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FAST-1.1: Integral Assessment

An integral assessment has been performed to quantify the predictive capabilities of FAST, a thermal-mechanical nuclear fuel performance code designed to analyze fuel behavior from beginning of life to burnup levels allowed by the U.S. Nuclear Regulatory Commission (NRC). FAST code calculations are shown to compare satisfactorily to a preselected set of experimental data with both steady-state and anticipated operating occurrence (AOO) conditions and design basis accident (DBA) transient operating conditions. This document describes the assessment of FAST-1.1, the latest version of FAST, released April 2022. Abstract

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

FAST-1.2: Integral Assessment

An integral assessment has been performed to quantify the predictive capabilities of FAST, a thermal-mechanical nuclear fuel performance code designed to analyze fuel behavior from beginning of life to burnup levels allowed by the U.S. Nuclear Regulatory Commission (NRC). FAST code calculations are shown to compare satisfactorily to a preselected set of experimental data with both steady-state and anticipated operating occurrence (AOO) conditions and design basis accident (DBA) transient operating conditions. This document describes the assessment of FAST-1.2, the latest version of FAST, released March 2023.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Genome-wide DNA methylation patterns harbour signatures of hatchling sex and past incubation temperature in a species with environmental sex determination

Conservation of thermally sensitive species depends on monitoring organismal and population-level responses to environmental change in real time. Epigenetic processes are increasingly recognized as key integrators of environmental conditions into developmentally plastic responses, and attendant epigenomic data sets hold potential for revealing cryptic phenotypes relevant to conservation efforts. Here, we demonstrate the utility of genome-wide DNA methylation (DNAm) patterns in the face of climate change for a group of especially vulnerable species, those with temperature-dependent sex determination (TSD). Due to their reliance on thermal cues during development to determine sexual fate, contemporary shifts in temperature are predicted to skew offspring sex ratios and ultimately destabilize sensitive populations. Using reduced-representation bisulphite sequencing, we profiled the DNA methylome in blood cells of hatchling American alligators (Alligator mississippiensis), a TSD species lacking reliable markers of sexual dimorphism in early life stages. We identified 120 sex-associated differentially methylated cytosines (DMCs; FDR < 0.1) in hatchlings incubated under a range of temperatures, as well as 707 unique temperature-associated DMCs. We further developed DNAm-based models capable of predicting hatchling sex with 100% accuracy (in 20 training samples and four test samples) and past incubation temperature with a mean absolute error of 1.2°C (in four test samples) based on the methylation status of 20 and 24 loci, respectively. Though largely independent of epigenomic patterning occurring in the embryonic gonad during TSD, DNAm patterns in blood cells may serve as nonlethal markers of hatchling sex and past incubation conditions in conservation applications. These findings also raise intriguing questions regarding tissue-specific epigenomic patterning in the context of developmental plasticity.

59 BASIC BIOLOGICAL SCIENCES↗

Sensitivity of a tonne-scale NEXT detector for neutrinoless double-beta decay searches

The Neutrino Experiment with a Xenon TPC (NEXT) searches for the neutrinoless double-beta (0νββ) decay of 136 Xe using high-pressure xenon gas TPCs with electroluminescent amplification. A scaled-up version of this technology with about 1 tonne of enriched xenon could reach in less than 5 years of operation a sensitivity to the half-life of 0νββ decay better than 10 27 years, improving the current limits by at least one order of magnitude. This prediction is based on a well-understood background model dominated by radiogenic sources. The detector concept presented here represents a first step on a compelling path towards sensitivity to the parameter space defined by the inverted ordering of neutrino masses, and beyond.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Sustainable recovery of critical metals from spent lithium-ion batteries through gluconic acid-based bioleaching: Techno-economic analysis, life cycle assessment and process optimization

Recycling spent lithium-ion batteries (LIB) could potentially bridge the ever increasing supply and demand gap for critical metals and simultaneously facilitate the management of hazardous battery waste. This study investigated the optimization of gluconic acid-based bioleaching technology through design of experiments (DOE), combined with techno-economic analysis (TEA), and life cycle assessment (LCA) with the aim of maximizing the net present value (NPV) and minimizing global warming impacts of the process. Biolixiviant containing predominantly gluconic acid produced by the genetically engineered (ΔpstS, P 112 :mgdh) Gluconobacter oxydans B58 through fermentation using non-recyclable paper as a growth substrate was used for the LIB leaching. At optimal bioleaching conditions of gluconic acid (160 mM), leaching time (2.5 h), reducing agent FeSO 4 to metal, i.e., cobalt (Co), nickel (Ni) and manganese (Mn), mole ratio (0.88), temperature (55 °C) and pulp density (2.5 %), the leaching efficiency was 87 % 72 %, 94 %, and 88 % for Co, Ni, Mn and lithium (Li), respectively. TEA analysis confirmed that bioleaching plant with an annual black mass processing capacity of 10,000 metric tons and plant life of 30 years would be economically viable with an NPV and profit margin of $136 million and 11 %, respectively. The predicted carbon footprint of gluconic acid-based bioleaching for recovering 1 kg of Co (13.2 kg of CO 2 eq.) is lower compared to that of most state-of-the-art leaching technologies. Moreover, gluconic acid-based bioleaching effectively recovered target metals when tested for different black mass chemistries.

Bioleaching↗

Volatile traits expand the microbial playbook

Microbial metabolic functions are increasingly conceptualized as fitness-regulating traits. However, volatile compounds (the volatilome), despite their key roles in metabolism and ecology, are often overlooked in trait-based frameworks. We propose that volatile traits not only reflect ecological strategies but also shape them by mediating responses to selection pressures. Their volatility affects diffusion, substrate access, and interactions across space, conferring selective advantages as resources or waste products. We outline approaches to incorporate volatile traits into predictive models to improve understanding of microbial selection and community dynamics. Furthermore, this integration enables a more holistic view of microbial life by accounting for the ecological and evolutionary consequences of volatile-mediated processes.

54 ENVIRONMENTAL SCIENCES↗

Search for 22 Na in novae supported by a novel method for measuring femtosecond nuclear lifetimes

Classical novae are thermonuclear explosions in stellar binary systems, and important sources of 26 Al and 22 Na. While γ rays from the decay of the former radioisotope have been observed throughout the Galaxy, 22 Na remains untraceable. Its half-life (2.6 yr) would allow the observation of its 1.275 MeV γ-ray line from a cosmic source. However, the prediction of such an observation requires good knowledge of its nucleosynthesis. The 22 Na(p, γ) 23 Mg reaction remains the only source of large uncertainty about the amount of 22 Na ejected. Its rate is dominated by a single resonance on the short-lived state at 7785.0(7) keV in 23 Mg. Here, we propose a combined analysis of particle-particle correlations and velocity-difference profiles to measure femtosecond nuclear lifetimes. The application of this method to the study of the 23 Mg states, places strong limits on the amount of 22 Na produced in novae and constrains its detectability with future space-borne observatories.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Metastability of diamond ramp-compressed to 2 terapascals

Carbon is the fourth-most prevalent element in the Universe and essential for all known life. In the elemental form it is found in multiple allotropes, including graphite, diamond and fullerenes, and it has long been predicted that even more structures can exist at pressures greater than those at Earth’s core. Several phases have been predicted to exist in the multi-terapascal regime, which is important for accurate modelling of the interiors of carbon-rich exoplanets. By compressing solid carbon to 2 terapascals (20 million atmospheres; more than five times the pressure at Earth’s core) using ramp-shaped laser pulses and simultaneously measuring nanosecond-duration time-resolved X-ray diffraction, we found that solid carbon retains the diamond structure far beyond its regime of predicted stability. The results confirm predictions that the strength of the tetrahedral molecular orbital bonds in diamond persists under enormous pressure, resulting in large energy barriers that hinder conversion to more-stable high-pressure allotropes, just as graphite formation from metastable diamond is kinetically hindered at atmospheric pressure. In conclusion, this work nearly doubles the highest pressure at which X-ray diffraction has been recorded on any material.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Cross sections of 147–149 Sm( 6 Li,x) reactions for the production of 149 Tb for targeted alpha therapy

Terbium-149g (t 1/2 = 4.12 h) is of particular interest for targeted alpha therapy cancer treatment due to its ability to decay via both alpha and positron emission, making it a potential theranostic nuclide. Due to many challenges facing its production, there are limited facilities worldwide that have demonstrated the ability to produce this nuclide in quantities sufficient for medical research. Since the Cyclotron Institute at Texas A&M University is a specialized accelerator facility capable of accelerating a wide variety of ions, we are investigating production pathway options. One of the major challenges facing its production is the known co-production of the excited isomeric state, 149m Tb (t 1/2 = 4.1 min). However, this state does not decay to the ground state of 149g Tb, negating any potential contribution to its yield. Due to its short-half life, the cross section for the population of this state has never been measured. After calculating several potential reaction yields using predictive models, the reactions of 147–149 Sm( 6 Li,xn) 149 Tb were identified as candidates. Lithium-6 beams of varied energies between 45-65 MeV were impinged on enriched 147 Sm, 148 Sm, and 149 Sm targets at the Cyclotron Institute at Texas A&M University, and the reaction products were measured immediately following irradiation using high-purity germanium detectors, enabling detection of both 149m Tb and 149g Tb. Cross sections for all nuclides produced in sufficient activity in these reactions were also measured and reported here. We conclude that the population of 149m Tb is much preferred over population of the ground state for these 6 Li-induced reactions, and it is necessary to explore other options for 149g Tb production.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Final Technical Report: Innovative Magnetron Power Sources for Superconducting RF (SRF) Accelerators

In this project, MUONS is designing and building custom magnetrons at Richardson Electronics (RELL) to test the predictions of the models and make improvements to the designs to match the needs of NP SRF accelerators and their life-cycle costs. To increase lifetime, the filament temperature is controlled by a feedback circuit that includes a model of back streaming of electrons. The gain of the magnetron is optimized by the design of an input port. A permanent magnet design with trim coil for amplitude adjustment reduces energy consumption. Moving the construction of the magnetron from prototype to manufacturing includes the utilization of RELL processes and designs. To the extent that outgassing of materials influences the lifetime of the magnetron, methods for minimizing outgassing was explored. Further experimentation of the potential of sub-critical voltage operation continues to be explored. The commercialization goal of the project will be naturally achieved as RELL already has world-wide marketing, sales, and support to exploit the assembly-line capabilities generated by this project to enable magnetron technologies for NP accelerators.

43 PARTICLE ACCELERATORS↗

The Local Topological Free Energy of the SARS-CoV-2 Spike Protein

The novel coronavirus SARS-CoV-2 infects human cells using a mechanism that involves binding and structural rearrangement of its Spike protein. Understanding protein rearrangement and identifying specific amino acids where mutations affect protein rearrangement has attracted much attention for drug development. In this manuscript, we use a mathematical method to characterize the local topology/geometry of the SARS-CoV-2 Spike protein backbone. Our results show that local conformational changes in the FP, HR1, and CH domains are associated with global conformational changes in the RBD domain. The SARS-CoV-2 variants analyzed in this manuscript (alpha, beta, gamma, delta Mink, G614, N501) show differences in the local conformations of the FP, HR1, and CH domains as well. Finally, most mutations of concern are either in or in the vicinity of high local topological free energy conformations, suggesting that high local topological free energy conformations could be targets for mutations with significant impact of protein function. Namely, the residues 484, 570, 614, 796, and 969, which are present in variants of concern and are targeted as important in protein function, are predicted as such from our model.

60 APPLIED LIFE SCIENCES↗

Deep learning-driven insights into super protein complexes for outer membrane protein biogenesis in bacteria

To reach their final destinations, outer membrane proteins (OMPs) of gram-negative bacteria undertake an eventful journey beginning in the cytosol. Multiple molecular machines, chaperones, proteases, and other enzymes facilitate the translocation and assembly of OMPs. These helpers usually associate, often transiently, forming large protein assemblies. They are not well understood due to experimental challenges in capturing and characterizing protein-protein interactions (PPIs), especially transient ones. Using AF2Complex, we introduce a high-throughput, deep learning pipeline to identify PPIs within the Escherichia coli cell envelope and apply it to several proteins from an OMP biogenesis pathway. Among the top confident hits obtained from screening ~1500 envelope proteins, we find not only expected interactions but also unexpected ones with profound implications. Subsequently, we predict atomic structures for these protein complexes. These structures, typically of high confidence, explain experimental observations and lead to mechanistic hypotheses for how a chaperone assists a nascent, precursor OMP emerging from a translocon, how another chaperone prevents it from aggregating and docks to a β-barrel assembly port, and how a protease performs quality control. This work presents a general strategy for investigating biological pathways by using structural insights gained from deep learning-based predictions.

60 APPLIED LIFE SCIENCES↗

Reductions in wind farm main bearing rating lives resulting from wake impingement

This paper studies the impacts of wake impingement on main bearing rating lives predicted during the wind turbine design stage. A computational tool chain was developed to explore and quantify these effects across a wind farm populated by 10 MW wind turbines. Wind field and turbine load modelling was undertaken using the Dynamiks Python package, including application of a dynamic wake meandering model. The ISO 281 basic bearing rating life formulation was subsequently applied in order to evaluate impacts from wake effects. Analyses included a two-turbine parametric analysis, followed by a full wind farm analysis undertaken for the TotalControl 32-turbine reference wind farm, including full wind rose simulations across all operational wind speeds. Site conditions were accounted for using a Weibull wind speed distribution and a range of parametric wind direction rose models. Results indicate that wind farm main bearing rating lives are negatively impacted by the effects of wake impingement, resulting in rating life reductions for the analysed wind farm of the order of 16 % on average and as much as 20 %–25 %, both for the locating main bearing. Despite these high sensitivities, it is important to note that these resultant rating lives (i.e. the predicted lives) still far exceed the standard wind turbine operational lifetimes of 20–30 years. Wake impacts were also found to be asymmetrically related to the side on which the rotor is impinged, suggesting that, for the main bearing, there may be a “better” side for wake impingement to occur. Rating life sensitivities to wind rose shape were also observed. While these findings must be interpreted with due consideration for the various methodological limitations present, they provide compelling evidence that wake effects at the wind farm level should necessarily be included when undertaking main bearing operational load modelling, rating life assessment, or other load-related analyses.

17 WIND ENERGY↗

A machine learning aided interpretable model for rupture strength prediction in Fe-based martensitic and austenitic alloys

Abstract The class of 9–12% Cr ferritic-martensitic alloys (FMA) and austenitic stainless steels have received considerable attention due to their numerous applications in high temperature power generation industries. To design high strength steels with prolonged service life requires a thorough understanding of the long-term properties, e.g., creep rupture strength, rupture life, etc., as a function of the chemical composition and processing parameters that govern the microstructural characteristics. In this article, the creep rupture strength of both 9–12% Cr FMA and austenitic stainless steel has been parameterized using curated experimental datasets with a gradient boosting machine. The trained model has been cross validated against unseen test data and achieved high predictive performance in terms of correlation coefficient ( $$R^{2} > 0.98 $$ R 2 > 0.98 for 9–12% Cr FMA and $$R^{2} > 0.95 $$ R 2 > 0.95 for austenitic stainless steel) thus bypassing the need for additional comprehensive tensile test campaigns or physical theoretical calculations. Furthermore, the feature importance has been computed using the Shapley value analysis to understand the complex interplay of different features.

36 MATERIALS SCIENCE↗

Metagenomic Alterations in Gut Microbiota Precede and Predict Onset of Colitis in the IL10 Gene-Deficient Murine Model

SUMMARY. Currently, predictive markers for the development andcourse of inflammatory bowel diseases (IBD) are not available. This study supports the notion that gut microbiome metagenomic profiles could be developed into a useful tool to assess risk and manage human IBD. BACKGROUND & AIMS: Inflammatory bowel diseases (IBD) are chronic inflammatory disorders where predictive bio-markers for the disease development and clinical course are sorely needed for development of prevention and early intervention strategies that can be implemented to improve clinical outcomes. Since gut microbiome alterations can reflect and/or contribute to impending host health changes, we examined whether gut microbiota metagenomic profiles would provide more robust measures for predicting disease outcomes in colitis-prone hosts. METHODS: Using the interleukin (IL) 10 gene-deficient (IL10KO) murine model where early life dysbiosis from antibiotic (cefoperozone [CPZ]) treated dams vertically transferred to pups increases risk for colitis later in life, we investigated temporal metagenomic profiles in the gut microbiota of post-weaning offspring and determined their relationship to even-tual clinical outcomes. RESULTS: Compared to controls, offspring acquiring maternalCPZ-induced dysbiosis exhibited a restructuring of intestinal microbial membership in both bacteriome and mycobiome that was associated with alterations in specific functional subsystems. Furthermore, among IL10 KO offspring fromCPZ-treated dams, several functional subsystems, particularly nitrogen metabolism, diverged between mice that developed spontaneous colitis (CPZ-colitis) versus those that did not (CPZ-no-colitis) at a time point prior to eventual clinical outcome. CONCLUSIONS: Our findings provide support that functional metagenomic profiling of gut microbes has potential and promise meriting further study for development of tools to assess risk and manage human IBD.

59 BASIC BIOLOGICAL SCIENCES↗

Structural and mechanistic basis for redox sensing by the cyanobacterial transcription regulator RexT

Abstract Organisms have a myriad of strategies for sensing, responding to, and combating reactive oxygen species, which are unavoidable consequences of aerobic life. In the heterocystous cyanobacterium Nostoc sp. PCC 7120, one such strategy is the use of an ArsR-SmtB transcriptional regulator RexT that senses H 2 O 2 and upregulates expression of thioredoxin to maintain cellular redox homeostasis. Different from many other members of the ArsR-SmtB family which bind metal ions, RexT has been proposed to use disulfide bond formation as a trigger to bind and release DNA. Here, we present high-resolution crystal structures of RexT in the reduced and H 2 O 2 -treated states. These structures reveal that RexT showcases the ArsR-SmtB winged-helix-turn-helix fold and forms a vicinal disulfide bond to orchestrate a response to H 2 O 2 . The importance of the disulfide-forming Cys residues was corroborated using site-directed mutagenesis, mass spectrometry, and H 2 O 2 -consumption assays. Furthermore, an entrance channel for H 2 O 2 was identified and key residues implicated in H 2 O 2 activation were pinpointed. Finally, bioinformatics analysis of the ArsR-SmtB family indicates that the vicinal disulfide “redox switch” is a unique feature of cyanobacteria in the Nostocales order, presenting an interesting case where an ArsR-SmtB protein scaffold has been evolved to showcase peroxidatic activity and facilitate redox-based regulation.

54 ENVIRONMENTAL SCIENCES↗

Heat of Mixing During Fast Charge/Discharge of a Li-Ion Cell: A Study on NMC523 Cathode

Predicting temperature rise accurately during fast charge/discharge of a Li-ion cell is essential to avoid thermal runaway and extend battery life. While modeling the temperature rise, it is necessary to model the heat generation correctly. Heat of mixing, one of the four main sources of heat generation in a Li-ion battery, has often been considered insignificant and therefore excluded from modeling. When included, it is modeled using the expression from a Taylor expansion approximation. In this work, we have shown the conditions when including the heat of mixing becomes important and quantified the error associated with using the Taylor expansion, especially under high charge/discharge conditions. Consequently, we carry out the calculation of the rate of enthalpy change and the heat generation rate from the most fundamental equation for the rate of the total enthalpy change without simplifying assumptions or approximations. The heat generation rate calculated doing so naturally includes irreversible, reversible and mixing heat. We then exclusively separate out the heat of mixing by subtracting the rate of enthalpy change by reaction from the rate of the total enthalpy change. Results show that the contribution of heat of mixing in the total heat generated increases with the charge/discharge rate and is as large as 23% for a 6 C discharge. This result suggests that while modeling heat generation for fast charge/discharge, it is necessary to include the heat of mixing and avoid calculating it using the Taylor expansion approximation.

25 ENERGY STORAGE↗

Integrating Survival Analysis with Bayesian Statistics to Forecast the Remaining Useful Life of a Centrifugal Pump Conditional to Multiple Fault Types

To improve the viability of nuclear power plants, there is a need to reduce their operational costs. Operational costs account for a significant portion of a plant’s yearly budget, due to their scheduled-based maintenance approach. In order to reduce these costs, proactive methods are required that estimate and forecast the state of a machine in real time to optimize maintenance schedules. In this research, we use Bayesian networks to develop a framework that can forecast the remaining useful life of a centrifugal pump. To do so, we integrate survival analysis with Bayesian statistics to forecast the health of the pump conditional to its current state. We complete our research by successfully using the Bayesian network on a case study. This solution provides an informed probabilistic viewpoint of the pumping system for the purpose of predictive maintenance.

42 ENGINEERING↗