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NASA NTRS2022

NASA Satellites and Data Fusion: A Case Study with Coral Reefs

As the world is experiencing a significant rise in both AI, Climate, and Space start-up companies, we are in a new wave of limitless innovation. NASA's statutory responsibility is to "provide for the widest practicable and appropriate dissemination of information concerning its activities and the results thereof." (51 U.S.C. § 20112) In particular, through machine learning, the public data drawn from NASA’s space assets can provide insights for addressing climate-related problems here on Earth. And many climate start-up companies can benefit from leveraging this data, either for proof of concepts or their own missions. In the Fall of 2021, several scientists from NASA and Coral Vita led a Practicum with the Georgia Institute of Technology Masters in Data Analytics program. The Practicum saw two teams of students develop and implement machine learning models to infer, from CALIPSO satellite imagery, vitality properties upon satellite pass. This kind of capability can lead to real-time mapping of coral health around the world, giving organization an understanding of where to prioritize reef reconstitution.. In this presentation, we will highlight this use case and discuss other concrete applications in which space data is used to solve problems here on Earth.

Earth Sciences↗

NASA NTRS2013

Space View Issues for Hyperspectral Sounders

The expectation for climate quality measurements from hyperspectral sounders is absolute calibration accuracy at the 100 mK level and stability at the < 40 mK/decade level. The Atmospheric InfraRed Sounder (AIRS)1, Cross-track Infrared Sounder (CrIS), and Infrared Atmospheric Sounding Interferometer (IASI) hyperspectral sounders currently in orbit have been shown to agree well over most of their brightness temperature range. Some larger discrepancies are seen, however, at the coldest scene temperatures, such as those seen in Antarctic winter and deep convective clouds. A key limiting factor for the calibrated scene radiance accuracy for cold scenes is how well the effective radiance of the cold space view pertains to the scene views. The space view signal is composed of external sources and instrument thermal emission at about 270 K from the scan mirror, external baffles, etc. Any difference in any of these contributions between space views and scene views will impact the absolute calibration accuracy, and the impact can be critical for cold scenes. Any change over time in these will show up as an apparent trend in calibrated radiances. We use AIRS data to investigate the validity of the space view assumption in view of the 100 mK accuracy and 40 mK/decade trend expectations. We show that the space views used for the cold calibration point for AIRS v5 Level-1B products meet these standards except under special circumstances and that AIRS v6 Level-1B products will meet them under all circumstances. This analysis also shows the value of having multiple distinct space views to give operational redundancy and analytic data, and that reaching climate quality requires continuing monitoring of aging instruments and adjustment of calibration.

trends↗

DOE OSTI2024

Tutorial on In Situ and Operando (Scanning) Transmission Electron Microscopy for Analysis of Nanoscale Structure–Property Relationships

In situ and operando (scanning) transmission electron microscopy [(S)TEM] is a powerful characterization technique that uses imaging, diffraction, and spectroscopy to gain nano-to-atomic scale insights into the structure–property relationships in materials. This technique is both customizable and complex because many factors impact the ability to collect structural, compositional, and bonding information from a sample during environmental exposure or under application of an external stimulus. In the past two decades, in situ and operando (S)TEM methods have diversified and grown to encompass additional capabilities, higher degrees of precision, dynamic tracking abilities, enhanced reproducibility, and improved analytical tools. Much of this growth has been shared through the community and within commercialized products that enable rapid adoption and training in this approach. This tutorial aims to serve as a guide for students, collaborators, and nonspecialists to learn the important factors that impact the success of in situ and operando (S)TEM experiments and assess the value of the results obtained. As this is not a step-by-step guide, readers are encouraged to seek out the many comprehensive resources available for gaining a deeper understanding of in situ and operando (S)TEM methods, property measurements, data acquisition, reproducibility, and data analytics.

(S)TEM↗

DOE OSTI2026

Comparability of Liquid Chromatography Tandem Mass Spectrometry Analysis of Dissolved Organic Matter across Laboratories

Non-targeted liquid chromatography tandem highresolution mass spectrometry (LC−MS/MS) is increasingly applied for the structure-resolved chemical analysis of dissolved organic matter (DOM). With new developments in MS instrumentation and analysis software, the approach has gained substantial momentum over the past decade. However, achieving high-quality analytical data that is reproducible and comparable across laboratories can be a bottleneck in non-targeted metabolomics and organic matter chemical analysis, especially for data reuse in repository-scale analyses. Understanding the capabilities as well as challenges of comparing LC−MS/MS data from different laboratories is necessary for inferring global trends from public data sets. To illuminate instrumentation factors that drive differences and variability, we used a standardized data analysis pipeline, including classical (CMN) and featurebased molecular networking (FBMN), to analyze data from a ring trial by 24 laboratories on identical sample sets of algal and DOM extracts that were mixed in predefined concentrations and spiked with standards. Our results showed that data sets from similar mass spectrometer types with unified instrument parameters were qualitatively comparable, resolving the same general trends and shared mass spectral features. Interlaboratory comparability was best for high-intensity features, while low-intensity features showed greater detection variability. Our analysis also highlights challenges when comparing data from instruments with different acquisition rates or operating with less standardized methods. Lastly, we provide recommendations for data integration, public data sharing, standardization, and best practices for standardized LC−MS/MS data acquisition, which will be critical for long-term time series and intercomparability of DOM chemical analyses.

DOM↗

DOE OSTI2024

Analytical capabilities for iodine detection: Review of possibilities for different applications

This Review summarizes a range of analytical techniques that can be used to detect, quantify, and/or distinguish between isotopes of iodine (e.g., long-lived 129 I, short-lived 131 I, stable 127 I). One reason this is of interest is that understanding potential radioiodine release from nuclear processes is crucial to prevent environmental contamination and to protect human health as it can incorporate into the thyroid leading to cancer. It is also of interest for evaluating iodine retention performances of next-generation iodine off-gas capture materials and long-term waste forms for immobilizing radioiodine for disposal in geologic repositories. Depending upon the form of iodine (e.g., molecules, elemental, and ionic) and the matter state (i.e., solid, liquid, and gaseous), the available options can vary. In addition, several other key parameters vary between the methods discussed herein, including the destructive vs nondestructive nature of the measurement process (including in situ vs ex situ measurement options), the analytical data collection times, and the amount of sample required for analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Emulation and detection of physical faults and cyber-attacks on building energy systems through real-time hardware-in-the-loop experiments

The increasing use of remote or mobile access, integrated wearable technologies, data exchange, and cloud-based data analytics in modern smart buildings is steering the building industry towards open communication technologies. The increased connectivity and accessibility could lead to more cyber-attacks in smart buildings. On the other hand, physical faults (e.g., HVAC -heating, ventilation, and air-conditioning faults) may have similar adverse impacts as those from the cyber-attacks on building energy systems, such as occupant discomfort, energy wastage, and equipment downtime. However, current physical behavior-based anomaly detection methods fail to differentiate between cyber-attacks and physical faults in building energy systems. Moreover, the challenge in collecting real-world threat data with ground truth has led researchers to rely on numerical models with user-defined assumptions, which may not accurately reflect real-world conditions due to the lack of in-situ experimental datasets. To address these challenges and gaps, this paper presents a flexible hardware-in-the-loop (HIL) testbed for generating cyber-attack and physical fault datasets and demonstrating threat detection algorithms in a real building automation system (BAS) environment. This testbed combines hardware (i.e., real BAS with local HVAC controllers and a physical network) with software (i.e., high-fidelity models to represent behaviors of building envelope and HVAC energy systems), enabling emulations of realistic threats. Five HIL experiments, including one baseline without any threats, two with physical faults, and two with cyber-attacks, were conducted to generate datasets containing detailed network traffic and system states. A joint classification framework, incorporating a network analyzer and a physical HVAC fault detector, was proposed to automatically detect cyber-physical abnormalities on BAS at both the network and the physical HVAC levels. The network analyzer comprises a conditional random fields (CRF) based command validator and a statistics-based detection strategy. The fault detector employs a weather and schedule-based pattern matching and feature-based principal component analysis (WPM-FPCA) method. Evaluation of the classification using four metrics from the multi-class confusion matrix revealed an average accuracy of 90.2%, recall of 89.7%, precision of 88.5% and F1-score of 89.2%. Finally, these results demonstrate that the proposed joint classification framework can effectively differentiate between specific types of cyber-attacks (e.g., device reinitialization attack, network Denial-of-Service attack) and physical faults (e.g., air handling unit operational fault, cooling coil valve stuck) in real time for improved building energy management.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2011

Transformation of Air Quality Monitor Data from the International Space Station into Toxicological Effect Groups

The primary reason for monitoring air quality aboard the International Space Station (ISS) is to determine whether air pollutants have collectively reached a concentration where the crew could experience adverse health effects. These effects could be near-real-time (e.g. headache, respiratory irritation) or occur late in the mission or even years later (e.g. cancer, liver toxicity). Secondary purposes for monitoring include discovery that a potentially harmful compound has leaked into the atmosphere or that air revitalization system performance has diminished. Typical ISS atmospheric trace pollutants consist of alcohols, aldehydes, aromatic compounds, halo-carbons, siloxanes, and silanols. Rarely, sulfur-containing compounds and alkanes are found at trace levels. Spacecraft Maximum Allowable Concentrations (SMACs) have been set in cooperation with a subcommittee of the National Research Council Committee on Toxicology. For each compound and time of exposure, the limiting adverse effect(s) has been identified. By factoring the analytical data from the Air Quality Monitor (AQM), which is in use as a prototype instrument aboard the ISS, through the array of compounds and SMACs, the risk of 16 specific adverse effects can be estimated. Within each adverse-effect group, we have used an additive model proportioned to each applicable 180-day SMAC to estimate risk. In the recent past this conversion has been performed using archival data, which can be delayed for months after an air sample is taken because it must be returned to earth for analysis. But with the AQM gathering in situ data each week, NASA is in a position to follow toxic-effect groups and correlate these with any reported crew symptoms. The AQM data are supplemented with data from real-time CO2 instruments aboard the ISS and from archival measurements of formaldehyde, which the AQM cannot detect.

James, John T.↗

NASA NTRS2014

Space Weathering of Olivine in Lunar Soils: A Comparison to Itokawa Regolith Samples

Regolith particles from airless bodies preserve a record of the space weathering processes that occurred during their surface exposure history. These processes have major implications for interpreting remote-sensing data from airless bodies. Solar wind irradiation effects occur in the rims of exposed grains, and impact processes result in the accumulation of vapordeposited elements and other surface-adhering materials. The grains returned from the surface of Itokawa by the Hayabusa mission allow the space weathering "style" of a chondritic, asteroidal "soil" to be compared to the lunar case. Here, we present new studies of space-weathered olivine grains from lunar soils, and compare these results to olivine grains from Itokawa. Samples and Methods: We analyzed microtome thin sections of olivine grains from the 20-45 micron fractions of three lunar soils: 71061, 71501 and 10084 (immature, submature and mature, respectively). Imaging and analytical data were obtained using a JEOL 2500SE 200kV field-emission scanning-transmission electron microscope equipped with a thin-window energy-dispersive x-ray spectrometer. Similar analyses were obtained from three Hayabusa olivine grains. Results and Discussion: We observed lunar grains showing a range of solar flare track densities (from <10(exp 9) to approx.10(exp 12)/sq cm). The lunar olivines all show disordered, highly strained, nanocrystalline rims up to 150-nm thick. The disordered rim thickness is positively correlated with solar flare track density. All of the disordered rims are overlain by a Si-rich amorphous layer, ranging up to 50-nm thick, enriched in elements that are not derived from the host olivine (e.g., Ca, Al, and Ti). The outmost layer represents impact-generated vapor deposits typically observed on other lunar soil grains. The Hayabusa olivine grains show track densities <10(exp 10)/sq cm and display disordered rims 50- to 100-nm thick. The track densities are intermediate to those observed in olivines in immature and submature lunar soils and indicate surface exposures of approx. 10(exp 5) years. The outermost few nanometers of the disordered rims on Hayabusa olivines are more Si-rich and Mg- and Fe-depleted relative to the cores of the grains and likely represent a minor accumulation of impact-generated vapors or sputter deposits. Nanophase Fe metal particles are less abundant in the Hayabusa rims compared to the rims on lunar grains. Conclusions: The Hayabusa and lunar olivine grain rims have widths and microstructures consistent with formation from atomic displacement damage from solar wind ions. The space weathering features in the Hayabusa grains are similar to those observed in olivines from immature to submature lunar soils. A major difference, however, is that the Hayabusa grains appear to lack the hypervelocity impact products (melt spherules, thick vapor deposits, and abundant nanophase Fe metal particles) that are common in lunar soil grains with a similar exposure history.

Keller, L. P.↗

DOE OSTI2025

Mic-hackathon 2024: hackathon on machine learning for electron and scanning probe microscopy

Microscopy is one of the primary sources of information on materials structure and functionality at the nanometer and atomic scales. The data generated through microscopy is often contained in well-structured datasets, enriched with extensive metadata and sample histories, although not always with the same level of detail or storage format. The broad incorporation of data management plans by major funding agencies ensures the preservation and accessibility of this data. However, deriving insights from these rich datasets remains challenging due to the lack of established code ecosystems, standardized benchmarks, and integration strategies. Correspondingly, the efficiency of data usage is very low, and time expenditures at the analysis stage are enormous. In addition to post-acquisition data analysis, the emergence of application programming interfaces by major microscope manufacturers now creates opportunities for real-time ML-based data analytics to enable automated decision making, and particularly ML-agent controlled real-time microscope operation. Despite these opportunities, there is a significant gap in integrating the ML community with the broader microscopy community, limiting the value that these methods bring to physics and materials discovery and materials optimization. Hackathons address these challenges by fostering collaboration between ML experts and microscopy professionals, encouraging the development of innovative solutions that leverage ML for microscopy and preparing the workforce of the future both for microscopy-intensive domains areas, instrument manufacturers, and ML scientists interested in real world applications for fundamental research, materials optimization, and manufacturing. The hackathon generated benchmark datasets and digital twins of microscopes that further contribute to the development of the field and establish data analysis ecosystems. All the codes can be found at GitHub(https://github.com/KalininGroup/Mic-hackathon-2024-codes-publication/tree/1.0.0.1) and Zenodo (https://zenodo.org/records/15579940).

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2022

Un-Numbered Operational Areas PRL 229 Railroad Tie Disposal Area Pond Confirmation Sampling Report

This Confirmatory Sampling (CS) Report (CSR) was prepared for the National Aeronautics and Space Administration (NASA), Kennedy Space Center (KSC), Florida in accordance with the CS Work Plan (CSWP) (HGL, 2022a). The CSR summarizes investigation activities performed on the Railroad Tie Disposal Area (RTDA) of the Un-Numbered Operational Areas (UNOA), Potential Release Location (PRL) 229 located at KSC. HydroGeoLogic, Inc. (HGL) prepared this report under Contract Number 80KSC019D0012. The purpose of the CSR is to provide information to evaluate the level of potential contamination in surface water and sediment samples collected from the RTDA PRL 229 Pond and determine if contaminants pose unacceptable risks to ecological receptors. The CSR provides analytical data of 10 sets of surface water and sediment samples collected in 2021. Surface water samples were analyzed for volatile organic compounds (VOCs), semi-volatile organic compounds (SVOCs), polynuclear aromatic hydrocarbon (PAHs), metals, hardness, and salinity, while sediment samples were analyzed for metals, total organic carbon (TOC), SVOCs, PAHs, and total petroleum hydrocarbons (TPH). The CSR includes a Screening Level Ecological Risk Assessment (SLERA) conducted under KSC’s Resource Conservation and Recovery Act (RCRA) Corrective Action Program to determine if unacceptable risks to ecological receptors exist at PRL 229 Pond. Metals and PAHs were detected in surface water samples, including detections of antimony, arsenic, barium, calcium, copper, lead, magnesium, thallium, zinc, anthracene, benzo(a)anthracene, benzo(a)pyrene, benzo(b)fluoranthene, benzo(g,h,i)perylene, benzo(k)fluoranthene, chrysene, dibenzo(a,h)anthracene, fluoranthene, indeno(1,2,3-c,d)pyrene and pyrene. Based on measured salinity (1.03 to 1.21 parts per thousand), the pond was identified as freshwater. Sediment analytical results also contained detections of metals and PAHs, including antimony, arsenic, barium, beryllium, cadmium, chromium, copper, lead, mercury, nickel, selenium, thallium, zinc, anthracene benzo(a)anthracene, benzo(a)pyrene, benzo(b)fluoranthene, benzo(g,h,i)perylene, benzo(k)fluoranthene, chrysene, dibenzo(a,h)anthracene, fluoranthene, indeno(1,2,3-c,d)pyrene and pyrene. Potential risks to ecological receptors were evaluated in accordance with the SLERA Work Plan and the Decision Process Document for the Resource Conservation and Recovery Act (RCRA) Corrective Action Program at KSC (DPD) (Geosyntec, 2019), and using the 2021 sediment and surface water analytical results. Potential ecological receptors evaluated in the SLERA include the aquatic community, benthic invertebrates, aquatic birds, and aquatic mammals. The SLERA included Steps 2a through 2c of the Ecological Risk Assessment (ERA) process in accordance with the DPD. Using multiple lines of evidence, the SLERA concluded that many of the detected analytes are present at concentrations similar to those in background or reference locations at KSC, and/or at concentrations that would not pose a significant risk to ecological communities. There are no screening values available for the avian community, and PAHs are bioaccumulative compounds. For this reason, food web modeling was completed as a supplement to Step 2c to provide a quantitative evaluation of this exposure pathway. Food web modeling indicates that PAHs are unlikely to pose a risk to birds exposed to site sediment and surface water. Based on the results of the SLERA, the contaminants in sediment and surface water pose no to minimal risk to the ecological communities that could live or forage at the site. Based on the results of the SLERA, no further study is recommended for the RTDA Pond at PRL 229.

Confirmation Sampling↗

DOE OSTI2024

Influence of tritium exposure route on vegetation types at the Savannah River Site

Plant, soil, water, and other media from various locations at the Savannah River Site were measured for total tritium (T) content and T speciation to characterize T in these areas, as well as investigate its uptake behavior and the transport of T species in these media. This characterization included the isolation and measurement of T in tritiated water (HTO), and (when possible) exchangeable organic bound T (E-OBT) and non-exchangeable organic bound T (NE-OBT). Two areas of interest were investigated: (1) a holding pond with T-contaminated water and (2) open basins or streams with low to background levels of T. Water in the holding pond is used to irrigate forest plots in the local area as a T remediation approach. This study compares the analytical data for water, soil/sediment, plants, and lichens from these locations. Here, the results indicate that the behavior of T in plants from these areas can be a function of one or more of the following: seasonal precipitation, the plant's primary route of access to the T-contamination (such as water uptake through the root vs. shoot), plant physical location (relative to T-contaminated water sources), plant rooting depth, pond water level, and plant height above the ground. Total T concentrations were lowest in the un-irrigated forest plants, followed by irrigated forest plants, shallow rooting plants near the pond, deep rooting plants further from the pond, and then water-saturated plants. The OBT:HTO and NE-OBT:E-OBT ratios were always greater for plants from irrigated forest plots compared to those from the holding pond.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Scaling microstructural processes in the sintering of ionic ceramics

A multi-scale framework, combining a multiphase field formulation and large deformation mechanics, was developed as a stepping stone to perform the data analytics of the microstructural level kinetics of a sintering solid. Relevant microstructural information from this framework, such as grain, stress, and porosity statistics, was scaled up to describe the macroscopic level sintering kinetics. Here, the developed formulation was applied to describe the electric field assisted sintering of Y 2 O 3 . Microstructural inhomogeneities in a multi-granular solid result in the formation of a field of compressive stress networks, which interleave with low compression and weakly tensile regions, defining a scaffolding for sintering concentration regions to develop. A Poisson effect-induced lateral stress network is also naturally self-induced as a result of the mechanical constraints imposed by the sintering apparatus. For long sintering times, localized shear stresses enhancing mass flow along grain boundaries and internal surfaces develop. Three-sided pores are removed by either vacancy transport to the surrounding pores, or move towards the external surfaces through grain boundary diffusion. Four- and higher order-sided pores stabilize because an equal amount of vacancies are gained and lost through the connecting grain boundaries. Grain dewetting contributes to pore coalescence, suggesting that pore kinetics and grain growth are coupled and should be analyzed in concert. The combined sintering and grain growth kinetics define six regimes of sintering behavior: (1) T, the transient regime; (2) E$_Υ$, the surface energy dominated, early sintering regime, where the grain growth exponent, p = 1, and the stress concentration factor, $f$ ~ $1/\hat{ρ}^{4.6}$; (3) E S , the stress dominated, early sintering regime, where p = 1 and $f$ ~ $1/\hat{ρ}^{4}$; (4) I$_Υ$, the surface energy dominated, intermediate sintering regime, where p = 2 and $f$ ~ $1/\hat{ρ}^{4.6}$; (5) I S , the stress dominated, intermediate sintering regime, where p = 2 and $f$ ~ $1/\hat{ρ}^{4}$; and (6) L, the late sintering regime, where p = 3 and $f$ ~ 1. At the macroscopic level, the rapid densification and suppression of grain growth observed in the electric field assisted sintering process is a consequence of the compounding effects of the underlying stress-, transport-, and interfacial-energy-induced energy minimization kinetics, as predicted by the multi-scale framework.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Distributed water desalination and purification systems: perspective and future directions

Distributed water treatment and desalination (DWTD) systems are critical for the development of a diverse water portfolio of the desired quality and intended use at the target location. Widespread adoption of DWTD has been hampered given the need for round-the-clock monitoring and the lack of local technical expertise for system management. However, self-adaptive operation, real-time remote monitoring, supervisory control, and asset management of DWTD systems are now feasible with the implementation of advanced local system control, cyberinfrastructure that facilitates real-time cloud-based analytics, data management, and artificial intelligence–powered decision support. Such an approach will introduce transformative virtual networks of DWTD systems to provide needed water to locations that are not served by centralized and satellite water treatment and desalination systems.

Cohen, Yoram [University of California, Los Angele↗

DOE OSTI2024

Recent and future developments in pultrusion technology with consideration for curved geometries: A review

Herein this paper examined the current state and future developments in pultrusion with particular emphasis on its application in curved part manufacturing. The relationship between factors such as resin chemistry, fiber characteristics, and die geometry that influences the properties of pultruded product were highlighted. Moreover, the specific challenges associated with pultruding curved parts such as the complexities in achieving uniformity and structural integrity in such geometries were discussed. The review emphasized mold design, process improvement, adaptive control systems for precise resin impregnation and material selection to address these challenges. Additionally, the paper suggests the integration of real-time monitoring and data analytics as ways to enhance quality control during curved parts pultrusion. These advancements will help to overcome challenges specific to curved pultrusion and make the process more efficient. Other manufacturing techniques such as filament winding, thermoforming, pulforming were mentioned as alternatives to curved parts pultrusion. The review also explores pultruded variable curvature processes, highlighting some notable patents and article related to this subject matter. Production of pultruded variable curvature parts was seen as a key driver that can shape the future of pultrusion. Finally, the paper anticipates future trends, with sustainability, customization, integration of advanced materials, and development of techniques for pultrusion of composites parts.

42 ENGINEERING↗

DOE OSTI2024

Envisioning U.S. Climate Predictions and Projections to Meet New Challenges

In the face of a changing climate, the understanding, predictions, and projections of natural and human systems are increasingly crucial to prepare and cope with extremes and cascading hazards, determine unexpected feedbacks and potential tipping points, inform long-term adaptation strategies, and guide mitigation approaches. Increasingly complex socio-economic systems require enhanced predictive information to support advanced practices. Such new predictive challenges drive the need to fully capitalize on ambitious scientific and technological opportunities. These include the unrealized potential for very high-resolution modeling of global-to-local Earth system processes across timescales, reduction of model biases, enhanced integration of human systems and the Earth Systems, better quantification of predictability and uncertainties; expedited science-to-service pathways, and co-production of actionable information with stakeholders. Enabling technological opportunities include exascale computing, advanced data storage, novel observations and powerful data analytics, including artificial intelligence and machine learning. Looking to generate community discussions on how to accelerate progress on U.S. climate predictions and projections, representatives of Federally-funded U.S. modeling groups outline here perspectives on a six-pillar national approach grounded in climate science that builds on the strengths of the U.S. modeling community and agency goals. This calls for an unprecedented level of coordination to capitalize on transformative opportunities, augmenting and complementing current modeling center capabilities and plans to support agency missions. Tangible outcomes include projections with horizontal spatial resolutions finer than 10 km, representing extremes and associated risks in greater detail, reduced model errors, better predictability estimates, and more customized projections to support next generation climate services.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Energy-efficient scientific computing using chemical reservoirs

The rapid growth of computing demands driven by scientific computing, data analytics, and artificial intelligence (AI) advancements has exposed the limitations of traditional digital processing systems. These systems are nearing physical energy barriers, making significant gains in energy efficiency increasingly unattainable. As we advance toward post-exascale computing, disruptive approaches are critical to overcoming these limitations. Among emerging analog solutions, biochemical computing offers a transformative path for achieving orders-of-magnitude improvements in energy efficiency. By leveraging the natural optimization capabilities of chemical reaction networks (CRNs), biochemical systems have the potential to meet high-performance computing needs through natural scalability. However, numerous challenges remain, including theoretical limitations in mapping computational problems to CRNs and practical barriers in implementing biochemical computing devices. In this paper, we present a framework for chemical computation using biochemical systems and introduce key components of our approach for energy-efficient scientific computing. We showcase the feasibility of this framework by solving a system of ordinary differential equations by emulating a chemical reservoir device, demonstrating its potential for addressing modern computing challenges. This work lays a foundational step toward harnessing the computational power of chemistry to design energy-efficient, scalable, high-performance next-generation computing systems.

Johnson, Connah G. M. [Pacific Northwest National ↗

DOE OSTI2024

Enabling HPC Scientific Workflows for Serverless

The convergence of edge computing, big data analytics, and AI with traditional scientific calculations is increasingly being adopted in HPC workflows. Workflow management systems are crucial for managing and orchestrating these complex computational tasks. However, it is difficult to identify patterns within the growing population of HPC workflows. Serverless has emerged as a novel computing paradigm, offering dynamic resource allocation, quick response time, fine-grained resource management and auto-scaling. In this paper, we propose a framework to enable HPC scientific workflows on serverless. Our approach integrates a widely used traditional HPC workflow generator with an HPC serverless workflow management system to create benchmark suites of scientific workflows with diverse characteristics. These workflows can be executed on different serverless platforms. We comprehensively compare executing workflows on traditional local containers and serverless computing platforms. Our results show that serverless can reduce CPU and memory usage respectively by 78.11% and 73.92% without compromising performance.

Andrei da silva, Anderson↗

DOE OSTI2025

Feed the fish: A review of aquaculture feeders and their strategic implementation

Automatic feeders are revolutionizing aquaculture by enabling precise and controlled feeding regimens that optimize growth, reduce feed waste, and enhance the overall efficiency of farming operations. Demand feeders provide some similar benefits but with feeding tailored to fish appetites and, in some cases, feed dispersal without electricity. This review explores the evolution, technological advancements, and applications of these feeders with a survey of recent research. It looks at common feeder designs and compares the pros and cons of five automatic feeder configurations in commercial use today. The article contrasts feeders and feed sizes for farmed species in different life stages and facilities, from hatcheries to ponds and offshore cages. It discusses the importance of species-tailored feeding strategies as well as impacts on fish behavior and health, nutrient delivery, and environmental sustainability. Incorporating sensors and on-site computing enables optimization in feeding algorithms that feeders then implement precisely and reliably. The review compiles results from multiple studies comparing growth rate, weight, and feed conversion ratio (FCR) outcomes from automatic feeders and demand feeders versus traditional hand-feeding regimens. The integration of feeders with real-time monitoring and data analytics is also discussed, highlighting future directions for research and adoption across the industry.

42 ENGINEERING↗