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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Evidence for Two Excited Ω − Hyperons

Using e + e − collision data corresponding to an integrated luminosity of 19 fb − 1 collected by the BESIII detector at center-of-mass energies ranging from 4.13 to 4.70 GeV, we report the first evidence for a new excited Ω − hyperon, the Ω ( 2109 ) − , through the process e + e − → Ω ( 2109 ) − Ω ¯ + + c . c . with a significance of 4.1 σ . The mass and width of Ω ( 2109 ) − are measured to be 2108.5 ± 5.2 stat ± 0.9 syst MeV / c 2 and 18.3 ± 16.4 stat ± 5.7 syst MeV , respectively. We also present evidence for a new production mechanism for the previously identified Ω ( 2012 ) − via the process e + e − → Ω ( 2012 ) − Ω ¯ + + c . c . with a significance of 3.5 σ . Published by the American Physical Society 2025

Ablikim, M.↗
DOE OSTI2024

Search for the e + e − → ϕ χ c 1 ( 3872 ) process at BESIII

Based on 368.5 p b − 1 of e + e − collision data collected at center-of-mass energies 4.914 and 4.946 GeV by the BESIII detector, the e + e − → ϕ χ c 1 ( 3872 ) process is searched for the first time. No significant signal is observed and the upper limits at the 90% confidence level on the product of the Born cross section σ ( e + e − → ϕ χ c 1 ( 3872 ) ) and the branching fraction B [ χ c 1 ( 3872 ) → π + π − J / ψ ] at 4.914 and 4.946 GeV are set to be 0.85 and 0.96 pb, respectively. These measurements provide useful information for the production of the χ c 1 ( 3872 ) at e + e − colliders and deepen our understanding about the nature of this particle. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2026

A Survey on the Expanding Scope and Interdisciplinary Opportunities for Processing-in-Memory Techniques

Processing-in-Memory (PIM) is emerging as a practical path to overcome the limitations of traditional von Neumann architectures. At its core, PIM systems implement computing primitives such as logic operations and multiply-accumulate acceleration through compute-in-memory, near-memory processing, or hybrid designs. The role of memory cells varies widely across technologies, acting as inputs, outputs, or analog accumulators through bit-lines and sense amplifiers. This diversity creates trade-offs in precision, bandwidth, latency, and programmability, making it difficult to build a unified understanding on the progress of the field. In this survey, we organize recent advances of PIM into three areas. First, we discuss the progress on the architectural optimizations of PIM and its integration with both DRAM and emerging non-volatile memories. Second, we examine how PIM is being used to accelerate key computing domains, including generative AI workloads and high-performance kernels, along with new approaches. Third, we highlight the growing adoption of PIM in computational sciences, where it is being applied to solve interdisciplinary problems such as genome analysis, mRNA quantification, mass spectrometry, quantum circuit simulation, wave modeling, and secure computation. Finally, we synthesize the major challenges that continue to slow PIM adoption, including manufacturing constraints, power delivery, thermal reliability, data consistency, runtime and memory-management coordination, and the difficulty of building portable software abstractions without sacrificing commercial viability. This work provides an updated, structured perspective on PIM’s potential across computing and computational sciences and the barriers that must be solved for it to reach its full impact.

Asifuzzaman, Kazi [Oak Ridge National Laboratory (↗
DOE OSTI2025

CryoDRGN-AI: neural ab initio reconstruction of challenging cryo-EM and cryo-ET datasets

Proteins and other biomolecules form dynamic macromolecular machines that are tightly orchestrated to move, bind, and perform chemistry. Cryo-electron microscopy (cryo-EM) and cryo-electron tomography (cryo-ET) can access the intrinsic heterogeneity of these complexes and are therefore key tools for understanding their function. However, 3D reconstruction of the collected imaging data presents a challenging computational problem, especially without any starting information, a setting termed ab initio reconstruction. Here, in this study, we introduce cryoDRGN-AI, a method leveraging an expressive neural representation and combining an exhaustive search strategy with gradient-based optimization to process challenging heterogeneous datasets. Using cryoDRGN-AI, we reveal new conformational states in large datasets, reconstruct previously unresolved motions from unfiltered datasets, and demonstrate ab initio reconstruction of biomolecular complexes from in situ data. With this expressive and scalable model for structure determination, we hope to unlock the full potential of cryo-EM and cryo-ET as a high-throughput tool for structural biology and discovery.

Levy, Axel [Stanford Univ., CA (United States); SL↗
DOE OSTI2021

Transforming Energy through Computational Science: Computing for Clean Energy

This fact sheet discusses the opportunity space for NREL's computational science capabilities to address national clean energy objectives. Achieving a carbon-free power sector by 2035 as a step towards a decarbonized U.S. energy economy in 2050 will require major advances in power generation, autonomous energy systems, transportation, and buildings/communities. Development of integrated modeling approaches for complex energy systems will be essential for deployment. Success requires developments in optimization and control theory, complemented by machine learning (ML) and artificial intelligence (AI), all of which in turn need targeted investments in breadth and scale of computing. This document defines an opportunity space where: embracing computing can link established research and development (R&D) to a decarbonization agenda; pursuing emerging approaches can accelerate the pace of technology advancement across the portfolio; and leading by example could reduce the carbon footprint of computing worldwide.

advanced computing↗
NASA NTRS2011

NASA A-Train and Terra Observations of the 2010 Russian Wildfires

Wildfires raged throughout western Russia and parts of Eastern Europe during a persistent heat wave in the summer of 2010. Anomalously high surface temperatures (35 - 41 C) and low relative humidity (9 - 25 %) from mid- June to mid-August 2010 shown by analysis of radiosonde data from multiple sites in western Russia were ideal conditions for the wildfires to thrive. Measurements of outgoing longwave radiation (OLR) from the Atmospheric Infrared Sounder (AIRS) over western Russian indicate persistent subsidence during the heat wave. Daily three-day back-trajectories initiated over Moscow reveal a persistent anticyclonic circulation for 18 days in August, coincident with the most intense period of fire activity observed by Moderate Resolution Imaging Spectroradiometer (MODIS). This unfortunate meteorological coincidence allowed transport of polluted air from the region of intense fires to Moscow and the surrounding area. We demonstrate that the 2010 Russian wildfires are unique in the record of observations obtained by remote-sensing instruments on-board NASA satellites: Aura and Aqua (part of the A-Train Constellation) and Terra. Analysis of the distribution of MODIS fire products and aerosol optical thickness (AOT), UV aerosol index (AI) and single-scattering albedo (SSA) from Aura's Ozone Monitoring Instrument (OMI), and total column carbon monoxide (CO) from Aqua s Atmospheric Infrared Sounder (AIRS) show that the region in the center of western Russia surrounding Moscow (52-58 deg N, 33 -43 deg E) is most severely impacted by wildfire emissions. Over this area, AIRS CO, OMI AI, and MODIS AOT are significantly enhanced relative to the historical satellite record during the first 18 days in August when the anti-cyclonic circulation persisted. By mid-August, the anti-cyclonic circulation was replaced with westerly transport over Moscow and vicinity. The heat wave

Witte, J. C.↗
DOE OSTI2024

First measurements of the absolute branching fraction of Λ c ( 2625 ) + → Λ c + π + π − and upper limit on Λ c ( 2595 ) + → Λ c + π + π −

The absolute branching fraction of the decay Λ c ( 2625 ) + → Λ c + π + π − is measured for the first time to be ( 50.2 ± 5.7 stat ± 3.5 syst ) % with 368.48 pb − 1 of e + e − collision data collected by the BESIII detector at the center-of-mass energies of s = 4.918 and 4.950 GeV. Although the central value of the result is lower than the theoretical prediction of 67%, obtained from isospin symmetry, they are consistent taking the uncertainties into account. This is the first absolute branching fraction measurement for Λ c ( 2625 ) + since it was found. This measurement is necessary to obtain the coupling constants for the transitions between s -wave and p -wave charmed baryons in heavy hadron chiral perturbation theory. In addition, we search for the decay Λ c ( 2595 ) + → Λ c + π + π − . No significant signal is observed, and the upper limit on its branching fraction is determined to be 85.0% at the 90% confidence level. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2024

Observation of D → a 0 ( 980 ) π in the decays D 0 → π + π − η and D + → π + π 0 η

We report the first amplitude analyses of the decays D 0 → π + π − η and D + → π + π 0 η using a data sample taken with the BESIII detector at the center-of-mass energy of 3773 MeV, corresponding to an integrated luminosity of 7.9 fb − 1 . The contribution from the process D 0 ( + ) → a 0 ( 980 ) + π − ( 0 ) is significantly larger than the D 0 ( + ) → a 0 ( 980 ) − ( 0 ) π + contribution. The ratios B ( D 0 → a 0 ( 980 ) + π − ) / B ( D 0 → a 0 ( 980 ) − π + ) and B ( D + → a 0 ( 980 ) + π 0 ) / B ( D + → a 0 ( 980 ) 0 π + ) are measured to be 7.5 − 0.8 stat + 2.5 ± 1.7 syst and 2.6 ± 0.6 stat ± 0.3 syst , respectively. The measured D 0 ratio disagrees with the theoretical predictions by orders of magnitudes, thus implying a substantial contribution from final-state interactions. Published by the American Physical Society 2024

Ablikim, M.↗
NASA NTRS1994

An operations and command systems for the extreme ultraviolet explorer

About 40% of the budget of a scientific spacecraft mission is usually consumed by Mission Operations & Data Analysis (MO&DA) with MO driving these costs. In the current practice, MO is separated from spacecraft design and comes in focus relatively late in the mission life cycle. As a result, spacecraft may be designed that are very difficult to operate. NASA centers have extensive MO expertise but often lessons learned in one mission are not exploited for other parallel or future missions. A significant reduction of MO costs is essential to ensure a continuing and growing access to space for the scientific community. We are addressing some of these issues with a highly automated payload operations and command system for an existing mission, the Extreme Ultraviolet Explorer (EUVE). EUVE is currently operated jointly by the Goddard Space Flight Center (GSFC), responsible for spacecraft operations, and the Center for Extreme Ultraviolet Astrophysics (CEA) of the University of California, Berkeley, which controls the telescopes and scientific instruments aboard the satellite. The new automated system is being developed by a team including personnel from the NASA Ames Research Center (ARC), the Jet Propulsion Laboratory (JPL) and the Center for EUV Astrophysics (CEA). An important goal of the project is to provide AI-based technology that can be easily operated by nonspecialists in AI. Another important goal is the reusability of the techniques for other missions. Models of the EUVE spacecraft need to be built both for planning/scheduling and for monitoring. In both cases, our modeling tools allow the assembly of a spacecraft model from separate sub-models of the various spacecraft subsystems. These sub-models are reusable; therefore, building mission operations systems for another small satellite mission will require choosing pre-existing modules, reparametrizing them with respect to the actual satellite telemetry information, and reassembling them in a new model. We briefly describe the EUVE mission and indicate why it is particularly suitable for the task. Then we briefly outline our current work in mission planning/scheduling and spacecraft and instrument health monitoring.

Muscettola, Nicola↗
DOE OSTI2022

Research Trends and Applications of PMUs

This work is a survey of current trends in applications of PMUs. PMUs have the potential to solve major problems in the areas of power system estimation, protection, and stability. A variety of methods are being used for these purposes, including statistical techniques, mathematical transformations, probability, and AI. The results produced by the techniques reviewed in this work are promising, but there is work to be performed in the context of implementation and standardization. As the smart grid initiative continues to advance, the number of intelligent devices monitoring the power grid continues to increase. PMUs are at the center of this initiative, and as a result, each year more PMUs are deployed across the grid. Since their introduction, myriad solutions based on PMU-technology have been suggested. The high sampling rates and synchronized measurements provided by PMUs are expected to drive significant advancements across multiple fields, such as the protection, estimation, and control of the power grid. This work offers a review of contemporary research trends and applications of PMU technology. Most solutions presented in this work were published in the last five years, and techniques showing potential for significant impact are highlighted in greater detail. Being a relatively new technology, there are several issues that must be addressed before PMU-based solutions can be successfully implemented. This survey found that key areas where improvements are needed include the establishment of PMU-observability, data processing algorithms, the handling of heterogeneous sampling rates, and the minimization of the investment in infrastructure for PMU communication. Solutions based on Bayesian estimation, as well as those having a distributed architectures, show great promise. The material presented in this document is tailored to both new researchers entering this field and experienced researchers wishing to become acquainted with emerging trends.

42 ENGINEERING↗
NASA NTRSDate not supplied

Developing Open-Source Training Materials for AI/ML and Space Biological Sciences Using NASA Cloud-Based Data

Artificial Intelligence (AI) and Machine Learning (ML) has gained significant traction in the biological and biomedical research fields in the last two decades, in part thanks to an increasing culture of open data sharing and reuse. Due to its capability for identifying complex relationships and patterns, AI/ML methodology is particularly well suited to recognize and predict biological patterns from high-dimensional next-generation sequencing data (e.g. whole genome sequencing, transcriptomic sequencing), as well as from biological or medical imaging data (e.g. microscopy, computed tomography, ultrasound, magnetic resonance imaging, radiography). These methodologies hold particular promise for space biosciences research and automated space health monitoring systems. However, there are many key considerations for properly training, validating, and testing a machine learning model in biological research or clinical application. Even with the positive culture of Open Science and data sharing, inexperienced researchers working quickly without proper checks can produce models that perform poorly outside of the immediate training dataset. Lessons learned from biological AI/ML research indicate that Open Science principles such as data sharing and open-source code must go hand-in-hand with publicly available, high-quality training curricula in best practices, with modules centered on real-life scientific use cases and data so future AI/ML practitioners gain experience on real problems. Here we present the development of open-source training materials for AI/ML and space biosciences, as part of the NASA Transform to Open Science Training (TOPST) initiative. We develop 4 independent training programs, focused on the following topics: 1) Fundamentals of Machine Learning and Space Biosciences Domain, 2) Open Science, Artificial Intelligence, and Ethical Best Practices for Data Sharing and Analysis, 3) Using AI/ML Classification to Identify Gene Networks Affected By Space Exposure in Mouse Liver, and 4) Using Neural Networks to Find DNA Damage Patterns in Immune Cells after Radiation. All programs leverage cloud-based NASA biological datasets. The curriculum we present will enable worldwide access to training in AI/ML and scientific analysis.

James Andrew Casaletto↗
DOE OSTI2024

Search for D 0 → K − η e + ν e , D + → K S 0 η e + ν e and D + → η η e + ν e decays

By analyzing e + e − annihilation data corresponding to an integrated luminosity of 7.93 fb − 1 , collected at the center-of-mass energy of 3.773 GeV with the BESIII detector, we search for the semileptonic decays D 0 → K − η e + ν e , D + → K S 0 η e + ν e and D + → η η e + ν e for the first time. We present evidence for D 0 → K − η e + ν e with a significance of 3.3 σ . The branching fraction of D 0 → K − η e + ν e is measured to be ( 0.8 4 − 0.34 + 0.29 ± 0.22 ) × 10 − 4 . No significant signals are observed for the decays D + → K S 0 η e + ν e and D + → η η e + ν e and we set the upper limits on their branching fractions. Published by the American Physical Society 2024

Ablikim, M.↗
NASA NTRSDate not supplied

Use of the SPoRT Stoplight Product to Support NWS Decision Support Services

The National Weather Service Forecast Offices (NWSFOs) use many weather tools and observational datasets to provide support for critical decision-making by core partners such as public safety officials, emergency managers, and first responders. These core partners who need weather decision support services (DSS) for outdoor events require up-to-the-minute weather information to ensure the safety and protection of attendees and workers. Storms and lightning, potentially deadly, pose a significant threat during outdoor events and are among the weather phenomena frequently cited as a DSS requirement. According to the National Lightning Safety Council, from 2014 up to August 2024, lightning resulted in 222 fatalities in the U.S. For outdoor events with hundreds to thousands of attendees, having the right tools to detect and monitor lightning activity is of utmost importance to protect lives. Common guidelines for lightning safety include moving inside a substantial structure at the first sight of threatening skies or the first sound of thunder, and waiting 30 minutes after the last lightning flash or thunder before returning outside. Using this guidance as a framework, scientists at the NASA Short-term Prediction Research and Transition (SPoRT) center have developed the Geostationary Lightning Mapper (GLM) Stoplight tool. This experimental tool uses the GLM Flash Extent Density imagery to display the location and recency of lightning flashes. To simplify interpretation, these lightning pixels are color-coded in 10-minute bins, ranging from red (lightning detected 0 to 10 minutes ago) to yellow (10 to 20 minutes ago) to green (20 to 30 minutes ago). The Stoplight tool also allows users to place markers at the location of outdoor events with range rings around the location to help in assessing the location and relative age of lightning flashes near and upstream of the event. The goal is to help NWS forecasters provide core partners with the necessary information to make the best decisions possible. While the Stoplight tool is experimental, forecasters at NWSFO Raleigh, NC, have periodically used the Stoplight guidance to evaluate its utility within NWS DSS. This presentation will discuss how the Stoplight tool was successfully used for DSS for four outdoor events in central NC in 2023 and 2024. Future improvements to this tool, including the addition of AI applications and the merging of ground-based lightning data with GLM data, will be reviewed.

Gail Hartfield↗
NASA NTRS1999

Autonomous Formation Flying from Ground to Flight

The cost of on-orbit operations remains a significant and increasingly visible concern in the support of satellite missions. Headway has been made in automating some ground operations; however, increased mission complexity and more precise orbital constraints have compelled continuing human involvement in mission design and maneuver planning operations. AI Solutions, Inc. in cooperation with the National Aeronautics and Space Administration's (NASA) Goddard Space Flight Center (GSFC) has tackled these more complex problems through the development of AutoCon as a tool for an automated solution. NASA is using AutoCon to automate the maneuver planning for the Earth Orbiter-1 (EO-1) mission. AutoCon was developed originally as a ground system tool. The EO-1 mission will be using a scaled version of AutoCon on-board the EO-1 satellite to command orbit adjustment maneuvers. The flight version of AutoCon plans maneuvers based on formation flying algorithms developed by GSFC, JPL, and other industry partners. In its fully autonomous mode, an AutoCon planned maneuver will be executed on-board the satellite without intervention from the ground. This paper describes how AutoCon automates maneuver planning for the formation flying constraints of the EO-1 mission. AutoCon was modified in a number of ways to automate the maneuver planning on-board the satellite. This paper describes how the interface and functionality of AutoCon were modified to support the on-board system. A significant component of this modification was the implementation of a data smoother, based on a Kalman filter, that ensures that the spacecraft states estimated by an on-board GPS receiver are as accurate as possible for maneuver planning. This paper also presents the methodology use to scale the AutoCon functionality to fit and execute on the flight hardware. This paper also presents the modes built that allow the incremental phasing in of autonomy. New technologies for autonomous operations are usually received with significant, and probably appropriate trepidation. A number of safeguards have been designed in both AutoCon and the interfacing systems to alleviate the potential of mission-impacting anomalies from the on-board autonomous system. This paper describes the error checking, input data integrity validation and limits set on maneuvers in AutoCon and the on-board system.

Chapman, Keith B.↗
NASA NTRS1993

Space Shuttle main engine OPAD: The search for a hardware enhanced plume

The process of applying spectroscopy to the Space Shuttle Main Engine (SSME) for plume diagnostics, as it exists today, originated at Marshall Space Flight Center in Huntsville, Alabama, and its implementation was assured largely through the efforts of Sverdrup AEDC, in Tullahoma, Tennessee. This team continues to lead and guide efforts in the plume diagnostics arena. The process, Optical Plume Anomaly Detection (OPAD), formed the basis for various activities in the development of ground-based systems as well as the development of in-flight plume spectroscopy. OPAD currently provides and will continue to provide valuable information relative to future systems definitions, instrumentation development, code validation, and data diagnostic processing. OPAD is based on the detection of anomalous atomic and molecular species in the SSME plume using two complete, stand-alone optical spectrometers. To-date OPAD has acquired data on 44 test firings of the SSME at the Technology Test Bed (TTB) at MSFC. The purpose of this paper will be to provide an introduction to the OPAD system by discussing the process of obtaining data as well as the methods of examining and interpreting the data. It will encompass such issues as selection of instrumentation correlation of data to nominal engine operation, investigation of SSME component erosion via OPAD spectral data, necessity and benefits of plume seeding, application of artificial intelligence (AI) techniques to data analysis, and the present status of efforts to quantify specie erosion utilizing standard plume and chemistry codes as well as radiative models currently under development.

Powers, W. T.↗
DOE OSTI2024

Search for X ( 3872 ) → π 0 π 0 χ c 1 , 2

Using 10.1 fb − 1 of e + e − collision data collected by the BESIII detector with center-of-mass energies between 4.15 GeV and 4.30 GeV, we search for the decays X ( 3872 ) → π 0 π 0 χ c 1 , 2 , where the X ( 3872 ) is produced in e + e − → γ X ( 3872 ) . No evidence above 3 σ is found for either decay. Upper limits at the 90% CL on the branching fractions of X ( 3872 ) → π 0 π 0 χ c 1 , 2 normalized to the branching fraction of X ( 3872 ) → π + π − J / ψ are set to be B ( X ( 3872 ) → π 0 π 0 χ c 1 ) / B ( X ( 3872 ) → π + π − J / ψ ) < 1.1 and B ( X ( 3872 ) → π 0 π 0 χ c 2 ) / B ( X ( 3872 ) → π + π − J / ψ ) < 0.5 , taking into account both statistical and systematic uncertainties. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Observation of the singly Cabibbo-suppressed decay Λ c + → p π 0

Utilizing 4.5 fb − 1 of e + e − annihilation data collected with the BESIII detector at the BEPCII collider at center-of-mass energies between 4.600 and 4.699 GeV, the first observation of the singly Cabibbo-suppressed decay Λ c + → p π 0 is presented, with a statistical significance of 5.4 σ . The ratio of the branching fractions of Λ c + → p π 0 and Λ c + → p η is measured as B ( Λ c + → p π 0 ) / B ( Λ c + → p η ) = ( 0.120 ± 0.02 6 stat ± 0.00 7 syst ) . This result resolves the longstanding discrepancy between earlier experimental searches, providing both a decisive conclusion and valuable input for QCD-inspired theoretical models. A sophisticated deep learning approach using a Transformer-based architecture is employed to distinguish the signal from the prevalent hadronic backgrounds, complemented by thorough validation and systematic uncertainty quantification. Published by the American Physical Society 2025

Ablikim, M.↗
DOE OSTI2025

Study of D s + → f 0 ( 980 ) ρ + and ϕ π + Decays through D s + → π + π + π − π 0

We perform the first amplitude analysis of D s + → π + π + π − π 0 decays based on data samples of electron-positron collisions recorded with the BESIII detector at center-of-mass energies between 4.128 and 4.226 GeV, corresponding to an integrated luminosity of 7.33 fb − 1 . We report the observation of D s + → f 0 ( 980 ) ρ ( 770 ) + with a statistical significance greater than 10 σ and determine the branching fractions B ( D s + → π + π + π − π 0 | non − η ) = ( 2.04 ± 0.0 8 stat ± 0.0 5 syst ) % and B ( D s + → η π + ) = ( 1.56 ± 0.0 9 stat ± 0.0 4 syst ) % . Moreover, we measure the relative branching fraction between ϕ → π + π − π 0 and ϕ → K + K − to be [ B ( ϕ ( 1020 ) → π + π − π 0 ) / B ( ϕ ( 1020 ) → K + K − ) ] = 0.230 ± 0.01 4 stat ± 0.01 0 syst ., which deviates from the world average value by more than 4 σ . Published by the American Physical Society 2025

Ablikim, M.↗