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DOE OSTI2025

AI-assisted transport of radioactive ion beams

Beams of radioactive heavy ions allow researchers to study rare and unstable atomic nuclei, shedding light into the internal structure of exotic nuclei and on how chemical elements are formed in stars. However, the extraction and transport of radioactive beams rely on time-consuming expert-driven tuning methods, where hundreds of parameters are manually optimized. Here, in this study, we introduce a system that employs Artificial Intelligence (AI), specifically utilizing Bayesian Optimization, to assist in the transport process of radioactive beams. We apply our methodology to real-life scenarios showing advantages when compared with standard tuning methods. This AI-assisted approach can be extended to other radioactive beam facilities around the world to improve operational efficiency and enhance scientific output.

43 PARTICLE ACCELERATORS↗

DOE OSTI2020

Towards Feature-Preserving 2D and 3D Vector Field Compression

The objective of this work is to develop error-bounded lossy compression methods to preserve topological features in 2D and 3D vector fields. Specifically, we explore the preservation of critical points in piecewise linear vector fields. We define the preservation of critical points as, without any false positive, false negative, or false type change in the decompressed data, (1) keeping each critical point in its original cell and (2) retaining the type of each critical point (e.g., saddle and attracting node). The key to our method is to adapt a vertex-wise error bound for each grid point and to compress input data together with the error bound field using a modified lossy compressor. Our compression algorithm can be also embarrassingly parallelized for large data handling and in situ processing. We benchmark our method by comparing it with existing lossy compressors in terms of false positive/negative/type rates, compression ratio, and various vector field visualizations with several scientific applications.

critical points↗

DOE OSTI2025

MiniMOD

SAND2025-03854O MiniMod is a user-friendly software tool designed to assess the performance of high-performance computing (HPC) systems. Researchers can use the program to test communication methods and computational tasks to understand how different setups can affect application efficiency. This software is particularly useful for optimizing network performance in scientific research, simulations, and data analysis. MiniMod‘s flexible design allows users to make informed decisions about their computing environments, which can enhance productivity and results in real-world applications. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Dosanjh, Matthew [Sandia National Lab. (SNL-CA), L↗

DOE OSTI2020

Kinetics Data of Iron(II), Manganese(II), Dissolved Organic Carbon and Nitrate from Batch Incubation Experiments Using Hyporheic Sediments from the East River Watershed, Colorado.

Hyporheic zones act as critical ecological links between terrestrial and aquatic systems where redox-sensitive metals of iron (Fe) and manganese (Mn) significantly impact nutrient cycling and water quality. In order to understand the production, release and speciation of Fe(II) and Mn(II) in groundwater, we conducted batch incubation experiments using sediment samples from a hyporheic zone of the East River floodplain in Colorado. The East River is part of the Watershed Function Scientific Focus Area (WFSFA) located in the Upper Colorado River Basin, United States. Collection and processing of the data is described in the Methods, along with details of data file contents. There are 6 data files provided in two formats: 1 zip-folder of .csv (open source) files, and 1 zip-folder of .xlsx (Excel) files. The data tables provided in the two formats are the exact same.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

ASU’s DAC polymer-enhanced cyanobacterial bioproductivity (AUDACity)

ASU’s DAC polymer-enhanced cyanobacterial bioproductivity (AUDACity) project aims to demonstrate a novel, scalable method for removing carbon dioxide (CO 2 ) directly from ambient air and delivering it to cyanobacterial cultures to produce commodity biofuel, mid-value protein for supplements, and high value phycocyanin (PC), a natural blue colorant (Figure A). This approach uses low-cost, reusable anion exchange polymers embedded in modular mesh packets, which capture CO 2 during drying cycles when exposed to ambient air, and release concentrated CO 2 into aqueous cultivation systems. The project addresses a critical challenge in energy research needed for developing sustainable, economically viable methods of Direct Air Capture (DAC) that can be integrated with bio-based systems for fuel and chemical production. AUDACity contributes to scientific understanding by integrating materials chemistry, cyanobacterial biology, and system engineering to create a distributed CO 2 delivery platform. Key insights have emerged around the design of biocompatible sorbents, optimization of CO 2 capture-release cycles, and durability of packet-based delivery systems under outdoor conditions. Notably, the team has synthesized and tested a range of polymer sorbents, identified mechanisms of material degradation and fouling, and advanced both lab- and pilot-scale cultivation systems to evaluate performance. From a technical and economic standpoint, AUDACity shows promise for achieving cost-effective CO 2 capture and delivery into aqueous media and biofuel production. Preliminary techno-economic analysis (TEA) indicates that the DAC system based on current performance can reach $\$$680/tonne CO 2 delivered into aqueous solution; with reasonable improvements to sorbent lifetime, sorbent capacity, reducing water uptake the approach could reach $\$$66/tonne by avoiding the need for energy-intensive sorbent regeneration and CO 2 compression, making it more feasible for decentralized deployment. With these costs for CO 2 and by extracting and selling high-value PC ($\$$50/kg) and mid-value protein supplement ($\$$6/kg), the remaining biomass can be hydrothermally treated into biofuel for $\$$2.50/gallon, and would support a small first-of-a-kind biorefinery capable of producing 500 barrels per day of biofuel. The project offers meaningful public benefits by advancing carbon removal technologies that are low-energy, modular, and adaptable to non-arable land and brackish water use. It aligns with national goals to develop advanced biotechnology and supports future pathways for bio-based fuels and products. By enabling direct coupling of CO 2 transfer into aqueous medium and biological carbon utilization, AUDACity lays the groundwork for effective algae cultivation without wasteful CO 2 delivery and is a promising and innovative solution for low-carbon fuel and bioproduct generation contributing to a vigorous bioeconomy.

09 BIOMASS FUELS↗

NASA NTRS1986

Liquid helium pumps for in-orbit transfer

Both mechanical and fountain-effect pumps are being considered for use in the in-orbit resupply of superfluid helium to a number of scientific instrument systems. This paper presents a review of the operating characteristics of these pumps. Particular emphasis will be given to the different methods of evaluating the efficiency of these pumps and their effectiveness in a transfer system.

Kittel, P.↗

NASA NTRS1993

Modeling Thermodynamics Of Charring Of A Polymer

Improved method of predicting and of nondestructively analyzing pyrolytic effects in, and thermomechanical properties of, polymers combines theories and techniques from several engineering and scientific disciplines. Evolved in effort to understand charring and erosion of carbon phenolic ablative material in nozzle of rocket engine. Also applicable to other polymers and particularly to nondestructive engineering analysis of specimens heated, charred, or burned.

Funaro, Gregory V.↗

NASA NTRS1992

Intelligent text retrieval in the NASA astrophysics data system

In collaboration with the NASA Scientific and Technical Information System, the NASA Astrophysics Data System (ADS) is establishing a service to provide access to the literature abstracts relevant to astronomy in the NASA Scientific and Technical Aerospace Reports and the International Aerospace Abstracts (together also known as NASA RECON). The service will include several sophisticated retrieval methods, which may be combined. Included will be methods to perform relevancy ranking from natural language queries, synonym and misspelling recognition, author name translation (e.g. for multiple transliteration possibilities), and other features. The capabilities of the current release will be shown, and the plans for the near future will be discussed.

Kurtz, M. J.↗

NASA NTRS2001

Development of an Early Warning Fire Detection System using Correlation Spectroscopy

Combustion byproducts are numerous. A few examples of the gaseous byproducts include carbon dioxide, carbon monoxide, hydrogen chloride, hydrogen cyanide and ammonia. For detecting these chemical species, classic absorption spectroscopy has been used for many decades, but the sensitivity of steady-state methods is often unsuitable for the detection of trace compounds at the low levels (parts per million to parts per billion) appropriate for scientific purposes. This is particularly so for monitoring equipment, which must be compact and cost-effective, and which is often subjected to shock, vibration, and other environmental effects that can severely degrade the performance of high-sensitivity spectrometers in an aircraft. Steady-state techniques also suffer from a lack of specificity; the deconvolution of the spectra of complex mixtures is a laborious and error prone process. These problems are exacerbated in remote fiber-optic monitoring where, for practical reasons, the fundamental absorbance region of the spectrum (often between 3 and 8 microns) is inaccessible, and the low-strength, closely spaced, near-infrared overtone absorbance bands must be used. We circumvented these challenges by employing correlation spectroscopy, a variation of modulation spectroscopy.

Goswami, K.↗

NASA NTRS2001

The Statistical Consulting Center for Astronomy (SCCA)

The process by which raw astronomical data acquisition is transformed into scientifically meaningful results and interpretation typically involves many statistical steps. Traditional astronomy limits itself to a narrow range of old and familiar statistical methods: means and standard deviations; least-squares methods like chi(sup 2) minimization; and simple nonparametric procedures such as the Kolmogorov-Smirnov tests. These tools are often inadequate for the complex problems and datasets under investigations, and recent years have witnessed an increased usage of maximum-likelihood, survival analysis, multivariate analysis, wavelet and advanced time-series methods. The Statistical Consulting Center for Astronomy (SCCA) assisted astronomers with the use of sophisticated tools, and to match these tools with specific problems. The SCCA operated with two professors of statistics and a professor of astronomy working together. Questions were received by e-mail, and were discussed in detail with the questioner. Summaries of those questions and answers leading to new approaches were posted on the Web (www.state.psu.edu/ mga/SCCA). In addition to serving individual astronomers, the SCCA established a Web site for general use that provides hypertext links to selected on-line public-domain statistical software and services. The StatCodes site (www.astro.psu.edu/statcodes) provides over 200 links in the areas of: Bayesian statistics; censored and truncated data; correlation and regression, density estimation and smoothing, general statistics packages and information; image analysis; interactive Web tools; multivariate analysis; multivariate clustering and classification; nonparametric analysis; software written by astronomers; spatial statistics; statistical distributions; time series analysis; and visualization tools. StatCodes has received a remarkable high and constant hit rate of 250 hits/week (over 10,000/year) since its inception in mid-1997. It is of interest to scientists both within and outside of astronomy. The most popular sections are multivariate techniques, image analysis, and time series analysis. Hundreds of copies of the ASURV, SLOPES and CENS-TAU codes developed by SCCA scientists were also downloaded from the StatCodes site. In addition to formal SCCA duties, SCCA scientists continued a variety of related activities in astrostatistics, including refereeing of statistically oriented papers submitted to the Astrophysical Journal, talks in meetings including Feigelson's talk to science journalists entitled "The reemergence of astrostatistics" at the American Association for the Advancement of Science meeting, and published papers of astrostatistical content.

Akritas, Michael↗

NASA NTRS1961

Flight Performance Handbook for Orbital Operations: Orbital Mechanics and Astrodynamics Formulae, Theorems, Techniques, and Applications

This handbook provides parametric data useful both to the space vehicle designer and mission analyst. It provides numerical and analytical relationships between missions and gross vehicle characteristics as a function of performance parameters. The effects of missile constraints and gross guidance limitations plus operational constraints such as launch site location, tracking net location, orbit visibility and mission on trajectory and orbit design parameters are exhibited. The influence of state-of- the-art applications of solar power as compared to future applications of nuclear power on orbit design parameters, such as eclipse time, are among the parameters included in the study. The principal aim, however, is in providing the analyst with useful parametric design information to cover the general area of earth satellite missions in the region of near-earth to cislunar space and beyond and from injection to atmospheric entry and controlled descent. The chapters are organized around the central idea of orbital operations in the 1961-1969 era with emphasis on parametric flight mechanics studies for ascent phase and parking orbits, transfer maneuvers, rendezvous maneuver, operational orbit considerations, and operational orbit control. The results are based almost entirely on the principles of flight and celestial mechanics. Numerous practical examples have been worked out in detail. This is especially important where it has been difficult or impossible to represent all possible variations of the parameters. The handbook contains analytical formulae and sufficient textual material to permit their proper use. The analytic methods consist of both exact and rapid, approximate methods. Scores of tables, working graphs and illustrations amplify the mathematical models which, together with important facts and data, cover the engineering and scientific applications of orbital mechanics. Each of the five major chapters are arranged to provide a rapid review of an entire astrodynamic subject. By the use of compact graphical and tabular presentation the full scope of the material is made available in an easy-to-use style. Throughout the volume the analyst is shown, by means of suitable introductions, notes, authoritative examples, and cross-references the vital interrelation of the various orbital mechanics topics in the general field of earth satellites and satellite rendezvous. The handbook is designed to give the analyst rapid, reliable access to the mathematics of orbital mechanics needed for virtually any working requirements.

Ambrosio, Alphonso↗

NASA NTRS2000

Scanning Electron Microscopy Investigation of a Sample Depth Profile Through the Martian Meteorite Nakhla

The ongoing scientific debate as to whether or not the Martian meteorite ALH84001 contained evidence of possible biogenic activities showed the need to establish consistent methods to ascertain the origin of such evidence. To distinguish between terrestrial organic material/microbial contaminants and possible indigenous microbiota within meteorites is therefore crucial. With this in mind a depth profile consisting of four samples from a new sample allocation of Martian meteorite Nakhla was investigated using scanning electron microscopy (SEM) and energy dispersive X-ray analysis. SEM imaging of freshly broken fractured chips revealed structures strongly recent terrestrial microorganisms, in some cases showing evidence of active growth. This conclusion was supported by EDX analysis, which showed the presence of carbon associated with these structures, we concluded that these structures represent recent terrestrial contaminants rather than structures indigenous to the meteorite. Page

Toporski, Jan↗

NASA NTRS2003

Processing Digital Imagery to Enhance Perceptions of Realism

Multi-scale retinex with color restoration (MSRCR) is a method of processing digital image data based on Edwin Land s retinex (retina + cortex) theory of human color vision. An outgrowth of basic scientific research and its application to NASA s remote-sensing mission, MSRCR is embodied in a general-purpose algorithm that greatly improves the perception of visual realism and the quantity and quality of perceived information in a digitized image. In addition, the MSRCR algorithm includes provisions for automatic corrections to accelerate and facilitate what could otherwise be a tedious image-editing process. The MSRCR algorithm has been, and is expected to continue to be, the basis for development of commercial image-enhancement software designed to extend and refine its capabilities for diverse applications.

Woodell, Glenn A.↗

NASA NTRS2014

File Specification for the 7-km GEOS-5 Nature Run, Ganymed Release Non-Hydrostatic 7-km Global Mesoscale Simulation

This document describes the gridded output files produced by a two-year global, non-hydrostatic mesoscale simulation for the period 2005-2006 produced with the non-hydrostatic version of GEOS-5 Atmospheric Global Climate Model (AGCM). In addition to standard meteorological parameters (wind, temperature, moisture, surface pressure), this simulation includes 15 aerosol tracers (dust, sea-salt, sulfate, black and organic carbon), O3, CO and CO2. This model simulation is driven by prescribed sea-surface temperature and sea-ice, daily volcanic and biomass burning emissions, as well as high-resolution inventories of anthropogenic sources. A description of the GEOS-5 model configuration used for this simulation can be found in Putman et al. (2014). The simulation is performed at a horizontal resolution of 7 km using a cubed-sphere horizontal grid with 72 vertical levels, extending up to to 0.01 hPa (approximately 80 km). For user convenience, all data products are generated on two logically rectangular longitude-latitude grids: a full-resolution 0.0625 deg grid that approximately matches the native cubed-sphere resolution, and another 0.5 deg reduced-resolution grid. The majority of the full-resolution data products are instantaneous with some fields being time-averaged. The reduced-resolution datasets are mostly time-averaged, with some fields being instantaneous. Hourly data intervals are used for the reduced-resolution datasets, while 30-minute intervals are used for the full-resolution products. All full-resolution output is on the model's native 72-layer hybrid sigma-pressure vertical grid, while the reduced-resolution output is given on native vertical levels and on 48 pressure surfaces extending up to 0.02 hPa. Section 4 presents additional details on horizontal and vertical grids. Information of the model surface representation can be found in Appendix B. The GEOS-5 product is organized into file collections that are described in detail in Appendix C. Additional details about variables listed in this file specification can be found in a separate document, the GEOS-5 File Specification Variable Definition Glossary. Documentation about the current access methods for products described in this document can be found on the GEOS-5 Nature Run portal: http://gmao.gsfc.nasa.gov/projects/G5NR. Information on the scientific quality of this simulation will appear in a forthcoming NASA Technical Report Series on Global Modeling and Data Assimilation to be available from http://gmao.gsfc.nasa.gov/pubs/tm/.

GEOS-5↗

NASA NTRS2011

Automatic Facial Expression Recognition and Operator Functional State

The prevalence of human error in safety-critical occupations remains a major challenge to mission success despite increasing automation in control processes. Although various methods have been proposed to prevent incidences of human error, none of these have been developed to employ the detection and regulation of Operator Functional State (OFS), or the optimal condition of the operator while performing a task, in work environments due to drawbacks such as obtrusiveness and impracticality. A video-based system with the ability to infer an individual's emotional state from facial feature patterning mitigates some of the problems associated with other methods of detecting OFS, like obtrusiveness and impracticality in integration with the mission environment. This paper explores the utility of facial expression recognition as a technology for inferring OFS by first expounding on the intricacies of OFS and the scientific background behind emotion and its relationship with an individual's state. Then, descriptions of the feedback loop and the emotion protocols proposed for the facial recognition program are explained. A basic version of the facial expression recognition program uses Haar classifiers and OpenCV libraries to automatically locate key facial landmarks during a live video stream. Various methods of creating facial expression recognition software are reviewed to guide future extensions of the program. The paper concludes with an examination of the steps necessary in the research of emotion and recommendations for the creation of an automatic facial expression recognition program for use in real-time, safety-critical missions.

Blanson, Nina↗

NASA NTRS2012

Automatic Facial Expression Recognition and Operator Functional State

Blanson, Nina↗

DOE OSTI2022

Artificial Intelligence and Machine Learning for Bioenergy Research: Opportunities and Challenges

The integration of artificial intelligence and machine learning (AI/ML) with automated experimentation, genomics, biosystems design, and bioprocessing technologies is poised to revolutionize scientific investigation and, particularly, bioenergy research. To identify the opportunities and challenges in this emerging research area, the U.S. Department of Energy’s (DOE) Biological and Environmental Research program (BER) and Bioenergy Technologies Office (BETO) held a joint virtual workshop on AI/ML for Bioenergy Research (AMBER) on August 23–25, 2022. These interests have since been amplified in a September 2022 Executive Order, “Advancing Biotechnology and Biomanufacturing Innovation for a Sustainable, Safe, and Secure U.S. Bioeconomy,” to promote a whole-of government approach to biotechnology development (White House 2022). Approximately 50 scientists with various backgrounds and expertise from academia, industry, and DOE national laboratories met to discuss the opportunities and challenges of AI/ML for bioenergy research. Workshop participants were tasked with assessing the potential for AI/ML and laboratory automation to advance biological understanding and engineering in general. They particularly examined how integrating AI/ML tools with laboratory automation could accelerate biosystems design and optimize biomanufacturing. Discussions included the data and computational infrastructure needed to augment biosystems design applications and the expertise and workforce development efforts urgently required to shift integrated systems toward bioenergy research more broadly. Participants discussed many existing and future applications of AI/ML for biosystems design ranging from enzymes to plants and microbes, microbiomes, and bioprocess development. They also identified three key categories of scientific and technical opportunities and challenges: high-quality data, AI/ML algorithms, and laboratory automation. Several main takeaways emerged from the workshop: 1. Numerous AI/ML and automated experimentation applications exist for a variety of DOE mission needs in energy and the environment; 2. Exemplary research grand challenges for which AI/ML could provide solutions include: building microbes and microbial communities to specifications, developing closed-loop autonomous design and control for biosystems design, and advancing scale-up and automation; 3. Lack of sufficient high-quality, annotated data hinders the development of AI/ML applications; 4. New and improved AI/ML tools are needed, particularly those meeting the specific needs of the BER and BETO research communities; 5. Trade-offs in performance, cost, and reliability exist between deploying commercially available versus building custom-developed instrumentation and software for automated or autonomous experimentation; translation of manual to automated or autonomous methods is often a nontrivial endeavor; 6. Training a new generation of young scientists who can develop and apply AI/ML tools is needed to solve long-standing scientific challenges in bioenergy research. The integration of AI/ML tools and automated experimentation represents a new data-driven research paradigm complementary to the traditional hypothesis-driven research paradigm. This paradigm accelerates design and optimization of biological systems and processes for a variety of DOE mission needs in energy and the environment. The AMBER workshop broadly explored the potential of this new paradigm for bioenergy research, of particular interest to BER and BETO, and identified key challenges and opportunities that DOE can address in the coming years by leveraging its unique capabilities and resources.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRSDate not supplied

INCREASING THE TRANSPARENCY AND REPRODUCIBILITY OF SPACE RADIATION SCIENCE: THE RADIATION BIOLOGY ONTOLOGY

Among the primary objectives of the Open/Open-Source Science paradigm are making scientific investigation data transparent and results reproducible [1], objectives shared by the FAIR principles [2]. To accomplish this, the conceptual framework that includes all the investigation objects needs to be accurately captured and communicated to all data consumers. A large part of this requires using metadata standards to annotate data collected. These standards should be readily accessible, informed by scientific community consensus and sufficiently specific to encompass all of the important aspects of the investigation. Starting in 2020 we have been co-leading an open consortium to develop a new metadata standard, the Radiation Biology Ontology (RBO), through the Open Biological and Biomedical Ontologies (OBO) Foundry [3]. We began by transforming many of the terms from the National Council on Radiation Protection and Measurement into concepts that can be formally related to existing OBO Foundry classes or attributes. We then identified and imported into the RBO existing OBO Foundry classes that have obvious relevance for radiation biomedicine (for example, concepts from the Environment Ontology that describe radiative processes, and concepts from the Gene Ontology dealing with molecular and cellular responses to radiation). Finally, we scrutinized datasets from investigations of radiation effects held in NASA GeneLab and LSDA repositories and added additional classes, instances, and attributes into the RBO that should be used to annotate these data. We developed the RBO using the open-source tools of GitHub and publish the RBO periodically through the NIH/NCBI BioPortal website, so systems worldwide can leverage the knowledge it contains [4]. This initial phase of concept modeling has yielded an RBO that at present has more than 300 declared concepts, with more than 3500 additional concepts imported from other OBO Foundry ontologies. While this first phase has focused on concepts for annotating samples, environments, exposures, and measurements, the next phase will center on supporting annotation of results and findings, such as concept models of molecular, cellular and tissue effects. The value of the RBO will be determined in part by our ability to engage the community in its development, and we have established a Radiobiology Informatics Consortium with unrestricted membership as the owner of the RBO in order to encourage investigators, system owners and other to join in this effort. Anyone can report issues or request new concept modeling or other features directly on GitHub. By using the BioPortal application programming interface, systems can pose dynamic queries to the latest version of the RBO for information on individual classes or entire hierarchies; this design eliminates the need for systems to be updated in order to use newer versions of the RBO. We hope to contribute to the advancement of open radiobiological science through the continued, open development of the RBO, that will provide more precise, machine-interpretable descriptions of investigations, as well as support data meta-analysis through machine learning or other artificial intelligence methods. REFERENCES [1] Open science in space. Nature Medicine, 2021. 27(9): p. 1485-1485. [2] Wilkinson, M.D., et al., The FAIR Guiding Principles for scientific data management and stewardship. Sci Data, 2016. 3: p. 160018. [3] Smith, B., et al., The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol, 2007. 25(11): p. 1251-5. [4] Whetzel, P.L., et al., BioPortal: enhanced functionality via new Web services from the National Center for Biomedical Ontology to access and use ontologies in software applications. Nucleic Acids Res, 2011. 39(Web Server issue): p. W541-5.

informatics↗