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DOE OSTI2020

Predicting Biological Cleanliness: An Empirical Bayes Approach for Spacecraft Bioburden Accounting

To comply with the international planetary protection policy set forth by the Committee on Space Research and NASA Agency level requirements, spacecraft destined to biologically sensitive planetary bodies have to minimize terrestrial biological contamination. Analysis, testing and inspection are the standard forward verification activities that are used to demonstrate compliance with the biological contamination requirements. For testing of spacecraft surface areas, a swab or wipe sample is collected from surfaces prior to last access and subsequently processed in the lab using NASA Approved Planetary Protection Methods for Culture Based Assays. Raw data resulting from this assay is then statistically treated employing a mathematical paradigm stemming from the 1970’s Viking Lander Project to generate the bioburden density and total microbial bioburden present. This standard approach arbitrarily accounts for error and provides an upper conservative bound as it reports the maximum number of spores estimated to be present on flight hardware surfaces. A bioburden density estimate factors in the following variables: the observed bioburden count, representative volume processed, sampling efficiencies. Notably, to account for error in the approach, a 0 observed count is arbitrarily changed to a count of 1 for each hardware grouping. The data generated by spacecraft bioburden verification campaigns in the past have resulted in <80% of wipes and <90% of swabs containing a bioburden count of 0. As such, having a robust and well documented statistical approach for dealing with the probability of low incident rates is necessary to be able to estimate spacecraft bioburden. Being able to statistically describe the bioburden distribution and associated confidence level is a gamechanger for the development of bioburden allocations during mission design and will allow for tighter management of risk throughout spacecraft build. Thus, Empirical Bayes statistical approach was evaluated to estimate the microbial bioburden on spacecraft to mitigate the aforementioned mathematical concerns and provide a probabilistic bioburden distribution of the flight hardware surface. For application of this approach to performing bioburden calculations, a range of non-informative prior assumptions on hardware surfaces are explored for Bayesian analyses while informative priors using posterior distributions from prior assays are utilized for Empirical Bayes analyses. Several non-informative priors are currently under investigation to assess fitness including use of these priors to serve as a foundation to build off of NASA specification values or a basis of risk to account for unknowns during the integration and testing process. Informative priors under consideration are generated using sampled bioburden values from hardware originating within like processing environments (e.g. vendor cleaning process or similar assembly process), temporal spacecraft status events as a prediction for hardware cleanliness of future samples, and heritage system bioburden actuals to predict allocation for subsequent missions. Informative priors and probabilistic bioburden distributions are then validated using data sets from the Mars Exploration Rover, Mars Science Laboratory, and InSight missions. Using Empirical Bayes approach to generate a probabilistic bioburden distribution as demonstrated through mission use cases provides a valid approach for use in the end-to-end requirements verification process.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Bayesian Framework for Bioburden Density Estimation in Planetary Protection

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Hubble Space Telescope Captures UGC 12591: bulge/disc properties, star formation and ‘missing baryons’ census in a very massive and fast-spinning hybrid galaxy

We present Hubble Space Telescope (HST) observations of the nearby, massive, highly rotating hybrid galaxy UGC 12591, along with observations in the UV to FIRbands. HST data in V, I, and H bands is used to disentangle the structural components. Surface photometry shows a dominance of the bulge over the disc with an H-band B/D ratio of $69{{\,\rm per\,cent}}$. The spectral energy distribution (SED) fitting reveals an extremely low global star formation rate (SFR) of $\rm \sim 0.1\!-\!0.2\, M_\odot \, yr^{-1}$, exceptionally low for the galaxy’s huge stellar mass of $\rm 1.6\times 10^{11}M_\odot$, implying a strong quenching of its SFR with a star formation efficiency of 3–5 per cent. For at least the past $\rm 10^{8}$ yr, the galaxy has remained in a quiescent state as a sterile, ‘red and dead’ galaxy. UGC 12591 hosts a supermassive black hole (SMBH) of $\rm 6.18\times 10^{8} \, M_\odot$, which is possibly quiescent at present, i.e. we neither see large ($\rm \gt 1 kpc$) radio jets nor the SMBH contributing significantly to the mid-IR SED, ruling out strong radiative feedback of AGN. We obtained a detailed census of all observable baryons with a total mass of $\rm 6.46\times 10^{11} \, M_\odot$ within the virial radius, amounting to a baryonic deficiency of ${\sim }85{{\,\rm per\,cent}}$ relative to the cosmological mean. Only a small fraction of these baryons reside in a warm/hot circumgalactic X-ray halo, while the majority are still unobservable. We discussed various astrophysical scenarios to explain its unusual properties. Our work is a major step forward in understanding the assembly history of such extremely massive, isolated galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Comprehensive uncertainty quantification (UQ) for full engineering models by solving probability density function (PDF) equation

This report details a new method for propagating parameter uncertainty (forward uncertainty quantification) in partial differential equations (PDE) based computational mechanics applications. The method provides full-field quantities of interest by solving for the joint probability density function (PDF) equations which are implied by the PDEs with uncertain parameters. Full-field uncertainty quantification enables the design of complex systems where quantities of interest, such as failure points, are not known apriori. The method, motivated by the well-known probability density function (PDF) propagation method of turbulence modeling, uses an ensemble of solutions to provide the joint PDF of desired quantities at every point in the domain. A small subset of the ensemble is computed exactly, and the remainder of the samples are computed with approximation of the driving (dynamics) term of the PDEs based on those exact solutions. Although the proposed method has commonalities with traditional interpolatory stochastic collocation methods applied directly to quantities of interest, it is distinct and exploits the parameter dependence and smoothness of the dynamics term of the governing PDEs. The efficacy of the method is demonstrated by applying it to two target problems: solid mechanics explicit dynamics with uncertain material model parameters, and reacting hypersonic fluid mechanics with uncertain chemical kinetic rate parameters. A minimally invasive implementation of the method for representative codes SPARC (reacting hypersonics) and NimbleSM (finite- element solid mechanics) and associated software details are described. For solid mechanics demonstration problems the method shows order of magnitudes improvement in accuracy over traditional stochastic collocation. For the reacting hypersonics problem, the method is implemented as a streamline integration and results show very good accuracy for the approximate sample solutions of re-entry flow past the Apollo capsule geometry at Mach 30.

42 ENGINEERING↗

DOE OSTI2020

Initial Radiation of Nuclear Power Plant Components (CRADA NFE-17-06892 Final Report)

As advanced reactor concepts are developed, instrumentation and control (I&C) cables and sensors will play a significant role in assuring their operation is well understood, and safety-related process information can be collected reliably over the course of their design life. As a first step to develop acceptance criteria and define the limits of currently available nuclear I&C cable and sensor technology, a collaboration between Oak Ridge National Laboratory and Analysis and Measurement Services (AMS) Corporation was initiated under the Gateway for Accelerated Innovation in Nuclear (GAIN) Program. This collaborative effort focused on providing technical information related to the combined thermal and radiation aging of nuclear power plant (NPP) cables, companion NPP cable insulation samples, and two prototype temperature and two pressure sensors. This work was carried out using the instrumented gamma irradiation system that is part of the High Flux Isotope Reactor Gamma Irradiation Facility (HFIR GIF). This system provided the opportunity for the condition of the prototype sensors to be tracked during the irradiation in order to determine their functional limits with greater granularity when compared to a simple irradiation insertion at the HFIRGIF. Experimental assemblies for sensor irradiation were successfully completed, and sensor irradiation to accumulated dose of 3000 kGy at a rate of approximately 6 kGy/hr was carried out. Two prototype temperature assemblies were continuously monitored during exposure to 3000 kGy and found to have no observable degradation from the irradiation. Two pressure sensors were first irradiated to 1000 kGy. At which point, one of the sensors was found to operate normally; however, a second sensor failed the operability test. The operable pressure sensor output was then continuously monitored from 1000 kGy to 3000 kGy. The sensor output exhibited steady trendable drift versus the accumulated radiation dose. At the conclusion of the irradiation, the four test sensors were released for laboratory calibration checks. The calibration check of the temperature sensors found no significant change after irradiation compared to baseline measurements before irradiation; however, both pressure sensors failed the post-test calibration checks and both sensors were not functioning properly. These results will help inform sensor manufacturers and I&C design engineers of potential limitations of these types of sensors for use in high radiation environments associated with the compact configuration of new Small Modular Reactors (SMRs) such as NuScale’s reactor power module. Irradiations on NPP cables and companion samples were not completed due to programmatic delays, however a path forward that was based on lessons learned from this project was defined to accommodate future, comparable instrumented gamma irradiations at the HFIR GIF.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

The role of quantum computing in advancing scientific high-performance computing: A perspective from the ADAC institute

Quantum computing (QC) has gained significant attention over the past two decades due to its potential for speeding up classically demanding tasks. This transition from an academic focus to a thriving commercial sector is reflected in substantial global investments. While advancements in qubit counts and functionalities continue at a rapid pace, current quantum systems still lack the scalability for practical applications, facing challenges such as too high error rates and limited coherence times. Here, this perspective paper examines the relationship between QC and high-performance computing (HPC), highlighting their complementary roles in enhancing computational efficiency. It is widely acknowledged that even fully error-corrected QC will not be suited for all computational tasks. Rather, future compute infrastructures are anticipated to employ quantum acceleration within hybrid systems that integrate HPC and QC. While QC can enhance classical computing, traditional HPC remains essential for maximizing quantum acceleration. This integration is a priority for supercomputing centers and companies, sparking innovation to address the challenges of merging these technologies. The novelty of this work lies in its unique perspective, reflecting the collective insights of the Accelerated Data Analytics and Computing (ADAC) Institute, a global consortium of over 20 leading HPC centers. Recognizing the growing importance of QC, ADAC established a Quantum Computing Working Group in 2023 to foster collaboration and knowledge-sharing among its members. This paper synthesizes insights from the group’s collaborative efforts and incorporates findings from a member survey that captures shared experiences, ongoing projects, and strategic directions. By outlining the current landscape and challenges of QC integration into HPC ecosystems, this work offers HPC specialists practical and forward-looking guidance on the opportunities and implications of QC in computationally intensive endeavors.

Accelerated Data Analytics and↗

DOE OSTI2022

Enhanced collisionless laser absorption in strongly magnetized plasmas

We report that strongly magnetizing a plasma adds a range of waves that do not exist in unmagnetized plasmas and enlarges the laser-plasma interaction (LPI) landscape. In this paper, we use particle-in-cell simulations to investigate strongly magnetized LPI in one dimension under conditions relevant for magneto-inertial fusion experiments, focusing on a regime where the electron-cyclotron frequency is greater than the plasma frequency and the magnetic field is at an oblique angle with respect to the wave vectors. We show that when electron-cyclotron-like hybrid wave frequency is about half the laser frequency, the laser light resonantly decays to magnetized plasma waves via primary and secondary instabilities with large growth rates. These distinct magnetic-field-controlled instabilities, which we collectively call two-magnon decays, are analogous to two-plasmon decays in unmagnetized plasmas. Since additional phase mixing mechanisms are introduced by the oblique magnetic field, collisionless damping of large-amplitude magnetized waves substantially broadens the electron distribution function, especially along the direction of the magnetic field. During this process, energy is transferred efficiently from the laser to plasma waves and then to electrons, leading to a large overall absorptivity when strong resonances are present. The enhanced laser energy absorption may explain hotter-than-expected temperatures observed in magnetized laser implosion experiments and may also be exploited to develop more efficient laser-driven x-ray sources.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Beyond $\rho ^{2/3}$ scaling: microscopic origins and multimessengers of high-density nuclear symmetry energy

The nature and Equation of State (EOS) of dense neutron-rich matter are still very poorly known, while they have broad impacts on many interesting issues in both astrophysics and nuclear physics. In particular, the nuclear symmetry energy $E_{\textrm{sym}}(\rho )$ encoding the cost to make nuclear matter more neutron-rich has been the most uncertain component of the EOS of dense neutron-rich nucleonic matter. It significantly affects the radii, tidal deformations, cooling rates, and frequencies of various oscillation modes of isolated neutron stars as well as the strain amplitude and frequencies of gravitational waves from their mergers, besides its many effects on the structures of nuclei as well as the dynamics and observables of their collisions. Siemens (1970s) observed that $E_{\textrm{sym}}(\rho )$ scales as $(\rho /\rho _0)^{2/3}$ near the saturation density $\rho _0$ of nuclear matter, since both the kinetic part and the potential contribution (quadratic in momentum) exhibit this dependence. The scaling holds if: (1) the nucleon isoscalar potential is quadratic in momentum, and (2) the isovector interaction is weakly density-dependent. After examining many empirical evidences and understanding theoretical findings in the literature, we conclude that: (1) Siemens’ $\rho ^{2/3}$ scaling is robust and serves as a valuable benchmark for both nuclear theories and experiments up to $2\rho _0$ but breaks down at higher densities, (2) Experimental and theoretical findings about $E_{\textrm{sym}}(\rho )$ up to $2\rho _0$ are broadly consistent, but uncertainties remain large for its curvature $K_{\textrm{sym}}(\rho )$ and higher-order parameters, (3) Above $2\rho _0$ , uncertainties grow due to poorly constrained spin-isospin-dependent tensor and three-body forces as well as the resulting nucleon short-range correlations. Looking forward, combining signals from both observations of neutron stars and terrestrial heavy-ion reaction experiments is the most promising path to finally constraining the high-density $E_{\textrm{sym}}(\rho )$ and the EOS of supradense neutron-rich matter. Multiple examples of community efforts to further constrain the high-density $E_{\textrm{sym}}(\rho )$ using both real and mocked data of present and future high-precision observations of neutron stars, as well as heavy-ion collisions involving high-energy rare isotopes, are briefly reviewed.

Li, Bao-An [East Texas A & M Univ., Commerce, TX (↗

DOE OSTI2021

Simulation of decelerating streamers in inhomogeneous atmosphere with implications for runaway electron generation

The dynamics of positive and negative streamers is numerically simulated in atmospheric pressure air in the range of parameters corresponding to the streamer deceleration and termination in the middle of the discharge gap. A detailed comparison with experiments in air at constant and variable density demonstrates good agreement between the 2D simulation results and the observations. It is shown that positive and negative streamers behave in radically different ways when decelerating and stopping. When the head potential drops, the negative streamer transits to the mode in which the propagation is due to the forward electron drift. In this case, the radius of the ionization wave front increases, whereas the electric field at the streamer head decreases further and the streamer stops. Its head diameter continues to increase due to the slow drift of free electrons in the residual under-breakdown field. On the contrary, the only advancement mechanism for a positive streamer with a decreasing head potential is a decrease in the effective radius of the ionization wave, leading to a local increase in the electric field. This mechanism makes it possible to compensate for the reduction in the efficiency of gas photoionization at small head diameters. A qualitative 1D model is suggested to describe streamer deceleration and stopping for different discharge polarities. Estimates show that, during positive streamer stopping, the local electric field at the streamer head can exceed the threshold corresponding to the transition of electrons to the runaway mode when the head potential (relative to the surrounding space) decreases to~1.2 kV in atmospheric pressure air. In this case, pulsed generation of a beam of runaway electrons directed into the channel of a stopping positive streamer can occur. The energy of the formed pulsed electron beam depends on the intensity of photoionization in front of the streamer head. This energy can vary from 700 V (when increasing the photoionization rate by a factor of 10 with respect to the value in atmospheric pressure air) to 2.6 kV (when decreasing the photoionization rate by a factor of 1000). It is possible that this behavior of decelerating positive streamers can explain the observed bursts of x-ray radiation during the streamer propagation in long air gaps.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Bicarbonate-Carbonate Selectivity through Nanofiltration for Direct Air Capture of Carbon Dioxide

Direct air capture (DAC) of carbon dioxide is one approach among many proposed that is capable of offsetting hard-to-avoid emissions. In previous work, we developed the alkalinity concentration swing (ACS) method, which is driven through concentrating an alkaline solution that has been loaded with atmospheric CO 2 by desalination technologies, such as reverse osmosis or capacitive deionization. Though the ACS is promising in terms of energy usage and implementation, its absorption rate and water requirements are infeasible for a large-scale DAC process. Here, we propose an improvement on the ACS, the bicarbonate-enriched alkalinity concentration swing (BE-ACS), which selects bicarbonate ions from a stream of aqueous alkaline solution that has absorbed atmospheric CO 2 . The bicarbonate-rich stream is then concentrated, which greatly increases its CO 2 partial pressure, and then CO 2 is extracted from solution. We experimentally investigate the use of pressure-driven nanofiltration (NF) membrane-based separation to select bicarbonate ions over carbonate ions. We screen commercial membranes and select one high-performance membrane for detailed studies, quantifying its bicarbonate-carbonate selectivity factor and bicarbonate-passage factor. Feed pH, the combined concentration of aqueous CO 2 , bicarbonate, and carbonate species (or dissolved inorganic carbon), alkalinity, and permeation flux are systematically varied to study NF separation properties. We find that the selectivity factor, which exceeds 30 times in certain regimes, increases with higher feed pH and higher alkalinity. Lastly, the performance metrics of the selected NF membrane are input into a theoretical BE-ACS cycle analysis, and the required energy input and cycle capacity output are evaluated. Ideal cycle energy is found to be as low as around 250 kJ/mol, with opportunities identified for further decreases through process engineering and forward osmosis energy recovery.

animal feed↗

DOE OSTI2021

Cambium Documentation: Version 2021

Cambium is a tool that assembles structured data sets of simulated hourly emission, cost, and operational data for modeled futures of the U.S. electric sector with metrics designed to be useful for long-term decision-making. It was built to expand the metrics reported in the National Renewable Energy Laboratory's (NREL's) Standard Scenarios - an annually released set of projections of how the U.S. electric sector could evolve across a suite of different potential futures, looking forward through 2050 (Cole et al. 2021) Information about Cambium and related publications can be found at https://nrel.gov/analysis/cambium.html, and the Cambium data sets for the Standard Scenarios can be viewed and downloaded at https://cambium.nrel.gov/. In this documentation, we define the metrics reported in Cambium databases (Section 4) and document the Cambium-specific methods for calculating those metrics (Section 5). As this document is intended to cover multiple Cambium data releases, we do not document specific scenarios here - for individual data releases, readers should look for an accompanying report that describes the assumptions and data that underlie that specific release. For Cambium databases that are built on NREL's Standard Scenarios, for example, reports describing the scenarios can be found on the Standard Scenarios web site (https://www.nrel.gov/analysis/standard-scenarios.html).

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Jupiter Laser Facility Annual Report, FY 2025

Dear JLF community, I cannot believe I am now entering my third year as JLF director — time definitely flies when you are having fun! FY25 was another pivotal year for the Jupiter Laser Facility, marked by both scientific achievement and growing visibility for our community. Building on the successful reopening and refurbishment of the facility, we continued to demonstrate how JLF drives innovation in high energy density and fusion energy science, laser technology, and workforce development. Across Janus, Titan, and COMET, users executed a diverse portfolio of experiments, from dynamic compression and opacity measurements to laser plasma interactions, laboratory astrophysics, and advanced diagnostics. These efforts are highlighted in this report, including the development of new probes that capture the time evolution of plasmas on a single shot, and diagnostics and platforms that are already impacting experiments at NIF and other large facilities. JLF continues to serve as both a testbed for new ideas and a bridge to larger scale campaigns. FY25 also showcased the broader role of JLF within the Laboratory and the national HED science ecosystem. The NIF JLF User Groups Meeting in February brought nearly 180 participants to Livermore and highlighted the scientific progress made during JLF’s first full year of renewed operations. JLF research and users were recognized with Director’s Institutional Awards and Early and Mid Career awards, underscoring the quality and impact of the work performed here. Our team also contributed prominently to national conversations about laser safety, plasma physics, and inertial fusion energy through invited talks, conferences, and professional society leadership. JLF’s integration with LaserNetUS deepened this year as well. We launched a new technical exchange program across LaserNetUS facilities and kicked it off with a JLF team visit to the BELLA Center at Lawrence Berkeley National Laboratory. These exchanges are strengthening operations, sharing best practices, and improving the user experience across the network. Filming for the LaserNetUS “Behind the Scenes” series and participation in the annual LaserNetUS meeting further increased the visibility of our facility and our users. At the same time, JLF continues to play a central role in ambitious new programs, such as the Big Aperture Thulium laser effort funded through one of the DOE Office of Science Microelectronics Science Research Centers, which will use JLF infrastructure to explore next generation high rep rate lasers for EUV and x-ray source development. A core part of our mission remains training the next generation of scientists. In FY25, we welcomed another cohort of summer students, who joined experimental teams on Titan and presented their research at LLNL’s student poster symposium and national inertial fusion energy meetings. JLF users and early career scientists showcased their work at conferences across the country, highlighting experiments performed at the facility. These hands on experiences, and the mentoring provided by our staff and user teams, are central to JLF’s identity as a true user facility. Finally, FY25 reinforced JLF’s role as a focal point for partnerships and outreach. We hosted visits from international collaborators, science leaders, and we shared the story of the facility through venues such as the Big Ideas Lab podcast. These interactions help connect our work to a broader scientific and policy audience and open new pathways for collaboration. As we look ahead, the combination of refurbished hardware, new capabilities like STILETTO and enhanced short pulse performance on Titan, strong partnerships across LLNL and LaserNetUS, and a growing user community positions JLF for an even more ambitious program in the coming years. I am deeply grateful to our technical and operations staff for their dedication, to our LLNL partners for their continued support, and to our users for bringing bold, creative ideas to the facility. I look forward to more experiments, capabilities, partnerships, and groundbreaking science in the years to come! With brightest regards, Félicie Albert, JLF Director.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Deep learning models for interpretation of point of care ultrasound in military working dogs

Introduction: Military working dogs (MWDs) are essential for military operations in a wide range of missions. With this pivotal role, MWDs can become casualties requiring specialized veterinary care that may not always be available far forward on the battlefield. Some injuries such as pneumothorax, hemothorax, or abdominal hemorrhage can be diagnosed using point of care ultrasound (POCUS) such as the Global FAST® exam. This presents a unique opportunity for artificial intelligence (AI) to aid in the interpretation of ultrasound images. In this article, deep learning classification neural networks were developed for POCUS assessment in MWDs. Methods: Images were collected in five MWDs under general anesthesia or deep sedation for all scan points in the Global FAST® exam. For representative injuries, a cadaver model was used from which positive and negative injury images were captured. A total of 327 ultrasound clips were captured and split across scan points for training three different AI network architectures: MobileNetV2, DarkNet-19, and ShrapML. Gradient class activation mapping (GradCAM) overlays were generated for representative images to better explain AI predictions. Results: Performance of AI models reached over 82% accuracy for all scan points. The model with the highest performance was trained with the MobileNetV2 network for the cystocolic scan point achieving 99.8% accuracy. Across all trained networks the diaphragmatic hepatorenal scan point had the best overall performance. However, GradCAM overlays showed that the models with highest accuracy, like MobileNetV2, were not always identifying relevant features. Conversely, the GradCAM heatmaps for ShrapML show general agreement with regions most indicative of fluid accumulation. Discussion: Overall, the AI models developed can automate POCUS predictions in MWDs. Preliminarily, ShrapML had the strongest performance and prediction rate paired with accurately tracking fluid accumulation sites, making it the most suitable option for eventual real-time deployment with ultrasound systems. Further integration of this technology with imaging technologies will expand use of POCUS-based triage of MWDs.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Global polarization of hyperons and spin alignment of vector mesons in quark matters

Relativistic heavy ion collider (RHIC) as a dedicated nuclear facility has made a few major discoveries in physics. This year marks the 30th year STAR Collaboration formation and the 23th year of STAR detector operation and data collection at RHIC. In the last two decades, STAR has collected many datasets, exhibiting scientific versatility and flexibility of the RHIC facility. The total dataset in the first year is less than 1 million good events, and currently there are about 1 billion events per dataset. The Global Hyperon Polarization was proposed in 2004. This immediately prompted the STAR Collaboration to search for this phenomenon from the early datasets. The null results were presented at Quark Matter Conference in Shanghai in 2006 and subsequently published. Although there were peripheral and continuous efforts in the following decade, no positive result has been observed experimentally. This situation changed in the following decade with the upgrade of high data rate and time-of-flight (TOF) detector and the progress of the Beam Energy Scan Phase I (BES-I). The experimental discoveries of the global polarization of hyperons in 2017 and the spin alignment of vector mesons in 2023 at RHIC-STAR confirm the theory which was established nearly twenty years ago. The theory and these measurements open the way to studying the properties of the hot and dense nuclear matter created in high-energy heavy ion collisions from a new degree of freedom, spin. We briefly review these discoveries from the proposals of theory to the experimental measurements, and summarize the related measurements at the existing facilities and the theoretical explanations to the original proposal. The basic understanding and the original proposal are still valid and fundamental, that is, the angular momentum of system can transform into a spin effect observable in experiment. However, it appears that in each case a new model is needed to explain the new experimental observation. We need a more basic theory to help us unify all these spin related phenomena. Over the past five years, STAR has successfully installed 3 new detectors and we have begun to see the physical analysis results from datasets with those new functions. What makes the STAR detector viable after 20 years of operation is its continuous evolution through successful upgrades, with new scientific programs added year by year. The next big thing is to forward upgrade a tracking system (3 layers of silicon strips and 4 layers of sTGC chambers) and a calorimetry system (electromagnetic and hadronic calorimeters). In addition to studying the spin structure of protons by using the polarized proton beams at RHIC, the upgrades also provide a unique ability to investigate the origin of Λ Global Polarization as a function of rapidity and rapidity (de-)correlations in Au+Au collisions.

Physics↗

DOE OSTI2022

Direct and Sensitive Electrochemical Evaluation of Pramipexole Using Graphitic Carbon Nitride (gCN) Sensor

Pramipexole (PMXL) belongs to the benzothiazole class of aromatic compounds and is used in treating Parkinson’s disease; however, overdosage leads to some abnormal effects that could trigger severe side effects. Therefore, it demands a sensitive analytical tool for trace level detection. In this work, we successfully developed an electrochemical sensor for the trace level detection of PMXL, using the voltammetric method. For the analysis, graphitic carbon nitride (gCN) was opted and synthesized by using a high-temperature thermal condensation method. The synthesized nanoparticles were employed for surface characterization, using transmission electron microscopy (TEM), X-ray diffraction (XRD), and atomic force microscopy (AFM) techniques. The electrochemical characterization of the material was evaluated by using the electrochemical impedance spectroscopy (EIS) technique to evaluate the solution–electrode interface property. The cyclic voltammetry (CV) behavior of PMXL displayed an anodic peak in the forward scan, indicating that PMXL underwent electrooxidation, and an enhanced detection peak with lower detection potential was achieved for gCN-modified carbon paste electrode (gCN·CPE). The influence of different parameters on the electrochemical behavior was analyzed, revealing the diffusion governing the electrode process with an equal number of hydronium ions and electron involvement. For the fabricated gCN·CPE, good linearity range was noticed from 0.05 to 500 µM, and a lower detection limit (L D ) of 0.012 µM was achieved for the selected concentration range (0.5 to 30 µM). Selectivity of the electrode in PMXL detection was investigated by conducting an interference study, while the tablet sample analysis demonstrates the sensitive and real-time application of the electrode. The good recovery values for the analysis illustrate the efficiency of the electrode for PMXL analysis.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Springtime Drought Shifts Carbon Partitioning of Recent Photosynthates in 10-Year Old Picea mariana Trees, Causing Restricted Canopy Development

Springtime bud-break and shoot development induces substantial carbon (C) costs in trees. Drought stress during shoot development can impede C uptake and translocation. This is therefore a channel through which water shortage can lead to restricted shoot expansion and physiological capacity, which in turn may impact annual canopy C uptake. We studied effects of drought and re-hydration on early season shoot development, C uptake and partitioning in five individual 10-year old Picea mariana [black spruce] trees to identify and quantify dynamics of key morphological/physiological processes. Trees were subjected to one of two treatments: (i) well-watered control or (ii) drought and rehydration. We monitored changes in morphological [shoot volume, leaf mass area (LMA)], biochemical [osmolality, non-structural carbohydrates (NSC)] and physiological [rates of respiration (R d ) and light-saturated photosynthesis ( A sat )] processes during shoot development. Further, to study functional compartmentalization and use of new assimilates, we 13 C-pulse labeled shoots at multiple development stages, and measured isotopic signatures of leaf respiration, NSC pools and structural biomass. Shoot water potential dropped to a minimum of −2.5 MPa in shoots on the droughted trees. Development of the photosynthetic apparatus was delayed, as shoots on well-watered trees broke-even 14 days prior to shoots from trees exposed to water deficit. R d decreased with shoot maturation as growth respiration declined, and was lower in shoots exposed to drought. We found that shoot development was delayed by drought, and while rehydration resulted in recovery of A sat to similar levels as shoots on the well-watered trees, shoot volume remained lower. Water deficit during shoot expansion resulted in longer, yet more compact (i.e., with greater LMA) shoots with greater needle osmolality. The 12 C: 13 C isotopic patterns indicated that internal C partitioning and use was dependent on foliar developmental and hydration status. Shoots on drought-stressed trees prioritized allocating newly fixed C to respiration over structural components. In conclusion, temporary water deficit delayed new shoot development and resulted in greater LMA in black spruce. Since evergreen species such as black spruce retain active foliage for multiple years, impacts of early season drought on net primary productivity could be carried forward into subsequent years.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

On the feasibility of using physics-informed machine learning for underground reservoir pressure management

In this work, we evaluate the feasibility of using physics-informed machine learning (PIML) for underground energy-related pressure management. To this end, we develop a PIML framework to manage underground reservoir pressures by training neural networks to determine fluid extraction rates for dedicated extraction wells during fluid injection operations given a range of reservoir conditions (e.g., transmissivity and storativity). We implement an automatically-differentiable analytical physics model of fluid flow in porous media within the PIML framework as a proxy for more complicated models. This allows us to execute a sufficient number of training scenarios to fully evaluate the feasibility of using PIML to support pressure management activities. We quantify the number of physics-model parameters required for automatic differentiation to become more efficient than finite-difference gradient calculations. We use a simple scenario with a single injector, extractor, and critical location for our feasibility analysis. We evaluate the effect of the size of the training dataset (i.e., the number of reservoir condition samples) on the accuracy and efficiency of the PIML framework. For an equivalent number of model evaluations, the larger training dataset took less time to train and produced a neural network that was able to more accurately manage reservoir pressures. We also evaluate the effect of the training dataset batch size (i.e., number of reservoir condition samples used to update the neural network coefficients during training; i.e., how the training dataset is partitioned). While training ran faster with larger batch sizes, they produced neural networks that managed pressures less accurately. We demonstrate the approach on a more complex scenario involving 10 injectors, 10 extractors, and 4 critical locations (a relatively high well density of 20 wells/km2). We provide the number of forward and adjoint model evaluations required in each case as an indication of the feasibility of using PIML for pressure management when more complicated physics models with longer execution times are used.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Decay Curve Correction Analysis Report

The decay curve analysis that is done on the short-lived radionuclide gas samples is used to differentiate between gaseous radionuclides that have the same characteristic gamma decay energy, 511 kiloelectron-volts (keV). A sample of stack gas is isolated and the total counts in the 511 keV peak are counted repeatedly in 10-second intervals to evaluate the decay rate of the sample over time. Analysis of this decay data required a series of steps. First, a raw data report is generated by the gamma acquisition system, based on an analysis template within the acquisition software. The data report file was then loaded into Microsoft Word, and a macro was used to perform minor formatting (remove colons and insert tabs between data columns) to allow analysis within Excel. The file is then saved as a text file at this point. The text file is then uploaded into Excel and a series of macros are used to add labels, calculate radioactive decay constants, and analyze the gamma decay data using linear regression techniques. The analysis template has been used since 1998 for stack 53000303 (TA-53, building 0003, exhaust stack 03) and 2000 for stack 53000702. The overall process, including the gamma report format and the macros used in Word and Excel for processing the report, had remained unchanged until 2015. In October of 2015, staff made a change to the report template in the gamma acquisition software which resulted in an error in the calculations later performed by the Excel macro. This error was not caught until a more in-depth review of the analysis took place regarding 2020 data. This report covers a much more complete review of the issue that occurred regarding the decay curve analysis, a review of the calculations completed to correct the issue, a review of the updated decay curve analysis process, and recommendations for moving forward.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗