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At least 307 records · Page 17

Atomic Force Microscope Observation of Growth and Defects on As-Grown (111) 3C-SiC Mesa Surfaces

This paper presents experimental atomic force microscope (AFM) observations of the surface morphology of as-grown (111) silicon-face 3C-SiC mesa heterofilms. Wide variations in 3C surface step structure are observed as a function of film growth conditions and film defect content. The vast majority of as-grown 3C-SiC surfaces consisted of trains of single bilayer height (0.25 nm) steps. Macrostep formation (i.e., step-bunching) was rarely observed, and then only on mesa heterofilms with extended crystal defects. As supersaturation is lowered by decreasing precursor concentration, terrace nucleation on the top (111) surface becomes suppressed, sometimes enabling the formation of thin 3C-SiC film surfaces completely free of steps. For thicker films, propagation of steps inward from mesa edges is sometimes observed, suggesting that enlarging 3C mesa sidewall facets begin to play an increasingly important role in film growth. The AFM observation of stacking faults (SF's) and 0.25 nm Burgers vector screw component growth spirals on the as-grown surface of defective 3C films is reported.

Neudeck, Philip G.↗

Some easily analyzable convolutional codes

Convolutional codes have played and will play a key role in the downlink telemetry systems on many NASA deep-space probes, including Voyager, Magellan, and Galileo. One of the chief difficulties associated with the use of convolutional codes, however, is the notorious difficulty of analyzing them. Given a convolutional code as specified, say, by its generator polynomials, it is no easy matter to say how well that code will perform on a given noisy channel. The usual first step in such an analysis is to computer the code's free distance; this can be done with an algorithm whose complexity is exponential in the code's constraint length. The second step is often to calculate the transfer function in one, two, or three variables, or at least a few terms in its power series expansion. This step is quite hard, and for many codes of relatively short constraint lengths, it can be intractable. However, a large class of convolutional codes were discovered for which the free distance can be computed by inspection, and for which there is a closed-form expression for the three-variable transfer function. Although for large constraint lengths, these codes have relatively low rates, they are nevertheless interesting and potentially useful. Furthermore, the ideas developed here to analyze these specialized codes may well extend to a much larger class.

Mceliece, R.↗

A tri-level optimization model for interdependent infrastructure network resilience against compound hazard events

Resilient operation of interdependent infrastructures against compound hazard events is essential for maintaining societal well-being. To address consequence assessment challenges in this problem space, we propose a novel policy-guided tri-level optimization model applied to a proof-of-concept case study with fuel distribution and transportation networks – encompassing one realistic network; one fictitious, yet realistic network; as well as networks drawn from three synthetic distributions. Mathematically, our approach takes the form of a defender-attacker-defender (DAD) model—a multi-agent tri-level optimization, comprised of a defender, attacker, and an operator acting in sequence. Here, in this study, our notional operator may choose proxy actions to operate an interdependent system comprised of fuel terminals and gas stations (functioning as supplies) and a transportation network with traffic flow (functioning as demand) to minimize unmet demand at gas stations. A notional attacker aims to hypothetically disrupt normal operations by reducing supply at the supply terminals, and the notional defender aims to identify best proxy defense policy options which include hardening supply terminals or allowing alternative distribution methods such as trucking reserve supplies. We solve our DAD formulation at a metropolitan scale and present practical defense policy insights against hypothetical compound hazards. We demonstrate the generalizability of our framework by presenting results for a realistic network; a fictitious, yet realistic network; as well as for three networks drawn from synthetic distributions. Additionally, we demonstrate the scalability of the framework by investigating runtime performance as a function of the network size. Steps for future research are also discussed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Metal hybridization in dilute-alloy catalysts promotes sintering resistance by decreasing surface mobility

Dilute-metal-alloy nanoparticles exhibit enhanced catalytic performance compared with monometallic nanoparticles for many reactions. Anecdotal reports indicate that very dilute alloying can also slow the sintering rates of supported nanoparticles, although this has not been rigorously assessed and cannot be explained using bulk descriptors such as metal melting temperature. Here, in this study, we utilize methanol synthesis reactivity, microscopy and in situ spectroscopy measurements to demonstrate that 1 atom% Pt addition to ~1–2-nm-diameter Cu (Pt 1 Cu 100 ) nanoparticles supported on SiO 2 dramatically decreases their sintering rates. Minimal sintering of Pt 1 Cu 100 nanoparticles is observed during aging in H 2 up to 700 °C versus 500 °C for Cu nanoparticles. Scanning tunnelling microscopy reveals that the addition of 0.01 monolayer of Pt to a Cu(110) surface decreases the detachment rate of undercoordinated atoms, demonstrating that dilute dopants can locally decrease the rate of the first step in nanoparticle sintering. Density functional theory calculations quantify the stabilization and predict other sinter-resistant dilute alloys. We find that the degree of host–dopant d-state hybridization correlates with decreased surface mobility, providing a mechanistic framework for designing sinter-resistant catalysts.

Finzel, Jordan [Univ. of California, Santa Barbara↗

APSO-enhanced algebraic derivative estimation approach for real-time traffic flow prediction on critical road sections during wildfire evacuation

In rapid-onset disaster scenarios such as wildfires, evacuation traffic often significantly deviates from historical patterns, rendering conventional data-driven forecasting methods less effective. To address this challenge, we propose an improved algebraic derivative estimation (ADE) incorporating particle swarm optimization (PSO) for real-time traffic flow prediction. Our approach dynamically adjusts the ADE prediction time window at each step by minimizing a cost function based on the mean and variance of accumulated forecasting errors within the window, thereby balancing bias and variability. We evaluate the method using traffic data from the January 2025 California wildfires, focusing on key road segments critical for large-scale evacuations. The results demonstrate that our approach surpasses established machine learning and deep learning models—XGBoost, LSTM, and GRU—in predictive accuracy and maintains high computational efficiency. Notably, the proposed method eliminates the need for offline model training. Moreover, rapid PSO-based tuning enables real-time deployment, which provides a crucial advantage in scenarios where evacuation timings and road closures change dynamically. In conclusion, these findings highlight the benefits of the PSO-enhanced ADE framework for emergency traffic management, where rapid, data-sparse forecasts are essential for effective evacuation planning.

Algebraic derivative estimation↗

The effect of TiO2 nanoparticles on antral follicles is dependent on the nanoparticle internalization rate

Abstract Titanium dioxide nanoparticles (TiO2 NPs) are among the most widely produced metallic NPs due to commercial and industrial applications in products including food, cosmetics, paints, and plastics. TiO2 NPs are released into the environment posing health risks for humans and wildlife. Widespread uses have raised concerns about the potential toxicity of TiO2 NPs in reproduction. The ovary is an important endocrine organ responsible for sex steroid hormone production and folliculogenesis. NPs can reach the ovary, but limited information is available regarding NP toxicity and its effects on ovarian antral follicles. Thus, we tested the hypothesis that exposure to TiO2 NP affects sex hormone synthesis, oxidative stress, and antioxidant response in ovarian antral follicles in vitro. In addition, we characterized the NP internalization in the antral follicles over time to determine any association between NP internalization and effects on the antral follicle. Antral follicles were exposed to vehicle control or TiO2 NPs (5, 25, and 50 µg/ml) for 96 h. The lowest NP concentration (5 µg/ml) showed no internalization and no effects in antral follicles. The 25-µg/ml concentration had the highest internalization rate, leading to increased mRNA ratio of Bax to Bcl2. Interestingly, the highest concentration (50 µg/ml) showed lower internalization compared with the 25 µg/ml, with altered levels of steroidogenic involved genes and increased levels of progesterone and testosterone compared with control. In conclusion, these data suggest that TiO2 NP is internalized in antral follicles as the first step process in impairing follicle functions.

Santacruz-Márquez, Ramsés (ORCID:0000000225239064)↗

Improved energies and local energies with weighted variational Monte Carlo

Neural network parametrizations have increasingly been used to represent the ground and excited states in variational Monte Carlo (VMC) with promising results. However, traditional VMC methods only optimize the wave function in regions of peak probability. The wave function is uncontrolled in the tails of the probability distribution, which can limit the accuracy of the trained wave function. To improve the approximation accuracy in the probability tails, this paper interprets VMC as a gradient flow in the space of wave functions, followed by a projection step. From this perspective, arbitrary probability distributions can be used in the projection step, allowing the user to prioritize accuracy in different regions of state space. Motivated by this theoretical perspective, the paper tests a weighted VMC method on the antiferromagnetic Heisenberg model for a periodic spin chain. Compared to traditional VMC, weighted VMC reduces the error in the ground state energy by a factor of 2, and it reduces the errors in the local energies away from the mode by large factors of 10 2 –10 4 .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Scalable multiplexed machine learning gas sensor chips for food classification

Multiplexed gas sensor arrays combined with machine learning have unlocked previously inaccessible applications for scent-based sensing. Current platforms are limited by overlapping sensing materials with similar compositions, leading to highly correlated responses, or multistep deposition processes that hinder scalability. In this work, we developed a 16-element monolithic chip with fully distinct sensing layers, enabling a truly heterogeneous array. The system consists of highly sensitive carbon nanotube field effect transistors that are functionalized through a single-step microdispensing method compatible with automated pipetting systems. The resulting chip produces characteristic signal patterns in response to object-specific scent profiles and, when combined with machine learning algorithms, can perform automated object identification. We demonstrate the classification of 16 different objects, including food spoilage and nut allergens, with a 92.6% overall prediction accuracy.

Bassil, Carla [University of California, Berkeley,↗

The MVM imaging system and its spacecraft interactions

The present work describes the main considerations and steps taken in determining the functional design of the imaging system of the Mariner Venus/Mercury (MVM) spacecraft and gives examples of some of the interactions between the spacecraft and the imaging instrument during the design and testing phases. Stringent cost and scheduling constraints dictated the use of the previous Mariner 9 dual-camera TV system. The TV parameters laid the groundwork for the imaging definition. Based on the flyby distances from Venus and Mercury and the goal of surface resolution better than 500 meters per sample pair, calculation was performed on focal length, format size, planetary coverage, and data rates. Some problems encountered in initial mechanical operation and as a result of spacecraft drift during the mission are also discussed.

Vescelus, F. E.↗

Calculation of charge-state ratios for satellite Tor I

The diffusion of ions in a satellite plasma torus is presently modeled in terms of a one-dimensional random walk in which the particle source is at 0, the particle sink is at an N value that is an integer greater than 2, and the scale size of the diffusion cell is unity. The probability distribution function of the number of steps to exit for an ion is obtained and used in a model which incorporates ionization by electron impact to derive steady state expressions for the ratio of doubly to singly ionized ions, as well as the total number of ions in the torus. The results thus obtained are applied to the torus of the Jovian satellite Io, in order to predict mean residence times for sulfur and oxygen ions.

Summers, D.↗

A new algorithm for modeling friction in dynamic mechanical systems

A method of modeling friction forces that impede the motion of parts of dynamic mechanical systems is described. Conventional methods in which the friction effect is assumed a constant force, or torque, in a direction opposite to the relative motion, are applicable only to those cases where applied forces are large in comparison to the friction, and where there is little interest in system behavior close to the times of transitions through zero velocity. An algorithm is described that provides accurate determination of friction forces over a wide range of applied force and velocity conditions. The method avoids the simulation errors resulting from a finite integration interval used in connection with a conventional friction model, as is the case in many digital computer-based simulations. The algorithm incorporates a predictive calculation based on initial conditions of motion, externally applied forces, inertia, and integration step size. The predictive calculation in connection with an external integration process provides an accurate determination of both static and Coulomb friction forces and resulting motions in dynamic simulations. Accuracy of the results is improved over that obtained with conventional methods and a relatively large integration step size is permitted. A function block for incorporation in a specific simulation program is described. The general form of the algorithm facilitates implementation with various programming languages such as FORTRAN or C, as well as with other simulation programs.

Hill, R. E.↗

Chaotic appearance of the AE index

Results are reported from a stochastic analysis of a 5-day time series of the geomagnetic AE index during an active period. The original data, the power spectrum, and the autocorrelation function are shown, and the steps in the analysis are described in detail. It is found that the autocorrelation time scale is about 50 min, giving a correlation dimension (for the construction of a time series of m-dimensional vectors) of 2.4. This result is consistent with either colored-noise or deterministic-chaos magnetosphere models, indicating the need for further investigation.

Shan, L.-H.↗

Astrometry using the Hubble Space Telescope fine guidance sensors

Plans for the use of the three fine guidance sensors (FGSs) of the NASA Hubble Space Telescope for direct astrometric observations are reviewed. Topics addressed include the optical elements and detectors of the FGSs, the basic and astrometric operating modes of the FGSs, spacecraft pointing control during astrometric observations, and the astrometric data-reduction software provided to HST users. Particular attention is given to the calibration procedures for optical-field angle distortion, the plate scale, filter-wedge errors, lateral color effects, secular changes, velocity aberration, and transfer function. Also discussed are the steps being taken to verify the HST orbit. It is pointed out that the performance of the interferometric FGSs should not be affected by the focusing problems of the main HST instrument.

Duncombe, Raynor L.↗

A numerical solution method for acoustic radiation from axisymmetric bodies

A new and very efficient numerical method for solving equations of the Helmholtz type is specialized for problems having axisymmetric geometry. It is then demonstrated by application to the classical problem of acoustic radiation from a vibrating piston set in a stationary infinite plane. The method utilizes 'Green's Function Discretization', to obtain an accurate resolution of the waves using only 2-3 points per wave. Locally valid free space Green's functions, used in the discretization step, are obtained by quadrature. Results are computed for a range of grid spacing/piston radius ratios at a frequency parameter, omega R/c(sub 0), of 2 pi. In this case, the minimum required grid resolution appears to be fixed by the need to resolve a step boundary condition at the piston edge rather than by the length scale imposed by the wave length of the acoustic radiation. It is also demonstrated that a local near-field radiation boundary procedure allows the domain to be truncated very near the radiating source with little effect on the solution.

Caruthers, John E.↗

Analyzing Spacecraft Telecommunication Systems

Multi-Mission Telecom Analysis Tool (MMTAT) is a C-language computer program for analyzing proposed spacecraft telecommunication systems. MMTAT utilizes parameterized input and computational models that can be run on standard desktop computers to perform fast and accurate analyses of telecommunication links. MMTAT is easy to use and can easily be integrated with other software applications and run as part of almost any computational simulation. It is distributed as either a stand-alone application program with a graphical user interface or a linkable library with a well-defined set of application programming interface (API) calls. As a stand-alone program, MMTAT provides both textual and graphical output. The graphs make it possible to understand, quickly and easily, how telecommunication performance varies with variations in input parameters. A delimited text file that can be read by any spreadsheet program is generated at the end of each run. The API in the linkable-library form of MMTAT enables the user to control simulation software and to change parameters during a simulation run. Results can be retrieved either at the end of a run or by use of a function call at any time step.

Kordon, Mark↗

The Use of Solar Heating and Heat Cured Polymers for Lunar Surface Stabilization

Dust ejecta can affect visibility during a lunar landing, erode nearby coated surfaces and get into mechanical assemblies of in-place infrastructure. Regolith erosion was observed at many of the Apollo landing sites. This problem needs to be addressed at the beginning of the lunar base missions, as the amount of infrastructure susceptible to problems will increase with each landing. Protecting infrastructure from dust and debris is a crucial step in its long term functionality. A proposed way to mitigate these hazards is to build a lunar launch pad. Other areas of a lunar habitat will also need surface stabilization methods to help mitigate dust hazards. Roads would prevent dust from being lifted during movement and dust free zones might be required for certain areas critical to crew safety or to critical science missions. Work at NASA Kennedy Space Center (KSC) is investigating methods of stabilizing the lunar regolith including: sintering the regolith into a solid and using heat or UV cured polymers to stabilize the surface. Sintering, a method in which powders are heated until fusing into solids, has been proposed as one way of building a Lunar launch/landing pad. A solar concentrator has been built and used in the field to sinter JSC-1 Lunar stimulant. Polymer palliatives are used by the military to build helicopter landing pads and roads in dusty and sandy areas. Those polymers are dispersed in a solvent (water), making them unsuitable for lunar use. Commercially available, solvent free, polymer powders are being investigated to determine their viability to work in the same way as the solvent borne terrestrial analog. This presentation will describe the ongoing work at KSC in this field. Results from field testing will be presented. Physical testing results, including compression and abrasion, of field and laboratory prepared samples will be presented.

Hintze, Paul↗

Low-Thrust Trajectory Optimization with Simplified SQP Algorithm

The problem of low-thrust trajectory optimization in highly perturbed dynamics is a stressing case for many optimization tools. Highly nonlinear dynamics and continuous thrust are each, separately, non-trivial problems in the field of optimal control, and when combined, the problem is even more difficult. This paper de-scribes a fast, robust method to design a trajectory in the CRTBP (circular restricted three body problem), beginning with no or very little knowledge of the system. The approach is inspired by the SQP (sequential quadratic programming) algorithm, in which a general nonlinear programming problem is solved via a sequence of quadratic problems. A few key simplifications make the algorithm presented fast and robust to initial guess: a quadratic cost function, neglecting the line search step when the solution is known to be far away, judicious use of end-point constraints, and mesh refinement on multiple shooting with fixed-step integration.In comparison to the traditional approach of plugging the problem into a “black-box” NLP solver, the methods shown converge even when given no knowledge of the solution at all. It was found that the only piece of information that the user needs to provide is a rough guess for the time of flight, as the transfer time guess will dictate which set of local solutions the algorithm could converge on. This robustness to initial guess is a compelling feature, as three-body orbit transfers are challenging to design with intuition alone. Of course, if a high-quality initial guess is available, the methods shown are still valid.We have shown that endpoints can be efficiently constrained to lie on 3-body repeating orbits, and that time of flight can be optimized as well. When optimizing the endpoints, we must make a trade between converging quickly on sub-optimal endpoints or converging more slowly on end-points that are arbitrarily close to optimal. It is easy for the mission design engineer to adjust this trade based on the problem at hand.The biggest limitation to the algorithm at this point is that multi-revolution transfers (greater than 2 revolutions) do not work nearly as well. This restriction comes in because the relationship between node 1 and node N becomes increasingly nonlinear as the angular distance grows. Trans-fers with more than about 1.5 complete revolutions generally require the line search to improve convergence. Future work includes: Comparison of this algorithm with other established tools; improvements to how multiple-revolution transfers are handled; parallelization of the Jacobian computation; in-creased efficiency for the line search; and optimization of many more trajectories between a variety of 3-body orbits.

Parrish, Nathan L.↗

Creating a Wastewater Technology ‘Toolbox’ for Space Exploration ECLSS

Life Support Systems (LSS) are essential for manned spaceflight; without them, humans would not survive. Upcoming long-duration missions demand robust environmental control LSS (ECLSS) due to their insolation and limited prospect for immediate resupply. As part of LSS, water purification systems will require high reliability, sustainability, and efficiency due to transport mass limitations, because routine water delivery will be very difficult and costly to resupply future habitats. This suggests a highly effective treatment method and reuse of every wastewater source. A variety of wastewater streams are generated by crew, and although not all are currently treated, habitat success will require each stream to be treated and utilized as a ‘resource’ rather than 'waste’. These wastewater streams include human wastewater (urine, feces), food waste (plate waste, inedible plant biomass), humidity condensate, hygiene water (shower, oral, handwash), and laundry. Proven technologies are often relied upon due to long-term operations. For future, longer-term missions, this paradigm must shift to include technologies based on meeting mission requirements rather than sacrificing productivity in lieu of proven existing technology capabilities. Many physical, chemical, and biological water-processing technologies are proven and established for terrestrial applications. Herein, these technologies were collected into a ‘toolbox’ to perform possible functions towards effective water purification steps in reduced gravity. Selection criteria are dependent on approach (physical, chemical, or biological), complexity/components, terrestrial performance, and potential applicability to space life support. Utilization of this ‘toolbox’ approach provides a streamline methodology for technology development and down-selection into future architecture in direct response to the dynamic space life support requirements. Establishing the ‘toolbox’ also provides organized and efficient identification of the most appropriate technologies. From there, the technologies with the largest potential to be configured for mission requirements can be further developed and appropriately assessed. This presentation seeks to provide a comprehensive review of space life support water purification requirements and challenges, as well as to present a ‘toolbox’ methodology of available technologies to aid in the difficult process of selecting appropriate LSS water purification for short and long-term NASA mission architectures.

Luke Roberson↗