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At least 1,009 records · Page 56

Resonance absorption of compressible magnetohydrodynamic waves at thin 'surfaces'

The behavior of plasma and fields in the transition layer supporting MHD surface waves is analyzed, assuming that the total pressure fluctuations, delta-P(tot), can be taken to be nearly constant across this thin transition layer, with a value nearly the same as would be obtained if the MHD wave were supported by a truly discontinuous surface. Regarding therefore delta-P(tot) as known, the plasma and field equations in the transition layer were cast into a form in which delta-P(tot) appeared as a driving term. Among the two resonances that appear (the cusp resonance and the Alfven resonance) special attention is given to the Alfven resonance, which affects the velocity and magnetic field components normal to the background magnetic field. The effects of three types of viscosity on the Alfven resonance are considered, and it is shown that energy is pumped out of the surface wave into thin layers surrounding the resonant field lines.

Hollweg, Joseph V.↗

Unsteady surface pressure measurements on a slender delta wing undergoing limit cycle wing rock

An experimental investigation of slender wing limit cycle motion known as wing rock was investigated using two unique experimental systems. Dynamic roll moment measurements and visualization data on the leading edge vortices were obtained using a free to roll apparatus that incorporates an airbearing spindle. In addition, both static and unsteady surface pressure data was measured on the top and bottom surfaces of the model. To obtain the unsteady surface pressure data a new computer controller drive system was developed to accurately reproduce the free to roll time history motions. The data from these experiments include, roll angle time histories, vortex trajectory data on the position of the vortices relative to the model's surface, and surface pressure measurements as a function of roll angle when the model is stationary or undergoing a wing rock motion. The roll time history data was numerically differentiated to determine the dynamic roll moment coefficient. An analysis of these data revealed that the primary mechanism for the limit cycle behavior was a time lag in the position of the vortices normal to the wing surface.

Arena, Andrew S., Jr.↗

A model for the hydrologic and climatic behavior of water on Mars

An analysis is carried out of the hydrologic response of a water-rich Mars to climate change and to the physical and thermal evolution of its crust, with particular attention given to the potential role of the subsurface transport, assuming that the current models of insolation-driven change describe reasonably the atmospheric leg of the planet's long-term hydrologic cycle. Among the items considered are the thermal and hydrologic properties of the crust, the potential distribution of ground ice and ground water, the stability and replenishment of equatorial ground ice, basal melting and the polar mass balance, the thermal evolution of the early cryosphere, the recharge of the valley networks and outflow, and several processes that are likely to drive the large-scale vertical and horizontal transport of H2O within the crust. The results lead to the conclusion that subsurface transport has likely played an important role in the geomorphic evolution of the Martian surface and the long-term cycling of H2O between the atmosphere, polar caps, and near-surface crust.

Clifford, Stephen M.↗

Elucidating Abnormal Grain Growth in Thermomagnetic Processed Materials with Transfer Learning and Reinforcement Learning

The goal of this research program is to establish the mechanism governing local grain boundary motion, which is needed to design and process desirable microstructures for better performance, by identifying the relative contributions of grain boundary (GB) energy and mobility to grain growth. Classical models for grain growth assume that the primary mechanism for reducing the total interfacial energy is area reduction and that GB restructuring is not significant. This assumption implies that grain growth is locally driven by curvature. However, recent experimental observations using new non-destructive 3D x-ray diffraction microscopy techniques (3D-XRM) reveal that classic descriptors (i.e., curvature, number of neighbors, grain size) do not predict real grain growth. Instead, local GB motion appears to be governed by its energy relative to its neighbors such that low-energy boundaries replace those of higher energy. However, simulations that incorporate GB energy anisotropy still fail to reproduce these observations. These discrepancies suggest that the common assumption for grain growth theory must be re-examined to predict and, thus, control microstructure evolution in real polycrystals. A significant challenge to testing this assumption is due to anisotropic GB mobility. Mobility may cause abnormal grain growth or affect the final grain shapes or growth rate but its true contributions are unknown because it is difficult to measure. For example, observations in Fe have found that grains associated with high energy and high mobility boundaries tend to experience abnormal grain growth, whereas abnormal grain growth is associated with low energy and high mobility boundaries in alumina. As mobility and energy both control GB motion, it is challenging to isolate the local driving forces necessary to test the common assumption that the primary mechanism is area reduction. The novelty of this work is the use of machine learning tools to capture GB mobility and energy from 3D-XRM measurements in polycrystals to test the common assumption used in grain growth models. Machine learning can capture high-order correlations in dynamic systems like those found in the evolving GB topology. The PIs have developed a physics-regularized interpretable machine learning microstructure evolution (PRIMME) model that accurately replicates the grain growth behavior of its trained data set.

36 MATERIALS SCIENCE↗

Exploring Object Detection and Image Classification Tasks for Niche Use Case in Naturalistic Driving Studies

Naturalistic driving studies consist of drivers using their personal vehicles and provide valuable real-world data, but privacy issues must be handled very carefully. Drivers sign a consent form when they elect to participate, but passengers do not for a variety of practical reasons. However, their privacy must still be protected. One large study includes a blurred image of the entire cabin which allows reviewers to find passengers in the vehicle; this protects the privacy but still allows a means of answering questions regarding the impact of passengers on driver behavior. A method for automatically counting the passengers would have scientific value for transportation researchers. We investigated different image analysis methods for automatically locating and counting the non-drivers including simple face detection and fine-tuned methods for image classification and a published object detection method. We also compared the image classification using convolutional neural network and vision transformer backbones. Our studies show the image classification method appears to work the best in terms of absolute performance, although we note the closed nature of our dataset and nature of the imagery makes the application somewhat niche and object detection methods also have advantages. We perform some analysis to support our conclusion.

Peruski, Ryan↗

Artificial neural network implementation of a near-ideal error prediction controller

A theory has been developed at the University of Virginia which explains the effects of including an ideal predictor in the forward loop of a linear error-sampled system. It has been shown that the presence of this ideal predictor tends to stabilize the class of systems considered. A prediction controller is merely a system which anticipates a signal or part of a signal before it actually occurs. It is understood that an exact prediction controller is physically unrealizable. However, in systems where the input tends to be repetitive or limited, (i.e., not random) near ideal prediction is possible. In order for the controller to act as a stability compensator, the predictor must be designed in a way that allows it to learn the expected error response of the system. In this way, an unstable system will become stable by including the predicted error in the system transfer function. Previous and current prediction controller include pattern recognition developments and fast-time simulation which are applicable to the analysis of linear sampled data type systems. The use of pattern recognition techniques, along with a template matching scheme, has been proposed as one realizable type of near-ideal prediction. Since many, if not most, systems are repeatedly subjected to similar inputs, it was proposed that an adaptive mechanism be used to 'learn' the correct predicted error response. Once the system has learned the response of all the expected inputs, it is necessary only to recognize the type of input with a template matching mechanism and then to use the correct predicted error to drive the system. Suggested here is an alternate approach to the realization of a near-ideal error prediction controller, one designed using Neural Networks. Neural Networks are good at recognizing patterns such as system responses, and the back-propagation architecture makes use of a template matching scheme. In using this type of error prediction, it is assumed that the system error responses be known for a particular input and modeled plant. These responses are used in the error prediction controller. An analysis was done on the general dynamic behavior that results from including a digital error predictor in a control loop and these were compared to those including the near-ideal Neural Network error predictor. This analysis was done for a second and third order system.

Mcvey, Eugene S.↗

GPS Monitoring of Surface Change During and Following the Fortuitous Occurrence of the M(sub w) = 7.3 Landers Earthquake in our Network

Accomplishments: (1) Continues GPS monitoring of surface change during and following the fortuitous occurrence of the M(sub w) = 7.3 Landers earthquake in our network, in order to characterize earthquake dynamics and accelerated activity of related faults as far as 100's of kilometers along strike. (2) Integrates the geodetic constraints into consistent kinematic descriptions of the deformation field that can in turn be used to characterize the processes that drive geodynamics, including seismic cycle dynamics. In 1991, we installed and occupied a high precision GPS geodetic network to measure transform-related deformation that is partitioned from the Pacific - North America plate boundary northeastward through the Mojave Desert, via the Eastern California shear zone to the Walker Lane. The onset of the M(sub w) = 7.3 June 28, 1992, Landers, California, earthquake sequence within this network poses unique opportunities for continued monitoring of regional surface deformation related to the culmination of a major seismic cycle, characterization of the dynamic behavior of continental lithosphere during the seismic sequence, and post-seismic transient deformation. During the last year, we have reprocessed all three previous epochs for which JPL fiducial free point positioning products available and are queued for the remaining needed products, completed two field campaigns monitoring approx. 20 sites (October 1995 and September 1996), begun modeling by development of a finite element mesh based on network station locations, and developed manuscripts dealing with both the Landers-related transient deformation at the latitude of Lone Pine and the velocity field of the whole experiment. We are currently deploying a 1997 observation campaign (June 1997). We use GPS geodetic studies to characterize deformation in the Mojave Desert region and related structural domains to the north, and geophysical modeling of lithospheric behavior. The modeling is constrained by our existing and continued GPS measurements, which will provide much needed data on far-field strain accumulation across the region and on the deformational response of continental lithosphere during and following a large earthquake, forming the basis for kinematic and dynamic modeling of secular and seismic-cycle deformation. GPS geodesy affords both regional coverage and high precision that uniquely bear on these problems.

Miller, M. Meghan↗

Nonlinear Insolation Forcing: A Physical Mechanism for Climate Change

This paper focuses on recent advances in the understanding of nonlinear insolation forcing for climate change. The amplitude-frequency resonances in the insolation variations induced by the Earth's changing obliquity are emergent and may provide a physical mechanism to drive the glaciation cycles. To establish the criterion that nonlinear insolation forcing is responsible for major climate changes, the cooperative phenomena between the frequency and amplitude of the insolation are defined as insolation pulsation. Coupling of the insolation frequency and amplitude variations has established an especially new and interesting series of insolation pulses. These pulses would modulate the insolation in such a way that the mode of insolation variations could be locked to generate the 100-kyr ice age cycle which is a long-time geophysical puzzle. The nonlinear behavior of insolation forcing is tested by energy balance and ice sheet climate models and the physical mechanism behind this forcing is explained in terms of pulse duration in the incoming solar radiation. Calculations of the solar energy flux at the top of the atmosphere show that the duration of the negative and positive insolation pulses is about 2 thousand years which is long enough to prolong glaciation into deep ice ages and cause rapid melting of large ice sheets in the high latitudes of the northern hemisphere. We have performed numerical simulations of climate response to nonlinear insolation forcing for the past 2 million years. Our calculated results of temperature fluctuations are in good agreement with the climate cycles as seen in the terrestrial biogenic silica (BDP-96-2) data as well as in the marine oxygen isotope (delta(sup 18)O) records.

Liu, H. S.↗

Thermally driven surface phase separation in intermetallic alloys

Intermetallic compounds are widely recognized for their high-temperature phase stability and resistance to composition and structural changes. However, we reveal athermally activated bulk-to-surface mass exchange mechanism that drives surface phase separation, resulting in the formation of surface precipitates with distinct composition andstructure from the bulk matrix. Using the archetypal β-NiAl system, we show that asymmetries in vacancy formation energies between Ni and Al atoms induce preferential Ni segregation to the surface, forming Ni-rich γ'-Ni 3 Al precipitates. By integrating in-situ electron microscopy, synchrotron X-ray absorption spectroscopy and first-principles computational modeling, we establish a direct mechanistic connection between bulk thermal defect dynamics, surface compositional evolution, and phase segregation behavior. This bulk-surface coupling mechanism can be a driver of surface phase separation in multicomponent alloys under thermal stress. In conclusion, these results refine the thermodynamic boundaries of intermetallic stability and provide insights into managingthe performance and durability of intermetallic alloys for demanding high-temperature applications.

36 MATERIALS SCIENCE↗

Lubrication System Failure Baseline Testing on an Aerospace Quality Gear Mesh

Aerospace drive systems are required to survive a loss-of-lubrication test for qualification. In many cases emergency lubrication systems need to be designed and utilized to permit the drive system to pass this difficult requirement. The weight of emergency systems can adversely affect the mission capabilities of the aircraft. The possibility to reduce the emergency system weight through the use of mist lubrication will be described. Mist lubrication involves the delivery of a minute amount of an organic liquid as a vapor or fine mist in flowing compressed air to rubbing surfaces. At the rubbing surface, the vapor or mist reacts to form a solid lubricating film. The aim of this study was to establish a baseline for gear behavior under oil depleted conditions. A reactive vapor-mist lubrication method is described and proposed as a candidate emergency lubrication system.

Handschuh, Robert F.↗

Enabling Stable Cycling of 4.2 V High-Voltage All-Solid-State Batteries with PEO-Based Solid Electrolyte

Poly(ethylene oxide) (PEO)-based solid electrolytes are expected to be exploited in solid-state batteries with high safety. Its narrow electrochemical window, however, limits the potential for high voltage and high energy density applications. In this paper, the electrochemical oxidation behavior of PEO and the failure mechanisms of LiCoO 2 -PEO solid-state batteries are studied. It is found that although for pure PEO it starts to oxidize at a voltage of above 3.9 V versus Li/Li + , the decomposition products have appropriate Li + conductivity that unexpectedly form a relatively stable cathode electrolyte interphase (CEI) layer at the PEO and electrode interface. The performance degradation of the LiCoO 2 -PEO battery originates from the strong oxidizing ability of LiCoO 2 after delithiation at high voltages, which accelerates the decomposition of PEO and drives the self-oxygen-release of LiCoO 2 , leading to the unceasing growth of CEI and the destruction of the LiCoO 2 surface. When LiCoO 2 is well coated or a stable cathode LiMn 0.7 Fe 0.3 PO 4 is used, a substantially improved electrochemical performance can be achieved, with 88.6% capacity retention after 50 cycles for Li 1.4 Al 0.4 Ti 1.6 (PO 4 ) 3 coated LiCoO 2 and 90.3% capacity retention after 100 cycles for LiMn 0.7 Fe 0.3 PO 4 . The results suggest that, when paired with stable cathodes, the PEO-based solid polymer electrolytes could be compatible with high voltage operation.

25 ENERGY STORAGE↗

Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling as Catalysts for Next-Generation Breakthroughs

The Presidential Symposium (PRES) at the 2025 Fall Meeting, hosted by the President’s Office and Energy and Fuels Division, American Chemical Society (ACS) in Washington, DC, brought together a diverse group of chemists, engineers, and materials scientists working in battery materials & systems, automation and artificial intelligence from academia, industry, and national laboratories. The accelerating demand for high-performance, scalable, and sustainable energy storage has catalyzed a paradigm shift in how materials are dis-covered, devices are engineered, and systems are optimized. This Presidential Symposium, entitled “Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling Driving Next-Gen Breakthroughs”, brings together global leaders to unveil transformative strategies anchored in the AAA framework: Artificial Intelligence, Automation, and Advanced Modeling. Artificial Intelligence is redefining the frontiers of energy storage by enabling predictive design, real-time optimization, and intelligent control across diverse chemistries and architectures. Automation is streamlining the synthesis, characterization, and testing of battery materials, dramatically accelerating innovation cycles and unlocking scalable solutions for grid and mobility applications. Advanced Modeling, spanning atomic to system-level scales, provides unprecedented insight into electrochemical dynamics, degradation pathways, and thermal behavior, particularly when coupled with physics-informed machine learning and digital twin technologies. Digital twins, in turn, leverage the AAA framework by integrating real-time data, physics-based models, and AI predictions into dynamic virtual replicas, enabling proactive diagnostics, optimization, and system resilience. Together, these synergistic pillars are not only re-shaping the scientific landscape but also forging a new era of reproducible, data-driven, and resilient energy storage innovation. In conclusion, this symposium marks a pivotal moment in the convergence of computational intelligence and experimental rigor, charting the course for next-generation breakthroughs in lithium-ion, solid-state, and flow battery technologies.

Artificial Intelligence (AI)↗

Skyrmion-skyrmionium phase separation and laning transitions via spin-orbit torque currents

Many driven binary systems can exhibit laning transitions when the two species have different mobilities, such as colloidal particles with opposite charges in electric fields. Another example is pedestrian or active-matter systems, where particles moving in opposite directions form a phase-separated state that enhances the overall mobility. In this work, we use atomistic simulations to demonstrate that mixtures of skyrmions and skyrmioniums also exhibit pattern formation and laning transitions. Skyrmions move more slowly and at a finite skyrmion Hall angle compared to skyrmioniums, which move faster and without a skyrmion Hall effect. At low drives, the system forms a partially jammed phase where the skyrmioniums are dragged by the surrounding skyrmions, resulting in a finite angle of motion for the skyrmioniums. At higher drives, the system transitions into a laned state, but unlike colloidal systems, the lanes in the skyrmion-skyrmionium mixture are tilted relative to the driving direction due to the intrinsic skyrmion Hall angle. In the laned state, the skyrmionium angle of motion is reversed when it aligns with the tilted lane structure. At even higher drives, the skyrmioniums collapse into skyrmions. Below a critical skyrmion density, both textures can move independently with few collisions, but above this density, the laning state disappears entirely, and the system transitions to a skyrmion-only state. We map out the velocity and Hall responses of the different textures and identify three distinct phases: partially jammed, laned, and skyrmion-only moving crystal states. In conclusion, we compare our results to recent observations of tilted laning phases in pedestrian flows, where chiral symmetry breaking in the particle interactions leads to similar behavior.

36 MATERIALS SCIENCE↗

Trap Passivation for Reducing On-Resistance and Saturation Voltage in Wafer-Bonded InGaAs-Channel/GaN-Drain Vertical FETs

High frequency and high power are the driving forces behind semiconductor transistor technology. However, conventional devices have the tradeoff of either being high speed or high breakdown—but not both. Wafer-bonded current aperture vertical electron transistors (BAVETs) help eliminate the tradeoff by combining a high-speed III-As channel to a high-breakdown III-N drift region. The device presented herein comprises of an InAlAs gate-barrier/InGaAs channel, wafer-bonded to an InGaN/GaN drift region, with the InGaAs/InGaN interface referred to as the wafer-bonded interface (WBI). The electronic behavior of WBIs is yet less known but necessary in realizing the potential of a BAVET. Herein, strong trap activity at the WBI is shown to be the cause of abnormally high saturation voltage ( V DS_SAT ) in BAVETs. The traps cause unintentional space charge (SC) region in the drain region of the device. This causes a drain resistance, a higher ON-resistance ( R ON ), and a higher V DS_SAT . Here, the challenge is overcome by hydrogen passivation of traps at WBI by using a p-doping for the InAlAs layer, which reduces the trap-charge concentration at the WBI. Consequently, the width of the SC region is reduced and a reduction in V DS_SAT is demonstrated, wherein it reduces from >12 to 5 V.

36 MATERIALS SCIENCE↗

Enhanced heat transfer combustor technology, subtasks 1 and 2, tast C.1

Analytical and experimental studies are being conducted for NASA to evaluate means of increasing the heat extraction capability and service life of a liquid rocket combustor. This effort is being conducted in conjunction with other tasks to develop technologies for an advanced, expander cycle, oxygen/hydrogen engine planned for upper stage propulsion applications. Increased heat extraction, needed to raise available turbine drive energy for higher chamber pressure, is derived from combustion chamber hot gas wall ribs that increase the heat transfer surface area. Life improvement is obtained through channel designs that enhance cooling and maintain the wall temperature at an accepatable level. Laboratory test programs were conducted to evaluate the heat transfer characteristics of hot gas rib and coolant channel geometries selected through an analytical screening process. Detailed velocity profile maps, previously unavailable for rib and channel geometries, were obtained for the candidate designs using a cold flow laser velocimeter facility. Boundary layer behavior and heat transfer characteristics were determined from the velocity maps. Rib results were substantiated by hot air calorimeter testing. The flow data were analytically scaled to hot fire conditions and the results used to select two rib and three enhanced coolant channel configurations for further evaluation.

Baily, R. D.↗

Trade Studies of Space Launch Architectures using Modular Probabilistic Risk Analysis

A top-down risk assessment in the early phases of space exploration architecture development can provide understanding and intuition of the potential risks associated with new designs and technologies. In this approach, risk analysts draw from their past experience and the heritage of similar existing systems as a source for reliability data. This top-down approach captures the complex interactions of the risk driving parts of the integrated system without requiring detailed knowledge of the parts themselves, which is often unavailable in the early design stages. Traditional probabilistic risk analysis (PRA) technologies, however, suffer several drawbacks that limit their timely application to complex technology development programs. The most restrictive of these is a dependence on static planning scenarios, expressed through fault and event trees. Fault trees incorporating comprehensive mission scenarios are routinely constructed for complex space systems, and several commercial software products are available for evaluating fault statistics. These static representations cannot capture the dynamic behavior of system failures without substantial modification of the initial tree. Consequently, the development of dynamic models using fault tree analysis has been an active area of research in recent years. This paper discusses the implementation and demonstration of dynamic, modular scenario modeling for integration of subsystem fault evaluation modules using the Space Architecture Failure Evaluation (SAFE) tool. SAFE is a C++ code that was originally developed to support NASA s Space Launch Initiative. It provides a flexible framework for system architecture definition and trade studies. SAFE supports extensible modeling of dynamic, time-dependent risk drivers of the system and functions at the level of fidelity for which design and failure data exists. The approach is scalable, allowing inclusion of additional information as detailed data becomes available. The tool performs a Monte Carlo analysis to provide statistical estimates. Example results of an architecture system reliability study are summarized for an exploration system concept using heritage data from liquid-fueled expendable Saturn V/Apollo launch vehicles.

Mathias, Donovan L.↗

Heats of Segregation of BCC Metals Using Ab Initio and Quantum Approximate Methods

Many multicomponent alloys exhibit surface segregation, in which the composition at or near a surface may be substantially different from that of the bulk. A number of phenomenological explanations for this tendency have been suggested, involving, among other things, differences among the components' surface energies, molar volumes, and heats of solution. From a theoretical standpoint, the complexity of the problem has precluded a simple, unified explanation, thus preventing the development of computational tools that would enable the identification of the driving mechanisms for segregation. In that context, we investigate the problem of surface segregation in a variety of bcc metal alloys by computing dilute-limit heats of segregation using both the quantum-approximate energy method of Bozzolo, Ferrante and Smith (BFS), and all-electron density functional theory. In addition, the composition dependence of the heats of segregation is investigated using a BFS-based Monte Carlo procedure, and, for selected cases of interest, density functional calculations. Results are discussed in the context of a simple picture that describes segregation behavior as the result of a competition between size mismatch and alloying effects

Good, Brian↗

Rapid Cycle Amine 4.0 System Development

Carbon dioxide (CO2) and humidity control is a key function of the spacesuit Portable Life Support Subsystem (PLSS). The latest spacesuit design utilizes a pressure swing bed containing a solid amine sorbent to scrub CO2 and humidity produced by the crewmember from the ventilation loop. The solid amine sorbent removes CO2 and humidity from the ventilation loop through a chemisorption mechanism. Simultaneously, CO2 and humidity are desorbed to vacuum via the two-bed pressure swing system during operation. This continuous regeneration allows for longer Extravehicular Activity (EVA) times while minimizing maintenance, consumables, and power usage. This concept has been in development for over 20 years, during which many prototypes and design iterations have been fabricated and evaluated. This paper discusses the recent Rapid Cycle Amine (RCA) design, development, and testing that has been done to advance the technology. The most recent fabrication is the RCA 3.0. It was delivered to NASA Johnson Space Center in 2015 and has since been tested at the component level and at the integrated PLSS level. The purpose of the component level testing was to understand CO2 removal capacity, end-of-life performance, and establish a baseline performance prior to integrated testing. The RCA 3.0 was integrated into the Exploration Extravehicular Mobility Unit (xEMU) PLSS for a comprehensive Design Verification Test (DVT) series. The integrated testing provided the benefit of characterizing the impact performance degradation has on the system. Many of the RCA requirements were developed through analysis, based on the limitations of the PLSS and, in some cases, assumptions about the system and flow behavior. Integrated testing was an opportunity to validate those requirements and assumptions. While the RCA 3.0 was being tested, the next design iteration, RCA 4.0, was under development. The RCA 4.0 preliminary design phase began in late-2019 and shortly after the Preliminary Design Review, the critical design phase began in 2021. The design work has concluded with the completion of a Pre-Manufacturing Review in 2022. This paper provides an overview of the RCA 4.0 system design, summarizes the results of integrated RCA 3.0 testing, and discusses the pertinence of driving requirements such as mass, volume, and power consumption.

Kelsey Bloom↗