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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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1,366 records · Page 9

Analysis of Surface and Bulk Behavior in Ni-Pd Alloys

The most salient features of the surface structure and bulk behavior of Ni-Pd alloys have been studied using the BFS method for alloys. Large-scale atomistic simulations were performed to investigate surface segregation profiles as a function of temperature, crystal face, and composition. Pd enrichment of the first layer was observed in (111) and (100) surfaces, and enrichment of the top two layers occurred for (110) surfaces. In all cases, the segregation profile shows alternate planes enriched and depleted in Pd. In addition, the phase structure of bulk Ni-Pd alloys as a function of temperature and composition was studied. A weak ordering tendency was observed at low temperatures, which helps explain the compositional oscillations in the segregation profiles. Finally, based on atom-by-atom static energy calculations, a comprehensive explanation for the observed surface and bulk features will be presented in terms of competing chemical and strain energy effects.

Ordering

Reduced fast-ion transport calculations of m = n = 1 fishbone-like instabilities in MAST-U

Fast-ion transport associated with an m = n = 1 fishbone-like burst in MAST-U discharge 47128 is investigated using a reduced guiding-center-based transport model (ORBIT-Kick) constrained by multi-diagnostic measurements. The two-dimensional beam-emission spectroscopy system provides measurements of the core poloidal mode structure and fluctuation amplitude, while EFIT++ reconstructions constrained by the motional Stark effect diagnostic indicate a flat q-profile with q 0 > 1⁠, indicating the absence of a resonant q = 1 surface and supporting a pressure-driven infernal-mode interpretation. Analytic m = n = 1 displacement profiles consistent with the measured core mode structure and equilibrium constraints are used as the mode structure inputs to ORBIT-Kick. The calculations show that the dominant resonances occur between the mode and co-passing fast ions, producing redistribution localized near the magnetic axis. Synthetic neutron camera signals from TRANSP-Kick recover up to 90% of the experimentally observed neutron deficit at the time of peak mode amplitude, indicating that the measured m = n = 1 mode is a dominant contributor to core fast-ion transport. However, the synthetic neutron signals recover rapidly, whereas the measured neutron emission continues to decrease after the peak amplitude. In conclusion, the remaining discrepancy may arise from contributions not included in the present single-harmonic model, including higher-m and higher-n harmonics, multi-harmonic interactions, and additional transport mechanisms, motivating future diagnostic development and modeling efforts to resolve and incorporate these additional contributions.

Wong, Henry H. [University of California, Los Ange

Distributed quantum approximate optimization algorithm on a quantum-centric supercomputing architecture

Quantum approximate optimization algorithm (QAOA) has shown promise in solving combinatorial optimization problems by providing quantum speedup on near-term gate-based quantum computing systems. However, QAOA faces challenges for high-dimensional problems due to the large number of qubits required and the complexity of deep circuits, limiting its scalability for real-world applications. In this study, we present a distributed QAOA (DQAOA), which leverages distributed computing strategies to decompose a large computational workload into smaller tasks that require fewer qubits and shallower circuits than are necessary to solve the original problem. These sub-problems are processed using a combination of high-performance and quantum computing resources. The global solution is iteratively updated by aggregating sub-solutions, allowing convergence toward the optimal solution. We demonstrate that DQAOA can handle considerably large-scale optimization problems (e.g., 1000-bit problem), achieving a high solution quality and short time-to-solution, outperforming existing strategies. Furthermore, we realize DQAOA on a quantum-centric supercomputing architecture, paving the way for practical applications of gate-based quantum computers in real-world optimization tasks. To extend DQAOA’s applicability to materials science, we further develop an active learning algorithm integrated with our DQAOA (AL-DQAOA), which involves machine learning, DQAOA, and active data production in an iterative loop. We successfully optimize photonic structures using AL-DQAOA, indicating that solving real-world optimization problems using gate-based quantum computing is feasible. We expect the proposed DQAOA to be applicable to a wide range of optimization problems and AL-DQAOA to find broader applications in material design.

Kim, Seongmin [ORNL] (ORCID:0000000159063004)

Modeling phase transformations in Mn-rich disordered rocksalt cathodes with machine-learning interatomic potentials

Mn-rich disordered rocksalt (DRX) cathode materials exhibit a phase transformation from a disordered to a partially disordered spinel-like structure (δ-phase) during electrochemical cycling. Here, in this computational study, we use charge-informed molecular dynamics with a fine-tuned CHGNet foundation potential to investigate the phase transformation in LixMn 0.8 Ti 0.1 O 1.9 F 0.1 . Our results indicate that transition metal migration occurs and reorders to form the spinel-like ordering in an FCC anion framework. The transformed structure contains a higher concentration of nontransition metal (0-TM) face-sharing channels, which are known to improve Li transport kinetics. Analysis of the Mn valence distribution suggests that the appearance of tetrahedral Mn 2+ is a consequence of spinel-like ordering, rather than the trigger for cation migration as previously suggested. Calculated equilibrium intercalation voltage profiles demonstrate that the δ-phase, unlike the ordered spinel, exhibits solid-solution signatures at low voltage. A higher Li capacity is obtained than in the DRX phase. This study provides atomic insights into solid-state phase transformation and its relation to experimental electrochemistry, highlighting the potential of machine-learning interatomic potentials for understanding complex oxide materials.

Zhong, Peichen [University of California, Berkeley

Thermal Data-driven Model Reduction for Enhanced Battery Health Monitoring

Electric aviation faces a major challenge of avoiding potentially catastrophic consequences of the battery’s thermal runaway while keeping the weight of the battery low. Detection of early warning signals of battery failures requires accurate monitoring of the battery’s health throughout its lifespan. However, identifying the parameters of the battery from field data is notoriously difficult. We investigate this problem within the framework of modeling the temperature dynamics of a Li-ion cell during tests simulating loading in electric aircraft flights. It is found that the parameters of a higher-fidelity physics-based thermal model cannot be identified from the simulated flight data. To resolve this issue, we reduce the higher-fidelity thermal model to a model with fewer parameters. The resulting reduced-order model can predict temperature dynamics accurately and is identifiable throughout the cell’s lifespan which allows using the model’s parameters to monitor the state-of-health of the aging cell and detect anomalies in thermal behavior.

Li ion batteries

ORNL Report of Analysis for the Verification of NRMP CRM U030A

In support of the Certified Reference Material (CRM) program managed by the Nuclear Reference Material Program (NRMP), the Material Signatures and Isotopic Standards (MSIS) group of Oak Ridge National Laboratory (ORNL) was asked to prepare a set of CRM U030A units for use as standards for isotopic analysis using multicollector thermal ionization mass spectrometry (TIMS) and inductively coupled plasma mass spectrometry (ICP-MS) instruments. This report documents the results of the verification measurements performed on three randomly selected units by the MSIS group’s ISO/IEC 17025:2017 accredited operating procedure CSD-AM-CIMS-IN20, Determination of Uranium and Plutonium Isotopic Composition using Thermal Ionization Mass Spectrometry [1], and in accordance with the quality assurance plan as described in QAP-X-96-CSD/RML-001, Nuclear Analytical Chemistry Laboratory Section Quality Assurance Plan [2].

Mathew, Kattathu [Oak Ridge National Laboratory (O

Erosion Behavior of Ti-hBN Multifunctional Coatings in A Custom-Made Planetary Test Rig at Extreme Lunar Temperatures

Spacecraft landings and takeoffs on the lunar surface, along with extreme temperature variations between day and night (-196 to 150° C), cause high-velocity dust impacts and erosion, resulting in the premature failure of structures. Ti/2 vol% hBN coatings were deposited using atmospheric (APS) and vacuum plasma spray (VPS) using cryo-milled powder feedstock to protect the structural components. The erosion performance of coatings at extreme lunar temperature regimes (-150 to 150° C) was evaluated in a custom-made planetary erosion test rig (PETR) at low (50 mph) and high impact velocities (250 mph). The mass loss of VPS coatings was reduced by 50% compared to the APS coatings and 40% compared to the Ti6Al4V substrate. The cryogenic temperature induces brittleness in the material, rendering it susceptible to extreme conditions of material loss. The particle impact-deformation behavior was captured using a high-speed camera to study the erosion mechanism. This analysis revealed chipping in substrates and brittle APS coatings, while particles rebounding and embedding were observed in VPS coatings. Energy calculations, aided by particle trajectory tracking from the high-speed camera, have conclusively shown that VPS coatings absorb 5–10% more energy than APS coatings during erosion tests. A modified erosion index was developed incorporating the fracture toughness and temperatures. New erosion models for brittle and ductile target materials are proposed for developing erosion-resistant material systems.

Abhijith Kunneparambil Sukumaran

In Silico Chemical Experiments in the Age of AI: From Quantum Chemistry to Machine Learning and Back

Computational chemistry is an indispensable tool for understanding molecules and predicting chemical properties. However, traditional computational methods face significant challenges due to the difficulty of solving the Schrödinger equations and the increasing computational cost with the size of the molecular system. In response, there has been a surge of interest in leveraging artificial intelligence (AI) and machine learning (ML) techniques to in silico experiments. Integrating AI and ML into computational chemistry increases the scalability and speed of the exploration of chemical space. However, challenges remain, particularly regarding the reproducibility and transferability of ML models. This review highlights the evolution of ML in learning from, complementing, or replacing traditional computational chemistry for energy and property predictions. Starting from models trained entirely on numerical data, a journey set forth toward the ideal model incorporating or learning the physical laws of quantum mechanics. This paper also reviews existing computational methods and ML models and their intertwining, outlines a roadmap for future research, and identifies areas for improvement and innovation. Ultimately, the goal is to develop AI architectures capable of predicting accurate and transferable solutions to the Schrödinger equation, thereby revolutionizing in silico experiments within chemistry and materials science.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Healable Coatings as a Mechanism to Repair Leading Edge Erosion in Wind Energy

Wind turbine blades are highly engineered structures designed to face temperature extremes and high winds. However, erosion of the blade's leading edge and subsequent repair remains a significant and costly challenge for the wind energy industry. Repair of these leading edges can lead to large amounts of downtime for the turbine and significant operational inefficiencies. In this work, the strength of adhesion and healing ability of a commercially available vitrimer (Mallinda's VITRIMAX) was compared to that of a thermoplastic resin, which has previously been demonstrated in wind energy applications (Arkema's Elium) to evaluate their efficacy as surface coatings for wind turbine blades, particularly their leading edges. Vitrimers are a class of inherently reprocessable thermosets, and it was theorized that vitrimer-based leading edge coatings could enable more robust and efficient wind turbine blades with decreased operational downtime and safer maintenance practices. It was found that the VITRIMAX adhered better to the wind blades' surfaces than both the manufacturer's paint and Elium, with increases in pull-off strength of adhesion ranging from 24% to 83% above that of the original paint. Furthermore, the VITRIMAX adhered strongly to the underlying composite of each blade with strength of adhesion values increasing in ranges from 42% to 97% above that of the original paint. Finally, the vitrimer coating showed an 88% decrease in surface roughness compared to end-of-life blade materials, and initial healing demonstrations in which coatings were manually scratched and subsequently healed exhibited an ~84.5% decrease in scratch depths.

Hubbard, Amber [ORNL]

Pulsed Magnetic Field Driven Gas Core Reactors for Space Power & Propulsion Applications

The present results indicated that: 1. A pulsed magnetic driven fission power concept, PMD-GCR is developed for closed (NER) and semi-open (NTR) operations. 2. In power mode, power is generated at alpha less than 1 for power levels of hundreds of KW or higher 3. IN semi open NTR mode, PMD-GCR generates thrust at I(sub sp) approx. 5,000 s and jet power approx. 5KW/Kg. 4. PMD-GCR is highly subcritical and is actively driven to critically. 5. Parallel path with fusion R&D needs in many areas including magnet and plasma.

Samim Anghaie

Dynamic sparse x-ray nanotomography reveals ionomer hydration mechanism in polymer electrolyte fuel-cell catalyst

Tomographic imaging of time-evolving samples is a challenging yet important task for various research fields. At the nanoscale, current approaches face limitations of measurement speed or resolution due to lengthy acquisitions. We developed a dynamic nanotomography technique based on sparse dynamic imaging and 4D tomography modeling. We demonstrated the technique, using ptychographic x-ray computed tomography as its imaging modality, on resolving the in situ hydration process of polymer electrolyte fuel cell (PEFC) catalyst. The technique provides a 40-time increase in temporal resolution compared to conventional approaches, yielding 28 nm half-period spatial and 12 min temporal resolution. The results allow a quantitative characterization of the water intake process inside PEFC catalysts with nanoscale resolution, which is crucial for understanding their electrochemical mechanisms and optimizing their performance. Our technique enables high-speed operando nanotomography studies and paves the way for wider application of dynamic tomography at the nanoscale.

Science & Technology - Other Topics

Swamp Works Regolith Compaction Technologies

While the level of compaction below the lunar surface increases quickly after only a few cm of depth, in many cases during a construction mission there will be a need to excavate and transport regolith to a new location for cut-and-fill or horizontal construction of structures such as berms. In these cases to achieve high levels of bulk density, compaction must be per-formed. Additionally, in some cases surface technologies such as systems that sinter/melt the surface may desire the maximum possible compaction at the sur-face to improve melting/heating performance and the final material strength properties. Kennedy Space Center’s (KSC) Swamp Works has developed two means of compaction, lunar and mar-tian compaction. Planetary Autonomous Compaction Technology (PACT) which is part of the Multifunction End Effector for Regolith Compaction Acquisition and Transfer (MEERCAT) robotic arm end effector system’s capabilities and the Site Preparation Tooling for Operations on Mobility Platforms (STOMP) vibratory roller compactor. PACT on MEERCAT has been demonstrated to a TRL 5 and STOMP to a TRL 4 in ambient testing. The results of PACT on MEERCAT and STOMP testing will be shared with results for various simulants including BP-1, ICN-LHT-1G (aka CSM-LHT-1G), RDW-LHT-1GH (a simulant developed for the Mason Tipping Point to match characteristics of ICN-LHT-1G), and Exolith LHS-1E. This will also include discussions on methods used to verify relative density before and after compaction and means to verify density effects below depth. To calculate relative density, maximum and minimum densities for simulants were taken from literature and additional lab testing (publication in work).

redwire

Speciation of Transition Metal Dissolution in Electrolyte from Common Cathode Materials

Significant capacity loss has been observed across extended cycling of lithium-ion batteries cycled to high potential. One of the sources of capacity fade is transition metal dissolution from the cathode active material, ion migration through the electrolyte, and deposition on the solid-electrolyte interphase on the anode. While much research has been conducted on the oxidation state of the transition metal in the cathode active material or deposited on the anode, there have been limited investigations of the oxidation state of the transition metal ions dissolved in the electrolyte. Here, in this work, X-ray absorption spectroscopy has been performed on electrolytes extracted from cells built with four different cathode active materials (LiMn 2 O 4 (LMO), LiNi 0.5 Mn 1.5 O 4 (LNMO), LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811), and (x Li 2 MnO 3 *(1-x) LiNi a Mn b Co c O 2 , with a+b+c=1) (LMRNMC)) that were cycled at either high or standard potentials to determine the oxidation state of Mn and Ni in solution. Inductively coupled plasma-mass spectrometry has been performed on the anodes from these cells to determine the concentration of deposited transition metal ions. While transition metal ions were found dissolved in all electrolytes, the oxidation state(s) of Mn and Ni were determined to be dependent on the cathode material and independent of cycling potential.

25 ENERGY STORAGE

NanoPSD: A software for automatic detection of Nano-Particle Shape Distribution in electron microscopy images

Accurate quantification of the size and morphology of nanoparticles from electron microscopy (EM) images is essential to understand growth mechanisms, surface reactivity, and functional behavior in nanoscale materials. Manual analysis remains slow, subjective, and difficult to reproduce in large datasets. We introduce NanoPSD (Nano-Particle Shape Distribution), an open-source and fully automated framework for quantitative particle detection and morphology analysis from EM images. NanoPSD integrates adaptive contrast enhancement, polarity-agnostic scale-bar detection, Optical Character Recognition (OCR)-based calibration, and classical segmentation via Otsu thresholding with morphological refinement. Particle contours are used to extract geometric descriptors, including equivalent circular diameter, aspect ratio, circularity, and solidity, enabling automated classification into spherical, rod-like, and aggregate morphologies. The framework supports both single-image and batch processing, generating publication-quality visualizations, LaTeX-ready tables, and structured comma-separated values (CSV) datasets. As a demonstration, we applied NanoPSD to plasma-synthesized nanoparticle samples diagnosed via transmission electron microscopy (TEM). The code produced statistically robust size and morphology distributions spanning a few to tens of nanometers with minimal user supervision. The pipeline demonstrates high reproducibility and scalability, processing large image collections with consistent calibration and output formatting. Its modular design enables seamless integration of future deep-learning-based segmentation models, providing a pathway toward intelligent, data-driven electron microscopy analysis.

36 MATERIALS SCIENCE

Evaluation of Low-Energy Hydrogen Separation Method Using Metal-Organic Frameworks (MOFs) for Closed-Loop ECLSS Air Revitalization (CLEAR)

The State-of-the-Art (SOA) air revitalization architecture onboard the International Space Station (ISS) recovered approximately 50% of the oxygen (O 2 ) from metabolic carbon dioxide (CO 2 ) via the Sabatier process from 2011 to 2017. O 2 recovery is currently constrained by the limited availability of reactant hydrogen (H 2 ) preventing complete conversion of CO 2 to H 2 O. Increasing O 2 recovery within Closed-Loop ECLSS is essential to reducing resupply mass for long-duration manned missions; specifically focusing on water (H 2 O) which supplies H 2 for Sabatier via water electrolysis. Past ground test endeavors at Marshall Space Flight Center (MSFC) have attempted to recover H 2 from Sabatier-produced CH 4 using technologies such as carbon vapor deposition (CVD) and plasma pyrolysis. The byproducts of these technologies can act as a catalyst poison or reactor deadload to the Sabatier reactor. Hydrogen separation techniques must be utilized to maintain the Sabatier catalyst during gas recycling and must be scalable, non-energy intensive, and safe to operate in a habitation setting. Research indicated that metal-organic frameworks (MOFs) could meet these criteria and were tested for their capability to capture the various carbon-based gaseous products of CVD and plasma pyrolysis such as acetylene (C 2 H 2 ), ethylene (C 2 H 4 ), ethane (C 2 H 6 ), and carbon monoxide (CO) which would purify the hydrogen gas stream passing through the MOF. A sub-scale adsorption column was developed by Marshall Space Flight Center to test three MOF candidates against a synthetic gas mixture comprised of process-relevant carbonous gases and hydrogen to evaluate the separation capability of the MOFs. The results of the hydrogen separation capability, isothermal desorption capability, and demonstrated cyclic reuse of the MOF are presented in this paper.

Kagen Crawford

Neuromorphic overparameterisation and few-shot learning in multilayer physical neural networks

Abstract Physical neuromorphic computing, exploiting the complex dynamics of physical systems, has seen rapid advancements in sophistication and performance. Physical reservoir computing, a subset of neuromorphic computing, faces limitations due to its reliance on single systems. This constrains output dimensionality and dynamic range, limiting performance to a narrow range of tasks. Here, we engineer a suite of nanomagnetic array physical reservoirs and interconnect them in parallel and series to create a multilayer neural network architecture. The output of one reservoir is recorded, scaled and virtually fed as input to the next reservoir. This networked approach increases output dimensionality, internal dynamics and computational performance. We demonstrate that a physical neuromorphic system can achieve an overparameterised state, facilitating meta-learning on small training sets and yielding strong performance across a wide range of tasks. Our approach’s efficacy is further demonstrated through few-shot learning, where the system rapidly adapts to new tasks.

Science & Technology - Other Topics

Electrochemical Deconstruction of Ortho-Phthalate Plasticizers and Recovery of Plasticizing Moieties

Electrochemical methods for the direct reduction of alkyl esters have been understudied but provide a potential advantage for addressing specific waste streams given that such strategies often require only a minimal chemical profile. One such waste stream that could benefit from electrochemical remediation is poly(vinyl chloride) (PVC) plastics. PVC recycling often faces challenges due to the complexity of such waste. Solvent-based recycling methods pose several advantages for addressing post-use PVC; however, such methods are complicated by the high amounts of toxic legacy plasticizers (ortho-phthalates) present in PVC. A potential solution to addressing such phthalates is to address them electrochemically, coupled with recovery of the resulting valuable products. Presented herein is an optimized electrochemical method for ester activation that is leveraged to separate and recover the aromatic and alkyl components of ortho-phthalate plasticizers. The resulting aliphatic alcohols may be reused to prepare other non-toxic plasticizers. This electro-degradation method is demonstrated on six phthalates that have been identified to pose health concerns in addition to plasticizers recovered from commercial samples of PVC.

di-(2-ethylhexyl) phthalate

Observational evidence for Criegee intermediate oligomerization reactions relevant to aerosol formation in the troposphere

Criegee intermediates are reactive intermediates that are implicated in transforming the composition of Earth’s troposphere and in the formation of secondary organic aerosol, impacting Earth’s radiation balance, air quality and human health. Yet, direct identification of their signatures in the field remains elusive. Here, from particulate and gas-phase mass-spectrometric measurements in the Amazon rainforest, we identify sequences of masses consistent with the expected signatures of oligomerization of the CH 2 OO Criegee intermediate, a process implicated in ozonolysis-driven aerosol formation. In this study, we assess the potential contributions of oligomerization through laboratory ozonolysis experiments, direct kinetic studies of Criegee intermediate reactions, and high-level theoretical calculations. Global atmospheric models built on these kinetics results indicate that Criegee intermediate chemistry may play a larger role in altering the composition of Earth’s troposphere than is captured in current atmospheric models, especially in areas of high humidity. However, the models still capture only a relatively small fraction of the observed signatures, suggesting considerable underestimates of Criegee intermediate concentrations and reactivity and/or the dominance of other, presently uncharacterized, oxidation mechanisms. Resolving the remaining uncertainties in emission inventories and the effects of atmospheric water vapour on key chemical reactions will be required to definitively assess the role of Criegee intermediate oligomerization reactions.

58 GEOSCIENCES