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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25

Developing Fluorescence-Based Sensors to Support Rare Earth Element Separation

Rare earth elements (REEs) are essential to most renewable energy technologies. Unfortunately, as we transition to sustainable energy production, the demand for REEs is rapidly growing well beyond current rates of production. As a result, novel means of efficient, scalable, and easily adaptable methods for processing primary and recycle feedstocks are needed. Development and integration of sensors for highly selective in-line monitoring can support more efficient design and testing of such novel separation processes, as well as more cost-effective deployment of those separation flowsheets. Work here will explore the application of fluorescence spectroscopy, a highly sensitive and selective technique, to quantify multiple lanthanides in complex mixtures including known interferents or quenching agents. Results include identification of the optimal excitation wavelength and the limit of detection of various rare earth elements as well as the performance of data-science-based quantification approaches in streams where “unknowns” are present. Overall, the data science tools in conjunction with optical sensor data were able to quantify analytes in the presence of other lanthanides which can be anticipated in the actual industrial stream. Here we include characterization of lanthanides in a microfluidic device similar to those used in new process development. This study demonstrates the capability of utilizing fluorescence spectroscopy to quantify analytes in a complicated solution matrix, suggesting this is a successful approach for in-line monitoring to optimize the separation efficiency in an industrial stream.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Arvia Organics Destruction: An Innovative Treatment Approach for Dioxins, Furans and Other Problematic (Orphan) Organic Wastes - 16262

The safe and efficient disposal of radionuclide-contaminated organic wastes is a key component in the lifecycle of a nuclear power plant. Technologies are available for the processing of some of these wastes although there are a number of waste streams for which the disposition path is not clear or does not exist at all. For example, waste streams such as dioxin, furan and PCB-laden oils and aqueous organic matrices pose an issue for the US Dept. of Energy complex. These wastes present a challenge as they cannot be readily treated using existing treatment technologies because of legislative and material constraints such as gaseous phase radioactivity discharge limits, waste elemental content, by-product generation and waste resistance to thermal decomposition. Alternate methods of organics destruction can circumvent some of these issues by using different mechanisms of organics oxidation. One such innovative method, known as the Arvia organics destruction process, combines adsorption with electrochemical combustion and offers such an alternative. This technology, based on a patented material, Nyex{sup TM} that is able to act as both an adsorbent and as an electrode, allows the electrochemical combustion of adsorbed organics to occur on the material's surface. The result is the destruction of organics whilst the bulk of inorganic and radionuclide components remain in the aqueous phase. These components can subsequently be treated using existing waste processing technologies. This paper outlines recent work conducted on demonstrating the Arvia process against the destruction of dioxin, furan and PCB-laden wastes that demonstrates that the technology successfully removes these target species to below discharge standards in the aqueous phase. Based on these successful trials a test unit has been designed to demonstrate the process on actual radioactive wastes at the DOE Oak Ridge facility. During commissioning at Arvia's facility the unit achieved a destruction rate of over 1.5 ml of 100% organic waste per hour. The unit is currently at a partner laboratory facility based at Oak Ridge National Laboratories and has recently completed a further suite of simulant trials which are reported here. The above work showcases the development, testing and initial application of an innovative technology, first presented to the industry at the Waste Management 2012, as another option for the treatment of challenging wastes with expensive, complex or no current disposal routes. Over the years the technology has gone through a number of proving stages culminating in the testing on real orphan wastes based at the Oak Ridge Facility. The Arvia Organics Destruction Cell technology adds to the portfolio of available treatment technologies and will help facilitate the decommissioning and waste disposal responsibilities of the nuclear industry. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A2SD: Accelerating Scientific Innovation Through Autonomous Discovery Systems

The 2025 Advancing Autonomous Scientific Discovery (A2SD) workshop convened researchers from academia, national laboratories, and industry to explore the transformative role of autonomy in scientific discovery. The workshop highlighted a convergence of artificial intelligence, robotics, and computational workflows into autonomous systems capable of accelerating the scientific process. Presentations and discussions spanned autonomous experimentation, intelligent workflow orchestration, digital twins, and agent-based systems for managing complex research ecosystems. Key challenges discussed included interoperability across heterogeneous infrastructures, near real-time data management under FAIR principles, reproducibility, and the integration of human oversight. The workshop also emphasized the need for modular software interfaces, federated learning models, and education initiatives to support a next-generation scientific workforce.

Taufer, Michela [University of Tennessee, Knoxvill↗

Precision Joining Center

The establishment of a Precision Joining Center (PJC) is proposed. The PJC will be a cooperatively operated center with participation from U.S. private industry, the Colorado School of Mines, and various government agencies, including the Department of Energy's Nuclear Weapons Complex (NWC). The PJC's primary mission will be as a training center for advanced joining technologies. This will accomplish the following objectives: (1) it will provide an effective mechanism to transfer joining technology from the NWC to private industry; (2) it will provide a center for testing new joining processes for the NWC and private industry; and (3) it will provide highly trained personnel to support advance joining processes for the NWC and private industry.

Powell, John W.↗

Monte Carlo Methodology Serves Up a Software Success

Widely used for the modeling of gas flows through the computation of the motion and collisions of representative molecules, the Direct Simulation Monte Carlo method has become the gold standard for producing research and engineering predictions in the field of rarefied gas dynamics. Direct Simulation Monte Carlo was first introduced in the early 1960s by Dr. Graeme Bird, a professor at the University of Sydney, Australia. It has since proved to be a valuable tool to the aerospace and defense industries in providing design and operational support data, as well as flight data analysis. In 2002, NASA brought to the forefront a software product that maintains the same basic physics formulation of Dr. Bird's method, but provides effective modeling of complex, three-dimensional, real vehicle simulations and parallel processing capabilities to handle additional computational requirements, especially in areas where computational fluid dynamics (CFD) is not applicable. NASA's Direct Simulation Monte Carlo Analysis Code (DAC) software package is now considered the Agency s premier high-fidelity simulation tool for predicting vehicle aerodynamics and aerothermodynamic environments in rarified, or low-density, gas flows.

Source record↗

Design and Development of a Custom Laser Powder Bed Fusion System

Additive manufacturing (AM) has gained great momentum both in industrial and research applications. Due to the ability to create custom and complex parts directly from a computer-aided design (CAD) file, AM is becoming a more reliable and efficient means to fabricate components. While being implemented throughout the aerospace, medical, automotive, and energy industries, the development of metal AM is still ongoing and presents many unique scientific challenges. For example, in laser powder bed fusion (PBF), intense localized heating of metal powder followed by rapid cooling leads to residual stresses and unique microstructures within a build. This may lead to cracking and a decrease in mechanical performance. In-situ diagnostics enable the laser-material interaction to be monitored as it occurs in order to optimize process parameters, and can be leveraged to develop tailored materials with specific microstructures that are more conducive for the complex thermal patterns encountered during laser PBF. Unfortunately, most commercial laser PBF machines are not suitable for research applications due to their large size, lack of diagnostics, and black box operation. A smaller system is better suited for using smaller quantities of powder to develop new tailored materials for AM, and a custom, modular design permits greater flexibility for incorporating in-situ diagnostics. Therefore, this project consisted of the design and construction of a custom, small scale, modular PBF system.

36 MATERIALS SCIENCE↗

Development of an in situ temperature stage for synchrotron X-ray spectromicroscopy

In situ characterization of micro- and nanoscale defects in polycrystalline thin-film materials is required to elucidate the physics governing defect formation and evolution during photovoltaic device fabrication and operation. X-ray fluorescence spectromicroscopy is particularly well-suited to study defects in compound semiconductors, as it has a large information depth appropriate to study thick and complex materials, is sensitive to trace amounts of atomic species, and provides quantitative elemental information, non-destructively. Current in situ methods using this technique typically require extensive sample preparation. In this work, we design and build an in situ temperature stage to study defect kinetics in thin-film solar cells under actual processing conditions, requiring minimal sample preparation. Careful selection of construction materials also enables controlled non-oxidizing atmospheres inside the sample chamber such as H 2 Se and H 2 S. Temperature ramp rates of up to 300 °C/min are achieved, with a maximum sample temperature of 600 °C. As a case study, we use the stage for synchrotron X-ray fluorescence spectromicroscopy of CuIn x Ga 1–x Se 2 (CIGS) thin-films and demonstrate predictable sample thermal drift for temperatures 25–400°C, allowing features on the order of the resolution of the measurement technique (125 nm) to be tracked while heating. As a result, the stage enables previously unattainable in situ studies of nanoscale defect kinetics under industrially relevant processing conditions, allowing a deeper understanding of the relationship between material processing parameters, materials properties, and device performance.

47 OTHER INSTRUMENTATION↗

Overcoming Oxidation State-Dependent Spectral Interferences: Online Monitoring of U(VI) Reduction to U(IV) via Raman and UV–vis Spectroscopy

Analytical characterization of chemical processes is an essential component of both industrial processes and fundamental studies. Applicable techniques abound, but optical spectroscopy has the unique combination of being easily incorporated into on-line (in-situ) monitoring probes and can also provide abundant chemical information (concentration, oxidation state, speciation). However, this abundance of chemical information can make applying optical spectroscopy to complex chemical processes challenging. This is particularly evident in the bulk electrolysis of U(VI) to U(IV), an essential preparatory step in some nuclear fuel recycling schemes. Starting and product materials have interfering spectral signatures in both electronic and vibrational spectroscopies, making accurate and real-time analysis difficult to achieve. In this paper, we discuss the application of optical spectroscopy to the on-line monitoring of a bulk electrolysis process and the methods utilized to analyze data as well as characterize the efficiency and mechanism of U(IV) generation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A shift between mineral and nonmineral sources of iron and sulfur causes proteome-wide changes in Methanosarcina barkeri

ABSTRACT Iron (Fe) and sulfur (S) are required elements for life, and changes in their availability can limit the ecological distribution and function of microorganisms. In anoxic environments, soluble Fe typically exists as ferrous iron [Fe(II)] and S as sulfide (HS − ). These species exhibit a strong affinity that ultimately drives the formation of sedimentary pyrite (FeS 2 ). Recently, paradigm-shifting studies indicate that Fe and S in FeS 2 can be made bioavailable by methanogens through a reductive dissolution process. However, the impact of the utilization of FeS 2 , as opposed to canonical Fe and S sources, on the phenotype of cells is not fully understood. Here, shotgun proteomics was utilized to measure changes in the phenotype of Methanosarcina barkeri MS grown with FeS 2 , Fe(II)/HS − , or Fe(II)/cysteine. Shotgun proteomics tracked 1,019 proteins overall, with 307 observed to change between growth conditions. Functional characterization and pathway analyses revealed these changes to be systemic and largely tangential to Fe/S metabolism. As a final step, the proteomics data were viewed with respect to previously collected transcriptomics data to deepen the analysis. Presented here is evidence that M. barkeri adopts distinct phenotypes to exploit specific sources of Fe and S in its environment. This is supported by observed protein abundance changes across broad categories of cellular biology. DNA adjacent metabolism, central carbon metabolism methanogenesis, metal trafficking, quorum sensing, and porphyrin biosynthesis pathways are all features in the phenotypic differentiation. Differences in trace metal availability attributed to complexation with HS − , either as a component of the growth medium [Fe(II)/HS − ] or generated through reduction of FeS 2 , were likely a major factor underpinning these phenotypic differences. IMPORTANCE The methanogenic archaeon Methanosarcina barkeri holds great potential for industrial bio-mining and energy generation technologies. Much of the biochemistry of this microbe is poorly understood, and its characterization will provide a glimpse into biological processes that evolved close to life’s origin. The discovery of its ability to extract iron and sulfur from bulk, solid-phase minerals shifted a longstanding paradigm that these elements were inaccessible to biological systems. The full elucidation of this process has the potential to help scientists and engineers extract valuable metals from low-grade ore and mine waste generating energy in the form of methane while doing so.

59 BASIC BIOLOGICAL SCIENCES↗

Utility-Scale Operational Consequences for Solar Grid Services

This report delves into the critical aspects of grid services provided by solar inverter-based resources (IBRs), with an emphasis on the evolving landscape of microgrids, virtual power plants (VPPs), aggregators, and distributed energy resource management systems (DERMS). As the energy sector undergoes a transformative shift towards more decentralized and resilient grid architectures, understanding the multifaceted risks associated with these technologies becomes paramount. The report categorizes these risks into organizational, technical, and procedural domains, providing a thorough risk assessment framework that stakeholders can utilize to anticipate and mitigate potential issues. In addressing the increasing complexity of grid interconnections, the report highlights the importance of Cyber-Informed Engineering (CIE). By embedding engineering controls and cybersecurity measures into the early stages of system design, this approach aims to fortify grid infrastructure against emerging cyber threats. The analysis includes an exploration of best practices and strategies for integrating CIE principles to enhance grid security and resilience. To provide practical insights, the report conducts a detailed consequence analysis of various grid services and cyber mitigations that can be applied through the interconnection process. This analysis evaluates the potential impacts of different failure modes and vulnerabilities, offering a clear understanding of the consequences that could arise from disruptions within the energy grid. The findings are further enriched by a series of case studies that illustrate real-world scenarios and lessons learned from past incidents. Through this comprehensive examination of grid services and their criticality, the report aims to prepare industry professionals with the knowledge and tools necessary to navigate the complexities of modern energy systems. By providing a comprehensive approach that includes risk assessment, cybersecurity, and consequence analysis, solar stakeholders can more effectively guarantee the reliability, efficiency, and security of the energy grid.

14 SOLAR ENERGY↗

Sustainability in Directed Energy Deposition

Directed energy deposition (DED) additive manufacturing (AM) has been recognized as an efficient and sustainable technology in the field of advanced manufacturing. In the past few years, Considerable discussion has been made by researchers to promote DED AM for better performance in manufacturing. The discussions focus on basic theoretical research, process optimization and control, technology innovation, and industrial applications. However, this technology׳s environmental and economic benefits over traditional manufacturing processes are still to be seen and its sustainability is also a mystery. Here, this chapter presents a critical overview of the environmental sustainability of DED to provide a comprehensive understanding of the effects of materials, processing conditions, and geometric complexities on the energy consumption and environmental impacts of DED and provide a better guide for decision-makers in terms of selecting suitable manufacturing processes. In addition, this chapter proposes a novel framework for DED AM sustainability assessment and improvement based on the Life Cycle Assessment (LCA) method and multi-objective optimization. At last, future perspectives and recommendations for the sustainability of DED AM are put forward.

54 ENVIRONMENTAL SCIENCES↗

Protonation Dynamics of Confined Ethanol–Water Mixtures in H-ZSM-5 from Machine Learning-Driven Metadynamics

Zeolites are indispensable heterogeneous catalysts in industrial chemical processes, valued for their strong Brønsted acidity, well-defined microporous frameworks, and tunable pore structures. Their catalytic activity arises primarily from Brønsted acid sites (BAS), typically present as bridging hydroxyl groups (Si–OH–Al). Under aqueous reaction conditions, these protons interact dynamically with water and alcohol molecules, leading to complex solvation and protonation behavior within confined pores. In this study, we investigate the protonation equilibrium occurring between ethanol and water at the BAS of acidic zeolites under varying hydration levels, i.e., C2H5OH–(H2O)n, n=1–4. Local structure was analyzed through an adaptive-learning global optimization algorithm, while enhanced sampling molecular dynamics simulations with Well-Tempered Metadynamics (WMetaD) and machine learning interatomic potentials (MLPs) provide free-energy surfaces (FES) at variable hydration levels. The results reveal a strong dependence of proton localization on the degree of hydration. At low hydration (1 water molecule), the proton resides predominantly on ethanol; with 2 water molecules, it shifts toward water, and at higher hydration (3 or more water molecules), it becomes extensively delocalized over the water cluster. These findings underscore the critical role of solvation in modulating acid site behavior and suggest that a minimum of three water molecules is necessary to fully stabilize the proton on water within the zeolite framework. This solvation threshold has significant implications for catalytic processes, particularly in biomass conversion reactions where alcohol protonation is a key step in dehydration mechanisms.

machine learning↗

IX Cell Wall Research Conference 2022 (IXCWRC): Cell wall research for new fundamental discoveries and applications in plant biology

This application is for securing funds to offset the registration fees and lodging costs for US-based early career investigators (ERCs) to participate to the IX Cell Wall Research Conference 2022 (IXCWRC 2022): Cell wall research for new fundamental discoveries and applications in plant biology. The conference will be held in East Lansing, Michigan on June 13-17, 2022. The conference will focus on the plant cell wall. Plant cells are encapsulated by the cell wall, a dynamic structure that protects them, enables them to interface with the external environment and supports the growth of the entire organism. There is a growing interest in understanding the complex processes necessary to build and deconstruct the plant cell wall. A better understanding of how the cell wall is synthesized during plant growth and in response to the environment, and how it is deconstructed for a broad variety of applications can inform and improve biotechnological processes for increasing biomass yield and improving industrial processes for the recovery of valuable, sustainable polymers. Acquiring such knowledge requires the exchange of new ideas and results as well as the development and application of new technologies. The IXCWRC 2022 aims to reach this goal by providing an opportunity for an open forum to discuss new ideas and theories and develop collaborations for scientists across the globe in a diverse and supportive environment. A distinction of the IXCWRC 2022 from all the preceding plant cell wall conferences will be its focus on the training and inclusion of the next generation of scientists, the ERCs. The overall goal of this application is to broaden the participation of ERCs with a focus on underrepresented communities. The specific goal of this application is to secure support for registration and lodging for US-based ERCs to attend the conference. Priority will be given to ERCs from underrepresented communities in science. We expect that support from DOE will allow the development of an exciting and innovative program to discuss the latest scientific advances in cell wall biology research, advance the next generation of plant cell wall researchers and foster the foundations of an inclusive community in science.

59 BASIC BIOLOGICAL SCIENCES↗

Content and Representation of Information Needed to Support Time-Constrained Problem Solving

NASA’s current mission-operations paradigm originated with Project Mercury and endured with minimum evolution through the Apollo Program, Space Shuttle Program, and ISS missions. At its foundation is a near-complete real-time dependence on a ground team to manage the combined state of the mission, vehicle, and crew. Utilizing many engineers and operators with broad and deep expertise; large, distributed datasets including extensive telemetry; and expansive analytical and computing power, this ground team has served as the safety net for crewed spaceflight missions over the past 60 years. This approach must change to address challenges associated with missions beyond low Earth orbit (BLEO), including infrequent resupply, reduced ability to evacuate, and delayed communications that prohibit real-time operational support. We anticipate that a necessary part of this change will be increased independence for the crew, as roles and responsibilities traditionally performed by ground teams move on board the vehicle. While many risks are associated with Earth-independent operations, one particular concern is ensuring that the crew will have adequate onboard support to perform urgent problem solving when communication with the ground is delayed or intermittent. A key resource that enables the ground team to respond to anomalies quickly and effectively is the extraordinary expertise and experience it possesses. It is comprised of 80+ experts on at any given time, with a combined 600+ years of system-specific experience across 22 unique console disciplines. A small crew will face the unprecedented challenge of independently responding to anomalies that have historically been handled by a team 20 times their size. Another important resource upon which the ground heavily relies to support procedure execution and anomaly response is data. The amount of telemetry data that each flight controller monitors is extensive. In addition, as the ground team works to further assess impacts, trouble shoot, identify workarounds, and oversee procedure execution, it accesses and synthesizes engineering and procedure information, as well as system build, test, and configuration documentation. It is not feasible nor useful to put all these data onboard as crews become more Earth independent. Each member of a small Mars mission small crew will have multiple roles beyond monitoring telemetry and data gathering, and multiple roles within anomaly resolution processes, thereby limiting their capacity for copious amounts of information. Moreover, while access is necessary, it alone is insufficient. Information will need to be compiled, refined, and represented appropriately to support the crew’s reduced attention and expertise. This work seeks to understand the content and representation of information needed to support time-constrained problem solving and decision making by the crew without real-time ground support. To build this understanding, we first surveyed the literature, focusing on how expert problem solvers construct and manipulate their mental models. Next, we interviewed expert problem solvers in spaceflight and analogous domains and surveyed industry solutions for data presentation. Finally, we analyzed current spaceflight operations by investigating flight controller anomaly resolution processes during ISS training simulations and real operational events. These methods led to creating a problem-solving framework that details common themes and features of attending to, assessing, analyzing, and acting on problems in complex, time-constrained domains. Using this framework and the results of our analysis, we identified conceptual data representations needed for crew-led problem-solving. Preliminary onboard user interface concepts to meet identified needs will be presented.

anomaly response↗

Opportunities and Challenges for Nuclear-Renewable Hybrid Energy Systems

TTightly coupled nuclear-renewable hybrid energy systems (N-R HESs) are systems that link subsystems to generate dispatchable electricity and produce at least one industrial product from two or more energy resources. Because N-R HESs are designed to produce different products based on the value of those products in markets, their optimal designs and operations can be complex. This paper summarizes some key conclusions from a set of economic analyses of N-R HESs. Each N-R HES use case analyzed includes a nuclear reactor, a thermal power cycle to convert nuclear energy into electricity, either a wind or photovoltaic solar subsystem producing electricity, and an industrial process producing an energy or an industrial product. The analyses focused on identifying the optimal configuration and hours of operations for each N-R HES within ranges of hypothetical future electricity price profiles and industrial product prices. Four important insights are drawn from the results of those analyses.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Opportunities and Challenges for Nuclear-Renewable Hybrid Energy Systems

Tightly coupled nuclear-renewable hybrid energy systems (N-R HESs) are systems that link subsystems to generate dispatchable electricity and produce at least one industrial product from two or more energy resources. Because N-R HESs are designed to produce different products based on the value of those products in markets, their optimal designs and operations can be complex. This paper summarizes some key conclusions from a set of economic analyses of N-R HESs. Each N-R HES use case analyzed includes a nuclear reactor, a thermal power cycle to convert nuclear energy into electricity, either a wind or photovoltaic solar subsystem producing electricity, and an industrial process producing an energy or an industrial product. The analyses focused on identifying the optimal configuration and hours of operations for each N-R HES within ranges of hypothetical future electricity price profiles and industrial product prices. Four important insights are drawn from the results of those analyses.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

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]↗

Cold Commissioning Simulant Selection for the Hanford Tank Waste Treatment Plant LAW Facility - 18465

Commissioning the Low-Activity Waste (LAW) Facility of the Hanford Tank Waste Treatment and Immobilization Plant (WTP) will require large volumes (∼2,000,000 liters) of a non-radioactive, chemically analogous waste simulant. Cold commissioning will provide for operator training in an integrated facility, demonstration of mechanical process equipment capacity, environmental performance demonstration of emissions control systems, and process control systems shakedown and tuning. Selection of the cold commissioning simulant is following a structured four-phase process to arrive at the preferred composition and recipe. Phases I, II and III are complete. Phase I laid the framework for decision making with preparation of a Project Management Plan, an update to the Simulant Development, Approval, Validation, and Documentation procedure, and a kickoff meeting to gather stakeholder input into the simulant definition and selection criteria. Phase II consisted of a comprehensive literature search and compilation of LAW simulant recipes, followed by initial screening against the selection criteria identified in Phase I. This process identified 72 candidate simulant recipes and down-selected 9 for further study. Phase III studies involved a) statistical comparisons of the similarity of candidate simulant compositions to the tank waste feed vector, b) process modelling of the commissioning sequence with each simulant to estimate glass former and simulant material consumption, offgas and effluent volumes and compositions, and product glass volumes and compositions, and c) evaluation of simulants against the immobilized LAW glass composition algorithm to determine allo able waste loading to ensure compliance with product specifications and process constraints. The results of these studies identified two of the candidate recipes to be carried forward to full-scale testing. Phase IV consists of testing these two recipes at vendor facilities to determine scalability, fabricability, and stability of the simulants when produced at industrial scale. Scalability is the ability to take a recipe from bench scale (1 to 40 liters) batch size to full scale (>35,000 liters) batch size. Fabricability is the ability of a recipe to be prepared in large batches without the need for complex or expensive mechanical equipment, heating, or cooling systems. Stability is the ability of a simulant to withstand long term storage and variations in environmental conditions without unacceptable changes in key characteristics (the set of chemical, physical, and rheological parameters that the simulant is intended to exhibit during cold commissioning tests). Simulants will also be tested for compatibility with other startup material (i.e., frit), tuning simulants, and environmental performance demonstration test spiking solutions to ensure against unexpected situations. Using a structured process is essential when making high impact decisions such as waste simulant selection. Proper planning and a clear explanation of how the decision process will unfold is key to obtaining stakeholder buy-in as more information is gathered. The documentation resulting from this structured selection process will be compiled and summarized in a Cold Commissioning Simulant Definition deliverable due to the Department of Energy 24 months before the start of Cold Commissioning. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗