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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

SQMS Quantum R&D in Machine Learning, Optimization and Sensing beyond Fundamental Physics Applications

This newly formed team at SQMS under the Ecosystem Thrust is looking to develop capabilities impacting societal advances outside the core domain of HEP and condensed matter physics. We explicitly leverage the experimental and algorithmic innovations developed across all groups as well as connect to broad-scope external projects of the diverse team of PIs. As the inaugural set of projects, we are studying numerically quantum machine learning models inspired by efficiently trainable echo-state and orthogonal neural networks and developing designs for related experiments to be performed on quantum processors based on SQMS SRF cQED technology and Rigetti s transmon arrays. Investigated models exploit ideas and lessons learned from multiple prior work by SQMS team members in a variety of internal and external activities [R1]. Target initial applications include noisy signal processing, potentially captured by quantum sensors or noisy QPUs, as well as simulation and classification of healthcare data. For instance, image reconstruction of the brain s electrical properties by solving the inverse Maxwell equation problem with uncertainty [R2] through a hybrid quantum-classical physics-informed architecture for time-dependent processes [R3]. The group is also investigating the application and development of novel quantum sensors based on magnetic levitation of a superconducting sphere coupled to a superconducting qubit. This coupling enables high-precision measurements of the position of the sphere, which can be used for sensitive detection of forces, enabling practical applications such as gravimetry for geophysics analysis, or accelerometry for GPS-denied navigation [R4] [R1] Rieffel, Eleanor G., Ata Akbari Asanjan, M. Sohaib Alam, Namit Anand, David E. Bernal Neira, Sophie Block, Lucas T. Brady et al. "Assessing and advancing the potential of quantum computing: A NASA case study." Future Generation Computer Systems (2024). [R2] Yu, X., Serrall s, J.E., Giannakopoulos, I.I., Liu, Z., Daniel, L., Lattanzi, R. and Zhang, Z., 2023. Pifon-ept: Mr-based electrical property tomography using physics-informed fourier networks. IEEE Journal on Multiscale and Multiphysics Computational Techniques. [R3] Wudarski, Filip, Daniel OConnor, Shaun Geaney, Ata Akbari Asanjan, Max Wilson, Elena Strbac, P. Aaron Lott, and Davide Venturelli. "Hybrid quantum-classical reservoir computing for simulating chaotic systems." arXiv preprint arXiv:2311.14105 (2023). [R4] Higgins, Gerard, Saarik Kalia, and Zhen Liu. "Maglev for dark matter: Dark-photon and axion dark matter sensing with levitated superconductors." Physical Review D 109.5 (2024): 055024.

Venturelli, Davide↗
NASA NTRS1980

Phase 1 of the near term hybrid passenger vehicle development program. Appendix B: Trade-off studies, volume 1

Tradeoff study activities and the analysis process used are described with emphasis on (1) review of the alternatives; (2) vehicle architecture; and (3) evaluation of the propulsion system alternatives; interim results are presented for the basic hybrid vehicle characterization; vehicle scheme development; propulsion system power and transmission ratios; vehicle weight; energy consumption and emissions; performance; production costs; reliability, availability and maintainability; life cycle costs, and operational quality. The final vehicle conceptual design is examined.

Traversi, M.↗
DOE OSTI2024

Building Artificial Layered Solids from the Bottom-up: Materials by Design to Enable New Energy Technologies

This final technical report summarizes the key accomplishments on this DOE Early Career Program award received by PI Guihua Yu at the University of Texas at Austin. The main goal of this ECP award was to develop synthetic methodologies, self-assembly approaches towards structurally controlled nanosheets-like solids from the bottom up, and to understand and characterize their chemical/physical characteristics for the design of future-generation energy devices with novel functions and properties, that will have direct implications for energy science and technologies such as energy storage and conversion, and catalysis. The project accomplished these goals by completing the following objectives: • Rational design, synthesis, and self-assembly of structurally-controlled molecular ‘nanosheets’ materials. Moving beyond conventional van der Waals two-dimensional crystals, this project enables new synthesis and processing strategies to develop ultrathin nanosheets materials, from inorganic transition-metal oxides-based, to hybrid organic-inorganic nanomaterials, with structural factors such as facet, thickness and pore structure being well controlled during synthesis or assembly processes. • Fundamental understanding and electrochemical characterization of these assembled molecular ‘nanosheets’ materials via charge/mass transport studies through electrochemical intercalation of different metal ions for next-generation energy storage, as well as electrocatalytic studies using this new material platform for understanding catalytic reaction kinetics and the roles of surface functionalization and interface interactions owing to atomic thickness, nanoscale porosity, and other structural factors.

36 MATERIALS SCIENCE↗
NASA NTRS1989

Ion conics and counterstreaming electrons generated by lower hybrid waves in the earth's magnetosphere

The exotic phenomenon of energetic ion-conic and counterstreaming electron formation by lower hybrid waves along discrete auroral field lines in the earth magnetosphere is considered. Mean-particle calculations, plasma simulations, and analytical treatments of the acceleration processes are described. It is shown that, in the primary auroral electron-beam region, lower hybrid waves could be an efficient mechanism for the transverse heating of H (+) and O(+) ions of ionospheric origin, as well as for the field-aligned heating of the ambient electrons leading to coincident counterstreaming electron distributions. For O(+) ions to be energized by such a wave-particle interaction process, however, some sort of preheating mechanism is required.

Chang, Tom↗
DOE OSTI2025

Effect of Networking Density on the Patterning Performance of Molecular Layer Deposited Alucone Electron Beam/EUV Resists

One of the main barriers to continued device scaling in the era of extreme ultraviolet (EUV) lithography is the need for improved photoresist chemistries to address challenges such as poor EUV sensitivity, inadequate etch resistance, and pattern collapse. Metal-organic photoresists are a promising class of materials that can address many of these challenges, and among them, resists deposited via hybrid molecular layer deposition (MLD) have attracted interest for their unique advantages in thickness control, chemical homogeneity, and compatibility with vacuum processing. However, despite many successful demonstrations of patterning, little is known about how the molecular design of hybrid MLD resists affects their lithographic performance. In this work, we study the effect of the network structure, a common feature among all hybrid MLD resists, via a series of aluminum alkoxide ("alucone") negative tone resists with varying networking density. Their patterning mechanism is investigated via electron beam lithography (EBL)─a common proxy for EUV─and compared to their EUV-induced reactions studied via flood exposure and in situ characterization. In conclusion, we show that the resist with the least networking density demonstrates the best sensitivity and resolution, with the ability to resolve dense line/space gratings as small as 14 nm half pitch via EBL.

electron beam lithography↗
DOE OSTI2025

Stimulated Emission from Below the Bandgap in Giant Quantum Shells

Colloidal semiconductor nanocrystals (NCs) have emerged as promising candidates for developing solution-processable optical gain media, with potential applications in integrated photonic circuits and lasers. However, the deployment of NCs in these technologies has been hindered by nonradiative Auger recombination of multiexciton states, which shortens the optical gain lifetime and reduces its spectral range. Here, we demonstrate that these limitations can be overcome by using giant colloidal quantum shells (g-QSs), comprising a quantum-confined CdSe shell grown over a large (~14 nm) CdS bulk core. Such bulk-nanoscale architecture minimizes exciton–exciton interactions, leading to suppressed Auger recombination and one of the broadest gain bandwidths reported for colloidal nanomaterials, spanning energies both above and, remarkably, below the bandgap. Ultrafast transient absorption and photoluminescence measurements demonstrate that the high-energy portion of optical gain arises from states containing more than 15 excitons per particle while the unusual sub-bandgap gain behaviour results from an Auger-assisted radiative recombination, a mechanism that has traditionally been viewed as a loss pathway. Altogether, these results reveal a unique gain regime associated with bulk-nanocrystal hybrid systems, which offers a promising path toward solution-processable light sources.

Absorption↗
DOE OSTI2025

Engineering long-lived entanglement through dissipation in quantum hybrid solid-state platforms

Spin squeezing, a form of many-body entanglement, is a crucial resource in quantum metrology and information processing. While experimentally viable protocols for generating stable spin squeezing have been proposed in quantum optics setups, there is growing interest in quantum hybrid solid-state systems as alternative platforms for both engineering and exploring many-body quantum phenomena. In this work, we propose a scheme to generate long-lived spin squeezing in an ensemble of solid-state qubits interacting with electromagnetic noise emitted by a squeezed solid-state bath. We identify the conditions under which quantum correlations within the bath can be transferred to the qubit array, driving it into an entangled state independently of its initial configuration. To assess the experimental feasibility of our approach, we analyze the dynamics of an array of solid-state spin defects coupled to a common ferromagnetic bath, which is driven into a non-equilibrium squeezed state through its interaction with a surface acoustic wave mode. Our results demonstrate that the ensemble can exhibit steady-state spin squeezing under suitable conditions, opening new pathways for the generation of robust many-body entanglement in solid-state spin ensembles.

NV centers↗
DOE OSTI2024

An integrative framework reveals widespread gene flow during the early radiation of oaks and relatives in Quercoideae (Fagaceae)

ABSTRACT Although the frequency of ancient hybridization across the Tree of Life is greater than previously thought, little work has been devoted to uncovering the extent, timeline, and geographic and ecological context of ancient hybridization. Using an expansive new dataset of nuclear and chloroplast DNA sequences, we conducted a multifaceted phylogenomic investigation to identify ancient reticulation in the early evolution of oaks (Quercus). We document extensive nuclear gene tree and cytonuclear discordance among major lineages ofQuercusand relatives in Quercoideae. Our analyses recovered clear signatures of gene flow against a backdrop of rampant incomplete lineage sorting, with gene flow most prevalent among major lineages ofQuercusand relatives in Quercoideae during their initial radiation, dated to the Early‐Middle Eocene. Ancestral reconstructions including fossils suggest ancestors ofCastanea + Castanopsis,Lithocarpus, and the Old World oak clade probably co‐occurred in North America and Eurasia, while the ancestors ofChrysolepis, Notholithocarpus, and the New World oak clade co‐occurred in North America, offering ample opportunity for hybridization in each region. Our study shows that hybridization—perhaps in the form of ancient syngameons like those seen today—has been a common and important process throughout the evolutionary history of oaks and their relatives. Concomitantly, this study provides a methodological framework for detecting ancient hybridization in other groups.

Biochemistry & Molecular Biology↗
NASA NTRS2006

Adapting Covariance Propagation to Account for the Presence of Modeled and Unmodeled Maneuvers

This paper explores techniques that can be used to adapt the standard linearized propagation of an orbital covariance matrix to the case where there is a maneuver and an associated execution uncertainty. A Monte Carlo technique is used to construct a final orbital covariance matrix for a 'prop-burn-prop' process that takes into account initial state uncertainty and execution uncertainties in the maneuver magnitude. This final orbital covariance matrix is regarded as 'truth' and comparisons are made with three methods using modified linearized covariance propagation. The first method accounts for the maneuver by modeling its nominal effect within the state transition matrix but excludes the execution uncertainty by omitting a process noise matrix from the computation. The second method does not model the maneuver but includes a process noise matrix to account for the uncertainty in its magnitude. The third method, which is essentially a hybrid of the first two, includes the nominal portion of the maneuver via the state transition matrix and uses a process noise matrix to account for the magnitude uncertainty. The first method is unable to produce the final orbit covariance except in the case of zero maneuver uncertainty. The second method yields good accuracy for the final covariance matrix but fails to model the final orbital state accurately. Agreement between the simulated covariance data produced by this method and the Monte Carlo truth data fell within 0.5-2.5 percent over a range of maneuver sizes that span two orders of magnitude (0.1-20 m/s). The third method, which yields a combination of good accuracy in the computation of the final covariance matrix and correct accounting for the presence of the maneuver in the nominal orbit, is the best method for applications involving the computation of times of closest approach and the corresponding probability of collision, PC. However, applications for the two other methods exist and are briefly discussed. Although the process model ("prop-burn-prop") that was studied is very simple - point-mass gravitational effects due to the Earth combined with an impulsive delta-V in the velocity direction for the maneuver - generalizations to more complex scenarios, including high fidelity force models, finite duration maneuvers, and maneuver pointing errors, are straightforward and are discussed in the conclusion.

Schiff, Conrad↗
NASA NTRS1980

Fabrication of LARC 160/NR150B2 hybrid matrix polyimide composites

Graphite-polyimide composite materials exhibit high performance, low weight, and good thermal-oxidative stability, making them promising candidates for Space Shuttle applications. However, no single material is excellent in all respects: processibility, thermal-oxidative stability, toughness, and mechanical properties. This paper describes the development of hybrid matrix composite laminates that combine the attributes of two polyimide resins, NR150B2 and LARC 160, while avoiding their drawbacks. High quality laminates were fabricated from each resin system, and hybrid laminates were successfully co-cured, evaluated, and optimized.

Bergren, O. D.↗
DOE OSTI2024

“Green” Fabrication of High-performance Transparent Conducting Electrodes by Blade Coating and Photonic Curing on PET for Perovskite Solar Cells

This study presents an innovative material processing approach to fabricate transparent conducting electrodes (TCEs) on polyethylene terephthalate (PET) substrates using blade coating and photonic curing. The hybrid TCEs consist of a multiscale Ag network, combining silver metal bus lines and nanowires, overcoated by an indium zinc oxide layer, and then photonically cured. Blade coating ensures film uniformity and thickness control over large areas. Photonic curing, a non-thermal processing method with significantly lower carbon emissions, enhances the conductivity and transparency of the coated layers. Our hybrid TCEs achieve an average transmittance of (81 ± 0.4)% referenced to air ((90 ± 0.4)% referenced to the PET substrate) in the visible range, an average sheet resistance of (11 ± 0.5) Ω sq−1, and an average surface roughness of (4.3 ± 0.4) nm. We benchmark these values against commercial PET/TCE substrates. Mechanical durability tests demonstrate <3% change in resistance after 2000 bending cycles at a 1 in radius. The scalable potential of the hybrid TCE fabrication method is demonstrated by high uniformity and excellent properties in 7 in × 8 in large-area samples and by performing the photonic curing process at 11 m min−1. Furthermore, halide perovskite solar cells fabricated on these hybrid TCEs achieve average and champion power conversion efficiencies of (10.5 ± 1.0) % and 12.2%, respectively, and significantly outperform devices made on commercial PET/TCEs. This work showcases our approach as a viable pathway for high-speed “green” manufacturing of high-performance TCEs on PET substrates for flexible optoelectronic devices.

Bonner, Justin C↗
DOE OSTI2024

Error mitigation in variational quantum eigensolvers using tailored probabilistic machine learning

Quantum computing technology has the potential to revolutionize the simulation of materials and molecules in the near future. A primary challenge in achieving near-term quantum advantage is effectively mitigating the noise effects inherent in current quantum processing units (QPUs). This challenge is also decisive in the context of quantum-classical hybrid schemes employing variational quantum eigensolvers (VQEs) that have attracted significant interest in recent years. In this paper, we present a method that employs parametric Gaussian process regression (GPR) within an active learning framework to mitigate noise in quantum computations, focusing on VQEs. Our approach, grounded in probabilistic machine learning, exploits a custom prior based on the VQE ansatz to capture the underlying correlations between VQE outputs for different variational parameters, thereby enhancing both accuracy and efficiency. We demonstrate the effectiveness of our method on a two-site Anderson impurity model and a eight-site Heisenberg model, using the IBM open-source quantum computing framework, Qiskit, showcasing substantial improvements in the accuracy of VQE outputs while reducing the number of direct QPU energy evaluations. This paper contributes to the ongoing efforts in quantum-error mitigation and optimization, bringing us a step closer to realizing the potential of quantum computing in quantum matter simulations. Published by the American Physical Society 2024

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2014

Multi-Objective Hybrid Optimal Control for Interplanetary Mission Planning

Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed, and in some cases the final destination. Because low-thrust trajectory design is tightly coupled with systems design, power and propulsion characteristics must be chosen as well. In addition, a time-history of control variables must be chosen which defines the trajectory. There are often may thousands, if not millions, of possible trajectories to be evaluated. The customer who commissions a trajectory design is not usually interested in a point solution, but rather the exploration of the trade space of trajectories between several different objective functions. This can be a very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the mission design problem as a multi-objective hybrid optimal control problem. The method is demonstrated on hypothetical mission to the main asteroid belt and to Deimos.

Low Thrust↗
NASA NTRS2015

Multi-Objective Hybrid Optimal Control for Interplanetary Mission Planning

Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed, and in some cases the final destination. Because low-thrust trajectory design is tightly coupled with systems design, power and propulsion characteristics must be chosen as well. In addition, a time-history of control variables must be chosen which defines the trajectory. There are often many thousands, if not millions, of possible trajectories to be evaluated. The customer who commissions a trajectory design is not usually interested in a point solution, but rather the exploration of the trade space of trajectories between several different objective functions. This can be very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the mission design problem as a multi-objective hybrid optimal control problem. The methods is demonstrated on hypothetical mission to the main asteroid belt and to Deimos.

Trajectory Design↗
DOE OSTI2026

Achieving high rate performance in hybrid pristine-recycled cathodes using model-informed electrode designs

Direct recycling lithium-ion battery cathodes, a process that retains the engineered oxide structures from end-of-life materials, presents a cost-effective and energy-efficient alternative to other battery recycling methods. However, while direct-recycled cathodes have demonstrated performance comparable to that of pristine materials at low cycling rates, their high-rate performance remains uncertain. Morphology changes in cathode particles, a main mode of degradation, directly impact rate performance by limiting surface kinetics and solid-phase diffusion. If direct recycling processes do not sufficiently restore pristine-like morphologies, the recycled materials may retain structural defects that hinder high-rate performance. The present work uses a physics-based pseudo-2D model to simulate hybrid electrodes with pristine and artificially “aged/recycled” NMC materials to investigate potential impacts of incorporating performance-limited aged cathode materials into cells. The study highlights how differences in transport and kinetic properties can influence rate capabilities in mixed electrodes — particularly in high-loading cells in high-demand applications. However, model results also reveal a possible mitigation strategy via dual-layer electrode architectures with lower-performing materials positioned near the current collector. Simulations of 4.0 mAh cm −2 cells cycled at 4C using a dual-layer architecture provided approximately 5%–30% more capacity in constant-current protocols compared to homogeneously blended electrode architectures with the same loadings and mixed-material compositions. These findings highlight the importance of strategic electrode design in minimizing potential performance losses and facilitating the integration of recycled materials into high-performance batteries, advancing sustainable and cost-effective battery manufacturing.

25 ENERGY STORAGE↗
NASA NTRS2015

Multi-Objective Hybrid Optimal Control for Interplanetary Mission Planning

Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed and in some cases the final destination. In addition, a time-history of control variables must be chosen which defines the trajectory. There are often many thousands, if not millions, of possible trajectories to be evaluated. The customer who commissions a trajectory design is not usually interested in a point solution, but rather the exploration of the trade space of trajectories between several different objective functions. This can be a very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very diserable. This work presents such as an approach by posing the mission design problem as a multi-objective hybrid optimal control problem. The method is demonstrated on a hypothetical mission to the main asteroid belt.

Optimization↗
DOE OSTI2024

Hybridized magnonic materials for THz frequency applications

The capability of magnons to hybridize and strongly couple with diverse excitations offers a promising avenue for realizing and controlling emergent properties that hold significant potential for applications in devices, circuits, and information processing. In this Letter, we present recent theoretical and experimental developments in magnon-based hybrid systems, focusing on the combination of magnon excitation in an antiferromagnet with other excitations, namely, plasmons in a topological insulator, phonons in a 2D antiferromagnetic (2D AFM), and photons. Here, the existence of THz frequency magnons, plasmons, and phonons makes magnon-based hybrid systems particularly appealing for high-operating-speed devices. In this context, we explore several directions to advance magnon hybrid systems, including strong coupling between a surface plasmon and magnon polariton in a topological insulator /AFM bilayer, a giant spin Nernst effect induced by magnon–phonon coupling in 2D AFMs, and control of magnon–photon coupling using spin torque.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Innovative Joining Method for Hybrid Composites with Tailored Performance

In various industries, such as renewables and aerospace, the demand for carbon fiber is rapidly growing to meet the requirements of high-performance applications with optimized designs. Traditionally, these optimized designs have been limited to single-material composites due to process constraints. However, this study aims to explore the feasibility of transitioning between two different fiber types for pultrusion and filament winding processes, thereby enhancing design flexibility, and optimizing performance. This research introduces a novel method of hybrid reinforcement through splicing techniques. By employing a splicing method, fibers are merged prior to infusion, resulting in a transition of higher strength compared to traditional joints. Moreover, this technique enables the creation of composites with variable compositions, allowing for the selective placement of properties in a process previously characterized by static properties. The objective of this paper is to evaluate the mechanical properties of dry fiber splicing and its impact on the resulting composite material. Through comprehensive analysis, we aim to provide insights into the feasibility and advantages of employing this innovative splicing technique in composite manufacturing processes.

Guzorek, Steven↗