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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 595 records · Page 33

Field-resolved observation of exciton coherence in a van der Waals magnet

The emergence of coherence among electronic quasiparticles underlies collective quantum phenomena from superconductivity to superradiance. In semiconductors, exciton coherence is generally thought to decay rapidly due to scattering and dephasing, limiting its persistence on ultrafast timescales. Here, in this work, we demonstrate a light-field-driven mechanism that creates and stabilizes exciton coherence in the layered antiferromagnet CrSBr. We directly record the coherent optical field emitted by excitons and track in real time how a deterministic phase, imprinted by the excitation laser, drives incoherent excitons to synchronize into a collective state. This ensemble remains phase coherent for more than 2 ps, whereas its resonance energy undergoes an ultrafast modulation mediated by spin and lattice interactions. The time-resolved field evolution indicates that the multiple peaks seen in conventional spectra originate from a single excitonic resonance subject to dynamic energy modulation. Our findings establish optical phase imprinting as a mechanism to control and sustain collective order in semiconducting magnets, bridging light-driven dynamics with excitonic and magnetic correlations in layered quantum materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Antiviral discovery using sparse datasets by integrating experiments, molecular simulations, and machine learning

Computational methods have demonstrated success in identifying virucidal agents, effectively contributing to the discovery of novel virucidal molecules. In this study, we developed a machine learning (ML) model, trained on a small dataset, to predict inhibitors of human enterovirus 71 (EV71), a pathological agent that causes severe disease in children and immunocompromised adults. Despite the dataset’s limitation, comprising of only 36 compounds tested, our ML framework demonstrated significant predictive capability. Notably, experimental validation revealed that five out of the eight compounds predicted by our model from the Chinese cosmetic material list exhibited virucidal activity. The inhibitor effects displayed by the main active compounds were further confirmed by molecular dynamics simulation. This underscores the potential of our AI-driven approach to bypass data constraints in identifying active molecules against viral pathogens.

60 APPLIED LIFE SCIENCES↗

Dynamic Life-Cycle Analysis of Fast Pyrolysis Biorefineries: Impacts of Feedstock Moisture Content and Particle Size

The commercialization of biorefineries has been met with significant obstacles due to the technical difficulties of handling solid biomass feedstocks, which are highly variable in physical properties and chemical compositions. An understanding of the principles of unit operations along the supply chain is key to the success of the biofuel industry. This study applies a dynamic life-cycle analysis (DLCA) methodology by developing quantitative relationships between the inputs and outputs for each unit operation based on scientific understanding of the causal effects. Using the DLCA, we assessed system sustainability of drop-in fuel production from fast pyrolysis of pine residues followed by hydro-processing. Life-cycle greenhouse gas (GHG) emissions were calculated for 4641 runs involving two key feedstock parameters: moisture content after field drying and particle size of the feed to pyrolyzer. Moisture contents varied between 25% and 35%, while particle sizes varied between 0.5 and 5 mm in these runs. The life-cycle GHG emissions of these cases vary from 22 to 40 g/MJ. Close examination of each unit operation's contribution to the total GHG emissions reveals that low moisture content after field drying produces savings in energy consumption during feedstock transportation and on-site drying. However, although small particle size leads to overall higher fuel yield, it also requires a significant amount of energy for feedstock size reduction and fuel production. The energy penalty outweighs the benefit of increased fuel yields, especially when fine particles (<1 mm) are used for pyrolysis; thus, small particle size leads to increased GHG emissions overall. The results highlight the trade-offs between the energy demand for preprocessing and the conversion yields, which can be addressed with DLCA.

09 BIOMASS FUELS↗

Latent space dynamics identification for interface tracking with application to shock-induced pore collapse

Capturing sharp, evolving interfaces remains a central challenge in reduced-order modeling, especially when data is limited and the system exhibits localized nonlinearities or discontinuities. Here, we propose LaSDI-IT (Latent Space Dynamics Identification for Interface Tracking), a data-driven framework that combines low-dimensional latent dynamics learning with explicit interface-aware encoding to enable accurate and efficient modeling of physical systems involving moving material boundaries. At the core of LaSDI-IT is a revised autoencoder architecture that jointly reconstructs the physical field and an indicator function representing material regions or phases, allowing the model to track complex interface evolution without requiring detailed physical models or mesh adaptation. The latent dynamics are learned through linear regression in the encoded space and generalized across parameter regimes using Gaussian process interpolation with greedy sampling. We demonstrate LaSDI-IT on the problem of shock-induced pore collapse in high explosives, a process characterized by sharp temperature gradients and dynamically deforming pore geometries. The method achieves relative prediction errors below 9% across the parameter space, accurately recovers key quantities of interest such as pore area and hot spot formation, and matches the performance of dense training with only half the data. This latent dynamics prediction was 10 6 times faster than the conventional high-fidelity simulation, proving its utility for multi-query applications. These results highlight LaSDI-IT as a general, data-efficient framework for modeling discontinuity-rich systems in computational physics, with potential applications in multiphase flows, fracture mechanics, and phase change problems.

Gaussian process↗

2-kW Solar Dynamic Space Power System Tested in Lewis' Thermal Vacuum Facility

Working together, a NASA/industry team successfully operated and tested a complete solar dynamic space power system in a large thermal vacuum facility with a simulated sun. This NASA Lewis Research Center facility, known as Tank 6 in building 301, accurately simulates the temperatures, high vacuum, and solar flux encountered in low-Earth orbit. The solar dynamic space power system shown in the photo in the Lewis facility, includes the solar concentrator and the solar receiver with thermal energy storage integrated with the power conversion unit. Initial testing in December 1994 resulted in the world's first operation of an integrated solar dynamic system in a relevant environment.

Source record↗

Dynamic Control System Mode Performance of the Space Technology-7 Disturbance Reduction System

The Space Technology-7 (ST-7) Disturbance Reduction System (DRS) is an experiment package aboard the European Space Agency (ESA) LISA Pathfinder spacecraft, launched on December 3, 2015. DRS consists of three primary components: Colloidal MicroNewton Thrusters (CMNTs), an Integrated Avionics Unit (IAU), and flight-software implementing the Command and Data Handling (C&DH) and Dynamic Control System (DCS) algorithms. The CMNTs were designed to provide thrust from 5 to 30 micro Newton, with thrust controllability and resolution of 0.1 micro Newton and thrust noise of 0.1 micro Newton/(square root of (Hz)) in the measurement band from 1-30 mHz. The IAU hosts the C&DH and DCS flight software, as well as interfaces with both the CMNT electronics and the LISA Pathfinder spacecraft. When in control, the DCS uses star tracker attitude data and capacitive or optically-measured position and attitude information from LISA Pathfinder and the LISA Technology Package (LTP) to control the attitude and position of the spacecraft and the two test masses inside the LTP. After completion of the nominal ESA LISA Pathfinder mission, the DRS experiment was commissioned followed by its nominal mission. DRS operations extended over the next five months, interspersed with station keeping, anomaly resolution, and periods where control was handed back to LISA Pathfinder for them to conduct further experiments. The primary DRS mission ended on December 6, 2016, with the experiment meeting all of its Level 1 requirements. The DCS, developed at the NASA Goddard Space Flight Center, consists of five spacecraft control modes and six test mass control modes, combined into six 'DRS Mission Modes'. Attitude Control and Zero-G were primarily used to control the spacecraft during initial handover and during many of the CMNT characterization experiments. The other Mission Modes, Drag Free Low Force, 18-DOF Transitional, and 18-DOF, were used to provide drag-free control of the spacecraft about the test masses. This paper will discuss the performance of these DCS spacecraft and test mass control modes. Flight data will be shown from each mode throughout the mission, both from nominal operations and during various flight experiments. The DCS team also made some changes to controller, filter, and limit parameters during operations; the motivation and results of these changes will be shown and discussed.

O'Donnell, James R., Jr.↗

Research on Supersonic Inlet Bleed

Phase I data results of the Fundamental Inlet Bleed Experiments project at NASA Glenn Research Center (GRC) are presented which include flow coefficient results for two single-hole boundary-layer bleed configurations. The bleed configurations tested are round holes at inclination angles of 90deg and 20deg both having length-to-diameter ratios of 2.0. Results were obtained at freestream Mach numbers of 1.33, 1.62, 1.98, 2.46, and 2.92 and unit Reynolds numbers of 0.984, 1.89, and 2.46 10(exp 7)/m. Approach boundary-layer data are presented for each flow condition and the flow coefficient results are compared to existing multi-hole data obtained under similar conditions. For the 90deg hole, the single and multi-hole distributions agree fairly well with the exception that under supercritical operation, the multi-hole data chokes at higher flow coefficient levels. This behavior is also observed for the 20deg hole but to a lesser extent. The 20deg hole also shows a markedly different characteristic at subcritical operation. Also presented are preliminary results of a Computational Fluid Dynamics (CFD) analysis of both configurations at the Mach 1.33 and a unit Reynolds number of 2.46 10(exp 7)/m. Comparison of the results shows the agreement to be very good.

Davis, David O.↗

Observation of polarization density waves in SrTiO 3

The nature of the incipient ferroelectric transition in SrTiO 3 has been a long-standing puzzle in condensed matter physics. One explanation involves the competition between ferroelectricity and an instability characterized by the mesoscopic modulation of the polarization. These polarization density waves, which should intensify near the quantum critical point, break local inversion symmetry and are difficult to characterize with conventional X-ray scattering methods. Here, in this study, we probe inversion symmetry breaking at finite momenta and visualize the instability of the polarization at the nanometre scale in SrTiO3 by combining a femtosecond X-ray free-electron laser with terahertz coherent control methods. We found polar-acoustic collective modes that are soft, particularly at the tens of nanometre scale. These precursor collective excitations provide evidence for the conjectured mesoscopic-modulated phase in SrTiO 3 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Photoinduced twist and untwist of moiré superlattices

This paper directly observes femtosecond photoinduced twist–untwist motion of WSe₂/MoSe₂ moiré superlattices using ultrafast electron diffraction, showing that optical excitation can dynamically reconfigure moiré lattice structure and interlayer coupling. It supports the proposal by establishing the team’s ability to probe ultrafast interfacial and moiré dynamics, which is relevant to using moiré TMDs as reconfigurable platforms for controlling spin, charge, and molecular interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A Multi-Architecture Approach for Implicit Computational Fluid Dynamics on Unstructured Grids

High-performance computing (HPC) architectures are trending toward manycore paradigms such as graphics processing units (GPUs). Approximately half of the top 100 publicly disclosed supercomputers in the world utilize GPU accelerators for performance. This is in contrast to a decade ago, where there were only a few such machines in the top 100. It is not currently possible to compile and run legacy central processing unit (CPU) software efficiently on GPUs without significant refactoring. Though a number of frameworks offering performance portability exist, none offer a standardized specification that is supported by all major hardware vendors. Additionally, experiences show that obtaining a high percentage of peak performance often requires architecture-specific code. This work details a pragmatic multi-architecture computational fluid dynamics library focused on aerospace problems across the speed range from low subsonic to hypersonic flows involving thermochemical nonequilibrium. A thin abstraction layer above NVIDIA CUDA C++ is utilized, which enables primarily single-source software currently capable of running efficiently on multicore CPUs, NVIDIA GPUs, AMD GPUs, and Intel GPUs. Results on various problems of interest across the speed range are presented and performance is compared between various architectures.

GPU↗

A Multi-Architecture Approach for Implicit Computational Fluid Dynamics on Unstructured Grids

High-performance computing (HPC) architectures are trending toward manycore paradigms such as graphics processing units (GPUs). Approximately half of the top 100 publicly disclosed supercomputers in the world utilize GPU accelerators for performance. This is in contrast to a decade ago, where there were only a few such machines in the top 100. It is not currently possible to compile and run legacy central processing unit (CPU) software efficiently on GPUs without significant refactoring. Though a number of frameworks offering performance portability exist, none offer a standardized specification that is supported by all major hardware vendors. Additionally, experiences show that obtaining a high percentage of peak performance often requires architecture-specific code. This work details a pragmatic multi-architecture computational fluid dynamics library focused on aerospace problems across the speed range from low subsonic to hypersonic flows involving thermochemical nonequilibrium. A thin abstraction layer above NVIDIA CUDA C++ is utilized, which enables primarily single-source software currently capable of running efficiently on multicore CPUs, NVIDIA GPUs, AMD GPUs, and Intel GPUs. Results on various problems of interest across the speed range are presented and performance is compared between various architectures.

GPU↗

Hardware interface unit for control of shuttle RMS vibrations

Vibration of the Shuttle Remote Manipulator System (RMS) increases the time for task completion and reduces task safety for manipulator-assisted operations. If the dynamics of the manipulator and the payload can be physically isolated, performance should improve. Rockwell has developed a self contained hardware unit which interfaces between a manipulator arm and payload. The End Point Control Unit (EPCU) is built and is being tested at Rockwell and at the Langley/Marshall Coupled, Multibody Spacecraft Control Research Facility in NASA's Marshall Space Flight Center in Huntsville, Alabama.

Lindsay, Thomas S.↗

Subseasonal-to-Seasonal Hindcast Skill Assessment of Ridging Events Related to Drought Over the Western United States

Persistent atmospheric ridging events centered near the western United States are associated with widespread precipitation deficits and meteorological drought. Due to the relatively low skill of- dynamical models in forecasting precipitation on subseasonal‐to‐seasonal (S2S) time scales across this region, forecasts of ridging are explored in this study as a potential bridge for early warning drought prediction. To assess skill, we evaluate deterministic and probabilistic S2S hindcasts (out to 6 week lead time) of ridging events and geopotential height anomalies over the western United States in five ensemble hindcast systems. Prediction skill for ridging events is shown to be highly variable across models. For some models, longer‐time‐averaged patterns of geopotential height anomalies across the first 6 weeks can be skillfully simulated, when evaluated probabilistically against climatology. The most skillful models show modest skill in forecasting above normal ridging occurrences at lead times of Weeks 3–4 and Weeks 5–6,with some sensitivity to the specific ridge location and method for determining skill. Using the European Centre for Medium‐Range Weather Forecasts (ECMWF) model as a case study, longer lead time forecast busts are shown to often occur under extended periods of highly active La Nina‐like tropical convection. Model errors at simulating these tropical convection features may have a disproportionately large impact and degrade downstream forecasts over the western United States. Despite the documented model shortcomings, our results highlight an opportunity to target skillful ridging forecasts from dynamical models for improving early warning drought forecasting at S2S lead times.

S2S↗

Steric Modulation of Protein‐Mediated Nanoparticle Assembly: Controlling Cluster Size, Polydispersity, and FRET Responses by Rebalancing Short‐ and Long‐Range Interactions

Understanding and manipulating protein-nanoparticle interactions is of broad interest to fields ranging from nanomedicine to the biological fabrication of functional hierarchical materials. This study investigates how steric forces introduced by a pegylated derivative of superfolder green fluorescent protein (sfGFP) that is monofunctional for silica binding modulate the delicate interplay of long-range (electrostatic and van der Waals) and short-range (protein-mediated) interactions in pH-responsive silica nanoparticle (SiNP) assembly by bifunctional silica-binding sfGFP. Increasing the length of the PEG segment and pre-incubating SiNPs with increasing concentrations of pegylated proteins enables precise control over cluster size within the 800–1450 nm range with a sixfold decrease in polydispersity index to a remarkable 0.1 endpoint. Weakening short-range attractive interactions via mutagenesis extends this control to clusters in the 50–250 nm range and reveals that the Förster resonance energy transfer (FRET) efficiency of clusters scales linearly with cluster diameter below 230 nm but increases only by 15% as clusters grow to 1450 nm. Furthermore, these findings enable the development of a system that provides an optical readout to dynamic changes in solution conditions enacted by a combination of pH adjustment and ion charge screening.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Field-Focused Load-Leveled Dynamic Wireless Charging System for Electric Vehicles

Electric vehicles offer much higher well-to-wheel efficiency than gasoline vehicles and can significantly reduce U.S. dependence on foreign oil, lower greenhouse gas emissions, improve local air quality, and support continued technological and economic growth. Despite these advantages, widespread adoption remains constrained by limitations in current battery technology, including high cost, limited driving range, and long charging times. One promising approach to address these challenges is to reduce onboard energy storage and instead deliver power wirelessly to vehicles while they are at a traffic stop or in motion.

33 ADVANCED PROPULSION SYSTEMS↗

The Role of Musculoskeletal Dynamics and Neuromuscular Control in Stress Development in Bone

The role of forces produced by the musculotendon units in the stress development of the long bones during gait has not been fully analyzed. It is well known that the musculotendons act as actuators producing the joint torques which drive the body. Although the joint torques required to perform certain motor tasks can be recovered through a kinematic analysis, it remains a difficult problem to determine the actual forces produced by each muscle that resulted in these torques. As a consequence, few studies have focused on the role of individual muscles in the development of stress in the bone. This study takes a control theoretic approach to the problem. A seven-link, eight degrees of freedom model of the body is controlled by various muscle groups on each leg to simulate gait. The simulations incorporate Hill-type models of muscles with activation and contraction dynamics controlled through neural inputs. This direct approach allows one to know the exact muscle forces exerted by each musculotendon throughout the gait cycle as well the joint torques and reaction forces at the ankle and knee. Stress and strain computed by finite element analysis on skeletal members will be related to these derived loading conditions. Thus the role of musculoskeletal dynamics and neuromuscular control in the stress development of the tibia during gait can be analyzed.

DeWoody, Yssa↗

Shake test of rotor test apparatus in the 40- by 80-foot wind tunnel

A shake test was conducted to determine the dynamic characteristics of a rotor test apparatus on strut systems. The rotor-off hub transfer function (acceleration per unit force as a function of frequency) was measured in the longitudinal and lateral directions, using a combination of broadband and discrete frequency excitation techniques. The dynamic data is summarized for the configurations tested, giving the following properties for each mode identified: the natural frequency, the hub response at resonance, and the fixed system damping. The complete transfer functions are presented, and the detailed test results are included as an appendix. Data analysis techniques developed to obtain on-line measurements of the system modal properties, including the damping coefficient and the damping ratio are discussed.

Johnson, W.↗