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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Efficient machine learning interatomic potentials robust for liquid and multiple solid polymorphs of NaF and KF

Achieving atomic-level understanding of crystallization of molten salts is of importance to a wide range of technological applications. Recent work [Fan et al., Proc. Natl. Acad. Sci. USA 122, e2425702122 (2025)] revealed that crystal nucleation in molten LiF salt is a multistage process according to the molecular-dynamics (MD) simulations based on an atomic cluster expansion (ACE) machine-learning interatomic potential (MLIP). In order to understand the influence of increasing cation size on nucleation pathways and nucleation rates of molten fluoride salts, here we develop two new ACE MLIPs for NaF and KF. The two ACE MLIPs feature DFT-SCAN-level accuracy for liquid and multiple solid polymorphs over a wide temperature (0–2000 K) and pressure (0–100 GPa) range, and also reproduce well a number of experimental data for solid and liquid equilibrium properties. The efficiency of the two ACE MLIPs enable million-atom-scale or microsecond-scale MD simulations. The two general-purpose ACE MLIPs are expected to be useful for atomistic simulations for different purposes, in addition to studying crystallization of molten NaF and KF salts.

Crystal melting↗
NASA NTRS1988

Acoustic containerless experiment system: A non-contact surface tension measurement

The Acoustic Containerless Experiment System (ACES) was flown on STS 41-B in February 1984 and was scheduled to be reflown in 1986. The primary experiment that was to be conducted with the ACES module was the containerless melting and processing of a fluoride glass sample. A second experiment that was to be conducted was the verification of a non-contact surface tension measurement technique using the molten glass sample. The ACES module consisted of a three-axis acoustic positioning module that was inside an electric furnace capable of heating the system above the melting temperature of the sample. The acoustic module is able to hold the sample with acoustic forces in the center of the chamber and, in addition, has the capability of applying a modulating force on the sample along one axis of the chamber so that the molten sample or liquid drop could be driven into one of its normal oscillation modes. The acoustic module could also be adjusted so that it could place a torque on the molten drop and cause the drop to rotate. In the ACES, a modulating frequency was applied to the drop and swept through a range of frequencies that would include the n = 2 mode. A maximum amplitude of the drop oscillation would indicate when resonance was reached and from that data the surface tension could be calculated. For large viscosity samples, a second technique for measuring surface tension was developed. The results of the ACES experiment and some of the problems encountered during the actual flight of the experiment will be discussed.

Elleman, D. D.↗
NASA NTRS2004

The Processing of Airspace Concept Evaluations Using FASTE-CNS as a Pre- or Post-Simulation CNS Analysis Tool

As NASA speculates on and explores the future of aviation, the technological and physical aspects of our environment increasing become hurdles that must be overcome for success. Research into methods for overcoming some of these selected hurdles have been purposed by several NASA research partners as concepts. The task of establishing a common evaluation environment was placed on NASA's Virtual Airspace Simulation Technologies (VAST) project (sub-project of VAMS), and they responded with the development of the Airspace Concept Evaluation System (ACES). As one examines the ACES environment from a communication, navigation or surveillance (CNS) perspective, the simulation parameters are built with assumed perfection in the transactions associated with CNS. To truly evaluate these concepts in a realistic sense, the contributions/effects of CNS must be part of the ACES. NASA Glenn Research Center (GRC) has supported the Virtual Airspace Modeling and Simulation (VAMS) project through the continued development of CNS models and analysis capabilities which supports the ACES environment. NASA GRC initiated the development a communications traffic loading analysis tool, called the Future Aeronautical Sub-network Traffic Emulator for Communications, Navigation and Surveillance (FASTE-CNS), as part of this support. This tool allows for forecasting of communications load with the understanding that, there is no single, common source for loading models used to evaluate the existing and planned communications channels; and that, consensus and accuracy in the traffic load models is a very important input to the decisions being made on the acceptability of communication techniques used to fulfill the aeronautical requirements. Leveraging off the existing capabilities of the FASTE-CNS tool, GRC has called for FASTE-CNS to have the functionality to pre- and post-process the simulation runs of ACES to report on instances when traffic density, frequency congestion or aircraft spacing/distance violations have occurred. The integration of these functions require that the CNS models used to characterize these avionic system be of higher fidelity and better consistency then is present in FASTE-CNS system. This presentation will explore the capabilities of FASTE-CNS with renewed emphasis on the enhancements being added to perform these processing functions; the fidelity and reliability of CNS models necessary to make the enhancements work; and the benchmarking of FASTE-CNS results to improve confidence for the results of the new processing capabilities.

Mainger, Steve↗
NASA NTRS2008

The Interaction of the Space Shuttle Launch and Entry Suits and Sustained Weightless on Astronaut Egress Locomotion

The purpose of this study was to determine the consequences of extended periods of weightlessness during space missions on astronauts f ability to perform a simulated contingency egress while wearing either of the Launch and Entry suits immediately after space flight. In our previous lab-based study of simulated contingency egress, we found only 4 of 12 non-astronauts wearing the Launch and Entry Suit (LES) successfully completed the simulated egress. However, 4 of 4 of the previous failures (when tested wearing the LES), were then successful in completing the test wearing the Advanced Crew Escape Suit (ACES). Therefore, this study tested 21 Astronaut Volunteers wearing either the LES or ACES while performing a simulated egress on a treadmill (TM) onboard the Crew Transportation Vehicle immediately after space flight at either the Kennedy Space Center or Edwards AFB. Astronauts walked for 400 meters at 1.6m/sec with g-suit inflation level set to preflight testing levels, visor down, breathing from the suit emergency O2 supply. Metabolic, heartrate, and perceived exertion data were collected during these post-flight tests. Exactly the same preflight simulated egress tests on a TM were performed in the lab at NASA/JSC by each crewmember at L-60. Preflight testing found 2 of the 21 crewmembers were unable to complete the simulated contingency egress. Postflight, 9 crew (8 ACES, 1 LES) completed the simulated contingency egress of 400 meters at 1.6m/sec. and 12 failed to meet that standard (7 ACES, 5 LES). Preflight physiological response tests failed to identify crew capable of performing the egress vs. those who failed. However, 18 of the 21 crew did make at least 2.67 minutes into the postflight egress testing. At that point in time, heartrate was higher (P <=.20) for the failures compared to the finishers. These findings indicate that NASA fs switch to the ACES for space flight crews should be expedited.

Greenisen, M. C.↗
NASA NTRS2009

Implications of Advanced Crew Escape Suit Transpiration for the Orion Program

Human testing was conducted to more fully characterize the integrated performance of the Advanced Crew Escape Suit (ACES) with liquid cooling provide by an Individual Cooling Unit (ICU) across a broad range of environmental conditions and metabolic rates. Together with a correlation for the ACES Liquid Cooling Garment as a function of inlet temperature, metabolic rate, and crew size, a reasonably conservative correlation for core temperature was achieved for the human thermal model applied to the ACES with ICU cooling. A key observation for this correlation was accounting for transpiration of evaporated sweat through the Gortex(Registered TradeMark) liner of the ACES indicated by as much as 0.6 lbm of sweat evaporated over the course of the 1 hour test profile, most of which could not be attributed to respiration or head sweat evaporation of the crew. Historically it has been assumed that transpiration was not an important design feature of the ACES suit. The correlated human thermal model will show transpiration to be highly useful in hot survival situations for the Orion Program when adequate liquid cooling is not available.

Bue, Grant↗
NASA NTRS2009

Water Vapor Permeability of the Advanced Crew Escape Suit

Crew Exploration Vehicle (CEV) crewmembers are expected to return to earth wearing a suit similar to the current Advanced Crew Escape Suit (ACES). To ensure optimum cognitive performance, suited crewmembers must maintain their core body temperature within acceptable limits. There are currently several options for thermal maintenance in the post-landing phase. These include the current baseline, which uses an ammonia boiler, purge flow using oxygen in the suit, accessing sea water for liquid cooling garment (LCG) cooling and/or relying on the evaporative cooling capacity of the suit. These options vary significantly in mass, power, engineering and safety factors, with relying on the evaporative cooling capacity of the suit being the least difficult to implement. Data from previous studies indicates that the evaporative cooling capacity of the ACES was much higher than previously expected, but subsequent tests were performed for longer duration and higher metabolic rates to better define the water vapor permeability of the ACES. In these tests five subjects completed a series of tests performing low to moderate level exercise in order to control for a target metabolic rate while wearing the ACES in an environmentally controlled thermal chamber. Four different metabolic profiles at a constant temperature of 95 F and relative humidity of 50% were evaluated. These tests showed subjects were able to reject about twice as much heat in the permeable ACES as they were in an impermeable suit that had less thermal insulation. All of the heat rejection differential is attributed to the increased evaporation capability through the Gortex bladder of the suit.

Bue, Grant↗
NASA NTRS2015

The Advanced Composition Explorer Shock Database and Application to Particle Acceleration Theory

The theory of particle acceleration via diffusive shock acceleration (DSA) has been studied in depth by Gosling et al. (1981), van Nes et al. (1984), Mason (2000), Desai et al. (2003), Zank et al. (2006), among many others. Recently, Parker and Zank (2012, 2014) and Parker et al. (2014) using the Advanced Composition Explorer (ACE) shock database at 1 AU explored two questions: does the upstream distribution alone have enough particles to account for the accelerated downstream distribution and can the slope of the downstream accelerated spectrum be explained using DSA? As was shown in this research, diffusive shock acceleration can account for a large population of the shocks. However, Parker and Zank (2012, 2014) and Parker et al. (2014) used a subset of the larger ACE database. Recently, work has successfully been completed that allows for the entire ACE database to be considered in a larger statistical analysis. We explain DSA as it applies to single and multiple shocks and the shock criteria used in this statistical analysis. We calculate the expected injection energy via diffusive shock acceleration given upstream parameters defined from the ACE Solar Wind Electron, Proton, and Alpha Monitor (SWEPAM) data to construct the theoretical upstream distribution. We show the comparison of shock strength derived from diffusive shock acceleration theory to observations in the 50 keV to 5 MeV range from an instrument on ACE. Parameters such as shock velocity, shock obliquity, particle number, and time between shocks are considered. This study is further divided into single and multiple shock categories, with an additional emphasis on forward-forward multiple shock pairs. Finally with regard to forwardforward shock pairs, results comparing injection energies of the first shock, second shock, and second shock with previous energetic population will be given.

Parker, L. Neergaard↗
NASA NTRS2015

The Advanced Composition Explorer Shock Database and Application to Particle Acceleration Theory

The theory of particle acceleration via diffusive shock acceleration (DSA) has been studied in depth by Gosling et al. (1981), van Nes et al. (1984), Mason (2000), Desai et al. (2003), Zank et al. (2006), among many others. Recently, Parker and Zank (2012, 2014) and Parker et al. (2014) using the Advanced Composition Explorer (ACE) shock database at 1 AU explored two questions: does the upstream distribution alone have enough particles to account for the accelerated downstream distribution and can the slope of the downstream accelerated spectrum be explained using DSA? As was shown in this research, diffusive shock acceleration can account for a large population of the shocks. However, Parker and Zank (2012, 2014) and Parker et al. (2014) used a subset of the larger ACE database. Recently, work has successfully been completed that allows for the entire ACE database to be considered in a larger statistical analysis. We explain DSA as it applies to single and multiple shocks and the shock criteria used in this statistical analysis. We calculate the expected injection energy via diffusive shock acceleration given upstream parameters defined from the ACE Solar Wind Electron, Proton, and Alpha Monitor (SWEPAM) data to construct the theoretical upstream distribution. We show the comparison of shock strength derived from diffusive shock acceleration theory to observations in the 50 keV to 5 MeV range from an instrument on ACE. Parameters such as shock velocity, shock obliquity, particle number, and time between shocks are considered. This study is further divided into single and multiple shock categories, with an additional emphasis on forward-forward multiple shock pairs. Finally with regard to forward-forward shock pairs, results comparing injection energies of the first shock, second shock, and second shock with previous energetic population will be given.

Parker, L. Neergaard↗
NASA NTRS2015

Technology Advancement for Active Remote Sensing of Carbon Dioxide from Space Using the ASCENDS CarbonHawk Experiment Simulator: First Results

The ASCENDS CarbonHawk Experiment Simulator (ACES) is a newly developed lidar developed at NASA Langley Research Center and funded by NASA's Earth Science Technology Office (ESTO) Instrument Incubator Program (IIP) that seeks to advance technologies critical to measuring atmospheric column carbon dioxide (CO2) mixing ratios in support of the NASA Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) mission. The technology advancements targeted include: (1) increasing the power-aperture product to approach ASCENDS mission requirements by implementing multi-aperture telescopes and multiple co-aligned laser transmitters; (2) incorporating high-efficiency, high-power Erbium-Doped Fiber Amplifiers (EDFAs); (3) developing and incorporating a high-bandwidth, low-noise HgCdTe detector and transimpedence amplifier (TIA) subsystem capable of long-duration autonomous operation on Global Hawk aircraft, and (4) advancing algorithms for cloud and aerosol discrimination. The ACES instrument architecture is being developed for operation on high-altitude aircraft and will be directly scalable to meet the ASCENDS mission requirements. These technologies are critical towards developing not only spaceborne instruments but also their airborne simulators, with lower platform requirements for size, mass, and power, and with improved instrument performance for the ASCENDS mission. ACES transmits five laser beams: three from commercial EDFAs operating near 1.57 microns, and two from the Exelis oxygen (O2) Raman fiber laser amplifier system operating near 1.26 microns. The three EDFAs are capable of transmitting up to 10 watts average optical output power each and are seeded by compact, low noise, stable, narrow-linewidth laser sources stabilized with respect to a CO2 absorption line using a multi-pass gas absorption cell. The Integrated-Path Differential Absorption (IPDA) lidar approach is used at both wavelengths to independently measure the CO2 and O2 column number densities and retrieve the average column CO2 mixing ratio. The ACES receiver uses three fiber-coupled 17.8-cm diameter athermal telescopes. The transmitter assembly consists of five fiber-coupled laser collimators and an associated Risley prism pair for each laser to co-align the outgoing laser beams and to align them with the telescope field of view. The backscattered return signals collected by the three telescopes are combined in a fiber bundle and sent to a single low noise detector. The detector/TIA development has improved the existing detector subsystem by increasing its bandwidth to 4.7 MHz from 500 kHz and increasing the duration of autonomous, service-free operation periods from 4 hours to >24 hours. The new detector subsystem enables the utilization of higher laser modulation rates, which provides greater flexibility for implementing advanced thin-cloud discrimination algorithms as well as improving range-determination resolution and error reduction. The cloud/aerosol discrimination algorithm development by Langley and Exelis features a new suite of algorithms for the minimization/elimination of bias errors in the return signal induced by the presence of intervening thin clouds. Multiple laser modulation schemes are being tested in an effort to significantly mitigate the effects of thin clouds on the retrieved CO2 column amounts. Full instrument development concluded in the spring of 2014. After ground range tests of the instrument, ACES successfully completed six test flights on the Langley Hu-25 aircraft in July, 2014, and recorded data at multiple altitudes over land and ocean surfaces with and without intervening clouds. Preliminary results from these test flights will be presented in this paper.

Obland, Michael D.↗
NASA NTRS2018

Characterization of On-Orbit GPS Transmit Antenna Patterns for Space Users

The GPS Antenna Characterization Experiment (GPS ACE) has made extensive observations of GPS L1 signals received at geosynchronous (GEO) altitude, with the objective of developing comprehensive models of the signal levels and signal performance in the GPS transmit antenna side lobes. The experiment was originally motivated by the fact that data on the characteristics and performance of the GPS signals available in GEO and other high Earth orbits was limited. The lack of knowledge of the power and accuracy of the side lobe signals on-orbit added risk to missions seeking to employ the side lobes to meet navigation requirements or improve performance. The GPS ACE Project lled that knowledge gap through a collaboration between The Aerospace Corporation and NASA Goddard Space Fight Center to collect and analyze observations from GPS side lobe transmissions to a satellite at GEO using a highly-sensitive GPS receiver installed at the ground station. The GPS ACE architecture has been in place collecting observations of the GPS constellation with extreme sensitivity for several years. This sensitivity combined with around-the-clock, all-in-view processing enabled full azimuthal coverage of the GPS transmit gain patterns over time to angles beyond 90 degrees off-boresight. Results discussed in this paper include the reconstructed transmit gain patterns, with comparisons to available pre-fight gain measurements from the GPS vehicle contractors. For GPS blocks with extensive ground measurements, the GPS ACE results show remarkable agreement with ground based measurements. For blocks without extensive ground measurements, the GPS ACE results provide the only existing assessments of the full transmit gain patterns. The paper also includes results of pseudorange deviation analysis to assess systematic errors associated with GPS side lobe signals.

space↗
NASA NTRS2018

Characterization of On-Orbit GPS Transmit Antenna Patterns for Space Users

The GPS Antenna Characterization Experiment (GPS ACE) has made extensive observations of GPS L1 signals received at geosynchronous (GEO) altitude, with the objective of developing comprehensive models of the signal levels and signal performance in the GPS transmit antenna side lobes. The experiment was originally motivated by the fact that data on the characteristics and performance of the GPS signals available in GEO and other high Earth orbits was limited. The lack of knowledge of the power and accuracy of the side lobe signals on-orbit added risk to missions seeking to employ the side lobes to meet navigation requirements or improve performance. The GPS ACE Project lled that knowledge gap through a collaboration between The Aerospace Corporation and NASA Goddard Space Fight Center to collect and analyze observations from GPS side lobe transmissions to a satellite at GEO using a highly-sensitive GPS receiver installed at the ground station. The GPS ACE architecture has been in place collecting observations of the GPS constellation with extreme sensitivity for several years. This sensitivity combined with around-the-clock, all-in-view processing enabled full azimuthal coverage of the GPS transmit gain patterns over time to angles beyond 90 degrees o -boresight. Results discussed in this paper include the reconstructed transmit gain patterns, with comparisons to available pre-fight gain measurements from the GPS vehicle contractors. For GPS blocks with extensive ground measurements, the GPS ACE results show remarkable agreement with ground based measurements. For blocks without extensive ground measurements, the GPS ACE results provide the only existing assessments of the full transmit gain patterns. The paper also includes results of pseudorange deviation analysis to assess systematic errors associated with GPS side lobe signals.

Donaldson, Jennifer E.↗
NASA NTRS2018

Advancements Towards Active Remote Sensing of CO2 from Space Using Intensity-Modulated, Continuous-Wave (IM-CW) Lidar

The Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) CarbonHawk Experiment Simulator (ACES) is a NASA Langley Research Center instrument funded by NASA’s Science Mission Directorate that seeks to advance technologies critical to measuring atmospheric column carbon dioxide (CO2) mixing ratios in support of the NASA ASCENDS mission. The ACES instrument, an Intensity-Modulated Continuous-Wave (IM-CW) lidar, was designed for high-altitude aircraft operations and can be directly applied to space instrumentation to meet the ASCENDS mission requirements. The ACES design demonstrates advanced technologies critical for developing an airborne simulator and spaceborne instrument with lower platform consumption of size, mass, and power, and with improved performance. ACES recently flew on the NASA DC-8 aircraft during the 2017 NASA ASCENDS/Arctic-Boreal Vulnerability Experiment (ABoVE) airborne measurement campaign to test ASCENDS-related technologies in the challenging Arctic environment. Data were collected over a wide variety of surface reflectivities, terrain, and atmospheric conditions during the campaign’s 8 research flights. ACES also flew during the 2017 and 2018 Atmospheric Carbon and Transport – America (ACT-America) Earth Venture Suborbital -2 (EVS-2) campaigns along with the primary ACT-America CO2 lidar, Harris Corporation’s Multi-Frequency Fiber Laser Lidar (MFLL). Regional CO2 distributions of the lower atmosphere were observed from the C-130 aircraft during the ACT-America campaigns in support of ACT-America’s science objectives. The airborne lidars provide unique data that complement the more traditional in situ sensors. This presentation shows the applications of CO2 lidars in meeting these science needs from airborne platforms and an eventual spacecraft.

Obland, Michael D.↗
NASA NTRS2020

Characterization of On-Orbit GPS Transmit Antenna Patterns for Space Users

The GPS Antenna Characterization Experiment (GPS ACE) has made extensive observations of GPS L1 signals received at geosynchronous (GEO) altitude, with the objective of developing comprehensive models of the signal levels and signal performance in the GPS transmit antenna side lobes. The experiment was originally motivated by the fact that data on the characteristics and performance of the GPS signals available in GEO and other high Earth orbits was limited. The lack of knowledge of the power and accuracy of the side lobe signals on-orbit added risk to missions seeking to employ the side lobes to meet navigation requirements or improve performance. The GPS ACE Project lled that knowledge gap through a collaboration between The Aerospace Corporation and NASA Goddard Space Fight Center to collect and analyze observations from GPS side lobe transmissions to a satellite at GEO using a highly-sensitive GPS receiver installed at the ground station. The GPS ACE architecture has been in place collecting observations of the GPS constellation with extreme sensitivity for several years. This sensitivity combined with around-the-clock, all-in-view processing enabled full azimuthal coverage of the GPS transmit gain patterns over time to angles beyond 90 degrees o -boresight. Results discussed in this paper include the reconstructed transmit gain patterns, with comparisons to available pre-fight gain measurements from the GPS vehicle contractors. For GPS blocks with extensive ground measurements, the GPS ACE results show remarkable agreement with ground based measurements. For blocks without extensive ground measurements, the GPS ACE results provide the only existing assessments of the full transmit gain patterns. The paper also includes results of pseudorange deviation analysis to assess systematic errors associated with GPS side lobe signals.

Jennifer E Donaldson↗
DOE OSTI2024

Permutation-adapted complete and independent basis for atomic cluster expansion descriptors

Atomic cluster expansion (ACE) methods provide a systematic way to describe particle local environments of arbitrary body order. For practical applications it is often required that the basis of cluster functions be symmetrized with respect to rotations and permutations. Existing methodologies yield sets of symmetrized functions that are over-complete. These methodologies thus require an additional numerical procedure, such as singular value decomposition (SVD), to eliminate redundant functions. In this work, it is shown that analytical linear relationships for subsets of cluster functions may be derived using recursion and permutation properties of generalized Wigner symbols. From these relationships, subsets (blocks) of cluster functions can be selected such that, within each block, functions are guaranteed to be linearly independent. It is conjectured that this block-wise independent set of permutation-adapted rotation and permutation invariant (PA-RPI) functions forms a complete, independent basis for ACE. Along with the first analytical proofs of block-wise linear dependence of ACE cluster functions and other theoretical arguments, numerical results are offered to demonstrate this. The utility of the method is demonstrated in the development of an ACE interatomic potential for tantalum. Using the new basis functions in combination with Bayesian compressive sensing sparse regression, some high degree descriptors are observed to persist and help achieve high-accuracy models.

Angular momentum↗
DOE OSTI2026

Dual Context: Leveraging Structured Application Context for Code Generation and Runtime Feature Activation via Chat Interfaces

Integrating artificial intelligence (AI) capabilities into software applications typically involves two common paths. For developers, AI assists in generating and documenting source code and other related software engineering efforts. For users, AI assists them through question-and-answer exchanges via chatbots. Both approaches have their value, but neither effectively leverages the modularity of component-based architectures that modern web application frameworks offer. We implement a proof of concept within a centralized suite of applications used for the Atmospheric Radiation Measurement (ARM) Data Center Operational Tools, where we introduce a third integration path through the ARM Context Engine (ACE). ACE is a context driven system that uses structured contextual specifications to enable Large Language Models (LLMs) to render interactive and feature-rich user interface (UI) components directly within chat responses, alongside or in place of conventional text outputs. These specifications serve two important purposes across what we call code context and UI context. Code context provides AI-assisted development tools with structured application knowledge beyond raw code, including component relationships, architectural patterns and schematic information, enabling the generation of consistent, well-structured code. UI context defines the rules for enabling and rendering component features at runtime based on the user's natural language input, allowing end users to activate capabilities such as data export, filtering, and pagination within chat responses, without requiring code changes or redeployment. We demonstrate, through a comparative evaluation against general-purpose AI chatbots, that context-driven component rendering provides interactive capabilities that text-based responses cannot replicate, including deterministic component behavior, application-consistent design language, and on-demand feature activation. A development effort comparison further shows that features that traditionally require multi-step development cycles can be activated with a single naturallanguage request. In this ongoing work, we present ACE as an emerging approach to AI integration that positions modular, well-documented software architecture as the foundation for AI-ready applications. ACE treats context as a shared resource across both development and user-facing AI, bringing cohesion to conventionally disconnected efforts, bridging developer tooling and end-user capabilities within a single framework.

Tadimeti, Vijay [ORNL]↗
DOE OSTI2024

Methods for Quantitative Thermal Analysis of Lithium Solid-State and Beyond Battery Safety

The use of differential scanning calorimetry (DSC) to measure the thermal behavior of individual components and electrolyte/electrode combinations is common. However, here we focus on DSC tests on an anode, cathode, and electrolyte (ACE) component combination over a temperature range that includes many of the phase transitions and key reactions (i.e., to 500 °C) that contribute to thermal runaway. This method can help quantify the complex reaction network in a full cell, thereby informing potential safety issues. Here, we used DSC heat flow data from a solid-state Li 0.43 CoO 2 +C+PVDF | LLZO | Li metal ACE sample and its components to quantify key factors affecting results. We focused on three areas: (1) ACE sample preparation and assembly in DSC pans, (2) DSC measurement parameters, and (3) heat flow analysis. Key points include the choice of component ratios (e.g., commercially relevant N:P capacity ratio), the importance of conductive carbon and binder, type of pan used, DSC ramp rate, and integration method used when dealing with broad and overlapping exothermic peaks. This work deepens the scientific basis and best practices for obtaining heat flow data from ACE samples for early-stage evaluation of solid-state and beyond battery safety.

25 ENERGY STORAGE↗
DOE OSTI2026

Cyote-attack Chain Estimator

Attack Chain Estimator (ACE) Application Overview The Attack Chain Estimator (ACE) Application is a sophisticated tool designed for the ingestion, classification, sequencing, and enrichment of cybersecurity threat reports. This application leverages advanced machine learning models and extensive historical data to provide comprehensive insights into cyber threats, specifically targeting Industrial Control Systems (ICS). Purpose The primary functions of the ACE Application include: Ingestion of Cybersecurity Threat Reporting: Capable of ingesting text-based threat reports in markdown or text file format. Supports ingestion of structured data from other sources in STIX/JSON format. Classification of Report’s Text-Based Events: Utilizes a DeBERTa classifier, specifically trained on cybersecurity data, to map the events to MITRE ATT&CK for ICS Tactics and Techniques. Classification is performed using multiple Jupyter notebooks and machine learning workflows hosted as FastAPI microservices: regex_data deberta_base_35_train_hft_classifier_mlflow.ipynb hft_regex_classifier_mlflow.ipynb param_train_hft_classifier_mlflow.ipynb regex_tactic_tech.ipynb Ordering of Tactics, Techniques, and Observable Events: Sequences the identified tactics, techniques, and events to form a coherent attack chain. Enrichment with Historical Attack Chain Details: Enhances the attack chain with details from historical attacks using a Markov model developed from CyOTE Precursor Analysis Report data. The Markov model is available as a FastAPI endpoint for seamless integration. Enrichment with Adversary Emulation Capabilities Data: Integrates adversary emulation capabilities data using MITRE Caldera for OT adversary abilities UUIDs. Export of Output Files: Provides options to export the enriched attack chain in JSON or CSV formats. Routing of Output to Other Applications: Facilitates routing of output to various platforms and applications, including: Threat Intelligence Platforms COREII Scout for Threat Intelligence Analysis COREII Modeling and Simulation for Adversary Emulation Technical Description The ACE Application is an advanced cybersecurity tool designed to provide detailed threat analysis and sequence generation. It is built on a robust architecture that integrates natural language processing, machine learning, and historical data modeling. Key Components: Data Ingestion Module: Handles the input of threat reports and data from various formats, ensuring flexibility in data sources. Classification Engine: Employs DeBERTa-based classifiers hosted as FastAPI microservices to analyze and classify threat report events in accordance with the MITRE ATT&CK framework for ICS. Sequence Generator: Orders the classified events into a logical attack chain, providing clear insight into the sequence of tactics and techniques used in the threat. Enrichment Engine: Integrates historical data and adversary emulation capabilities to enhance the attack chain with valuable context and additional details. The historical data enrichment is powered by a Markov model, which is available as a FastAPI endpoint. Export and Routing Module: Facilitates the export of the enriched attack chain in multiple formats and routes the output to designated applications for further analysis or emulation.

Paul, Tony [Idaho National Laboratory (INL), Idaho↗
NASA NTRS1989

The Advanced Composition Explorer

The Advanced Composition Explorer (ACE) was recently selected as one of two new Explorer-class missions to be developed for launch during the mid-1990's. ACE will observe particles of solar, interplanetary, interstellar, and galactic origins, spanning the energy range from that of the solar wind (approx. 1 keV/nucleon) to galactic cosmic ray energies (several hundred MeV/nucleon). Definitive studies will be made of the abundance of nearly all isotopes from H to Zn (1 less than or = Z less than or = 30), with exploratory isotope studies extending to Zr (Z = 40). To accomplish this, the ACE payload includes six high-resolution spectrometers, each designed to provide the optimum charge, mass, or charge-state resolution in its particular energy range, and each having a geometry factor optimized for the expected flux levels, so as to provide a collecting power a factor of 10 to 1000 times greater than previous or planned experiments. The payload also includes several instruments of standard design that will monitor solar wind and magnetic field conditions and energetic H, He, and electron fluxes. The scientific objectives, instrumentation, spacecraft, and mission approach that were defined for ACE during the Phase-A study period are summarized.

Stone, E. C.↗