-level marginal approach, the changes in energy use and emissions of co-processing cases compared to the petroleum-only baseline case are allocated to the changes in fuel production (assuming renewable fuels). This approach generates the life cycle GHG emission values of co-processed renewable fuels, which are comparable to the CIs of standalone biofuel production pathways. However, as this approach relies on a rough assumption that product yields and emissions from co-processing units on fossil feedstocks remain the same with and without biofeedstock inputs, co-processing cases like FCC pyrolysis oil may generate quite skewed results.

02 PETROLEUM↗
DOE OSTI2022

Integration of Omics into a New Comprehensive Rate Law for Competitive Terminal Electron-Accepting Processes in Reactive Transport Models: Application to N, Fe, S, and Contaminant Transformations in Stream and Wetland Sediments

Surface waters represent important sources of alternate energy and drinking water in the United States, and characterizing the biogeochemical processes that affect surface water quality is relevant to the DOE-BER mission. Sediment biogeochemical processes regulate the release of carbon (C), nutrients, and contaminants to surface waters and thus influence water quality. Sediment biogeochemical processes are dynamic and affected by the deposition and remobilization of solid material and changes in environmental conditions driven by water discharge variations. Wetlands are important natural filters of surface waters which may either trap, metabolize, or mobilize nutrients and contaminants. Despite their importance, biogeochemical processes regulating nutrient and contaminant release and C transformation in stream and wetland sediments cannot be predicted accurately by current mathematical models. These reactive transport models largely rely on detectable changes in geochemical conditions to activate metabolic processes, do not accurately account for the competition between microbial processes, and poorly constrain effects of hydrological perturbations on biogeochemical processes. In this BER-SBR exploratory project, metagenomic and geochemical signatures were combined to identify microbially-mediated redox processes in anaerobic stream and wetland sediments from the Savannah River Site (SRS, ANL SFA) and East Fork Poplar Creek (EFPC, ORNL SFA) that play important roles in C, uranium (U), and mercury (Hg) transformations. In addition, sediment incubations were conducted to examine the competition between anaerobic respiration processes Finally, new rate laws were developed for reactive transport models that rely on complementary metagenomic and geochemical signatures to identify the underlying anaerobic microbial processes in stream and wetland sediments, describe the competition between the dominant metabolic processes involved in nutrient release and U and Hg mobilization, and more accurately quantify carbon transformation and the response of microbial processes to changes in redox conditions associated with hydrological forcing. These rate laws were optimized in batch reactors with SRS wetland sediments, where iron and sulfate reduction dominate. Anaerobic carbon remineralization processes followed the expected thermodynamic sequence of microbial respiration with depth in both sediments, except that geochemical signals indicated that sulfate reduction was inactive in EFPC sediments and moderate in SRS wetland sediments. Estimates indicated that microbial iron reduction contributed to at least half of the production of reduced iron in these sediments. Incubations demonstrated that nitrate reduction, denitrification, and dissimilatory nitrate reduction to ammonium were active in the natural EFPC sediment and activated upon nitrate amendment in these nitrate-rich sediments. In turn, these processes were outcompeted by the addition of either iron oxides or sulfate as alternative terminal electron acceptors. Although geochemical products of sulfate reduction were not detected in the incubations, the abundance of sulfate reduction genes increased with depth in the sediment and was equally more pronounced in treatments amended with either iron oxides or sulfate. Simultaneously, anaerobic sulfide oxidizing bacteria coupling sulfide oxidation to DNRA (and not conventional denitrification) were apparently enriched over time, regardless of the treatments. These findings indicate that sulfate reduction is important in freshwater stream sediments and probably catalyzed by a cryptic sulfur cycle involving nitrogen species, in which the sulfur products from sulfate reduction are immediately removed by side reactions and not detectable by geochemical measurements alone. Similar experiments in SRS sediments, however, demonstrated little interaction between nitrogen and sulfur cycling microorganisms. Sulfate reduction was impacted by the addition of more thermodynamically favorable electron acceptors, suggesting either that iron-reducing microorganisms outcompeted sulfate-reducing microorganisms for organic substrate, depleting the stock of electron donor available for sulfate reduction, or that the cryptic sulfur cycle was shunted by the precipitation of FeS generated as a result of the abiotic reduction of iron oxides by dissolved sulfide. A diagnostic modeling exercise was conducted to further investigate the competition between terminal electron accepting processes. As conventional kinetic models typically do not account for cryptic cycles and used inaccurate formulations to describe competition between microbial communities, new metabolic rate laws were developed that explicitly express the electron acceptor-specific enzyme of each energetically favorable metabolic process based on gene abundance detected in the incubations. The model was tested with the sediment slurry incubation data to determine whether substrate competition could explain the decrease in sulfate reduction observed in the presence of iron oxide competitor. The model was able to reproduce geochemical concentrations really well in each treatment once the model was calibrated with the unamended control, suggesting that microbial competition was indeed driven by thermodynamic considerations. Overall, carbon remineralization processes and rates will be reproduced much more realistically with the new metabolic rate laws.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2011

Evaluation of Co-precipitation Processes for the Synthesis of Mixed-Oxide Fuel Feedstock Materials

The focus of this report is the evaluation of various co-precipitation processes for use in the synthesis of mixed oxide feedstock powders for the Ceramic Fuels Technology Area within the Fuels Cycle R&D (FCR&D) Program's Advanced Fuels Campaign. The evaluation will include a comparison with standard mechanical mixing of dry powders and as well as other co-conversion methods. The end result will be the down selection of a preferred sequence of co-precipitation process for the preparation of nuclear fuel feedstock materials to be used for comparison with other feedstock preparation methods. A review of the literature was done to identify potential nitrate-to-oxide co-conversion processes which have been applied to mixtures of uranium and plutonium to achieve recycle fuel homogeneity. Recent studies have begun to study the options for co-converting all of the plutonium and neptunium recovered from used nuclear fuels, together with appropriate portions of recovered uranium to produce the desired mixed oxide recycle fuel. The addition of recycled uranium will help reduce the safeguard attractiveness level and improve proliferation resistance of the recycled fuel. The inclusion of neptunium is primarily driven by its chemical similarity to plutonium, thus enabling a simple quick path to recycle. For recycle fuel to thermal-spectrum light water reactors (LWRs), the uranium concentration can be {approx}90% (wt.), and for fast spectrum reactors, the uranium concentration can typically exceed 70% (wt.). However, some of the co-conversion/recycle fuel fabrication processes being developed utilize a two-step process to reach the desired uranium concentration. In these processes, a 50-50 'master-mix' MOX powder is produced by the co-conversion process, and the uranium concentration is adjusted to the desired level for MOX fuel recycle by powder blending (milling) the 'master-mix' with depleted uranium oxide. In general, parameters that must be controlled for co-precipitation processes include (1) feed solution concentration adjustment, (2) precipitant concentration and addition methods, (3) pH, temperature, mixing method and time, (4) valence adjustment, (5) solid precipitate separation from the filtrate 'mother liquor,' generally by means of centrifugation or filtration, and (6) temperatures and times for drying, calcination, and reduction of the MOX product powder. Also a recovery step is necessary because of low, but finite solubility of the U/TRU metals in the mother liquor. The recovery step usually involves destruction of the residual precipitant and disposal of by-product wastes. Direct denitrations of U/TRU require fewer steps, but must utilize various methods to enable production of MOX with product characteristics that are acceptable for recycle fuel fabrication. The three co-precipitation processes considered for evaluation are (1) the ammonia co-precipitation process being developed in Russia, (2) the oxalate co-precipitation process, being developed in France, and (3) the ammonium-uranyl-plutonyl-carbonate (AUPuC) process being developed in Germany. Two direct denitration processes are presented for comparison: (1) the 'Microwave Heating (MH)' automated multi-batch process developed in Japan and (2) the 'Modified Direct Denitration (MDD)' continuous process being developed in the USA. Brief comparative descriptions of the U/TRU co-conversion processes are described. More complete details are provided in the references.

Collins, Emory D↗
DOE OSTI2022

High-Silicon Steel Strip by Single-Step Shear Deformation Processing

It is well known that Fe-Si alloys with Si content higher than in conventional electrical sheet steels (>3.2% Si) can make a significant impact in improving the efficiency of electrical motors if they are available in sheet/foil (strip) forms at suitable cost. While the magnetic and electrical attributes (e.g., resistivity, core loss) of these high-Si Fe alloys, of relevance to electrical motor core laminations, are known to be exceptional, the alloys have limited workability, making them difficult to produce consistently in sheet/foil (strip) forms. Current processing techniques such as rolling, while adequate for producing conventional electrical steel sheet, do have important disadvantages - large energy consumption and emissions, limitations in processing of low-workability alloys (e.g., high-Si content steels), large-scale plant infrastructure, and less than adequate capability to engineer sheet metals with specific microstructures (e.g., fine-grained) and crystallographic textures (e.g., shear textures). It is therefore of interest to have an alternative commercial process that can produce sheet/foil (strip) from high-Si Fe alloys and which can also overcome some of the deficiencies of current multistage strip processes. The goal of the present project was design and demonstration of a new energy-efficient pilot process for producing high-Si electrical steel strip of commercial widths and thickness, and with superior electrical and magnetic properties than current electrical steels (Fe-3.2% Si as benchmark). The applications domain for these steels is electrical motor core laminations. We have addressed this goal by accomplishment of the following specific objectives and tasks: a) Development of an Fe-4Si-4Cr alloy with electrical resistivity >80 μΩ-cm, induction flux density >1.48 T at 5000 A/m and core loss 35% lower than the benchmark 3.2% Si alloy. The alloy which meets DOE target specifications for motor core attributes was designed with the Si content controlled for the electrical properties and the Cr content tailored to meet material/process workability requirements. b) A unique machining-based deformation processing system was designed and scaled-up to produce strip of commercial width (25 mm to 150 mm) and thickness (up to 0.5 mm) from the Fe-4Si-4Cr alloy and other alloys of varied workability including copper, Al6061-T6 and naval brass. The key attributes of the machining-based strip production are deformation processing by concentrated simple-shear; single-step production of strip from ingot using compact machine infrastructure; strip surface finish of Ra 0.35 to 1 micrometer that is comparable/superior to that of rolled strip; discrete production of strip that can potentially be done at point of use; and controllability of strip mechanical/formability properties by deformation control. c) The electrical, magnetic, surface quality, mechanical, formability, and metallurgical properties/attributes of the machining-based strip were established by direct ASTM standard or equivalent measurement techniques. d) Punching characteristics of the strip in terms of load, edge quality and macro defects were similar to those of conventional 3.2% Si electrical steels. These punching characteristics are critical from a manufacturability perspective for motor/transformer core applications. e) A modeling framework for energy analysis of multistage rolling and the machining-based deformation processing has been established. Application of this modeling to the two strip-processes showed that the machining-based process requires significantly lower specific energy for processing, ~ 25% of that for rolling. The modeling framework can be adapted for a range of sheet-metal forming, bulk metal forming, and machining processes. It can be used to identify key parameters controlling process specific energy. f) A comparative analysis of advantages and disadvantages of machining-based processing against rolling for strip production. The single stage machining-based processing, with compact infrastructure, represents a new manufacturing paradigm for sheet and foil manufacturing that can potentially also be applied to advanced titanium, aluminum, copper and magnesium alloys. The goals and objectives were accomplished by a cross-disciplinary project team comprising of personnel from Purdue University; M4 Sciences LLC, a small-business focused on advanced manufacturing technology development; the Pacific Northwest National Labs; and tool manufacturers. The team is currently in advanced discussions with multiple entities for future process development for commercialization.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Laboratory-Scale Coal-Derived Graphene Process (Final Report)

The Energy & Environmental Research Center (EERC) conducted a laboratory-scale coal-derived graphene (CDG) project focused on developing a technological process for making graphene from four U.S. domestic coal or coal wastes, including lignite from North Dakota, subbituminous coal from Wyoming, bituminous coal from Utah, and anthracite from Pennsylvania. The project was divided into two performance or budget periods (BPs), with BP1 comprising the up-front laboratory experiments to make graphene materials from coal beginning on May 1, 2020, to April 30, 2022. BP2 was conducted from May 1, 2022, to April 30, 2023, and was focused on analyzing the CDG process economic feasibility and the technical gaps for technological scale-up and commercialization. During this project, a few different coal-derived high-value products have been demonstrated, including graphite, graphene oxide (GO), reduced graphene oxide (rGO), and graphene quantum dots (GQDs). A new graphite microstructure was discovered and named “croissant graphite” because of the exterior morphological and textural resemblance to croissant food items sold in commercial groceries stores. The new graphite structure and the associated preparation from coal or coal waste feedstocks has been the subject of a U.S. patent application. The systematic experimental processes involving coal cleaning, upgrading, and conversion to high-value carbon products culminated into a developed upgraded coal-to-products (UCP) technology that is being pursued for potential fast-track commercialization, if funding is available. It is envisioned that commercialization of the UCP technology would increase consumption of U.S. domestic coals or coal wastes to make environmentally sustainable high-value products for the electronics industry, high-energy-storage applications, and clean energy technologies such as electric vehicle (EV) lithium-ion batteries (LIBs), for which graphite has become a critical mineral commodity. Croissant graphite microstructures, when observed by field emission scanning electron microscopy (FESEM), display wavy surface morphology and often grow from a base that is made of graphitized particles with honeycomb-like layers, which are believed to be graphene layers. While more studies are needed to fully ascertain the mechanisms of the croissant graphite microstructure formation, it is postulated that their growth may begin from curling of the graphene sheets into ribbon-like structures, and continuous growth and densification of the ribbon-like structures forms croissant microstructures. Additional studies are ongoing to evaluate the electrochemical performance of croissant graphite for LIB applications and to determine the experimental conditions necessary to tune on/off croissant formation so that it can be either optimized or suppressed depending on performance evaluation results. In addition to the discovery of croissant graphite, the graphitization process from the four coal ranks in general was successful. X-ray diffraction (XRD) analysis showed that the degree of graphitization (DoG) ranged from 12% to 80% in an early sample set, and further optimization on lignite coal produces a DoG of about 92%, which was spectacular to see as lignite is the lowest-rank coal. Thus, it is expected that the graphitization performance for higher-rank coals will be similar or better when optimized as well. The coal-derived graphite was used to make GO and rGO. Analytical characterization, e.g., by methods such as Raman spectroscopy, XRD, Fourier transform infrared (FTIR) spectroscopy and FESEM, showed that the sequence of converting the coal to graphite, exfoliating it to GO, and then chemically reducing the GO to rGO was successful. Although coal naturally contains aromatic compounds and some relatively small-sized condensed aromatic units, it does not contain graphene sheets. In the UCP process, the aromatic domains in the coals, particularly low-rank coals, are concentrated and condensed further into graphene sheets, which are ordered into a 3D stack during graphitization. The synthesized graphite is then unpacked by methods such as exfoliation to various graphene products. GQDs were synthesized from all four coal types, and their optical properties were demonstrated to be tunable by the coal precursor preprocessing treatments. In all four coal types, enhanced optical properties were observed for the produced GDQs with incremental improvements made to the coal precursors. GQDs produced from raw coal samples displayed lower ultraviolet–visible (UV–Vis) spectroscopy absorbance intensity compared to those obtained from cleaned and upgraded coal residues. The photoluminescence (PL) intensities also varied with pretreatment conditions and with the concentration of GQDs in aqueous solutions. GQDs obtained from anthracite show longer emission wavelengths and can be excited by visible light as opposed to GQDs derived from the other coal ranks. UV fluorescence 3D maps and spectra revealed that the emission wavelength at which the GQDs solutions display the highest intensity was slightly redshifted based on the coal precursor pretreatments. In low-rank coal (lignite and subbituminous) samples, two clusters were observed in the maps for GQDs, which may suggest that there are potentially two types of fluorophores in solution or two main size populations. The ability to tune the properties of GQDs based on processing methods can be exploited to make GQDs for various optical display or optoelectronics applications. The results also highlight the importance of removing coal-borne impurities to improve the quality of the coal precursor for preparation of graphene products. Coal and/or coal wastes preprocessing methods were developed and applied to clean and upgrade the coal precursors prior to graphitization and subsequent conversion to graphene products. The preprocessing methods involve high specific-gravity separations, mineral acid cleaning (no hydrofluoric acid), and subsequent upgrading by reducing the coal-borne heteroatom (nitrogen, sulfur, and oxygen) content using proprietary chemical agents. Analytical characterization revealed that the preprocessing steps were successful, with ash reductions that range from 38% to 80% and residual ash content that was below the 5 wt% initial target. Based on proximate and ultimate analysis, the heteroatom reduction reactions produced upgraded coal residues with the oxygen content reduced by 8% to 24%, with additional reductions in the nitrogen and sulfur contents. An initial assessment of the waste streams from the UCP process shows very small to negligible environmental impact due to CO 2 , NO x , and SO x because most process steps are performed under inert atmosphere with argon. Consequently, reactive oxygen environments that tend to create these species are avoided. The inorganic and potentially hazardous species are released into aqueous waste streams that are easy to handle for proper disposal. The liquid waste streams were found to contain low-level concentrations of rare-earth elements (REEs), which could be concentrated and recovered as value-added by-products. Additionally, the volatile and gaseous fractions from carbonization and heat treatment contain useful organic compounds that can also be recovered as potential valuable by-products. Thus, the UCP technology is considered an environmentally sustainable and promising emerging technology for making high-value products from coal and coal wastes, with potential additional value-added by-products. Analysis of potential markets for the coal-derived carbon products shows a strong demand in both niche market sectors and across a wide variety of other industrial sectors. Graphite is currently considered a critical mineral commodity that has a large and growing demand in the LIB industry for EV applications. Based on data from Fortune Business Insights (2022) and Marketwatch (2023) reports, the average global graphite market is projected to reach about 33 billion by 2028, growing at a compound annual growth rate (CAGR) of about 7%, with much of this growth expected to be in the LIB industry. GO and rGO have strong market potentials in various application areas, such as coatings for anticorrosion, anti-icing, and antimicrobial protection, thermal barriers, wear resistance, sensors, additive manufacturing such as 3D inks, and others. GQDs are the emerging key player in the bioimaging, photovoltaics, and light-emitting diodes (LEDs) applications, with the potential to replace traditional semiconductor quantum dots (SQDs), which are based on metallic systems that are more toxic and more expensive. Biomedical applications of GQDs are becoming more attractive because of low to no toxicity and extremely low cost compared to SQDs. The major challenges for scale-up and commercialization of coal-derived carbon products such as graphene vary from the inherent attributes of graphene itself to reluctance to accept graphene in new manufacturing processes because of the uncertainty of the unknown. The 2D nature of graphene materials with a thickness of one atom presents significant challenges to proper handling/processing, and process scale-up becomes difficult because it requires high-end, expensive equipment, even for routine handling and analysis for quality assurance and control. Pristine graphene can also be extremely difficult to work into other matrices, thus hindering downstream processibility, especially at large scale. Currently, the cost of graphene and graphene products is still high and presents an economic risk that tends to slow down investment in scaling up emerging technologies. The lack of a standard for graphene materials for quality assurance and quality control poses a great challenge not only for the markets but also for commercialization efforts. A first-look economic feasibility analysis of the UCP technology provided valuable information that suggests the UCP process would be feasible, especially when it is scaled to a pilot scale and could be more competitive at the full scale. Graphitization was found to be the most energy-consuming and most capital-intensive step in the overall process. In small laboratory- and bench-scale experiments, labor is a significant contributor to the total process costs. Although these energy, capital, and labor constraints contribute to a higher selling price for the product, a preliminary economic model suggests that the process would be feasible at large scale when the process is fully integrated, optimized, and automated.

01 COAL, LIGNITE, AND PEAT↗