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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 1,459 records · Page 81
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Analytical Cost Metrics : Days of Future Past

As we move towards the exascale era, the new architectures must be capable of running the massive computational problems efficiently. Scientists and researchers are continuously investing in tuning the performance of extreme-scale computational problems. These problems arise in almost all areas of computing, ranging from big data analytics, artificial intelligence, search, machine learning, virtual/augmented reality, computer vision, image/signal processing to computational science and bioinformatics. With Moore’s law driving the evolution of hardware platforms towards exascale, the dominant performance metric (time efficiency) has now expanded to also incorporate power/energy efficiency. Therefore the major challenge that we face in computing systems research is: “how to solve massive-scale computational problems in the most time/power/energy efficient manner?”

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Bioluminescence Tomography–Guided Radiation Therapy for Preclinical Research

Purpose: In preclinical radiation research, it is challenging to localize soft tissue targets based on cone beam computed tomography (CBCT) guidance. As a more effective method to localize soft tissue targets, we developed an online bioluminescence tomography (BLT) system for small-animal radiation research platform (SARRP). We demonstrated BLT-guided radiation therapy and validated targeting accuracy based on a newly developed reconstruction algorithm. Methods and Materials: The BLT system was designed to dock with the SARRP for image acquisition and to be detached before radiation delivery. A 3-mirror system was devised to reflect the bioluminescence emitted from the subject to a stationary charge-coupled device (CCD) camera. Multispectral BLT and the incomplete variables truncated conjugate gradient method with a permissible region shrinking strategy were used as the optimization scheme to reconstruct bioluminescent source distributions. To validate BLT targeting accuracy, a small cylindrical light source with high CBCT contrast was placed in a phantom and also in the abdomen of a mouse carcass. The center of mass (CoM) of the source was recovered from BLT and used to guide radiation delivery. The accuracy of the BLT-guided targeting was validated with films and compared with the CBCT-guided delivery. In vivo experiments were conducted to demonstrate BLT localization capability for various source geometries. Results: Online BLT was able to recover the CoM of the embedded light source with an average accuracy of 1 mm compared to that with CBCT localization. Differences between BLT- and CBCT-guided irradiation shown on the films were consistent with the source localization revealed in the BLT and CBCT images. In vivo results demonstrated that our BLT system could potentially be applied for multiple targets and tumors. Conclusions: The online BLT/CBCT/SARRP system provides an effective solution for soft tissue targeting, particularly for small, nonpalpable, or orthotopic tumor models.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Discovery of a weak topological insulating state and van Hove singularity in triclinic RhBi2

Abstract Time reversal symmetric (TRS) invariant topological insulators (TIs) fullfil a paradigmatic role in the field of topological materials, standing at the origin of its development. Apart from TRS protected strong TIs, it was realized early on that more confounding weak topological insulators (WTI) exist. WTIs depend on translational symmetry and exhibit topological surface states only in certain directions making it significantly more difficult to match the experimental success of strong TIs. We here report on the discovery of a WTI state in RhBi 2 that belongs to the optimal space group P $$\bar{1}$$ 1 ¯ , which is the only space group where symmetry indicated eigenvalues enumerate all possible invariants due to absence of additional constraining crystalline symmetries. Our ARPES, DFT calculations, and effective model reveal topological surface states with saddle points that are located in the vicinity of a Dirac point resulting in a van Hove singularity (VHS) along the (100) direction close to the Fermi energy ( E F ). Due to the combination of exotic features, this material offers great potential as a material platform for novel quantum effects.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Solving the Bernstein-Vazirani problem using Majorana-based topological quantum algorithms

Executing quantum algorithms using Majorana zero modes—a major milestone for the field of topological quantum computing—requires a platform that can be scaled to large quantum registers, can be controlled in real time and space, and a braiding protocol that uses the unique properties of these exotic particles. Here, we demonstrate the first successful simulation of a Majorana-based, fault-tolerant quantum algorithm to solve the Bernstein-Vazirani problem in two-dimensional magnet-superconductor hybrid structures from initialization to read-out of the final many-body state. Utilizing the Majorana zero modes’ topological properties, we introduce an optimized braiding protocol for the algorithm and a scalable architecture for its implementation with an arbitrary number of qubits. We visualize the algorithm protocol in real time and space by computing the non-equilibrium density of states, which is proportional to the time-dependent differential conductance, and the non-equilibrium charge density, which assigns a unique signature to each final state of the algorithm.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Engineered Pseudomonas putida KT2440 co-utilizes galactose and glucose

Abstract Background Efficient conversion of plant biomass to commodity chemicals is an important challenge that needs to be solved to enable a sustainable bioeconomy. Deconstruction of biomass to sugars and lignin yields a wide variety of low molecular weight carbon substrates that need to be funneled to product. Pseudomonas putida KT2440 has emerged as a potential platform for bioconversion of lignin and the other components of plant biomass. However, P. putida is unable to natively utilize several of the common sugars in hydrolysate streams, including galactose. Results In this work, we integrated a De Ley–Doudoroff catabolic pathway for galactose catabolism into the chromosome of P. putida KT2440, using genes from several different organisms. We found that the galactonate catabolic pathway alone (DgoKAD) supported slow growth of P. putida on galactose. Further integration of genes to convert galactose to galactonate and to optimize the transporter expression level resulted in a growth rate of 0.371 h −1 . Additionally, the best-performing strain was demonstrated to co-utilize galactose with glucose. Conclusions We have engineered P. putida to catabolize galactose, which will allow future engineered strains to convert more plant biomass carbon to products of interest. Further, by demonstrating co-utilization of glucose and galactose, continuous bioconversion processes for mixed sugar streams are now possible.

09 BIOMASS FUELS↗
DOE OSTI2026

Scalable foundation models for numerical simulations on HPC platforms

In recent years, foundation models (FMs) have begun to reshape numerical simulations on high-performance computing (HPC) platforms. These large, pre-trained AI models enable rapid predictions across a broad range of physical domains, including Earth system modeling, fluid dynamics, materials science, as well as complex multi-modal simulations in aerospace engineering and fusion research. By training on diverse datasets, FMs learn intricate relationships and underlying physical behavior while also enabling the quantification of uncertainty in their predictions. This capability allows simulations that once required days of numerical calculation to be completed in minutes (FM inference), supporting real-time design optimization, uncertainty-aware decision making, and more comprehensive exploration of complex scenarios.

AI↗
DOE OSTI2018

Target tracking via recursive Bayesian state estimation in cognitive radar networks

To cope with complicated environments and stealthier targets, incorporating intelligence and cognition cycles into target tracking is of great importance in modern sensor network management. With remarkable advances in sensor techniques and deployable platforms, a sensing system has freedom to select a subset of available radars, plan their trajectories, and transmit designed waveforms. In this paper, we propose a general framework for single target tracking in cognitive networks of radars, including consideration of waveform design, path planning, and radar selection, which are separately but not jointly taken into account in existing work. The tracking procedure, built on the theories of dynamic graphical models (DGM) and recursive Bayesian state estimation (RBSE), is formulated as two iterative steps: (i) solving a combinatorial optimization problem to select the optimal subset of radars, waveforms, and locations for the next tracking instant, and (ii) acquiring the recursive Bayesian state estimation to accurately track the target. Further, an illustrative example introduces a specific scenario in 2-D space. Simulation results based on the scenario demonstrate that the proposed framework can accurately track the target under the management of the network of radars.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Active Site and Electronic Structure Elucidation of Pt Nanoparticles Supported on Phase-Pure Molybdenum Carbide Nanotubes

Here, we recently showed that phase-pure molybdenum carbide nanotubes can be durable supports for platinum (Pt) nanoparticles in hydrogen evolution reaction (HER). In this paper we further characterize surface properties of the same Pt/β-Mo 2 C catalyst platform using carbon monoxide (CO)-Pt and CO-Mo 2 C bond strength of different Pt particle sizes in the <3 nm range. Results from diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and temporal analysis of products (TAP) revealed the existence of different active sites as Pt particle size increases. Correlation between the resultant catalyst activity and deposited Pt particle size was further investigated using water–gas-shift (WGS) as a probe reaction, suggesting that precise control of particle diameter and thickness is needed for optimized catalytic activity.

36 MATERIALS SCIENCE↗
DOE OSTI2025

TRANSP Workshop Summary - September 27-28, 2024, Princeton Plasma Physics Laboratory, NJ

The TRANSP Code Workshop provided a platform for in-depth discussions on advancing the capabilities of the TRANSP code, focusing on key areas such as predictive capabilities, interpretive frameworks, core-edge coupling, and integration with engineering components. More than 25 scientists from PPPL and around the world contributed to the workshop by making presentations and participating in discussions. The workshop covered a range of topics including: (1) Current Status of TRANSP; (2) Code Infrastructure, Core-Edge Coupling, and Engineering Integration; (3) Enhancing Interpretive Capabilities, and (4) Predictive Capabilities for Discharge Optimization

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Supervisory Control System for Multi-Modular Advanced Reactors

The proposed supervisory control system (SCS) may provide considerable benefits to advanced small modular reactors, including reduced plant staffing, optimized maintenance activities, greater plant availability, and higher operating efficiency. The SCS makes risk-informed decisions based on (1) a probabilistic assessment of the likelihood of success given the status of the plant/systems and component health, and (2) a deterministic assessment between plant operating parameters and reactor protection parameters to prevent unnecessary trips and challenges to plant safety system—one measure of SCS success. The probabilistic portion of the decision-making engine of the SCS is based on the control actions associated with an advanced liquid-metal reactor (ALMR) Power Reactor, Innovative, Small Module (PRISM). Within the SCS, the probabilistic assessment provides a ranking of viable control actions; however, certain instructions generated by the probabilistic model only include an abstract notion of action without specifications. For instance, one instruction may be to reduce power without specifying how much reduction is needed. The prognostic/diagnostic models incorporate the health of components into the decision-making process. Once the control options are identified and ranked based on the likelihood of success, the SCS transmits the options to the deterministic portion of the platform. The performance-based system models assess and rank each of the probabilistically identified control actions by taking into account the physical behavior (current and projected) of the system. The performance-based decision making module receives inputs from the probabilistic decision-making module and the ERM module to generate a single solution. Interfaces to these modules are defined later in the section. A utility theory algorithm factors into the decision making by estimating the distance from and approach to a trip setpoint for each control option. If the magnitude of a negative utility value increases rapidly as the system approaches the trip setpoint, that option is not likely to be the preferred option. This can lead to a re-ranking of the control options. The SCS then transmits a control signal(s) to a component or system and informs the operator of actions taken based on the action chosen. The SCS successfully coupled probabilistic and performance-based system models to arrive at optimal control decisions based on the actual status of the plant and components. The automatic, autonomous, and real-time performance requirements for a control system were met by the SCS. The value of coupling probabilistic and performance-based system models was demonstrated by the re-ranking of control options based on the use of a utility algorithm. The use of ERM monitors provides added value to the SCS as demonstrated by the re-ranking of control options based on a components degraded state.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Optimizing Microenvironment of Asymmetric N,S-Coordinated Single-Atom Fe via Axial Fifth Coordination toward Efficient Oxygen Electroreduction

We report single-atom catalysts (SACs) are attractive candidates for oxygen reduction reaction (ORR). The catalytic performances of SACs are mainly determined by the surrounding microenvironment of single metal sites. Microenvironment engineering of SACs and understanding of the structure–activity relation-ship is critical, which remains challenging. Herein, a self-sacrificing strategy is developed to synthesize asymmetric N,S-coordinated single-atom Fe with axial fifth hydroxy (OH) coordination (Fe-N 3 S 1 OH) embedded in N,S codoped porous carbon nanospheres (Fe-N/S-C). Such unique penta-coordination microenvironment is determined by cutting-edge techonologies aiding of systematic simulations. The as-obtained Fe-;N/S-C exhibits superior catalytic ORR activity, and showcases a half-wave potential of 0.882 V surpassing the benchmark Pt/C. Moreover, theoretical calculations confirmed the axial OH in Fe-N 3 S 1 OH can optimize 3d orbitals of Fe center to strengthen O 2 adsorption and enhance O 2 activation on Fe site, thus reducing the ORR barrier and accelerating ORR dynamics. Furthermore, Fe-N/S-C containing H 2 -O 2 fuel cell performs a high peak power density of 512 mW cm -2 , and Fe-N/S-C based Zn-air batteries show the peak power density of 203 and 49 mW cm -2 in liquid and flexible all-solid-state configurations, respectively. This study offers a new platform for fundamentally understand the axial fifth coordination in asymmetrical planar single-atom metal sites for electrocatalysis.

microenvironment↗
DOE OSTI2026

Arctic Deployment of a Fully Integrated Self-Powered Drifting Buoy Harvesting Wave Energy via a Triboelectric Nanogenerator

The Arctic Ocean remains one of the most poorly sampled regions on Earth, where improved in situ environmental monitoring is vital for advancing oceanographic and atmospheric studies. However, data collection efforts are constrained by the short operational lifespans and high costs of conventional systems. Drifting buoys powered by pendulum-driven wave energy harvesters offer a cost-effective alternative, yet earlier designs have neither been optimized for real-world wave conditions nor validated in the Arctic. In this study, we develop a self-powered drifting buoy that integrates a pendulum-driven triboelectric nanogenerator (TENG) system with a mechanical motion rectifier, a high-gear-ratio transmission, and power management circuits. Through coupled buoy–pendulum dynamic simulations and laboratory testing using a motion simulator, we identify an optimal pendulum mass of 1.6 kg (12.7% of total buoy weight) that maximizes energy output while maintaining buoy stability. Laboratory experiments achieved average power outputs of 12.7 mW under Arctic-like wave and temperature conditions. The system was successfully deployed in the Bering Sea, where it generated 11 J of energy in 3.1 m waves, marking the first Arctic deployment of a TENG-based drifting buoy for sea surface temperature monitoring. This work establishes a cost-effective framework for designing self-powered Arctic monitoring platforms and advances the feasibility of long-term environmental observations in real Arctic waters.

marine enerby↗
DOE OSTI2024

Enhancement of magnetic domain wall velocity via resonant dissipation of standing wave modes of domain wall structure with perpendicular magnetic anisotropy

The dynamic behaviors of magnetic domain walls have significant implications for developing advanced spintronic devices. In this study, we investigate the intriguing resonance phenomenon within the magnetic domain wall structure, focusing on the dissipation mechanism and its impact on domain wall dynamic motion. By applying a static external magnetic field, we observe a remarkable amplification of domain wall velocity through the resonant excitations of the flexure modes. The resonance of the flexure mode exerts an indirect influence on the domain wall velocity through energy dissipation, leading to a significant enhancement from the predictions of the one-dimensional Walker model. We establish a robust model platform rooted in energy dissipation allows comprehensive understanding the dramatic enhancement of domain wall velocity observed during width-directional flexure mode resonance. By directly quantifying energy dissipation, our approach provides highly effective and accurate estimates of domain wall velocity, surpassing previous methods that focus solely on the instantaneous dynamics of the domain wall structure. These findings offer crucial insights into the fundamental mechanisms governing the dynamics of domain walls and other magnetic systems, such as magnetic skyrmions, bubbles, and magnetic vortices, paving the way for development and optimization of next-generation spintronic devices.

Collective dynamics↗
DOE OSTI2016

Effects of the microstructure and porosity on properties of Ti-6Al-4V ELI alloy fabricated by electron beam melting (EBM)

Electron Beam Melting (EBM) is a metal powder bed-based Additive Manufacturing (AM) technology that makes possible the fabrication of three dimensional near-net-shaped parts directly from computer models. EBM technology has been in continuously updating, obtaining optimized properties of the processed alloys. Ti-6Al-4V titanium alloy is the most widely used and studied alloy for this technology and is the focus of this work. Several research works have been completed to study the mechanisms of microstructure formation as well as its influence on mechanical properties. However, the relationship is not completely understood, and more systematic research work is necessary in order to attain a better understanding of these features. In this work, samples fabricated at different locations, orientations, and distances from the build platform have been characterized, studying the relationship of these variables with the resulting material intrinsic characteristics and properties (surface topography, microstructure, porosity, micro-hardness and static mechanical properties). This study has revealed that porosity is the main factor controlling mechanical properties relative to the other studied variables. Therefore, in future process developments, decreasing of the porosity should be considered as the primary goal in order to improve mechanical properties.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Understanding the structural mechanics of ligated DNA crystals via molecular dynamics simulation

DNA self-assembly is a highly programmable method to construct arbitrary architectures based on sequence complementarity. Among various constructs, DNA crystals are macroscopic crystalline materials formed by assembling motifs via sticky end association. Due to their high structural integrity and size ranging from tens to hundreds of micrometers, DNA crystals offer unique opportunities to study the structural properties and deformation behaviors of DNA assemblies. For example, enzymatic ligation of sticky ends can selectively seal nicks resulting in more robust structures with enhanced mechanical properties. However, the research efforts have been mostly on experiments involving different motif designs, structural optimization, or new synthesis methods, while their mechanics are not yet fully understood. The complex properties of DNA crystals are difficult to study via experiments alone, and numerical simulation can complement and aid the experiments. The coarse-grained molecular dynamics (MD) simulation is a powerful tool that can probe the mechanics of DNA assemblies. Here, we investigate DNA crystals made of four different motif lengths with various ligation patterns (full ligation, major directions, connectors, and in-plane) using oxDNA, an open-source, coarse-grained MD platform. We found that several distinct deformation stages emerge in response to mechanical loading and that the number and the location of ligated nucleotides can significantly modulate structural behaviors. These findings should be useful for predicting crystal properties and thus improving the design.

DNA crystal↗
DOE OSTI2021

Copper Electrode on Flexible Substrate by Intense Pulsed Light Sintering of Microsized Copper Particles

Metal electrodes deposited in a grid pattern onto flexible polymer substrates have been shown to be a viable alternative to replace indium tin oxide (ITO) as the transparent anode for organic photovoltaics. copper may be a better alternative in terms of cost and stability for large area low-cost solar modules, specifically on roll-to-roll platforms. These customized electrode patterns can be fabricated from copper nanoparticles through various printing techniques applicable to solution phase processing. The Intense Pulsed Light (IPL) technique has been used to sinter copper nanoparticles (~100nm) to fabricate conductive copper electrodes on flexible polymer substrates. However, compared to nanosized (~100 nm) copper particles, microsized (~2 um) copper is much cheaper. In this work, microsized (~2 um) copper is used to produce high conductive copper inks. The conductivity of the print can be adjusted through the use of surfactant. IPL sintering was optimized to obtain high conductivity copper films. In conclusion, several microscopic and electrical spectroscopic characterization techniques such as scanning electron microscopy (SEM), x-ray diffraction (XRD), 4-point probe resistivity measurements were employed to characterize the copper electrodes.

14 SOLAR ENERGY↗
DOE OSTI2022

Bayesian homodyne and heterodyne tomography

Continuous-variable (CV) photonic states are of increasing interest in quantum information science, bolstered by features such as deterministic resource state generation and error correction via bosonic codes. Data-efficient characterization methods will prove critical in the fine-tuning and maturation of such CV quantum technology. Although Bayesian inference offers appealing properties—including uncertainty quantification and optimality in mean-squared error—Bayesian methods have yet to be demonstrated for the tomography of arbitrary CV states. Here we introduce a complete Bayesian quantum state tomography workflow capable of inferring generic CV states measured by homodyne or heterodyne detection, with no assumption of Gaussianity. As examples, we demonstrate our approach on experimental coherent, thermal, and cat state data, obtaining excellent agreement between our Bayesian estimates and theoretical predictions. Our approach lays the groundwork for Bayesian estimation of highly complex CV quantum states in emerging quantum photonic platforms, such as quantum communications networks and sensors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Toward a persistent event-streaming system for high-performance computing applications

High-performance computing (HPC) applications have traditionally relied on parallel file systems and file transfer services to manage data movement and storage. Alternative approaches have been proposed that use direct communications between application components, trading persistence and fault tolerance for speed. Event-driven architectures, as popularized in enterprise contexts, present a compelling middle ground, avoiding the performance cost and API constraints of parallel file systems while retaining persistence and offering impedance matching between application components. However, adapting streaming frameworks to HPC workloads requires addressing challenges unique to HPC systems. This paper investigates the potential for a streaming framework designed for HPC infrastructures and use cases. We introduce Mofka, a persistent event-streaming framework designed specifically for HPC environments. Mofka combines the capabilities of a traditional streaming service with optimizations tailored to the HPC context, such as support for massively multicore nodes, efficient scaling for large producer-consumer workflows, RDMA-enabled high-performance network communications, specialized network fabrics with multiple links per node, and efficient handling of large scientific data payloads. Built using the Mochi suite of HPC data service components, Mofka provides a lightweight, modular, and high-performance solution for persistent streaming in HPC systems. We present the architecture of Mofka and evaluate its performance against Kafka and Redpanda using benchmarks on diverse platforms, including Argonne's Polaris and Oak Ridge's Frontier supercomputers, showing up to 8× improvement in throughput in some scenarios. We then demonstrate its utility in several real-world applications: a tomographic reconstruction pipeline, a workflow for the discovery of metal-organic frameworks for carbon capture, and the instrumentation of Dask workflows for provenance tracking and performance analysis.

HPC↗