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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Enhancing anomalous Hall effect with suppressed ferromagnetism in the SrTiO 3 -confined bilayer heterostructure of ultrathin SrRuO 3 and SrIrO 3

Ferromagnetism is an essential ingredient for anomalous Hall effect. SrRuO 3 is a representative ferromagnetic oxide that exhibits anomalous Hall effect even down to the monolayer confinement limit. Paramagnetic metal SrIrO 3 , on the other hand, becomes an antiferromagnetic insulator when confined to a monolayer. Here, in this study, we show that, by forming a confined bilayer structure of SrRuO 3 and SrIrO 3 monolayers with SrTiO 3 spacers, the anomalous Hall effect is significantly enhanced while the ferromagnetism as well as the perpendicular magnetic anisotropy are suppressed. These effects originate from interfacial Ru–Ir hybridization that modifies the electronic structure in the vicinity of the Fermi level. Our work demonstrates that confined bilayer heterostructure is an useful design for exploring the synergistic combination of interfacial coupling and quantum confinement of complex oxides.

anomalous hall effect↗
DOE OSTI2021

Strong Electronic Coupling of Graphene Nanoribbons onto Basal Plane of a Glassy Carbon Electrode

The grafting of molecular motifs to the conductive carbon represents a promising approach toward improved hybrid materials for electrocatalytic applications. Here, we investigate the electrochemical behavior of graphene nanoribbons (GNR) deposited onto a glassy carbon electrode using pi - pi stacking interactions. Using the bipyrimidine moiety on the nanoribbon edges as a reporter of the proton-coupled electron transfer chemistry, we illustrate that the simple electrochemical treatment of as-deposited nanoribbon generates a hybrid material that is in strong electronic communication with the conductive support. Overall, this work shows a strategy for modifying the basal plane of carbon materials and provides a potential platform for the incorporation of catalytic metal sites via coordination through the N-functionalities of GNR.

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

..delta..-Learning of High-Fidelity Electronic Structure Using Graph Neural Networks with Modified Node-Level Features

In this work, we present a ..delta..-learning approach for predicting the eigenvalues calculated with the hybrid functional HSE06 (..epsilon..nkHSE) for a set of metal and nitrogen doped graphene catalysts (MNCs) from Perdew-Burke-Ernzerhof (PBE) inputs. The model presented here incorporates electronic scalar features along with structural information in a graph neural network (GNN). In particular, the PBE eigenvalues for different bands and k-points and orbital-resolved projectors are combined with the applied potential as node-level features along with structural information within the Atomistic Line Graph Neural Network (ALIGNN) architecture. These features enable flexibility for systems with electrified interfaces, such as in electrocatalysts and achieves mean absolute error (MAE) of less than 0.1 eV. The machine learning model reported here achieves a strong generalization to left-out adsorbates (MAE = 0.074 eV) and leave-one-chemical-space-out (MAE = 0.08 eV) and completely left-out metals (MAE = 0.072 eV), confirming the robustness of the machine learning (ML) model in predicting ..epsilon..nkHSE.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Surface plasmons induce topological transition in graphene/α-MoO3 heterostructures

Abstract Polaritons in hyperbolic van der Waals materials—where principal axes have permittivities of opposite signs—are light-matter modes with unique properties and promising applications. Isofrequency contours of hyperbolic polaritons may undergo topological transitions from open hyperbolas to closed ellipse-like curves, prompting an abrupt change in physical properties. Electronically-tunable topological transitions are especially desirable for future integrated technologies but have yet to be demonstrated. In this work, we present a doping-induced topological transition effected by plasmon-phonon hybridization in graphene/α-MoO 3 heterostructures. Scanning near-field optical microscopy was used to image hybrid polaritons in graphene/α-MoO 3 . We demonstrate the topological transition and characterize hybrid modes, which can be tuned from surface waves to bulk waveguide modes, traversing an exceptional point arising from the anisotropic plasmon-phonon coupling. Graphene/α-MoO 3 heterostructures offer the possibility to explore dynamical topological transitions and directional coupling that could inspire new nanophotonic and quantum devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Angle-resolved polarimetry of hybrid perovskite emission for photonic technologies

Coupling between light and matter strongly depends on the polarization of the electromagnetic field and the nature of excitations in a material. As hybrid perovskites emerge as a promising class of materials for light-based technologies such as LEDs, LASERs, and photodetectors, it is critical to understand how their microstructure changes the intrinsic properties of the photon emission process. While the majority of optical studies have focused on the spectral content, quantum efficiency and lifetimes of emission in various hybrid perovskite thin films and nanostructures, few studies have investigated other properties of the emitted photons such as polarization and emission angle. Here, we use angle-resolved cathodoluminescence microscopy to access the full polarization state of photons emitted from large-grain hybrid perovskite films with spatial resolution well below the optical diffraction limit. In this work, mapping these Stokes parameters as a function of the angle at which the photons are emitted from the thin film surface, we reveal the effect of a grain boundary on the degree of polarization and angle at which the photons are emitted. Such studies of angle- and polarization-resolved emission at the single grain level are necessary for future development of perovskite-based flat optics, where effects of grain boundaries and interfaces need to be mitigated.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Phenomenological mechanisms of hybrid organic–inorganic perovskite thin film deposition by RIR-MAPLE

Resonant infrared, matrix-assisted pulsed laser evaporation (RIR-MAPLE) is a promising technique for the physical vapor deposition of hybrid organic–inorganic perovskites. The approach already has been used to deposit both three-dimensional and two-dimensional hybrid perovskites with material quality comparable to those synthesized by solution processing. However, the phenomenological mechanisms of hybrid perovskite film formation by RIR-MAPLE have not been articulated. Therefore, this work presents a careful investigation of film formation mechanisms of three-dimensional methylammonium lead halide perovskites by considering the temporal evolution of morphology, crystallinity, and optical properties of films deposited by RIR-MAPLE.

Barraza, E. T. (ORCID:0000000328681496)↗
DOE OSTI2024

Electronic properties of corundum-like Ir 2 O 3 and Ir 2 O 3 -Ga 2 O 3 alloys

In the hexagonal, corundum-like structure, α-Ga 2 O 3 has a bandgap of ~5.1 eV, which, combined with its relatively small electron effective mass, high Baliga's figure of merit, and high breakdown field, makes it a promising candidate for power electronics. Ga 2 O 3 is easy to dope n-type, but impossible to dope p-type, impeding the realization of some electronic device designs. Developing a lattice-matched p-type material that forms a high-quality heterojunction with n-type Ga 2 O 3 would open new opportunities in electronics and perhaps optoelectronic devices. In this work, we studied Ir 2 O 3 as a candidate for that purpose. Using hybrid density functional theory calculations we predict the electronic band structure of α-Ir 2 O 3 and compare that to α-Ga 2 O 3 , and study the stability and electronic properties of α-(Ir x Ga 1–x ) 2 O 3 alloys. We discuss the band offset between the two materials and compare it with recently available experimental data. We find that the Ir d bands that compose the top of the valence band in α-Ir 2 O 3 are much higher in energy than O p bands in α-Ga 2 O 3 , possibly enabling effective p-type doping. Finally, our results provide an insight into using the Ir 2 O 3 or Ir 2 O 3 -Ga 2 O 3 alloys as p-type material lattice-matched to α-Ga 2 O 3 for the realization of p–n heterojunctions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Quantum criticality in coupled hybrid metal-semiconductor islands

We show that the combined effects of a dynamical Coulomb blockade and integer quantum Hall effect in a coupled hybrid metal-semiconductor setup provide a pathway for realizing resonant tunneling in Luttinger liquids. This hybrid setup can be brought to the quantum critical regime by varying gate voltages and contact resistances. We explore the nature of quantum criticality, Kondo effect, charge fractionalization, and transport in such a hybrid setup, and verify their robust non-Fermi-liquid behaviors. In conclusion, our work opens a promising route for quantum simulating exotic zero-temperature quantum critical phenomena associated with Luttinger-liquid physics in a nanoengineered electronic circuit with well-defined quantum Hall channels.

Coulomb blockade↗
DOE OSTI2023

Convex Optimization for Nonequilibrium Steady States on a Hybrid Quantum Processor

Finding the transient and steady state properties of open quantum systems is a central problem in various fields of quantum technologies. Here, in this work, we present a quantum-assisted algorithm to determine the steady states of open system dynamics. By reformulating the problem of finding the fixed point of Lindblad dynamics as a feasibility semidefinite program, we bypass several well-known issues with variational quantum approaches to solving for steady states. We demonstrate that our hybrid approach allows us to estimate the steady states of higher dimensional open quantum systems and discuss how our method can find multiple steady states for systems with symmetries.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Fault-Tolerant Operation of Bosonic Qubits with Discrete-Variable Ancillae

Fault-tolerant quantum computation with bosonic qubits often necessitates the use of noisy discrete-variable ancillae. In this work, we establish a comprehensive and practical fault-tolerance framework for such a hybrid system and synthesize it with fault-tolerant protocols by combining bosonic quantum error correction (QEC) and advanced quantum control techniques. We introduce essential building blocks of error-corrected gadgets by leveraging ancilla-assisted bosonic operations using a generalized variant of path-independent quantum control. Using these building blocks, we construct a universal set of error-corrected gadgets that tolerate a single-photon loss and an arbitrary ancilla fault for four-legged cat qubits. Notably, our construction requires only dispersive coupling between bosonic modes and ancillae, as well as beam-splitter coupling between bosonic modes, both of which have been experimentally demonstrated with strong strengths and high accuracy. Moreover, each error-corrected bosonic qubit is comprised of only a single bosonic mode and a three-level ancilla, featuring the hardware efficiency of bosonic QEC in the full fault-tolerant setting. We numerically demonstrate the feasibility of our schemes using current experimental parameters in the circuit-QED platform. Finally, we present a hardware-efficient architecture for fault-tolerant quantum computing by concatenating the four-legged cat qubits with an outer qubit code utilizing only beam-splitter couplings. Our estimates suggest that the overall noise threshold can be reached using existing hardware. These developed fault-tolerant schemes extend beyond their applicability to four-legged cat qubits and can be adapted for other rotation-symmetrical codes, offering a promising avenue toward scalable and robust quantum computation with bosonic qubits. Published by the American Physical Society 2024

Physics↗
DOE OSTI2021

Fiber optic system for direct detection of CO 2 leakage in carbon storage wells (Abbreviated Final Report)

The feasibility study focused on the development of new fiber for distributed chemical sensing that will allow direct detection of CO2 leakages in the environment. This is particularly important for monitoring well integrity for carbon capture and storage (CSS), which can provide early warning for an incoming well failure and potential CO2 leaking through it. We proposed Raman or IR interrogation within gas-filled Holey Fibers (HoFs) interleaved with Fiber Bragg Grating (FBG) sections, so that the location and concentration of the gases would be provided simultaneously. The methodology would overcome current roadblocks to using fiber optics for CO2 (and other gases) detection in wells with direct in-situ measurements of concentration along with other important parameters such as temperature and pressure. We were able to assess commercially available IR/Raman hollow core fiber and demonstrated detection of CO2 through them in our controlled environment setups at various pressure conditions. We have also established the ability of drilling precisely with fs-lases side holes to enable penetration of CO2 into the hollow core fiber and reduce diffusion rates. Open joint collars were also explored with double functionality: to obtain splice to solid core fiber critical for field deployment and create gas ingress locations. Both diffusion-only and pressurized fiber system have been constructed following COMSOL based semi-hybrid optical /fluidodynamics models. FBGs have been identified and procured and characterized. Along the work we leveraged internal modeling/design, photonics/laser characterization, optical fiber fabrication, and AM lab capabilities to design, develop and test in-house components or assemblies. Our results indicate the potential of HoF for CO2 downhole direct detection.

25 ENERGY STORAGE↗
DOE OSTI2025

AI Applications to Physics Experiments at Jefferson Lab

We survey how AI/ML is being deployed across Jefferson Lab's experimental and accelerator programs. In EPSCI, Hydra applies computer vision to automate real-time data-quality monitoring across all four experimental halls, replacing manual inspection of hundreds to thousands of histograms per shift. AIEC (AI Experiment Controls) uses ML to stabilize drift chamber gains and is now part of standard CEBAF production running, while AI Optimized Polarization (AIOP) targets autonomous control of polarized targets and photon beam angular alignment. In CASA, cavity fault classification models identify faulted cavities and trip types from waveform data with ~85% and ~78% agreement to labeled data, respectively, and are deployed in production; a separate effort applies LLMs and hybrid search to make the CEBAF operations logbook AI-ready. QCD-focused work includes transformer- and GAN-based generative models for particle-level event simulation, with distributed GAN training scaling studies on Polaris. Additional efforts span ML-on-FPGA for the EIC and a new Data Science Department coordinating anomaly detection, uncertainty quantification, and HPC-scalable ML lab-wide. Collectively, these projects illustrate AI's growing role in improving efficiency across JLab's nuclear physics mission.

Mei, Xinxin [Thomas Jefferson National Accelerator↗
DOE OSTI2022

Developments in Performance and Portability for MadGraph5_aMC@NLO

Event generators simulate particle interactions using Monte Carlo techniques, providing the primary connection between experiment and theory in experimental high energy physics. These software packages, which are the first step in the simulation worflow of collider experiments, represent approximately 5 to 20% of the annual WLCG usage for the ATLAS and CMS experiments. With computing architectures becoming more heterogeneous, it is important to ensure that these key software frameworks can be run on future systems, large and small. In this contribution, recent progress on porting and speeding up the Madgraph5_aMC@NLO event generator on hybrid architectures, i.e. CPU with GPU accelerators, is discussed. The main focus of this work has been in the calculation of scattering amplitudes and "matrix elements", which is the computational bottleneck of an event generation application. For physics processes limited to QCD leading order, the code generation toolkit has been expanded to produce matrix element calculations using C++ vector instructions on CPUs and using CUDA for NVidia GPUs, as well as using Alpaka, Kokkos and SYCL for multiple CPU and GPU architectures. Performance is reported in terms of matrix element calculations per time on NVidia, Intel, and AMD devices. The status and outlook for the integration of this work into a production release usable by the LHC experiments, with the same functionalities and very similar user interfaces as the current Fortran version, is also described.

Valassi, Andrea↗
DOE OSTI2022

Examining polymer‐protein biophysical interactions with small‐angle x‐ray scattering and quartz crystal microbalance with dissipation

Abstract Polymer‐protein hybrids can be deployed to improve protein solubility and stability in denaturing environments. While previous work used robotics and active machine learning to inform new designs, further biophysical information is required to ascertain structure–function behavior. Here, we show the value of tandem small‐angle x‐ray scattering (SAXS) and quartz crystal microbalance with dissipation (QCMD) experiments to reveal detailed polymer‐protein interactions with horseradish peroxidase (HRP) as a test case. Of particular interest was the process of polymer‐protein complex formation under thermal stress whereby SAXS monitors formation in solution while QCMD follows these dynamics at an interface. The radius of gyration ( R g ) of the protein as measured by SAXS does not change significantly in the presence of polymer under denaturing conditions, but thickness and dissipation changes were observed in QCMD data. SAXS data with and without thermal stress were utilized to create bead models of the potential complexes and denatured enzyme, and each model fit provided insight into the degree of interactions. Additionally, QCMD data demonstrated that HRP deforms by spreading upon surface adsorption at low concentration as shown by longer adsorption times and smaller frequency shifts. In contrast, thermally stressed and highly inactive HRP had faster adsorption kinetics. The combination of SAXS and QCMD serves as a framework for biophysical characterization of interactions between proteins and polymers which could be useful in designing polymer‐protein hybrids.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Hybrid Machine Learning for Scanning Near-Field Optical Spectroscopy

The underlying physics behind an experimental observation often lacks a simple analytical description. This is especially the case for scanning probe microscopy techniques, where the interaction between the probe and the sample is nontrivial. Realistic modeling to include the details of the probe is always exponentially more difficult than its "spherical cow" counterparts. On the other hand, a well-trained artificial neural network based on real data can grasp the hidden correlation between the signal and sample properties. In this work, we show that, via a combination of model calculation and experimental data acquisition, a physics-infused hybrid neural network can predict the tip-sample interaction in the widely used scattering-type scanning near-field optical microscope. This hybrid network provides a long-sought solution for accurate extraction of material properties from tip-specific raw data. The methodology can be extended to other scanning probe microscopy techniques as well as other data-oriented physical problems in general.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Distributed Wind-Hybrid Microgrids with Autonomous Controls and Forecasting

Distributed wind-hybrid microgrids have the potential to provide key resilience and economic benefits to both the customers they serve and the utility grids they are connected to. Such microgrids will likely be a key part of the grid of the future, whether connected to large utility grids or linked together in multi-microgrid systems. Through the hybridization of distributed wind and solar photovoltaics, autonomous device-level and system-level controls, battery energy storage systems with smart inverters, and forecasting, these microgrids could maintain local stability and provide grid services - all with renewable power. In the literature, these elements have been considered individually. However, they have not been combined and demonstrated at a high fidelity, which is essential to prove the concept's operation before moving to hardware-in-the-loop and physical demonstrations. In this work, we develop a high-fidelity MATLAB-Simulink model of a real distributed wind-hybrid microgrid that includes all these elements. We demonstrate the microgrid maintaining stability and production in a variety of islanded, grid-connected, and transition scenarios. This includes riding through faults and grid transitions, handling resource variability, and providing grid services. The results demonstrate, at a high fidelity, how distributed wind-hybrid microgrids can operate in an economic and resilient fashion. Finally, we provide recommendations for future research to move advanced distributed wind-hybrid microgrids toward deployment.

ancillary services↗
DOE OSTI2021

Coherent Gate Operations in Hybrid Magnonics

Electromagnonics-the hybridization of spin excitations and electromagnetic waves-has been recognized as a promising candidate for coherent information processing in recent years. Among its various implementations, the lack of available approaches for real-time manipulation on the system dynamics has become a common and urgent limitation. In this work, by introducing a fast and uniform modulation technique, we successfully demonstrate a series of benchmark coherent gate operations in hybrid magnonics, including semiclassical analogies of Landau-Zener transitions, Rabi oscillations, Ramsey interference, and controlled mode swap operations. Finally, our approach lays the groundwork for dynamical manipulation of coherent signals in hybrid magnonics and can be generalized to a broad range of applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗