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Novel techniques for constraining neutron-capture rates relevant for r -process heavy-element nucleosynthesis

The rapid-neutron capture process (r process) is identified as the producer of about 50% of elements heavier than iron. This process requires an astrophysical environment with an extremely high neutron flux over a short amount of time ( seconds), creating very neutron-rich nuclei that are subsequently transformed to stable nuclei via beta decay. In 2017, one site for the r process was confiimed: the advanced LIGO and advanced Virgo detectors observed two neutron stars merging, and immediate follow-up measurements of the electromagnetic transients demonstrated an "afterglow" over a broad range of frequencies fully consistent with the expected signal of an r process taking place. Although neutronstar mergers are now known to be r-process element factories, contributions from other sites are still possible, and a comprehensive understanding and description of the r process is still lacking. One key ingredient to large-scale r-process reaction networks is radiative neutron-capture ( n , γ ) rates, for which there exist virtually no data for extremely neutron rich nuclei involved in the r process. Due to the current status of nuclear-reaction theory and our poor understanding of basic nuclear properties such as level densities and average g-decay strengths, theoretically estimated ( n , γ ) rates may vary by orders of magnitude and represent a major source of uncertainty in any nuclear-reaction network calculation of r-process abundances. Here in this review, we discuss new approaches to provide information on neutron-capture cross sections and reaction rates relevant to the r process. In particular, we focus on indirect, experimental techniques to measure radiative neutron-capture rates. While direct measurements are not available at present, but could possibly be realized in the future, the indirect approaches present a first step towards constraining neutron-capture rates of importance to the r process.

(n, γ,) cross sections↗

TYPE Ia SUPERNOVAE AS SITES OF THE p-PROCESS: TWO-DIMENSIONAL MODELS COUPLED TO NUCLEOSYNTHESIS

Beyond Fe, there is a class of 35 proton-rich nuclides, between {sup 74}Se and {sup 196}Hg, called p-nuclei. They are bypassed by the s and r neutron capture processes and are typically 10-1000 times less abundant than the s- and/or r-isotopes in the solar system. The bulk of p-isotopes is created in the 'gamma processes' by sequences of photodisintegrations and beta decays in explosive conditions in both core collapse supernovae (SNe II) and in Type Ia supernovae (SNe Ia). SNe II contribute to the production of p-nuclei through explosive neon and oxygen burning. However, the major problem in SN II ejecta is a general underproduction of the light p-nuclei for A < 120. We explore SNe Ia as p-process sites in the framework of a two-dimensional SN Ia delayed detonation model as well as pure deflagration models. The white dwarf precursor is assumed to have reached the Chandrasekhar mass in a binary system by mass accretion from a giant/main-sequence companion. We use enhanced s-seed distributions, with seeds directly obtained from a sequence of thermal pulse instabilities both in the asymptotic giant branch phase and in the accreted material. We apply the tracer-particle method to reconstruct the nucleosynthesis by the thermal histories of Lagrangian particles, passively advected in the hydrodynamic calculations. For each particle, we follow the explosive nucleosynthesis with a detailed nuclear reaction network for all isotopes up to {sup 209}Bi. We select tracers within the typical temperature range for p-process production, (1.5-3.7) x 10{sup 9} K, and analyze in detail their behavior, exploring the influence of different s-process distributions on the p-process nucleosynthesis. In addition, we discuss the sensitivity of p-process production to parameters of the explosion mechanism, taking into account the consequences on Fe and alpha elements. We find that SNe Ia can produce a large amount of p-nuclei, both the light p-nuclei below A = 120 and the heavy-p nuclei, at quite flat average production factors, tightly related to the s-process seed distribution. For the first time, we find a stellar source able to produce both light and heavy p-nuclei almost at the same level as {sup 56}Fe, including the debated neutron magic {sup 92,} {sup 94}Mo and {sup 96,} {sup 98}Ru. We also find that there is an important contribution from the p-process nucleosynthesis to the s-only nuclei {sup 80}Kr, {sup 86}Sr, to the neutron magic {sup 90}Zr, and to the neutron-rich {sup 96}Zr. Finally, we investigate the metallicity effect on p-process production in our models. Starting with different s-process seed distributions for two metallicities Z = 0.02 and Z = 0.001, running two-dimensional SN Ia models with different initial composition, we estimate that SNe Ia can contribute to at least 50% of the solar p-process composition. A more detailed analysis of the role of SNe Ia in Galactic chemical evolution of p-nuclei is in preparation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A novel digital pulse processing architecture for nuclear instrumentation

The field of nuclear instrumentation covers a wide range of applications, including counting, spectrometry, pulse shape discrimination and multi-channel coincidence. These applications are the topic of many researches, new algorithms and implementations are constantly proposed thanks to advances in digital signal processing. However, these improvements are not yet implemented in instrumentation devices. This is especially true for neutron-gamma discrimination applications which traditionally use charge comparison method while literature proposes other algorithms based on frequency domain or wavelet theory which show better performances. Another example is pileups which are generally rejected while pileup correction algorithms also exist. These processes are traditionally performed offline due to two issues. The first is the Poissonian characteristic of the signal, composed of random arrival pulses which requires to current architectures to work in data flow. The second is the real-time requirement, which implies losing pulses when the pulse rate is too high. Despite the possibility of treating the pulses independently from each other, current architectures paralyze the acquisition of the signal during the processing of a pulse. This loss is called dead-time. These two issues have led current architectures to use dedicated solutions based on re-configurable components like Field Programmable Gate Arrays (FPGAs) to overcome the need of performance necessary to deal with dead-time. However, dedicated hardware algorithm implementations on re-configurable technologies are complex and time-consuming. For all these reasons, a programmable Digital pulse Processing (DPP) architecture in a high level language such as Cor C++ which can reduce dead-time would be worthwhile for nuclear instrumentation. This would reduce prototyping and test duration by reducing the level of hardware expertise to implement new algorithms. However, today's programmable solutions do not meet the need of performance to operate online and not allow scaling with the increase in the number of measurement channel. That is why an innovative DPP architecture is proposed in this paper. This architecture is able to overcome dead-time while being programmable and is flexible with the number of measurement channel. Proposed architecture is based on an innovative execution model for pulse processing applications which can be summarized as follow. The signal is not composed of pulses only, consequently, pulses processing does not have to operate on the entire signal. Therefore, the first step of our proposal is pulse extraction by the use of dedicated components named pulse extractors. The triggering step can be achieved after the analog-to-digital conversion without any signal shaping or filtering stages. Pileup detection and accurate pulse time stamping are done at this stage. Any application downstream this step can work on adaptive variable-sized array of samples simplifying pulse processing methods. Then, once the data flow is broken, it is possible to distribute pulses on Functional Units (FUs) which perform processing. As the date of each pulse is known, they can be processed individually out-of-order to provide the results. To manage the pulses distribution, a scheduler and an interconnection network are used. pulses are distributed on the first FU which is not busy without congesting the interconnection network. For this reason, the process duration does not result anymore in dead-time if there are enough FUs. FUs are designed to be standalone and to comprises at least a programmable general purpose processor (ARM, Microblaze) allowing the implementation of complex algorithms without any modification of the hardware. An acquisition chain is composed of a succession of algorithms which lead to organize our FUs as a software macro-pipeline, A simple approach consists in assigning one algorithm per FU. Consequently, the global latency becomes the worst latency of algorithms execution on FU. Moreover, as algorithms are executed locally - i.e. on a FU - this approach limits shared memory requirement. To handle multichannel, we propose FUs sharing, this approach maximize the chance to find a non-busy FU to process an incoming pulse. This is possible since each channel receive random event independently, the pulse extractors associated to them do not necessarily need to access simultaneously to all Computing resources at the same time to distribute their pulses. The major contribution of this paper is the proposition of an execution model and its associated hardware programmable architecture for digital pulse processing that can handle multiple acquisition channels while maintaining the scalability thanks to the use of shared resources. This execution model and associated architecture are validated by simulation of a cycle accurate architecture SystemC model. Proposed architecture shows promising results in terms of scalability while maintaining zero dead-time. This work also permit the sizing of hardware resources requirement required for a predefined set of applications. Future work will focus on the interconnection network and a scheduling policy that can exploit the variable-length of pulses. Then, the hardware implementation of this architecture will be performed and tested for a representative set of application.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SU-D-BRD-07: Evaluation of the Effectiveness of Statistical Process Control Methods to Detect Systematic Errors For Routine Electron Energy Verification

Purpose: To evaluate the ability of statistical process control methods to detect systematic errors when using a two dimensional (2D) detector array for routine electron beam energy verification. Methods: Electron beam energy constancy was measured using an aluminum wedge and a 2D diode array on four linear accelerators. Process control limits were established. Measurements were recorded in control charts and compared with both calculated process control limits and TG-142 recommended specification limits. The data was tested for normality, process capability and process acceptability. Additional measurements were recorded while systematic errors were intentionally introduced. Systematic errors included shifts in the alignment of the wedge, incorrect orientation of the wedge, and incorrect array calibration. Results: Control limits calculated for each beam were smaller than the recommended specification limits. Process capability and process acceptability ratios were greater than one in all cases. All data was normally distributed. Shifts in the alignment of the wedge were most apparent for low energies. The smallest shift (0.5 mm) was detectable using process control limits in some cases, while the largest shift (2 mm) was detectable using specification limits in only one case. The wedge orientation tested did not affect the measurements as this did not affect the thickness of aluminum over the detectors of interest. Array calibration dependence varied with energy and selected array calibration. 6 MeV was the least sensitive to array calibration selection while 16 MeV was the most sensitive. Conclusion: Statistical process control methods demonstrated that the data distribution was normally distributed, the process was capable of meeting specifications, and that the process was centered within the specification limits. Though not all systematic errors were distinguishable from random errors, process control limits increased the ability to detect systematic errors using routine measurement of electron beam energy constancy.

07 ISOTOPE AND RADIATION SOURCES↗

EV Charging Infrastructure Energization An Overview of Approaches for Simplifying and Accelerating Timelines to Processing EV Charging Load Service Requests

The United States has seen significant growth in electric vehicle (EV) adoption, leading to increased demand for EV charging infrastructure. Over the past decade, EV charging infrastructure site developers, site hosts, and electric distribution utilities have navigated the process to integrate chargers onto the electric grid. Site developers and site hosts have raised the alarm that the integration process for high-powered EV charging projects does not meet the needs of the EV market for timeliness or cost. High-powered charging stations typically require a load service request or an agreement with the local utility to connect to the grid. The process of energizing a new high-powered charging site can be complex and time-consuming, often taking up to 2 years. This timeline is the result of current utility energization processes having been designed for construction projects that take longer to build (i.e., buildings). The specific challenges stem from various factors, including compartmentalization in application processes, the integration of EV charging process approvals with other distributed energy resources (DERs), and the need to ensure grid reliability. The energization process needs to evolve to meet the growing demand for high-powered EV charging. This white paper compiles information gathered through various conversations with key stakeholders, including utilities, utility regulators, EV charging operators, site developers, and authorities having jurisdiction (AHJ) as well as through an extensive literature review. This document identifies the challenges and provides potential solutions to streamline the process of connecting EV charging infrastructure to the power grid in the United States, serving as a starting point for future conversations around these solutions. The solutions noted in this white paper require collaborative efforts among utilities, regulators, and EV charging infrastructure developers to streamline the grid connection process for EV charging infrastructure. They are broadly organized into four areas: 1. Increase data access and transparency: Develop automated load service request tools, integrate hosting capacity and load service request analyses, incorporate EV adoption forecasts, and provide transparency on the processing queue. 2. Improve energization processes and timing: Create fast-track options based on prescreening criteria, provide flexibility or phased approvals in the load service request/interconnection process, build internal knowledge within utilities about EV charging technologies, and provide standardized workforce training. 3. Promote economic efficiency: Right size distribution components to accurately reflect the load requirements of EV charging infrastructure, make proactive investments in grid infrastructure based on EV adoption forecasts and growth projections, and consider energy equity and environmental justice factors such as equitable access to EV charging when planning infrastructure. 4. Improve grid reliability and resilience: Use load management/power control systems (PCS) at EV charging stations, adopt and implement harmonized standards for communication protocols and information models between the EV charging and grid control infrastructure, and address cybersecurity considerations by implementing robust security measures and standards for EV charging infrastructure—with particular emphasis on clarifying the security requirements for the interface to the grid. The objective of the solutions proposed in this white paper is to accelerate the timeline and decrease costs associated with connecting EV charging infrastructure to the grid. Electric utilities, utility regulators, EV charging infrastructure developers, and site hosts will first need to understand which solutions are available in their service territory, and if warranted, which combination of solutions would support their specific needs. Through the successful implementations of solutions at scale detailed here, industry will demonstrate a new and innovative ecosystem where timely deployment and energization of EV charging infrastructure with greater grid resiliency and reliability is a reality.

24 POWER TRANSMISSION AND DISTRIBUTION↗

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↗

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↗

How Can Construction Process Simulation Modeling Aid the Integration of Lean Principles in the Factory-Built Housing Industry?

New and existing factories that produce and deliver factory-built housing can benefit from construction process simulation modeling to explore the integration of Lean principles in their operations. Construction process simulation modeling provides digital or virtual recreations of the real-world factory environments to visualize, quantify, analyze, and optimize their underlying behavior, including factory productivity, material flow, labor dynamics, bottlenecks, and work scope. One of the key benefits of process simulation modeling is the ability to create and compare "what-if" scenarios, including integrating Lean principles such as reducing waste (for example, transportation, waiting), line balancing, and just-in-time concepts. In general, three process simulation methods are widely used: discrete event simulation (DES), agentbased modeling (ABM), and system dynamics (SD). Myriad process simulation software also is available, but depending on the industry, complexity of the system, and purposes of the simulation, some software might be more appropriate. Similar to how computer-aided design (CAD) software such as AutoCAD and Rhinoceros enable building design of modular or factory-built housing, process simulation modeling software such as jStrobe, ProModel, and AnyLogic can enable factory design of new and existing factories to deliver modular affordable housing at scale, as opposed to traditional site-built construction. Software with DES capabilities can help generate a process model that is a logical representation of resources and activities in a factory. Software with CAD-DES integration can leverage product-process data integration to help spatially visualize a DES model of the factory in the CAD environment. Software with multimethod simulation capabilities, widely used in the manufacturing industry, brings together DES, ABM, and SD in a single platform that allows visualization, quantification, analyses, and optimization at varying data fidelities. Near-real-time data from an existing factory can be directly plugged into multimethod simulation software so that the construction process simulation model is a near-accurate representation of the real-world factory conditions. This report provides insights into the use of simulation as an aid to integrate Lean concepts in factories, including guidelines for selecting the appropriate process simulation modeling method and software. These insights have been developed as part of ongoing process simulation modeling research, development, and demonstration projects at the U.S. Department of Housing and Urban Development, the U.S. Department of Energy, and the National Renewable Energy Laboratory focused on how process simulation models can enable better integration of resilience, energy efficiency, and low-carbon design strategies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

STATUS OF THE DEVELOPMENT OF IN-TANK/AT-TANK SEPARATIONS TECHNOLOGIES FOR FOR HIGH-LEVEL WASTE PROCESSING FOR THE U.S. DEPARTMENT OF ENERGY

Within the U.S. Department of Energy's (DOE) Office of Technology Innovation and Development, the Office of Waste Processing manages a research and development program related to the treatment and disposition of radioactive waste. At the Savannah River (South Carolina) and Hanford (Washington) Sites, approximately 90 million gallons of waste are distributed among 226 storage tanks (grouped or collocated in 'tank farms'). This waste may be considered to contain mixed and stratified high activity and low activity constituent waste liquids, salts and sludges that are collectively managed as high level waste (HLW). A large majority of these wastes and associated facilities are unique to the DOE, meaning many of the programs to treat these materials are 'first-of-a-kind' and unprecedented in scope and complexity. As a result, the technologies required to disposition these wastes must be developed from basic principles, or require significant re-engineering to adapt to DOE's specific applications. Of particular interest recently, the development of In-tank or At-Tank separation processes have the potential to treat waste with high returns on financial investment. The primary objective associated with In-Tank or At-Tank separation processes is to accelerate waste processing. Insertion of the technologies will (1) maximize available tank space to efficiently support permanent waste disposition including vitrification; (2) treat problematic waste prior to transfer to the primary processing facilities at either site (i.e., Hanford's Waste Treatment and Immobilization Plant (WTP) or Savannah River's Salt Waste Processing Facility (SWPF)); and (3) create a parallel treatment process to shorten the overall treatment duration. This paper will review the status of several of the R&D projects being developed by the U.S. DOE including insertion of the ion exchange (IX) technologies, such as Small Column Ion Exchange (SCIX) at Savannah River. This has the potential to align the salt and sludge processing life cycle, thereby reducing the Defense Waste Processing Facility (DWPF) mission by 7 years. Additionally at the Hanford site, problematic waste streams, such as high boehmite and phosphate wastes, could be treated prior to receipt by WTP and thus dramatically improve the capacity of the facility to process HLW. Treatment of boehmite by continuous sludge leaching (CSL) before receipt by WTP will dramatically reduce the process cycle time for the WTP pretreatment facility, while treatment of phosphate will significantly reduce the number of HLW borosilicate glass canisters produced at the WTP. These and other promising technologies will be discussed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Techno-economic optimization of shale gas to dimethyl ether production processes via direct and indirect synthesis routes

The shale gas to dimethyl ether process via direct synthesis route with a syngas H2/CO=1 has a higher dimethyl ether yield than that via indirect synthesis route. However, the direct synthesis route involves various energy and capital-intensive processes, such as the complicated dimethyl ether separation process, and the CO2 recycle and comprssion process. In this study, a techno-economic analysis of the shale gas to dimethyl ether process via direct and indirect synthesis routes is performed using Aspen Process Economic Analyzer based on the rigorous process model developed in Aspen Plus. Effects of different CO2 removal technologies and dimethyl ether synthesis technologies from syngas are evaluated. Both, direct and indirect plants are optimized in Aspen Plus equation-oriented environment using the rigorous process models. The effects of key design parameters (i.e. H2/CO in the syngas) as well as investment parameters (i.e. prices of raw materials, products, and utilities, plant scale) on the process economics as been evaluated. The direct dimethyl ether synthesis route processing a syngas with H2/CO =1 and using the Rectisol process for CO2 capture has the highest overall thermal efficiency on the lower heat value basis is found to be much lower than the current U.S. market diesel price indicating the feasibility of the process.

Mevawala, Chirag↗

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↗

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↗

Process assessment of small scale low temperature methanol synthesis

Biomass is a renewable energy resource and has the potential to make a significant impact on domestic fuel supplies. Biomass can be converted to fuel like methanol via several step process. The process can be split into following main steps: biomass preparation, gasification, gas cooling and cleaning, gas shift and methanol synthesis. Untill now these configuration still has a problem like high production cost, catalyst deactivation, economy of scale and a huge energy requirements. These problems become the leading inhibition for biomass conversion to methanol, which should be resolved to move towards the economical. To address these issues, we developed various process and new configurations for methanol synthesis via methyl formate. This configuration combining two reactors: the one reactor for the carbonylation of methanol and CO to form methyl formate, and the second for the hydrogenolysis of methyl formate and H{sub 2} to form two molecule of methanol. Four plant process configurations were compared with the biomass basis is 300 ton/day. The first configuration (A) is equipped with a steam reforming process for converting methane to CO and H{sub 2} for increasing H{sub 2}/CO ratio. CO{sub 2} removal is necessary to avoid poisoning the catalyst. COSORB process used for the purpose of increasing the partial pressure of CO in the feed gas. The steam reforming process in B configuration is not used with the aim of reducing the number of process equipment, so expect lower investment costs. For C configuration, the steam reforming process and COSORB are not used with the aim of reducing the number of process equipment, so expect lower investment costs. D configuration is almost similar to the configuration A. This configuration difference is in the synthesis of methanol which was held in a single reactor. Carbonylation and hydrogenolysis reactions carried out in the same reactor one. These processes were analyzed in term of technical process, material and energy balance and economic analysis. The presented study is an attempt to compile most of these efforts in order to guide future work to get cheaper low cost investment. From our study the interesting configuration to the next development is D configuration with methanol yield 112 ton/day and capital cost with 526.4 10{sup 6} IDR. The configuration of D with non-discounted and discounted rate had the break-even point approximately six and eight years.

09 BIOMASS FUELS↗

TU-AB-BRD-01: Process Mapping

Current quality assurance and quality management guidelines provided by various professional organizations are prescriptive in nature, focusing principally on performance characteristics of planning and delivery devices. However, published analyses of events in radiation therapy show that most events are often caused by flaws in clinical processes rather than by device failures. This suggests the need for the development of a quality management program that is based on integrated approaches to process and equipment quality assurance. Industrial engineers have developed various risk assessment tools that are used to identify and eliminate potential failures from a system or a process before a failure impacts a customer. These tools include, but are not limited to, process mapping, failure modes and effects analysis, fault tree analysis. Task Group 100 of the American Association of Physicists in Medicine has developed these tools and used them to formulate an example risk-based quality management program for intensity-modulated radiotherapy. This is a prospective risk assessment approach that analyzes potential error pathways inherent in a clinical process and then ranks them according to relative risk, typically before implementation, followed by the design of a new process or modification of the existing process. Appropriate controls are then put in place to ensure that failures are less likely to occur and, if they do, they will more likely be detected before they propagate through the process, compromising treatment outcome and causing harm to the patient. Such a prospective approach forms the basis of the work of Task Group 100 that has recently been approved by the AAPM. This session will be devoted to a discussion of these tools and practical examples of how these tools can be used in a given radiotherapy clinic to develop a risk based quality management program. Learning Objectives: Learn how to design a process map for a radiotherapy process Learn how to perform failure modes and effects analysis analysis for a given process Learn what fault trees are all about Learn how to design a quality management program based upon the information obtained from process mapping, failure modes and effects analysis and fault tree analysis. Dunscombe: Director, TreatSafely, LLC and Center for the Assessment of Radiological Sciences; Consultant to IAEA and Varian Thomadsen: President, Center for the Assessment of Radiological Sciences Palta: Vice President of the Center for the Assessment of Radiological Sciences.

60 APPLIED LIFE SCIENCES↗

The s process in massive stars, a benchmark for neutron capture reaction rates

A clear definition of the contribution from the slow neutron-capture process (s process) to the solar abundances between Fe and the Sr-Zr region is a crucial challenge for nuclear astrophysics. Robust s-process predictions are necessary to disentangle the contribution from other stellar processes producing elements in the same mass region. Nuclear uncertainties are affecting s-process calculations, but most of the needed nuclear input are accessible to present nuclear experiments or they will be in the near future. Neutron-capture rates have a great impact on the s process in massive stars, which is a fundamental source for the solar abundances of the lighter s-process elements heavier than Fe (weak s-process component). In this work we present a new nuclear sensitivity study to explore the impact on the s process in massive stars of 86 neutron-capture rates, including all the reactions between C and Si and between Fe and Zr. We derive the impact of the rates at the end of the He-burning core and at the end of the C-burning shell, where the 22 Ne(α,n) 25 Mg reaction is is the main neutron source. We confirm the relevance of the light isotopes capturing neutrons in competition with the Fe seeds as a crucial feature of the s process in massive stars. For heavy isotopes we study the propagation of the neutron-capture uncertainties, finding a clear difference of the impact of Fe and Co isotope rates with respect to the rates of heavier stable isotopes. The local uncertainty propagation due to the neutron-capture rates at the s-process branching points is also considered, discussing the example of 85 Kr. The complete results of our study for all the 86 neutron-capture rates are available online. Finally, we present the impact on the weak s process of the neutron-capture rates included in the new ASTRAL library (v0.2).

79 ASTRONOMY AND ASTROPHYSICS↗

Manuscript Workflows from and Processed Organic Matter Composition of Experimentally Burned Open Air and Muffle Furnace Vegetation Chars across Differing Burn Severity and Feedstock Types from Pacific Northwest, USA (v3)

This dataset includes processed organic matter chemistry data from an experimental study designed to compare how the chemical composition of organic matter changes across different burn conditions and vegetation materials representative of major land cover types of the Pacific Northwest, USA. Chars were created in a closed muffle furnace or on an open burn table from four different feedstock species representing vegetation commonly impacted by fire regimes across the Pacific Northwest, USA. Source data and associated metadata (including methods and geospatial information) can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1894135 (Grieger et al. 2022). This dataset provides processing scripts and processed data for both solid and dissolved phase organic matter characterization data from experimentally generated chars. These processed data can be used to compare how different burn conditions may influence resultant organic matter chemistry and help further our understanding of potential biogeochemical impacts on river corridors post-fire. The processed data were subsequently analyzed; and the results and ecological implications of the findings were published in peer-reviewed manuscripts. The scripts and workflows used to develop the manuscripts are also included in this data package.This data package was originally published June 2024. It was updated September 2024 (new and modified files) and in January 2025 (modified files). See the change history section in the readme for more details.This dataset is comprised of one data package readme, one data dictionary (dd), one file level metadata (flmd), and folders containing (A) processed data; (B) general processing scripts; and (C) additional folders with specific manuscript analysis scripts and processed data. Step-by-step instructions to assist the user in recreating the workflow used to generate the results in the manuscripts is also provided. The processed data folder includes (1) a folder of processed Parallel Factor Analysis (PARAFAC) and spectra indices outputs from excitation emissions matrix (EEM) fluorescence and absorbance data; (2) a folder of processed solid state carbon-13 (13-C NMR) integrals; (3) folder of high resolution characterization of organic matter via 21 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory) processed data outputs from Formultitude (https://github.com/PNNL-Comp-Mass-Spec/Formultitude), blank corrections and data aggregation, and calculated molecular indices. All files are .pdf, .csv, .html, .Rmd, .R, or .RData.

54 ENVIRONMENTAL SCIENCES↗

A Low-cost, High-yield Process for the Direct Productin of High Energy Density Liquid Fuel from Biomass

The primary objective and outcome of this project was the development and validation of a novel, low-cost, high-pressure fast-hydropyrolysis/hydrodeoxygenation (HDO) process (H 2 Bioil) using supplementary hydrogen (H 2 ) to produce liquid hydrocarbons from biomass. The research efforts under the various tasks of the project have culminated in the first experimental demonstration of the H 2 Bioil process, producing 100% deoxygenated >C4+ hydrocarbons containing 36-40% of the carbon in the feed of pyrolysis products from biomass. The demonstrated H{sub 2}Bioil process technology (i.e. reactor, catalyst, and downstream product recovery) is scalable to a commercial level and is estimated to be economically competitive for the cases when supplementary H 2 is sourced from coal, natural gas, or nuclear. Additionally, energy systems modeling has revealed several process integration options based on the H 2 Bioilprocess for energy and carbon efficient liquid fuel production. All project tasks and milestones were completed or exceeded. Novel, commercially-scalable, high-pressure reactors for both fast-hydropyrolysis and hydrodeoxygenation were constructed, completing Task A. These reactors were capable of operation under a wide-range of conditions; enabling process studies that lead to identification of optimum process conditions. Model compounds representing biomass pyrolysis products were studied, completing Task B. These studies were critical in identifying and developing HDO catalysts to target specific oxygen functional groups. These process and model compound catalyst studies enabled identification of catalysts that achieved 100% deoxygenation of the real biomass feedstock, sorghum, to form hydrocarbons in high yields as part of Task C. The work completed during this grant has identified and validated the novel and commercially scalable H 2 Bioil process for production of hydrocarbon fuels from biomass. Studies on model compounds as well as real biomass feedstocks were utilized to identify optimized process conditions and selective HDO catalyst for high yield production of hydrocarbons from biomass. In addition to these experimental efforts, in Tasks D and E, we have developed a mathematical optimization framework to identify carbon and energy efficient biomass-to-liquid fuel process designs that integrate the use of different primary energy sources along with biomass (e.g. solar, coal or natural gas) for liquid fuel production. Using this tool, we have identified augmented biomass-to-liquid fuel configurations based on the fast-hydropyrolysis/HDO pathway, which was experimentally studied in this project. The computational approach used for screening alternative process configurations represents a unique contribution to the field of biomass processing for liquid fuel production.

09 BIOMASS FUELS↗

Managing Zirconium Chemistry and Phase Compatibility in Combined Process Separations for Minor Actinide Partitioning

In response to the NEUP Program Supporting Fuel Cycle R&D Separations and Waste Forms call DEFOA- 0000799, this report describes the results of an R&D project focusing on streamlining separation processes for advanced fuel cycles. An example of such a process relevant to the U.S. DOE FCR&D program would be one combining the functions of the TRUEX process for partitioning of lanthanides and minor actinides from PUREX(UREX) raffinates with that of the TALSPEAK process for separating transplutonium actinides from fission product lanthanides. A fully-developed PUREX(UREX)/TRUEX/TALSPEAK suite would generate actinides as product(s) for reuse (or transmutation) and fission products as waste. As standalone, consecutive unit-operations, TRUEX and TALSPEAK employ different extractant solutions (solvating (CMPO, octyl(phenyl)-N,Ndiisobutylcarbamoylmethylphosphine oxide) vs. cation exchanging (HDEHP, di-2(ethyl)hexylphosphoric acid) extractants), and distinct aqueous phases (2-4 M HNO 3 vs. concentrated pH 3.5 carboxylic acid buffers containing actinide selective chelating agents). The separate processes may also operate with different phase transfer kinetic constraints. Experience teaches (and it has been demonstrated at the lab scale) that, with proper control, multiple process separation systems can operate successfully. However, it is also recognized that considerable economies of scale could be achieved if multiple operations could be merged into a single process based on a combined extractant solvent. The task of accountability of nuclear materials through the process(es) also becomes more robust with fewer steps, providing that the processes can be accurately modeled. Work is underway in the U.S. and Europe on developing several new options for combined processes (TRUSPEAK, ALSEP, SANEX, GANEX, ExAm are examples). There are unique challenges associated with the operation of such processes, some relating to organic phase chemistry, others arising from the variable composition of the aqueous medium. This project targets in particular two problematic issues in designing combined process systems: managing the chemistry of challenging aqueous species (like Zr 4+ ) and optimizing the composition and properties of combined extractant organic phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗