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At least 631 records · Page 35

Quality Assurance Project Plan for the Salish Sea Model – Continuing Development of New Capabilities and Applications: European Green Crab (EGC) Larval Transport, Coupling to VELMA and Atlantis, Performance Improvements and Diagnostic Applications

This quality assurance project plan (QAPP) is for proposed FY24-FY27 efforts to (a) develop/expand a predictive European Green Crab (EGC) larval dispersal model for the Salish Sea, (b) add linkage between VELMA (Visualizing Ecosystem Land Management Assessments) watershed model and Atlantis model (ecosystem dynamics and food web) through SSM, and (c) continue SSM capability development through the addition of metals, harmful algal blooms (HABs), and FVCOM-LTRANS (Lagrangian Larval Transport) modules.

54 ENVIRONMENTAL SCIENCES↗

Catalytic Activation of Pyran Ethers in Self-Solvating Saccharides with Alkaline Earth Metals (Final Report)

Catalytic activation of cellulose ethers occurs via hydroxyl-stabilized cleavage of inter-monomer glycosidic bonds. Cooperativity between two hydroxyl groups lowers the ether cleavage transition state necessary to break apart long carbohydrate chains to initiate small molecule formation as fuel precursors. Metals existing with lignocellulosic materials including alkaline earth metals (Ca 2+ , Mg 2+ ) or alkali (Na + , K + ) also can catalyze ether scission cooperatively. By bonding with carbohydrate hydroxyl groups, a metal cation disrupt the hydrogen bonding network and free carbohydrate functional groups to react; a second metal cation stabilizes the carbohydrate ether transition state and enhances the rate of polymer scission. In this work, we expanded our initial understanding of metal-catalyzed glycoside ether scission. Within polysaccharides such as cellulose, two ether groups exist: one between monomers (glycosidic linkages) and one within a pyran ring. The hydroxyl-group hydrogen bonding network and bound metal ions form low energy binding states that interact with both ether oxygens simultaneously. Based on this interaction, our primary hypothesis was that the competition between stabilizing the two ether scission transition states determines the extent of the major pathways. Metals that disrupt the hydrogen bonding network of the C6 of sugars and stabilize the glycosidic ether promote transglycosylation to levoglucosan; in contrast, metals that stabilize the pyran ether oxygen promote sugar ring fragmentation to furans such as furfural. Varying characteristics of metal cation catalysts and configurations of bound polysaccharide chains dictate the relative rates of ether scission.

09 BIOMASS FUELS↗

Stepping into the Midwest Bioeconomy: Stakeholder Engagement and Geospatial Tools to Assist in Perennial Bioenergy Crop Decision Making and Entrepreneurship

This project, “Ecosystem Services and Farm Entrepreneurship Technical Assistance,” was a three-year project originally planned for FY22–FY24. Due to a late start and a few extensions, it is being completed in early FY25. This project explored opportunities to support the deployment of a bioeconomy with a circular, more sustainable supply chain. Using a tool developed by Argonne to identify agricultural areas suitable for use in the bioeconomy, we sought to create opportunities in the bioeconomy as biomass producers, bioenergy users, and environmental entrepreneurs. We proposed to focus at the beginning on enhancing the tool’s capabilities, while engaging with key stakeholders to improve and expand the tool’s functionality for all potential stakeholders in the bioeconomy. We believe that expanding our tools and technologies, coupled with conversations in agricultural spaces, will be needed as we continue to explore how best to offer farmers whole-of supply-chain opportunities to participate in the bioeconomy. Through this project we have continued to gain a better understanding of the ways in which farmers, landowners, bioenergy users, and environmental entrepreneurs may approach the bioeconomy. In addition, as we improve our analytic toolkit, we can continue to refine our communication and the ways in which we can valuate the bioeconomy. Refining these tools allows us to dive deeper into conversations around plausible policies and drivers for future bioeconomy investment and engagement by stakeholders. By working with farmers and agricultural landowners to enable a sustainable bioeconomy business model, enhance their energy options, and recover resources from their waste streams, this project directly responds to the Bioenergy Technology Office’s (BETO) priorities of building a resilient energy economy. It addresses BETO’s focus on fostering the development and adoption of energy technologies that enable the conversion of waste to energy, efficient land use, and robust job creation. By establishing a technical assistance program that develops capabilities and practices in agricultural areas to implement a bioeconomy future, this program will develop an important linkage between technology being developed at U.S. Department of Energy national laboratories and the agricultural communities of the Midwest. This project focuses on farmers with lower productivity farmland. Because less productive lands create a more difficult revenue stream for conventional crops, these farmers may therefore be more open to alternative agricultural land management regimes. Consequently, the technical assistance program and the methodologies for targeting perennial bioenergy crop application on marginal land provide a distinct opportunity to engage with and invest in the bioeconomy in these economically stressed areas. Stakeholders in this project include farmers and landowners, local conservation organizations (NRCS, SWCS, etc.), universities, non-profit environmental and agricultural entities, farm consultants, environmental regulators, and industry, including the industries working on conversion technologies, anaerobic digestion, pyrolysis, and biochar generation, and the companies interested in trading or purchasing/supporting the valuation of ecosystem services (ES).

09 BIOMASS FUELS↗

Non-Destructive, Three-Dimensional Imaging of Processes in the Rhizosphere Utilizing High Energy Photons

Soil structure, which can be described as the aggregation and distribution of pore spaces, regulates carbon, nutrient, and water cycling across the Earth system. Yet the inability to make quantitative, dynamic, in situ measurements of soil structure and rhizosphere carbon flow has prevented meaningful incorporation of soil structural processes into Earth System Models (ESMs). The key limitations are: (i) Lack of scale integration between micron-scale soil structure and ecosystem-scale models, (ii) Poor functional linkage between soil structural properties and biogeochemical processes, and (iii) Absence of dynamic 3D measurements of rhizosphere structural changes and carbon transformations. To address these challenges, we developed a new integrated positron emission tomography (PET) - microcomputed tomography (CT) imaging platform that enables the first 4D (spatial 3D and time), non-invasive, quantitative imaging of carbon allocation and rhizosphere structural dynamics in living plants and intact soils. The system combines: • Rhizo-PET (R-PET): a high-resolution positron emission tomography scanner optimized for 11 CO 2 tracing in plant roots. • a-Se micro-CT: a high-contrast, high-spatial resolution CT system based on amorphous selenium (a-Se) direct conversion technology, enabling micron-scale visualization of soil structure and root–soil interfaces. Together, these advances allow us to quantify how carbon exudates move, transform, and stabilize within the rhizosphere, directly informing missing processes in BER-relevant carbon cycle models.

42 ENGINEERING↗

From tides to seasons: How cyclic tidal drivers and plant physiology interact to affect carbon cycling at the terrestrial-estuarine boundary (Final technical report)

Coastal ecosystems are among the most biologically and biogeochemically active and diverse systems on Earth. Because they act as important linkages between terrestrial ecosystems and the open ocean, their incorporation in Earth system models (ESMs) is critical to predict coastal and global responses to environmental changes. However, they vary greatly in the magnitude of tides and the volume and timing of freshwater input from land, making it challenging to model the major biogeochemical reactions that control productivity and greenhouse gas emissions across coastal terrestrial aquatic interfaces (TAIs). Our overall objective was to improve mechanistic process understanding and modeling of tidal wetland hydro-biogeochemistry in coastal TAIs. We established a new flux tower site (Ameriflux US-PLo) in the oligohaline part of the Parker River to continuously monitor ecosystem-scale carbon fluxes under temporally varying salinity conditions. The site is co-located with long-term monitoring plots of the Plum Island Ecosystems LTER project. We installed wells and redox sensors in the marsh interior and creek bank, established biomass monitoring plots and deployed novel optode sensors in both locations. We used this data to parameterize plant-mediated transport in PFLOTRAN and tested the impact of soil heterogeneity on porewater constituents and gas fluxes. We collected observations of root oxygen release with a novel planar optode system in the field. Flux data collected during the measurement period encompasses a large variation in salinity ranging from drought to record precipitation years. We developed a method to extract functional relationships from the flux data using artificial neural networks, identifying salinity thresholds for CH 4 fluxes. Finally, we are using the coupled ELM-PFLOTRAN model to test the impact of antecedent hydrological conditions on the salinity-CH 4 flux relationship. This grant contributed to the professional development of one postdoc, three research assistants and one graduate student. The sensor data has been shared with external collaborators.

54 ENVIRONMENTAL SCIENCES↗

Solid Amine CO2 Adsorbent Degradation: Insights from Experiments and Atomistic Simulations

Direct air capture (DAC) has received significant attention this decade as a viable solution to limit global warming, although large-scale deployment is currently not economically feasible. To reach the ambitious cost target set by the U.S. of $100/ton CO2 captured and stored, significant improvements must be made to sorbent lifetime and capacity. Aminosilanes grafted onto silica supports are promising candidates for deployment in DAC systems due to their relatively high oxidative stability and low regeneration temperature. Despite myriad advancements in the field, there still exists a fundamental knowledge gap relating sorbent structure to performance. In this work, we grafted various aminosilanes onto the highly porous silica SBA-15 and characterized both oxidative stability and CO2 capacity. Material properties systematically investigated included amine moiety (primary vs. secondary), silane group structure, number of linkages to the silica support, and co-addition of impregnated amines (e.g., PEI), among others. A fixed bed system was used to execute accelerated degradation studies in the presence of humidity and varying temperatures to simulate realistic operating conditions. Atomistic simulations were combined with the experimental results to gain mechanistic insight, ultimately informing the design of next-generation materials

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ocean physical‐biogeochemical interactions in the CMIP6 and E3SM Earth System Models

The primary objectives of this project are to quantify the spatio‐temporal linkages between physical climate and ocean biogeochemical variables in the U.S. Department of Energy (DOE) Energy Exascale Earth System Model (E3SM), in CMIP6 Earth System Models (ESMs), and in historical observations, to evaluate the E3SM’s ability to reproduce the observations, and to develop a solid diagnostic package to do so. It will revolve around four hypotheses and will focus on key physical and biogeochemical processes that regulate the upper ocean carbon and oxygen cycling: water mass distribution, ventilation, and biological production.

54 ENVIRONMENTAL SCIENCES↗

Southeast Regional CO 2 Utilization and Storage Acceleration Partnership (SECARB-USA): Data Quality Methodology (4.2.1)

SECARB-USA Deliverable 4.2.1 utilizes the outputs from the Needs Assessment (Subtask 2.1) to develop a data quality methodology. Many types of data are needed to evaluate a site for technical and financial viability. Several inventories of data types have been produced (for example NETL, 2010). The objective here is to organize the data types so that the needs met are specified. From this cross index (Table 1 in the Appendix), it will be possible in future tasks to (1) determine, on a site-specific basis, how much of each data type is required at each stage of a project to meet the need, and conversely (2) to further specify and define the data collection methods applied such that the data are tailored to fit that need. Derivative tables can then be developed to semi-quantitively evaluate the extent to which need is critical for early go/no decision points, or if it is more important than average, requiring faster or larger capitalization and spend to meet the need. In an additional step, the current availability of data for a site can be semi-quantitively assessed. From the table of data criticality and the table of data availability, site-specific cost for meeting the data needs can be determined, and allow a pre-permit spend estimated for a portfolio of projects. All of the data needs to evaluate a site are somewhat interconnected. We used criterion (2) above to determine if the data collection design would have to be modified to meet the need; if this was commonly true a linkage was shown. The application of this cross index to sites in the subsequent tasks will demonstrate that the demand for data types varies site-to-site and project-to-project. Examples of factors to be considered are the complexity of the geology, the injection goals such as rate and duration of the injection, and the types of risk and risk tolerance of key stakeholders. In future tasks the team will compare the demand for data with existing data availability. This will, in turn, determine when data needs to be acquired to support project development. For example, in a project area with complex structure, 3-D seismic data may be needed earlier and more urgently than in an area with simple rock body geometries. In some locations, a 3-D seismic survey has already been collected and can be purchased. In other locations the project developer will need to collect these data. For another example, a project near an urban area or near to a park may generate earlier and more substantive public concern than a site that is developed in mined lands. A calculation using the derivative from table 1 will show the different investment needs. Project cost will vary corresponding to data criticality and data availability.

42 ENGINEERING↗

Core Model Proposal #377: Breaking out food processing sector in GCAM

Purpose: This Core Model Proposal (CMP) expands the representation of detailed industry (CMP-326) in GCAM by separating the food processing sector from the aggregate “other industry sector”. Historical energy use is calibrated to IEA data for food processing, with some infilling for regions with limited IEA data. Food processing is linked to the GCAM food demand module, setting the energy demand for food processing in future periods based on food demand. While the direct price feedback is currently muted and the linkage is represented at the aggregated regional level, this CMP establishes the groundwork for a more detailed connection between the agrifood sectors and energy sectors in future work.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Functional characterization of glycosyltransferases in duckweed to enable predictive biology

Glycosyltransferases (GTs) catalyze the formation of glycosidic linkages to produce almost all complex carbohydrates. This project used a multi-disciplinary, high-throughput (HTP) biochemical and computational biology approach focused on duckweed as a model energy crop, to study carbohydrate metabolic processes. To achieve this, developed and carried out out high-throughput (HTP) functional characterization of plant glycosyltransferases (GTs) role of enzymatic microenvironments be assessed through a combined proteomic and computational biology approach, and the combined data was used to populate deep-learning frameworks to predict plant GT function. Functional validation achieved through this research is being used to assign gene function and study plant processes at the systems level to efficiently link the genome sequence with gene function. Together, the combined approaches used within this study provide a foundation for how computational prediction, in combination with high-throughput functional validation, can be used to study plant processes at the systems level and translate knowledge gained to efficiently link genome sequence with gene function in a species agnostic manner.

09 BIOMASS FUELS↗

Comparing Synthetic Routes and Thermal Characteristics of Alternate APO Variants

Low density, high-strength, temperature-resistant foams see widespread application in the aerospace and weapons fields due to their excellent qualities as structural supports. In these demanding environments, the most common formulation is a three-phase syntactic foam containing APOCure-601, BMI, and carbon or glass microballoons. Of these, APOCure-601 and BMI form the polymer resin amino-poly(oxadiazole) bismaleimide (APO-BMI), also known as Legacy APO or S-1,2-Ethyl-APO. In manufacturing this foam, the selective laser sintering (SLS) additive manufacturing technique is quickly gaining prominence, over more traditional injection molding since SLS allows for 3D printing of materials and reduces overall cost and waste production. That said, SLS also requires a narrow window between the melt and cure temperatures for a successful print. SLS printing of APO-BMI is therefore difficult since the compound possesses a broad window between its melting and curing temperatures, and also requires several post-cure steps or complete polymerization. This work explores synthesis optimization and thermal characteristics for variant Apo-BMI structures by observing the effect that alternative heteroatoms in the APO linkages, geometries 0f the BMI groups, and bridge structure identities impart on the resultant material. Synthetic methods for these altered structures were established in batch, with some others further converted to continuous flow chemistry, a method that produces materials in a continuous stream and is highly reproducible and readily scaled. Additionally, each structural change significantly altered the melt and cure properties for each APO variant, which is advantageous for SLS manufacturing.

60 APPLIED LIFE SCIENCES↗

Use of Graph Theory and Neural Networks for Microstructural Classification

Recent advances in materials data analytics have provided new avenues for determining process-structure-property (PSP) linkages in a variety of materials. Machine learning techniques including few-shot learning have increased the efficiency of classifying microscopy images for the purposes of material characterization. Modifications in segmentation also show potential in improving the accuracy of our current pyCHIP classifier. Replacing previous encoders trained on ImageNet with those trained on microscopy images like MicroNet has initially shown better performance at classifying images of irradiated samples. Additionally, different normalization approaches were tested to show no discernable effect on classification. The Louvain method for community detection is analyzed on a set of irradiated samples with different parameters to determine which proved beneficial under what circumstances. We suggest that microscopy experiments be automated in the future using a combination of these techniques to enable high-throughput analyses.

36 MATERIALS SCIENCE↗

Preliminary Plan to Inform Testing of a Heat Exchanger Test Article

This report presents a preliminary plan to guide the qualification testing of advanced heat exchanger (HX) components for nuclear-to-industrial heat transfer applications. The objective is to establish a defensible, physics-based methodology that integrates computational modeling, targeted experimentation, and in-service inspection considerations to demonstrate component performance and reliability under representative reactor conditions. The analysis identifies Sodium-cooled Fast Reactor (SFR) and High-Temperature Gas-cooled Reactor (HTGR) systems as reference configurations in terms of temperature, pressure, and chemical environment. Within these operating envelopes, dominant degradation mechanisms— including creep–fatigue interaction, flow-induced vibration, corrosion, and diffusion-bond deterioration—were evaluated to define test requirements. A comprehensive computationalexperimental framework is proposed to support life prediction and qualification activities. The framework couples high-fidelity structural-mechanics, thermal-hydraulic, and fluid-structure interaction models with accelerated degradation testing to produce a traceable linkage between microstructural evolution, mechanical performance, and remaining useful life (RUL). The approach adheres to established Verification, Validation, and Uncertainty Quantification (VVUQ) standards (ASME V&V 10/20; NUREG-2152) and incorporates a digital-twin architecture for continuous model refinement through data assimilation. The plan further outlines testing methodologies, including pre-test analyses, test-loop design parameters, and sensor placement strategies that maximize information yield while maintaining mechanistic fidelity. Complementary sections describe in-service inspection (ISI), on-line monitoring (OLM), and structural-health-monitoring (SHM) techniques applicable to compact HX geometries typical of advanced reactors. Collectively, these activities establish the technical foundation for demonstrating 40-60-year equivalent service life of advanced heat exchangers in support of the U.S. Department of Energy’s Advanced Reactor and Integrated Energy Systems programs. The forthcoming phase will execute the defined pre-test analyses, initiate hardware fabrication, and implement the integrated testing campaign to validate the proposed qualification methodology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Development of Multimodal Few-Shot Analytics for Electron Micrographs

Recent advances in materials data analytics have provided new avenues for determining process-structure-property (PSP) linkages in a variety of materials. Machine learning techniques including few-shot learning have increased the efficiency of classifying microscopy images for the purposes of material characterization. Attempts at creating a multimodal approach can provide further improvements to current models and help extract more salient features from data. In this vein, raw spectrum data was taken to provide an additional modality to our current pyCHIP classifier. Modifications in segmentation also show potential in improving the accuracy of the pyCHIP classifier. Classifier output was analyzed using network graphs and unsupervised clustering algorithms such as spectral clustering to detect better segmentation methods than the current “chipping” approach. We suggest that the chip selection process can be automated in the future using a combination of these techniques to enable high-throughput analyses.

36 MATERIALS SCIENCE↗

A Genomic Catalogue of Earth’s Microbiomes - Introductory KBase Narrative

The reconstruction of bacterial and archaeal genomes from shotgun metagenomes has enabled unprecedented insights into the ecology and evolution of environmental and host-associated microbiomes. Here we applied this powerful approach to over 10,000 metagenomes collected from diverse habitats covering all of Earth’s continents and oceans, human- and animal-host associated microbiomes, engineered environments, and natural and agricultural soils to capture extant microbial metabolic and functional potential. We present a comprehensive catalogue of 52,515 metagenome-assembled genomes representing 12,556 novel candidate species-level operational taxonomic units (OTUs), spanning 135 phyla, which expand the known phylogenetic diversity of Bacteria and Archaea by 44%. We also demonstrate the utility of this collection for secondary metabolite biosynthetic potential and predicting host-virus linkage, which can provide a view into the global distribution of lysogenic viruses. This resource underscores the value of leveraging genome-centric approaches to reveal genomic properties of uncultivated microbes that impact on ecosystem processes.

59 BASIC BIOLOGICAL SCIENCES↗

Genome_shuffling_enables_quantitative_trait_locus_mapping_in_Bacillus_subtilis

Genetic mapping is a powerful tool for eukaryotic genetics that has only been applied to bacteria in limited circumstances. Quantitative trait locus (QTL) mapping generally relies on sexual recombination to break linkages between genes, yet bacteria rarely undergo sufficient homologous recombination to generate suitable mapping populations. In this work, we used iterative biparental genome shuffling by protoplast fusion inBacillus subtilisto generate a population of bacteria with substantial random recombination throughout their genomes. Individual shuffled progeny were arrayed in well plates, resequenced, and characterized for a range of complex phenotypes including spore germination and swarming motility. Genetic mapping of the resulting phenotypes identified high-confidence QTLs of moderate size (∼10 kb), and these associations were validated through targeted genetic swaps. ThisB. subtilisQTL population can easily be used to map additional phenotypes, and the general approach for QTL mapping is applicable in a wide range of bacteria.

Bacillus subtilis↗

Comparison of copper and aluminum as the thermal link material for conduction-cooled accelerator cavities

Cryocooler conduction-cooling has recently emerged as a new frontier for cryogenic cooling for superconducting radiofrequency (SRF) cavities. In this scheme, an SRF cavity is mechanically coupled to a closed-cycle cryocooler using linkages made of high thermal conductivity metals. In this note, we compare the thermal transport properties of high purity aluminum and high purity copper as applied to SRF cavity conduction cooling. We show that copper can enable faster cooldown than aluminum from room temperature to the base temperature near 4 K and behave equally well or better during steady state cavity operation near the base temperature.

36 MATERIALS SCIENCE↗

Micro–Global Positioning Systems for Identifying Nightly Opportunities for Marburg Virus Spillover to Humans by Egyptian Rousette Bats

Marburg virus disease, caused by Marburg and Ravn orthomarburgviruses, emerges sporadically in sub-Saharan Africa and is often fatal in humans. The natural reservoir is the Egyptian rousette bat (ERB), which sheds virus in saliva, urine, and feces. Frugivorous ERBs discard test-bitten and partially eaten fruit, potentially leaving infectious virus behind that could be consumed by other susceptible animals or humans. Historically, 8 of 17 known Marburg virus disease outbreaks have been linked to human encroachment on ERB habitats, but no linkage exists for the other 9 outbreaks, raising the question of how bats and humans might intersect, leading to virus spillover. We used micro–global positioning systems to identify nightly ERB foraging locations. ERBs from a known Marburg virus–infected population traveled long distances to feed in cultivated fruit trees near homes. Our results show that ERB foraging behavior represents a Marburg virus spillover risk to humans and plausibly explains the origins of some past outbreaks.

60 APPLIED LIFE SCIENCES↗