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Galactic chemical evolution and solar s-process abundances: Dependence on the {sup 13}C-pocket structure

We study the s-process abundances (A ≳ 90) at the epoch of the solar system formation. Asymptotic giant branch yields are computed with an updated neutron capture network and updated initial solar abundances. We confirm our previous results obtained with a Galactic chemical evolution (GCE) model: (1) as suggested by the s-process spread observed in disk stars and in presolar meteoritic SiC grains, a weighted average of s-process strengths is needed to reproduce the solar s distribution of isotopes with A > 130; and (2) an additional contribution (of about 25%) is required in order to represent the solar s-process abundances of isotopes from A = 90 to 130. Furthermore, we investigate the effect of different internal structures of the {sup 13}C pocket, which may affect the efficiency of the {sup 13}C(α, n){sup 16}O reaction, the major neutron source of the s process. First, keeping the same {sup 13}C profile adopted so far, we modify by a factor of two the mass involved in the pocket; second, we assume a flat {sup 13}C profile in the pocket, and we test again the effects of the variation of the mass of the pocket. We find that GCE s predictions at the epoch of the solar system formation marginally depend on the size and shape of the {sup 13}C pocket once a different weighted range of {sup 13}C-pocket strengths is assumed. We obtain that, independently of the internal structure of the {sup 13}C pocket, the missing solar system s-process contribution in the range from A = 90 to 130 remains essentially the same.

79 ASTRONOMY AND ASTROPHYSICS↗

A high-entropy-wind r-process study based on nuclear-structure quantities from the new finite-range droplet model FRDM(2012)

Attempts to explain the source of r-process elements in our solar system (S.S.) by particular astrophysical sites still face entwined uncertainties, stemming from the extrapolation of nuclear properties far from stability, inconsistent sources of different properties (e.g., nuclear masses and β-decay properties), and the poor understanding of astrophysical conditions, which are hard to disentangle. In this paper we present results from the investigation of r-process in the high-entropy wind (HEW) of core-collapse supernovae (here chosen as one of the possible scenarios for this nucleosynthesis process), using new nuclear-data input calculated in a consistent approach, for masses and β-decay properties from the new finite-range droplet model FRDM(2012). The accuracy of the new mass model is 0.56 MeV with respect to AME2003, to which it was adjusted. We compare the new HEW r-process abundance pattern to the latest S.S. r-process residuals and to our earlier calculations with the nuclear-structure quantities based on FRDM(1992). Substantial overall and specific local improvements in the calculated pattern of the r-process between A ≅ 110 and {sup 209}Bi, as well as remaining deficiencies, are discussed in terms of the underlying spherical and deformed shell structure far from stability.

79 ASTRONOMY AND ASTROPHYSICS↗

Reverse engineering nuclear properties from rare earth abundances in the r process

The bulk of the rare earth elements are believed to be synthesized in the rapid neutron capture process or r process of nucleosynthesis. The solar r-process residuals show a small peak in the rare earths around $A\sim 160$, which is proposed to be formed dynamically during the end phase of the r process by a pileup of material. This abundance feature is of particular importance as it is sensitive to both the nuclear physics inputs and the astrophysical conditions of the main r process. Here, we explore the formation of the rare earth peak from the perspective of an inverse problem, using Monte Carlo studies of nuclear masses to investigate the unknown nuclear properties required to best match rare earth abundance sector of the solar isotopic residuals. When nuclear masses are changed, we recalculate the relevant β-decay properties and neutron capture rates in the rare earth region. The feedback provided by this observational constraint allows for the reverse engineering of nuclear properties far from stability where no experimental information exists. We investigate a range of astrophysical conditions with this method and show how these lead to different predictions in the nuclear properties influential to the formation of the rare earth peak. Finally, we conclude that targeted experimental campaigns in this region will help to resolve the type of conditions responsible for the production of the rare earth nuclei, and will provide new insights into the longstanding problem of the astrophysical site(s) of the r process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

r-Process Nucleosynthesis: Connecting Rare-Isotope Beam Facilities with the Cosmos

This is a pivotal time for the study of r-process nucleosynthesis. Recently, a neutron star merger GW170817 was observed in extraordinary detail with gravitational waves and electromagnetic radiation from radio to γ rays. The very red color of the associated kilonova suggests that neutron star mergers are an important r-process site. Astrophysical simulations of neutron star mergers and core collapse supernovae are making rapid progress. Detection of both electron neutrinos and antineutrinos from the next Galactic supernova will constrain the composition of neutrino-driven winds and provide unique nucleosynthesis information. Finally, FRIB and other rare-isotope beam facilities will soon have dramatic new capabilities to synthesize many neutron-rich nuclei that are involved in the r-process. The new capabilities can significantly improve our understanding of the r-process and likely resolve one of the main outstanding problems in classical nuclear astrophysics. Yet, to make best use of the new experimental capabilities and to fully interpret the results, a great deal of infrastructure is needed in many related areas of astronomy, astrophysics, and nuclear theory. We place these experiments in context by discussing astrophysical simulations and observations of r-process sites, observations of stellar abundances, Galactic chemical evolution, and nuclear theory for the structure and reactions of very neutron-rich nuclei. This review paper was initiated at a three week International Collaborations in Nuclear Theory program in June 2016, where we explored promising r-process experiments and discussed their likely impact, and their astronomical, astrophysical, and nuclear theory context.

79 ASTRONOMY AND ASTROPHYSICS↗

A Framework for Process-to-Module Modeling of a-Si/c-Si (HIT) Heterojunction Solar Cells to Investigate the Cell-to-Module Efficiency Gap

The cell-to-module efficiency gap observed in a-Si/c-Si heterojunction solar cells is a key challenge to the broad adoption of this technology. To systematically address this issue, we describe an end-to-end modeling framework to explore the implications of process and device variations at the module level. First, a process model is developed to connect the a-Si deposition parameters to the material properties. Next, a physics-based device model is presented; the model uses the thermionic emission/diffusion theory to capture the essential features of photocurrent and diode injection current. Using the process and device models, the effects of process conditions on cell performance are explored. Finally, the performance of the module, as a function of device and process parameters, is explored to establish the cell-to-module efficiency gap. As a result, the insights developed through this process-to-module modeling framework will help close the cell-to-module efficiency gap of this commercially promising technology.

14 SOLAR ENERGY↗

WE-G-204-01: BEST IN PHYSICS (IMAGING): Effect of Image Processing Parameters On Nodule Detectability in Chest Radiography

Purpose: To investigate the effect of varying system image processing parameters on lung nodule detectability in digital radiography. Methods: An anthropomorphic chest phantom was imaged in the posterior-anterior position using a GE Discovery XR656 digital radiography system. To simulate lung nodules, a polystyrene board with 6.35mm diameter PMMA spheres was placed adjacent to the phantom (into the x-ray path). Due to magnification, the projected simulated nodules had a diameter in the radiographs of approximately 7.5 mm. The images were processed using one of GE’s default chest settings (Factory3) and reprocessed by varying the “Edge” and “Tissue Contrast” processing parameters, which were the two user-configurable parameters for a single edge and contrast enhancement algorithm. For each parameter setting, the nodule signals were calculated by subtracting the chest-only image from the image with simulated nodules. Twenty nodule signals were averaged, Gaussian filtered, and radially averaged in order to generate an approximately noiseless signal. For each processing parameter setting, this noise-free signal and 180 background samples from across the lung were used to estimate ideal observer performance in a signal-known-exactly detection task. Performance was estimated using a channelized Hotelling observer with 10 Laguerre-Gauss channel functions. Results: The “Edge” and “Tissue Contrast” parameters each had an effect on the detectability as calculated by the model observer. The CHO-estimated signal detectability ranged from 2.36 to 2.93 and was highest for “Edge” = 4 and “Tissue Contrast” = −0.15. In general, detectability tended to decrease as “Edge” was increased and as “Tissue Contrast” was increased. A human observer study should be performed to validate the relation to human detection performance. Conclusion: Image processing parameters can affect lung nodule detection performance in radiography. While validation with a human observer study is needed, model observer detectability for common tasks could provide a means for optimizing image processing parameters.

60 APPLIED LIFE SCIENCES↗

Smart Manufacturing Pathways for Industrial Decarbonization and Thermal Process Intensification

Rapid decarbonization is fast becoming the primary environmental and sustainability initiative for many economic sectors. Industry consumes more than 30 % of all primary energy in the United States and accounts for nearly 25 % of all greenhouse gas (GHG) emissions. More than 70 % of energy consumed by the industrial sector is related to thermal processes, which are also the largest contributors of carbon emissions, overwhelmingly due to the combustion of fossil fuels. Thermal process intensification (TPI) seeks to dramatically improve the energy performance of thermal systems through technology pillars focusing on alternative energy sources and processes, supplemental technologies, and waste heat management. The impacts of TPI have significant overlap with the goals of industrial decarbonization (ID) that seeks to phase out all GHG emissions from industrial activities. Emerging supplemental technologies such as smart manufacturing (SM) and the industrial internet of things (IoT) enable significant opportunities for the optimization of manufacturing processes. Combining strategies for TPI and ID with SM and IoT can open and enhance existing opportunities for saving time and energy via approaches such as tighter control of temperature zones, better adjustment of thermal systems for variations in production levels and feedstock properties, and increased process throughput. Data collected by smart processes will also enable new advanced solutions such as digital twins and machine learning algorithms to further improve thermal system savings. Herein, this paper examines the individual pathways of TPI, ID, and SM and how the combination of all three can accelerate energy and GHG reductions.

42 ENGINEERING↗

Tidal Energy Resource Characterization, Velocity and Turbulence Measurements, Processed Data, Cook Inlet, AK, 2021

This submission contains processed datasets from a long-term deployment of 3 moorings and a transect survey of the proposed tidal energy site off the East Forelands in Cook Inlet, AK. The long-term mooring datasets were created from 8 instruments mounted on a Terrasond High Energy Oceanographic Mooring (THEOM) bottom lander and two Mid-Water Mooring (MWM) Stablemoor buoys from 1 July 2021 to 31 August 2021 (60 days). The west-most mooring (MWM1) was deployed at 60.720225 N, 151.436196 W in ~50 m of water. The middle mooring (THEOM) was deployed at 60.720703 N, 151.429500 W in ~52 m of water. The east-most buoy (MWM2) was deployed at 60.720081 N, 151.420896 W in ~50 m of water. Each Stablemoor carried three instruments: 1. A Nortek Vector acoustic Doppler velocimeter (ADV) mounted at the Stablemoor's nose. Data were recorded at 8 Hz on a 5 minute duty cycle every 20 minutes. Data was motion-corrected using the internal IMU and external ADCP bottom-track data and then bin-averaged into 4 minute bins and converted to the Principal (streamwise, cross-stream, vertical) coordinate system. (Note: 30 seconds were trimmed from the beginning and end of each 5 minute duty cycle to account for the filter end-effects from turning on and turning off the IMU.) 2. A down-looking Nortek Signature 1000 kHz acoustic Doppler current profiler (ADCP) mounted in the first Stablemoor instrument well. Data were recorded in 2 Hz with 5-beam burst and bottom-track enabled. Processed data has been averaged into 10 minute bins and converted into the Principal coordinate system. 3. An up-looking Nortek Signature 1000 kHz acoustic Doppler current profiler (ADCP) mounted in the second Stablemoor instrument well. Data were recorded at 4 Hz with 5 beam burst enabled. Processed data has been averaged into 10 minute bins and converted into the Principal coordinate system. Note: the down-facing ADCP on MWM1 failed on July 10th, 2021, only recording 9 days of data. Because ADV motion-correction required bottom track, the ADV from MWM1 also only has 9 days processed. Additionally, only 25 days of data were processed from the MWM2 ADV because it appeared to have been impacted by debris on 7/25. Two instruments were mounted on the THEOM (see MHKDR link further below for THEOM raw data): 4. A Nortek Vector acoustic Doppler velocimeter (ADV). Data were recorded at 8 Hz on a 5 minute duty cycle every 20 minutes. Data was bin-averaged into 5 minute bins, and converted to the Principal coordinate system. 5. A Nortek Signature 500 kHz acoustic Doppler current profiler (ADCP). Data were recorded in 4 Hz in the beam coordinate system from all 5 beams. Processed data has been averaged into 10 minutes bins and converted to the Principal coordinate system.

16 TIDAL AND WAVE POWER↗

Advanced Optical Sensors to Minimize Energy Consumption in Polymer Extrusion Processes (Final Technical Report)

Project Objective: The objectives of this study are to develop an accurate and stable on-line sensor system to monitor color and composition on-line in polymer melts, to develop a scheme for using the output to control extruders to eliminate the energy, material and operational costs of off-specification product, and to combine or eliminate some extrusion processes. Background: Polymer extrusion processes are difficult to control because the quality achieved in the final product is complexly affected by the properties of the extruder screw, speed of extrusion, temperature, polymer composition, strength and dispersion properties of additives, and feeder system properties. Extruder systems are engineered to be highly reproducible so that when the correct settings to produce a particular product are found, that product can be reliably produced time after time. However market conditions often require changes in the final product, different products or grades may be processed in the same equipment, and feed materials vary from lot to lot. All of these changes require empirical adjustment of extruder settings to produce a product meeting specifications. Optical sensor systems that can continuously monitor the composition and color of the extruded polymer could detect process upsets, drift, blending oscillations, and changes in dispersion of additives. Development of an effective control algorithm using the output of the monitor would enable rapid corrections for changes in materials and operating conditions, thereby eliminating most of the scrap and recycle of current processing. This information could be used to identify extruder systems issues, diagnose problem sources, and suggest corrective actions in real-time to help keep extruder system settings within the optimum control region. Using these advanced optical sensor systems would give extruder operators real-time feedback from their process. They could reduce the amount of off-spec product produced and significantly reduce energy consumption. Also, because blending and dispersion of additives and components in the final product could be continuously verified, we believe that, in many cases, intermediate compounding steps could be eliminated (saving even more time and energy).

47 OTHER INSTRUMENTATION↗

Imaging-based optical caliper for objects in hot manufacturing processes

OG Technologies, Inc. (OGT), in conjunction with its industrial and academic partners, proposes to develop an Imaging-Based Optical Caliper (hereafter referred to as OC) for Objects in Hot Manufacturing Processes. The goal is to develop and demonstrate the OC with the synergy of OGT's current technological pool and other innovations to provide a light weight, robust, safe and accurate portable dimensional measurement device for hot objects with integrated wireless communication capacity to enable real time process control. The technical areas of interest in this project are the combination of advanced imaging, Sensor Fusion, and process control. OGT believes that the synergistic interactions between its current set of technologies and other innovations could deliver products that are viable and have high impact in the hot manufacture processes, such as steel making, steel rolling, open die forging, and glass industries, resulting in a new energy efficient control paradigm in the operations through improved yield, prolonged tool life and improved quality. In-line dimension measurement and control is of interest to the steel makers, yet current industry focus is on the final product dimension only instead of whole process due to the limit of man power, system cost and operator safety concerns. As sensor technologies advances, the industry started to see the need to enforce better dimensional control throughout the process, but lack the proper tools to do so. OGT along with its industrial partners represent the indigenous effort of technological development to serve the US steel industry. The immediate market that can use and get benefited from the proposed OC is the Steel Industry. The deployment of the OC has the potential to provide benefits in reduction of energy waste, CO2 emission, waste water amount, toxic waste, and so forth. The potential market after further expended function includes Hot Forging and Freight Industries. The OC prototypes were fabricated, and were progressively tested on-site in several steel mill and hot forging facilities for evaluation. Software refinements and new calibration procedures were also carried out to overcome the discovered glitches. Progress was presented to the hot manufacture facilities worldwide. Evidence showed a great interest and practical need for this product. OGT is in the pilot commercialization mode for this new development. The R&D team also successfully developed a 3D measurement function with no additional investment of hardware or equipment to measure low or room temperature object dimensions. Several tests were conducted in the reality environment to evaluate the measurement results. This new application will require additional development in product design.

47 OTHER INSTRUMENTATION↗

Data Preparation Process for the Buildings Performance Database

The Buildings Performance Database (BPD) includes empirically measured data from a variety of data sources with varying degrees of data quality and data availability. The purpose of the data preparation process is to maintain data quality within the database and to ensure that all database entries have sufficient data for meaningful analysis and for the database API. Data preparation is a systematic process of mapping data into the Building Energy Data Exchange Specification (BEDES), cleansing data using a set of criteria and rules of thumb, and deriving values such as energy totals and dominant asset types. The data preparation process takes the most amount of effort and time therefore most of the cleansing process has been automated. The process also needs to adapt as more data is contributed to the BPD and as building technologies over time. The data preparation process is an essential step between data contributed by providers and data published to the public in the BPD.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Manufacture of Carbon Foam in Continuous Process at Atmospheric Pressure

CFOAM LLC has been manufacturing vitreous carbon foam from coal in panel form for several years. The process is currently set up in batch mode as two steps, where the first step is conducted at very high pressure. In order to reduce cost and increase capacity, a new process for making carbon foam is being developed that can be performed at atmospheric pressure. This advance in turn would enable the development of a continuous manufacturing process, which is also being pursued. Both carbon foam panels and light weight aggregates are being investigate. Progress on the evolution of the pilot scale manufacturing plant and initial results of processing, microstructure, properties and performance of carbon foam products made using this new process will be discussed. This project is being supported by a cooperative agreement with the Department of Energy – National Energy Technology Laboratory (DE-FOA-0002185, Area of Interest 4: Coal-Derived Carbon Foam Produced via a Continuous Process, award number DE-FE-0031992).

01 COAL, LIGNITE, AND PEAT↗

Manufacture of Carbon Foam in Continuous Process at Atmospheric Pressure

CFOAM LLC has been manufacturing vitreous carbon foam from coal in panel form for several years. The process is currently set up in batch mode as two steps, where the first step is conducted at very high pressure. In order to reduce cost and increase capacity, a new process for making carbon foam is being developed that can be performed at atmospheric pressure. This advance in turn would enable the development of a continuous manufacturing process, which is also being pursued. Both carbon foam panels and light weight aggregates are being investigate. Construction of the pilot scale manufacturing plant has been completed and results of processing, microstructure, properties and performance of carbon foam products made using this new process will be discussed. This project is being supported by a cooperative agreement with the Department of Energy – National Energy Technology Laboratory (DE-FOA-0002185, Area of Interest 4: Coal-Derived Carbon Foam Produced via a Continuous Process, award number DE-FE-0031992).

01 COAL, LIGNITE, AND PEAT↗

Integrating Cyber-Informed Engineering into Process Automation

As organizations increasingly automate their core missions and essential functions to address business risks and enhance efficiency, process automation becomes pivotal. This shift, involving minimal or no manual intervention, significantly impacts an organization's cyber-risk landscape. While automation drives efficiencies, it also introduces new cyber risks if not properly managed. Cyber-Informed Engineering (CIE) provides a proactive framework for managing these digital risks, enhancing cyber-resilience in process automation. This document supports organizations in applying CIE principles to mitigate the cyber risks associated with automation. The outlined approach can be independently implemented to improve any organization’s cyber-resilience, ensuring that the advantages of automation do not result in unaddressed or unmanaged digital risks. It serves as a starting point, offering considerations for integrating CIE principles and practices into organizational processes. CIE is presented as an iterative process, fostering continuous improvement and reinforcing the engineering and operational cultures to manage digital risks effectively. The document is structured as follows: Section 1 provides background on CIE and process automation, and their integration. Section 2 explores the twelve CIE principles in the context of process automation, highlighting key questions, engineering considerations, and implications for digital risk management. Section 3 synthesizes the findings and offers recommendations to advance resilience by design.

42 - ENGINEERING↗

Solar Thermal Energy Planner (STEP 1): A New Decision Support Tool for Solar Industrial Process Heat Applications

Solar thermal technologies are a promising technology to supply low-cost thermal energy to industrial processes, but there are often significant barriers to entry to industrial owners considering these technologies for their energy demands. To overcome this barrier and convey economic value to customers, NREL and Sandia National Laboratories developed Solar Thermal Energy Planner (STEP 1), a new web-based decision support tool for solar industrial process heat systems. At SolarPACES 2024, the STEP 1 tool was still under development; progress, methodologies, and a preliminary case study was presented. With the STEP 1 tool launch in May 2025, in this work, the initial version of the full public tool will be presented with demonstrations of its capabilities using a few case studies. First, the user's process heat needs such as location, process media (e.g., steam, air), process temperature, land availability, electricity and fuel costs, among other parameters. STEP 1 features a mapping interface that allows users to draw land and roof boundaries. The process media and temperature inform technology selection criteria modules that determine the appropriate solar thermal collection technologies, as well as congruent heat transfer media (e.g., hot water, oil, salt). Once the solar thermal technology selected, its nominal thermal production for the given site is characterized using NREL's System Advisor Model (SAM). Then, a modified version of NREL's REopt optimal sizing and dispatch optimization tool determines cost-optimal sizing. Within minutes, the user receives the results of the technoeconomics analysis, including the size and performance of the cost-optimal solar-plus-storage system. The cost of the system is compared to business-as-usual (e.g., an existing, standalone natural gas boiler). Users can download key results to store for sensitivity analyses. Examples of flat plate collector, parabolic trough, and molten salt tower applications with and without PV hybridization for different industrial facility types are presented in this work. The STEP 1 tool aims to reduce barriers to the adoption of solar heating solutions stemming from a lack of familiarity and technical background with solar system design options and costs among industry stakeholders.

14 SOLAR ENERGY↗

Microbes as engines of ecosystem function: When does community structure enhance predictions of ecosystem processes?

In this study, microorganisms are vital in mediating the earth’s biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: ‘When do we need to understand microbial community structure to accurately predict function?’ We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.

respiration↗

Investigating the Effects of Mixing Dynamics on Twin-Screw Granule Quality Attributes via the Development of a Physics-Based Process Map

Twin-screw granulation (TSG) is an emerging continuous wet granulation technique that has not been widely applied in the industry due to a poor mechanistic understanding of the process. This study focuses on improving this mechanistic understanding by analyzing the effects of the mixing dynamics on the granule quality attributes (PSD, content uniformity, and microstructure). Mixing is an important dynamic process that simultaneously occurs along with the granulation rate mechanisms during the wet granulation process. An improved mechanistic understanding was achieved by identifying and quantifying the physically relevant intermediate parameters that affect the mixing dynamics in TSG, and then their effects on the granule attributes were analyzed by investigating their effects on the granulation rate mechanisms. The fill level, granule liquid saturation, extent of nucleation, and powder wettability were found to be the key physically relevant intermediate parameters that affect the mixing inside the twin-screw granulator. An improved geometrical model for the fill level was developed and validated against existing experimental data. Finally, a process map was developed to depict the effects of mixing on the temporal and spatial evolution of the materials inside the twin-screw granulator. This process map illustrates the mechanism of nucleation and the growth of the granules based on the fundamental material properties of the primary powders (solubility and wettability), liquid binders (viscosity), and mixing dynamics present in the system. Furthermore, it was shown that the process map can be used to predict the granule product quality based on the granule growth mechanism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ON THE r -PROCESS ENRICHMENT OF DWARF SPHEROIDAL GALAXIES

Recent observations of Reticulum II have uncovered an overabundance of r -process elements compared to similar ultra-faint dwarf spheroidal galaxies (UFDs). Because the metallicity and star formation history of Reticulum II appear consistent with all known UFDs, the high r -process abundance of Reticulum II suggests enrichment through a single, rare event, such as a double neutron star (NS) merger. However, we note that this scenario is extremely unlikely, as binary stellar evolution models require significant supernova natal kicks to produce NS–NS or NS–black hole (BH) mergers, and these kicks would efficiently remove compact binary systems from the weak gravitational potentials of UFDs. We examine alternative mechanisms for the production of r -process elements in UFDs, including a novel mechanism wherein NSs in regions of high dark matter (DM) density implode after accumulating a BH-forming mass of DM. We find that r -process proto-material ejection by tidal forces, when a single NS implodes into a BH, can occur at a rate matching the r -process abundance of both Reticulum II and the Milky Way. Remarkably, DM models which collapse a single NS in observed UFDs also solve the missing pulsar problem in the Milky Way Galactic Center. We propose tests specific to DM r -process production which may uncover or rule out this model.

79 ASTRONOMY AND ASTROPHYSICS↗