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DOE OSTI2025

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials using MALAMUTE

The Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy aims to develop and qualify additively manufactured materials for nuclear applications. One key challenge to this is the microstructural variability observed in the additively manufactured products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-throughput experimental and modeling techniques to accelerate qualification. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the additive manufacturing process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture microstructural variability is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning models to develop a digital twin for additive manufacturing that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation. The melting and subsequent solidification that occurs during the additive process is a complex phenomenon that requires multiscale multiphysics analysis. This work package focuses on understanding the role of process variabilities on the unique microstructural characteristics of additively manufactured materials. Microstructural features at the subgrain level, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. Idaho National Laboratory’s Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for additively manufactured materials in an efficient, reliable, and cost-effective way. This work focuses on capturing the microstructural variabilities at the subgrain level that are often missing in the part-scale models. In fiscal year 2025, we significantly advanced upon our work in the last fiscal year, in terms of the predictive capabilities of the physics-based and ML models, by adding the capabilities to capture subgrain-level micro-segregation during solidification using phase-field model and to predict the time-dependent dynamics of the AM process through the MOGPAR model. The alloy solidification model in MOOSE incorporates the thermodynamic properties and free energy relevant to 316 stainless steel. The model demonstrates the Cr and Ni segregation that occurs during solidification, including that the rate of solidification. The microstructural evolution model is connected to the process conditions via the surrogate model developed in this work. This enables predictions of the final microstructure in conjunctions with the manufacturing process. This work supports AMMT's rapid qualification goals by laying the foundation for an efficient and cost-effective model establishing the PSPP correlation for AM. The generated microstructures and predicted micro-segregation can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work helps to identify the key microstructural features at the subgrain level that are significant in property and performance predictions of additively manufactured components. This work will also provide inputs to the large-scale process variability models to reevaluate and validate assumptions and simplifications made in the part-scale models. Furthermore, through active learning this work can help identify the data need from both modeling and experimental sides for development of a robust digital twin for additive manufacturing and accelerate the AMMT's qualification efforts.

36 - MATERIALS SCIENCE↗

DOE OSTI2026

Solar Heat for Industrial Processes: Integration with Chemical Reactors

The integration of solar thermal systems with chemical reactors has been proposed as part of a larger effort to develop and deploy solar heat for industrial processes (SHIP) technologies. A strong motivation for SHIP processes and technologies is the potential for high thermal efficiency coupled with low-cost thermal energy storage (TES) which can enable commercial deployment of such systems. While there are different ways to categorize SHIP technologies, one important such distinction is between directly irradiated systems and indirect off-sun process driven by a SHIP system. While directly irradiated systems can provide high thermal efficiencies and high fluxes, they usually require complex engineering solutions due to the need for redesigning the established processes and unit operations. In most cases, it is also more challenging to couple such a process to a TES system, losing some of the benefits of SHIP. On the other hand, using a SHIP system to drive an industrial process off-sun can allow better integration with existing process chains, easier TES capabilities, and potential for more applications fitting a specific SHIP technology. However, the integration of SHIP systems with the industrial processes is not fully explored in detail, especially in the case of high-temperature processes such as reforming, cracking, cement manufacturing, and iron/steelmaking. Many of these systems require heating fluxes of >50 kW/m^2, supplied via combustion of hydrocarbons in a fire box and benefitting from radiative heat transfer between the flue gases and the reaction zones. As such, using SHIP systems for such processes is more complex than providing the same thermal input in the form of a heat transfer medium (HTM) entering the reactor, kiln, or furnace. Moreover, in case convective heat transfer using SHIP is envisioned, for example using supercritical CO2 as the HTM from a particle receiver, the thermal integration might be more challenging than initially envisioned: lower heat transfer coefficients and limited approach temperature might require large flow rates, causing a mismatch between the process thermal requirements and the thermal capacity of the SHIP system. In addition, even if the heat exchange between SHIP and reactor is effective, there is still a cold leg HTM at the reaction temperature or slightly below it. Chemical plants usually include a set of heat exchangers, heat recovery steam generators, and even power generation units - in a tightly integrated design - to recover the flue gases which are eventually vented. With SHIP systems mostly operating on a closed HTM loop, bottoming the cold leg is crucial. In this talk, we will present different modeling results for a variety of syngas production reactions, using catalytic and chemical looping processes, and discuss some of the challenges and design considerations for off-sun chemical reactors using SHIP systems.

14 SOLAR ENERGY↗

DOE OSTI2026

Opportunities and challenges in process modeling and simulation of electrochemical systems

Electrochemical technologies have garnered intense interest in both academic research and industrial applications due to their potential to increase energy efficiency and reduce carbon footprint. However, electrochemical process fundamentals have been absent from the chemical process simulators available to millions of chemical engineers worldwide. To expedite process research and development of electrochemical technologies in the chemical industry, it is imperative that essential electrochemical process fundamentals be incorporated into process simulators to support modeling and simulation of electrochemical processes. Here, this study examines three process fundamentals key to the research and development of electrochemical processes: electrochemical reaction kinetics, electrolyte thermodynamics, and heat and mass transfer. It further illustrates application of these process fundamentals with a case study modeling an electrochemical process for the conversion of acrylonitrile to adiponitrile. The modeling example highlights the roles of applied voltage on reaction rates, and electron flow rates on the performance of electrochemical processes. It suggests that the applied voltage and electron flow rates are two unique concepts that should be included in simulators for electrochemical processes.

09 BIOMASS FUELS↗

DOE OSTI2024

Barium stars as tracers of s -process nucleosynthesis in AGB stars

Barium (Ba) stars help to verify asymptotic giant branch (AGB) star nucleosynthesis models since they experienced pollution from an AGB binary companion and thus their spectra carry the signatures of the slow neutron capture process (s process). For a large number (180) of Ba stars, we searched for AGB stellar models that match the observed abundance patterns. We aim to uncover any systematic deviations of the sample abundances from the predictions of the nucleosynthesis models. We employed three machine learning algorithms as classifiers: a Random Forest method, developed for this work, and the two classifiers used in our previous study. Compared to that work, we also expanded our observational sample with 11 Ba stars available in the supersolar metallicity range. We studied the statistical behaviour of the different s-process elements in the observational sample to investigate if the AGB models systematically under- or overpredict the abundances observed in the Ba stars and show the results in the form of violin plots of the residuals between spectroscopic abundances and model predictions. We inspected the correlations between the observed [Fe/H], the s-process elemental abundances, and the residuals. We employed the [Zr/Fe] and [Nb/Fe] abundances as a thermometer to constrain the operational temperature that rules the production of these elements in the sample stars, assuming a steady-state s process. We also investigated the mass distribution of the identified polluter AGB stars and the behaviour of the δ parameter, which describes the fraction of accreted AGB material relative to the Ba star envelope. We find a significant trend in the residuals that implies an underproduction of the elements just after the first s-process peak (Nb, Mo, and Ru) in the models relative to the observations. This may originate from a neutron-capture process (e.g. the intermediate neutron-capture process, i process) not yet included in the AGB models of metallicity from solar to roughly 1/5 solar, corresponding to the range of the Ba stars. Correlations are found between the residuals of these peculiar elements, suggesting a common origin for the deviations from the models. In addition, there is a weak metallicity dependence of the residuals of these elements. The s-process temperatures derived with the [Zr/Fe] – [Nb/Fe] thermometer have an unrealistic value for the majority of our stars. The most likely explanation is that at least a fraction of these elements are not produced in a steady-state s process, and instead may be due to processes not included in the AGB models. The mass distribution of the identified models confirms that our sample of Ba stars was polluted by low-mass AGB stars (< 4 M ⊙ ). Most of the matching AGB models require low accreted mass, but a few systems with high accreted mass are needed to explain the observations.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Intensified biogas to liquid (IBGTL) Process: Experimental validation and modeling analysis

The Intensified Biogas to Liquid (IBGTL) process aims to overcome traditional economy-of-scale barriers in biogas-to-liquid fuel production by integrating bi-reforming and Fischer-Tropsch synthesis (FTS) in a single IBGTL reactor. This reactor operates at uniform pressure with different optimized temperatures across two zones for efficient conversion, utilizing multifunctional bi-reforming catalysts and high-temperature FTS catalysts. Bench scale experiments were carried out using landfill gas (LFG) in a single pass process, and the yield data from these experiments were fed into process scale-up design and techno-economic analysis (TEA) across four scenarios: (1) a single pass process, (2) a process with material recycling, (3) a process with liquefied petroleum gas (LPG) co-product recovery, and (4) a process with electricity generation from the fuel gas produced. TEA identified Scenario 2 as the most cost-effective, achieving a Minimum Fuel Selling Price (MFSP) of $\$4.59$ per gallon, competitive with the current national diesel price of $\$4.7$ per gallon. However, comparison with the conventional two-reactor system highlights the need for catalyst performance improvements. Sensitivity analysis emphasized the importance of manufacturing cost, liquid fuel yield, and biogas flow rate. Further analysis determined that the IBGTL process must achieve a diesel mass yield beyond 11.7% to surpass the economic viability of the conventional TriFTS (Tri-reforming followed by Fischer-Tropsch Synthesis) process. If the IBGTL process attains the TriFTS yield of up to 17%, the resulting MFSP could be approximately 31% lower than the current TriFTS MFSP. Furthermore, renewable energy credits and carbon credits can further enhance the economic viability of BGTL processes.

09 BIOMASS FUELS↗

DOE OSTI2025

Advanced electrode processing for lithium-ion battery manufacturing

Lithium-ion batteries (LIBs) need to be manufactured at speed and scale for their use in electric vehicles and devices. However, LIB electrode manufacturing via conventional wet slurry processing is energy-intensive and costly, challenging the goal to achieve sustainable, affordable and facile manufacturing of high-performance LIBs. Here, in this Review, we discuss advanced electrode processing routes (dry processing, radiation curing processing, advanced wet processing and 3D-printing processing) that could reduce energy usage and material waste. Maxwell-type dry processing is a scalable alternative to conventional processing and has relatively low manufacturing cost and energy consumption. Radiation curing processing could enable high-throughput manufacturing, but binder selection is limited to certain radiation curable chemistries. 3D-printing processing can produce electrodes with diverse architectures and improved rate performance, but scalability is yet to be demonstrated. 3D-printing processing is good for special applications where throughput and cost can be compromised for performance.

25 ENERGY STORAGE↗

DOE OSTI2026

Development of a Techno-Economic Analysis Framework for a Solar Thermochemical Fuel Production Process

Synthetic liquid fuels can provide a drop-in substitute for fossil-based fuels in sectors such as aviation and maritime, where electrification is not a viable option due to the need for high specific energy density. However, for these alternative fuels to be adopted at a commercial scale, their price must be competitive compared to their fossil-based counterparts. The reverse water-gas shift (RWGS) reaction offers a promising pathway, using hydrogen (sourced from electrolysis) and carbon dioxide as the feed and reacting to produce syngas - a mixture of H2 and CO at a specific ratio. Syngas is a useful precursor that can be converted into fuels and chemicals via known downstream processes, such as liquid transportation fuels via Fischer-Tropsch (FT) synthesis. The RWGS reaction is currently not applied in commercial scale, unlike the rest of the components in the process chain (electrolyzers and syngas-to-fuel synthesis units). The RWGS reaction poses several challenges due to its restrictive thermodynamics. Being an equimolar reaction, high temperatures and a large excess of H2 are needed to achieve reasonable CO2 conversion at equilibrium. This has detrimental effects on practical process implementation and the quality of syngas that can be produced, with direct effect on the energy and capital requirements, as well as the need for expensive downstream separation. In this work, we are proposing to develop a new concentrating solar thermal (CST) compatible RWGS reactor, performing the reaction in a 2-step chemical looping process using metal oxide at a temperature range of 600-800 degrees Celsius. By decoupling the reactor from the solar receiver, the Generation 3 (Gen3) CST technology could be utilized, together with its proposed thermal energy storage (TES) technology, benefitting from a good match to the required temperatures. CST technology is a viable option for supplying the heat that could be rapidly deployed in scale, thus being a good match to the gas-to-liquid (GTL) process which requires a large minimal scale to be commercially viable. The integration of TES with CST also allows operating the plant at large annual capacity factors and avoids multiple shutdown/startup cycles, thus fitting into the steady-state operation mode that most GTL processes require. The main innovation in the proposed design hinges on a countercurrent reaction design using a packed bed reactor. In 2019 Metcalfe et al. showed the benefits of countercurrent species exchange could be realized in a redox chemical-looping processes, by storing the favorable countercurrent chemical potential profiles in a packed bed of non-stoichiometric oxide. Metcalfe et al. applied this breakthrough concept to the WGS reaction, which is conventionally a co-feed catalytic process, showing a dramatic improvement. Bulfin et al. (2023) performed a similar proof-of-concept demonstration for the RWGS reaction using CeO2, achieving cumulative and peak CO2 conversions of 88% and 95%, respectively, compared to a thermodynamic limit of 58% for the co-feed catalytic process at the same conditions. In our new REGENLOOP project, we are developing a reactor prototype from the heat-exchange packed bed reactor-type, a commonly used reactor in the chemical industry. The endothermic heat of reduction will be supplied to the reactor using CST, while the same heat transfer fluid (HTF) mechanism will be used to extract the exothermic heat of oxidation. An array of multiple reactors is used to supply constant high-purity CO stream, that is then mixed with H2 from electrolysis to produce a high-purity syngas at the required composition. By removing the CO-CO2 separation after the RWGS process, significant energy and cost reduction can be achieved. A physics-based TEA framework is currently being developed, covering all the major plant processes, from the solar collection through storage, chemical looping RWGS, GTL, and auxiliary unit operations, up to the liquid hydrocarbon product. This modeling framework will utilize reduced-order models for the chemical looping RWGS and TES, CST modeling using SolarPILOT, and Aspen Plus for the GTL. By using this combined physics-based approach, the effects of design/operating parameters on the performance and cost can be elucidated. In our presentation, the modeling framework will be presented in detail, including preliminary cost predictions of using this plant configuration under a few selected relevant case studies. This study will be used to identify the major cost drivers, informing further system design and optimization needed to chart the way for a commercially viable pathway.

14 SOLAR ENERGY↗

DOE OSTI2024

Radiopaque particle processing additive

A radiopaque processing medium comprising a plurality of radiopaque particles and a non-radiopaque processing medium. The plurality of radiopaque particles is added to the non-radiopaque processing medium to increase a bulk density of the processing medium thereby forming the radiopaque processing medium. The radiopaque processing medium allows excess process media to be located and characterized during X-ray inspection of an electronic device on which the radiopaque processing medium was used. The radiopaque processing medium may also be used to locate and identify flaws/defects of the electronic device based on the location of excess radiopaque processing medium. The radiopaque processing medium may also be used as an underfill material to reinforce electronic chips soldered to the electronic device.

Diamond, Louis↗

DOE OSTI2025

Optimization of edge bead removal (EBR) process to enhance defect reduction in optical lithography

Defect reduction remains a critical objective in the integrated circuit manufacturing process, particularly within the highly re-entrant lithography modules where minimizing defects is crucial. Defects at the wafer edge can contaminate lithography modules and downstream processing equipment, leading to redistribution onto the wafer surface and adversely affecting overall device yield. A persistent challenge in the resist coating process is the formation of resist edge beads, driven by the strong Van der Waals attraction of excess photoresist (PR) to itself and the underlying substrate. The edge bead removal (EBR) process is a standard cleaning step designed to eliminate these edge beads and prevent potential contamination. Here, in this study, we identify the sources of EBR induced defects and additional EBR process encroachment toward edge patterning during the EBR cleaning process. This study provides a comprehensive study aimed at optimizing the EBR cleaning process to effectively eliminate EBR-induced defects, thereby enhancing overall device yield. Specifically, we identify three primary defects induced by the EBR cleaning process: rainbow-type, finger-shaped, and teardrop-type defects. Our experimental study reveals that in addition to EBR rinse time, PR cast time is crucial parameters contributing to the formation of these defects. By properly optimizing the PR cast time and EBR rinse time, we were able to remove nearly 100 % of dense clusters of defects that were easily visible even at low magnification optical microscopy throughout the wafer edge. We observed that shorter PR casting times shows edge defects caused by inefficient EBR process because of insufficient time for PR to fully settle causing superfluous PR to continue flowing toward wafer edge during EBR clearing step, leading to partial removal of PR at the wafer edge and the formation of rainbow defects. Proper optimization of both PR casting time and EBR chemistries dispense time is essential to resolve these defects, ensuring efficient EBR cleaning process and improved overall device yield.

42 ENGINEERING↗

DOE OSTI2025

Small-scale Assessment of Simplified Ceramic Waste Form Processing

The feasibility of directly processing glass-bonded sodalite ceramic waste form materials by heating a mixture of Zeolite 4A, chloride salt, and sodium borosilicate binder glass was demonstrated by generating laboratory-scale materials. This direct processing method eliminates pre-setting the moisture content of the Zeolite 4A, eliminates the step of occluding salt in the prepared Zeolite 4A prior to processing, and can be conducted using larger particle sizes of crushed Zeolite 4A and crushed borosilicate glass than those called for in the current method. These simplifications are expected to facilitate material transfer and handling in a hot cell or controlled atmosphere environment and be more readily implemented at large scale than the current method. Most materials made to assess these simplifications were directly processed at 925 °C for two hours in an argon atmosphere glovebox, but one material was processed at 925 °C for four hours and one material was processed at 880 °C for two hours. Sodalite was generated and became microencapsulated by the binder glass in all materials. The microstructures were uniform throughout each product, were similar in all products, and were similar to the microstructures of materials made previously using the pressureless consolidation or hot isostatic pressing methods. Various formulations showed the efficiency of sodalite generation was not sensitive to the salt-to-Zeolite 4A ratio or salt-to-glass mass ratio, although a greater relative mass of glass is required to encapsulate sodalite generated from large particles of aggregated Zeolite 4A. The upper limit of salt loadings that can be effectively processed remains to be determined. The effectiveness of direct processing provided new insights into the conversion mechanism. The salt was likely dissolved into the glass that transported NaCl into the Zeolite 4A aggregates and sodalite was generated in situ as NaCl migrated from the outside of the aggregate inward. Other salt cations (e.g., potassium, strontium, cesium, and probably lithium) remain dissolved in the glass encapsulating the zeolite/sodalite domains. When the glass solidifies during cooling, small halite inclusion phases form in glass within sodalite domains and large mixed salt inclusions form in glass surrounding the sodalite due to the low solubility of chloride in the (solid) glass. Other salt cations were oxidized during processing and formed inclusions in the bulk glass (e.g., neodymium). Initial degradation tests show the dissolution behavior of directly processed CWF (SCWF) materials is similar to CWF materials made using different methods.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Ion Exchange Processing of AW-105 Hanford Tank Waste through Crystalline Silicotitanate in a Staged 2- then 3-Column System

The Hanford Site stores an estimated 56 million gallons of mixed radioactive and chemically hazardous waste in large underground tanks. In support of the Direct Feed Low-Activity Waste (DFLAW) Program for expediting Hanford tank waste supernate treatment, laboratory-scale ion exchange processing using prototypic unit operations was conducted on AW-105 tank waste at the Pacific Northwest National Laboratory Radiochemical Processing Laboratory. This report describes the small-scale ion exchange testing with 9.2 L of diluted and filtered supernate from Tank 241-AW-105 (hereafter referred to as AW-105) at 16 °C (62 °F). One of the waste acceptance criteria (WAC) for the Waste Treatment Plant (WTP) Low-Activity Waste Facility is that the waste must contain less than 3.18×10 -5 Ci 137 Cs per mole of Na. For the AW-105 tank waste to meet this criterion, only 0.225% of the influent 137 Cs concentration may be delivered to the WTP; this requires a Cs decontamination factor of 445. Testing with AW-105 matched current Tank Side Cesium Removal (TSCR) facility prototypic operations where a lead-lag configuration was used until the lag column reached the WAC limit, then a polish column was brought online for continued processing in a lead-lag-polish column configuration. Feed was processed at 1.9 bed volumes (BVs) per hour; the flowrate, in terms of contact time with the crystalline silicotitanate (CST) bed, matched the expected flowrate at TSCR. The Cs-decontaminated product was retained for vitrification testing (to be reported separately). The lead column reached 83% Cs breakthrough after processing ~1500 BVs of feed; the 50% Cs breakthrough was interpolated from the breakthrough data and occurred at 1041 BVs. Despite the AW-105 having a significantly higher K concentration (0.55 M compared to 0.10 M), testing compared to previous AP-107 ion exchange column testing at 16 °C showed no difference in BVs processed to reach the WAC on the lead column and only an approximate ~20 BV decrease in volume processed to reach the WAC limit on the lag column. The negligible differences in capacity despite the 5x concentration differences in K was determined to be due to the significantly lower NO3 concentration in the AW-105 supernate compared to the AP-107 tank waste matrix. A comparison in breakthrough curves for the two tests also indicated slightly faster kinetic behavior in the AW-105, with the variations in feed matrices (lower NO3 concentration) likely responsible for the deviation. The Cs effluent from the lag column reached the WAC limit after processing 772 BVs. Anticipating this breakthrough point, the polish column was preemptively installed around 675 BVs. Cs breakthrough from the lag column began at 300 BVs, reaching 1.10×10 1 µCi/mL, or 14.13 % Cs breakthrough, after processing all 1500 BVs of feed. The polish column processed nominally 830 BVs and reached 2.10×10 -1 µCi/mL, or 0.27 % Cs breakthrough at the conclusion of the test. Table S.1 and Figure S.1 summarize the observed column performance and relevant Cs loading characteristics.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2026

Quantitative characterization of gradient microstructures: A study on friction stir spot processing of pure cobalt

Heterogeneous microstructures in polycrystalline metals can enhance the strength and ductility, outperforming homogeneous structures of similar composition. This study investigates deformed cobalt via friction stir spot processing with varying dwell times to uncover the effects of plastic deformation and heat generation on the formation of morphological, phase, and grain boundary character gradients. A new approach to quantify the morphological gradients in materials, which describes grain morphology in terms of density followed by parametric regression, enables direct quantification of processing depth and gradient sharpness. Results show that longer processing times increase the steepness of morphological gradients and reduce the deformation depth for friction stir spot processing with low plunge depths and high tool rotational speeds. The amount of retained FCC is increased in the shorter processing conditions, primarily due to refined grain size, increased defect content, and reduced heat generation. Crystallographic texture analysis of the HCP phase indicated a dominant B-fiber described by (0001) ∥ shear plane normal in the extreme processing conditions and the formation of a P-fiber, shear direction ∥ ⟨11$\bar2$0⟩ for intermediate dwell times. The texture of the FCC phase for low processing times was a C texture {100}⟨011⟩ where longer processing times were dominated by a [001] fiber texture with a main {110}⟨100⟩ orientation and emergence of a slight [111] fiber in the longest processing condition. The approaches outlined in this work give insight into quantifying gradients and improve the understanding of highly deformed cobalt.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Low embodied energy and carbon, high lifetime silicon boules via a combined chemical vapor deposition/float zone process

This work evaluates a new process route to making float zone (Fz)-quality silicon wafers using a combination of computational fluid dynamics (CFD) modeling and technoeconomic analysis. Our analysis finds that the new process competes with Czochralski (Cz)-grown wafers on a levelized cost of energy system level. The new process also decreases embodied energy and carbon of silicon photovoltaics (PV) by ~6x circumventing the energy-costly Siemens process used in polycrystalline silicon (poly-Si) production plants to generate feedstock for Fz and Cz boules. Instead of using poly-Si from the Siemens process to feed crystallization, the new process uses the high-purity, trichlorosilane (TCS) precursor gas to grow a poly-Si feed rod in-situ during a modified Fz1,2 boule growth process. The gas-to-boule float zone process enables opportunity to produce high-purity (low metals and oxygen content), uniformly doped single crystal silicon boules and wafers with high bulk lifetimes (τ bulk > 15 ms) to enable higher efficiency cells (>27 %) with fewer known degradation mechanisms than Czochralski (Cz)-grown wafers. These benefits reduce the levelized cost of electricity (LCOE) of PV-produced electricity. Here we show the results of our CFD and chemical modeling of the process to prove feasibility and economic viability.

14 SOLAR ENERGY↗

DOE OSTI2024

AN OVERVIEW OF PLASMA PROCESSING OF SRF CAVITIES AT JLAB

Plasma processing is a common technique where the free oxygen produced in a low-pressure RF plasma breaks down and removes hydrocarbons from surfaces. This increases the work function and reduces the secondary emission coefficient of the treated surfaces. Jefferson Lab has an ongoing R&D program in plasma processing. The experimental program investigated processing using argon/oxygen and helium/oxygen gas mixtures. The initial focus of the effort was processing C100 cavities by injecting RF power into the HOM coupler ports. We also developed the methods for establishing a plasma C75 cavities where the RF power is injected via the fundamental power-coupler. As part of the process development we processed, three C100 cryomodules in our off-line cryomodule test facility. In May 2023 we processed four C100 cryomodules in-situ in the CEBAF accelerator with the cryomodules returning to an operational status in Sept. 2023. The cumulative improvement in field emission free operation, as measured on a cavity by cavity basis, was 59 MeV or 24%. We recently started processing 7 cryomodules in the CEBAF accelerator in August 2024. Methods systems and results from processing cryomodules and individual cavities in the vertical test will be presented. Current status and future plans will also be presented.

Ganey, Tiffany↗

DOE OSTI2025

A Zero-Emission Process for Direct Reduction of Iron by Hydrogen Plasma in a Rotary Kiln Reactor

This project’s goal was to demonstrate a hydrogen plasma (H-plasma)-rotary kiln process for reducing iron ore to iron as part of the steel manufacturing process. The H-plasma provides a greater thermodynamic driving force for reducing iron ores than thermal processes such as the DRI process, enabling lower reaction temperatures. We estimated that our process technology can reduce energy consumption by 45% compared to the blast furnace process and ~15% compared to the DRI process. Steel manufacturing produces about 1.8 tons of CO2/ton of steel with iron ore reduction accounting for about one-third of the CO2 produced in the overall manufacturing process. We estimated our process has the potential to reduce GHG emissions from ironmaking by 35% with today’s grid and by up to 88% with a future low-carbon grid while being cost competitive with the current blast furnace route. We demonstrated reduction of hematite and magnetite rich materials at temperatures from 600 to 800°C. We achieved 90-95% metallization on 100 gr samples in batch reduction experiments in the H-plasma rotary kiln furnace at 600-650°C. Attempts to perform tests in a continuous operation mode identified problems with the ore feed mechanism. We identified solutions but there was not time nor budget to correct these for this project

36 MATERIALS SCIENCE↗

DOE OSTI2025

A Zero-Emission Process for Direct Reduction of Iron by Hydrogen Plasma in a Rotary Kiln Reactor

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Machine Learning-Based Process Control for Injection Molding of Recycled Polypropylene

The increased interest in artificial intelligence in manufacturing has driven the adoption of machine learning to optimize processes and improve efficiency. A key challenge in injection molding is the variability of recycled materials, which affects part quality and processing stability. This study presents a novel closed-loop process control approach for injection molding, leveraging machine learning to adaptively predict processing inputs and quality outcomes. The methodology was tested on five blends of recycled polypropylene (rPP), using artificial neural networks (ANNs), linear regression, and polynomial regression to model the relationships between material properties and process parameters. The dataset was split 80/20 into training and testing sets. The ANN model was implemented using TensorFlow and Keras, with six hidden layers of 32 neurons per layer, ReLU activation, and an Adam optimizer. Empirical tuning and early stopping were used to optimize performance and prevent overfitting. Predictions were evaluated based on mean absolute error (MAE), mean squared error (MSE), and percentage error. The results showed that yield stress, ultimate elongation, and part weight were accurately predicted within a 5% error for linear and polynomial regression models and within a 10% error for the ANN. However, modulus predictions were less reliable, with errors of ~11% for ANN and linear regression and ~40% for polynomial regression, reflecting the inherent variability of this property in rPP blends. Predictions of processing inputs had errors ranging from 3% to 25%, depending on the model and response variable. No single modeling approach was consistently superior across all responses, highlighting the complexity of the relationship between material properties, process parameters, and quality metrics. Overall, the work demonstrates that closed-loop process control, powered by machine learning, can effectively predict key quality parameters in injection molding of recycled materials. The proposed approach can improve process stability and material utilization, facilitating increased adoption of sustainable materials.

Krantz, Joshua↗

DOE OSTI2026

Rapid Characterization Tools for Process Optimization: Cooperative Research and Development (Final Report)

In this project Prenexus Health, Inc. (Prenexus) and NLR will develop rapid characterization tools to improve the Prenexus production process. First, we will develop a tool to predict the overall performance of the Prenexus manufacturing process converting high-fiber sugarcane to xylo-oligosaccharides (XOS) (both the overall process yield and the composition of the XOS product) using rapid characterization of the incoming feedstock and knowledge of key process parameters. This tool will dramatically increase Prenexus’ understanding of the overall process. Second, we will develop a tool to predict the concentration of soluble oligomeric and monomeric xylose and organic acids in multiple process streams at-line in the Prenexus process, enabling real-time process control of the conversion process.

09 BIOMASS FUELS↗