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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,621 records · Page 90

Influence of surface charge on the transport characteristics of nanowire-field effect transistors in liquid environments

One dimensional nanowire field effect transistors (NW-FETs) are a promising platform for sensor applications. The transport characteristics of NW-FETs are strongly modified in liquid environment due to the charging of surface functional groups accompanied with protonation or deprotonation. In order to investigate the influence of surface charges and ionic concentrations on the transport characteristics of Schottky-barrier NW-FETs, we have combined the modified Poisson-Boltzmann theory with the Landauer-Büttiker transport formalism. For a typical device, the model is able to capture the reduction of the sensitivity of NW-FETs in ionic solutions due to the screening from counter ions as well as a local gating from surface functional groups. Our approach allows to model, to investigate, and to optimize realistic Schottky-barrier NW-FET devices in liquid environment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Electron mean-free-path filtering in Dirac material for improved thermoelectric performance

Recent advancements in thermoelectric materials have largely benefited from various approaches, including band engineering and defect optimization, among which the nanostructuring technique presents a promising way to improve the thermoelectric figure of merit ( zT ) by means of reducing the characteristic length of the nanostructure, which relies on the belief that phonons’ mean free paths (MFPs) are typically much longer than electrons’. Pushing the nanostructure sizes down to the length scale dictated by electron MFPs, however, has hitherto been overlooked as it inevitably sacrifices electrical conduction. Here we report through ab initio simulations that Dirac material can overcome this limitation. The monotonically decreasing trend of the electron MFP allows filtering of long-MFP electrons that are detrimental to the Seebeck coefficient, leading to a dramatically enhanced power factor. Using SnTe as a material platform, we uncover this MFP filtering effect as arising from its unique nonparabolic Dirac band dispersion. Room-temperature zT can be enhanced by nearly a factor of 3 if one designs nanostructures with grain sizes of ∼10 nm. Our work broadens the scope of the nanostructuring approach for improving the thermoelectric performance, especially for materials with topologically nontrivial electronic dynamics.

42 ENGINEERING↗

On The Theory of Speculative Checkpointing: Time and Energy Considerations

Collective checkpoint-rollback is the most popular approach to dealing with fail-stop errors on high-performance computing (HPC) platforms. Prior work has focused on choosing checkpoint intervals that minimize the total cost of checkpoint-rollback. In this paper, we introduce the notion of speculative checkpointing, where we probabilistically skip some checkpoints. Careful choice of check- points to be taken or skipped has the potential to further reduce the total checkpoint-rollback overhead. We mathematically formulate the overall checkpoint-rollback cost in the presence of speculation. We consider the choice of speculation being a fixed probability or a probability distribution. We formulate two criteria to be minimized: total execution time and approximate total energy. We derive the criteria for beneficial speculative checkpointing for exponential and arbitrary failure distributions. Further, we analyze the joint optimization of energy and time to mathematically express the trade-offs.

Subasi, Omer↗

Introduction to an MCGIDI Mini-App and Performance Comparisons with XSBench

In high-performance Monte Carlo (MC) radiation transport codes, cross section lookups often account for the majority of computational expens. In response to this observation, a number of nuclear data mini-apps have been developed to profile and optimize the lookup process. A review of these mini-apps can be found in Ref. In contrast to a fully fledged MC code, nuclear data mini-apps do not feature particle tracking; instead, the cross section lookup process is considered in isolation, a simplification that allows for easier implementation and evaluation of various lookup schemes and techniques. GIDI+, as described on its public repository1, is ...a collection of C++ libraries for accessing evaluated and processed nuclear data stored in the Generalized Nuclear Database Structure (GNDS). In addition to reading GNDS files, GIDI+ has functions to sum and collapse multi-group data as needed by deterministic transport codes, and to sample GNDS data as needed by Monte Carlo transport codes. Certain modes of Mercury, a LLNL-developed MC radiation transport code, utilize GIDI+ for cross section lookups. Specifically, Mercury uses the MCGIDI library contained within GIDI+ to perform lookups on GPUs. A mini-app exercising MCGIDI’s cross section lookup capabilities would prove useful for optimization, which in turn could improve the performance of client codes such as Mercury. Such a mini-app could also be used to assess the performance of MCGIDI compared to other nuclear data mini-apps. In this document, we introduce a nuclear data mini-app built with the MCGIDI library. The MCGIDI mini-app (MCGIDI-MA) was developed to closely resemble the methodology present in XSBench, a nuclear data mini-app developed at Argonne National Laboratory. The remainder of this section provides an overview on XSBench. Section 2 describes MCGIDI-MA and its usage. Section 3 contains performance results of MCGIDI-MA on LLNL’s Lassen and Quartz compute platforms, as well as comparisons to XSBench performance where appropriate. In Section 4, we present a summary of our findings.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Low-Cost Bio-Based Phase Change Materials as an Energy Storage Medium in Building Envelopes

A promising approach to increasing the energy efficiency of buildings is the implementation of phase change material (PCM) in building envelope systems. Several studies have reported the energy saving potential of PCM in building envelopes. However, wide application of PCMs in building applications has been inhibited, in part, by their high cost. This article describes a novel paraffin product made of naturally occurring fatty acids/glycerides trapped into high density polyethylene (HDPE) pellets and its performance in a building envelope application, with the ultimate goal of commercializing a low-cost PCM platform. The low-cost PCM pellets were mixed with cellulose insulation, installed in external walls and field-tested under natural weatherization conditions for a period of several months. In addition, several PCM samples and PCM-cellulose samples were prepared under controlled conditions for laboratory-scale testing. The laboratory tests were performed to determine the phase change properties of PCM-enhanced cellulose insulation both at microscopic and macroscopic levels. This article presents the data and analysis from the exterior test wall and the laboratory-scale test data. PCM behavior is influenced by the weather and interior conditions, PCM phase change temperature and PCM distribution within the wall cavity, among other factors. Under optimal conditions, the field data showed up to 20% reduction in weekly heat transfer through an external wall due to the PCM compared to cellulose-only insulation.

low-cost PCM↗

High-energy ion beams generated with high efficiency using laser-driven 3D microstructures

Laser-driven ion acceleration in plasma is being proposed as a source of ion beams with a high peak current that can be useful in many fields of science and medicine. Using this method, high proton energies have been achieved by increasing the laser power and by using ultrathin (≤ 200 nm) foils. However, this approach is limited by survivability of the nanotargets to laser prepulses and by difficulty in controlling the plasma acceleration properties. Here, we introduce a new target platform using two-photon polymerization, 3D laser-printed “clone” microstructures with average densities lower than solid that are relatively insensitive to the laser prepulse. Two types of microstructured targets consisting of either a multilayered log-pile or a stochastic arrangement of one micron diameter wires are used. Both demonstrate a higher energy and higher yield proton acceleration compared to thin solid-density foil targets by the robust target normal sheath acceleration (TNSA) mechanism. We find that when such 10–20 μm thick structures are irradiated with a petawatt laser, protons with energies up to 110 MeV and a laser-to-proton conversion efficiency of ~ 10% are obtained. Our work suggests that such microstructures optimized for 60–200 MeV compact proton accelerators are promising for future radiotherapy and other applications.

Physics - Plasma physics↗

Z-Target Radiography Postprocessing With A Deep Convolution Neural Network

Analyzing X-ray radiographs is crucial for understanding target behavior in Inertial Confinement Fusion (ICF) and High Energy Density (HED) platforms. However, the density of Magneto Raleigh Taylor (MRT) bands and limitations of target materials often obscure relevant spike growth and density information. To address this issue, machine learning postprocessing techniques can be applied to remove darkened regions in radiography images. In this study, a novel method is presented for removing MRT darkened regions from z-target radiographs using a convolutional neural network (CNN). The CNN, consisting of six layers, treats the darkened regions as noise and employs a mixed loss function and end-to-end frameworks to suppress them while preserving sharpness. The six-layer architecture is designed to effectively learn features when provided with a larger volume of learning space. Each layer is optimized using a mixed loss function that combines a standard loss pixel approach with a multi-scaled structural similarity index loss, which considers luminance, contrast, and structure in local neighborhoods. This approach is particularly beneficial for capturing the stochastic structure of MRT limbs. Due to the limited availability of experimental data, training is conducted using synthetic target radiography from 3D Alegra simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Towards Cooperative Control of Humanoid Robots for Handling High-Consequence Materials in Gloveboxes - 17291

In this paper, we describe our ongoing work with NASA's Valkyrie humanoid robot and present preliminary results on cooperative control of Valkyrie's hands for performing dexterous manipulation tasks inside gloveboxes commonly found in many nuclear facilities. First, we discuss our human-supervised robot control framework which is based on optimization-based whole-body motion and manipulation controllers. A key aspect of this approach is perception based grasping. We develop a grasping control module for realizing the grasps corresponding to sample tasks such as power, ball, key, pinch, and open palm grasps and their variations. Next, we introduce the notion of motion template library in order to develop generalizable robot grasping and manipulation. Motion template library stores the constraint setting information for the constrained motion planning methods and a framework which can implement the motion template library on different types of robots for accomplishing similar tasks. Motion templates are defined only based on the task requirements. As a result, they can be easily ported to different robot platforms. Lastly, we discuss our multi-modal interfaces designs which include a visual display for improved situational awareness as well as a tactile glove for robot hand control and feedback. Our goal is for the person tele-operating the Valkyrie robot to have better sensing and control than what he or she would have if actually standing at the glovebox doing the work. This improved sensing is comprised of the ability to 'see through' the robot's arms and hands in the gloves and to have an improved sense of touch. The paper concludes with a discussion of our validation strategy. Our success metrics are derived from the completion of a relatively complex experiment to be performed in the glovebox. We evaluate various realistic experiments and use them for task validation and demonstration with Valkyrie. We use speed, time of completion, accuracy, repeatability and reliability rates as success metrics by designing replicable experiments. (authors)

42 ENGINEERING↗

FLASSH 1.0: Thermal scattering law evaluation and cross section generation for reactor physics applications

The Full Law Analysis Scattering System Hub (FLASSH) is a modern, advanced code which evaluates the thermal scattering law (TSL) along with accompanying cross sections. FLASSH features generalized methods which accommodate any material structure. Historical approximations including the incoherent and cubic approximations have been removed. Instead, the latest release of FLASSH features advanced physics options including distinct corrections (1-phonon contributions) and non-cubic formulations. The non-cubic elastic and inelastic contributions are necessary to accurately evaluate 1-phonon contributions. Both non-cubic and 1-phonon calculations require high-density sampling of the various scattering directions. Optimization and parallelization of these routines were therefore necessary to produce results in a reasonable timeframe. With these notable improvements to the generalized TSL, FLASSH 1.0 meets benchmark requirements, demonstrating noticeable agreement with experiment for both TSLs and the resulting integrated cross sections. Additional features including a graphical user interface (GUI), plotting diagnostics, and formatted output options including ACE files allow users to complete a TSL evaluation with minimal input and maximum flexibility. The user GUI creates input files for FLASSH, reducing user error and also providing built-in error checks. Autofill options and suggested input values help make TSL evaluation accessible to novice users. The FLASSH code is compiled to run on both Windows and Linux platforms with automatic parallelization. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A Simple and Versatile 2-Dimensional Platform to Study Plant Germination and Growth under Controlled Humidity

We describe a simple, inexpensive, but remarkably versatile and controlled growth environment for the observation of plant germination and seedling root growth on a flat, horizontal surface over periods of weeks. The setup provides to each plant a controlled humidity (between 56% and 91% RH), and contact with both nutrients and atmosphere. The flat and horizontal geometry of the surface supporting the roots eliminates the gravitropic bias on their development and facilitates the imaging of the entire root system. Experiments can be setup under sterile conditions and then transferred to a non-sterile environment. The system can be assembled in 1-2 minutes, costs approximately 8.78$\$$ per plant, is almost entirely reusable (0.43$\$$ per experiment in disposables), and is easily scalable to a variety of plants. We demonstrate the performance of the system by germinating, growing, and imaging Wheat (Triticum aestivum), Corn (Zea mays), and Wisconsin Fast Plants (Brassica rapa). Germination rates were close to those expected for optimal conditions.

59 BASIC BIOLOGICAL SCIENCES↗

Discovery of Self-Assembling π-Conjugated Peptides by Active Learning-Directed Coarse-Grained Molecular Simulation

Electronically active organic molecules have demonstrated great promise as novel soft materials for energy harvesting and transport. Self-assembled nanoaggregates formed from π-conjugated oligopeptides composed of an aromatic core flanked by oligopeptide wings offer emergent optoelectronic properties within a water-soluble and biocompatible substrate. Nanoaggregate properties can be controlled by tuning core chemistry and peptide composition, but the sequence–structure–function relations remain poorly characterized. Here, we employ coarse-grained molecular dynamics simulations within an active learning protocol employing deep representational learning and Bayesian optimization to efficiently identify molecules capable of assembling pseudo-1D nanoaggregates with good stacking of the electronically active π-cores. We consider the DXXX-OPV3-XXXD oligopeptide family, where D is an Asp residue and OPV3 is an oligophenylenevinylene oligomer (1,4-distyrylbenzene), to identify the top performing XXX tripeptides within all 20 3 = 8000 possible sequences. By direct simulation of only 2.3% of this space, we identify molecules predicted to exhibit superior assembly relative to those reported in prior work. Spectral clustering of the top candidates reveals new design rules governing assembly. This work establishes new understanding of DXXX-OPV3-XXXD assembly, identifies promising new candidates for experimental testing, and presents a computational design platform that can be generically extended to other peptide-based and peptide-like systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nanoscale Control of Intrinsic Magnetic Topological Insulator MnBi 2 Te 4 Using Molecular Beam Epitaxy: Implications for Defect Control

Intrinsic magnetic topological insulators have emerged as a promising platform to study the interplay between the topological surface states and ferromagnetism. This unique interplay can give rise to a variety of exotic quantum phenomena, including the quantum anomalous Hall effect and axion insulating states. Here, in this study, utilizing molecular beam epitaxy (MBE), we present a comprehensive study of the growth of MnBi 2 Te 4 thin films on Si (111), epitaxial graphene, and highly ordered pyrolytic graphite substrates. By combining a suite of in situ characterization techniques, we obtain critical insights into the nanoscale control of MnBi 2 Te 4 epitaxial growth. First, we extract the free energy landscape for the epitaxial relationship as a function of the in-plane angular distribution. Then, by employing an optimized layer-by-layer growth, we determine the chemical potential and Dirac point of the thin film at different thicknesses and how this quantity is manifested by the dopant compensation from different antisite defects. Overall, these results establish a foundation for understanding the growth kinetics of MnBi 2 Te 4 and pave the way for future applications of MBE-grown thin films in emerging topological quantum materials.

36 MATERIALS SCIENCE↗

Potential up-scaling of inkjet-printed devices for logical circuits in flexible electronics

Inkjet Technology is often mis-believed to be a deposition/patterning technology which is not meant for high fabrication throughput in the field of printed and flexible electronics. In this work, we report on the 1) printing, 2) fabrication yield and 3) characterization of exemplary simple devices e.g. capacitors, organic transistors etc. which are the basic building blocks for logical circuits. For this purpose, printing is performed first with a Proof of concept Inkjet printing system Dimatix Material Printer 2831 (DMP 2831) using 10 pL small print-heads and then with Dimatix Material Printer 3000 (DMP 3000) using 35 pL industrial print-heads (from Fujifilm Dimatix). Printing at DMP 3000 using industrial print-heads (in Sheet-to-sheet) paves the path towards industrialization which can be defined by printing in Roll-to-Roll format using industrial print-heads. This pavement can be termed as 'Bridging Platform'. This transfer to 'Bridging Platform' from 10 pL small print-heads to 35 pL industrial print-heads help the inkjet-printed devices to evolve on the basis of functionality and also in form of up-scaled quantities. The high printed quantities and yield of inkjet-printed devices justify the deposition reliability and potential to print circuits. This reliability is very much desired when it comes to printing of circuits e.g. inverters, ring oscillator and any other planned complex logical circuits which require devices e.g. organic transistors which needs to get connected in different staged levels. Also, the up-scaled inkjet-printed devices are characterized and they reflect a domain under which they can work to their optimal status. This status is much wanted for predicting the real device functionality and integration of them into a planned circuit.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Control And Optimization Modular Modeling Application For Nuclear Deployment

The purpose of the COMMAND code is to provide a flexible, scalable tool for use in developing, integrating, and testing the technologies necessary for achieving autonomous operations of advanced nuclear reactors. The code enables users to efficiently implement custom simulations and experiments by combining key methods from different software modules. These modules are focused on: modeling and simulation tools, such as nuclear simulation tools used for high-fidelity modeling (e.g., Reactor Excursion and Leak Analysis Program [RELAP5-3D] and Monte Carlo N-Particle [MCNP]); machine learning and optimization tools (e.g., anomaly detection and data-driven modeling techniques); advanced control in its digital, high-performance, and supervisory control forms (e.g., proportional integral derivative (PID) control and model predictive control (MPC); and integration with hardware through industrial communication protocols. To ensure flexibility and scalability, COMMAND was designed to be both modular—the software “pieces” all inherit from generic building blocks and can be combined and connected to create complicated simulations—and high performing—designed for parallel processing, enabling simulations and experiments to take advantage of multi-core computers, servers, and nodes. The code is written in the Python programming language due to the language's popularity, active community, and open-source and cross-platform nature. Maintaining consistency with other simulation tools used within the nuclear energy community, users implement simulations and experiments through text input files, which define components, parameters, connections, etc., through lines of text. Given that COMMAND is written in Python, these input files are native Python scripts, and so use the standard Python structure and formatting. This also enables users to take advantage of Python's extensive package library to develop custom capabilities for their specific use cases.

Faber, Jacob [Idaho National Laboratory (INL), Ida↗

Recent Progress in Electrochemical Upgrading of Bio-Oil Model Compounds and Bio-Oils to Renewable Fuels and Platform Chemicals

Sustainable production of renewable carbon-based fuels and chemicals remains a necessary but immense challenge in the fight against climate change. Bio-oil derived from lignocellulosic biomass requires energy-intense upgrading to produce usable fuels or chemicals. Traditional upgrading methods such as hydrodeoxygenation (HDO) require high temperatures (200–400 °C) and 200 bar of external hydrogen. Electrochemical hydrogenation (ECH), on the other hand, operates at low temperatures (<80 °C), ambient pressure, and does not require an external hydrogen source. These environmental and economically favorable conditions make ECH a promising alternative to conventional thermochemical upgrading processes. ECH combines renewable electricity with biomass conversion and harnesses intermediately generated electricity to produce drop-in biofuels. This review aims to summarize recent studies on bio-oil upgrading using ECH focusing on the development of novel catalytic materials and factors impacting ECH efficiency and products. Here, electrode design, reaction temperature, applied overpotential, and electrolytes are analyzed for their impacts on overall ECH performance. We find that through careful reaction optimization and electrode design, ECH reactions can be tailored to be efficient and selective for the production of renewable fuels and chemicals. Preliminary economic and environmental assessments have shown that ECH can be viable alternative to convention upgrading technologies with the potential to reduce CO2 emissions by 3 times compared to thermochemical upgrading. While the field of electrochemical upgrading of bio-oil has additional challenges before commercialization, this review finds ECH a promising avenue to produce renewable carbon-based drop-in biofuels. Finally, based on the analyses presented in this review, directions for future research areas and optimization are suggested.

09 BIOMASS FUELS↗

Tailored Micromagnet Sorting Gate for Simultaneous Multiple Cell Screening in Portable Magnetophoretic Cell‐On‐Chip Platforms

Abstract Conventional magnetophoresis techniques for manipulating biocarriers and cells predominantly rely on large‐scale electromagnetic systems, which is a major obstacle to the development of portable and miniaturized cell‐on‐chip platforms. Herein, a novel magnetic engineering approach by tailoring a nanoscale notch on a disk micromagnet using two‐step optical and thermal lithography is developed. Versatile manipulations are demonstrated, such as separation and trapping, of carriers and cells by mediating changes in the magnetic domain structure and discontinuous movement of magnetic energy wells around the circumferential edge of the micromagnet caused by a locally fabricated nano‐notch in a low magnetic field system. The motion of the magnetic energy well is regulated by the configuration of the nanoscale notch and the strength and frequency of the magnetic field, accompanying the jump motion of the carriers. The proposed concepts demonstrate that multiple carriers and cells can be manipulated and sorted using optimized nanoscale multi‐notch gates for a portable magnetophoretic system. This highlights the potential for developing cost‐effective point‐of‐care testing and lab‐on‐chip systems for various single‐cell‐level diagnoses and analyses.

36 MATERIALS SCIENCE↗

Carbon Isotope Composition and the NDVI as Phenotyping Approaches for Drought Adaptation in Durum Wheat: Beyond Trait Selection

High-throughput phenotyping platforms provide valuable opportunities to investigate biomass and drought-adaptive traits. We explored the capacity of traits associated with drought adaptation such as aerial measurements of the Normalized Difference Vegetation Index (NDVI) and carbon isotope composition (δ13C) determined at the leaf level to predict genetic variation in biomass. A panel of 248 elite durum wheat accessions was grown at the Maricopa Phenotyping platform (US) under well-watered conditions until anthesis, and then irrigation was stopped and plot biomass was harvested about three weeks later. Globally, the δ13C values increased from the first to the second sampling date, in keeping with the imposition of progressive water stress. Additionally, δ13C was negatively correlated with final biomass, and the correlation increased at the second sampling, suggesting that accessions with lower water-use efficiency maintained better water status and, thus, performed better. Flowering time affected NDVI predictions of biomass, revealing the importance of developmental stage when measuring the NDVI and the effect that phenology has on its accuracy when monitoring genotypic adaptation to specific environments. The results indicate that in addition to choosing the optimal phenotypic traits, the time at which they are assessed, and avoiding a wide genotypic range in phenology is crucial.

54 ENVIRONMENTAL SCIENCES↗

Enabling Floating Offshore VAWT Design by Coupling OWENS and OpenFAST

Vertical-axis wind turbines (VAWTs) have a long history, with a wide variety of turbine archetypes that have been designed and tested since the 1970s. While few utility-scale VAWTs currently exist, the placement of the generator near the turbine base could make VAWTs advantageous over tradition horizontal-axis wind turbines for floating offshore wind applications via reduced platform costs and improved scaling potential. However, there are currently few numerical design and analysis tools available for VAWTs. One existing engineering toolset for aero-hydro-servo-elastic simulation of VAWTs is the Offshore Wind ENergy Simulator (OWENS), but its current modeling capability for floating systems is non-standard and not ideal. This article describes how OWENS has been coupled to several OpenFAST modules to update and improve modeling of floating offshore VAWTs and discusses the verification of these new capabilities and features. The results of the coupled OWENS verification test agree well with a parallel OpenFAST simulation, validating the new modeling and simulation capabilities in OWENS for floating VAWT applications. These developments will enable the design and optimization of floating offshore VAWTs in the future.

17 WIND ENERGY↗