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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Q-VR: System-Level Design for Future Mobile Collaborative Virtual Reality

High Quality Mobile Virtual Reality (VR) is what the incoming graphics technology era demands: users around the world, regardless of their hardware and network conditions, can all enjoy the immersive virtual experience. However, the state-of-the-art software-based mobile VR designs cannot fully satisfy the realtime performance requirements due to the highly interactive nature of user's actions and complex environmental constraints during VR execution. Inspired by the unique human visual system effects and the strong correlation between VR motion features and realtime hardware-level information, we propose Q-VR, a novel dynamic collaborative rendering solution via software-hardware co-design for enabling future low-latency high-quality mobile VR. At software-level, Q-VR provides flexible high-level tuning interface to reduce network latency while maintaining user perception. At hardware-level, Q-VR accommodates a wide spectrum of hardware and network conditions across users by effectively leveraging the computing capability of the increasingly powerful VR hardware. Extensive evaluation on real-world games demonstrates that Q-VR can achieve an average end-to-end performance speedup of 3.4x (up to 6.7x) over the traditional local rendering design in commercial VR devices, and a 4.1x frame rate improvement over the state-of-the-art static collaborative rendering.

Xie, Chenhao↗
DOE OSTI2020

High- Q Nanophotonic Resonators on Diamond Membranes using Templated Atomic Layer Deposition of TiO 2

Integrating solid-state quantum emitters with nanophotonic resonators is essential for efficient spin-photon interfacing and optical networking applications. While diamond color centers have proven to be excellent candidates for emerging quantum technologies, their integration with optical resonators remains challenging. Conventional approaches based on etching resonators into diamond often negatively impact color center performance and offer low device yield. In this work, we developed an integrated photonics platform based on templated atomic layer deposition of TiO 2 on diamond membranes. Our fabrication method yields high-performance nanophotonic devices while avoiding etching wavelength-scale features into diamond. Moreover, this technique generates highly reproducible optical resonances and can be iterated on individual diamond samples, a unique processing advantage. Our approach is suitable for a broad range of both wavelengths and substrates and can enable high-cooperativity interfacing between cavity photons and coherent defects in diamond or silicon carbide, rare earth ions, or other material systems.

42 ENGINEERING↗
DOE OSTI2023

Understanding hydrogen electrocatalysis by probing the hydrogen-bond network of water at the electrified Pt–solution interface

Rational construction of the electrode–solution interface where electrochemical processes occur is of paramount importance in electrochemistry. Efforts to gain better control and understanding of the interface have been hindered by lack of probing methods. Here, in this study, we show that the hydrogen evolution and oxidation reactions (HER/HOR) catalysed by platinum in base can be promoted by introduction of N-methylimidazoles at the platinum–water interface. In situ spectroscopic characterization together with simulations indicate that the N-methylimidazoles facilitate diffusion of hydroxides across the interface by holding the second layer of water close to platinum surfaces, thereby promoting the HER/HOR. We thus propose that the HER/HOR kinetics of platinum in acid and base is governed by diffusion of protons and hydroxides, respectively, through the hydrogen-bond network of interfacial water by the Grotthuss mechanism. Moreover, we demonstrate a 40% performance improvement of an anion exchange membrane electrolyser by adding 1,2-dimethylimidazole into the alkali fed into its platinum cathode.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Atomic‐Scale Mechanisms of Nucleation and Stabilization in CuCrO 2 and CuFeO 2 Delafossite Thin Films on Al 2 O 3

Abstract Delafossite thin films exhibit a range of intriguing physical properties derived from their layered structure, which consists of alternating noble metal ( A + ) and ( B O 2 − ) sublayers in an AB O 2 stoichiometry. The integration of these properties into functional devices requires the successful epitaxial growth of delafossites as thin films on appropriate substrates. Unfortunately, their unique lattice geometry complicates growth, as different delafossites display variable behavior on the same substrate, often unrelated to lattice mismatch. This suggests the presence of yet unidentified stabilization mechanisms that enable the selective growth of certain delafossites, allowing them to be grown either as films themselves or to be used as buffer layers for subsequent deposition. In this study, advanced scanning transmission electron microscopy (STEM) is employed to investigate the nucleation mechanisms governing the stable growth of Cu‐based delafossites on Al 2 O 3 , specifically CuCrO 2 and CuFeO 2 thin films synthesized via molecular‐beam epitaxy. These findings reveal that a combination of a misfit dislocation network at the interface and monolayer‐deep chemical intermixing effectively relieves lattice mismatch strain. This mechanism, which differs fundamentally from that observed in Pd‐based delafossites, provides key insights into the controlled epitaxy of delafossite materials.

Scheid, Anna [Max Planck Institute for Solid State↗
DOE OSTI2023

Proximity-induced chiral quantum light generation in strain-engineered WSe 2 /NiPS 3 heterostructures

Quantum light emitters capable of generating single photons with circular polarization and non-classical statistics could enable non-reciprocal single-photon devices and deterministic spin–photon interfaces for quantum networks. To date, the emission of such chiral quantum light relies on the application of intense external magnetic fields, electrical/optical injection of spin-polarized carriers/excitons or coupling with complex photonic metastructures. Here we report the creation of free-space chiral quantum light emitters via the nanoindentation of monolayer WSe 2 /NiPS 3 heterostructures at zero external magnetic field. These quantum light emitters emit with a high degree of circular polarization (0.89) and single-photon purity (95%), independent of pump laser polarization. In this study, scanning diamond nitrogen-vacancy microscopy and temperature-dependent magneto-photoluminescence studies reveal that the chiral quantum light emission arises from magnetic proximity interactions between localized excitons in the WSe 2 monolayer and the out-of-plane magnetization of defects in the antiferromagnetic order of NiPS 3 , both of which are co-localized by strain fields associated with the nanoscale indentations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

mDNS to support local price server discovery with OpenADR 3 (mDNS for OpenADR 3) v1.0

This software contains a template VEN with local VTN service discovery over mDNS. It provides common starter code for an OpenADR3.0 VEN that advertises itself over mDNS, conducts local VTN service discovery over mDNS, connects to the VTN over HTTP(S), and regularly polls and acts on energy prices and events hosted on the VTN. The software is written to be easily modified to accommodate different VEN appliances, VEN-VTN networking protocols, user interfaces, and default responses, given the wide range of possible use cases for local price server discovery. OpenADR3.0 is an open communications standard from the OpenADR Alliance that is designed to provide two-way information exchange regarding e.g., dynamic price and event signals to utility applications, so that customers can modify their energy usage to save money and reduce their carbon footprint.

Nordman, Bruce [Lawrence Berkeley National Laborat↗
DOE OSTI2022

Equipment Testing Environment (ETE) Process Specification

This document is intended to be utilized with the Equipment Test Environment being developed to provide a standard process by which the ETE can be validated. The ETE is developed with the intent of establishing cyber intrusion, data collection and through automation provide objective goals that provide repeatability. This testing process is being developed to interface with the Technical Area V physical protection system. The document will overview the testing structure, interfaces, device and network logging and data capture. Additionally, it will cover the testing procedure, criteria and constraints necessary to properly capture data and logs and record them for experimental data capture and analysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

A Comparative Study of Physics‐Informed and Data‐Driven Neural Networks for Compound Flood Simulation at River‐Ocean Interfaces: A Case Study of Hurricane Irene

Simulating compound flooding (CF) at the river-ocean interface within large-scale Earth System Models (ESMs) presents significant challenges due to complex interactions between river discharge, storm surge, and tides. This study assesses the comparative advantages of physics-informed and data-driven machine learning (ML) approaches for enhancing local ESM performance. We systematically compare data-driven neural network models (i.e., CNNs, U-Net, Long Short-Term Memory (LSTM), Gated Recurrent Unit), and physics-informed neural network (PINN) models, including vanilla PINN and a finite-difference-based PINN (FD-PINN). Specifically, FD-PINN is introduced to enhance computational efficiency, accelerating vanilla PINNs by ∼6.5 times while improving accuracy. To enhance data-driven model training, a new data-generation approach is developed to sample historical fluvial and coastal flood events, which ensures a robust data set for extreme event prediction. The models are evaluated using a realistic one-dimensional river domain extracted from an ESM's river mesh and the Hurricane Irene event as an independent test case. Results show that FD-PINN achieves accurate predictions with significantly reduced computational costs relative to vanilla PINNs. Among data-driven models, the best overall performance is achieved by a CNN-LSTM hybrid, which balances accuracy and efficiency. While a fully connected CNN (CNN-FC) provides the best accuracy, it incurs high computational cost. Architectures lacking strong temporal modeling tend to underperform on unseen events. These findings highlight the importance of sequence-aware designs for robust generalization. This study reveals the trade-offs between physics-informed and data-driven models and proposes an adaptive hybrid framework for integrating ML into ESMs to enhance local flood simulations.

Earth Systems Modeling↗
DOE OSTI2020

Ions Tune Interfacial Water Structure and Modulate Hydrophobic Interactions at Silica Surfaces

The structure and ultrafast dynamics of the electric double layer (EDL) are central to chemical reactivity and physical properties at solid/aqueous interfaces. While the Gouy–Chapman–Stern model is widely used to describe EDLs, it is solely based on the macroscopic electrostatic attraction of electrolytes for the charged surfaces. Structure and dynamics in the Stern layer are, however, more complex because of competing effects due to the localized surface charge distribution, surface–solvent–ion correlations, and the interfacial hydrogen bonding environment. Here, we report combined time-resolved vibrational sum frequency generation (TR-vSFG) spectroscopy with ab initio DFT-based molecular dynamics simulations (AIMD/DFT-MD) to get direct access to the molecular-level understanding of how ions change the structure and dynamics of the EDL. We show that innersphere adsorbed ions tune the hydrophobicity of the silica–aqueous interface by shifting the structural makeup in the Stern layer from dominant water–surface interactions to water–water interactions. This drives an initially inhomogeneous interfacial water coordination landscape observed at the neat interface toward a homogeneous, highly interconnected in-plane 2D hydrogen bonding (2D-HB) network at the ionic interface, reminiscent of the canonical, hydrophobic air–water interface. This ion-induced transformation results in a characteristic decrease of the vibrational lifetime (T 1 ) of excited interfacial O–H stretching modes from T 1 ~ 600 fs to T 1 ~ 250 fs. Hence, we propose that the T 1 determined by TR-vSFG in combination with DFT-MD simulations can be widely used for a quantitative spectroscopic probe of the ion kosmotropic/chaotropic effect at aqueous interfaces as well as of the ion-induced surface hydrophobicity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A phononic interface between a superconducting quantum processor and quantum networked spin memories

We introduce a method for high-fidelity quantum state transduction between a superconducting microwave qubit and the ground state spin system of a solid-state artificial atom, mediated via an acoustic bus connected by piezoelectric transducers. Applied to present-day experimental parameters for superconducting circuit qubits and diamond silicon-vacancy centers in an optimized phononic cavity, we estimate quantum state transduction with fidelity exceeding 99% at a MHz-scale bandwidth. By combining the complementary strengths of superconducting circuit quantum computing and artificial atoms, the hybrid architecture provides high-fidelity qubit gates with long-lived quantum memory, high-fidelity measurement, large qubit number, reconfigurable qubit connectivity, and high-fidelity state and gate teleportation through optical quantum networks.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Adaptive Interface-PINNs (AdaI-PINNs) for transient diffusion: Applications to forward and inverse problems in heterogeneous media

We model transient diffusion in heterogeneous materials using a novel physics-informed neural networks framework (PINNs) termed Adaptive interface physics-informed neural networks or AdaI-PINNs (Roy et al. arXiv preprint arXiv:2406.04626, 2024). AdaI-PINNs utilize different activation functions with trainable slopes tailored to each material region within the computational domain, allowing for a fully automated and adaptive PINNs approach to model interface problems with strongly and weakly discontinuous solutions. To enhance its performance in highly heterogeneous transient diffusion systems, we prescribe a suite of robust practices, including appropriate non-dimensionalization of equations, a biased sampling method, Glorot initialization, and the hard enforcement of boundary and initial conditions. Here we evaluate the efficacy of the proposed method on several benchmark forward and inverse problems. Comparative studies on one-dimensional and two-dimensional benchmark problems reveal that the modified AdaI-PINNs outperform its unmodified counterpart, achieving root-mean-square errors that are at least two orders of magnitude better in forward problems. For inverse problems, the maximum errors in the approximated diffusion coefficients by modified AdaI-PINNs are four orders of magnitude better than those of the unmodified version. Additionally, modified AdaI-PINNs demonstrate improved stability in problems with large material mismatches.

42 ENGINEERING↗
DOE OSTI2023

Microwave-Based Quantum Control and Coherence Protection of Tin-Vacancy Spin Qubits in a Strain-Tuned Diamond-Membrane Heterostructure

Robust spin-photon interfaces in solids are essential components in quantum networking and sensing technologies. Ideally, these interfaces combine a long-lived spin memory, coherent optical transitions, fast and high-fidelity spin manipulation, and straightforward device integration and scaling. The tin- vacancy center (SnV) in diamond is a promising spin-photon interface with desirable optical and spin properties at 1.7 K. However, the SnV spin lacks efficient microwave control, and its spin coherence degrades with higher temperature. In this work, we introduce a new platform that overcomes these challenges—SnV centers in uniformly strained thin diamond membranes. The controlled generation of crystal strain introduces orbital mixing that allows microwave control of the spin state with 99.36(9)% gate fidelity and spin coherence protection beyond a millisecond. Moreover, the presence of crystal strain suppresses temperature-dependent dephasing processes, leading to a considerable improvement of the coherence time up to 223(10) μs at 4 K, a widely accessible temperature in common cryogenic systems. Critically, the coherence of optical transitions is unaffected by the elevated temperature, exhibiting nearly lifetime-limited optical linewidths. Combined with the compatibility of diamond membranes with device integration, the demonstrated platform is an ideal spin-photon interface for future quantum technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A publicly available PyTorch-$\mathrm{ABAQUS}$ $\mathrm{UMAT}$ deep-learning framework for level-set plasticity

Here this paper introduces a publicly available PyTorch-ABAQUS deep-learning framework of a family of plasticity models where the yield surface is implicitly represented by a scalar-valued function. In particular, our focus is to introduce a practical framework that can be deployed for engineering analysis that employs a user-defined material subroutine (UMAT/VUMAT) for ABAQUS, which is written in FORTRAN. To accomplish this task while leveraging the back-propagation learning algorithm to speed up the neural-network training, we introduce an interface code where the weights and biases of the trained neural networks obtained via the PyTorch library can be automatically converted into a generic FORTRAN code that can be a part of the UMAT/VUMAT algorithm. To enable third-party validation, we purposely make all the data sets, source code used to train the neural-network-based constitutive models, and the trained models available in a public repository. Furthermore, the practicality of the workflow is then further tested on a dataset for anisotropic yield function to showcase the extensibility of the proposed framework. A number of representative numerical experiments are used to examine the accuracy, robustness and reproducibility of the results generated by the neural network models.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Contributions to the optical linewidth of shallow donor-bound excitonic transition in ZnO

Neutral shallow donors in zinc oxide (ZnO) are spin qubits with optical access via the donor-bound exciton. This spin–photon interface enables applications in quantum networking, memories, and transduction. Essential optical parameters which impact the spin–photon interface include radiative lifetime, optical inhomogeneous and homogeneous linewidth, and optical depth. We study the donor-bound exciton optical linewidth properties of Al, Ga, and In donors in single-crystal ZnO. The ensemble photoluminescence linewidth ranges from 4 to 11 GHz, less than two orders of magnitude larger than the expected lifetime-limited linewidth. The ensemble linewidth remains narrow in absorption through samples with an estimated optical depth up to several hundred. The primary thermal relaxation mechanism is identified and found to have a negligible contribution to the total linewidth at 2 K. We find that inhomogeneous broadening due to the disordered isotopic environment in natural ZnO is significant, contributing 2 GHz. Two-laser spectral hole burning measurements indicate that the dominant mechanism, however, is homogeneous. Despite this broadening, the high homogeneity, large optical depth, and potential for isotope purification indicate that the optical properties of the ZnO donor-bound exciton are promising for a wide range of quantum technologies, and motivate a need to improve the isotope and chemical purity of ZnO for quantum technologies.

Niaouris, Vasileios (ORCID:000000015313748X)↗
DOE OSTI2020

Distributed Macroscopic Traffic Simulation with Open Traffic Models

This paper presents OTM-MPI, an extension of the Open Traffic Models platform (OTM) for running macroscopic traffic simulations in high-performance computing environments. OTM-MPI represents the first open-source, distributed-memory, macroscopic simulation model developed for modern high performance parallel machines and large networks. Macroscopic simulations are appropriate for studying regional traffic scenarios when aggregate trends are of interest, rather than individual vehicle traces. They are also appropriate for studying the routing behavior of classes of vehicles, such as app-informed vehicles. The network partitioning was performed with METIS. Inter-process communication was done with MPI (message-passing interface). Results are provided for two networks: one realistic network which was obtained from Open Street Maps for Chattanooga, TN, and another larger synthetic grid network. The software recorded a speedups of 198x using 256 cores for Chattanooga, and 475x with 1,024 cores for the synthetic network.

macro-scopic traffic simulation↗
DOE OSTI2020

Dynamic Microgrids in Resilient Distribution Systems With Reconfigurable Cyber-Physical Networks

Modern distribution systems energized by inverter-interfaced distributed generators (DGs) operate as coupled cyber-physical networks (C/P-networks), where the controllable components in the physical network (P-network) are coordinated through the cyber network (C-network). The concept of dynamic microgrids (MGs) operation has been adopted to enable distribution system autonomous operation with varying electric boundaries. To further enhance system operation resiliency and flexibility, dynamic MGs operation with reconfigurable C/P-networks is discussed in this work. An evaluation framework is proposed to assess the operational feasibility of distribution feeders with multiple inverter-based dynamic MGs and come out with possible restoration solutions in the context of cross-layer C/P-network reconfiguration. Furthermore, distributed controllers are developed for components with different operating characteristics to realize seamless system topology variations and provide coordinated secondary regulation in various operation modes. Furthermore, the proposed evaluation framework along with the developed distributed controller has been validated using a Hardware-in-the-Loop (HIL) real-time CPS testbed.

24 POWER TRANSMISSION AND DISTRIBUTION↗