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All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Potential Precursor Compounds for Chlorohydrocarbons Detected in Gale Crater, Mars, by the SAM Instrument Suite on the Curiosity Rover

The detection of chlorinated organic compounds in near-surface sedimentary rocks by the Sample Analysis at Mars (SAM) instrument suite aboard the Mars Science Laboratory Curiosity rover represents an important step toward characterizing habitable environments on Mars. However, this discovery also raises questions about the identity and source of their precursor compounds and the processes by which they become chlorinated. Here we present the results of analog experiments, conducted under conditions similar to SAM gas chromatography-mass spectrometry analyses, in which we pyrolyzed potential precursor compounds in the presence of various Cl salts and Fe oxides that have been identified in Martian sediments. While chloromethanes could not be unambiguously identified, 1,2-dichloropropane (1,2-DCP), which is one of the chlorinated compounds identified in SAM data, is formed from the chlorination of aliphatic precursors. Additionally, propanol produced more 1,2-DCP than nonfunctionalized aliphatics such as propane or hexanes. Chlorinated benzenes ranging from chlorobenzene to hexachlorobenzene were identified in experiments with benzene carboxylic acids but not with benzene or toluene. Lastly, the distribution of chlorinated benzenes depended on both the substrate species and the nature and concentration of the Cl salt. Ca and Mg perchlorate, both of which release O2 in addition to Cl2 and HCl upon pyrolysis, formed less chlorobenzene relative to the sum of all chlorinated benzenes than in experiments with ferric chloride. FeCl3, a Lewis acid, catalyzes chlorination but does not aid combustion. Accordingly, both the precursor chemistry and sample mineralogy exert important controls on the distribution of chlorinated organics.

Miller, Kristen E.↗
NASA NTRS2019

A 3 Gyr White Dwarf with Warm Dust Discovered via the Backyard Worlds: Planet 9 Citizen Science Project

Infrared excesses due to dusty disks have been observed orbiting white dwarfs with effective temperatures between 7200 and 25,000 K, suggesting that the rate of tidal disruption of minor bodies massive enough to create a coherent disk declines sharply beyond 1 Gyr after white dwarf formation. We report the discovery that the candidate white dwarf LSPM J0207+3331, via the Backyard Worlds: Planet 9 citizen science project and Keck Observatory follow-up spectroscopy, is hydrogen dominated with a luminous compact disk (L IR/L star = 14%) and an effective temperature nearly 1000 K cooler than any known white dwarf with an infrared excess. The discovery of this object places the latest time for large-scale tidal disruption events to occur at ~3 Gyr past the formation of the host white dwarf, making new demands of dynamical models for planetesimal perturbation and disruption around post-main-sequence planetary systems. Curiously, the mid-infrared photometry of the disk cannot be fully explained by a geometrically thin, optically thick dust disk as seen for other dusty white dwarfs, but requires a second ring of dust near the white dwarf's Roche radius. In the process of confirming this discovery, we found that careful measurements of WISE source positions can reveal when infrared excesses for white dwarfs are co-moving with their hosts, helping distinguish them from confusion noise.

Debes, John H.↗
NASA NTRS2020

A NICER Look at the State Transitions of the Black Hole Candidate MAXI J1535-571 During its Reflares

The black hole candidate and X-ray binary MAXI J1535−571 was discovered in 2017 September. During the decay of its discovery outburst, and before returning to quiescence, the source underwent at least four reflaring events, with peak luminosities of ∼1035–36 erg s−1 (d/4.1 kpc)2. To investigate the nature of these flares, we analysed a sample of NICER (Neutron star Interior Composition Explorer) observations taken with almost daily cadence. In this work, we present the detailed spectral and timing analysis of the evolution of the four reflares. The higher sensitivity of NICER at lower energies, in comparison with other X-ray detectors, allowed us to constrain the disc component of the spectrum at ∼0.5 keV. We found that during each reflare the source appears to trace out a q-shaped track in the hardness–intensity diagram similar to those observed in black hole binaries during full outbursts. MAXI J1535−571 transits between the hard state (valleys) and softer states (peaks) during these flares. Moreover, the Comptonized component is undetected at the peak of the first reflare, while the disc component is undetected during the valleys. Assuming the most likely distance of 4.1 kpc, we find that the hard-to-soft transitions take place at the lowest luminosities ever observed in a black hole transient, while the soft-to-hard transitions occur at some of the lowest luminosities ever reported for such systems.

V A Cuneo↗
NASA NTRSDate not supplied

New developments in space radiation research at NASA: Annotating data using a novel radiation biology ontology

Like many interdisciplinary sciences, data producers and consumers in the field of radiation biology often use a wide variety of terminology to describe their experiments and data. Furthermore, space systems and technologies are rapidly evolving, and a shared understanding and common terminology for these is also lacking. The efficiency of research organizations can be enhanced by standardizing metadata through the use of knowledge resources like ontologies. Employing a sophisticated model such as a formal ontology to standardize metadata enables automated data acquisition processes and supports more complete, accurate meta-analysis through more efficient and complete data discovery and retrieval, particularly when using multiple data sources. Thus, we developed the Radiation Biology Ontology (RBO) in order to improved radiation biology metadata uniformity and transparency. We used open-source software (the Ontology Development Kit, Protégé and WebProtégé) and worked within the OBO Foundry framework, which includes a set of ontology development principles and practices for ontology consistency, uniformity, and accountability. The RBO has now been incorporated into two radiation research data repositories, NASA’s GeneLab omics database (https://genelab.nasa.gov), and the European Commission STORE database (https://www.storedb.org/). Continuous build integration tools allowed our international RBO collaboration to be more efficient and focus its efforts on semantic model design. Currently, the RBO contains over 300 annotated classes and individuals specific to the study of radiation on biological systems, as well as imports of many additional classes from other OBO Foundry ontologies that relate to and/or provide context for these RBO entities. We publish the RBO through the OBO Foundry, so that it is available for browsing, download, and querying through NCBI Bioportal web site and application programming interface. The NASA Ames Life Science Data Archive (ALSDA) is also in the process of adopting use of the RBO, taking NASA one step closer to a knowledge-based system for space biology data. It is our hope that the global communities of radiation research Investigators, data curators and data analysts can similarly leverage the RBO and will contribute to its further development.

radiation↗
NASA NTRSDate not supplied

Developing Concepts of Operations Using Multi-Step Tool Techniques With Large Language Models

The National Aeronautics and Space Administration (NASA) Air Mobility Pathfinders (AMP) project is developing and evaluating concepts of operations (ConOps) for safe, secure, and scalable Urban Air Mobility (UAM) operations. The AMP project’s Operational Concepts, Architecture, and Requirements Integration (OCARI) Team is using a Model Based System Engineering (MBSE) approach for integration, interoperability, and traceability of Advanced Air Mobility (AAM) ecosystems centered around urban air taxi services. The team’s goal is to define structures and behaviors needed for system feasibility, readiness, and interoperability, establish a UAM knowledge base, and trace and validate assumptions and requirements relevant to AAM. NASA Langley Research Center (LaRC) is spearheading an innovative digital engineering approach to integrate, communicate, and facilitate the research of multi-modal transportation systems. The Knowledge-based Digital Platform (KbDP) is a concept being developed that ties the workflows of Project Managers (PM), Principal Investigators (PI), and System Engineers together across organizational boundaries. It does so through the management of an information database defined by mathematical, data science, and system engineering principles. Machine Learning (ML) algorithms play a key role in this concept by extracting meaningful knowledge from relational and graph databases, document repositories, and system artifacts, which the human user leverages to greatly improve the efficiency and effectiveness of their research. Recent advancements in the field of Large Language Models (LLMs), specifically models trained for tool use, such as Command-R , now allow for the reliable implementation of single-step and multi-step tool-centric systems. These techniques provide the LLM with a set of tools, in our case Python functions, that can be called on to answer a much wider range of questions compared to LLMs implemented using a traditional single-source or Retrieval Augmented Generation (RAG) approach. Through this method, the LLM can pull information from multiple data sources, such as relational or graph databases, document repositories, application programming interfaces (APIs), and SysML artifacts depending on the user’s question. The LLM can also output the information in a variety of different formats, using output generation tools, such as CSV, UML, or SysML artifacts. Additionally, tools can be assigned roles and can work together to provide answers to queries in an “agent” like approach, similar to that implemented by Microsoft’s AutoGen framework where different agents can converse with each other to accomplish tasks. Previously, our team developed a chatbot system with “agent like” functionality in the form of different “modes” the user could select from a user interface (UI), this architecture can be seen on the left in figure 1. Three different modes were implemented, the first mode allowed the LLM to utilize the structures and algorithms within a graph database to trace UAM requirements. The second mode gave the LLM access to a vector search capable of providing relevant information from thousands of document pages related to UAM ConOps and requirements. The third mode served as a general assistant where users could enter open-ended questions and custom prompts to utilize the LLM for different use-cases. This system improved the process surrounding generating and analyzing information related to UAM requirements, however, the implementation provided a clunky user experience. Users were required to know what mode to select within the UI in advance before entering their question to the selected tool. Moreover, the different tools were isolated from each other, they lacked bidirectional links that would allow for tools to collaborate to generate better responses. Our team is working on a new architecture, seen on the right in the below figure, with the goal to address many of the UX shortcomings of our original system while improving the accuracy and depth of responses from the LLM. This new system will automatically select the appropriate tool to use based off the user’s question. Each tool will be capable of calling on any of the other tools available to the LLM, resulting in a collaborative pipeline where tools can pass data between other tools until enough data is received to generate an answer to the user’s question. Using a locally deployed, open-source, LLM, the NASA OCARI team, in collaboration with Collins Aerospace, will implement a prototype application that will bridge knowledge across multiple sources to assist System Engineers (SEs) with requirements discovery and tracing, research question and use case identification, and assumption validation. Such a system will also allow SEs to more easily, and intuitively, explore the AAM ecosystem, ultimately improving the efficiency and effectiveness of the SE's research and decision-making processes surrounding ConOps development and validation. In this session, our team will provide a video demonstration of our new prototype architecture in action. We will also present an overview of our prototype system architecture and talk about its advantages over traditional LLM deployments along with how those advantages can provide additional value to the field of System Engineering.

systems engineering↗
NASA NTRS2024

NASA HECC Geometry and Performance Review Part 2: Geometric Differences Between the As-Manufactured and Design-Intent Impeller Geometry and their Effects on the Vaneless Diffuser Configuration Performance

An investigation of the NASA High Efficiency Centrifugal Compressor (HECC) vaneless diffuser configuration was performed. This multipart investigation focused on validating the computational model against experimental data. The validated model was then used to explore the effects of observed geometric differences between the As-Manufactured and Design-Intent impellers. Lastly, the validated model was used for comparison against an experimental tip clearance study. Part II of the investigation of the NASA HECC vaneless diffuser configuration focused on understanding the differences in geometry and performance between the As-Manufactured impeller and the Design-Intent impeller. This was achieved through comparison of the As-Manufactured HECC vaneless computational model, developed from the solid model of the impeller and validated in Part I, against a new model developed from the Design-Intent blade sections published in NASA/CR-2014-218114/Rev1. The 1D performance values showed that the As-Manufactured impeller underperformed compared to the Design-Intent for all four speedlines that were simulated. Further investigation of profiles, loading and contours showed consistent underperformance of the As-Manufactured relative to the Design-Intent. An investigation into the source of the performance differences led to the discovery of several significant variations in the impeller geometries. The differences that were observed can be summarized into four categories: fillets, trailing-edge exit radii variation, dissimilarity in the splitter leading-edge geometry and main blade thickness differences. The investigation then shifted its effort to quantify the performance effects caused by geometric differences. The investigation showed that out of the four geometric differences that were explored, the differences in the splitter blade had the largest impact. These differences most notably changed flow physics near the splitter leading edge, especially near the tip of the impeller.

centrifugal compressor↗
DOE OSTI2015

CONFIRMATION OF THE OGLE-2005-BLG-169 PLANET SIGNATURE AND ITS CHARACTERISTICS WITH LENS–SOURCE PROPER MOTION DETECTION

We present Keck NIRC2 high angular resolution adaptive optics observations of the microlensing event OGLE-2005-BLG-169Lb, taken 8.21 years after the discovery of this planetary system. For the first time for a microlensing planetary event, the source and the lens are completely resolved, providing a precise measurement of their heliocentric relative proper motion, μ{sub rel,helio}=7.44±0.17 mas yr{sup −1}. This confirms and refines the initial model presented in the discovery paper and rules out a range of solutions that were allowed by the microlensing light curve. This is also the first time that parameters derived from a microlensing planetary signal are confirmed, both with the Keck measurements, presented in this paper, and independent measurements obtained with the Hubble Space Telescope in I,V and B bands, presented in a companion paper. Hence, this new measurement of μ{sub rel,helio}, as well as the measured brightness of the lens in H band, enabled the mass and distance of the system to be updated: a Uranus-mass planet (m{sub p}=13.2±1.3M{sub ⊕}) orbiting a K5-type main sequence star (M{sub ∗}=0.65±0.05M{sub ⊙}) separated by a{sub ⊥}=3.4±0.3 AU, at the distance D{sub L}=4.0±0.4 kpc from us.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

An artificial intelligence accelerated virtual screening platform for drug discovery

Abstract Structure-based virtual screening is a key tool in early drug discovery, with growing interest in the screening of multi-billion chemical compound libraries. However, the success of virtual screening crucially depends on the accuracy of the binding pose and binding affinity predicted by computational docking. Here we develop a highly accurate structure-based virtual screen method, RosettaVS, for predicting docking poses and binding affinities. Our approach outperforms other state-of-the-art methods on a wide range of benchmarks, partially due to our ability to model receptor flexibility. We incorporate this into a new open-source artificial intelligence accelerated virtual screening platform for drug discovery. Using this platform, we screen multi-billion compound libraries against two unrelated targets, a ubiquitin ligase target KLHDC2 and the human voltage-gated sodium channel Na V 1.7. For both targets, we discover hit compounds, including seven hits (14% hit rate) to KLHDC2 and four hits (44% hit rate) to Na V 1.7, all with single digit micromolar binding affinities. Screening in both cases is completed in less than seven days. Finally, a high resolution X-ray crystallographic structure validates the predicted docking pose for the KLHDC2 ligand complex, demonstrating the effectiveness of our method in lead discovery.

Science & Technology - Other Topics↗
NASA NTRS2005

Development, Integration and Utilization of Surface Nuclear Energy Sources for Exploration Missions

Throughout the past five decades numerous studies have identified nuclear energy as an enhancing or enabling technology for human surface exploration missions. Nuclear energy sources were used to provide electricity on Apollo missions 12, 14, 15, 16, and 17, and on the Mars Viking landers. Nuclear energy sources were used to provide heat on the Pathfinder; Spirit, and Discovery rovers. Scenarios have been proposed that utilize -1 kWe radioisotope systems for early missions, followed by fission systems in the 10 - 30 kWe range when energy requirements increase. A fission energy source unit size of approximately 150 kWt has been proposed based on previous lunar and Mars base architecture studies. Such a unit could support both early and advanced bases through a building block approach.

Houts, Michael G.↗
DOE OSTI2018

Parallel k-means Clustering of Geospatial Data Sets Using Manycore CPU Architectures

The increasing availability of high-resolution geospatiotemporal data sets from sources such as observatory networks, remote sensing platforms, and computational Earth system models has opened new possibilities for knowledge discovery and mining of weather, climate, ecological, and other geoscientific data sets fused from disparate sources. Many of the standard tools used on individual workstations are impractical for the analysis and synthesis of data sets of this size; however, new algorithmic approaches that can effectively utilize the complex memory hierarchies and the extremely high levels of parallelism available in state-of-the-art high-performance computing platforms can enable such analysis. Here, we describe pKluster, an open-source tool we have developed for accelerated k-means clustering of geospatial and geospatiotemporal data, and discuss algorithmic modifications and code optimizations we have made to enable it to effectively use parallel machines based on novel CPU architectures—such as the Intel “Knights Landing” Xeon Phi and Skylake Xeon processors—with many cores and hardware threads, and employing significant single instruction, multiple data (SIMD) parallelism. We outline some applications of the code in ecology and climate science contexts and present a detailed discussion of the performance of the code for one such application, LiDAR-derived vertical vegetation structure classification.

Mills, Richard T↗
NASA NTRS1997

Hard X-Ray Emission of X-Ray Bursters

The main results from this investigation were serendipitous. The long observation approved for the study of the hard X-ray emission of X-ray bursters lead, instead, to one of the largest early samples of the behavior of fast quasi-periodic oscillations (QPOS) in an atoll sources. Our analysis of this data set lead to the several important discoveries including the existence of a robust correlation between QPO frequency and the flux of a soft blackbody component of the X-ray spectrum in the atoll source 4U 0614+091.

Kaaret, Phillip↗
DOE OSTI2021

Geochemical advances in Arctic Alaska oil typing – North Slope oil correlation and charge history

The Arctic Alaska petroleum province is geologically and geochemically complex. Mixed hydrocarbon charge from multiple source rocks and/or levels of thermal maturity is common within an individual oil pool. Biomarker and chemometric statistical analyses were used to correlate twenty-nine oils to five oil families derived from: (1) Triassic Shublik Formation (calcareous organofacies), (2) Triassic Shublik Formation (shaly organofacies), (3) Jurassic Kingak Shale, (4) Cretaceous shale (pebble shale unit and Hue Shale), and (5) Paleogene shale (Canning Formation). Age-diagnostic and source-related oil biomarker parameters establish clear genetic relationships between the normal oil-window components and their putative source designations. However, application of diamondoid analyses reveals mixed-oil accumulations with postmature charge contributions (diamondoid-rich and biomarker-poor) in many oils. Most sampled reservoirs contain a predominant charge derived from a single oil-window source plus a minor contribution from one or more higher maturity source(s). Variations in source organofacies also are recognized in the Shublik, Kingak, and Cretaceous oil families. In some cases, oils from multiple pools within a single field display relatively homogeneous geochemical profiles, suggesting a common source and migration pathway. For example, oil from the significant Pikka discovery is inferred to originate mainly from the calcareous Shublik Formation. In other cases, variability among oils from multiple pools within a single field (e.g., Milne Point, Colville River, and Northstar) likely indicates a more complex source, migration, and charge history. The results of this study may be useful for anticipating the composition of oil charge in stratigraphic traps with low-permeability sandstone reservoirs, where oil gravity and other chemical parameters may influence economic viability.

58 GEOSCIENCES↗
DOE OSTI2014

Observations of the unidentified gamma-ray source TeV J2032+4130 by Veritas

TeV J2032+4130 was the first unidentified source discovered at very high energies (VHEs; E > 100 GeV), with no obvious counterpart in any other wavelength. It is also the first extended source to be observed in VHE gamma rays. Following its discovery, intensive observational campaigns have been carried out in all wavelengths in order to understand the nature of the object, which have met with limited success. We report here on a deep observation of TeV J2032+4130 based on 48.2 hr of data taken from 2009 to 2012 by the Very Energetic Radiation Imaging Telescope Array System experiment. The source is detected at 8.7 standard deviations (σ) and is found to be extended and asymmetric with a width of 9.'5 ± 1.'2 along the major axis and 4.'0 ± 0.'5 along the minor axis. The spectrum is well described by a differential power law with an index of 2.10 ± 0.14{sub stat} ± 0.21{sub sys} and a normalization of (9.5 ± 1.6{sub stat} ± 2.2{sub sys}) × 10{sup –13} TeV{sup –1} cm{sup –2} s{sup –1} at 1 TeV. We interpret these results in the context of multiwavelength scenarios which particularly favor the pulsar wind nebula interpretation.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1994

Gamma-ray burst theory: Back to the drawing board

Gamma-ray bursts have always been intriguing sources to study in terms of particle acceleration, but not since their discovery two decades ago has the theory of these objects been in such turmoil. Prior to the launch of Compton Gamma-Ray Observatory and observations by Burst and Transient Source Experiment (BATSE), there was strong evidence pointing to magnetized Galactic neutron stars as the sources of gamma-ray bursts. However, since BATSE the observational picture has changed dramatically, requiring much more distant and possibly cosmological sources. I review the history of gamma-ray burst theory from the era of growing consensus for nearby neutron stars to the recent explosion of halo and cosmological models and the impact of the present confusion on the particle acceleration problem.

Harding, Alice K.↗
DOE OSTI2017

Models of the strongly lensed quasar DES J0408-5354

We present gravitational lens models of the multiply imaged quasar DES J0408-5354, recently discovered in the Dark Energy Survey (DES) footprint, with the aim of interpreting its remarkable quad-like configuration. We first model the DES single-epoch $grizY$ images as a superposition of a lens galaxy and four point-like objects, obtaining spectral energy distributions (SEDs) and relative positions for the objects. Three of the point sources (A,B,D) have SEDs compatible with the discovery quasar spectra, while the faintest point-like image (G2/C) shows significant reddening and a `grey' dimming of $\approx0.8$mag. In order to understand the lens configuration, we fit different models to the relative positions of A,B,D. Models with just a single deflector predict a fourth image at the location of G2/C but considerably brighter and bluer. The addition of a small satellite galaxy ($R_{\rm E}\approx0.2$") in the lens plane near the position of G2/C suppresses the flux of the fourth image and can explain both the reddening and grey dimming. All models predict a main deflector with Einstein radius between $1.7"$ and $2.0",$ velocity dispersion $267-280$km/s and enclosed mass $\approx 6\times10^{11}M_{\odot},$ even though higher resolution imaging data are needed to break residual degeneracies in model parameters. The longest time-delay (B-A) is estimated as $\approx 85$ (resp. $\approx125$) days by models with (resp. without) a perturber near G2/C. The configuration and predicted time-delays of J0408-5354 make it an excellent target for follow-up aimed at understanding the source quasar host galaxy and substructure in the lens, and measuring cosmological parameters. We also discuss some lessons learnt from J0408-5354 on lensed quasar finding strategies, due to its chromaticity and morphology.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Framework for Analysis and Visualization of Simulation Data (VizAly)

As supercomputing resources increase, cosmological scientists are able to run more detailed and larger simulations generating massive amounts of data. Analyzing these simulations with an available open-source toolkit is important for collaborative Department of Energy scientific discovery across labs, universities, and other partners. Developed software as a part of this collection include: comparing data with other existing simulations, verifying and validating results with observation databases, new halo finder algorithms, and using analytical tools to get insights into the physics of the cosmological universe. The goal of this software project is to provide a set of open-source libraries, tools, and packages for large-scale cosmology that allows scientists to visualize, analyze, and compare large-scale simulation and observational data sets. Developed software will provide a variety of methods for processing, visualization, and analysis of astronomical observation and cosmological simulation data. These tools are intended for deployment on multiple scientific computing platforms, including but not limited to personal computers, cloud computing, experimental sites (telescopes) and high performance supercomputers.

Wendelberger, Joanne↗
DOE OSTI2023

ESnet Requirements Review Program Through the IRI Lens: A Meta-Analysis of Workflow Patterns Across DOE Office of Science Programs (Final Report)

The Department of Energy (DOE) ensures America’s security and prosperity by addressing its energy, environmental, and nuclear challenges through transformative science and technology solutions. The DOE’s Office of Science (SC) delivers groundbreaking scientific discoveries and major scientific tools that transform our understanding of nature and advance the energy, economic, and national security of the United States. The SC’s programs advance DOE mission science across a wide range of disciplines and have developed the research infrastructure needed to remain at the forefront of scientific discovery. The DOE SC’s world-class research infrastructure — exemplified by the 28 SC scientific user facilities — provides the research community with premier observational, experimental, computational, and network capabilities. Each user facility is designed to provide unique capabilities to advance core DOE mission science for its sponsor SC program and to stimulate a rich discovery and innovation ecosystem. Research communities gather and flourish around each user facility, bringing together diverse perspectives. A hallmark of many facilities is the large population of students, postdoctoral researchers, and early-career scientists who contribute as full-fledged users. These facility staff and users collaborate over years to devise new approaches to utilizing the user facility’s core capabilities. The history of the SC user facilities has many examples of wildly inventive researchers challenging operational orthodoxy to pioneer new vistas of discovery; for example, the use of the synchrotron X-ray light sources for study of proteins and other large biological molecules. This continual reinvention of the practice of science — as users and staff forge novel approaches expressed in research workflows — unlocks new discoveries and propels scientific progress. Within this research ecosystem, the high-performance computing (HPC) and networking user facilities stewarded by SC’s Advanced Scientific Computing Research (ASCR) program play a dynamic cross-cutting role, enabling complex workflows demanding high performance data, networking, and computing solutions. The DOE SC’s three HPC user facilities and the Energy Sciences Network (ESnet) high-performance research network serve all of the SC’s programs as well as the global research community. Argonne Leadership Computing Facility (ALCF), the National Energy Research Scientific Computing Center (NERSC), and Oak Ridge Leadership Computing Facility (OLCF) conceive, build, and provide access to a range of supercomputing, advanced computing, and large-scale data-infrastructure platforms, while ESnet interconnects DOE SC research infrastructure and enables seamless exchange of scientific data. All four facilities operate testbeds to expand the frontiers of computing and networking research. Together, the ASCR facilities enterprise seeks to understand and meet the needs and requirements across SC and DOE domain science programs and priority efforts, highlighted by the formal requirements reviews (RRs) methodology. In recent years, the research communities around the SC user facilities have begun experimenting with and demanding solutions integrated with HPC and data infrastructure. This rise of integrated-science approaches is documented in many community and high-level government reports. At the dawn of the era of exascale science and the acceleration of artificial intelligence (AI) innovation, there is a broad need for integrated computational, data, and networking solutions. In response to these drivers, DOE has developed a vision for an Integrated Research Infrastructure (IRI): To empower researchers to meld DOE’s world-class research tools, infrastructure, and user facilities seamlessly and securely in novel ways to radically accelerate discovery and innovation.

42 ENGINEERING↗
DOE OSTI2026

Operating advanced scientific instruments with AI agents that learn on the job

Advanced scientific user facilities, such as next generation X-ray light sources and self-driving laboratories, are revolutionizing scientific discovery by automating routine tasks and enabling rapid experimentation and characterizations. However, these facilities must continuously evolve to support new experimental workflows, adapt to diverse user projects, and meet growing demands for more intricate instruments and experiments. This continuous development introduces significant operational complexity, necessitating a focus on usability, reproducibility, and intuitive human-instrument interaction. In this work, we explore the integration of agentic AI, powered by Large Language Models (LLMs), as a transformative tool to achieve this goal. We present our approach to developing a human-in-the-loop pipeline for operating advanced instruments including an X-ray nanoprobe beamline and an autonomous robotic station dedicated to the design and characterization of materials. Specifically, we evaluate the potential of various LLMs as trainable scientific assistants for orchestrating complex, multi-task workflows, which also include multimodal data, optimizing their performance through optional human input and iterative learning. We demonstrate the ability of AI agents to bridge the gap between advanced automation and user-friendly operation, paving the way for more adaptable and intelligent scientific facilities.

Large Language Models↗