Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Hybrid Work”

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.

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

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Bi-modal particle size distribution for high energy product hybrid Nd–Fe–B—Sm–Fe–N bonded magnets

In this work, we have demonstrated high energy product bonded magnet by leveraging the variation in sizes between Nd-Fe-B and Sm-Fe-N, as well as their hard magnetic properties. The hybrid anisotropic bonded magnets contain 70 vol% of magnet powder (Dy-free Nd-Fe-B and Sm-Fe-N) and 30 vol% of nylon. The objective of the work was to create bi-modal and bi-compositional bonded magnets in which the fine (3μm) particles of Sm-Fe-N would be used to fill the voids between the bigger Nd-Fe-B (105μm) particles, thus improve packing density. The magnetic hysteresis loop did not show significant signs of decoupled interactions between the magnetic phases. It was also found that the performance of the bonded magnet was most enhanced at 1:4 ratio of Nd-Fe-B and Sm-Fe-N. At that ratio, maximum density of 5 g/cm 3 and the highest (BH) max value of 18.5 MGOe were obtained, although the intrinsic coercivity decreased, relative to the trend seen for other ratios. This work advances the opportunity to expand the use of Sm-Fe-N in bonded magnet applications.

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

Robust implementation of generative modeling with parametrized quantum circuits

Although the performance of hybrid quantum-classical algorithms is highly dependent on the selection of the classical optimizer and the circuit ansätze, a robust and thorough assessment on-hardware of such features has been missing to date. From the optimizer perspective, the primary challenge lies in the solver’s stochastic nature, and their significant variance over the random initialization. Therefore, a robust comparison requires one to perform several training curves for each solver before one can reach conclusions about their typical performance. Since each of the training curves requires the execution of thousands of quantum circuits in the quantum computer, such a robust study remained a steep challenge for most hybrid platforms available today. In this work, we leverage on Rigetti’s Quantum Cloud Services (QCS™) to overcome this implementation barrier, and we study the on-hardware performance of the data-driven quantum circuit learning (DDQCL) for three different state-of-the-art classical solvers, and on two-different circuit ansätze associated to different entangling connectivity graphs for the same task. Additionally, we assess the gains in performance from varying circuit depths. To evaluate the typical performance associated with each of these settings in this benchmark study, we use at least five independent runs of DDQCL towards the generation of quantum generative models capable of capturing the patterns of the canonical Bars and Stripes dataset. In this experimental benchmarking, the gradient-free optimization algorithms show an outstanding performance compared to the gradient-based solver. In particular, one of them had better performance when handling the unavoidable noisy objective function to be minimized under experimental conditions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Liquid lithium wetting and percolation in a porous tungsten/liquid Li plasma facing component (PFC)

This work explores the concept of a hybrid material system designed to protect the plasma from high-Z material emission while also protecting an underlying high-Z wall material from erosion by integrating a low-Z component in the liquid phase. Plasma-surface interaction properties of a porous tungsten (W)-liquid metal hybrid system, having the favorable bulk thermomechanical properties of W while serving as a scaffold for a liquid metal with self-healing and radiative vapor shielding characteristics, are examined. W-substrates with 70% density of bulk W and 1–5 μm sized pores have been fabricated with 50-nm W powders using spark plasma sintering. Enhanced lithium (Li) wettability, driven by percolation through the porous W architecture, is demonstrated with in-situ liquid Li drop measurements. Finally, results show complete wetting of liquid Li at 250 °C in the porous W, 100 °C lower temperature than what has been observed on traditional W surfaces. In operando ion beam analysis of Li films deposited on porous W substrates provides microscopic evidence of Li percolation into the substrate and a first look at D retention up to a depth of 100 nm after plasma exposure at a flux of 10 20 m –2 s –1 , 250 eV/amu D + plasma to a fluence of 1.16 × 10 23 m –2 at a temperature of 200 °C.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Thermal management of a high temperature sodium sulphur battery stack

The sodium sulfur battery is an advanced secondary battery with high potential for grid-level storage due to their high energy density, low cost of the reactants, and high open-circuit voltage. However, as the operating temperature of the battery is high (about 300 °C), effective thermal management is required to prevent thermal runaway under high current density operation. Here, to develop efficient thermal management strategies, a detailed, thermo-electrochemical, non-isothermal, distributed dynamic model of a sodium-sulfur battery stack is developed. Models of three thermal management strategies are developed and analyzed in this work: active cooling, passive cooling, and hybrid cooling. The active cooling strategy uses air as the cooling medium whereas, the passive cooling strategy uses a phase change material. In the hybrid cooling strategy, both active and passive cooling strategies are used. Due to the high operating temperature of the sodium sulfur batteries, the rejected heat can be utilized effectively and consequently a high variability in the heat rejection rate may not be acceptable. Performance of these strategies is analyzed under high current density operation by evaluating the variability in the cell temperature during charge/discharge cycles, temperature difference between the cells based on their locations, and variability in the heat rejection rate. The phase change-based hybrid thermal management strategy with an embedded controller maintained the temperature variation within ±/- 2.8 °C. Considering the tradeoff between the capital cost for PCM, fan power requirement, and variability in the heat rejection rate, the optimal quantity of the PCM and the maximum air velocity for the maximum current density of 260 mA/cm 2 (0.55 C-rate) were found be 0.74 g/Wh and 3 m/s, respectively.

25 ENERGY STORAGE↗
DOE OSTI2025

Self-Assembled Oligomers Facilitate Amino Acid-Driven CO 2 Capture at the Air–Aqueous Interface

Direct air capture of CO 2 using amino acid absorbents, such as glycine or sarcosine, is constrained by the relatively slow mass transfer of CO 2 through the air–aqueous interface. Our recent study showed a marked improvement in CO 2 capture by introducing CO 2 -permeable oligo-dimethylsiloxane (ODMS-MIM + ) oligomers with cationic (imidazolium, MIM + ) headgroups. Here, in this work, we have employed all-atom molecular dynamics simulations in combination with subensemble analysis using network theory to provide a detailed molecular picture of the behavior of CO 2 and the glycinate anions (Gly – ) at the ODMS-MIM + decorated air–aqueous interfaces. We show that the cationic head groups of the surfactants enhance the concentration and lifetime of Gly – in the interfacial region, while ODMS tails promote the physisorption of CO 2 in the interfacial region. Together, these two factors increase the effective region of contact and the probability of interactions between CO 2 and Gly – compared to that of the pure air–aqueous interface. The fundamental insights gained in this work establish essential foundations for developing hybrid systems with oligomer-decorated interfaces to maximize the overall CO 2 capture rates.

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

Unraveling the Mechanism of Interfacial Charge Transfer and Photoresponsivity of WS 2 Quantum Dots/MoS 2 (0D–2D) Heterostructure-Based Transistors

To assess the efficacy of a mixed-dimensional van der Waals (vdW) heterostructure in modulating the optoelectronic responses of nanodevices, the charge transport properties of the transition-metal dichalcogenide (TMD)-based heterostructure comprising zero-dimensional (0D) WS 2 quantum dots (QDs) and two-dimensional (2D) MoS 2 flakes are critically analyzed. Herein, a facile strategy was materialized in developing an atomically thin phototransistor assembled from mechanically exfoliated MoS 2 and WS 2 QDs synthesized using a one-pot hydrothermal route. The amalgamated photodetectors exhibited a high responsivity of ∼8000 A/W at an incident power of 0.05 nW of white light, surpassing that of the pristine MoS 2 devices. Furthermore, the detectivity of pristine MoS 2 , which was on the order of 10 10 , increased to 10 12 Jones for the WS 2 QDs/MoS 2 heterostructure photodetector, outperforming other WS 2 -based materials. The quasiparticle band gap and density of states (DOS) are further analyzed to elucidate the photophysics of the WS 2 QD/MoS 2 hybrid assembly. The difference in the work function between MoS 2 and WS 2 QDs gives rise to an electric field across the 0D–2D interface, facilitating effective charge separation and migration and contributing to the enhancement of photoresponsivity. The analysis of optical responses using density functional theory (DFT) revealed stronger absorption and less reflection over a broader spectrum of wavelengths for the heterostructure compared to the pristine materials. The estimated optical conductivity aligns well with the experimentally predicted maximum photoresponsivity under visible light, which is attributed to the high absorbance of 2D MoS 2 . In conclusion, combining diverse spectroscopic and imaging techniques with quantum simulation provides insights that clarify the pertinence of 0D–2D TMDs in designing phototransistors.

WS2 QDs/MoS2 heterostructure↗
DOE OSTI2024

Unveiling the Multielectron Acceptor Properties of π-Expanded Pyracylene: Reversible Boat to Chair Conversion

In this work, the chemical reduction of a hybrid pyracylene-hexa-peri-hexabenzocoronene (HPH) nanographene was investigated with different alkali metals (Na, K, Rb) to reveal its remarkable multielectron acceptor abilities. The UV–vis and 1 H NMR spectroscopy monitoring of the stepwise reduction reactions supports the existence of all intermediate reduction states up to the hexaanion for HPH. Tuning the experimental conditions enabled the synthesis of the HPH anions with gradually increasing reduction states (up to –5) isolated with different alkali metal ions as crystalline materials. The single-crystal X-ray diffraction structure analysis demonstrates that the highly negatively charged HPH anions (–4 and –5) exhibit a drastic geometry change from boat-shaped (observed in the neutral parent, mono- and dianions) to a chair conformation, which was proved to be fully reversible by NMR spectroscopy. DFT calculations show that this geometry change is induced by an enhanced interaction between the coordinated metal ions and negatively charged HPH core in the chair conformation.

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

Probing initial baryon stopping and equation of state with rapidity-dependent directed flow of identified particles

In this work, using a (3 + 1)-dimensional hybrid framework with parametric initial conditions, we study the rapidity-dependent directed flow $v_1 (y)$ of identified particles, including pions, kaons, protons, and lambdas in heavy-ion collisions. Cases involving Au + Au collisions are considered, performed at $\sqrt {^SNN}$ ranging from 7.7 to 200 GeV. The dynamics in the beam direction is constrained using the measured pseudo-rapidity distribution of charged particles and the net proton rapidity distribution. Within this framework, the directed flow of mesons is driven by the sideward pressure gradient from the tilted source, and that of baryons mainly due to the initial asymmetric baryon distribution with respect to the beam axis driven by the transverse expansion. Our approach successfully reproduces the rapidity- and beam energy-dependence of $v_1$ for both mesons and baryons. We find that the $v_1 (y)$ of baryons has strong constraining power on the initial baryon stopping, and together with that of mesons, the directed flow probes the equation of state of the dense nuclear matter at finite chemical potentials.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Fast Algorithms for Scientific Data Compression

Many scientific simulations and experiments generate terabytes to petabytes of data daily, necessitating data compression techniques. Unlike video and image compression, scientists require methods that accurately preserve primary data (PD) and derived quantities of interest (QoIs). In our previous work, we demonstrated the effectiveness of hybrid compression techniques that combine machine learning with traditional approaches. This paper presents innovative computational techniques aimed at expediting the compression pipeline. Our experiments, conducted on two distinct platforms with a large-scale XGC-based fusion simulation, demonstrate that the overhead incurred by these new approaches is less than one percent of the computational resources needed for the simulation.

Banerjee, Tania↗
DOE OSTI2020

Review—Development of Highly Active and Durable Hybrid Compressive Platinum Lattice Catalysts for Polymer Electrolyte Membrane Fuel Cells: Mathematical Modeling and Experimental Work

This review provides a comprehensive overview on the development of highly active and durable platinum catalysts with ultra-low Pt loadings for polymer electrolyte membrane fuel cells (PEMFCs) through a combined mathematical modeling and experimental work. First, simulation techniques were applied to evaluate the validity of the Tafel approximation for the calculation of the mass activity (MA) and specific activity (SA). A one-dimensional agglomeration model was developed and solved to understand the effects of exchange current density, porosity, agglomerate size, Nafion ® film thickness, and Pt loading on the MA and SA. High porosity (> 60%) and agglomerations at high Pt loadings cause the loss of the Tafel approximation and consequently the decrease in MA and SA. A new structure parameter was introduced to estimate the real porous structure using the fractal theory. The volumetric catalyst density was corrected by the fractal dimension (measured by Hg porosimetry), which gave a good agreement with the experimental values. The loading-dependent Tafel equation was then derived, which contains both the utilization and the non-linear scaling factor. Second, activated carbon composite support (ACCS) with optimized surface area, porosity, pore size, and pore size distribution was developed. The hydrophilic/hydrophobic ratio, structural properties (amorphous/crystalline ratio), and the number of active sites were optimized through metal-catalyzed pyrolysis. Stability of ACCS and Pt/ACCS were evaluated using an accelerated stress test (AST). The results indicated that Pt/ACCS showed no significant loss of MA and power density after 5,000 cycles at 1.0–1.5 V, while the commercial Pt/C catalysts showed drastic losses of MA and power density. Finally, monolayers of compressed Pt (core–shell-type Pt 3 Co 1 ) catalysts were structured by diffusing Co atoms (previously embedded in ACCS) into Pt. Compressive Pt lattice (Pt * ) catalysts were synthesized through an annealing procedure developed at the University of South Carolina (USC). The Pt * /ACCS catalyst showed high initial power density (rated) of 0.174 g Pt kW −1 and high stability (24 mV loss) at 0.8 A cm −2 after 30,000 cycles (0.6–1.0 V). The outstanding performance of Pt * /ACCS is due to the synergistic effect of ACCS and compressive Pt * lattice.

25 ENERGY STORAGE↗
DOE OSTI2022

Dynamics Informed Optimization for Resilient Energy Systems

Optimal mitigation planning for highly disruptive contingencies to a transmission-level power system requires optimization with dynamic power system constraints, due to the key role of dynamics in system stability to major perturbations. We formulate a generalized disjunctive program to determine optimal grid component hardening choices for protecting against major failures, with differential algebraic constraints representing system dynamics (specifically, differential equations representing generator and load behavior and algebraic equations representing instantaneous power balance over the transmission system). We optionally allow stochastic optimal pre-positioning across all considered failure scenarios, and optimal emergency control within each scenario. This novel formulation allows, for the first time, analyzing the resilience interdependencies of mitigation planning, preventive control, and emergency control. Using all three strategies in concert is particularly effective at maintaining robust power system operation under severe contingencies, as we demonstrate on the Western System Coordinating Council (WSCC) 9-bus test system using synthetic multi-device outage scenarios. Towards integrating our modeling framework with real threats and more realistic power systems, we explore applying hybrid dynamics to power systems. Our work is applied to basic RL circuits with the ultimate goal of using the methodology to model protective tripping schemes in the grid. Finally, we survey mitigation techniques for HEMP threats and describe a GIS application developed to create threat scenarios in a grid with geographic detail.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Stochastic Price Generation for Evaluating Wholesale Electricity Market Bidding Strategies

This work presents a novel method for generating electricity price scenarios from statistical properties of past electricity prices using a hybrid statistical and reduced-form stochastic model. Previous work in applying stochastic differential equations (SDE) to model electricity prices has focused on daily average prices. To extend stochastic price generation methods to hourly or sub-hourly pricing, we address several weaknesses in the state-of-the-art: (1) we replace the mean-reversion component of the SDE with an ARIMA process that is better able to characterize the daily and weekly trends; (2) we extend the price-spike, or jump process to account for conditional probabilities of price spikes occurring in consecutive time steps by replacing the traditional Poisson process for modeling jumps with a generalized point process model inspired by brain neuron models; and (3) we replace the traditional method of estimating spike intensity with empirical variance with a Markov process based on observed price spike intensity transitions. The method is demonstrated with electricity prices from the US ERCOT market and a use-case example is provided for bidding an energy storage unit into the day-ahead and real-time energy markets of ERCOT using stochastic optimization methods. Results show that the the synthetic price model out performs a (naive) persistence forecast model by resulting in 24% to 47% more in profits over 168 simulated days.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

IoT Devices and Applications for Wire-Based Hybrid Manufacturing Machine Tools

Hybrid manufacturing machine tools have the potential to be a disruptive technology as they can leverage the benefits of both additive and subtractive manufacturing by incorporating both processes on the same machine while limiting the downsides of the individual processes. Since these machines use two very disparate manufacturing processes and hybrid manufacturing is an emerging technology, it will be useful to monitor data coming from the machine and apply it to improve the manufacturing process, the operation of the machine, and to integrate the machine into the larger digital framework of Industrial Internet of Things (IoT). The present work discusses IoT devices that would be beneficial to add to a hybrid machine tool as well as applications for those devices. The proposed methods discussed in this work have not been experimentally implemented on a hybrid machine tool and so there are no performance data available yet. The hybrid machine tool used as a basis to generate these IoT applications is the Mazak VC-500A/5x AM Hot Wire Deposition, which is a 5-axis machine tool incorporated with a wire feedstock 4kW laser deposition system. Methodologies and applications will be outlined for machine health and process monitoring. Other areas covered include process benchmarking, secure networking options for the proposed IoT framework, and hybrid process improvement. Limitations of these methods and future work for new sensor devices and application areas is also discussed.

Thien, Austen↗
DOE OSTI2020

Enabling 6C Fast Charging of Li–Ion Batteries with Graphite/Hard Carbon Hybrid Anodes

Li-ion batteries that can simultaneously achieve high-energy density and fast charging are essential for electric vehicles. Graphite anodes enable a high-energy density, but suffer from an inhomogeneous reaction current and irreversible Li plating during fast charging. In contrast, hard carbon exhibits superior rate performance but lower energy density owing to its lower initial coulombic efficiency and higher average voltage. In this work, these tradeoffs are overcome by fabricating hybrid anodes with uniform mixtures of graphite and hard carbon, using industrially-relevant multi-layer pouch cells (>1 Ah) and electrode loadings (3 mAh cm –2 ). By controlling the graphite/hard carbon ratio, this study shows that battery performance can be systematically tuned to achieve both high-energy density and efficient fast charging. Pouch cells with optimized hybrid anodes retain 87% and 82% of their initial specific energy after 500 cycles of 4C and 6C fast-charge cycling, respectively. This is significantly higher than the 61% and 48% specific energy retention with graphite anodes under the same conditions. The enhanced performance is attributed to improved homogeneity of the reaction current throughout the hybrid anode, which is supported by continuum-scale modeling. Furthermore, this process is directly compatible with existing roll-to-roll battery manufacturing, representing a scalable pathway to fast charging.

25 ENERGY STORAGE↗
DOE OSTI2021

Bidirectional interconversion of microwave and light with thin-film lithium niobate

Abstract Superconducting cavity electro-optics presents a promising route to coherently convert microwave and optical photons and distribute quantum entanglement between superconducting circuits over long-distance. Strong Pockels nonlinearity and high-performance optical cavity are the prerequisites for high conversion efficiency. Thin-film lithium niobate (TFLN) offers these desired characteristics. Despite significant recent progresses, only unidirectional conversion with efficiencies on the order of 10 −5 has been realized. In this article, we demonstrate the bidirectional electro-optic conversion in TFLN-superconductor hybrid system, with conversion efficiency improved by more than three orders of magnitude. Our air-clad device architecture boosts the sustainable intracavity pump power at cryogenic temperatures by suppressing the prominent photorefractive effect that limits cryogenic performance of TFLN, and reaches an efficiency of 1.02% (internal efficiency of 15.2%). This work firmly establishes the TFLN-superconductor hybrid EO system as a highly competitive transduction platform for future quantum network applications.

42 ENGINEERING↗
DOE OSTI2022

Optimal management of electric hotel loads in mild hybrid heavy duty truck

Here, the problem of engine idling for heavy-duty trucks has been under study for decades with Auxiliary Power Units (APUs) and Truck Stop Electrification (TSE) as the most compelling solutions. With the electrification of trucks approaching feasibility in terms of cost-effective technology, hybridization offers another “degree of freedom” to tackle the problem. Here, this work aims at exploiting a battery pack of a 48 V mild-hybrid heavy-duty truck to store sufficient onboard energy for powering the auxiliary loads during the hoteling. This problem is not trivial, as the battery packs typically cannot recover the entire energy required through regeneration alone; hence an optimal energy management strategy needs to be employed to charge the battery through the engine during drive operation. This strategy optimizes powertrain performances among the four modes: (i) Engine of Coasting (EOC), (ii) Regeneration by braking, (iii) Regeneration by engine, and (iv) engine idling. This paper presents the development of a Dynamic Programming (DP) framework that employs a multi-objective cost function to minimize the fuel consumption and maximize the regeneration using the above-mentioned four modes. A typical heavy-duty truck drive cycle is used to represent the drive phase, with mandatory hoteling stops as per regulations. A comprehensive powertrain model is developed using validated components’ model. The DP employs two state variables: battery State-of-Charge (SOC) and engine mode, and three control inputs: (i) the engine ON–OFF state, (ii) clutch engagement state, and (iii) power request at the Electric Machine (EM) for calculating optimal SOC trajectory. The framework also tackles rapid engine ON–OFF scenarios to avoid the challenges associated with DP and the compromises in fuel cost with those approaches. Finally, the effectiveness of the proposed framework is tested for potential fuel savings on two different battery packs by performing the full cycle simulations. The results show 6.47% of fuel consumption reduction as compared to traditional APU-based heavy-duty truck.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Plasmon Energy Transfer in Hybrid Nanoantennas

Plasmonic metal nanoparticles exhibit large dipole moments upon photoexcitation and have the potential to induce electronic transitions in nearby materials, but fast internal relaxation has to date limited the spatial range and efficiency of plasmonic mediated processes. In this work, we use photo-electrochemistry to synthesize hybrid nanoantennas comprised of plasmonic nanoparticles with photoconductive polymer coatings. Here, we demonstrate that the formation of the conductive polymer is selective to the nanoparticles and that polymerization is enhanced by photoexcitation. In situ spectroscopy and simulations support a mechanism in which up to 50% efficiency of nonradiative energy transfer is achieved. These hybrid nanoantennas combine the unmatched light-harvesting properties of a plasmonic antenna with the similarly unmatched device processability of a polymer shell.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Revealing pressure-driven structural transitions in the hybrid improper ferroelectric Sr 3 Sn 2 O 7

In this work, we combine diamond anvil cell techniques and synchrotron-based infrared spectroscopy with a detailed symmetry analysis and lattice dynamics calculations to uncover a series of pressure induced structural phase transitions in the hybrid improper ferroelectric Sr 3 Sn 2 O 7 . The microscopic character of each high pressure phase is determined by comparing the measured spectrum with the predicted vibrational patterns of several related but distinct candidate space groups. Our analysis reveals a sequence of compression-induced transitions from A2 1 am ↔ Pnab ↔ Acaa ↔ I4/mmm at room temperature. Remarkably, this space group progression matches the sequence of temperature-dependent structural transitions observed in Sr 3 Sn 2 O 7 between 77 and 1000 K. Other hybrid improper ferroelectrics display a similar set of transitions, suggesting that pressure and probably strain will be very effective tuning parameters for this entire class of materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗