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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 109 records · Page 6

Resilient Operation of Power Distribution Systems Using MPC-Based Critical Service Restoration

Power distribution systems are more prone to disruptions and cause most power system outages. We propose a service restoration technique to recover the system service (electricity delivery) following an extreme event-triggered substation outage. The proposed technique considers the problem of controlling distributed energy resources (DERs) of a distribution system with the objective of achieving maximum load pick up while satisfying network flow and voltage constraints. The problem is formulated as a model predictive control (MPC), where a linearized optimal power flow (OPF) model is employed to describe the network. The formulation is augmented with a ramping (up) reserve product for the DERs to ensure an upward monotonic load restoration as time evolves. We perform simulations considering the IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage devices. We demonstrate the efficacy of the devised technique in restoring the system loads monotonically, without shedding previously restored loads. We also show the benefit of co-optimization of power and reserve products for DERs on service restoration. In addition, the capability of the technique in regulating nodal voltages and reducing renewable power curtailment is demonstrated.

61 RADIATION PROTECTION AND DOSIMETRY↗

Multimodal communication system

A multimodal communication system includes a vehicle controller that controls one or more systems or subsystems of an unmanned vehicle. The communication controller manages communication and logical access to the unmanned vehicle. One or more sensors in communication with the communication controller detects and measures physical properties in proximity to the unmanned vehicle. Transceivers receive the unmanned vehicle commands that are transmitted simultaneously or concurrently and a monotonic generator generates a monotonic object each time the unmanned vehicle's operating state changes. The communication controller executes the first unmanned vehicle command received that has the correct cryptographic hash validating knowledge of the unmanned vehicle's current operating state.

Duncan, Andrew M.↗

Sampling Size Optimization for Bioburden Density Estimation in Planetary Protection

Planetary protection (PP) is a discipline that focuses on minimizing the biological contamination of spacecraft to ensure compliance with international policy. Precise estimation of bioburden - the total number of microbes in or on spacecraft hardware – and the bioburden density are of utmost importance for PP. Such estimation is the way concordance with requirements is demonstrated, and it is critical for quantifying the potential risk of inadvertently contaminating other planetary bodies. Although a suite of molecular techniques have been used to thoroughly characterize and profile the microbiome of various cleanroom environments and spacecraft, the gold standard remains the physical enumeration of microbes via culturing of samples directly taken from spacecraft and associated surfaces. However, due to technical, budgetary, and programmatic constraints, only a manageable portion (around 10%) of the entire spacecraft surface is directly sampled with cotton swabs or wipes. To generate the bioburden current best estimate (CBE) for components not directly verifiable, the accepted approach is to apply a NASA-defined bioburden estimate based on the components’ manufacturing or assembly environment. This approach utilizes a prespecified bioburden density estimation that applies a maximum value across the total surface area of the specified component. For hardware components that underwent similar assembly processes, an implied bioburden is adopted for all components, based on a direct verification of a representative component within the same lot. Once all components have a CBE, the bioburden estimates are generated. In previous publication [ 1], we have shown that statistical risks quantifying the accuracy of the estimates for sampled, prespecified, and implied components can be derived and ranked. For mean squared error (MSE) function, the risks are available analytically and hence a cost function can be obtained to optimize the risks with respect to the sampling area and sampling cost. Since the sampling area and sampling cost are two complimentary variables, their sum will have a well-defined minimum. This paper presents the multivariate optimization of the integrated risk of an empirical Bayes estimator to determine the optimal sampling schedule for a given number of components. It is assumed that given a number of components, N, the bioburden density for each component can either be sampled, implied, or prespecified. The multivariate optimization searches through different options to sample, imply or prespecify the bioburden density for a component, and account for the component’s surface area and cost of sampling. The idea of the optimization is based on the observation that the statistical risk of using an estimator is a monotonically decreasing function of the sampled area. The larger the sampled area, the lower the risk of using the estimator as the estimator becomes more and more accurate as the sampling area increases. On the other hand, the cost of sampling is monotonically increasing as the sampled surface grows. This makes the risk and total cost of sampling complimentary variables which can be counterbalanced to achieve an optimal overall value with respect to the sampled surface. In this paper, the integrated risk has been used to quantify the accuracy of the estimator. This risk has been selected because it depends on neither the true value of the parameter nor on the collected data. The cost of each sample was also available to obtain the total cost of sampling of N components. The paper will present the results based on computer-simulated data as well as the data collected during the InSight mission. The computer-simulated data have N components with randomly generated total areas and each component assigned to one of the three categories according to the method of estimating of bioburden density: sampled, implied, or prespecified. The cost of sampling is also available. The cost of sampling is estimated based on a cost model provided by the planetary protection group at JPL. For this paper, the overall cost was assumed to be a linear function of exposure. The optimization process finds the allocation of the components to the three categories that minimizes the tradeoff between integrated risk and total cost. For the InSight data, a set of components is selected representing all three categories, and optimization is performed to determine if the performed allocation was optimal or if a better allocation could have been obtained. To the best of our knowledge, this work is the first attempt not only perform an accurate estimation of bioburden density but also do it in an optimal way.

97 - MATHEMATICS AND COMPUTING↗

On the Sampling-Based Computation of Nash Equilibria Under Uncertainty via the Nikaido–Isoda Function

We consider the computation of an equilibrium of a stochastic Nash equilibrium problem, where the player objectives are assumed to be L 0 -Lipschitz continuous and convex, given rival decisions with convex and closed player-specific feasibility sets. To address this problem, we consider minimizing a suitably defined value function defined using the Nikaido–Isoda function. Such an avenue does not necessitate either monotonicity properties of the concatenated gradient map or potentiality requirements on the game but does require a suitable regularity requirement under which a stationary point is a Nash equilibrium. We design and analyze a sampling-enabled projected-gradient-response method, reliant on inexact resolution of a player-level best-response subproblem. Here, by deriving suitable Lipschitzian guarantees on the value function, we derive both asymptotic guarantees for the sequence of generated iterates as well as rate and complexity guarantees for computing a stationary point by appropriate choices of the sampling rate and inexactness sequence.

Nikaido-Isoda function↗

Virtual Time III, Part 1: Unified Virtual Time Synchronization for Parallel Discrete Event Simulation

Algorithms for synchronization of parallel discrete event simulation have historically been divided between conservative methods that require lookahead but not rollback, and optimistic methods that require rollback but not lookahead. In this paper we present a new approach in the form of a framework called Unified Virtual Time (UVT) that unifies the two approaches, combining the advantages of both within a single synchronization theory. Whenever timely lookahead information is available, a logical process (LP) executes conservatively using an irreversible event handler. When lookahead information is not available the LP does not block, as it would in a classical conservative execution, but instead executes optimistically using a reversible event handler. The switch from conservative to optimistic synchronization and back is decided on an event-by-event basis by the simulator, transparently to the model code. UVT treats conservative synchronization algorithms as optional accelerators for an underlying optimistic synchronization algorithm, enabling the speed of conservative execution whenever it is applicable, but otherwise falling back on the generality of optimistic execution. We describe UVT in a novel way, based on fundamental invariants, monotonicity requirements, and synchronization rules. UVT permits zero-delay messages and pays careful attention to tie-handling using superposition. We prove that under fairly general conditions a UVT simulation always makes progress in virtual time. This is Part 1 of a trio of papers describing the UVT framework for PDES, mixing conservative and optimistic synchronization and integrating throttling control.

97 MATHEMATICS AND COMPUTING↗

Ionic‐Liquid‐Gating‐Induced Hydrogenation in Epitaxial Strontium Ferrite

Abstract Incorporating hydrogen into complex oxides holds promise for discovering exotic phenomena and novel functionalities by promoting couplings between ion and lattice/charge/spin/orbital degrees of freedom. Here, electrolyte gating‐driven hydrogenation is investigated in epitaxial brownmillerite SrFeO 2.5 thin films in which the hydrogenation‐induced lattice distortion is qualitatively different from its counterpart SrCoO 2.5 . The achievable lattice expansion in hydrogenated SrFeO 2.5 is weaker than in SrCoO 2.5 and primarily occurs along the normal of the stacked octahedral FeO 6 and tetrahedral FeO 4 layers. Upon the substitution of Fe with Co, the lattice expansion monotonically increases with increase of Co/Fe ratio, implying an intrinsic difference in accommodating hydrogen between Fe‐ and Co‐based brownmillerites. Moreover, a net magnetic moment in hydrogenated SrFeO 2.5 films is observed above room temperature, which gradually weakens with the increase of Co substitution, suggesting a stronger canted magnetism in Fe‐based hydrogenated brownmillerites. This work clarifies the electrolyte gating‐driven hydrogenation mechanisms in brownmillerite SrFeO 2.5 epitaxial thin films and those with Co substitution, particularly the deterministic role of Co/Fe ratio in the evolution of structure and properties upon hydrogenation.

Chemistry↗

Temperature‐Dependent Crystallization in Two‐Step Perovskite Deposition Revealed by In Situ GIWAXS and Machine Learning‐Guided Analysis

The performance and stability of perovskite solar cells are strongly governed by the crystallization behavior of their active layer. In two-step sequential deposition, early-stage film formation plays a decisive role in determining final phase purity and device quality. Guided by a data-driven analysis of nearly 39 000 devices in the FAIR perovskite database, we identified solvent-mediated quenching and thermal processing as key variables affecting power conversion efficiency (PCE), particularly in two-step fabrication. Here, to investigate these effects in real time, we designed and implemented a custom-built, temperature-controlled spin-coating system, enabling precise thermal modulation during precursor deposition. Using this platform, we performed in situ GIWAXS measurements to study the crystallization dynamics of FA 0.5 MA 0.5 PbI 3 films over a temperature range of 30°C–90°C. Our results reveal a non-monotonic relationship between spin-coating temperature and α-phase formation, governed by the interplay between precursor interdiffusion, PbI 2 crystallinity, and δ-phase suppression. The custom thermal control enabled us to isolate and quantify these competing effects during the earliest stages of film formation, providing mechanistic insight into how spin-coating temperature governs both phase purity and kinetic pathways in two-step perovskite systems. Temperature-dependent SEM and photovoltaic device measurements further demonstrate that early-stage crystallization pathways directly translate into differences in morphology, charge-transport continuity, and device performance. These findings inform targeted strategies for optimizing deposition protocols to balance rapid nucleation, phase stability, and device performance.

Saadawy, Ahmed [King Fahd University of Petroleum ↗

Dihydroxyterephthalate—A Trojan Horse PET Counit for Facile Chemical Recycling

Abstract Here, low‐energy poly(ethylene terephthalate) (PET) chemical recycling in water: PET copolymers with diethyl 2,5‐dihydroxyterephthalate (DHTE) undergo selective hydrolysis at DHTE sites, autocatalyzed by neighboring group participation, is demonstrated. Liberated oligomeric subchains further hydrolyze until only small molecules remain. Poly(ethylene terephthalate‐ stat ‐2,5‐dihydroxyterephthalate) copolymers were synthesized via melt polycondensation and then hydrolyzed in 150–200 °C water with 0–1 wt% ZnCl 2 , or alternatively in simulated sea water. Degradation progress follows pseudo‐first order kinetics. With increasing DHTE loading, the rate constant increases monotonically while the thermal activation barrier decreases. The depolymerization products are ethylene glycol, terephthalic acid, 2,5‐dihydroxyterephthalic acid, and bis(2‐hydroxyethyl) terephthalate dimer, which could be used to regenerate virgin polymer. Composition‐optimized copolymers show a decrease of nearly 50% in the Arrhenius activation energy, suggesting a 6‐order reduction in depolymerization time under ambient conditions compared to that of PET homopolymer. This study provides new insight to the design of polymers for end‐of‐life while maintaining key properties like service temperature and mechanical properties. Moreover, this chemical recycling procedure is more environmentally friendly compared to traditional approaches since water is the only needed material, which is green, sustainable, and cheap.

36 MATERIALS SCIENCE↗

Cationic Copper Species Stabilized by Zinc during the Electrocatalytic Reduction of CO 2 Revealed by In Situ X‐Ray Spectroscopy

Abstract Advanced in situ X‐ray absorption spectroscopy characterization of electrochemically co‐electrodeposited bi‐element copper alloy electrodes shows that zinc yields the formation of a stable cationic Cu species during the electroreduction of CO 2 at high cathodic polarization. In contrast, the formation/stabilization of cationic Cu species in copper oxides, or doping Cu with another element, like Ni, is not possible. It is found that the pure and mixed Cu:Zn electrodes behave similarly in term of electrocatalytic selectivity to multi‐carbon products. At higher Zn concentrations the electrode behaves like the pure Zn catalyst, which indicates that the Cu cationic species do not have a significant influence on the selectivity to multi‐carbon products. It is found that in the non‐monotonically distribution of products is dominated in term of surface energy in which copper prefers the surface. Otherwise, this work highlights the importance of in situ characterization to uncover the mechanisms mediating the catalytic reactions in contrast to ex situ or post mortem analysis, which can be a source of misinterpretation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Temperature Dependence of Low‐Frequency Noise Characteristics of NiO x /β‐Ga 2 O 3 p–n Heterojunction Diodes

Temperature dependence of the low-frequency electronic noise in NiO x /β-Ga 2 O 3 p–n heterojunction diodes is reported. The noise spectral density is of the 1/f-type near room temperature but shows signatures of Lorentzian components at elevated temperatures and at higher current levels (f is the frequency). It is observed that there is an intriguing non-monotonic dependence of the noise on temperature near T = 380 K. The Raman spectroscopy of the device structure suggests material changes, which results in reduced noise above this temperature. The normalized noise spectral density in such diodes is determined to be on the order of 10 −14 cm 2 Hz −1 (f = 10 Hz) at 0.1 A cm −2 current density. In terms of the noise level, NiO x /β-Ga 2 O 3 p–n diodes perform excellently for new technology and occupy an intermediate position among devices of various designs implemented with different ultra-wide-bandgap semiconductors. The obtained results are important for understanding the electronic properties of NiO x /β-Ga 2 O 3 heterojunctions and contribute to the development of noise spectroscopy as the quality assessment tool for new electronic materials and device technologies.

1/f noise↗

Understanding and Tuning Magnetism in Layered Ising‐Type Antiferromagnet FePSe 3 for Potential 2D Magnet

Abstract Recent developments in 2D magnetic materials have motivated the search for new van der Waals magnetic materials, especially Ising‐type magnets with strong magnetic anisotropy. Fe‐based M P X 3 ( M = transition metal, X = chalcogen) compounds such as FePS 3 and FePSe 3 both exhibit an Ising‐type magnetic order, but FePSe 3 receives much less attention compared to FePS 3 . This work focuses on establishing the strategy to engineer magnetic anisotropy and exchange interactions in this less‐explored compound. Through chalcogen and metal substitutions, the magnetic anisotropy is found to be immune against S substitution for Se whereas tunable only with heavy Mn substitution for Fe. In particular, Mn substitution leads to a continuous rotation of magnetic moments from the out‐of‐plane direction toward the in‐plane. Furthermore, the magnetic ordering temperature displays non‐monotonic doping dependence for both chalcogen and metal substitutions but due to different mechanisms. These findings provide deeper insight into the Ising‐type magnetism in this important van der Waals material, shedding light on the study of other Ising‐type magnetic systems as well as discovering novel 2D magnets for potential applications in spintronics.

2D magnet↗

Baseplate Temperature–Dependent Vertical Composition Gradient in Pseudo–Bilayer Films for Printing Non–Fullerene Organic Solar Cells

Numerous previous reports on the sequential deposition (SD) technique have demonstrated that this approach can achieve a p–i–n active layer architecture with an ideal vertical composition gradient, which is one of the critical factors that can influence the physical processes that determine the photovoltaic performance of organic solar cells. Herein, a commonly used photovoltaic system comprised of PM6 as a donor and Y6 as an acceptor is investigated with respect to sequential blade–processing deposition to comprehensively explore the morphology characteristics as a function of baseplate temperature. A systematic study of the temperature–dependent blend morphology elucidates the SD–processed configuration merits and device physics behind temperature–controlled degree of vertical composition gradient, and constructs the temperature–microstructure–property relationship for the corresponding photovoltaic parameters. The result shows, as the temperature increases, the morphology of the active layer has undergone a distinct evolution from the pseudo–bulk heterojunction to a pseudo–planar heterojunction and then to a pseudo–planar bilayer, leading to a non–monotonic correlation between baseplate temperature and device performance. Further, this investigation not only reveals the importance of precisely controlling baseplate temperature for gaining vertical morphology control, but also provides a path toward rational optimization of device performance in the lab–to–fab transition.

14 SOLAR ENERGY↗

The Origin of Improved Performance in Boron‐Alloyed Silicon Nanoparticle‐Based Anodes for Lithium‐Ion Batteries

Stabilizing the solid electrolyte interphase (SEI) remains a key challenge for silicon‐based lithium‐ion battery anodes. Alloying silicon with secondary elements like boron has emerged as a promising strategy to improve the cycle life of silicon anodes, yet the underlying mechanism remains unclear. To address this knowledge gap, how boron concentration influences battery performance is systematically investigated. These results show a near‐monotonic increase in cycle lifetime with higher boron content, with boron‐rich electrodes significantly outperforming pure silicon. Additionally, silicon‐boron alloy anodes exhibit nearly three times longer calendar life than pure silicon. Through detailed mechanistic analysis, alternative contributing factors are systematically ruled out, and it is proposed that improved passivation arises from a strong permanent dipole at the nanoparticle surface. This dipole, formed by undercoordinated and highly Lewis acidic boron, creates a static, ion‐dense layer that stabilizes the electrochemical interface, reducing parasitic electrolyte decomposition and enhancing long‐term stability. These findings suggest that, within the SEI framework, the electric double layer is an important consideration in surface passivation. This insight provides an underexplored parameter space for optimizing silicon anodes in next‐generation lithium‐ion batteries.

25 ENERGY STORAGE↗

Design and operational considerations of catalytic membrane reactors for ammonia synthesis

Production of ammonia using hydrogen derived from renewable electricity instead of hydrocarbon reforming would dramatically reduce the carbon footprint of this commodity chemical. Novel technologies such as catalytic membrane reactors may potentially be more compatible with distributed ammonia production than the conventional Haber-Bosch process. Here, a reactor model is developed based on integrating a standard industrial iron catalyst into a catalytic membrane reactor (CMR) equipped with an inorganic membrane that is selective to NH 3 over N 2 /H 2 . CMR performance is studied as functions of wide ranges of membrane properties and operating conditions. Conversion and ammonia recovery are dictated principally by the ammonia permeance, and the benefits by using membranes become significant above 100 GPU = 3.4 × 10 –8 mol m –2 s –1 Pa –1 . To be effective, the CMR requires a minimum selectivity for ammonia of 10 over both nitrogen and hydrogen, and purity scales with the effective selectivity. Increasing the pressure of operation significantly improves all metrics, and at P = 30 bar with a quality membrane ammonia is almost completely recovered, enabling direct recycle of un-reacted hydrogen and nitrogen without need for recompression. Temperature drives conversion and scales monotonically without thermodynamic limitations in a CMR. Alternatively, the temperature may be reduced as low as 300°C while achieving conversion levels surpassing equilibrium limits at T = 400°C in a conventional reactor.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling salt adsorption in electrical double layer for capacitive deionization

Abstract This work presents an electrical double layer (EDL) model for capacitive deionization (CDI) by intercorrelating the salt adsorption, the electrode voltage, and the surface charge density. The counterion condensation is considered a crucial contribution to salt adsorption because of the high surface charge density in the charged micropores. The counterions condense when the surface charge density exceeds a critical value, which is predicted by the counterion condensation theory. The EDL model accurately correlates the NaCl salt adsorption and electrode voltage with various surface charge densities and well predicts the salt adsorption in a wide range of external salt concentrations. The EDL model reproduces the non‐monotonic relationship between the salt adsorption and the specific surface area observed in experiments and provides an explanation from the modeling perspective. Exhibiting superior accuracy and predictability for salt adsorption, the EDL model could serve as an enabling tool contributing to the development of CDI processes.

Lin, Yu‐Jeng↗

Relaxing the constant molar overflow assumption in distillation optimization

Abstract The constant molar overflow (CMO) framework, while useful for shortcut distillation models, assumes that all components have the same latent heats of vaporization. A simple transformation, from molar flows to latent‐heat flows, allows shortcut models to retain the mathematical simplicity of the CMO framework while accounting for different latent heats, resulting in the constant heat transport (CHT) framework for adiabatic distillation columns. Although several past works have already proposed this transformation in the literature, it has not been well utilized in recent times. In this article, we show the utility of this transformation in upgrading various applications such as identifying energy‐efficient multicomponent distillation configurations based on heat duty rather than surrogate vapor flow. The method transforms the diagram to a diagram. Furthermore, we derive new and insightful analytical results in distillation, such as cumulative latent‐heat stage fractions having monotonic profiles within a distillation column under the CHT framework.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Vibrational Properties of Pristine and Lithium-Intercalated Black Phosphorous under High-Pressure

Structural evolution of Li-intercalated and pristine black phosphorous (BP) under high-pressure (up to ≈8 GPa) is studied using in situ Raman spectroscopy. Even though both materials show a monotonic blueshift of the out-of-plane vibrational mode (A 1 g ) with pressure, Li-intercalated BP do not show a blueshift until a threshold pressure (2.4 GPa) is reached to compensate the structural expansion caused by intercalation. However, the in-plane modes (B 2g and A 2 g) in each sample respond differently. In the mid-pressure region, they both show redshifts which in Li-intercalated BP is also followed by abrupt blueshifts. Such behavior indicates pressure-induced structural reorganizations inside the material. Computational modeling reveals the existence of a process of P-P bond breaking and reforming in the system due to the redistribution of intercalated Li atoms under pressure. This work shows the significance of combined effect of pressure and intercalation on structural changes in the search for new phases of BP and other two-dimensional (2D) materials.

36 MATERIALS SCIENCE↗