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Verification and validation of developed short-term forecasting models

Recent advancements in machine learning (ML) and artificial intelligence (AI) technologies provide an opportunity for leveraging data-driven algorithms to predict future nuclear power plant (NPP) operating conditions by using recorded plant process data. Successfully implementing these models can lead to cost-reducing, conditioned-based predictive maintenance through optimized maintenance schedules and a reduction of unnecessary maintenance activities. This report discusses the verification and validation of short-term forecasting processes (i.e., data cleaning, feature selection, model optimization, and forecasting) developed in previous reports. The verification and validation (V&V) process demonstrates the expected precision and accuracy when the ML model encounters new datasets from different systems. Shapley additive explanations were used as the primary means of feature selection across these different data set. Individual models were trained for each data set, then validated through a cross-validation procedure. In this report, two different ML models were tasked to predict variables from three different plant process data sets with varying prediction horizons. The results indicate that support vector regression (SVR) outperformed long short-term memory (LSTM) neural networks in regard to each data set and each prediction horizon in this study, but further tuning and optimization could improve long short-term memory results. However, each forecasting model showed reduced performance as the prediction horizon was extended from 1 hour to 1 day ahead. Research is ongoing to evaluate the optimal input variable space, which is based on a given set of process parameters, to further improve forecasting accuracy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Developing a Roadmap for Bio-Derivable and Recyclable Composites: Re-Design and Scale-Up Considerations

Composites, often in the form of fiber reinforced plastics, are used in multiple facets of modern life from snowboards to vehicles, to wind turbines and beyond. Despite their prolific, and often renewable energy related uses, they are currently subject to a linear material economy from emission intensive precursors; thus, there is an opportunity to re-design these materials to be both bio-derivable and recyclable. In the present work, we provide a roadmap of what application considerations must be considered for vacuum assisted resin transfer molding (VARTM) processes for large composites materials at scale (e.g. infusible viscosities, moderate cure times, proper fiber adhesion, low cost, and maximum peak exotherm) when implementing bio-derivable and recyclable materials. We also provide illustrative concepts utilizing polyester covalently adaptable networks, from epoxy-anhydride chemistry, to achieve these goals. We further provide considerations when developing recycling process (e.g. maintenance of fiber sizing and orientation) and demonstrate these practices using low temperature methanolysis. Accompanying technoeconomic and life cycle analysis further illustrate the decarbonization benefits to bio-derivable and recyclable thermosets while informing future research and recycling processes. Finally, we provide a brief introduction to synergistic work within our team exploring how to further decarbonize the manufacturing of these materials.

BIOMASS FUELS,ENERGY CONSERVATION, CONSUMPTION, AN↗

Demonstrate Viability of Accelerated Fuel Qualification Approaches

This presentation summarizes the research under LDRD grogram, Demonstrate Viability of Accelerated Fuel Qualification Approaches. It is demonstrated that the fabrication process of uranium carbide fuel has been developed and neutronic, thermal and hydraulic analysis have been conducted for the Fission Accelerated Steady-state Testing (FAST). This program provides basis of expansion of FAST as an efficient platform to broad nuclear fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Orthogonal Gelations to Synthesize Core–Shell Hydrogels Loaded with Nanoemulsion‐Templated Drug Nanoparticles for Versatile Oral Drug Delivery

Hydrophobic active pharmaceutical ingredients (APIs) are ubiquitous in the drug development pipeline, but their poor bioavailability often prevents their translation into drug products. Industrial processes to formulate hydrophobic APIs are expensive, difficult to optimize, and not flexible enough to incorporate customizable drug release profiles into drug products. Here, a novel, dual-responsive gelation process that exploits orthogonal thermo-responsive and ion-responsive gelations is introduced. This one-step “dual gelation” synthesizes core–shell (methylcellulose-alginate) hydrogel particles and encapsulates drug-laden nanoemulsions in the hydrogel matrices. In situ crystallization templates drug nanocrystals inside the polymeric core, while a kinetically stable amorphous solid dispersion is templated in the shell. Drug release is explored as a function of particle geometry, and programmable release is demonstrated for various therapeutic applications including delayed pulsatile release and sequential release of a model fixed-dose combination drug product of ibuprofen and fenofibrate. Independent control over drug loading between the shell and the core is demonstrated. This formulation approach is shown to be a flexible process to develop drug products with biocompatible materials, facile synthesis, and precise drug release performance. This work suggests and applies a novel method to leverage orthogonal gel chemistries to generate functional core–shell hydrogel particles.

60 APPLIED LIFE SCIENCES↗

Homogeneous CuGaSe 2 growth by the CuPRO process with In-Situ AgBr treatment

Homogeneous CuGaSe 2 thin film growth is limited by slow kinetics of formation. A modified growth process was previously developed to address this issue but requires two separate long, high temperature anneals. Here, we demonstrate that a short AgBr treatment can replace this modified growth process. The AgBr works as a transport agent to catalyze CuGaSe 2 formation and atomic mobility. Furthermore, this treatment results in large grains with homogeneous composition through the bulk. Solar cells made with this material show better performance.

14 SOLAR ENERGY↗

High-Efficiency and Low-Carbon Energy Storage and Power Generation System for Electric Aviation

This report summarizes the work performed by University of California San Diego (UCSD) – Honeywell Aerospace (Honeywell) team for the U.S. Department of Energy/Advanced Research Projects Agency-Energy (DOE/ARPA-E) under Phase 1 (April 2021 – October 2023) project, Cooperative Agreement DE-AR0001347 entitled “High-Efficiency and Low-Carbon Energy Storage and Power Generation System for Electric Aviation”. The main objective of this project is to develop and demonstrate an energy storage and power generation (ESPG) system operating on bio liquid natural gas (LNG) for electric aviation applications. The ESPG system concept in this project is a fuel cell, battery, and gas turbine hybrid system that incorporates an innovative solid oxide fuel cell (SOFC) technology. This SOFC technology has two main novel elements: (i) a lightweight and compact stack architecture that consists of cells and cell modules in electrical parallel and series connections (the module design) and (ii) exceptionally high performance, direct methane thin-film cells on porous substrate made by sputtering deposition process. This fuel cell has the specific power and volumetric power density suitable for electric aviation applications. Based on the current status of the SOFC technology, the Phase 1 work focused on the following activities: (i) ESPG System Modeling – to design and optimize an aircraft SOFC-based ESPG system concept that met the performance, weight and cost targets; (ii) Cell Material Development and Scaleup – to demonstrate scalability of the sputtering process for manufacture of thin-film SOFC cells of practical sizes, confirm the exceptional performance of sputtered cells, improve cell stability and durability for operation with hydrogen and methane fuel, and develop a suitable electrically conducting porous substrate to replace the current non-conducting ceramic substrate; (iii) Stack Development – to design and manufacture stack components for the stack architecture, evaluate and select a suitable sealant, and build and operate multi-cell stacks to demonstrate stack operation, and (iv) Technology to Market – to develop business models and commercialization plans, conduct various market and technology analysis and estimate SOFC and ESPG system costs.

25 ENERGY STORAGE↗

Pilot-Scale Testing of an Integrated Circuit for the Extraction of Rare Earth Minerals and Elements from Coal and Coal Byproducts Using Advanced Separation Technologies

The primary objective of this project was to develop and demonstrate an integrated pilot-scale circuitry for recovering high-value rare earth elements (REEs) from coal and coal byproducts. The target performance was to produce a mixed REE product with content of at least two percent by weight on a dry mass basis in a cost-effective and environmentally benign manner. During the first nine months of the project period (Phase 2 Budget Period 2), pilot plant construction was completed including all field site startup activities such as permitting, engineering design, procurement/bidding, unit fabrication, site construction, equipment installation, module assembly, safety training, and circuit shakedown. During the remaining 21 months of project period (Phase 2 Budget Period 3), detailed field-testing activities were performed including feedstock sample collection and preparation, exploratory testing, circuit modification, detailed parametric study, and performance optimization. A detailed techno-economic analysis was performed based on the pilot plant testing findings which provided various scenarios for REE production. The project successfully accomplished the proposed target performance by producing mixed rare earth oxide (REO) with greater than 90% purity by weight in a continuous pilot scale operation from two distinctly different coarse refuse materials (i.e., West Kentucky No. 13 and Fire Clay coal seams), and at least three secondary sources (i.e., heap leach process and naturally formed acid mine drainage system). Project partners included the University of Kentucky, Virginia Tech, West Virginia University, Alliance Coal, Blackhawk Mining, Mineral Refining Company, and Mineral Separation Technologies. The pilot scale test facility was constructed at a former mining complex owned by Alliance Natural Resource Partners (Alliance Coal). The site was rehabilitated to accommodate the equipment installation, construction and fabrication, electrical power requirement, water line management and containment. The process units constructed and installed included X-ray sorting unit, crushing and grinding unit, physical separation unit, acid leaching unit, solvent extraction unit, and wastewater management unit. A rare earth mineral concentration unit was constructed as a standalone unit for flexible operation. A detailed environmental assessment and control plan was carried out to identify and quantify any potential impacts of the pilot-scale processing circuitry on the human and eco-system health and well-being. Corresponding mitigation strategies and control measures were provided. A conceptual flowsheet was developed to effectively remove thorium and uranium from high purity rare earth oxide mix or any potential radionuclide enriched stream. The two distinct feedstock materials were secured from the Blackhawk Mining Complex in eastern Kentucky where the Fire Clay (Hazard No. 4) seam is processed. The West Kentucky No. 13 (Baker) coarse refuse material was collected from an active process stream at an Alliance coal preparation plant located in western Kentucky. Characterization analysis indicated that both of feed materials generated from the two sources contained >300 ppm of TREEs on a dry whole mass basis which met the requirements for a qualified feed stock. The two feedstocks were further upgraded using a dual x-ray sorter to prepare the feed material for hydrometallurgical circuit. Thermal treatment on feed material prior to leaching was found to: 1) improve the leaching recovery of REEs, 2) increase the leaching kinetics, and 3) allow the leaching reaction to occur at lower acidity. Roasting at 600°C was selected as the pre-treatment condition for both West Kentucky No. 13 and Fire Clay coarse refuse material. Over 40% of leaching recovery was achieved by roasting West Kentucky No. 13 material having a top particle size of 3 mm in the pilot scale operation using 1.2M sulfuric acid leaching at 75OC. Initial pilot scale testing involved continuous operation of the pilot plant for 94 hours. The leaching unit was operated at solid-to-liquid ratio of 1 to 10 (w/v) using 0.5M sulfuric acid solution at a temperature of 75°C. The continuous solvent extraction circuit utilized rougher and cleaner units with DEHPA and TBP as the extractants. An innovative stripping circuit was developed to accumulate the REE concentration in the stripping solution to a level above 600 ppm. A bleed stream from the recycled strip solution was treated using oxalic acid precipitation which produced a high grade rare earth oxalate. The oxalate product was roasted to remove the oxalate which produced a rare earth oxide product having a purity greater 90%. Due to high concentrations of contaminant ions in the pregnant leach solution (PLS), a modified flowsheet was developed that involved pre-concentration of the REEs using multiple stages of precipitation and redissolution. The advantage of this process was improved removal of contamination before the downstream purification process and a significant cost reduction relative to the circuit that utilized the solvent extraction process. The modified circuitry included processes involving leaching, multistage precipitation, redissolution, and oxalate precipitation followed by roasting of the oxalate product. The circuit produced a mixed REO that was 92.96% pure from the initial test. A detailed parametric test plan was carried out which involved varying key parameters including solids feed rate, acid flowrate, acid concentration, multistage precipitation pH, redissolution pH, oxalate precipitation dosage and pH. The response variables included REE recovery, contaminant recovery, REO product grade and overall chemical consumption. Test results indicated that the acid-to-solid ratio is the key parameter to leaching efficiency as performance deteriorated with an increase in solids concentration. The optimal pH determined for REE precipitation and redissolution was 6.5 and 2.5, respectively. Additional tests were conducted to further improve the flowsheet. Recirculating a portion of the PLS to the feed of the leach tanks improved the leaching performance by lowering the pH of the leaching system and reducing the contamination recovery by shortening the residence time. Moreover, the removal of Al prior to REE precipitation significantly reduced the oxalic acid consumption in the oxalate precipitation circuit. The modified circuit produced over 90% grade REO by weight from both West Kentucky No. 13 and Fire Clay coarse refuse material in pilot scale continuous test programs. A case analysis model was developed to project the REE and major contaminants concentration in each PLS stream based on the leaching condition, pH cut point, and oxalic acid dosage. A correlation was established using empirical and semi-empirical models. Using the models, chemical consumption required for each stage was predicted based on the projected performance of the hydrometallurgy circuit. After identifying the optimum conditions, validation tests were carried out for the treatment of both West Kentucky No. 13 and Fire Clay coarse refuse materials in the pilot plant. The actual circuit performance and chemical consumptions were very close to the model predictions. Other than the two coarse refuse sources, several secondary feedstocks were also tested in the pilot plant facility. A “heap leach” system was constructed using the coarse refuse material generated from cleaning the West Kentucky No. 13 seam coal. Using the two stage SX rougher and cleaner circuit, a concentrate with a grade >90% REO was produced while recovering >97% of the REEs from the heap leach PLS. Naturally generated acid mine drainage (AMD) from West Kentucky No.13 mine was processed using the multistage precipitation circuit in the pilot plant in a test conducted for a period of 32 hours. The final grade of the mix RE oxide produced from the AMD was 90.84% with an overall circuit recovery of 64%. The primary source of REE was the selective precipitation steps involving iron and aluminum rejection. The hydrophobic-hydrophilic separation (HHS) process was proven to effectively recover coal from fine waste materials. For REM recovery, the HHS process was able to produce concentrates at grades of approximately 1.8% REE on an ash basis; however, recovery values were typically low, <10%, under the optimal conditions determined in the laboratory-scale testing. Staged testing of the pilot-scale HHS process for coal recovery and semi-continuous laboratory testing for REM testing showed that a total concentration ratio of more than 15x was observed for the REM recovery process. A circuit simulation package was developed for REE extraction and purification using a spreadsheet-based platform (Microsoft Excel). The REESim circuit simulation package is configured to track the mass and volume flows of components passing through a series of unit operations specified and configured by the user. The mass rates can then be utilized by the user to determine important performance indicators such as product mass yields, concentrate purity levels, element-by-element recoveries, and so forth. The techno-economic analysis showed that the roasting and leaching operations were the most expensive capital items, each contributing approximately 30% to the total capital cost. One notable contributor to the high production costs was the low REE recovery observed in the pilot scale trials. The product basket price was shown to have a strong influence on the economic viability of the scenarios, with the scandium price being the most significant influencer. Operating cost was shown to be extremely sensitive to REE recovery, REE feed grade, and leaching acid consumption. An analysis of ten different scenarios for a 500 t/h commercial operation revealed that three were economically favorable, producing internal rates of return varying from 27.7% to 33.1% and payback periods of 4 to 5 years. The project successfully developed and demonstrated a process to recover REEs from coal and coal byproducts in a pilot-plant operation which consistently produced over 90% grade REO mix from varies types of feedstocks. Commercialization analysis showed that the technology readiness level successfully achieved TRL 6 at the end of the project and demonstrated the need and the potential for scaling the process to further advance the technologies toward the goal of providing a domestic supply of REEs at a commercial scale.

01 COAL, LIGNITE, AND PEAT↗

Even Higher-Level Synthesis: An Exploration of AI Hardware Accelerators using HLS4ML

With the rise of artificial intelligence, the popularization of deep learning, and a constantly evolving industry, the demand for flexible and efficient tools has never been greater. As algorithms grow more complex, their runtime and energy consumption increase exponentially. Customized hardware accelerators, long used for specific mathematical operations, remain essential for managing modern applications' computational and power demands. Hardware accelerators can speed up complex computations by orders of magnitude, but their manual design and verification processes are often challenging and time-consuming. High-Level Synthesis (HLS) provides a solution by transforming high-level algorithm descriptions, typically written in C++ or SystemC, into synthesizable RTL suitable for hardware implementation. This approach reduces development time for RTL engineers while offering flexibility beyond what traditional handwritten RTL can provide. We extended this capability to the machine-learning domain with the open-source framework hls4ml, which allows neural networks trained in Python frameworks like Tensorflow or PyTorch to be synthesized into efficient hardware representations for the traditional FPGA and ASIC flows. This breakthrough addresses the growing need for reduced design turnaround and easy verification of ML hardware accelerators with low latency and power efficiency constraints. During this tutorial, we will demonstrate how Python complements HLS by simplifying the ML design process, bridging the gap between software and hardware development. Attendees will explore how we translate neural networks modeled in Python into fixed-point C++ models suitable for HLS workflows. We will dive into strategies like Value-Range Analysis and Quantization-Aware Training, which optimize these designs for deployment and evaluate their accuracy, power consumption, and energy efficiency. To exemplify these concepts, experts from Fermilab will share their experiences applying this technology to high-energy physics experiments, where real-time, low-latency processing is critical. Over the years, Fermilab engineers have demonstrated how deep neural networks, optimized for hardware using hls4ml, can meet the stringent requirements of trigger systems at the CERN Large Hadron Collider. These systems rely on rapid decision-making to process immense data volumes while retaining only the most relevant events for further analysis. The application of hls4ml has also been extended to innovative technologies like smart pixel arrays. These smart pixels integrate ML inference capabilities directly into sensor devices, enabling localized data processing at the pixel level. This approach drastically reduces the need to transmit raw data to external processing units, significantly decreasing power consumption and latency. By embedding neural networks within the pixel architecture, the smart pixels can identify and prioritize relevant data in real time, providing a highly efficient solution for edge computing in scenarios such as particle detectors and imaging systems. Fermilab's work highlights the potential of hardware-accelerated ML in scenarios where both speed and power efficiency are mission-critical. Through this tutorial, attendees will gain valuable insights into the challenges and solutions of deploying ML in hardware. Understanding how HLS and hls4ml streamline the development of neural network-based hardware accelerators is fundamental for the industry's future. Participants will learn how these technologies are shaping the future of AI and scientific computing.

Di Guglielmo, Giuseppe [Fermilab]↗

Assessment of Process Modeling Tools for Determining Variability in Additively Manufactured Parts

The Advanced Materials and Manufacturing Technologies (AMMT) program aims to accelerate the development, qualification, demonstration, and deployment of advanced materials and manufacturing technologies to enable reliable and economical nuclear energy However, the unique aspects of additive manufacturing (AM) materials in terms of their processing history, microstructure, and properties, are a major barrier for qualification and certification of nuclear components. Much of this challenge may be attributed to component scale variations in microstructure and properties that are driven by local influences of process conditions and geometry on thermal history, melt pool dynamics, and corresponding microstructure evolution. Computational modeling tools may be helpful in this regard to aid in predicting and controlling this level of variability. The purpose of this report is to review the current state-of-the-art for process modeling with regards to metal AM. For this purpose, we consider specifically the case study of laser powder bed fusion (LPBF) processing of SS316, a family of alloys that are both commonly used in nuclear energy applications and suitable for AM processing. The report first introduces the necessary components of a process modeling workflow, followed by a review of the current status of each. At the end, application of these modeling tools to understanding variability in AM process given their current state are considered, and recommendations for future development are proposed

36 MATERIALS SCIENCE↗

Novel Electrowinning Reactor for the Energy-Efficient, Low- Cost Production of Rare Earth Metals

This project developed a novel neodymium (Nd) electrowinning reactor for energy-efficient electrowinning of Nd metal. Throughout this project we have developed an alternative chloride based molten salt electrolysis process. Our process lowers the specific electrical energy consumption compared to the state of the art, while producing reusable chlorine gas and eliminating direct CO2 and PFC emissions. Facilities required for implementing the project were setup and designs were finalized, and a standard operating procedure for safe operation of high temperature electrolysis cells was written. The electrowinning reactor was designed and constructed. Electrolysis experiments confirmed the ability to reproducibly electrowin Nd metal on a Mo cathode. The current efficiency for Nd electrowinning was measured as a function of applied current density in the presence of the separator. Successful electrowinning of Nd sponge at high current densities (200 mA/cm2 and above) at a current efficiency >80% was demonstrated using multiple techniques. Stable Nd electrowinning up to 10h at 250 mA/cm2 was demonstrated. All of these design advancements were used to develop a techno-economic and life cycle assessment model that demonstrated that our process could be operated at cost of less than $0.20/kg-Nd (~30% lower compared to state of the art when comparing electrolysis energy cost) with a >20% total reduction in global warming potential compared to the state of the art while generating no direct CO2 or perfluorocarbon emissions.

42 ENGINEERING↗

Dual-Purpose Canister Filling Demonstration Project Progress Report

This report discusses the initial progress made at the Oak Ridge National Laboratory to support direct disposal of dual-purpose canisters (DPCs) using filler materials to demonstrate that the probability of criticality in DPCs during disposal to be below the probability for inclusion in a repository performance assessment. In the initial phase of a multi-phase effort that will result in a full-scale demonstration, a computational fluid dynamics (CFD) model was developed to gauge the filling process and to uncover any unforeseen issues. The initial filling simulations of the lower region (mouse holes) of a prototypic DPC show successful removal of the inner space voids and smooth, even progression of the liquid level. In the initial phase, flow through a pipe that is similar to the drain pipe in a DPC will be investigated separately to gain valuable insight of flow regime inside a pipe. The initial experimental setups for validating the computational filling model have been designed, and the various assembly parts are being procured. The experience gained from the initial experiments will be applied to the next steps toward a full-scale demonstration and to the validation of multiphysics filling simulation models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Tank Waste LDR Organics Data Summary for Sample-and-Send (Rev.1A)

The presence of organic chemicals regulated under the Resource Conservation and Recovery Act (RCRA) Land Disposal Restrictions (LDR) adds complexity to treating and disposing of the low activity fraction of Hanford tank waste if a low temperature treatment method such as grouting is used (SRNL-STI-2020-00228). The complexity arises from the fact that the baseline vitrification method is considered by the Washington State Department of Ecology (Ecology) as providing adequate thermal treatment for organics; a status not automatically extended to a lowtemperature process, such as solidifying the waste in a cementitious waste form. In addition, the Environmental Protection Agency (EPA) LDR program is intended to ensure that wastes are properly treated prior to disposal. Proper treatment makes hazardous waste less harmful to groundwater by reducing the mobility and/or toxicity of the hazardous constituents in the waste. EPA guidance indicates that stabilization/solidification of waste for organics could be considered impermissible dilution under the LDR dilution prohibition. In addition, waste storage activities at Hanford have required transferring and blending waste within the tank system and these activities have potentially altered the concentrations of the hazardous constituents. The LDR dilution prohibition found in 40 Code of Federal Regulations (CFR) 268.3 states that “… no generator, transporter, handler, or owner or operator of a treatment, storage, or disposal facility shall in any way dilute a restricted waste or the residual from treatment of a restricted waste as a substitute for adequate treatment …”. Hence, if LAW is to be treated using low temperature stabilization (such as cementation), then it is important to demonstrate both how past storage activities have contributed to the removal (by vacuum evaporation), or destruction (by in situ decomposition) of the LDR organics and how future retrieval and waste feed preparation will contribute to their removal (by filtration and ion exchange). Demonstrating these processes helps validate that cementation without additional organic treatment does not necessarily represent impermissible dilution. To aid in implementing cementitious solidification of Low Activity Waste (LAW), WRPS has been developing a regulatory and processing LDR treatment variance strategy termed “Sampleand-Send” that relies, in part, on demonstrating that in situ decomposition reactions along with historic evaporation of tank waste has destroyed or removed most of the LDR organics possibly associated with Hanford Tank Waste (SRNL-STI-2020-00582, SRNL-STI-2021-00453, SRNL-STI-2022-00391). Under the Sample-and-Send concept, Hanford tank waste would be retrieved, processed through a Tank-Side Cesium Removal-like system, and staged as a candidate feed that would then be sampled to confirm the waste acceptance criteria is met for solidification in an LAW cementitious treatment facility. If it can be shown that LDR organics are at concentrations below the waste acceptance criteria (WAC) for cementitious stabilization and have been sufficiently removed (by historic evaporation or by filtration and ion exchange during Cs removal), destroyed (by historic in situ decomposition), or are not soluble in LAW above the WAC then additional organic treatment is not needed prior to creating a cementitious final waste form and the concept of Sample-and-Send would be proposed to establish a non-rulemaking site-specific treatment variance using the specified method of treatment “STABL” to remove sampling requirements of the waste form after treatment. Waste not meeting the WAC could either be routed to the Hanford Waste Treatment and Immobilization Plant for LAW vitrification, or further processed by evaporation or chemical oxidation before solidifying in a cementitious waste form. A key component in implementing the Sample-and-Send strategy is identifying which of the 207 LDR organic compounds associated with the RCRA Part A permit application waste codes for the Double Shell Tanks (DSTs) and Single Shell Tanks (SSTs) and any applicable Underlying Hazardous Constituents (UHCs) from 40 CFR 268.48 should be considered as potentially present and thus subject to regulation. In addition, it is also necessary to understand the solubility volatility, and reactivity of these compounds in LAW to identify which of the potentially present LDR organic compounds are not soluble above regulatory levels or are likely to have been removed by historic evaporation or destroyed by in situ decomposition reactions. If there are potentially present LDR organic compounds that have not been removed or destroyed and are soluble above regulatorily significant concentrations then a treatability variance may be needed for these species to eliminate any concerns pertaining to impermissible dilution. The spreadsheet accompanying this calculation report contains the data and logic computations needed to screen the list of 207 LDR organics associated with Hanford tank waste to identify those potentially present and to indicate which compounds may need to be included in a treatability variance.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Bringing Automated Fault Detection and Diagnostics Tools for HVAC&R Into the Mainstream

Heating, ventilation, and air-conditioning (HVAC) systems consume over 5 quads of energy annually, representing 30% of energy consumption in the U.S. commercial buildings. Additionally, commercial refrigeration (R) systems add about 1 quad to commercial buildings energy consumption. Most HVAC systems operate with one or more faults that result in increased energy consumption. Fault detection and diagnostics (FDD) tools have been developed to address this national issue, and many tools are commercially available. FDD tools have the potential to save considerable energy for an existing commercial rooftop unit (RTU) and refrigeration systems. These devices can be used for both retro commissioning and, when faults are addressed, continuous commissioning. However, there appears to be multiple market barriers for this technology. Although there are efforts to develop FDD tool standards, currently there are no standards and methods to define functions, capabilities, accuracy, and reliability of FDD tools in the field. Moreover, most of the commercial FDD tools have not been verified in the field independently. This paper presents a comprehensive approach for bringing HVAC FDD tools into the mainstream. The approach involves demonstrating ten commercially available FDD tools installed at ten different sites, independent testing and evaluation of the FDD tools, communication with various stakeholders, identifying and assessing market barriers, creating a process evaluation methodology, and assisting utility companies in developing incentive programs. Furthermore, the preliminary baseline results from the case study demonstrate how the use of an independent monitoring system (IMS) can be used for ground-truth in evaluating FDD tools in the field.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Melt pool temperature measurement and monitoring during laser powder bed fusion based additive manufacturing via single-camera two-wavelength imaging pyrometry (STWIP)

Melt pool (MP) temperature is one of the determining factors and a key signature for evaluating the properties of printed components in metal additive manufacturing (AM). The state-of-the-art measurement systems are hindered, primarily by the large-scale data acquisition and processing demands. In this work, we introduce a novel coaxial, high-speed, single-camera two-wavelength imaging pyrometer (STWIP) system as opposed to the typical utilization of multiple cameras for measuring MP temperature profiles in laser powder bed fusion (LPBF) processes. Developed on a commercial LPBF machine (EOS M290), the STWIP system demonstrated its ability to quantitatively monitor the MP temperature and its variation for 50 layers at high framerates (>30,000 fps) for a real-world application (standard fatigue specimens) print. High performance computing is employed to analyze the acquired big data (MP images), for determining each MP's average temperature and 2D temperature profile. The MP temperature evolution in the gage section of a fatigue specimen is also examined at a temporal resolution of 1 ms, by evaluating the MP temperatures in the samples' first, middle, and last layers. This report is the first of its kind on monitoring MP temperature distribution and evolution at such a large, detailed scale for longer durations in practical applications.

42 ENGINEERING↗

Insights into Preceramic Polymer-Based Additive Manufacturing Inks via Rheological and Scattering Studies of Preceramic Polymer-Grafted Nanoparticles Suspended in Polycarbosilane

Preceramic polymers (PCPs) offer advantages in producing ceramics due to their processability and ability to tailor the final chemistry of the produced material. However, challenges such as volumetric shrinkage and mass loss during pyrolysis often result in polymer-derived ceramics containing pores and cracks. PCP-grafted ceramic nanoparticles (PCPGNPs) have been proposed and studied as a route to mitigate the shrinkage issues associated with neat PCPs. Prior studies on PCPGNPs have principally focused on the synthesis and characterization of neat materials. Dispersing PCPGNPs in commercial preceramic polymer is another attractive, but underexplored, route to control the rheological and char yield properties of PCP systems. In this work, a systematic rheological study of commercial PCP (SMP-877) and PCPGNP (silica with poly(1,1-dimethylpropylsilane) corona) mixtures was executed to develop design rules for the processing of such systems. A rheological study demonstrated the effect of increasing particle concentration on network formation with percolation occurring between 50 and 60 wt %. Samples above the percolation threshold exhibited higher viscosities and rapid shear thinning thus demonstrating their direct-write printability. X-ray photon correlation spectroscopy (XPCS) corroborated the rheology and showed two diffusive modes when the material was above percolation. Mixtures of PCPGNPs and SMP-877 had synergistically higher char yields upon thermal treatment and pyrolysis. XPCS and rheological measurements during thermal treatment identified thermal jamming of the polymer grafts as a key factor in improving the char yield. In conclusion, with the insights gained here, we expect these mixed systems to provide attractive feedstocks for polymer-derived ceramics, with proof-of-principal application as feedstocks for direct ink write (DIW) additive manufacturing.

36 MATERIALS SCIENCE↗

Unraveling the Formation Mechanism of a Hybrid Zr-Based Chemical Conversion Coating with Organic and Copper Compounds for Corrosion Inhibition

Environmental-friendly chromate-free, zirconium (Zr)-based conversion coating is a promising green technology for corrosion protection. Additives in the surface treatment provides critical functionalities and performance improvements; however, mechanistic understanding as of how the additives influence the coatings remains unclear. In this study, a new organic-inorganic hybrid Zrbased conversion coating which combines copper (Cu) compounds and polyamidoamine (PAMAM), taking advantages of a complementary nature of organic and inorganic additives. Here, a multimodal approach combining electron and X-ray characterization is applied to study the interaction of Cu 2+ and PAMAM and the resulting impacts on the coating formation. Adding PAMAM changed the surface morphology, thickness, distribution of Cu in the cluster and void formation of the coatings. High PAMAM (100-200 pm) leads to little conversion coating formation, and low PAMAM (0-25 ppm) shows voids formation under the coatings. Moreover, PAMAM incorporates in the coating in a form of PAMAM-Cu complex with a higher concentration towards the surface, provides an organic layer at the surface of the coating. X-ray absorption near-edge structure (XANES) spectroscopy shows a difference between the conventional and hybrid coating treatments in an alkaline solution to simulate the E-coat process, suggesting the contribution of PAMAM in the enhanced chemical stability in an alkaline environment. Therefore, an intermediate range of addition of PAMAM (50 ppm) is optimal to 1) avoid excessive voids formation, 2) promote some Cu cluster formation and thus enhancing the Zr-based coating formation and 3) incorporate organic components into the coating to improve the adhesion of the subsequent coatings. Overall, this work furthers our knowledge on the formation mechanism of an effective and environmentally friendly hybrid conversion coating for corrosion inhibition, demonstrating a critical processing-structureproperty relationship. This study will benefit future development of green and effective surface treatment technology.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Cost-optimized Automated Variance Reduction for Highly Angle-dependent Radiation Transport Analyses [Dissertation]

Monte Carlo variance-reduction techniques that directly bias particle direction have historically received limited attention despite being useful for many radiation transport applications such as those in which radiation travels through large regions with a low probability of colliding. One such technique is known as DXTRAN (short for deterministic transport) in the MCNP Monte Carlo radiation transport code. Until now, effectively applying DXTRAN in calculations is largely based on empirical observations of computational performance. Optimal DXTRAN parameters are identified through manual iteration. This work develops new mathematical descriptions of the DXTRAN variance-reduction process and demonstrates a new automated variance-reduction method that applies these mathematical formulations to determine the optimal application of DXTRAN in a given problem.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Synergistic Thermo-Microbial-Electrochemical (T-MEC) Approach for Drop-In Fuel Production from Wet Waste

This project successfully developed and demonstrated the synergistic thermo-microbial-electrochemical (T-MEC) process, converting food waste into sustainable biofuels while achieving self-sustaining wastewater treatment and hydrogen production. By integrating hydrothermal liquefaction (HTL) and microbial electrolysis cells (MECs), the project advanced waste-to-fuel technology and expanded the understanding of sustainable waste valorization. It established a scalable framework for achieving high carbon efficiency, effective pollutant removal, and energy recovery, showcasing the potential of combining biological, thermal, and electrochemical systems to optimize resource recovery and reduce environmental impacts. The project demonstrated the technical effectiveness of the T-MEC process, achieving over 50% improvement in carbon efficiency and reducing waste processing costs by more than 25% compared to anaerobic digestion (AD). The HTL pilot reactor processed food waste at 90 kg/h, producing up to 200 L/day of biocrude oil with high conversion efficiency. A critical desalting step in pretreatment prevented catalyst fouling, enabling efficient hydrotreating with 100% deoxygenation and denitrogenation and sulfur reduction to <15 ppm. This positioned the kerosene fraction as a strong candidate for sustainable aviation fuel (SAF). The MECs achieved rapid startup, 86.4% COD removal, and hydrogen production rates of 1.8 L H 2 /L cat /day, among the highest recorded for pilot-scale systems. The integrated process achieved 65% carbon efficiency to biocrude and 58% to finished fuels, outperforming AD's 41% and 33% efficiencies for biogas and natural gas vehicle fuels. System analysis highlighted economic potential, with minimum fuel selling prices (MFSP) decreasing from $\$$25/GGE at 5 tpd to $\$$10/GGE at 500 tpd due to economies of scale. Future work will focus on reducing MEC material and membrane costs, enhancing performance through higher current densities, and creating tailored operational strategies for diverse feedstocks. Optimization of the integrated system will improve scalability and feasibility, positioning the T-MEC process as a competitive solution for converting wet waste into sustainable fuels and clean water. Beyond its technical and economic achievements, the project offers significant public benefits. The T-MEC process provides a sustainable alternative to landfilling and incineration, reducing greenhouse gas emissions and conserving resources. Converting waste into SAF and renewable fuels supports decarbonization in the transportation sector, advancing energy independence and reducing reliance on fossil fuels. Additionally, the process minimizes environmental pollutants, transforming them into valuable products like hydrogen and fuels, contributing to a cleaner and more sustainable future.

09 BIOMASS FUELS↗