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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Intelligent Experiments Through Real-time AI: Fast Data Processing and Autonomous Detector Control for sPHENIX and Future EIC Detectors (Final Report)

The overall vision of this project was to integrate real-time artificial intelligence (AI) directly into the data acquisition and detector-control systems of nuclear physics experiments, including both fast online event selection and an autonomous detector-control feedback loop. The work carried out under the award focused on the fast online event-selection half of that vision: the efficient recording of low-momentum heavy-flavor (HF) hadron decays in proton-proton collisions at the sPHENIX experiment at the Relativistic Heavy Ion Collider (RHIC)—an observable that requires fast tracking and topological trigger selection not previously demonstrated at RHIC, and that is essential for QCD studies at future facilities such as the Electron-Ion Collider (EIC). The autonomous detector-control (GPU-based feedback) component named in the project title remained a design concept and was not implemented under this award. The Massachusetts Institute of Technology (MIT) group led the offline simulation and data processing needed to train the machine-learning (ML) models, the translation of trained models to Field-Programmable Gate Array (FPGA) firmware using the hls4ml framework, and the physics validation of heavy-flavor reconstruction. Over the award period, the team developed and hardware-tested the principal components of an AI-based heavy-flavor trigger on simulated and recorded sPHENIX tracker data: a software Bipartite Graph Attention Network (BiGAT) trigger model reaching > 95% signal efficiency at 99% background rejection; an FPGA-native hit clusterizer matching the offline clustering; smaller networks synthesized to FPGA within the required sub-10 µs latency; and an assembled decoder–clusterizer–inference firmware chain exercised on the FELIX readout board. A complete, fully integrated hardware demonstrator was not finished within the award period. This report documents the project goals, the MIT group’s contributions, the technical accomplishments, and the outlook toward applications at the future EIC ePIC detector.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Morphological and Genomic Features of the New Klosneuvirinae Isolate Fadolivirus IHUMI-VV54

Since the discovery of Mimivirus, viruses with large genomes encoding components of the translation machinery and other cellular processes have been described as belonging to the nucleocytoplasmic large DNA viruses. Recently, genome-resolved metagenomics led to the discovery of more than 40 viruses that have been grouped together in a proposed viral subfamily named Klosneuvirinae. Members of this group had genomes of up to 2.4Mb in size and featured an expanded array of translation system genes. Yet, despite the large diversity of the Klosneuvirinae in metagenomic data, there are currently only two isolates available. Here, we report the isolation of a novel giant virus known as Fadolivirus from an Algerian sewage site and provide morphological data throughout its replication cycle in amoeba and a detailed genomic characterization. The Fadolivirus genome, which is more than 1.5Mb in size, encodes 1,452 predicted proteins and phylogenetic analyses place this viral isolate as a near relative of the metagenome assembled Klosneuvirus and Indivirus. The genome encodes for 66 tRNAs, 23 aminoacyl-tRNA synthetases and a wide range of transcription factors, surpassing Klosneuvirus and other giant viruses. The Fadolivirus genome also encodes putative vacuolar-type proton pumps with the domains D and A, potentially constituting a virus-derived system for energy generation. The successful isolation of Fadolivirus will enable future hypothesis-driven experimental studies providing deeper insights into the biology of the Klosneuvirinae.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Validation of the SCALE/Polaris-PARCS Code Procedure with the ENDF/B-VII.1 AMPX 56-Group Library: Pressurized Water Reactor

This study was conducted to validate the SCALE/Polaris v6.3.0–PARCS v3.4.2 code procedure with the Evaluated Nuclear Data File (ENDF)/B-VII.1 AMPX 56-group library for pressurized water reactor (PWR) analysis, by comparing simulated results with measured data for critical experiments and operating PWRs. Uncertainties of the SCALE/Polaris–PARCS code procedure for PWR analysis were evaluated in the validation for the PWR key nuclear parameters such as critical boron concentrations, reactivity, control bank work, temperature coefficients, and pin and assembly power peaking factors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Neutron diffusion calculation in heterogeneous geometry based on local/global iteration using proper orthogonal decomposition

This study newly proposes a heterogeneous core calculation method based on local/global iteration using proper orthogonal decomposition (POD). By using the singular value decomposition (SVD) and the low-rank approximation, appropriate POD bases for expanding the neutron flux can be obtained from snapshot data of the neutron flux obtained by fine mesh calculations. By projection using the POD bases, the dimension of the target equation (e.g., discretized neutron diffusion equation) can be dramatically reduced. In the proposed method, POD is effectively applied to each single assembly calculation (local calculation). Furthermore, using the local/global iteration, the effective neutron multiplication factor and the neutron flux distribution in the whole core geometry can be obtained by combining the numerical results of the local calculation for each fuel assembly and the global calculation for the whole core. As a feasibility study, the proposed method is applied to a one-dimensional heterogeneous core analysis, and the accuracy is investigated by changing the total number of POD bases. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Specification of EBR-II Fabricated Fuel Diameter Data

All IFR EBR-II fuel pins were fabricated at one of the related fuel fabrication facilities at Argonne National Laboratory-West, at the EBR-II site [1]. U-Pu-Zr experimental pins were fabricated at the Experimental Fuels Laboratory (EFL), which was established in April of 1984 after the positive acceptance of the IFR concept, while the U-Zr experimental pins were fabricated at the Fuel Manufacturing Facility (FMF), along with the driver fuel pins [2]. The injection-casting fabrication process is described in detail in ref [1]. All the fuel pins that were loaded into EBR-II were examined after fabrication to ensure that they met the design dimensional requirements and tolerances prior to assembly. Fuel slug diameter was measured with either a laser profilometer (at FMF) or a hand micrometer (at EFL), at a minimum of 1-inch intervals over the length of the fuel slug, as shown in Figure 1 [2]. In all cases the average fuel diameter is reported, in some cases with additional summary statistics (e.g., minimum, maximum), and in rare cases the complete record of axially-varying fuel diameters is available. It should be noted that in cases where axial varying data is available, in general the orientation of the slug was not recorded or carried over to loading of the pin, so a diameter measurement at the bottom of the fabricated slug does not necessarily correspond to the bottom of the loaded slug, as it may have been loaded in either orientation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

The large-area hybrid-optics CLAS12 RICH: First years of data-taking

The CLAS12 deep-inelastic scattering experiment at the upgraded 12 GeV continuous electron beam accelerator facility of Jefferson Lab conjugates luminosity and wide acceptance to study the 3D nucleon structure in the yet poorly explored valence region, and to perform precision measurements in hadron spectroscopy. A large area ring-imaging Cherenkov detector has been designed to achieve the required hadron identification in the momentum range from 3 GeV/c to 8 GeV/c, with the kaon rate about one order of magnitude lower than the rate of pions and protons. The adopted solution comprises aerogel radiator and composite mirrors in a novel hybrid optics design, where either direct or reflected light could be imaged in a high-packed and high-segmented photon detector. The first RICH module was assembled during the second half of 2017 and installed at the beginning of January 2018, in time for the start of the experiment. The second RICH module, planned with the goal to be ready for the beginning of the operation with polarized targets, has been timely built despite the complications caused by the pandemic crisis and successfully installed in June 2022. Finally, the detector performance is here discussed with emphasis on the operation and stability during the data-taking, calibration and alignment procedures, reconstruction and pattern recognition algorithms, and particle identification.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Smart connected worker edge platform for smart manufacturing: Part 2—Implementation and on‐site deployment case study

Abstract In this paper, we describe specific deployments of the Smart Connected Worker (SCW) Edge Platform for Smart Manufacturing through implementation of four instructive real‐world use cases that illustrate the role of people in a Smart Manufacturing paradigm through which affordable, scalable, accessible, and portable (ASAP) information technology (IT) acquires and contextualizes data into information for transmission to operation technologies (OT). For case one, the platform captures the relationships between energy consumption and human workflows for improved energy productivity while workers interact with machines during semiconductor manufacturing. The platform utilizes human cognition to identify anomalous machine behavior for root cause analysis of system faults via neural network (NN) that recognize alarm postures of workers with cameras. For case two, a smart assembly line is demonstrated for state monitoring and fault detection. Machine learning (ML) models are used to recognize system states and identify fault scenarios with human intervention. For case three, the platform monitors human–machine interactions to classify manufacturing machine states for proper operations and energy productivity. Internal energy states of individual or collections of manufacturing equipment are determined via NN based algorithms that disaggregate signals associated with smart metering typically deployed at manufacturing facilities. These methods predict the real time energy profile of each machine from the total energy profile of a manufacturing site. For case four, a software defined sensor system built with scientific workflow engines is demonstrated for contextualizing data from laser surface refraction for characterization, and diagnostics in the processing of additively manufactured titanium alloy.

Donovan, Richard P.↗
DOE OSTI2026

Imaging and analysis data of short-term co-culture in soilchip

Fluorescently tagged bacterial soil isolates were cultured with N-acetylglucosamine, chitopentose, or chitin in porous SoilChip devices designed to mimic the structural habitats found in soil. Imaging analysis was used to examine how microbial traits, nutrient substrate solubility and degree of polymerization, and time affected microbial growth and species’ spatial assembly.

Feng, Song [Pacific Northwest National Laboratory ↗
DOE OSTI2021

Rates and delay times of type Ia supernovae in the Dark Energy Survey

We use a sample of 809 photometrically classified Type Ia supernovae (SNe Ia) discovered by the Dark Energy Survey (DES) along with 40 415 field galaxies to calculate the rate of SNe Ia per galaxy in the redshift range 0.2 < z < 0.6. We recover the known correlation between SN Ia rate and galaxy stellar mass across a broad range of scales 8.5 ≤ log (M*/M ⊙ ) ≤ 11.25. We find that the SN Ia rate increases with stellar mass as a power law with index 0.63 ± 0.02, which is consistent with the previous work. We use an empirical model of stellar mass assembly to estimate the average star formation histories (SFHs) of galaxies across the stellar mass range of our measurement. Combining the modelled SFHs with the SN Ia rates to estimate constraints on the SN Ia delay time distribution (DTD), we find that the data are fit well by a power-law DTD with slope index β = –1.13 ± 0.05 and normalization A = 2.11 ± 0.05 × 10 –13 SNe M ⊙ –1 yr –1 , which corresponds to an overall SN Ia production efficiency N Ia /M * = 0.9 $^{+4.0}_{–0.7}$ × 10 –3 SNe M$^{–1}_{⊙}$. Upon splitting the SN sample by properties of the light curves, we find a strong dependence on DTD slope with the SN decline rate, with slower-declining SNe exhibiting a steeper DTD slope. We interpret this as a result of a relationship between intrinsic luminosity and progenitor age, and explore the implications of the result in the context of SN Ia progenitors.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Exploiting non-linear scales in galaxy–galaxy lensing and galaxy clustering: A forecast for the dark energy survey

ABSTRACT The combination of galaxy–galaxy lensing (GGL) and galaxy clustering is a powerful probe of low-redshift matter clustering, especially if it is extended to the non-linear regime. To this end, we use an N-body and halo occupation distribution (HOD) emulator method to model the redMaGiC sample of colour-selected passive galaxies in the Dark Energy Survey (DES), adding parameters that describe central galaxy incompleteness, galaxy assembly bias, and a scale-independent multiplicative lensing bias Alens. We use this emulator to forecast cosmological constraints attainable from the GGL surface density profile ΔΣ(rp) and the projected galaxy correlation function wp, gg(rp) in the final (Year 6) DES data set over scales $r_p=0.3\!-\!30.0\, h^{-1} \, \mathrm{Mpc}$. For a $3{{\ \rm per\ cent}}$ prior on Alens we forecast precisions of $1.9{{\ \rm per\ cent}}$, $2.0{{\ \rm per\ cent}}$, and $1.9{{\ \rm per\ cent}}$ on Ωm, σ8, and $S_8 \equiv \sigma _8\Omega _m^{0.5}$, marginalized over all halo occupation distribution (HOD) parameters as well as Alens. Adding scales $r_p=0.3\!-\!3.0\, h^{-1} \, \mathrm{Mpc}$ improves the S8 precision by a factor of ∼1.6 relative to a large scale ($3.0\!-\!30.0\, h^{-1} \, \mathrm{Mpc}$) analysis, equivalent to increasing the survey area by a factor of ∼2.6. Sharpening the Alens prior to $1{{\ \rm per\ cent}}$ further improves the S8 precision to $1.1{{\ \rm per\ cent}}$, and it amplifies the gain from including non-linear scales. Our emulator achieves per cent-level accuracy similar to the projected DES statistical uncertainties, demonstrating the feasibility of a fully non-linear analysis. Obtaining precise parameter constraints from multiple galaxy types and from measurements that span linear and non-linear clustering offers many opportunities for internal cross-checks, which can diagnose systematics and demonstrate the robustness of cosmological results.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

DarkNESS Project Testing

This internship involved the design and assembly of a mechanical system for testing skipper-Charge Couple Devices (CCDs) for the DarkNESS project. Skipper-CCDs are highly-sensitive sensors with ultra-low readout noise that are deployed for direct detection of dark matter. DarkNESS is a CubeSat that aims to use skipper CCDs to search for dark matter decaying into X-rays. Currently, in the testing phase, the design process involved creating 3D models of mechanical adapters to operate a prototype space Multi Chip Module (sMCM) package in existing testing chambers in the CCD lab at Fermilab's IERC. The drawings were sent out to be machined, and while waiting to receive the finished adapters, we assembled a vacuum chamber for skipper-CCD testing and performed initial testing of a single CCD controlled by the space Low Threshold Acquisition (sLTA) board that will be employed on the CubeSat. The results showed that the testing conditions are optimal for data to start being taken and analyzed.

Akouedjinoude, Kodjo↗
DOE OSTI2024

Automated Assembly Progress Monitoring in Modular Construction Factories Using Computer Vision-Based Instance Segmentation

Modular construction has recently gained interest as a transformative construction method. In this method, a large portion of the construction is performed inside factories, where processes are fast-paced and interdependent; therefore, any deviation from the schedule can delay the production. Such deviations are frequent in modular factories due to the labor-intensive nature of the tasks. This propagation of delays can be mitigated by continuously monitoring each process; however, current manual monitoring methods are laborious, and recently proposed contact sensor-based methods are intrusive to the work. In addition, recent computer vision-based monitoring methods inside factories are limited to detection algorithms that fail to provide the pixel-level accuracy required for assembly progress monitoring in highly occluded factory scenes, and they require a large number of manual annotations. Therefore, this paper proposes a method to monitor the installation of subassemblies in modular construction factories using mask R-CNN instance segmentation and improves the data efficiency of the model using a copy-paste augmentation method. This method was validated on the CCTV videos captured from a modular construction factory in the US, resulting in a 9% mAP improvement in segmentation.

computer vision↗
DOE OSTI2022

HiFiAdapterFilt, a memory efficient read processing pipeline, prevents occurrence of adapter sequence in PacBio HiFi reads and their negative impacts on genome assembly

Abstract Background Pacific Biosciences HiFi read technology is currently the industry standard for high accuracy long-read sequencing that has been widely adopted by large sequencing and assembly initiatives for generation of de novo assemblies in non-model organisms. Though adapter contamination filtering is routine in traditional short-read analysis pipelines, it has not been widely adopted for HiFi workflows. Results Analysis of 55 publicly available HiFi datasets revealed that a read-sanitation step to remove sequence artifacts derived from PacBio library preparation from read pools is necessary as adapter sequences can be erroneously integrated into assemblies. Conclusions Here we describe the nature of adapter contaminated reads, their consequences in assembly, and present HiFiAdapterFilt, a simple and memory efficient solution for removing adapter contaminated reads prior to assembly.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Legacy Effects of Cropping System and Precipitation Influence the Core Camelina sativa Microbiome

Camelina ( Camelina sativa L.) is a potential biofuel crop and beneficial rotation crop in dryland cropping systems. Little is known about camelina microbiota or the legacy effect of soil origin/cropping system zones on camelina-associated microbiome assembly. To explore camelina-microbe associations, we grew camelina in the greenhouse using soil transplanted from 33 locations in the dryland wheat production area of eastern Washington. Bacterial, archaeal, and fungal communities from bulk soil, rhizosphere, and endosphere were characterized with 16S rRNA and internal transcribed spacer amplicon sequencing and were analyzed alongside site-specific climatic and edaphic data. We found that soil from the highest precipitation zone had higher alpha diversity than soil from the driest zone, but this effect was not seen in the greenhouse rhizosphere or endosphere. Plant compartment, cropping system zone, and soil origin all significantly influenced microbial composition, with soil pH and organic matter, as well as precipitation at origin, as major predictors. Analysis of abundance–occupancy distributions showed that the Actinobacteriota Aeromicrobium and Marmoricola and the fungus Pseudogymnoascus in the rhizosphere were plant-selected, while the endosphere was characterized by a number of Actinobacteriota, Rhizobium, and Clostridium. Sphingomonas amplicon sequence variants were also consistently enriched in the rhizosphere, suggesting that they are present in soils collected throughout eastern Washington and may represent good candidate biostimulants. Several lignin decomposing fungi had site-specific rhizospheric distributions, suggesting that they may be dispersal-limited or result from the legacy effect of long-term wheat cropping. Overall, this study contributes to our understanding of microbiome assembly in and on camelina roots while also highlighting the potential impact of cropping history on soil- and plant-associated microbiomes. [Formula: see text] The author(s) have dedicated the work to the public domain under the Creative Commons CC0 “No Rights Reserved” license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2025.

Barnes, Elle M↗
DOE OSTI2020

Mutations in the Pectin Methyltransferase QUASIMODO2 Influence Cellulose Biosynthesis and Wall Integrity in Arabidopsis

Abstract Pectins are abundant in the cell walls of dicotyledonous plants, but how they interact with other wall polymers and influence wall integrity and cell growth has remained mysterious. Here, we verified that QUASIMODO2 (QUA2) is a pectin methyltransferase and determined that QUA2 is required for normal pectin biosynthesis. To gain further insight into how pectin affects wall assembly and integrity maintenance, we investigated cellulose biosynthesis, cellulose organization, cortical microtubules, and wall integrity signaling in two mutant alleles of Arabidopsis (Arabidopsis thaliana) QUA2, qua2 and tsd2. In both mutants, crystalline cellulose content is reduced, cellulose synthase particles move more slowly, and cellulose organization is aberrant. NMR analysis shows higher mobility of cellulose and matrix polysaccharides in the mutants. Microtubules in mutant hypocotyls have aberrant organization and depolymerize more readily upon treatment with oryzalin or external force. The expression of genes related to wall integrity, wall biosynthesis, and microtubule stability is dysregulated in both mutants. These data provide insights into how homogalacturonan is methylesterified upon its synthesis, the mechanisms by which pectin functionally interacts with cellulose, and how these interactions are translated into intracellular regulation to maintain the structural integrity of the cell wall during plant growth and development.

Biochemistry & Molecular Biology↗
DOE OSTI2026

Multi‐season analysis reveals hundreds of drought‐responsive genes in sorghum

Persistent drought affects global crop production and is becoming more severe in many parts of the world in recent decades. Deciphering how plants respond to drought will facilitate the development of flexible mitigation strategies. Sorghum bicolor L. Moench (sorghum), a major cereal crop and an emerging bioenergy crop, exhibits remarkable resilience to drought. To better understand the molecular traits that underlie sorghum's remarkable drought tolerance, we undertook a large-scale sorghum gene expression profiling effort, totaling nearly 1500 transcriptome profiles, across a 3-year field study with replicated plots in California's Central Valley. This study included time-resolved gene expression data from roots and leaves of two sorghum genotypes, BTx642 and RTx430, with different pre-flowering and post-flowering drought-tolerance adaptations under control and drought conditions. Quantification of genotype-specific drought tolerance effects was enabled by de novo sequencing, assembly, and annotation of both BTx642 and RTx430 genomes. These reference-quality genomes were used to construct a pangene set for characterizing conserved and genotype-specific expression. By integrating time-resolved transcriptomic responses to drought in the field across three consecutive years, we identified a set of 726 drought-responsive genes that responded similarly in all 3 years of our field study. Functional enrichment analysis identified abiotic stress, secondary cell wall-related processes and metabolism as particularly affected under both types of drought stress. We also found that some glyoxylate cycle pathway genes, including malate synthase and isocitrate lyase, are differentially regulated particularly during post-flowering drought stress, implicating this pathway as potentially important for drought responsiveness. This expansive dataset represents a unique resource for sorghum and drought research communities and provides a methodological framework for the integration of multi-faceted time-resolved transcriptomic datasets.

Cole, Benjamin [USDOE Joint Genome Institute (JGI)↗
DOE OSTI2020

Microbial community dynamics and coexistence in a sulfide-driven phototrophic bloom

Background: Lagoons are common along coastlines worldwide and are important for biogeochemical element cycling, coastal biodiversity, coastal erosion protection and blue carbon sequestration. These ecosystems are frequently disturbed by weather, tides, and human activities. Here, we investigated a shallow lagoon in New England. The brackish ecosystem releases hydrogen sulfide particularly upon physical disturbance, causing blooms of anoxygenic sulfur-oxidizing phototrophs. To study the habitat, microbial community structure, assembly and function we carried out in situ experiments investigating the bloom dynamics over time. Results: Phototrophic microbial mats and permanently or seasonally stratified water columns commonly contain multiple phototrophic lineages that coexist based on their light, oxygen and nutrient preferences. We describe similar coexistence patterns and ecological niches in estuarine planktonic blooms of phototrophs. The water column showed steep gradients of oxygen, pH, sulfate, sulfide, and salinity. The upper part of the bloom was dominated by aerobic phototrophic Cyanobacteria, the middle and lower parts by anoxygenic purple sulfur bacteria (Chromatiales) and green sulfur bacteria (Chlorobiales), respectively. We show stable coexistence of phototrophic lineages from five bacterial phyla and present metagenome-assembled genomes (MAGs) of two uncultured Chlorobaculum and Prosthecochloris species. In addition to genes involved in sulfur oxidation and photopigment biosynthesis the MAGs contained complete operons encoding for terminal oxidases. The metagenomes also contained numerous contigs affiliating with Microviridae viruses, potentially affecting Chlorobi. Our data suggest a short sulfur cycle within the bloom in which elemental sulfur produced by sulfide-oxidizing phototrophs is most likely reduced back to sulfide by Desulfuromonas sp. Conclusions: The release of sulfide creates a habitat selecting for anoxygenic sulfur-oxidizing phototrophs, which in turn create a niche for sulfur reducers. Strong syntrophism between these guilds apparently drives a short sulfur cycle that may explain the rapid development of the bloom. The fast growth and high biomass yield of Chlorobi-affiliated organisms implies that the studied lineages of green sulfur bacteria can thrive in hypoxic habitats. This oxygen tolerance is corroborated by oxidases found in MAGs of uncultured Chlorobi. The findings improve our understanding of the ecology and ecophysiology of anoxygenic phototrophs and their impact on the coupled biogeochemical cycles of sulfur and carbon.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Evaluation of Hydrogen Generation in High Burnup Demonstration Dry Storage Cask

This report provides a best-estimate evaluation of residual water content (post-dry out) in the High Burnup (HBU) LWR Spent Fuel Demonstration project TN-32 cask, and evaluates the radiolysis of the residual free water, and the physisorbed and chemisorbed waters on the surfaces of the fuel and cask internal contents. The evaluation of radiolytic breakdown of those waters with gamma radiation causing the generation of hydrogen gas (H 2 ) is made using available literature data and models. This evaluation is part of the overall materials performance evaluation of the SNF-in-canister system, and is part of the technical bases for their continued safe dry storage. The TN-32 cask contents included 32 HBU LWR spent fuel assemblies each with 264 fuel rods clad in zirconium alloys, aluminum neutron absorber components, and aluminum and stainless steel structural components. The residual free and surface (physisorbed/chemisorbed) waters are ascribed to water vapor in the free volume and to components’ surfaces, respectively. The total potential radiolytic hydrogen inventory from the water vapor and from waters ascribed to surfaces has been calculated assuming all the water produced molecular H 2 . The residual water that is chemically incorporated into the bulk of a hydrated oxide, i.e., chemisorbed water, and its total potential hydrogen inventory has been calculated. These calculations are at the physical limit of material available and are used for a bounding assessment purpose only.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗