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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Virtual Volumetric Additive Manufacturing (VirtualVAM)

Abstract Tomographic volumetric additive manufacturing (VAM) produces arbitrary 3D geometries by exposure of a rotating volume of photopolymer resin to tomographically‐patterned illumination. This enables high speed, layer‐less printing of parts from a wide range of photopolymers not amenable to layer‐by‐layer processes. Since the entire geometry is produced at once over the course of a few seconds to minutes, molecular diffusion length scales become significant to the printing process. Understanding these molecular reaction and diffusion processes is imperative for advancing VAM to a usable technology. These processes are experimentally very difficult to monitor and measure. Herein, VirtualVAM ‐ a simulation framework for modeling the tomographic VAM process, is developed and experimentally validated. VirtualVAM simulates reaction, diffusion, and heat generation processes over the course of a print with single‐voxel resolution. From a few experimentally‐determined input parameters and a set of images for projection, VirtualVAM is able to generate a large spatio‐temporal data set for any given tomographic VAM print. Using VirtualVAM, a number of experimentally‐unattainable aspects of the VAM process are investigated such as single‐voxel conversion profiles, effect of molecular oxygen, and stopping time determination. VirtualVAM also enables the optimization of exposure patterns to further improve contrast between in‐part and out‐of‐part delivered dose.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

DNA for Assembly and Charge Transport Photocatalytic Reduction of CO 2

Abstract This report demonstrates the use of DNA to spatially organize photoactive nanocrystals into well‐defined Z‐scheme architectures to facilitate CO 2 reduction to usable fuels upon solar irradiation through electron transfer. Coupling donor (Titanium Oxide, TiO 2 ) and acceptor (Cadmium Sulfide, CdS) nanocrystals with DNA yield a 5.25‐fold improvement in CO 2 reduction over simply mixing the photocatalysts in solution. In addition, it is demonstrated that electron transfer occurs over distances far greater than those achieved with polyethylene glycol spacer. Efficient Z‐scheme photocatalytic reduction of CO 2 is observed for DNA lengths of 10–80 bases, which separate the donor and acceptor nanocrystals by 3–24 nm. More significantly, an interparticle distance of 9–10 nm yields the highest conversion of CO 2 , which is found for nanocrystals spaced using either linear 30mer double strand DNA (dsDNA) or a 40mer DNA composed of both linear and hairpin DNA. When the amount of 30mer DNA linking the photocatalysts is lowered, a corresponding decrease in CO 2 reduction yields is seen, showcasing the role of DNA in mediating electron transfer. These results demonstrate the highly unique attributes of DNA as both a templating agent for precise nanoscale assembly and for enabling charge transport. This work uncovers new research directions for nanoelectronics, electrochemistry, and photocatalysis.

Ma, Ke↗
DOE OSTI2023

Proxy quality control of biomass particles using thermogravimetric analysis and Gaussian process regression models

Abstract The temperature experienced by reactants during preparation in a reactor is a key component in determining the yield and homogeneity of usable chemical products such as biomass particles. Thermocouples with sensors can be used to monitor spatial temperature gradients within reactors but these sensors are often too expensive and/or invasive. The present work proposes a strategy to identify optimal machine learning models to infer the maximum effective temperature experienced by particles during oxidative biomass torrefaction using key thermochemical combustion parameters. The maximum rate of weight loss, the corresponding temperature, and fixed carbon content on a dry‐ash‐free basis are used as literature‐based predictor variables obtained from thermogravimetric analysis. The evaluation of 24 machine‐learning models using the standard tenfold cross‐validation method suggests that the exponential Gaussian process regression (GPR) model is the most effective, followed by other GPR models. These high‐performing GPR models were also utilized to predict the effective preparation temperature distribution of reactor‐produced biomass particles under eight conditions of varying residence time and air‐to‐biomass ratio. The effective preparation temperature and residence time of individual biomass particles were then encoded into the torrefaction severity factor and used to estimate the energy yield of the reactor output as a novel quality control method. © 2023 The Authors. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.

09 BIOMASS FUELS↗
DOE OSTI2018

Electrochemical Applications of Microphase-Separated Block Copolymer Thin Films

In this work, we discuss electrochemical applications of electrode-supported thin films derived from microphase-separated block copolymers (BCPs). In contrast to conventional homopolymers used for electrode modification, BCPs afford periodic nanoscale structures (microdomains) of uniform dimensions (5-100 nm) and predictable morphologies, which can be controlled by adjusting the lengths of individual homopolymer segments. BCPs usable for electrochemical applications consist of two or more segments that form solute-permeable, redox-active or etchable microdomains and a chemically inert matrix. The resulting microdomains afford nanoscale molecular/charge transport pathways toward the underlying electrode, whereas the matrix serves as a scaffold to improve film stability in a solution. In conclusion, these polymeric thin films provide a unique means for fabricating nanowire arrays via template-based electrochemical synthesis, designing electrochemical sensors with unique selectivity, and constructing electrochemically-tunable functional materials.

36 MATERIALS SCIENCE↗
DOE OSTI2017

An efficient parallel simulation of unsteady blood flows in patient-specific pulmonary artery

Simulation of blood flows in the pulmonary artery provides some insight into certain diseases by examining the relationship between some continuum metrics, eg, the wall shear stress acting on the vascular endothelium, which responds to flow-induced mechanical forces by releasing vasodilators/constrictors. V. Kheyfets, in his previous work, studies numerically a patient-specific pulmonary circulation to show that decreasing wall shear stress is correlated with increasing pulmonary vascular impedance. We develop a scalable parallel algorithm based on domain decomposition methods to investigate an unsteady model with patient-specific pulsatile waveforms as the inlet boundary condition. The unsteady model offers tremendously more information about the dynamic behavior of the flow field, but computationally speaking, the simulation is a lot more expensive since a problem which is similar to the steady-state problem has to be solved many times, and therefore, the traditional sequential approach is not suitable anymore. We show computationally that simulations using the proposed parallel approach with up to 10 000 processor cores can be obtained with much reduced compute time. Finally, this makes the technology potentially usable for the routine study of the dynamic behavior of blood flows in the pulmonary artery, in particular, the changes of the blood flows and the wall shear stress in the spatial and temporal dimensions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

An implementation and evaluation of the MPI 3.0 one-sided communication interface

The Q1 Message Passing Interface (MPI) 3.0 standard includes a significant revision to MPI’s remote memory access (RMA) interface, which provides support for one-sided communication. MPI-3 RMA is expected to greatly enhance the usability and performance ofMPI RMA.We present the first complete implementation of MPI-3 RMA and document implementation techniques and performance optimization opportunities enabled by the new interface. Our implementation targets messaging-based networks and is publicly available in the latest release of the MPICH MPI implementation. Here using this implementation, we explore the performance impact of new MPI-3 functionality and semantics. Results indicate that the MPI-3 RMA interface provides significant advantages over the MPI-2 interface by enabling increased communication concurrency through relaxed semantics in the interface and additional routines that provide new window types, synchronization modes, and atomic operations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Preparing NERSC users for Cori, a Cray XC40 system with Intel many integrated cores

The newest NERSC supercomputer Cori is a Cray XC40 system consisting of 2,388 Intel Xeon Haswell nodes and 9,688 Intel Xeon-Phi “Knights Landing” (KNL) nodes. Compared to the Xeon-based clusters NERSC users are familiar with, optimal performance on Cori requires consideration of KNL mode settings; process, thread, and memory affinity; fine-grain parallelization; vectorization; and use of the high-bandwidth MCDRAM memory. This paper describes our efforts preparing NERSC users for KNL through the NERSC Exascale Science Application Program, Web documentation, and user training. We discuss how we configured the Cori system for usability and productivity, addressing programming concerns, batch system configurations, and default KNL cluster and memory modes. Here, system usage data, job completion analysis, programming and running jobs issues, and a few successful user stories on KNL are presented.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Application-level regression testing framework using Jenkins

Monitoring and testing for regression of large-scale systems such as the NCSA's Blue Waters supercomputer are challenging tasks. In this paper, we describe the solution we came up with to perform those tasks. The goal was to find an automated solution for running user-level regression tests to evaluate system usability and performance. Jenkins, an automation server software, was chosen for its versatility, large user base, and multitude of plugins including collecting data and plotting test results over time. We also describe our Jenkins deployment to launch and monitor jobs on remote HPC system, perform authentication with one-time password, and integrate with our LDAP server for its authorization. We show some use cases and describe our best practices for successfully using Jenkins as a user-level system-wide regression testing and monitoring framework for large supercomputer systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Early experiences on the OLCF Frontier system with AthenaPK and Parthenon–Hydro

The Oak Ridge Leadership Computing Facility (OLCF) has been preparing the nation's first exascale system, Frontier, for production and end users. Frontier is based on HPE Cray's new EX architecture and Slingshot interconnect and features 74 cabinets of optimized 3rd Gen AMD EPYC CPUs for HPC and AI and AMD Instinct 250X accelerators. As a part of this preparation, “real-world” user codes have been selected to help assess the functionality, performance, and usability of the system. This article describes early experiences using the system in collaboration with the Hamburg Observatory for two selected codes, which have since been adopted in the OLCF test harness. Experiences discussed include efforts to resolve performance variability and per-cycle slowdowns. Results are shown for a performance portable astrophysical magnetohydronamics code, AthenaPK, and a mini-application stressing the core functionality of a performance portable block-structured adaptive mesh refinement framework, Parthenon-Hydro. Here, these results show good scaling characteristics to the full system. At the largest scale, the Parthenon-Hydro miniapp reaches a total of $1.7$ $\times$ $10^{13}$ zone-cycles/s on 9216 nodes (73,728 logical GPUs) at ≈92% weak scaling parallel efficiency (starting from a single node using a second-order, finite-volume method).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Semiconductor-Based, Solar-Driven Photochemical Cells for Fuel Generation from Carbon Dioxide in Aqueous Solutions

There has been active interest to identify new methods to reduce CO 2 into usable fuel sources. In this work, we demonstrate two types of photo-electrochemical cells (PECs) that photoreduce CO 2 directly to formate in aqueous solutions both in the presence and absence of external bias or additional electron sources. The photocathodes were either a CuFeO 2 /CuO electrode or a bilayer of CdTe on NiO, whereas the photoanode was a bilayer of NiO x on CdS. The PECs were characterized by using both electrochemistry and spectroscopy, and the products formed from CO 2 reduction were characterized and quantified by using 1 H NMR spectroscopy and ESI-MS. In addition, an organohydride catalyst was tested in conjunction with the PECs, which not only showed a significant gain of 85 times in CO 2 reduction (27 μm formate without the catalyst, 2.3 mm formate with it) compared to the NiO/CdTe photocathode system but could also generate methanol under an external bias (10 μm).

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

A phased workflow to define permit‐ready locations for large volume CO 2 injection and storage

Abstract To‐date, only two UIC Class VI permits have been issued by the US Environmental Protection Agency. We illustrate a four‐phase workflow to first identify regional storage resources and then down‐select sites to yield permit‐ready locations that can accept and store large volumes of CO 2 . Specific permit requirements should guide objectives and define deliverables of respective workflow phases. In the first phase we used available regional data and screened structure and injection zones to locate resources that match CO 2 volumes planned to be captured. Available data were also used to assess presence and depth of usable groundwater, the key resource being protected via permitting. We then used advanced, closed‐form, analytical solutions (EASiTool) to estimate CO 2 injectivity into each hydrologically connected injection compartment. In the second phase we acquired and conditioned additional wireline logs and leased available seismic datasets. We interpreted the depositional systems from wireline well‐log character and mapped sandbody geometry to interpolate injection and confining‐zone distribution. Using available data, we mapped faults and locations of freshwater and overpressure (or other capacity‐limiting geologic parameters) in more detail. In the third phase, we used the augmented geologic data to develop a static model for the selected area, extracted the areas of highest interest, and generated and ran dynamic (flow) models. In a fourth phase, we reduced major uncertainties identified in earlier phases. Our case study indicates that to complete preparation of a permit application requires (1) improved lithologic characterization information (thicknesses and horizontal and vertical connectivity) and (2) better definition of poorly defined local faults. © 2023 The Authors. Greenhouse Gases: Science and Technology published by Society of Chemical Industry and John Wiley & Sons Ltd.

58 GEOSCIENCES↗
DOE OSTI2019

eSHAFTS: Integrated and graphical drug design software based on 3D molecular similarity

With the development of computer technology, computer‐aided drug design (CADD) has become an important means for drug research and development, and its representative method is virtual screening. Various virtual screening platforms have emerged in an endless stream and play great roles in the field of drug discovery. With the increasing number of compound molecules, virtual screening platforms face two challenges: low fluency and low visibility of software operations. In this article, we present an integrated and graphical drug design software eSHAFTS based on three‐dimensional (3D) molecular similarity to overcome these shortcomings. Compared with other software, eSHAFTS has four main advantages, which are integrated molecular editing and drawing, interactive loading and analysis of proteins, multithread and multimode 3D molecular similarity calculation, and multidimensional information visualization. Experiments have verified its convenience, usability, and reliability. By using eSHAFTS, various tasks can be submitted and visualized in one desktop software without locally installing any dependent plug‐ins or software. The software installation package can be downloaded for free at http://lilab.ecust.edu.cn/home/resource.html . © 2019 Wiley Periodicals, Inc.

He, Gaoqi↗
DOE OSTI2022

Multistage mixed precision iterative refinement

Abstract Low precision arithmetic, in particular half precision (16‐bit) floating point arithmetic, is now available in commercial hardware. Using lower precision can offer significant savings in computation and communication costs with proportional savings in energy. Motivated by this, there has been a renewed interest in mixed precision iterative refinement schemes for solving linear systems , and new variants of GMRES‐based iterative refinement have been developed. Each particular variant with a given combination of precisions leads to different condition number‐based constraints for convergence of the backward and forward errors, and each has different performance costs. The constraints for convergence given in the literature are, as an artifact of the analyses, often overly strict in practice, and thus could lead a user to select a more expensive variant when a less expensive one would have sufficed. In this work, we develop a multistage mixed precision iterative refinement solver which aims to combine existing mixed precision approaches to balance performance and accuracy and improve usability. For a user‐specified initial combination of precisions, the algorithm begins with the least expensive approach and convergence is monitored via inexpensive computations with quantities produced during the iteration. If slow convergence or divergence is detected using particular stopping criteria, the algorithm switches to use a more expensive, but more reliable variant. A novel aspect of our approach is that, unlike existing implementations, our algorithm first attempts to use “stronger” GMRES‐based solvers for the solution update before resorting to increasing the precision(s). In some scenarios, this can avoid the need to refactorize the matrix in higher precision. We perform extensive numerical experiments on a variety of random dense problems and problems from real applications which confirm the benefits of the multistage approach.

Oktay, Eda↗
DOE OSTI2021

Catalase protects against nonenzymatic decarboxylations during photorespiration in Arabidopsis thaliana

Abstract Photorespiration recovers carbon that would be otherwise lost following the oxygenation reaction of rubisco and production of glycolate. Photorespiration is essential in plants and recycles glycolate into usable metabolic products through reactions spanning the chloroplast, mitochondrion, and peroxisome. Catalase in peroxisomes plays an important role in this process by disproportionating H 2 O 2 resulting from glycolate oxidation into O 2 and water. We hypothesize that catalase in the peroxisome also protects against nonenzymatic decarboxylations between hydrogen peroxide and photorespiratory intermediates (glyoxylate and/or hydroxypyruvate). We test this hypothesis by detailed gas exchange and biochemical analysis of Arabidopsis thaliana mutants lacking peroxisomal catalase. Our results strongly support this hypothesis, with catalase mutants showing gas exchange evidence for an increased stoichiometry of CO 2 release from photorespiration, specifically an increase in the CO 2 compensation point, a photorespiratory‐dependent decrease in the quantum efficiency of CO 2 assimilation, increase in the 12 CO 2 released in a 13 CO 2 background, and an increase in the postillumination CO 2 burst. Further metabolic evidence suggests this excess CO 2 release occurred via the nonenzymatic decarboxylation of hydroxypyruvate. Specifically, the catalase mutant showed an accumulation of photorespiratory intermediates during a transient increase in rubisco oxygenation consistent with this hypothesis. Additionally, end products of alternative hypotheses explaining this excess release were similar between wild type and catalase mutants. Furthermore, the calculated rate of hydroxypyruvate decarboxylation in catalase mutant is much higher than that of glyoxylate decarboxylation. This work provides evidence that these nonenzymatic decarboxylation reactions, predominately hydroxypyruvate decarboxylation, can occur in vivo when photorespiratory metabolism is genetically disrupted.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

PlantCV v4: Image analysis software for high‐throughput plant phenotyping

PlantCV is an open-source Python project aimed at developing tools to address a range of image-based, plant phenotyping questions. PlantCV has been used for more than 10 years to automate trait collection from image data, and the newest release, PlantCV version 4, continues to lower the barrier to entry for users without substantial coding experience through extensive example use-case tutorials and simplified installation. In addition to usability, we document added functionality since the release of PlantCV v2, including support for more image types such as fluorescence, thermal, and hyperspectral data. Finally, we describe the development of a new subpackage focused on morphological trait measurements like leaf angle, and demonstrate its utility as compared to more manual methods of data collection.

Schuhl, Haley [Donald Danforth Plant Science Cente↗
DOE OSTI2018

Integration of paper spray ionization high‐field asymmetric waveform ion mobility spectrometry for forensic applications

Rationale Paper spray ionization (PSI) is an attractive ambient ionization source for mass spectrometry (MS) since it allows the combination of surface sampling and ionization. The minimal sample preparation inherent in this approach greatly reduces the time needed for analysis. However, the ions generated from interfering compounds in the sample and the paper substrate may interfere with the analyte ions. Therefore, the integration of PSI with high‐field asymmetric ion mobility spectrometry (FAIMS) is of significant interest since it should reduce the background ions entering the mass analyzer without complicating the analysis or increasing analysis time. Here we demonstrate the integration of PSI with FAIMS/MS and its potential for analysis of samples of forensic interest. Methods In this work, the parameters that can influence the integration, including sampling and ionization by paper spray, the FAIMS separation of analytes from each other and background interferences, and the length of time that a usable signal can be observed for explosives on paper, were evaluated with the integrated system. Results In the negative ion analysis of 2,4,6‐trinitrotoluene (TNT), pentaerythritol tetranitrate (PETN), octahydro‐1,3,5,7‐tetranitro‐1,3,5,7‐tetrazocine (HMX), and 1,3,5‐trinitroperhydro‐1,3,5‐triazine (RDX), amounts as low as 1 ng on paper were readily observed. The successful positive ion separation of a set of illicit drugs including heroin, methamphetamine, and cocaine was also achieved. In addition, the positive ion analysis of the chemical warfare agent simulants dimethyl methylphosphonate (DMMP) and diisopropyl methylphosphonate (DIMP) was evaluated. Conclusions The integration of PSI‐FAIMS/MS was demonstrated for the analyses of explosives in negative ion mode and for illicit drugs and CW simulants in positive mode. Paper background ions that could interfere with these analyses were separated by FAIMS. The compensation voltage of an ion obtained by FAIMS provided an additional identification parameter to be combined with the mass spectrum for each analyte.

Tsai, Chia‐Wei↗
DOE OSTI2016

Information or resolution: Which is required from an SEM to study bulk inorganic materials?: Evaluate SEMs’ practical performance

Significant technological advances in scanning electron microscopy (SEM) have been achieved over the past years. Different SEMs can have significant differences in functionality and performance. This work presents the perspectives on selecting an SEM for research on bulk inorganic materials. Understanding materials demands quantitative composition and orientation information, and informative and interpretable images that reveal subtle differences in chemistry, orientation/structure, topography, and electronic structure. The capability to yield informative and interpretable images with high signal-to-noise ratios and spatial resolutions is an overall result of the SEM system as a whole, from the electron optical column to the detection system. The electron optical column determines probe performance. The roles of the detection system are to capture, filter or discriminate, and convert signal electrons to imaging information. The capability to control practical operating parameters including electron probe size and current, acceleration voltage or landing voltage, working distance, detector selection, and signal filtration is inherently determined by the SEM itself. As a platform for various accessories, e.g. an energydispersive spectrometer and an electron backscatter diffraction detector, the properties of the electron optical column, specimen chamber, and stage greatly affect the performance of accessories. Ease-of-use and ease-of-maintenance are of practical importance. It is practically important to select appropriate test specimens, design suitable imaging conditions, and analyze the specimen chamber geometry and dimensions to assess the overall functionality and performance of an SEM. Finally, for an SEM that is controlled/operated with a computer, the stable software and user-friendly interface significantly affect the usability of the SEM.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Trusted Simulation: Considering Model Quality in the Context of User Trust

A high‐quality simulation model should help its users to easily and appropriately calibrate their trust in the model. Traditional evaluation metrics such as validation and robustness are necessary but insufficient for this task. Trust calibration depends on factors like the model's transparency, applicability to intended use, usability, reputation, and consideration of potential bias. This article proposes a framework for designing and evaluating system dynamics models by considering factors that contribute to the proper calibration of user trust. This framework takes inspiration from trusted artificial intelligence, broadening our traditional concept of model quality and explicitly focusing on what users need to consider a model trustworthy and to understand the model's relevance to its intended purpose. The trusted simulation framework can improve our integration of model quality activities throughout the modeling process, leading to more impactful and better‐targeted model design, development, and evaluation.

Naugle, Asmeret Bier [Sandia National Laboratories↗