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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Exploring driving forces for length growth in graphene nanoribbons during chemical vapor deposition of hydrocarbons on Ge(0 0 1) via kinetic Monte Carlo simulations

Graphene grown slowly on Ge(0 0 1) using chemical vapor deposition of hydrocarbons leads to high-aspect ratio graphene nanoribbons with smooth edges and a technologically relevant band gap at room temperature; however, the driving forces leading to one-dimensional growth of such graphene crystals are not well understood. Here, we combine a lattice kinetic Monte Carlo approach based on steps in graphene growth and experimental measurements to study the growth of graphene nanoribbons via chemical vapor deposition on Ge(0 0 1). To identify potential reasons for growth of graphene as anisotropic ribbons, we study the impact of anisotropy in various growth parameters on the resulting graphene crystals. Comparing our model with experimental measurements indicates that anisotropy in the stabilization of a graphene precursor species bound to the graphene edge is the most likely reason why high aspect ratio graphene ribbons with smooth edges grow on Ge(0 0 1). Using the growth model developed here, we reproduce experimental trends in the synthesis of graphene nanoribbons on Ge(001) and arrive at an intuitive picture for their growth. These insights shed light on the driving forces governing this highly anisotropic regime of crystal growth.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A small-angle neutron scattering study of the physical mechanism that drives the action of a viral fusion peptide

Viruses have evolved a variety of ways for delivering their genetic cargo to a target cell. One mechanism relies on a short sequence from a protein of the virus that is referred to as a fusion peptide. In some cases, the isolated fusion peptide is also capable of causing membranes to fuse. Infection by HIV-1 involves the 23 amino acid N-terminal sequence of its gp41 envelope protein, which is capable of causing membranes to fuse by itself, but the mechanism by which it does so is not fully understood. In this study, a variant of the gp41 fusion peptide that does not strongly promote fusion was studied in the presence of vesicles composed of a mixture of unsaturated lipids and cholesterol by small-angle neutron scattering and circular dichroism spectroscopy to improve the understanding of the mechanism that drives vesicle fusion. The peptide concentration and cholesterol content govern both the peptide conformation and its impact on the bilayer structure. The results indicate that the mechanism that drives vesicle fusion by the peptide is a strong distortion of the bilayer structure by the peptide when it adopts the β-sheet conformation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Reducing Direct Drive Preheat with Dopants

Preheat in laser-driven experiments can have negative impacts on inertial confinement fusion (ICF) and hydrodynamic experiments. While many groups employ the use of dopants to reduce or block preheat, direct quantification has not previously been explored. We developed a planar platform and a series of ablator targets to measure the electron and x-ray spectra generated by laser-plasma interactions with a direct drive using OMEGA-60. By comparing both thin ablators (75 μm) and thick ablators (270 μm) that were either pure CH, 3% Si doped or 3% I doped, we were able to measure differences in electron and x-ray spectra. In addition, we observed the preheat growth of tracer layers and observed reductions in the growth with different materials. We find that iodine or a thin gold layer is the best at tamping the direct-drive preheat at OMEGA, but that the growth is still significant.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Experimental driving performance evaluation of battery-powered medium and heavy duty all-electric vehicles

As the push to reduce air pollutants and carbon dioxide for global warming continues, there is increasing interest in the development and deployment of battery electric vehicles for heavy-duty applications as one of the critical and challenging steps of a broader effort to fully electrify the transportation sector. This study evaluated and quantified the energy consumption rates and energy regeneration rates for three heavy-duty battery electric vehicles (a step van, a yard tractor, and a class 8 truck) using driving cycle tests with a heavy-duty vehicle chassis dynamometer. Information in this area is currently very limited, and yet it is critical to understanding how effective heavy-duty battery electric vehicles will be for a wide range of applications as the electrification of the heavy-duty vehicle market continues to expand. Energy consumption rates ranged from 0.37 and 2.71 kWh/km for most vehicle/cycle combinations. On a diesel liter energy-equivalent basis, the heavy-duty vehicles had approximately 3 to 6 times better energy consumption rates compared to comparable diesel vehicles, with weight normalized energy consumption rates also comparing favorably to the current and future greenhouse gas/fuel economy standards for equivalent diesel vehicles. Based on battery capacities ranging from 80 to 215 kWh, the vehicle ranges varied from 38.18 km to 171.2 km, with ranges of 115.9 km to 171.2 km for most types of driving and lower ranges of 38.18 to 42.20 km for sustained grade cycles. Overall, the advantage of improved energy consumption rates coupled with improvements that can be expected for battery technology and vehicle range, provide promise for expanded use of heavy-duty vehicles going into the future.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Plant litter traits control microbial decomposition and drive soil carbon stabilization

Efforts to manage soils for carbon (C) sequestration remain limited by our understanding of how differences in plant traits and microbial traits mechanistically drive soil organic C (SOC) storage. Addressing this uncertainty is particularly critical in bioenergy agriculture, due to its potential to enhance soil C and provide a C neutral fuel. As such, we examined differences between two contrasting feedstocks, Zea mays (corn) and Miscanthus x giganteus (miscanthus), in the ability of their litter to form new chemically resistant particulate SOC vs. physically protected mineral associated SOC and used this data to improve the parameterization of a microbial SOC model. We tested a hypothesized conceptual model whereby easy to decompose corn litters drive greater microbial carbon use efficiency (CUE) and the formation of more mineral associated SOC over particulate SOC than more complex miscanthus litters. To do this, we performed a soil microcosm experiment where we added 13 C enriched aboveground and belowground litters to soils and traced the fate of the 13 C into microbial respiration and SOC pools. We found that corn litters promoted higher microbial CUE (0.37) than miscanthus litters (0.24). In turn, corn litter formed approximately 50% more mineral associated SOC than miscanthus litters. Similarly, structurally complex root litters promoted a lower CUE and formed less mineral associated SOC than leaf and shoot litters for both crops. When we used our data to parameterize the SOC model, we found that modelling microbial trait differences uniquely allowed the model to capture the fate of litter C in SOC. Collectively, we found a robust link between litter quality, microbial efficiency, and the formation of SOC. This link bridges the empirical uncertainty in how different crops can form new soil C and provides an empirical basis for modelling SOC transformations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Robust cooperative control strategy for a platoon of connected and autonomous vehicles against sensor errors and control errors simultaneously in a real-world driving environment

In a real-world driving environment, a platoon of connected and autonomous vehicles (CAVs) is subject to many internal and external disturbances, resulting in uncertain vehicle dynamics. In general, the disturbances can be categorized into two types: disturbances due to vehicle sensor errors (e.g., GPS error) and disturbances due to vehicle control errors (e.g., actuator delay). In the literature, many control strategies have been proposed to improve the robustness of the CAV platoon against uncertain vehicle dynamics induced by these disturbances. However, most of these strategies only consider one type of disturbance and cannot tackle both types of disturbances simultaneously. Furthermore, they are designed to maximize the benefits of each vehicle in the platoon independently, which can deteriorate the performance of the platoon. Here, to address these problems, this study proposes a robust cooperative control (RCC) strategy to maneuver the vehicles in the platoon cooperatively to counteract the impacts of both types of disturbances. The RCC strategy is developed based on a minimax problem, where the maximization subproblem seeks to find the worst inputs for the uncertainty terms in the vehicle dynamics equation to minimize the platoon performance, while the minimization subproblem seeks to find the optimal control decisions for all subsequent vehicles to maximize the platoon performance in the worst case. To solve the minimax problem, this study proposes a globally convergent solution algorithm. It can solve the minimax problem very efficiently to enable real time deployment of the RCC strategy. Numerical application indicates that compared to the existing methods, the RCC strategy can dramatically improve the robustness of the CAV platoon against the uncertain vehicle dynamics induced by both vehicle state detection errors and vehicle control errors. Therefore, it can maneuver the CAV platoon safely and efficiently in a real-world driving environment.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Microsimulation of Energy and Flow Effects from Optimal Automated Driving in Mixed Traffic

In this paper we study the energy and traffic impact of a proposed Anticipative Cruise Controller in a PTV VISSIM microsimulation environment. We dissect our controller into two parts: 1. the unconnected mode, active when following a human-driven vehicle, and 2. the connected mode, active when following another automated vehicle equipped with connectivity. Probabilistic constraints balance safety considerations with inter-vehicle compactness, and vehicle constraints for acceleration capabilities are expressed through the use of powertrain maps. Emergent highway traffic scenarios are then modeled using time headway distributions from empirical traffic data. To study the impact of automation over a range of demands of free-flow to stop-and-go, we vary vehicle flux from low to high and vary automated vehicle penetration from low to high. When examining all-human driving scenarios, network capacity failed to meet demand in high-volume scenarios, such as rush-hour traffic. We further find that with connected automated vehicles introduced, network capacity was improved to support the high-volume scenarios. Finally, we examine energy efficiencies of the fleet for conventional, electric, and hybrid vehicles. We find that automated vehicles perform at a 10%-20% higher energy efficiency over human drivers when considering conventional powertrains, and find that automated vehicles perform at a 3%-9% higher energy efficiency over human drivers when considering electric and hybrid powertrains. Due to secondary effects of smoothing traffic flow and reducing unnecessary braking, energy benefits also apply to human-driven vehicles that interact with automated ones. Such simulated humans were found to drive up to 10% more energy-efficiently than they did in the baseline all-human scenario.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

The role of infrastructure to enable and support electric drive vehicles: A Transportation Research Part D Special Issue

Widespread vehicle electrification appears to be necessary to achieve timely and deep reductions in greenhouse gases (GHG) and pollutant emissions as well as petroleum use in the transportation sector. The lack of a sufficient refuelling infrastructure has defeated many past efforts to promote alternatives to petroleum fuels. The papers in this special issue on the “Role of Infrastructure to Enable and Support Electric Drive Vehicles” address the diverse challenges posed by a transition from fossil-fuelled internal combustion engine vehicles to vehicles powered by electric motors and the special role of refuelling/recharging infrastructure in this transition. Electric drive vehicles are herein considered to be plug-in electric vehicles (PEVs), including plug-in hybrid electric vehicles (PHEVs), battery electric vehicles (BEVs), and hydrogen fuel cell electric vehicles (FCEVs). BEVs and FCEVs are also known as Zero Emission Vehicles (ZEVs) because their propulsion systems produce no tailpipe emissions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Bortezomib activation of mTORC1 pathway mediated by NOX2-drived reactive oxygen species results in apoptosis in primary dorsal root ganglion neurons

Highlights: • Bort induces apoptosis in DRG neurons. • Bort activates mTORC1 pathway in DRG neurons. • Bort-activated mTORC1 pathway contributes to DRG neuronal apoptosis. • Bort activates mTORC1 pathway via NOX2-drived ROS overgeneration leading to DRG neuronal apoptosis. Bortezomib (Bort), a chemotherapeutic agent, is widely used for the clinical treatment of cancers. However, Bort-induced peripheral neurotoxicity (BIPN) significantly restricts its clinical application, which is difficult to deal with since the underlying mechanisms of BIPN are unclear. Here, we showed that Bort activates mTORC1 pathway leading to dorsal root ganglion (DRG) neuronal apoptosis. Inhibition of mTORC1 with rapamycin or knockdown of raptor, regulatory-associated protein of mTORC1, with shRNA dramatically rescued the cells from Bort-caused apoptosis. In addition, we found that Bort-activated mTORC1 pathway was attributed to Bort elevation of reactive oxygen species (ROS). This is supported by the evidence that using ROS scavenger N-acetyl cysteine (NAC) significantly alleviated Bort-activated mTORC1 pathway. Furthermore, we revealed that upregulation of NOX2 contributed to Bort-elicited ROS overproduction, leading to mTORC1 pathway-dependent apoptosis in DRG neurons. Inhibition of NOX2 with apocynin remarkably diminished Bort-induced overgeneration of ROS, activation of mTORC1 pathway and apoptosis in the cells. Taken together, these results indicate that Bort activation of mTORC1 pathway mediated by NOX2-drived ROS leads to apoptotic death in DRG neurons. Our findings highlight that manipulation of intracellular ROS level or NOX2 or mTORC1 activity may be exploited for prevention of BIPN.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Lower hybrid current drive in a tokamak for correlated passes through resonance

Standard quasilinear descriptions are based on the constant magnetic field form of the quasilinear operator so improperly treat the trapped electron modifications associated with tokamak geometry. Moreover, successive poloidal transits of the Landau resonance during lower hybrid current drive in a tokamak are well correlated, and these geometrical details must be properly retained to account for the presence of trapped electrons that do not contribute to the driven current. The recently derived quasilinear operator in tokamak geometry accounts for these features and finds that the quasilinear diffusivity is proportional to a delta function with a transit or bounce averaged argument (rather than a local Landau resonance condition). The new quasilinear operator is combined with the Cordey ( Nucl. Fusion , vol. 16, 1976, pp. 499–507) eigenfunctions to properly derive a rather simple and compact analytic expression for the trapped electron modifications to the driven lower hybrid current and the efficiency of the current drive.

Physics↗
DOE OSTI2022

Verifying raytracing/Fokker–Planck lower-hybrid current drive predictions with self-consistent full-wave/Fokker–Planck simulations

Raytracing/Fokker–Planck (FP) simulations used to model lower-hybrid current drive (LHCD) often fail to reproduce experimental results, particularly when LHCD is weakly damped. A proposed reason for this discrepancy is the lack of ‘full-wave’ effects, such as diffraction and interference, in raytracing simulations and the breakdown of the raytracing approximation. Previous studies of LHCD using non-Maxwellian full-wave/FP simulations have been performed, but these simulations were not self-consistent and enforced power conservation between the FP and full-wave code using a numerical rescaling factor. Here, we have created a fully self-consistent full-wave/FP model for LHCD that is automatically power conserving. This was accomplished by coupling an overhauled version of the non-Maxwellian TORLH full-wave solver and the CQL3D FP code using the Integrated Plasma Simulator. We performed converged full-wave/FP simulations of Alcator C-Mod discharges and compared them with raytracing. We found that excellent agreement in the power deposition profiles from raytracing and TORLH could be obtained, however, TORLH had somewhat lower current drive efficiency and broader power deposition profiles in some cases. This discrepancy appears to be a result of numerical limitations present in the TORLH model and a small amount of diffractional broadening of the TORLH wave spectrum. Our results suggest full-wave simulation of LHCD is likely not necessary as diffraction and interference represented only a small correction that could not account for the differences between simulations and experiment.

Physics↗
DOE OSTI2023

Self-Driving Laboratory for Polymer Electronics

Owing to the chemical pluripotency and viscoelastic nature of electronic polymers, polymer electronics have shown unique advances in many emerging applications such as skin-like electronics, large-area printed energy devices, and neuromorphic computing devices, but their development period is years-long. Recent advancements in automation, robotics, and learning algorithms have led to a growing number of self-driving (autonomous) laboratories that have begun to revolutionize the development and accelerated discovery of materials. In this perspective, we first introduce the current state of autonomous laboratories. Then we analyze why it is challenging to conduct polymer electronics research by an autonomous laboratory and highlight the needs. Here, we further discuss our efforts in building an autonomous laboratory, namely Polybot, for the automated synthesis and characterization of electronic polymers and their processing and fabrication into electronic devices. Finally, we share our vision in using a self-driving laboratory for different types of polymer electronics research.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Is the Local Ion Density Sufficient to Drive NaCl Nucleation from the Melt and Aqueous Solution?

Even though nucleation is ubiquitous in different science and engineering problems, investigating nucleation is extremely difficult due to the complicated ranges of time and length scales involved. In this work, we simulate NaCl nucleation in both molten and aqueous environments using enhanced sampling of all-atom molecular dynamics with deep-learning-based estimation of reaction coordinates. By incorporating various structural order parameters and learning the reaction coordinate as a function thereof, we achieve significantly improved sampling relative to traditional ad hoc descriptions of what drives nucleation, particularly in an aqueous medium. Our results reveal a one-step nucleation mechanism in both environments, with reaction coordinate analysis highlighting the importance of local ion density in distinguishing solid and liquid states. However, although fluctuations in the local ion density are necessary to drive nucleation, they are not sufficient. Our analysis shows that near the transition states, descriptors such as enthalpy and local structure become crucial. Furthermore, our protocol proposed here enables robust nucleation analysis and phase sampling and could offer insights into nucleation mechanisms for generic small molecules in different environments.

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

Electric Field’s Dueling Effects through Dehydration and Ion Separation in Driving NaCl Nucleation at Charged Nanoconfined Interfaces

Investigating nucleation in charged nanoconfined environments under electric fields is crucial for many scientific and engineering applications. Here we study the nucleation of NaCl from aqueous solution near charged surfaces using machine-learning-augmented enhanced sampling molecular dynamics simulations. Our simulations successfully drive phase transitions between the liquid and solid phases of NaCl. The solid phase is stabilized under electric fields, particularly at an intermediate surface charge density. We examine which physical characteristics drive the nucleation of NaCl from aqueous solutions and find that the removal of solvent water from Cl– at the solid precursor surface plays a more critical role than the accumulation of ions. Our simulations reveal the competing effects of electric fields on nucleation processes: they facilitate the removal of water, promoting nucleation, but also promote the separation of ion pairs, thereby hindering nucleation. Here, this work provides a framework for studying nucleation processes in nanoconfined environments under electric fields and provides physical insights for the design of electrochemistry materials.

Electric fields↗
DOE OSTI2022

Protecting qubit coherence by spectrally engineered driving of the spin environment

Abstract Modern quantum technologies rely crucially on techniques to mitigate quantum decoherence; these techniques can be either passive, achieved for example via materials engineering, or active, typically achieved via pulsed monochromatic driving fields applied to the qubit. Using a solid-state defect spin coupled to a microwave-driven spin bath, we experimentally demonstrate a decoherence mitigation method based on spectral engineering of the environmental noise with a polychromatic drive waveform, and show that it outperforms monochromatic techniques. Results are in agreement with quantitative modeling, and open the path to active decoherence protection using custom-designed waveforms applied to the environment rather than the qubit.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Spin–vibronic coherence drives singlet–triplet conversion

Design-specific control over the transitions between excited electronic states with different spin multiplicities is of the utmost importance in molecular and materials chemistry. Previous studies have indicated that the combination of spin-orbit and vibronic effects, collectively termed the spin-vibronic effect, can accelerate quantum-mechanically forbidden transitions at non-adiabatic crossings. However, it has been difficult to identify precise experimental manifestations of the spin-vibronic mechanism. Here we present coherence spectroscopy experiments that reveal the interplay between the spin, electronic and vibrational degrees of freedom that drive efficient singlet-triplet conversion in four structurally related dinuclear Pt(II) metal-metal-to-ligand charge-transfer (MMLCT) complexes. Photoexcitation activates the formation of a Pt-Pt bond, launching a stretching vibrational wavepacket. The molecular-structure-dependent decoherence and recoherence dynamics of this wavepacket resolve the spin-vibronic mechanism. Further, we find that vectorial motion along the Pt-Pt stretching coordinates tunes the singlet and intermediate-state energy gap irreversibly towards the conical intersection and subsequently drives formation of the lowest stable triplet state in a ratcheting fashion. This work demonstrates the viability of using vibronic coherences as probes to clarify the interplay among spin, electronic and nuclear dynamics in spin-conversion processes, and this could inspire new modular designs to tailor the properties of excited states.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Self-driving laboratories to autonomously navigate the protein fitness landscape

Abstract Protein engineering has nearly limitless applications across chemistry, energy and medicine, but creating new proteins with improved or novel functions remains slow, labor-intensive and inefficient. Here we present the Self-driving Autonomous Machines for Protein Landscape Exploration (SAMPLE) platform for fully autonomous protein engineering. SAMPLE is driven by an intelligent agent that learns protein sequence–function relationships, designs new proteins and sends designs to a fully automated robotic system that experimentally tests the designed proteins and provides feedback to improve the agent’s understanding of the system. We deploy four SAMPLE agents with the goal of engineering glycoside hydrolase enzymes with enhanced thermal tolerance. Despite showing individual differences in their search behavior, all four agents quickly converge on thermostable enzymes. Self-driving laboratories automate and accelerate the scientific discovery process and hold great potential for the fields of protein engineering and synthetic biology.

Rapp, Jacob T. (ORCID:0000000226835204)↗
DOE OSTI2026

Initial electron cyclotron heating/current drive scoping study for the SMall Aspect Ratio Tokamak (SMART)

In this work an initial electron cyclotron heating/current drive (EC H&CD) scoping study is presented for the SMall Aspect Ratio Tokamak (SMART), constructed and operated by the Plasma Science and Fusion Technology (PSFT) Laboratory of the University of Seville. We consider two planned phases of operation with different magnitude of magnetic field (B 0.4, and 1 T). This EC H&CD scoping study is carried out by using the ray tracing code TRAVIS, which allows to quickly perform a series of scans on the main SMART plasma scenarios. A scan in the poloidal and toroidal launching angles is performed for the B 0.4 T plasma scenario assuming three launching locations (mid-plane, off-mid-plane, and top-launcher) and the extraordinary (X-) mode polarization. The absorption occurs at the second harmonic and, overall, the highest power absorption is obtained launching the EC beam from the top of the machine. A numerical analysis of the fundamental X-mode EC H&CD start-up regime for the B 1.0 T plasma scenario with two different wave frequencies (28 and 35 GHz) is presented showing a very high current drive efficiency.

Bertelli, Nicola [Princeton Plasma Physics Laborat↗