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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Design of Neural Networks for Fast Convergence and Accuracy: Dynamics and Control

A procedure for the design and training of artificial neural networks, used for rapid and efficient controls and dynamics design and analysis for flexible space systems, has been developed. Artificial neural networks are employed, such that once properly trained, they provide a means of evaluating the impact of design changes rapidly. Specifically, two-layer feedforward neural networks are designed to approximate the functional relationship between the component/spacecraft design changes and measures of its performance or nonlinear dynamics of the system/components. A training algorithm, based on statistical sampling theory, is presented, which guarantees that the trained networks provide a designer-specified degree of accuracy in mapping the functional relationship. Within each iteration of this statistical-based algorithm, a sequential design algorithm is used for the design and training of the feedforward network to provide rapid convergence to the network goals. Here, at each sequence a new network is trained to minimize the error of previous network. The proposed method should work for applications wherein an arbitrary large source of training data can be generated. Two numerical examples are performed on a spacecraft application in order to demonstrate the feasibility of the proposed approach.

Maghami, Peiman G.↗
NASA NTRS2004

Wavefront Control Testbed (WCT) Experiment Results

The Wavefront Control Testbed (WCT) was created to develop and test wavefront sensing and control algorithms and software for the segmented James Webb Space Telescope (JWST). Last year, we changed the system configuration from three sparse aperture segments to a filled aperture with three pie shaped segments. With this upgrade we have performed experiments on fine phasing with line-of-sight and segment-to-segment jitter, dispersed fringe visibility and grism angle;. high dynamic range tilt sensing; coarse phasing with large aberrations, and sampled sub-aperture testing. This paper reviews the results of these experiments.

Burns, Laura A.↗
NASA NTRS2004

Coarsening in Solid-Liquid Mixtures-2: A Materials Science Experiment for the ISS

A materials science experiment has been developed and readied for operation aboard the International Space Station (ISS). Components of this experiment are onboard ISS and area awaiting the flight of science samples. The goal of the experiment is to understand the dynamics of Ostwald ripening, also known as coarsening, a process that occurs in nearly any two-phase mixture found in nature. Attempts to obtain experimental data in ground-based laboratories are hindered due to the presence of gravity, which introduces material transport modes other than that of the coarsening phenomenon. This introduces adjustable parameters in the formulation of theory. The original Coarsening in Solid-Liquid Mixtures (CSLM) mission, which flew on the Space Shuttle in 1997, produced data from a coarsened eutectic alloy. Unfortunately, both the science matrix and the hardware, while nominally functional, did not account adequately for operations in microgravity. A significantly redesigned follow-on experiment, CSLM-2 has been developed to redress the inadequacies of the original experiment. This paper reviews the CSLM-2 project: its history, science goals, flight hardware implementation, and planned operations and analysis

Hickman, J. Mark↗
NASA NTRS2004

The In-Space Soldering Investigation: Research Conducted on the International Space Station in Support of NASA's Exploration Initiative

Soldering is a well established joining and repair process that is of particular importance in the electronics industry. Still. internal solder joint defects such as porosity are prevalent and compromise desired properties such as electrical/thermal conductivity and fatigue strength. Soldering equipment resides aboard the International Space Station (ISS) and will likely accompany Exploration Missions during transit to, as well as on, the moon and Mars. Unfortunately, detrimental porosity appears to be enhanced in lower gravity environments. To this end, the In-Space Soldering Investigation (ISSI) is being conducted in the Microgravity Workbench Area (MWA) aboard the ISS as "Saturday Science" with the goal of promoting our understanding of joining techniques, shape equilibrium, wetting phenomena, and microstructural development in a microgravity environment. The work presented here will focus on direct observation of melting dynamics and shape determination in comparison to ground-based samples, with implications made to processing in other low-gravity environments. Unexpected convection effects, masked on Earth, will also be shown as well as the value of the ISS as a research platform in support of Exploration Missions.

Grugel, R. N.↗
NASA NTRS2006

The In-Space Soldering Investigation: To Date Analysis of Experiments Conducted on the International Space Station

Soldering is a well established joining and repair process that is of particular importance in the electronics industry. Still, internal solder joint defects such as porosity are prevalent and compromise desired properties such as electrical/thermal conductivity and fatigue strength. Soldering equipment resides aboard the International Space Station (ISS) and will likely accompany Exploration Missions during transit to, as well as on, the moon and Mars. Unfortunately, detrimental porosity appears to be enhanced in lower gravity environments. To this end, the In-Space Soldering Investigation (ISSI) is being conducted in the Microgravity Workbench Area (MWA) aboard the ISS as "Saturday Science" with the goal of promoting our understanding of joining techniques, shape equilibrium, wetting phenomena, and microstructural development in a microgravity environment. The work presented here will focus on direct observation of melting dynamics and shape determination in comparison to ground-based samples, with implications made to processing in other low-gravity environments. Unexpected convection effects, masked on Earth, will also be shown as well as the value of the ISS as a research platform in support of Exploration Missions.

Grugel, Richard N.↗
NASA NTRS2009

Long-Lived Venus Lander Conceptual Design: How To Keep It Cool

Surprisingly little is known about Venus, our neighboring sister planet in the solar system, due to the challenges of operating in its extremely hot, corrosive, and dense environment. For example, after over two dozen missions to the planet, the longest-lived lander was the Soviet Venera 13, and it only survived two hours on the surface. Several conceptual Venus mission studies have been formulated in the past two decades proposing lander architectures that potentially extend lander lifetime. Most recently, the Venus Science and Technology Definition Team (STDT) was commissioned by NASA to study a Venus Flagship Mission potentially launching in the 2020- 2025 time-frame; the reference lander of this study is designed to survive for only a few hours more than Venera 13 launched back in 1981! Since Cytherean mission planners lack a viable approach to a long-lived surface architecture, specific scientific objectives outlined in the National Science Foundation Decadal Survey and Venus Exploration Advisory Group final report cannot be completed. These include: mapping the mineralogy and composition of the surface on a planetary scale determining the age of various rock samples on Venus, searching for evidence of changes in interior dynamics (seismometry) and its impact on climate and many other key observations that benefit with time scales of at least a full Venus day (Le. daylight/night cycle). This report reviews those studies and recommends a hybrid lander architecture that can survive for at least one Venus day (243 Earth days) by incorporating selective Stirling multi-stage active cooling and hybrid thermoacoustic power.

Dyson, Ridger W.↗
NASA NTRS2026

Physical Parameters of Space Mission Asteroid Targets

Ground-based characterization of asteroids that are planned or potential targets of space missions provides important data on their physical parameters and properties. Knowledge of the properties of mission targets is important especially during mission preparation and planning, as it serves to select best or suitable targets for specific purpose of a given mission, to prepare mission plans, to constrain possible mission scenarios, and to design mission experiments. Such characterization efforts may be particularly critical for flyby missions that take only limited data during the high-speed flybys of their target asteroids, but they also provide very crucial data for targets of rendezvous missions. Moreover, long-term observations taken from Earth also allows the modelling of, or constraining, processes acting on the asteroids over extended time scales. Over the past years and decades we have obtained rich data on physical parameters of 82 asteroids that are planned or potential targets of space missions. Our primary observing technique is time-resolved (lightcurve) photometry, but we use also data obtained with other techniques, such as spectroscopy, thermal or radar observations. 15 of the 82 characterized asteroids are planned or possible targets of several space missions that are in flight or preparation, such as ESA’s Hera, RAMSES and PRIAMOS, NASA’s OSIRIS-APEX, JAXA’s Hayabusa2#, DESTINY+ and Next Generation Sample Return (NGSR), the Emirates Mission to Asteroids (EMA), and Karman+’s High Frontier, but we have also characterized 67 asteroids that are potential targets of space missions for their low delta-V’s and were announced as being “of interest to NASA” in the Small-Bodies-Observations- NASA mailing list or listed on the NHATS page of “Accessible NEAs”. The sample of asteroid targets span 3 orders of magnitude in size, with absolute magnitudes H from 12.57 to 26.8, corresponding to diameters from about 10 m to about 10 km. The sample contains a variety of taxonomic types and physically or dynamically interesting objects. Among them, we have identified 5 binary asteroids and 20 tumblers (i.e., asteroids in excited, non-principal axis rotation states). Rotation periods of the characterized asteroids range from 1.45 min to 280 h, reflecting diversity of their properties and formation/evolution paths. We will present an overview of the data set and highlight several representative cases.

Petr Pravec↗
DOE OSTI2022

Characterization of Acoustic Emissions From Analogue Rocks Using Sparse Regression‐DMDc

Abstract Moisture loss in rock is known to generate acoustic emissions (AE). Phenomena that result in AE during drying are related to the movement of fluids through the pores and induced‐cracks that arise from differential mineral shrinkage, especially in clay‐bearing rock. AE from the movement of fluids occurs from the reconfiguration of fluid interfaces during drying, while AE from mineral shrinkage involves the debonding within or between minerals. Here, analogue rock samples were used to examine the differences in the AE signatures when one or both AE source‐types are present. An unsupervised sparse regression model, Dynamic Mode Decomposition with control, that extends Dynamic Mode Decomposition is used to characterize the AE signals recorded during the drying of porous analogue rock samples fabricated with ordinary Portland cement, with and without clay. This method can effectively and accurately reconstruct acoustic signals emitted from samples that only experience moisture loss without cracking. However, the method struggles to reconstruct signals from samples with intricate crack networks that formed during drying because AE generating mechanisms can emit contemporaneously, and the resulting waves propagate through drying‐induced cracks that can lead to multiple internal reflections. Thus, the differential reconstruction accuracy of time series generated by different underlying physical processes provides a robust filter for reducing large data catalogs. In general, both dynamics and sparse initiating events are learned directly from data and this method exposes a data hierarchy based on the complexity of the intrinsic dynamics.

58 GEOSCIENCES↗
NASA NTRS2006

The Sloan Lens ACS Survey. I. A Large Spectroscopically Selected Sample of Massive Early-Type Lens Galaxies

The Sloan Lens ACS (SLACS) Survey is an efficient Hubble Space Telescope (HST) Snapshot imaging survey for new galaxy-scale strong gravitational lenses. The targeted lens candidates are selected spectroscopically from the Sloan Digital Sky Survey (SDSS) database of galaxy spectra for having multiple nebular emission lines at a redshift significantly higher than that of the SDSS target galaxy. The SLACS survey is optimized to detect bright early-type lens galaxies with faint lensed sources in order to increase the sample of known gravitational lenses suitable for detailed lensing, photometric, and dynamical modeling. In this paper, the first in a series on the current results of our HST Cycle 13 imaging survey, we present a catalog of 19 newly discovered gravitational lenses, along with nine other observed candidate systems that are either possible lenses, nonlenses, or nondetections. The survey efficiency is thus >=68%. We also present Gemini 8 m and Magellan 6.5 m integral-field spectroscopic data for nine of the SLACS targets, which further support the lensing interpretation. A new method for the effective subtraction of foreground galaxy images to reveal faint background features is presented. We show that the SLACS lens galaxies have colors and ellipticities typical of the spectroscopic parent sample from which they are drawn (SDSS luminous red galaxies and quiescent MAIN sample galaxies), but are somewhat brighter and more centrally concentrated. Several explanations for the latter bias are suggested. The SLACS survey provides the first statistically significant and homogeneously selected sample of bright early-type lens galaxies, furnishing a powerful probe of the structure of early-type galaxies within the half-light radius. The high confirmation rate of lenses in the SLACS survey suggests consideration of spectroscopic lens discovery as an explicit science goal of future spectroscopic galaxy surveys.

galaxies↗
DOE OSTI2017

Mechanisms of Lipid Scrambling by the G Protein-Coupled Receptor Opsin

Several class-A G protein-coupled receptor (GPCR) proteins act as constitutive phospholipid scramblases catalyzing the transbilayer translocation of >10,000 phospholipids per second when reconstituted into synthetic vesicles. To address the molecular mechanism by which these proteins facilitate rapid lipid scrambling, we carried out large-scale ensemble atomistic molecular dynamics simulations of the opsin GPCR. We report here that, in the process of scrambling, lipid head groups traverse a dynamically revealed hydrophilic pathway in the region between transmembrane helices 6 and 7 of the protein while their hydrophobic tails remain in the bilayer environment. We present quantitative kinetic models of the translocation process based on Markov State Model analysis. As key residues on the lipid translocation pathway are conserved within the class-A GPCR family, our results illuminate unique aspects of GPCR structure and dynamics while providing a rigorous basis for the design of variants of these proteins with defined scramblase activity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Wood-reinforced composites by stereolithography with the stress whitening behavior

In this study, poplar wood flour at various concentrations (1–10 wt%) is incorporated into a methacrylate-based resin via solution blending to fabricate wood-reinforced composites using stereolithography apparatus (SLA) 3D printing. Differential scanning calorimetry (DSC) along with Fourier transform infrared spectroscopy (FTIR) analysis shows the presence of a small amount of residual monomer in the printed samples. For the printed composites, the glass transition temperature (T g ) from dynamic mechanical analysis (DMA) decreases as more wood flour is incorporated, which indicates an increase in free volume occupied by polymer chains. The tensile strength is improved up to 17.3% from 21.1 MPa (no wood flour) to 24.7 MPa (1.0 wt% wood flour). The highest Young’s modulus reaches 323.8 MPa (2.0 wt% wood flour), which is 1.9-fold of that of the sample without wood flour. Moreover, the composites show “stress whitening” with the addition of wood flour during the uniaxial drawing. Morphology analysis of the tested samples show that the formation of microcraze and microvoids likely causing the stress whitening. This is the first study that demonstrates wood flour can be utilized in SLA 3D printed wood plastic composites (WPC) which can reinforce the printed products with a modest loading amount.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Investigation and validation of the dynamic response of an acoustically levitated particle using the lattice Boltzmann method

The stable levitation of an analyte sample in an acoustic levitator is a primary requirement for accurate x-ray characterization of its scientific structure. A rigid particle oscillates in an under-damped manner when introduced into the node of established standing acoustic waves. This investigation has employed the lattice Boltzmann method (LBM), a computational fluid dynamics technique, for the analysis of such rigid particle dynamics in acoustic levitation. The simulation uses the two dimensional and nine velocity (D2Q9) Bhatnagar-Gross-Krook formulation to levitate a rigid 1.6 mm diameter nylon ($\rho$ = 1150 kg/m 3 ) particle in the air at standard pressure and temperature conditions. The presented work is the first reported simulation of realistic acoustic levitator boundary conditions using the LBM. The simulation can capture the particle-fluid interactions that produce dynamic levitation at less than one-period timescale in the ultrasonic frequency regime. An experiment was conducted by levitating a 1.6mm-diameter nylon sphere to estimate the oscillations, and the oscillating frequency was found to be 50 Hz. The dynamic simulation results are consistent with experimental results for particle oscillations within the same order of magnitude, indicating that LBM formulation can be successfully used to study acoustic levitation to understand and mitigate particle jitter. The distortion of the acoustic field due to a levitating particle's presence was also analyzed to demonstrate how the presence of the particle can disrupt adjacent levitating nodes.

42 ENGINEERING↗
DOE OSTI2022

Representing Socio‐Economic Uncertainty in Human System Models

Abstract Socio‐economic development pathways and their implications for the environment are highly uncertain, and energy transitions will involve complex interactions among sectors. Here, traditional Monte Carlo analysis is paired with scenario discovery techniques to provide a richer portrait of these complexities. Modeled uncertain input variables include costs of advanced energy technologies, energy efficiency trends, fossil fuel resource availability, elasticities of substitution for labor, capital, and energy across economic sectors, population growth, and labor and capital productivity. The sampled values are simulated through a multi‐sector, multi‐region, recursively dynamic model of the world economy to explore a range of possible future outcomes. We find that many patterns of energy and technology development are possible for various long‐term environmental pathways and that sectoral output for most sectors is little affected through 2050 by the long‐term temperature target, but with tight constraints on emissions, emission intensities must fall much more rapidly. Scenario discovery techniques are applied to the large uncertainty ensembles to explore if there are prevailing storylines behind outcomes of interest. An illustrative investigation focused on different levels of economic growth shows many combinations of pathways and no single storyline emerging for a given economic outcome. This method can be extended to other outcomes of interest, exploring the nature of scenarios with both tail and median outcomes. Sampling from a Monte Carlo generated ensemble provides a rich set of scenarios to investigate, and potentially aids in avoiding heuristic biases in less structured scenario approaches.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Electric field dynamics in nitride structures containing quaternary alloy (Al, In, Ga)N

Molecular beam epitaxy growth and basic physical properties of quaternary AlInGaN layers, sufficiently thick for construction of electron blocking layers (EBL), embedded in ternary InGaN layers are presented. Transmission electron microscopy (TEM) measurement revealed good crystallographic structure and compositional uniformity of the quaternary layers contained in other nitride layers, which are typical for construction of nitride based devices. The AlInGaN layer was epitaxially compatible to InGaN matrix, strained, and no strain related dislocation creation was observed. The strain penetrated for limited depth, below 3 nm, even for relatively high content of indium (7%). For lower indium content (0.6%), the strain was below the detection limit by TEM strain analysis. The structures containing quaternary AlInGaN layers were studied by time dependent photoluminescence (PL) at different temperatures and excitation powers. It was shown that PL spectra contain three peaks: high energy donor bound exciton peak from the bulk GaN (DX GaN) and the two peaks (A and B) from InGaN layers. No emission from quaternary AlInGaN layers was observed. An accumulation of electrons on the EBL interface in high-In sample and formation of 2D electron gas (2DEG) was detected. The dynamics of 2DEG was studied by time resolved luminescence revealing strong dependence of emission energy on the 2DEG concentration. Theoretical calculations as well as power-dependence and temperature-dependence analysis showed the importance of electric field inside the structure. At the interface, the field was screened by carriers and could be changed by illumination. From these measurements, the dynamics of electric field was described as the discharge of carriers accumulated on the EBL.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Geothermal reservoir characterization using distributed temperature sensing at Brady Geothermal Field, Nevada

Distributed temperature sensing (DTS) systems provide near real-time data collection that captures borehole spatiotemporal temperature dynamics. For this study, temperature data was collected in an observation well at an active geothermal site for a period of eight days under geothermal production conditions. Collected temperature data showcase the ability of DTS systems to detect changes to the location of the steam-water interface, visualize borehole temperature recovery — following injection of a coldwater “slug” — and identify anomalously warm and/or cool zones. The high sampling rate and spatial resolution of DTS data also shows borehole temperature dynamics that are not captured by traditional pressure-temperature survey tools. Inversion of thermal recovery data using a finite-difference heat-transfer model produces a thermal-diffusivity profile that is consistent with laboratorymeasured values and correlates with identified lithologic changes within the borehole. Used alone or in conjunction with complementary data sets, DTS systems are useful tools for developing a better understanding of both reservoir rock thermal properties as well as within and near borehole fluid movement.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Machine learning model inputs, outputs, and scripts associated with “Artificial intelligence-guided iterations between observations and modeling significantly improve environmental predictions”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “Artificial intelligence-guided iterations between observations and modeling significantly improve environmental predictions” (Malhotra et al., in prep). This effort was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the contiguous United States (CONUS). New machine learning models were created every month to guide sampling locations. Data from the resulting samples were used to test and rebuild the machine learning models for the next round of sampling guidance. Associated sediment and water geochemistry and in situ sensor data can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1923689, https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1729719, and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1603775. This data package is associated with two GitHub repositories found at https://github.com/parallelworks/dynamic-learning-rivers and https://github.com/WHONDRS-Hub/ICON-ModEx_Open_Manuscript. In addition to this readme, this data package also includes two file-level metadata (FLMD) files that describes each file and two data dictionaries (DD) that describe all column/row headers and variable definitions. This data package consists of two main folders (1) dynamic-learning-rivers and (2) ICON-ModEx_Open_Manuscript which contain snapshots of the associated GitHub repositories. The input data, output data, and machine learning models used to guide sampling locations are within dynamic-learning-rivers. The folder is organized into five top-level directories: (1) “input_data” holds the training data for the ML models; (2) “ml_models” holds machine learning (ML) models trained on the data in “input_data”; (3) “examples” contains files for direct experimentation with the machine learning model, including scripts for setting up “hindcast” run; (4) “scripts” contains data preprocessing and postprocessing scripts and intermediate results specific to this data set that bookend the ML workflow; and (5) “output_data” holds the overall results of the ML model on that branch. Each trained ML model resides on its own branch in the repository; this means that inputs and outputs can be different branch-to-branch. There is also one hidden directory “.github/workflows”. This hidden directory contains information for how to run the ML workflow as an end-to-end automated GitHub Action but it is not needed for reusing the ML models archived here. Please see the top-level README.md in the GitHub repository for more details on the automation. The scripts and data used to create figures in the manuscript are within ICON-ModEx_Open_Manuscript. The folder is organized into four folders which contain the scripts, data, and pdf for each figure. Within the “fig-model-score-evolution” folder, there is a folder called “intermediate_branch_data” which contains some intermediate files pulled from dynamic-learning-rivers and reorganized to easily integrate into the workflows. NOTE: THIS FOLDER INCLUDES THE FILES AT THE POINT OF PAPER SUBMISSION. IT WILL BE UPDATED ONCE THE PAPER IS ACCEPTED WITH ANY REVISIONS AND WILL INCLUDE A DD/FLMD AT THAT POINT. We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Washington State Parks and Recreation Commission (Scientific Research Permit #210901), and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the samples labeled “SSS” were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview. WHONDRS consortium members were asked to provide any acknowledgments for the collection of samples labeled “CM” and the following is a list of acknowledgments that were submitted with their corresponding Site IDs: (MART) Research activities were conducted in part on the Wind River Experimental Forest within the Gifford Pinchot National Forest; (MP- 100379) Philadelphia is part of Lenapehoking, the ancestral homelands of the Lenape peoples; (MP-102398) Land surveyed is the ancestral homelands of the Nookhose'iinenno (Arapaho), Tsis tsis'tas (Cheyenne), and Nuuchu (Ute); (MP-100749 and MP- 100747) Georgia Coastal Ecosystem LTER, OCE-1832178; (SP-70 and SP-72) Eastern Shoshone, Shoshone-Bannock; (MP- 102944) Funded by Oregon Watershed Enhancement Board. On the traditional lands of the Confederated Tribes of the Siletz, Confederated Tribes of the Grand Rhonde, and the Clatsop-Nehalem Confederated Tribe; (MP- 100607) Holiday Creek is located on the traditional territory of the Monacan Indian Nation; (SP-45) Lafayette Blue Springs State Park; (MP-102420) NSF DEB-2016749; (MP-100019) New Hampshire Agriculture Experiment Station; (SP-35) Rayonier (land owner; https://www.rayonier.com/); (MP- 101276) US Department of Energy, Office of Science, Biological and Environmental Research, Subsurface Biogeochemical Research, Watershed Dynamics and Evolution SFA at ORNL; (MP- 103224) Watershed Dynamics and Evolution SFA at ORNL; (MP- 101584) Traditional lands of the Oceti Sakowin (Dakota, Lakota, Nakoda) and Anishinaabe Peoples.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

SDYN-GANs: Adversarial learning methods for multistep generative models for general order stochastic dynamics

We introduce adversarial learning methods for data-driven generative modeling of dynamics of nth-order stochastic systems. Our approach builds on Generative Adversarial Networks (GANs) with generative model classes based on stable m-step stochastic numerical integrators. From observations of trajectory samples, we introduce methods for learning long-time predictors and stable representations of the dynamics. Our approaches use discriminators based on Maximum Mean Discrepancy (MMD), training protocols using both conditional and marginal distributions, and methods for learning dynamic responses over different time-scales. We show how our approaches can be used for modeling physical systems to learn force-laws, damping coefficients, and noise-related parameters. Our adversarial learning approaches provide methods for obtaining stable generative models for dynamic tasks including long-time prediction and developing simulations for stochastic systems.

• Artificial intelligence (AI) / machine learning ↗
DOE OSTI2025

Statistically elucidated responses from low-signal contrast mechanisms in ultrafast electron microscopy

The emergence of ultrafast electron microscopy (UEM) has enabled the discovery of strongly correlated dynamic mechanisms, including electron–phonon coupling, structural phase transitions, thermal transport, and electromagnetic deflection. Most UEM systems operate stroboscopically, meaning that the technique is susceptible to artifacts, mistakes, and misinterpretation of the data due to extensive experimental effort. In contrast to the ultrafast designation, data acquisition is extraordinarily slow because the electron beam has significantly reduced signal compared to traditional transmission electron microscopy due to pulsing the electron beam. Consequently, the sample may drift, tilt, or undergo irreversible structural changes that are independent of the time-resolved dynamics throughout the experimental time frame. Furthermore, these datasets require significant user interpretation that can be problematic when proper controls are not implemented thoroughly. Here, we demonstrate a new algorithm designed to separate ultrafast structural dynamics from long-term artifacts using a LiNbO 3 sample experiencing electrically driven surface acoustic wave propagation. Additionally, we provide examples of the impact of user bias when analyzing the data and provide a methodology, which enables the extraction of time-resolved responses when the image signal is extraordinarily low. Overall, the goal of this publication is to provide methods that validate the experimental results and reduce researcher biases during UEM data interpretation.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗