SEARCH · Engineering Papers

Results for “Hybrid techniques”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 577 records · Page 32

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Efficient Hydraulic-to-electric Energy Conversion for PCM-based Ocean Thermal Gradient Energy System to Power Uncrewed Underwater Vehicles

Since the 2000, there have been numerous investigations into electrical energy storage types that use ocean thermal-to-electricity conversion techniques. Field tests have demonstrated that this technology is feasible for UUVs with long-term missions of over 3,000 km per deployment. Nonetheless, the energy generated by this method is not sufficient to meet the energy requirements of Unscrewed Underwater Vehicles (UUVs). The objective of this study is to design a highly effective ocean thermal gradient energy system to support long-term missions of a UUV. To enhance the performance of the thermal gradient energy system, we have developed a hybrid type (buoyancy regulation and electrical storage). Phase Change Material (PCM)-based energy harvesting system to facilitate efficient UUV operations. A prototype of the hydraulic-to-electric conversion system was implemented, and experimental findings indicate that the hybrid system successfully delivers hydraulic energy for buoyancy change and improved efficiency of hydraulic-to-electric energy conversion, demonstrating its potential as a promising technology for supporting long-term UUV missions.

Deng, Zhiqun↗

DOE OSTI2021

SULI Research Report Paper

Hybrid-CMOS (hCMOS) nanosecond x-ray imagers are a powerful timeresolved HED (high-energy-density) diagnostic due to their sensitivity to visible light, x-rays, and charged particles. However, significant pseudosinusoidal background oscillations have been observed in these sensors when exposed to an early incident excitation, a phenomenon that has been experimentally linked the sensor’s bond wire inductance. We analyze the oscillations both in the time domain and spatially to account for variations on the pixel level. Both theoretical techniques and analysis of experimental data have shown that the oscillations are a global sensor phenomenon. In addition, we effectively describe the oscillations with a physics-based model, giving further insight into the processes affecting them. This technique allows the hCMOS user to subtract out the oscillations from their measurements and improve accuracy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Dopants, Isotope, Pressure and Lead Sequestration for Hybrid Perovskite Materials

Dopants, Isotope, Pressure and Lead Sequestration for Hybrid Perovskite Materials The soaring power conversion efficiency (PCE) of solution process-based organic-inorganic hybrid perovskites solar cells (PSCs) assures their membership in the competitive photovoltaic technologies. However, stability, toxicity and scalability are the three grand challenges that still impedes the market adoption of PSCs. Careful fundamental studies on how their fascinating optoelectronic properties is related to their structures may provide leads to these challenges and also spin off new applications. In this talk, I will present our recent study on the dopants, isotope and pressure effects on hybrid perovskite materials (HPMs). We discovered an interesting bipolar electron injection in LiCl-doped MAPbI 3 -based UV detectors that respond to the energy of UV photons in distinguished photocurrents polarity. We also investigated how the underline interaction between the mass of the cationic rotors and the inorganic lattice in HPMs by isotope effect. In-situ synchrotron X-ray and time-resolved photoluminescence revealed abnormal optoelectronic properties of HPMs by modulating their bond angles and bond lengths using high pressure techniques. Moreover, I will also discuss our new technology to sequestrate lead leakage on perovskite solar cells that can absorb >99% leaked Pb ions under severe device damge while without sacrificing the PCE under normal operational conditions.

Xu, Tao↗

DOE OSTI2021

Secure boot, trusted boot and remote attestation for ARM TrustZone-based IoT Nodes

With the extensive application of IoT techniques, IoT devices have become ubiquitous in daily lives. Meanwhile, attacks against IoT devices have emerged to compromise IoT devices by tampering with system pre-installed programs or injecting new malware. To mitigate these attacks, integrity enforcement of IoT systems has been proposed. The integrity of an IoT device system includes load-time integrity and runtime integrity. In this paper, we design an IoT system based on ARM TrustZone to enforce the system integrity. First, we establish the root of trust and propose a hybrid booting approach consisting of both secure boot and trusted boot to enforce the system load-time integrity. Second, we investigate a paging-based process integrity measurement method to measure the NW processes and conduct remote attestation based on the measurement results ensuring the NW runtime process integrity. We implement an IoT prototype system on a NXP i.MX6Q SABRE SD development board to assess its feasibility. Finally, real-world experiment results demonstrate that our prototype introduces negligible performance overhead to the original system.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Low-energy spin dynamics in rare-earth perovskite oxides

We review recent studies of spin dynamics in rare-earth orthorhombic perovskite oxides of the type RMO 3 , where R is a rare-earth ion and M is a transition-metal ion, using single-crystal inelastic neutron scattering (INS). After a short introduction to the magnetic INS technique in general, the results of INS experiments on both transition-metal and rare-earth subsystems for four selected compounds (YbFeO 3 , TmFeO 3 , YFeO 3 , YbAlO 3 ) are presented. We show that the spectrum of magnetic excitations consists of two types of collective modes that are well separated in energy: gapped magnons with a typical bandwidth of <70 meV, associated with the antiferromagnetically (AFM) ordered transition-metal subsystem, and AFM fluctuations of <5 meV within the rare-earth subsystem, with no hybridization of those modes. We discuss the high-energy conventional magnon excitations of the 3d subsystem only briefly, and focus in more detail on the spectacular dynamics of the rare-earth sublattice in these materials. We observe that the nature of the ground state and the low-energy excitation strongly depends on the identity of the rare-earth ion. In the case of non-Kramers ions, the low-symmetry crystal field completely eliminates the degeneracy of the multiplet state, creating a rich magnetic field-temperature phase diagram. In the case of Kramers ions, the resulting ground state is at least a doublet, which can be viewed as an effective quantum spin-1/2. Equally important is the fact that in Yb-based materials the nearest-neighbor exchange interaction dominates in one direction, despite the three-dimensional nature of the orthoperovskite crystal structure. The observation of a fractional spinon continuum and quantum criticality in YbAlO3 demonstrates that Kramers rare-earth based magnets can provide realizations of various aspects of quantum low-dimensional physics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Verification and benchmarking relativistic electron beam transport through a background gas

It is necessary to establish confidence in high-consequence codes containing an extensive suite of physics algorithms in the regimes of interest. Verification problems allow code developers to assess numerical accuracy and increase confidence that specific sets of model physics were implemented correctly in the code. The two main verification techniques are code verification and solution verification. In this work, we present verification problems that can be used in other codes to increase confidence in simulations of relativistic beam transport. Specifically, we use the general plasma code EMPIRE to model and compare with the analytical solution to the evolution of the outer radial envelope of a relativistic charged particle beam. Additionally, we also outline a benchmark test of a relativistic beam propagating through a vacuum and pressurized gas cell, and present the results between EMPIRE and the hybrid code GAZEL. Further, we discuss the subtle errors that were caught with these problems and detail lessons learned.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

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 OSTI2023

Using mechanistic models and machine learning to design single-color multiplexed nascent chain tracking experiments

mRNA translation is the ubiquitous cellular process of reading messenger-RNA strands into functional proteins. Over the past decade, large strides in microscopy techniques have allowed observation of mRNA translation at a single-molecule resolution for self-consistent time-series measurements in live cells. Dubbed Nascent chain tracking (NCT), these methods have explored many temporal dynamics in mRNA translation uncaptured by other experimental methods such as ribosomal profiling, smFISH, pSILAC, BONCAT, or FUNCAT-PLA. However, NCT is currently restricted to the observation of one or two mRNA species at a time due to limits in the number of resolvable fluorescent tags. In this work, we propose a hybrid computational pipeline, where detailed mechanistic simulations produce realistic NCT videos, and machine learning is used to assess potential experimental designs for their ability to resolve multiple mRNA species using a single fluorescent color for all species. Our simulation results show that with careful application this hybrid design strategy could in principle be used to extend the number of mRNA species that could be watched simultaneously within the same cell. We present a simulated example NCT experiment with seven different mRNA species within the same simulated cell and use our ML labeling to identify these spots with 90% accuracy using only two distinct fluorescent tags. We conclude that the proposed extension to the NCT color palette should allow experimentalists to access a plethora of new experimental design possibilities, especially for cell Signaling applications requiring simultaneous study of multiple mRNAs.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Discovery and construction of surface kagome electronic states induced by p-d electronic hybridization in Co3Sn2S2

Abstract Kagome-lattice materials possess attractive properties for quantum computing applications, but their synthesis remains challenging. Herein, based on the compelling identification of the two cleavable surfaces of Co 3 Sn 2 S 2 , we show surface kagome electronic states (SKESs) on a Sn-terminated triangular Co 3 Sn 2 S 2 surface. Such SKESs are imprinted by vertical p-d electronic hybridization between the surface Sn (subsurface S) atoms and the buried Co kagome-lattice network in the Co 3 Sn layer under the surface. Owing to the subsequent lateral hybridization of the Sn and S atoms in a corner-sharing manner, the kagome symmetry and topological electronic properties of the Co 3 Sn layer is proximate to the Sn surface. The SKESs and both hybridizations were verified via qPlus non-contact atomic force microscopy (nc-AFM) and density functional theory calculations. The construction of SKESs with tunable properties can be achieved by the atomic substitution of surface Sn (subsurface S) with other group III-V elements (Se or Te), which was demonstrated theoretically. This work exhibits the powerful capacity of nc-AFM in characterizing localized topological states and reveals the strategy for synthesis of large-area transition-metal-based kagome-lattice materials using conventional surface deposition techniques.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Analysis and mitigation of an oscillating background on hybrid complementary metal-oxide semiconductor (hCMOS) imaging sensors at the National Ignition Facility

Nanosecond-gated hybrid complementary metal-oxide semiconductor imaging sensors are a powerful tool for temporally gated and spatially resolved measurements in high energy density science, including inertial confinement fusion, and in laser diagnostics. However, a significant oscillating background excited by photocurrent has been observed in image sequences during testing and in experiments at the National Ignition Facility (NIF). Characterization measurements and simulation results are used to explain the oscillations as the convolution of the pixel-level sensor response with a sensor-wide RLC circuit ringing. Finally, data correction techniques are discussed for NIF diagnostics, and for diagnostics where these techniques cannot be used, a proof-of-principle image correction algorithm is presented.

42 ENGINEERING↗

DOE OSTI2025

Hydrogen density mapping in biomolecular crystals through dynamic nuclear polarization

Many fundamental biological processes, including those in photosynthetic reaction centers and enzyme active sites, involve charge and energy transfer, bond cleavage, protonation and hydrogen bonding. Because H atoms play such central roles in these reactions, accurately determining their positions is essential. Yet, conventional X-ray crystallography primarily resolves the heavy atoms in biological structures and provides limited insight into hydrogen, even at atomic resolution. Neutron macromolecular crystallography (NMC) overcomes this limitation by offering exceptional sensitivity to hydrogen and deuterium. Here, we present a theoretical framework for the development of dynamic nuclear polarization NMC (DNP-NMC) techniques, which exploit the alignment of neutron and proton nuclear spins to enhance and tune the hydrogen signal contribution. The DNP-NMC approach advances the resolution of H atoms within biomolecular crystals, whether bound to protein residues or present in solvent. The method establishes key relationships for the coherent structure factor of polarized neutron scattering from hydrogenous matter. It theoretically achieves full accuracy in phase reconstruction and offers a path to improve neutron structure determination, achieving accuracies exceeding ≳80% by incorporating titration states. Using a variant of the hybrid input/output phase-retrieval algorithm, it allows recovery of the hydrogen density with ≳90% phase accuracy. In conclusion, we further discuss sources of experimental uncertainty for the upcoming DNP-enabled, quasi-Laue IMAGINE-X experiment at Oak Ridge National Laboratory's High Flux Isotope Reactor.

dynamic nuclear polarization↗

DOE OSTI2022

Interaction-expansion inchworm Monte Carlo solver for lattice and impurity models

Multiorbital quantum impurity models with general interaction and hybridization terms appear in a wide range of applications, including embedding, quantum transport, and nanoscience. However, most quantum impurity solvers are restricted to a few impurity orbitals, discretized baths, diagonal hybridizations, or density-density interactions. We generalize the inchworm quantum Monte Carlo method to the interaction expansion, and we explore its application to typical single- and multiorbital problems encountered in investigations of impurity and lattice models. Our implementation generically outperforms bare and bold-line quantum Monte Carlo algorithms in the interaction expansion. For the systems studied here, our implementation remains inferior to the more specialized hybridization expansion and auxiliary field algorithms. So, the problem of convergence to unphysical fixed points, which hampers so-called bold-line methods, is not encountered in inchworm Monte Carlo.

36 MATERIALS SCIENCE↗

DOE OSTI2026

First nucleon gluon PDF from large momentum effective theory

We report the first nucleon gluon parton distribution function (PDF) using Large-Momentum Effective Theory (LaMET). We focus on the gluon operator which was demonstrated to have the best signal-to-noise in the previous attempt [1] in computing gluon PDFs using LaMET. We compute the corresponding Wilson coefficients needed for the hybrid-renormalized matrix elements and the matching kernel to convert the quasi-PDF to the lightcone one at the one-loop level. We demonstrate that with the proper Wilson coefficients in place, the counterterms for the renormalization are independent of the hadron and mass within statistical error. Using the resulting renormalization, we then compute the nucleon PDF using a HISQ ensemble generated by the MILC collaboration with N f = 2 + 1 +1, a ≈ 0.12 fm, with valence pion masses of 310 and 690 MeV and two gauge link smearing techniques. Despite the physics effects of the heavier than physical pion masses and gauge link smearing, this calculation provides excellent proof of principle and compares reasonably with selected global fit results.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

Understanding Instability in Formamidinium Lead Halide Perovskites: Kinetics of Transformative Reactions at Grain and Subgrain Boundaries

Transformative and reconstructive reactions impart significant structural changes at particle boundaries of hybrid perovskites, which influence environmental stability and optoelectronic properties of these materials. Here, we investigate the moisture-induced transformative reactions in formamidinium based perovskites FAPbX 3 (X=I, Br) and show that the ambient stability of these materials can be adjusted from a few hours to several months. For FAPbI 3 , roles of water vapor, particle size, and light illumination on the kinetic pathways of the cubic (a) transformation to the hexagonal (d) phase are analyzed by X-ray diffraction, optical microscopy, photoluminescence and solid-state NMR spectroscopy techniques. The grain and sub-grain boundaries exhibit different α→δ-FAPbI 3 phase transformation kinetics. Our study suggests that the dynamic transformation involves the local water-induced dissolution of the cubic phase occurring at the crystal surfaces followed by precipitation of the hexagonal phase. Insights into structures and dynamics of a kinetically trapped α-|δ-FAPbI 3 are obtained by 1 H, 2 H, and 207 Pb ssNMR spectroscopy.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Phosphate‐functionalized Zirconium Metal–Organic Frameworks for Enhancing Lithium–Sulfur Battery Cycling

Abstract Lithium–sulfur batteries are promising candidates for next‐generation energy storage devices due to their outstanding theoretical energy density. However, they suffer from low sulfur utilization and poor cyclability, greatly limiting their practical implementation. Herein, we adopted a phosphate‐functionalized zirconium metal–organic framework (Zr‐MOF) as a sulfur host. With their porous structure, remarkable electrochemical stability, and synthetic versatility, Zr‐MOFs present great potential in preventing soluble polysulfides from leaching. Phosphate groups were introduced to the framework post‐synthetically since they have shown a strong affinity towards lithium polysulfides and an ability to facilitate Li ion transport. The successful incorporation of phosphate in MOF‐808 was demonstrated by a series of techniques including infrared spectroscopy, solid‐state nuclear magnetic resonance spectroscopy, and X‐ray pair distribution function analysis. When employed in batteries, phosphate‐functionalized Zr‐MOF (MOF‐808‐PO4) exhibits significantly enhanced sulfur utilization and ion diffusion compared to the parent framework, leading to higher capacity and rate capability. The improved capacity retention and inhibited self‐discharge rate also demonstrate effective polysulfide encapsulation utilizing MOF‐808‐PO4. Furthermore, we explored their potential towards high‐density batteries by examining the cycling performance at various sulfur loadings. Our approach to correlate structure with function using hybrid inorganic–organic materials offers new chemical design strategies for advancing battery materials.

Liu, Bingqian↗

DOE OSTI2025

A Digital Twin Framework Utilizing Machine Learning for Robust Predictive Maintenance: Enhancing Tire Health Monitoring

We introduce a novel digital twin (DT) framework for the predictive maintenance of long-term physical systems. Using monitoring tire health as an application, we show how the DT framework can be used to enhance automotive safety and efficiency, and how the technical challenges can be overcome using a three-step approach. First, to manage the data complexity over a long operation span, we employ data reduction techniques to concisely represent physical tires using historical performance and usage data. Relying on these data, for fast real-time prediction, we train a transformer-based model offline on our concise dataset to predict future tire health over time, represented as remaining casing potential (RCP). Based on our architecture, our model quantifies both epistemic and aleatoric uncertainties, providing reliable confidence intervals around predicted RCP. Second, to incorporate real-time data, we update the predictive model in the DT framework, ensuring its accuracy throughout its lifespan with the aid of hybrid modeling and the use of the discrepancy function. Third, to assist decision-making in predictive maintenance, we implement a tire state decision algorithm, which strategically determines the optimal timing for tire replacement based on RCP forecasted by our transformer model. This approach ensures that our DT accurately predicts system health, continually refines its digital representation, and supports predictive maintenance decisions. Furthermore, our framework effectively embodies a physical system, leveraging big data and machine learning (ML) for predictive maintenance, model updates, and decision-making.

advanced computing infrastructure↗

DOE OSTI2024

Species-specific ribosomal RNA-FISH identifies interspecies cellular-material exchange, active-cell population dynamics and cellular localization of translation machinery in clostridial cultures and co-cultures

ABSTRACT The development of synthetic microbial consortia in recent years has revealed that complex interspecies interactions, notably the exchange of cytoplasmic material, exist even among organisms that originate from different ecological niches. Although morphogenetic characteristics, viable RNA and protein dyes, and fluorescent reporter proteins have played an essential role in exploring such interactions, we hypothesized that ribosomal RNA-fluorescence in situ hybridization (rRNA-FISH) could be adapted and applied to further investigate interactions in synthetic or semisynthetic consortia. Despite its maturity, several challenges exist in using rRNA-FISH as a tool to quantify individual species population dynamics and interspecies interactions using high-throughput instrumentation such as flow cytometry. In this work, we resolve such challenges and apply rRNA-FISH to double and triple co-cultures of Clostridium acetobutylicum, Clostridium ljungdahlii, and Clostridium kluyveri . In pursuing our goal to capture each organism’s population dynamics, we demonstrate dynamic rRNA, and thus ribosome, exchange between the three species leading to the formation of hybrid cells. We also characterize the localization patterns of the translation machinery in the three species, identifying distinct, dynamic localization patterns among them. Our data also support the use of rRNA-FISH to assess the culture’s health and expansion potential, and, here again, our data find surprising differences among the three species examined. Taken together, our study argues for rRNA-FISH as a valuable and accessible tool for quantitative exploration of interspecies interactions, especially in organisms which cannot be genetically engineered or in consortia where selective pressures to maintain recombinant species cannot be used. IMPORTANCE Though dyes and fluorescent reporter proteins have played an essential role in identifying microbial species in co-cultures, we hypothesized that ribosomal RNA-fluorescence in situ hybridization (rRNA-FISH) could be adapted and applied to quantitatively probe complex interactions between organisms in synthetic consortia. Despite its maturity, several challenges existed before rRNA-FISH could be used to study Clostridium co-cultures of interest. First, species-specific probes for Clostridium acetobutylicum and Clostridium ljungdahlii had not been developed. Second, “state-of-the-art” labeling protocols were tedious and often resulted in sample loss. Third, it was unclear if FISH was compatible with existing fluorescent reporter proteins. We resolved these key challenges and applied the technique to co-cultures of C. acetobutylicum , C. ljungdahlii , and Clostridium kluyveri . We demonstrate that rRNA-FISH is capable of identifying rRNA/ribosome exchange between the three organisms and characterized rRNA localization patterns in each. In combination with flow cytometry, rRNA-FISH can capture sub-population dynamics in co-cultures.

Hill, John D.↗

DOE OSTI2025

Results and lessons learned from accelerating radio frequency modeling using machine learning [slides]

The “advanced tokamak” reactor concept is a leading candidate for a steady state fusion pilot plant. An advanced tokamak (AT) sustains a majority of the required plasma current with effects resulting from maintenance of the peaked pressure at the device center. This current is augmented by auxiliary current drive sources. These auxiliary actuators may consist of neutral particle beams and/or radio frequency (RF) systems such as lower hybrid current drive (LHCD) and high harmonic fast wave (HHFW) current drive using radio and microwaves from antennas. The primary focus of this work is to develop models of RF current profile control suitable for use in integrated modeling frameworks and for real-time control in experiments. Direct physics models of RF current drive can be computationally intensive. In order to achieve predictive times appropriate for the thousands of calls needed in real-time control of experiments and for use in integrated models, we will apply modern machine learning (ML) techniques to accelerate these models and interpolate their results. To generate the fast and accurate models for use in control level algorithms and integrated modeling we need to replace present models with high dimensional interpolation of their results. We will perform additional simulations across a broader parameter range for EAST and other tokamaks in different physics regimes (Alcator C-Mod, DIII-D, WEST, CFETR, ARC, ITER) and combine them into a larger database for training and testing of the ML models. Further testing of the control level models with experimental current profile data from EAST and C-Mod tokamaks will provide additional confirmation of the control level model before integration in a tokamak control system or integrated modeling suite. ML will be used to optimize the selection of training data consisting of RF current driven at different values of density profile, temperature profile, plasma current, and wavenumber. ML will also be used to facilitate classification of current drive from these input data. The output of this effort will be a validated classifier capable of determining the current drive profiles for HHFW CD and LHCD on a mille-second timescale. This will provide a breakthrough capability enabling real-time control of RF driven current profiles in experiments including ITER ICRF and use integrated modeling frameworks requiring thousands of current profile calculations in discharge simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗