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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Ternary and Quaternary Nickel-Iron-Oxide-Based Thin Films as Oxygen Evolution Reaction Catalysts in Alkaline Media

Alkaline water electrolyzers are a promising technology for energy storage and conversion through the electrochemical production of hydrogen, however the slow kinetics of the oxygen evolution reaction (OER) pose a major challenge. The alkaline environment enables the use of non-Pt-group metals as OER catalysts, in particular NiFe-based materials. In this study, Mn and/or Cr were elementally mixed with NiFe to further improve the OER catalyst properties through a controlled, systematic synthesis process involving thin films prepared by electron beam-induced physical vapor deposition (PVD). By exploring both simultaneous co-deposition and serial deposition of the different metals, the OER performance was investigated as a function of both the location of Mn or Cr in the multi-metal NiFe-based catalysts and the difference between surface versus bulk mixing. The distinct differences in the redox dynamics, surface oxidation, and stability of the seven studied catalysts reveal metal Cr- and/or Mn-overlayers as a promising synthesis approach for fine-tuning of catalyst properties and improving the OER performance.

Alkaline Water Electrolysis↗
DOE OSTI2021

Water Interplays during Dysprosium Electrodeposition in Pyrrolidinium Ionic Liquid: Deconvoluting the Pros and Cons for Rare Earth Metallization

The electrochemical production of rare earth metals (REMs) in ionic liquids (ILs) has received much attention as a promising, sustainable and replacement to the molten salt electrolysis. Water additives have been recently suggested as a strategy to overcome the limitations of the ionic liquid process, but without complete assessment of its overall viability for the REMs production. In this regard, a full investigation of water impact on dysprosium (Dy) electrodeposition in pyrrolidinium triflate (BMPyOTf) ionic liquid was carried out. Water introduction was revealed to involve an interplay of implications on the electrodeposition process, including coordination, speciation, reduction pathways, interfacial dynamics, nucleation and metal stability and purity. In highly dry conditions, the reduction occurs at very negative potentials (-3.3V) in a consecutive pathway, resulting in negligible metal electrodeposition (low rate and efficiency) at the electrode surface. Initial water introduction (<30% molar fraction) leads to partitioning of the Dy complex between water and IL coordinated speciation, giving rise to an additional wave at more positive potentials (-2.4V). Probing and quantification of the heterogeneous Dy speciation by spectroscopic analyses enabled the uncovering of the reduction mechanism and accurate evaluation of the mass transport properties. While lowering the reduction thermodynamics, water addition also improved the nucleation, deposition rate and faradaic efficiency. In spite of these benefits, stripping voltammetric analysis also indicated substantial chemical reactivity of the deposited Dy metal with water additives and/or electrolyte components, under extended timescales. Surface characterization of the obtained product confirmed limited Dy metal stability (mostly oxidized/fluorinated) and purity (~60%) in the studied system. Moreover, high water introduction (>30% molar fraction) was shown to trigger a fast hydrogen evolution reaction (HER), downgrading the robustness of system efficiency. We report the overall impact of water additives seems to engender both promoting and mitigating effects on the Dy electrodeposition process, making the case for more innovative strategies to be sought.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Polyethylene Upcycling to Liquid Alkanes in Molten Salts under Neat and External Hydrogen Source-Free Conditions

Development of facile approaches to convert plastic waste into liquid fuels under neat conditions is highly desired but challenging, particularly without noble metal catalysts and an external hydrogen source. Herein, highly efficient and selective polyethylene-to-gasoline oil (branched C 6 –C 12 alkanes) conversion was achieved under mild conditions (<170 °C) using commercially available AlCl 3 -containing molten salts as reaction media and to provide catalytic sites (no extra solvents, additives, or hydrogen feeding). The high catalytic efficiency and selectivity was ensured by the abundant active Al sites with strong Lewis acidity (comparable to the Al type in acidic zeolite) and highly ionic nature of the molten salts to stabilize the carbenium intermediates. Dynamic genesis of the Al sites was elucidated via time-resolved Al K-edge soft X-ray and 27 Al NMR, confirming the tricoordinated Al 3+ as active sites and its coordination with the as-generated alkene/aromatic intermediates. Further, the carbenium formation and polyethylene chain variation was illustrated by inelastic neutron scattering (INS) and an isotope-labeling experiment. Theoretical simulations further demonstrated the successive hydride abstraction, β-scission, isomerization, and internal hydrogen transfer reaction pathway with AlCl 3 as active sites. This facile catalytic system can further achieve the conversion of robust, densely assembled, and high molecular weight plastic model compounds to liquid alkane products in the diesel range.

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

Basal Melting and Oceanic Observations Beneath Central Fimbulisen, East Antarctica

Abstract Basal melting of ice shelves is fundamental to Antarctic ice sheet mass loss, yet direct observations remain sparse. We present the first year‐round melt record (2017–2021) from a phase‐sensitive radar on Fimbulisen, one of the fastest flowing ice shelves in Dronning Maud Land, East Antarctica. The observed long‐term mean ablation rate at 350 m depth below the central ice shelf was 1.0 ± 0.5 m yr −1 , marked by substantial sub‐weekly variability ranging from 0.4 to 3.5 m yr −1 . 36‐h filtered basal melt rate fluctuations closely align with ocean velocity. On seasonal time scales, melt rates peak during austral spring to autumn (September–March), driven by both elevated ocean velocities and thermal driving near the base. The combined effect of thermal driving and current speed explains the majority of the melt rate variability ( r = 0.84), highlighting the dominant role of shear‐driven turbulence. This relationship enables parameterization of melt rates for the decade‐long ocean record (2010–2021), although deviations appear under low and high forcing conditions. Both observed and parameterized melt rates show similar yearly mean magnitudes compared to satellite‐derived melt rates but with a tenfold lower seasonal amplitude and a 3‐month delay in seasonality. These detailed concurrent ice–ocean observations provide essential validation data for remote sensing and numerical models that aim to quantify and project ice‐shelf response to a change in ocean forcing. In situ measurements and continued monitoring are crucial for accurately assessing and modeling future basal melt rates, and for understanding the complex dynamics driving ice‐shelf stability and sea‐level change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Moisture-induced autonomous surface potential oscillations for energy harvesting

A variety of autonomous oscillations in nature such as heartbeats and some biochemical reactions have been widely studied and utilized for applications in the fields of bioscience and engineering. Here, we report a unique phenomenon of moisture-induced electrical potential oscillations on polymers, poly([2-(methacryloyloxy)ethyl] dimethyl-(3-sulfopropyl) ammonium hydroxide-co-acrylic acid), during the diffusion of water molecules. Chemical reactions are modeled by kinetic simulations while system dynamic equations and the stability matrix are analyzed to show the chaotic nature of the system which oscillates with hidden attractors to induce the autonomous surface potential oscillation. Using moisture in the ambient environment as the activation source, this self-excited chemoelectrical reaction could have broad influences and usages in surface-reaction based devices and systems. As a proof-of-concept demonstration, an energy harvester is constructed and achieved the continuous energy production for more than 15,000 seconds with an energy density of 16.8 mJ/cm 2 . A 2-Volts output voltage has been produced to power a liquid crystal display toward practical applications with five energy harvesters connected in series.

42 ENGINEERING↗
DOE OSTI2026

A scalable superconducting nanowire memory array with row–column addressing

Scalable superconducting memory is required for the development of low-energy superconducting computers and fault-tolerant quantum computers. Conventional superconducting logic-based memory cells possess a large footprint that limits scaling; nanowire-based superconducting memory cells, although more compact, have high error rates, which hinders integration into large arrays. Here we report a 4 × 4 superconducting nanowire memory array that is designed for scalable row–column operations and has a functional density of 2.6 Mbit cm −2 . Each memory cell is based on a nanowire loop consisting of two temperature-dependent superconducting switches and a variable kinetic inductor. The arrays operate at 1.3 K, where we implement and characterize multiflux quanta state storage and destructive read-out. By optimizing the write- and read-pulse sequences, we minimize bit errors and maximize operating margins. We achieve a minimum bit error rate of 10 −5 . Here, we also use circuit-level simulations to understand the memory cell’s dynamics, performance limits and stability under varying pulse amplitudes.

Electrical and electronic engineering↗
DOE OSTI2022

Large second harmonic generation in a penta-CdO 2 sheet exfoliated from its bulk phase

Two-dimensional (2D) materials composed solely of pentagonal motifs are of particular interest due to their unique geometries and novel properties. Especially, the broken centrosymmetry and in-plane mirror symmetry in penta-graphene-like materials result in both in-plane and out-of-plane second harmonic generation (SHG). Transition metal cations with a filled d 10 shell (d 10 -TM) can significantly enhance the SHG response as found in many previously studied bulk materials. Here, in this study, based on first-principles calculations combined with independent particle approximation, we show that large SHG can also exist in some 2D d 10 -TM oxides, such as penta-CdO 2 , which can be chemically exfoliated from its bulk phase with its dynamical, thermal, and mechanical stability intact. We further find that penta-CdO 2 possesses extraordinary in-plane and out-of-plane SHG responses with large static SHG susceptibilities of χ sheet 14 (0) = χ sheet 25 (0) = χ sheet 36 (0) = 8.86 pm 2 V -1 due to the phase-matching between fundamental and second-harmonic light. In addition, the low thermal expansion and a large optical band gap of 3.24 eV endow the penta-CdO 2 sheet with a high laser-induced damage threshold. Discussions are also made on the penta-ZnO 2 sheet. This study expands the family of 2D materials with outstanding SHG performance.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Blocking C-terminal processing of KRAS4b via a direct covalent attack on the CaaX-box cysteine

RAS is the most frequently mutated oncogene in cancer. RAS proteins show high sequence similarities in their G-domains but are significantly different in their C-terminal hypervariable regions (HVR). These regions interact with the cell membrane via lipid anchors that result from posttranslational modifications (PTM) of cysteine residues. KRAS4b is unique as it has only one cysteine that undergoes PTM, C185. Small molecule covalent modification of C185 would block any form of prenylation and subsequently inhibit attachment of KRAS4b to the cell membrane, blocking its biological activity. We translated this concept to the discovery and development of disulfide tethering screen hits into irreversible covalent modifiers of C185. These compounds inhibited proliferation of KRAS4b-driven mouse embryonic fibroblasts, but not cells driven by N-myristoylated KRAS4b that harbor a C185S mutation and are not dependent on C185 prenylation. Top–down proteomics was used to confirm target engagement in cells. These compounds bind in a pocket formed when the HVR folds back between helix 3 and 4 in the G-domain (HVR-α3-α4). This interaction can happen in the absence of small molecules as predicted by molecular dynamics simulations and is stabilized in the presence of C185 binders as confirmed by small-angle X-ray scattering and solution NMR. NOESY-HSQC, an NMR approach that measures internuclear distances of 6 Å or less, and structure analysis identified the critical residues and interactions that define the HVR-α3-α4 pocket. Further development of compounds that bind to this pocket could be the basis of a new approach to targeting KRAS cancers.

C185↗
DOE OSTI2021

Faraday Michelson Interferometers for Signal Demodulation of Fiber-Optic Sensors

We developed an all-fiber-based optical demodulator for the signal interrogation of low-coherence fiber-optic Fabry–Perot interferometric sensors. The optical demodulator consists of a Michelson interferometer implemented by using a 3×3 fiber coupler and two fiber-coupled Faraday reflectors with tunable fiber delay lines. The demodulator's output contains two optical interference signals with a constant phase shift and the output shows no sensitivity to the polarization variation in the light source or fibers. A digital phase recovery algorithm is used to extract the measurand information from the phase-shifted signals at high accuracy, high dynamic range, and high stability. The optical demodulator has been applied to the measurement of high-frequency vibrations and strains using fiber-optic sensors.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Revisiting Reentry Roll Resonance

Here, this paper revisits the subject of reentry roll resonance, which occurs when the roll rate and pitch frequency become equal in a spinning reentry vehicle. A first-principles model is developed and analyzed numerically and by using a reduced-order pendulum model for the relative phase of the roll and pitch/yaw axes. The results show good qualitative agreement with recent flight data and provide a natural physical interpretation. Based on the model it is suggested that sustained roll resonance depends primarily on the initial phase relationship between the pitch and roll axes, in addition to the vehicle moments of inertia and the vehicle symmetry. Finally the model is used to propose a mechanism for sustained resonance in vehicles spinning about a major axis, a condition previously thought to be forbidden.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Assembly of JAZ–JAZ and JAZ–NINJA complexes in jasmonate signaling

Jasmonates (JAs) are plant hormones with crucial roles in development and stress resilience. They activate MYC transcription factors by mediating the proteolysis of MYC inhibitors called JAZ proteins. In the absence of JA, JAZ proteins bind and inhibit MYC through the assembly of MYC–JAZ–Novel Interactor of JAZ (NINJA)–TPL repressor complexes. However, JAZ and NINJA are predicted to be largely intrinsically unstructured, which has precluded their experimental structure determination. Through a combination of biochemical, mutational, and biophysical analyses and AlphaFold-derived ColabFold modeling, we characterized JAZ–JAZ and JAZ–NINJA interactions and generated models with detailed, high-confidence domain interfaces. We demonstrate that JAZ, NINJA, and MYC interface domains are dynamic in isolation and become stabilized in a stepwise order upon complex assembly. By contrast, most JAZ and NINJA regions outside of the interfaces remain highly dynamic and cannot be modeled in a single conformation. Our data indicate that the small JAZ Zinc finger expressed in Inflorescence Meristem (ZIM) motif mediates JAZ–JAZ and JAZ–NINJA interactions through separate surfaces, and our data further suggest that NINJA modulates JAZ dimerization. This study advances our understanding of JA signaling by providing insights into the dynamics, interactions, and structure of the JAZ–NINJA core of the JA repressor complex.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Free Energy and Flexibility Analysis of Autoinhibited Human BRAF

The RAF serine/threonine protein kinases function as direct effectors of RAS in the intracellular transmission of extracellular growth signals, and they are key targets for drug discovery, given the high incidence of oncogenic mutations in RAF and other components of this signaling pathway. In its inactive state, RAF is held in an autoinhibited conformation in the cytosol through a combination of intramolecular interactions and binding to a regulatory 14−3−3 protein dimer. Activation of RAF is initiated by its interaction with membrane-localized GTP-bound RAS, which induces conformational changes that release RAF from its autoinhibited state. However, the molecular mechanisms governing RAF activation remain incomplete, largely due to the challenges in experimentally capturing the intermediate conformational states in this process. To address this gap, we developed a comprehensive all-atom model of BRAF based on existing cryo-EM structures. Using this model, we performed extensive molecular dynamics simulations to evaluate the stability and free energy landscape of autoinhibited BRAF in solution. Our analysis reveals conformational flexibility within the autoinhibited complex, suggesting that this dynamic behavior may play a role in facilitating BRAF activation upon engagement with the membrane-bound RAS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A Hybrid-Learning Algorithm for Online Dynamic State Estimation in Multimachine Power Systems

With the increasing penetration of distributed generators in the smart grids, having knowledge of rapid real-time electromechanical dynamic states has become crucial to system stability control. Conventional Supervisory Control and Data Acquisition (SCADA)-based dynamic state estimation (DSE) techniques are limited by the slow sampling rates, while the emerging phasor measurement units (PMUs) technology enables rapid real-time measurements at network nodes. Using generator bus terminal voltages, we propose a hybrid-learning DSE (HL-DSE) algorithm to estimate the synchronous machine rotor angle and speed in real time. The HL-DSE takes the power system model into account and trains neuroestimators with real-time data in an online manner. Compared with traditional DSE methods, the HL-DSE overcomes limitations by using a data-driven approach in conjunction with the physical power system model. The time efficiency, accuracy, convergence, and robustness of the proposed algorithm are tested under noises and fault conditions in both small- and large-scale test systems. Simulation results show that the proposed HL-DSE is much more computationally efficient than widely used Kalman filter (KF)-based methods while maintaining comparable accuracy and robustness. In particular, HL-DSE is over 100 times faster than square-root unscented KF (SR-UKF) and 80 times faster than extended KF (EKF). The advantages and challenges of the HL-DSE are also discussed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

New horizons in the holographic conformal phase transition

Abstract We describe 5D dynamical cosmological solutions of the stabilized holographic dilaton and their role in completion of the conformal phase transition. This analysis corresponds, via the AdS/CFT dictionary, to a study of out-of-equilibrium dynamics where trajectories of the dilaton do not depend solely on thermodynamic quantities in the early universe, but have sensitivity also to initial conditions. Unlike the well-studied thermal transition, which requires quantum tunneling of an infrared brane through the surface of an AdS-Schwarzschild horizon, our approach instead invokes an early epoch in which the cosmology is fully 5-dimensional, with highly relativistic brane motion and with Rindler horizons obscuring the infrared brane at early times. In this context, we demonstrate the existence of a large class of natural initial conditions that seed trajectories where the brane simply passes through the Rindler horizon and into the basin of attraction of the stabilized dilaton potential. This corresponds to successful completion of the phase transition without sacrificing perturbativity of the 5D theory.

Physics↗
DOE OSTI2025

A Dynamic Pricing Method to Manage the Impact of EV Charging on the Grid Using RL

This work addresses the challenge of managing electrical vehicle (EV) charging loads on distribution feeders with the increase in deployment of fast charging stations. To mitigate the adverse impacts on feeder health, a novel dynamic grid-informed pricing approach is proposed. This approach leverages reinforcement learning (RL) to determine hourly charging prices based on real-time grid conditions. A synthetic environment was developed to train the reinforcement learning agent. A model of an IEEE 34-bus distribution feeder with EV charging stations has been developed in OpenDSS utilizing Caldera for realistic EV charging profiles. Test cases demonstrate that the dynamic pricing strategy achieves higher energy delivery to the EV end user at a lower cost compared to constant pricing methods, while lowering voltage deviations and congestion. This approach offers more granular price adjustments, responding dynamically to feeder conditions and potentially improving grid stability and efficiency. The communication architecture to implement this dynamic pricing method is described. This research contributes to the development of smart grid-informed charging solutions that can reduce the cost of charging to the end user while also helping the grid.

EV charging, dynamic pricing, grid-informed chargi↗
DOE OSTI2025

A dynamic pricing method to manage the impact of EV charging on the grid using RL

This work addresses the challenge of managing electrical vehicle (EV) charging loads on distribution feeders with the increase in deployment of fast charging stations. To mitigate the adverse impacts on feeder health, a novel dynamic grid-informed pricing approach is proposed. This approach leverages reinforcement learning (RL) to determine hourly charging prices based on real-time grid conditions. A synthetic environment was developed to train the reinforcement learning agent. A model of an IEEE 34-bus distribution feeder with EV charging stations has been developed in OpenDSS utilizing Caldera for realistic EV charging profiles. Test cases demonstrate that the dynamic pricing strategy achieves higher energy delivery to the EV end user at a lower cost compared to constant pricing methods, while lowering voltage deviations and congestion. This approach offers more granular price adjustments, responding dynamically to feeder conditions and potentially improving grid stability and efficiency. The communication architecture to implement this dynamic pricing method is described. This research contributes to the development of smart grid-informed charging solutions that can reduce the cost of charging to the end user while also helping the grid.

24 - POWER TRANSMISSION AND DISTRIBUTION↗