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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Sulfur Conversion to Donor‐Acceptor Ladder Polymer Networks through Mechanochemical Nucleophilic Aromatic Substitution for Efficient CO 2 Photoreduction

The development of synthetic methods capable of converting elemental sulfur into conjugated porous sulfur‐rich polymers remains a great challenge, although direct utilization of this readily available feedstock can significantly enrich its uses and circumvent environmental problems during sulfur storage. Here, we report herein mechanochemical (MC) nucleophilic aromatic substitution (S N Ar) that enables sulfur conversion into thianthrene‐bridged porous ladder polymer networks with dense donor‐acceptor (D−A) molecular junctions. We demonstrate that the key lies in the generation of bent thianthrene units through a solid‐state ball‐milling condensation reaction between 1,2‐dihaloarenes and elemental sulfur. We also show that the assembling of D−A structural motifs into porous networks affords efficient visible‐light‐driven photocatalytic reduction of carbon dioxide (CO 2 ) with water (H 2 O) vapor, in the absence of any additional photosensitizer, sacrificial agents or cocatalysts. Exceptional photoinduced charge separation along with boosted exciton dissociation results in a high‐performance of carbon monoxide (CO) production rate of 306.1 μmol g −1 h −1 with near 100 % CO selectivity, which is accompanied by H 2 O oxidation to O 2 , as confirmed by both experimental and theoretical results. We anticipate this novel MC S N Ar approach will advance processing techniques for direct sulfur utilization and facilitate new possibilities for the synthesis of D−A ladder polymer networks with promising potential in photocatalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Thermodynamic Modeling of Complex Solid Solutions in the Lu-H-N System via Graph Neural Network Accelerated Monte Carlo Simulations

Metal hydrides are important across diverse applications, such as hydrogen storage, batteries, gas sensors, nuclear reactions, and high-temperature superconductivity. Previous computational studies of metal hydrides under extreme pressures, e.g., 𝑂⁡(10 2 ) ⁢GPa, usually treat them as stoichiometric compounds without considering interstitial lattice disorder. As pressures become more moderate in the 𝑂⁡(10 0 ) ⁢GPa and below range, hydrogen disorder at interstitial lattice sites becomes prominent, e.g., in the N-doped Lu hydride that was recently claimed superconducting near 1 GPa. Further adding compositional complexity from alloying and/or multielement interstitial occupation makes elucidating pressure- and temperature-dependent observables intractable by first-principles calculations alone. We therefore propose a lattice graph neural-network surrogate modeling approach to predict configuration- and pressure-dependent equation-of-state properties. Their efficiency permits Monte Carlo simulations to calculate Gibbs energies and pressure-dependent phase diagrams, thereby revealing insights into the synthesis conditions required for achieving desired phase equilibria. We demonstrate this concept for the compositionally complex cubic Lu(H,N,Va) 3 system where three constituents (hydrogen, nitrogen and vacancy) have disordered multielement interstitial occupancies and insights into pressure-dependent phase equilibria are critically needed, e.g., N-doping levels can significantly lower dehydrogenation temperatures and provide a new strategy to optimize hydrogen-storage alloys. This work can improve the thermodynamic understanding of the Lu-H-N system and help rational synthesis of N-doped Lu hydrides, but more generally demonstrates an efficient approach to model pressure-dependent thermodynamics of multicomponent solid solutions.

Monte Carlo methods↗
NASA NTRS2003

Improving TCP Network Performance by Detecting and Reacting to Packet Reordering

There are many factors governing the performance of TCP-basec applications traversing satellite channels. The end-to-end performance of TCP is known to be degraded by the reordering, delay, noise and asymmetry inherent in geosynchronous systems. This result has been largely based on experiments that evaluate the performance of TCP in single flow tests. While single flow tests are useful for deriving information on the theoretical behavior of TCP and allow for easy diagnosis of problems they do not represent a broad range of realistic situations and therefore cannot be used to authoritatively comment on performance issues. The experiments discussed in this report test TCP s performance in a more dynamic environment with competing traffic flows from hundreds of TCP connections running simultaneously across the satellite channel. Another aspect we investigate is TCP's reaction to bit errors on satellite channels. TCP interprets loss as a sign of network congestion. This causes TCP to reduce its transmission rate leading to reduced performance when loss is due to corruption. We allowed the bit error rate on our satellite channel to vary widely and tested the performance of TCP as a function of these bit error rates. Our results show that the average performance of TCP on satellite channels is good even under conditions of loss as high as bit error rates of 10(exp -5)

Kruse, Hans↗
DOE OSTI2024

Neural network emulation of flow in heavy-ion collisions at intermediate energies

Applications of new techniques in machine learning are speeding up progress in research in various fields. In this work, we construct and evaluate a deep neural network (DNN) to be used within a Bayesian statistical framework as a faster and more reliable alternative to the Gaussian process (GP) emulator of an isospin-dependent Boltzmann-Uehling-Uhlenbeck (IBUU) transport model simulator of heavy-ion reactions at intermediate beam energies. We found strong evidence of the DNN being able to emulate the IBUU simulator's prediction on the strengths of protons' directed and elliptical flow very efficiently even with small training datasets and with accuracy about ten times higher than the GP. Here, limitations of our present work and future improvements are also discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Complete Phase Transformation of Ir Nanowire Network into Defect-Rich Oxide Catalyst for High-Performance PEM Water Electrolysis

Iridium-based catalysts remain the most reliable option for the oxygen evolution reaction (OER) in proton exchange membrane water electrolyzers (PEMWEs). However, their high cost and limited performance represent critical barriers to the commercialization of this green hydrogen production technology. Herein, we report the creation of a metallic Ir nanowire network (IrNWN), which exhibits superior OER performance through its in-situ transition into an oxide structure with high intrinsic activity. At a low loading of 0.25 mgIr/cm2 in PEMWEs, IrNWN achieved a current density of 3.13 A/cm2 at a cell voltage of 1.8 V, outperforming the commercial Ir-based catalyst and surpassing the Department of Energy (DOE) 2026 technical target. Moreover, the high activity of IrNWN was maintained for 900 hours in a durability test at 2 A/cm2, showing a low degradation rate of 0.042 mV/hour. Structural analysis of the electrochemically oxidized IrNWN revealed the presence of mixed Ir oxidation states and a high density of surface terminal oxygen groups (μ1-O), which contributed to a reduced energy barrier for the rate-determining O-O coupling step.

oxygen evolution reaction↗
DOE OSTI2025

Motion Dynamics of Motile Microbes in Pore-Networks and its Implications for Reactive Transport Processes

This report outlines new methods to improve simulations of microbial transport and microbially mediated reactions in porous media. A range of experimental, modeling, and machine learning tools are introduced to make these simulations faster, more reliable, and useful for real-world applications. At the microscopic level, the study investigates how different types of bacteria move through confined spaces. A new artificial intelligence tool called DeepTrackStat, is introduced to track motions dynamics as observed in videos of particles migrating through pore networks. This tool is especially helpful for studying fast-moving microbes and requires less computing power than traditional tracking methods. At larger scales, the research looks at how microbes and chemicals interact in zones where surface water and groundwater meet. To connect the small- and large-scale findings, the study presents a neural network model called STAMNet. This tool helps scale up detailed small-scale microbial motion behaviors to predict large-scale environmental changes more efficiently. By combining lab experiments, computer models, and artificial intelligence, the research presented supports smarter environmental decision-making, especially in bioremediation of contaminated groundwater and protection of water quality.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

Neural Network for Positioning Space Station Solar Arrays

As a shuttle approaches the Space Station Freedom for a rendezvous, the shuttle's reaction control jet firings pose a risk of excessive plume impingement loads on Freedom solar arrays. The current solution to this problem, in which the arrays are locked in a feathered position prior to the approach, may be neither accurate nor robust, and is also expensive. An alternative solution is proposed here: the active control of Freedom's beta gimbals during the approach, positioning the arrays dynamically in such a way that they remain feathered relative to the shuttle jet most likely to cause an impingement load. An artificial neural network is proposed as a means of determining the gimbal angles that would drive plume angle of attack to zero. Such a network would be both accurate and robust, and could be less expensive to implement than the current solution. A network was trained via backpropagation, and results, which compare favorably to the current solution as well as to some other alternatives, are presented. Other training options are currently being evaluated.

Graham, Ronald E.↗
DOE OSTI2020

Revealing nanoscale dynamics during an epoxy curing reaction with x-ray photon correlation spectroscopy

In this work the evolution of nanoscale properties is measured during the thermally triggered curing of an industrial epoxy adhesive. We use x-ray photon correlation spectroscopy (XPCS) to track the progression of the curing reaction through the local dynamics of filler particles that reflect the formation of a thermoset network. Out-of-equilibrium dynamics are resolved through identification and analysis of the intensity– intensity autocorrelation functions obtained from XPCS. The characteristic time scale and local velocity of the filler is calculated as functions of time and temperature. We find that the dynamics speed up when approaching the curing temperature (T cure ), and decay rapidly once T cure is reached. We compare the results from XPCS to conventional macroscale characterization by differential scanning calorimetry (DSC). The demonstration and implementation of nanoscale characterization of curing reactions by XPCS proves useful for future development and optimization of epoxy thermoset materials and other industrial adhesive systems.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Theoretical H + O 3 rate coefficients from ring polymer molecular dynamics on an accurate global potential energy surface: assessing experimental uncertainties

Thermal rate coefficients and kinetic isotope effects have been calculated for an important atmospheric reaction H/D + O 3 → OH/OD + O2 based on an accurate permutation invariant polynomial-neural network potential energy surface, using ring polymer molecular dynamics (RPMD), quasi-classical trajectory (QCT) and variational transition-state theory (VTST) with multidimensional tunneling. The RPMD approach yielded results that are generally in better agreement with experimental rate coefficients than the VTST and QCT ones, especially at low temperatures, attributable to its capacity to capture quantum effects such as tunneling and zero-point energy. Additionally, the theoretical results support one group of existing experiments over the other. In addition, rate coefficients for the D + O 3 → OD + O 2 reaction are also reported using the same methods, which will allow a stringent assessment of future experimental measurements, thus helping to reduce the uncertainty in the recommended rate coefficients of this reaction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Design and evaluation of a dilute flow particle-to-air heat exchanger for energy storage applications

The use of inert and redox-active particles for high-temperature energy storage requires the development of components that can efficiently transfer energy to high-pressure working fluids like supercritical carbon dioxide (sCO 2 ). Dilute flow reactors can enable high working fluid outlet temperatures and minimal parasitic losses compared to moving packed bed and fluidized bed reactors. This research uses both computational and experimental methods to explore the design trade-offs and practical challenges of a novel component for transferring energy from dilute flows of hot, reduced metal oxide (MO x ) particles to sCO 2 in tubes. A discretized thermal resistance network model, which accounts for particle hydrodynamics, multi-mode heat transfer, and reaction equilibrium, guides the design of a prototype device. This device is experimentally tested with a surrogate heat transfer fluids and inert particle temperatures up to 400°C and a heat duty exceeding 1 kW. The data are used to validate the thermal hydraulic sub-models, allowing for the simulation of reacting particle scenarios. Under nominal design conditions, the flow rate of reactive particles is predicted to be 30% lower than that of inert particles for the same energy recovered, with over 70% of the stored particle energy transferred to the sCO 2 . Furthermore, these findings can inform the design of more efficient energy recovery reactors for particle-based systems and can be integrated into system-level concentrated solar power models with thermal storage to optimize operating conditions.

14 SOLAR ENERGY↗
DOE OSTI2021

Nitrate and Nitrite Incompatibility with Hydroxide Ions in Concentrated NaOH Solutions: Implications for Hydroxide and Gibbsite Reactivity in Alkaline Nuclear Waste

Electrolyte solutions in alkaline nuclear waste contain aluminate, hydroxide, nitrate and nitrite with sodium as the predominant counterion. The salts of these ions are highly soluble, so the liquids are highly concentrated. This study found that there is a substantial incompatibility between the hydroxide and nitrate and/or nitrate ions. This was determined by the observations that adding just one molal of NaNO2 or NaNO3 to saturated NaOH solution precipitation of 12 moles of NaOH·H2O salt, whereas the common ion effect would have expected only about 1 mole to precipitate. Further analysis indicates that the presence of nitrate and nitrite drastically increases the reactivity of sodium hydroxide ions in solution, which likely influences the reactivity of other hydroxide-mediated reactions. This enhanced reactivity is likely because it disrupts large Na+-OH- ion networks because nitrate and nitrite do not fit in those ion networks similarly to how some ions cannot substitute into a foreign crystal lattice. In contrast, the aluminate ion did not have the same large incompatibility with hydroxide.

Nitrite, Nitrate, Aluminate, NaOH*H2O, Ion-aggrega↗
DOE OSTI2025

Electrochemical Corrosion and Catalysis Dynamics of Tin Oxide during Water Oxidation

Metal oxide corrosion severely limits anodic electrocatalysis, particularly at high potentials in acidic environments, where degradation pathways remain poorly defined. This study establishes explicit connections between corrosion and electrocatalysis on tin oxide during water oxidation by examining the roles of lattice defects, reactive oxygen species, interfacial pH variations, and speciation of corroded tin in acid. We first demonstrate the presence of structural defects such as oxygen vacancies and substoichiometric Sn(II) species by integrating electron paramagnetic resonance spectroscopy, ultraviolet photoelectron spectroscopy, and Mott–Schottky analysis. Kohn–Sham density functional theory calculations reveal that explicit water structures thermodynamically stabilize reaction intermediates and lower reaction overpotentials. Moreover, we propose that water dissociation leads to hydrogen-bonding networks formed by H* and OH* intermediates, which may span the entire catalyst surface and decrease the interfacial pH to drive corrosion. In contrast, the electrochemical generation of reactive oxygen species is shown to play a minor role in catalyst corrosion during water oxidation using inductively coupled plasma mass spectrometry coupled with selective chemical scavengers. Square-wave voltammetry combined with rotating ring-disk electrodes is used to reveal that under open-circuit conditions, only Sn(IV) cations chemically dissolve from tin oxide, while both Sn(IV) and Sn(II) species electrochemically corrode during water oxidation. Our results unveil a dynamic and complicated interplay between corrosive and catalytic pathways on metal oxide electrocatalysts: a decrease in interfacial pH due to water oxidation exacerbates Sn(II)/Sn(IV) corrosion. Subsequently, the electrochemical corrosion of Sn(II)/Sn(IV) facilitates product formation from lattice oxygen, while the redeposition of corroded Sn(II) as Sn(IV) can enable oxygen exchange with water. By elucidating the roles of defects and interfacial chemistry, this work provides a roadmap for engineering improved electrocatalysts that balance activity and stability, a critical step toward scalable and durable energy technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Finding the Pareto front for high-entropy-alloy catalysts

Finding catalysts that have both high activity and high stability presents a long-standing challenge. Since optimizing activity and stability are conflicting objectives, the best one can do is find the Pareto front that yields optimal tradeoffs between these features. On the Pareto front, there is a trade-off where a portion of catalytic activity must be sacrificed to gain further stability and vice versa . Here, we provide a method to optimize the front by designing a multi-objective genetic algorithm that combines machine learning, graph neural network calculations, and density functional calculations. The application considered is the oxygen evolution reaction catalyzed by high-entropy alloys. We find that the Pareto front generally contains alloys with diverse elements, but that enhancing stability inevitably inflicts a toll on activity. We compare the general conclusions of our work to a survey of 545 experiments.

Zhang, Chengyi [Univ. of Auckland (New Zealand)]↗
DOE OSTI2025

Entropy is an important design principle in the photosystem II supercomplex

Photosystem II (PSII) can achieve near-unity quantum efficiency of light harvesting in ideal conditions and can dissipate excess light energy as heat to prevent the formation of reactive oxygen species (ROS) under light stress. Understanding how this pigment–protein complex accomplishes these opposing goals is a topic of great interest that has so far been explored primarily through the lens of the system energetics. Despite PSII’s known flat energy landscape, a thorough consideration of the entropic effects on energy transfer in PSII is lacking. In this work, we aim to discern the free energetic design principles underlying the PSII energy transfer network. To accomplish this goal, we employ a structure-based rate matrix and compute the free energy terms in time following a specific initial excitation to discern how entropy and enthalpy drive ensemble system dynamics. We find that the interplay between the entropy and enthalpy components differ among each protein subunit, which allows each subunit to fulfill a unique role in the energy transfer network. This individuality ensures that PSII can accomplish efficient energy trapping in the reaction center (RC), effective nonphotochemical quenching (NPQ) in the periphery, and robust energy trapping in the other-monomer RC if the same-monomer RC is closed. We also show that entropy, in particular, is a dynamically tunable feature of the PSII free energy landscape accomplished through regulation of LHCII binding. These findings help rationalize natural photosynthesis and provide design principles for more efficient solar energy harvesting technologies.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1986

Toughening of BIS maleimide resins: Synthesis and characterization of maleimide terminated poly(arylene ether) oligomers and polymers

Amine functional poly(arylene ether) sulfones were previously reported. Herein, the chemistry was extended to amorphous poly(arylene ether) ketones because of their higher fracture toughness values, relative to the polysulfones. It was demonstrated that the amino functional oligomers undergo a self-crosslinking reaction at temperatures above about 220 C. This produces an insoluble, but ductile network that has excellent resistance. A ketamine structure hypothesis was proposed and verified using solid state magic angle NMR. In most cases, the water generated upon ketamine formation is too low to produce porosity and solid networks are obtained. The stability of the ketamine networks towards hydrolysis is excellent. The chemistry was further demonstrated to be able to crosslink preformed nonfunctional poly(arylene ether) ketones if a difunctional amine was utilized. This concept has the possibility of greatly improving the creep resistance of thermoplastics. Also, a new technique was developed for converting the amine functional oligomers cleanly into maleimide structures. This method involves reacting maleic anhydride with monomeric aminophenols in the presence of solvent mixtures.

Mcgrath, J. E.↗
NASA NTRS1990

Planning for execution monitoring on a planetary rover

A planetary rover will be traversing largely unknown and often unknowable terrain. In addition to geometric obstacles such as cliffs, rocks, and holes, it may also have to deal with non-geometric hazards such as soft soil and surface breakthroughs which often cannot be detected until rover is in imminent danger. Therefore, the rover must monitor its progress throughout a traverse, making sure to stay on course and to detect and act on any previously unseen hazards. Its onboard planning system must decide what sensors to monitor, what landmarks to take position readings from, and what actions to take if something should go wrong. The planning systems being developed for the Pathfinder Planetary Rover to perform these execution monitoring tasks are discussed. This system includes a network of planners to perform path planning, expectation generation, path analysis, sensor and reaction selection, and resource allocation.

Gat, Erann↗
NASA NTRS2000

The Structure of Ice Nanoclusters: Implications for Interstellar Ice Grains

Crystalline ice nanoclusters and thin-films of pure and impure water ice were deposited and studied in order to evaluate the extent to which surface-related effects control bulk properties. In pure water ice nanoclusters and thin-films of impure water ice, the cubic to hexagonal phase transformation occurs at lower temperatures than in thin-film deposits of pure water ice. In laboratory-grown crystalline ice nanoclusters, approx. 20 nm diameter, a significant proportion of water molecules exists in surface and near-surface environments which have an amorphous or nearly amorphous character. These disordered regions, which are highly reactive, serve to promote transformations or reactions which would otherwise be kinetically hindered. Likewise, dilute impurities such as methanol, sequestered to the surface of thin-films on crystallization, introduce defects into the ice network, thereby allowing sluggish structural transitions to proceed. These structural effects, which are surface phenomena, are believed to play an important role in promoting molecular reactions known to occur within interstellar ice grains in cold molecular clouds, where the first organic compounds are formed.

Delzeit, L.↗
DOE OSTI2020

A requirement for an active proton delivery network supports a compound I-mediated C–C bond cleavage in CYP51 catalysis

CYP51 enzymes (sterol 14α-demethylases) are cytochromes P450 that catalyze multistep reactions. The CYP51 reaction occurs in all biological kingdoms and is essential in sterol biosynthesis. It removes the 14α-methyl group from cyclized sterol precursors by first forming an alcohol, then an aldehyde, and finally eliminating formic acid with the introduction of a Δ14–15 double bond in the sterol core. The first two steps are typical hydroxylations, mediated by an electrophilic compound I mechanism. The third step, C–C bond cleavage, has been proposed to involve either compound I (i.e. FeO 3+ ) or, alternatively, a proton transfer-independent nucleophilic ferric peroxo anion (compound 0, i.e. Fe 3+ O 2 – ). In this work, using comparative crystallographic and biochemical analyses of WT human CYP51 (CYP51A1) and its D231A/H314A mutant, whose proton delivery network is destroyed (as evidenced in a 1.98-Å X-ray structure in complex with lanosterol), we demonstrate that deformylation of the 14α-carboxaldehyde intermediate requires an active proton relay network to drive the catalysis. These results indicate a unified, compound I-based mechanism for all three steps of the CYP51 reaction, as previously established for CYP11A1 and CYP19A1. We anticipate that our approach can be applied to mechanistic studies of other P450s that catalyze multistep reactions, such as C–C bond cleavage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗