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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Nanomotor-enhanced transport of passive Brownian particles in porous media

Artificial micro/nanomotors are expected to perform tasks in interface-rich and species-rich environments for biomedical and environmental applications. In these highly confined and interconnected pore spaces, active species may influence the motion of coexisting passive participants in unexpected ways. Using three-dimensional super-resolution single-nanoparticle tracking, we observed enhanced motion of passive nanoparticles due to the presence of dilute well-separated nanomotors in an interconnected pore space. This enhancement acted at distances that are large compared to the sizes of the particles and cavities, in contrast with the insignificant effect on the passive particles with the same dilute concentration of nanomotors in an unconfined liquid. Experiments and simulations suggested an amplification of hydrodynamic coupling between self-propelled and passive nanoparticles in the interconnected confined environment, which enhanced the effective energy for passive particles to escape cavities through small holes. This finding represents an emergent behavior of confined nanomotors and suggests new strategies for the development of antifouling membranes and drug delivery systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2020

Design of higher valency in covalent organic frameworks

The valency (connectivity) of building units in covalent organic frameworks (COFs) has been primarily 3 and 4, corresponding to triangles and squares or tetrahedrons, respectively. We report a strategy for making COFs with valency 8 (cubes) and “infinity” (rods). The linker 1,4-boronophenylphosphonic acid—designed to have boron and phosphorus as an isoelectronic combination of carbon-group elements—was condensed into a porous, polycubane structure (BP-COF- 1 ) formulated as (–B 4 P 4 O 12 –)(–C 6 H 4 –) 4 . It was characterized by x-ray powder diffraction techniques, which revealed cubes linked with phenyls. The isoreticular forms (BP-COF- 2 to 5 ) were similarly prepared and characterized. Large single crystals of a constitutionally isomeric COF (BP-COF- 6 ), composed of rod units, were also synthesized using the same strategy, thus propelling COF chemistry into a new valency regime.

Gropp, Cornelius↗
DOE OSTI2025

A molecular conveyor belt-associated protein controls the rotational direction of the bacterial type 9 secretion system

ABSTRACT Many bacteria utilize the type 9 secretion system (T9SS) for gliding motility, surface colonization, and pathogenesis. This dual-function motor supports both gliding motility and protein secretion, where rotation of the T9SS plays a central role. Fueled by the energy of the stored proton motive force and transmitted through the torque of membrane-anchored stator units, the rotary T9SS propels an adhesin-coated conveyor belt along the bacterial outer membrane like a molecular snowmobile, thereby enabling gliding motion. However, the mechanisms controlling the rotational direction and gliding motility of T9SS remain elusive. Shedding light on this mechanism, we find that in the gliding bacteriumFlavobacterium johnsoniae, deletion of the C-terminus of the conveyor belt-associated protein GldJ controls and, in fact, reverses the rotational direction of T9SS from counterclockwise (CCW) to clockwise (CW). This suggests that the interface between the conveyor belt-associated protein GldJ and the T9SS ring protein GldK plays an important role in controlling the directionality of T9SS, potentially by modulating its interaction with the stator complex GldLM, which drives motor rotation. Combined with MD simulation of the T9SS stator units GldLM, we suggest a “tri-component gearset” model where GldJ controls the rotational direction of its driver, the T9SS, thus providing adaptive sensory feedback to influence the motility of the gliding bacterium. IMPORTANCE The type 9 secretion system (T9SS) is fundamental to bacterial gliding motility, pathogenesis, and surface colonization. Our findings reveal that the C-terminal region of the conveyor belt-associated protein GldJ functions as a molecular switch which is capable of reversing the rotational direction of T9SS. Through the coordinated actions of the T9SS stator units (akin to a driving motor), the GldK ring (the gear that converts rotational energy into linear movement), and GldJ, this machinery forms a smart conveyor belt system reminiscent of flexible or cognitive mechanical conveyors. Such advanced conveyors can alter their direction to adapt to shifting demands. Here, we show that the bacterial T9SS similarly adjusts its rotational bias based on feedback from the conveyor belt-associated protein GldJ. This dual-role feedback mechanism underscores an evolved, controllable biological snowmobile, offering new avenues for studying how bacteria fine-tune motility in dynamic environments.

Microbiology↗
DOE OSTI2026

Perspective on “Active Brownian particles moving in a random Lorentz gas”

Self-propelled active matter can exhibit vastly different behavior than systems with purely Brownian motion. In Eur. Phys. J. E 40, 23 (2017), Zeitz, Wolf, and Stark compared an active matter particle with a Brownian particle moving in a random obstacle array. They showed that near the obstacle percolation density, both Brownian and active particles exhibit the same subdiffusive behavior, but the active particle reaches a steady state more rapidly. They also found that for high activity, the active particle has a lower effective diffusion than the Brownian particle due to the increased self-trapping effect generated by the activity. This result opens new directions for the study of active matter in disordered media, including bacteria in porous media, active colloids on quenched disorder, and active particles in crowded environments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Generalizable coordination of large multiscale workflows: challenges and learnings at scale

The advancement of machine learning techniques and the heterogeneous architectures of most current supercomputers are propelling the demand for large multiscale simulations that can automatically and autonomously couple diverse components and map them to relevant resources to solve complex problems at multiple scales. Nevertheless, despite the recent progress in workflow technologies, current capabilities are limited to coupling two scales. In the first-ever demonstration of using three scales of resolution, we present a scalable and generalizable framework that couples pairs of models using machine learning and in situ feedback. We expand upon the massively parallel Multiscale Machine-Learned Modeling Infrastructure (MuMMI), a recent, award-winning workflow, and generalize the framework beyond its original design. We discuss the challenges and learnings in executing a massive multiscale simulation campaign that utilized over 600,000 node hours on Summit and achieved more than 98% GPU occupancy for more than 83% of the time. We present innovations to enable several orders of magnitude scaling, including simultaneously coordinating 24,000 jobs, and managing several TBs of new data per day and over a billion files in total. Finally, we describe the generalizability of our framework and, with an upcoming open-source release, discuss how the presented framework may be used for new applications.

Bhatia, Harsh↗
DOE OSTI2020

The Plant Microbiome: From Ecology to Reductionism and Beyond

Methodological advances over the past two decades have propelled plant microbiome research, allowing the field to comprehensively test ideas proposed over a century ago and generate many new hypotheses. Studying the distribution of microbial taxa and genes across plant habitats has revealed the importance of various ecological and evolutionary forces shaping plant microbiota. In particular, selection imposed by plant habitats strongly shapes the diversity and composition of microbiota and leads to microbial adaptation associated with navigating the plant immune system and utilizing plant-derived resources. Reductionist approaches have demonstrated that the interaction between plant immunity and the plant microbiome is, in fact, bidirectional and that plants, microbiota, and the environment shape a complex chemical dialogue that collectively orchestrates the plantmicrobiome. Finally, the next stage in plant microbiome research will require the integration of ecological and reductionist approaches to establish a general understanding of the assembly and function in both natural and managed environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Molten Salt Assisted Low-Temperature Electro-Catalytic Graphitization of Coal Chars

A great effort has been centered around developing clean energy technologies (energy storage devices) to curtail burning fossil fuels' deleterious environmental effects. Rechargeable batteries [lithium-ion batteries (LIBs)] are among the most invested and investigated storage devices showing potential to transform fossil fuel-powered mobility to next-generation safe electromobility. However, LIBs powered electric vehicles (EV) are expensive due to the high-cost graphite anode associated with LIBs. Herein, the synthesis of low-cost, highly crystalline nano-graphite with a tunable microstructural architecture has been demonstrated via molten salt assisted low-temperature electro-catalytic graphitization of coal chars, traditionally non-graphitizable carbon. Thus, graphite derived from coal chars exhibited nanoflake architecture and delivered high reversible capacity, stable long cycle life, and excellent electrochemical performance under fast charging/discharging conditions (5C, ~12 min charge/discharge time). This finding paves the way to manufacture cost-effective high-energy-density batteries using as-synthesized graphite from readily available coal sources that could propel the EVs to the next level.

25 ENERGY STORAGE↗
DOE OSTI2021

Dynamics of filaments during the edge-localized mode crash on NSTX

Edge localized modes (ELMs) are routinely observed in H-mode plasma regimes of the National Spherical Torus Experiment (NSTX). Due to the explosive nature of the instability, only diagnostics with high temporal and spatial resolution could provide a detailed insight into the dynamics associated with the ELMs. Gas-puff imaging (GPI) at NSTX provides 2D measurements of the magnetic field aligned fluctuations (e.g. ELM filaments) in the scrape-off layer and the at the plasma edge with 2.5 us temporal and 10 mm optical resolution.A novel analysis technique was developed to estimate the frame-by-frame velocities and the spatial parameters of the dominant structures associated with the ELMs. The analysis was applied to single ELM events to characterize the ELM crash dynamics, and then extended to a database of 169 ELM events.Statistical analysis was performed in order to find the characterizing dynamics of the ELM crash. The results show that on average an ELM crash consists of a filament with a circular cross-section which is propelled outwards with a characterizing peak radial velocity of ~3.3 km/s. The radial velocity was found to be linearly dependent on the distance of the filament from the separatrix, which has never been seen before. The ELM filament is characterized by propagation in the ion-diamagnetic direction poloidally with a peak velocity of 11.4 km/s. The ELM crash lasts for approximately 100us until the radial propulsion settles back to the pre-ELM level. The experimental findings were compared with analytical theory. Two possible mechanisms were identified for explaining the observations: the curvature interchange model and the current-filament interaction model.

correlation↗
DOE OSTI2024

Digital Twin for Chemical Science (DTCS) v0.01

Directly visualizing the trajectories of chemistry can unravel novel insights into the behavior of catalysts, gas phase reactions, photo-induced dynamics, and building blocks for quantum information processing. The ability of explicitly identifying, tracking, and tagging the exchange of matter, hence the annihilation and creation of new chemical species, can be best realized through a close coupling of theory and experiment. While the synchrotron-based characterization facilities propelled rapidly in its hardware, providing higher brightness, better resolution, and more precision, the software infrastructure is lagging. We developed DTCS (Digital Twin for Chemical Science) v.01, a central platform that faithfully mimics advanced instrumentations in Scientific User Facilities, by solving a variety of technical challenges in data acquisition, analysis, and model-driven interpretation. Rooted in physics and accelerated by AI, we validated this concept by direct comparison with precise experimental X-ray Photoelectron Spectroscopy (XPS) observations using a ubiquitous metal-water interfacial scenario, i.e., Ag/H2O as our main narrative. The DTCS v.01 input mirrors how the bench chemists work, with the output directly linked to the end station computer, thereby providing a user-friendly, knowledge-driven, and accessible user experience with mechanistic insights standardized in a way that are ready to be published, versioned, and transferred flexibly.

Qian, Jin↗
DOE OSTI2024

An emerging multi-omic understanding of the genetics of opioid addiction

Opioid misuse, addiction, and associated overdose deaths remain global public health crises. Despite the tremendous need for pharmacological treatments, current options are limited in number, use, and effectiveness. Fundamental leaps forward in our understanding of the biology driving opioid addiction are needed to guide development of more effective medication-assisted therapies. This Review focuses on the omics-identified biological features associated with opioid addiction. Recent GWAS have begun to identify robust genetic associations, including variants in OPRM1, FURIN, and the gene cluster SCAI/PPP6C/RABEPK. An increasing number of omics studies of postmortem human brain tissue examining biological features (e.g., histone modification and gene expression) across different brain regions have identified broad gene dysregulation associated with overdose death among opioid misusers. Drawn together by meta-analysis and multi-omic systems biology, and informed by model organism studies, key biological pathways enriched for opioid addiction–associated genes are emerging, which include specific receptors (e.g., GABAB receptors, GPCR, and Trk) linked to signaling pathways (e.g., Trk, ERK/MAPK, orexin) that are associated with synaptic plasticity and neuronal signaling. Studies leveraging the agnostic discovery power of omics and placing it within the context of functional neurobiology will propel us toward much-needed, field-changing breakthroughs, including identification of actionable targets for drug development to treat this devastating brain disease.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Idealized Large-Eddy Simulations of Stratocumulus Advecting over Cold Water. Part I: Boundary Layer Decoupling

Abstract We explore the decoupling physics of a stratocumulus-topped boundary layer (STBL) moving over cooler water, a situation mimicking warm-air advection (WADV). We simulate an initially well-mixed STBL over a doubly periodic domain with the sea surface temperature decreasing linearly over time using the System for Atmospheric Modeling large-eddy model. Due to the surface cooling, the STBL becomes increasingly stably stratified, manifested as a near-surface temperature inversion topped by a well-mixed cloud-containing layer. Unlike the stably stratified STBL in cold-air advection (CADV) that is characterized by cumulus coupling, the stratocumulus deck in the WADV is unambiguously decoupled from the sea surface, manifested as weakly negative buoyancy flux throughout the subcloud layer. Without the influxes of buoyancy from the surface, the convective circulation in the well-mixed cloud-containing layer is driven by cloud-top radiative cooling. In such a regime, the downdrafts propel the circulation, in contrast to that in CADV regime for which the cumulus updrafts play a more determinant role. Such a contrast in convection regime explains the difference in many aspects of the STBLs including the entrainment rate, cloud homogeneity, vertical exchanges of heat and moisture, and lifetime of the stratocumulus deck, with the last being subject to a more thorough investigation in Part II. Finally, we investigate under what conditions a secondary stratus near the surface (or fog) can form in the WADV. We found that weaker subsidence favors the formation of fog whereas a more rapid surface cooling rate does not. Significant Statement The low-lying blanketlike clouds, called stratocumulus (Sc), reflect much incoming sunlight, substantially modulating Earth’s temperature. While much is known about how the Sc evolves when it moves over warmer water, few studies examine the opposite situation of Sc moving over colder water. We used a high-resolution numerical model to simulate such a case. When moving over cold water, the Sc becomes unambiguously decoupled from the water surface, distinctive from its warm counterpart in which the Sc interacts with the water surface via intermittent cauliflower-like clouds called cumulus clouds. Such decoupling influences many aspects of the Sc–sea surface system, which combine to alter the ability of the Sc to reflect sunlight, thereby influencing the climate. This work laid the foundation for future work that quantifies the contribution of such a decoupled Sc regime to Earth’s radiative budget and climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

An HPC benchmark survey and taxonomy for characterization

The field of High-Performance Computing (HPC) is defined by providing computing devices with highest performance for a variety of demanding scientific users. The tight co-design relationship between HPC providers and users propels the field forward, paired with technological improvements, achieving continuously higher performance and resource utilization. A key device for system architects, architecture researchers, and scientific users are benchmarks, allowing for well-defined assessment of hardware, software, and algorithms. Many benchmarks exist in the community, from individual niche benchmarks testing specific features, to large-scale benchmark suites for whole procurements. We survey the available HPC benchmarks, summarizing them in table form with key details and concise categorization, also through an interactive website. For categorization, we present a benchmark taxonomy for well-defined characterization of benchmarks.

Benchmarking↗
DOE OSTI2021

Progressive transfer learning for low-frequency data prediction in full waveform inversion

To effectively overcome the cycle-skipping issue in full waveform inversion (FWI), we developed a deep neural network (DNN) approach to predict the absent low-frequency components by exploiting the hidden physical relation connecting the low- and the high-frequency data. To efficiently solve this challenging nonlinear regression problem, two novel strategies were proposed to design the DNN architecture and to optimize the learning process: (1) dual data feed structure; (2) progressive transfer learning. With the dual data feed structure, not only the high-frequency data, but also the corresponding beat tone data are fed into the DNN to relieve the burden of feature extraction. The second strategy, progressive transfer learning, enables us to train the DNN using a single evolving training dataset. Within the framework of the progressive transfer learning, the training dataset continuously evolves in an iterative manner by gradually retrieving the subsurface information through the physics-based inversion module, progressively enhancing the prediction accuracy of the DNN and propelling the inversion process out of the local minima. Here, the synthetic numerical experiments suggest that, without any a priori geological information, the low-frequency data predicted by the progressive transfer learning are sufficiently accurate for an FWI engine to produce reliable subsurface velocity models free of cycle-skipping artifacts.

02 PETROLEUM↗
DOE OSTI2023

Co-Harvest and Anaerobic Co-Storage of Corn Grain and Stover as Biomass Feedstocks

This research investigated the utility of co-harvesting and anaerobic co-storage of corn grain and stover to positively influence their physical and chemical characteristics as a biomass feedstock. Corn grain and stover were harvested in 2019 and 2020 with a self-propelled forage harvester. Stover yield, moisture content, and composition were altered by the harvest date, stubble height, and header configuration. Harvest date had the utility of varying the stover moisture content (p < 0.001) from 42.3% to 53.5% (w.b.) and 43.1% to 53.9% (w.b.) for the 2019 and 2020 harvest years, respectively. Stubble height was also utilized to vary stover moisture content. A negative linear relationship was established between stubble height and stover moisture content for the early (R2 = 0.76) and late harvest (R2 = 0.91) dates for both years. Stover yield also showed a negative linear relationship (R2 = 0.76) with stubble height over both years. Regardless of the stubble height, the row-crop header collected more stover (p < 0.001) than the ear-snapper header. In 2020, harvested stover ranged from 5.0 to 10.5 Mg ha-1, with ha-1 representing 41% to 85% of the total available stover. In both years, stover ash content was less than 64 g kg-1. Material stored in pilot-scale silos (19 L) was well conserved during anaerobic storage, with average DM losses of 4.8% and 3.4% in 2019 and 2020, respectively. Grain moisture content averaged 23.6% (w.b.) at harvest, and 31.0% (w.b.) after storage as moisture migrated from the moist stover to the drier grain. Harvesting whole-plant corn with a forage harvester had the unwanted effect of reducing the particle size of the grain fraction, which would complicate downstream utilization. However, reducing the harvester cutterhead speed increased the fraction of intact kernels from 47% to 85% by mass. The studied system was a viable alternative to conventional corn grain and stover systems for producing feedstocks for biochemical conversion.

09 BIOMASS FUELS↗
DOE OSTI2022

Neutronics Modeling of the pulsed plasma rocket reactor using rattlesnake

In the pulsed plasma rocket (PPR) reactor, neutron induced fission processes are utilized to implement a series of pulsed micro-explosions of very high power and eject plasma as a propellant. More specifically, projectiles (bullets) composed of moderated uranium are sent through the chamber of an unmoderated uranium barrel. By inducing rapid fission within the bullets, a plasma can be generated with appropriate delivery of neutrons. This study aims to assess the neutronics performance of the PPR reactor during normal operations using the MOOSE-based Rattlesnake code through the evaluation of the impact of the movement of the fuel bullet and the rotation of control drums on the criticality of the system. The Monte Carlo (MC) code Serpent 2 was employed to generate material-based cross sections for use in Rattlesnake and the reference neutronics solution. Cubit was used to generate the mesh for the Rattlesnake model. Parametric studies were conducted to evaluate the best approaches for cross section and mesh generation to ensure accurate results from Rattlesnake. As part of the verification process, the eigenvalue results of the system at various fuel bullet positions were obtained using Rattlesnake and compared with the reference solutions. The acceptable differences show that the Rattlesnake model with appropriate cross section and mesh generation procedure is a sufficiently accurate approximation of the continuous energy (CE) MC model for micro-sized reactors like the PPR reactor. Next, the impact of the rotation of the control drums on the system criticality was evaluated using the verified model. It was shown that the high-fidelity simulation using the deterministic code Rattlesnake can produce sufficiently accurate results for the evaluation of the reactor's neutronics performance in different phases of the normal operation with acceptable computational cost.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Frequency-bin photonic quantum information

Discrete frequency modes, or bins, present a blend of opportunities and challenges for photonic quantum information processing. Frequency-bin-encoded photons are readily generated by integrated quantum light sources, naturally high-dimensional, stable in optical fiber, and massively parallelizable in a single spatial mode. Yet quantum operations on frequency-bin states require coherent and controllable multifrequency interference, making them significantly more challenging to manipulate than more traditional spatial degrees of freedom. In this mini-review, we describe recent developments that have transformed these challenges and propelled frequency bins forward. Focusing on sources, manipulation schemes, and detection approaches, we introduce the basics of frequency-bin encoding, summarize the state of the art, and speculate on the field’s next phases. Given the combined progress in integrated photonics, high-fidelity quantum gates, and proof-of-principle demonstrations, frequency-bin quantum information is poised to emerge from the lab and leave its mark on practical quantum information processing—particularly in networking where frequency bins offer unique tools for multiplexing, interconnects, and high-dimensional communications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Control of multi-agent systems: Results, open problems, and applications

The purpose of this review article is to present some recent results on the modeling and control of large systems of agents. We focus on particular applications where the agents are capable of independent actions instead of simply reacting to external forces. In the literature, such agents were referred to as autonomous, intelligent, self-propelled, greedy, and others. The main applications we have in mind are social systems (as opinion dynamics), pedestrians’ movements (also called crowd dynamics), animal groups, and vehicular traffic. We note that the last three examples include physical constraints; however, the agents are able to inject energy into the system, thus preventing the typical conservation of momentum and energy. In addition, the control problems posed by such systems are new and require innovative methods. We illustrate some ideas developed recently, including the use of sparse controls, limiting the total variation of controls, and defining new control problems for measures. After reviewing various approaches, we discuss some future research directions of potential interest. The latter encompasses both new types of equations and new types of limiting procedures to connect several scales at which a system can be represented. We conclude by illustrating a recent real-life experiment using autonomous vehicles on an open highway to smooth traffic waves. This opens the door to a new era of interventions to control real-time multi-agent systems and to increase the societal impact of such interventions guided by control research.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

The structure of fly Teneurin-m reveals an asymmetric self-assembly that allows expansion into zippers

Teneurins are conserved cell adhesion molecules essential for embryogenesis and neural development in animals. Key to teneurin function is the ability of its extracellular region to form homophilic interactions in cis and/or in trans. However, our molecular understanding of teneurin homophilic interaction remains largely incomplete. Here, we showed that an extracellular fragment of Teneurin-m, the major teneurin homolog in flies, behaves as a homodimer in solution. The structure of Teneurin-m revealed that the transthyretin-related domain from one protomer and the β-propeller domain from the other mediates Teneurin-m self-association, which is abolished by point mutation of conserved residues. Strikingly, this architecture generates an asymmetric oligomerization interface that enables expansion of Teneurin-m into long zipper arrays reminiscent of protocadherins. An alternatively spliced site that exists only in vertebrates and regulates homophilic interaction in mammalian teneurins overlaps with the fly Teneurin-m self-association interface. Our work provides a molecular understanding of teneurin homophilic interaction and sheds light on its role in teneurin function throughout evolution.

59 BASIC BIOLOGICAL SCIENCES↗