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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 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Scheduling and Performance of Asynchronous Tasks in Fortran 2018 with FEATS

Most parallel scientific programs contain compiler directives (pragmas) such as those from OpenMP (Hermanns in Parallel programming in Fortran 95 using openMP, 2002. School of Aeronautical Engineering, Universidad Politécnica de Madrid, España, 2011), explicit calls to runtime library procedures such as those implementing the Message Passing Interface (MPI) (in A message-passing interface standard version 4.0, 2021. https://www.mpi-forum.org/docs/mpi-4.0/mpi40-report.pdf), or compiler-specific language extensions such as those provided by CUDA (Ruetsch and Fatica in CUDA Fortran for scientists and engineers: best practices for efficient CUDA Fortran programming, Elsevier, 2013). By contrast, the recent Fortran standards empower developers to express parallel algorithms without directly referencing lower-level parallel programming models (Numrich in Parallel programming with co-arrays, CRC Press, 2018, and Curcic in Modern Fortran: building efficient parallel applications, Manning Publications, 2020). Fortran’s parallel features place the language within the Partitioned Global Address Space (PGAS) class of programming models. When writing programs that exploit data parallelism, application developers often find it straightforward to develop custom parallel algorithms. Problems involving complex, heterogeneous, staged calculations, however, pose much greater challenges. Such applications require careful coordination of tasks in a manner that respects dependencies prescribed by a directed acyclic graph. When rolling one’s own solution proves difficult, extending a customizable framework becomes attractive. Further, the paper presents the design, implementation, and use of the Framework for Extensible Asynchronous Task Scheduling (FEATS), which we believe to be the first task scheduling tool written in modern Fortran. We describe the benefits and compromises associated with choosing Fortran as the implementation language, and we propose ways in which future Fortran standards can best support the use case in this paper.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Theory and numerics of subspace approximation of eigenvalue problems

Large-scale eigenvalue problems arise in various fields of science and engineering and demand computationally efficient solutions. In this study, we investigate the subspace approximation for parametric linear eigenvalue problems, aiming to mitigate the computational burden associated with high-fidelity systems. Furthermore, we provide general error estimates under non-simple eigenvalue conditions, establishing some theoretical foundations for understanding the convergence behavior of subspace approximations. Numerical examples, including problems with one-dimensional to three-dimensional spatial domain and one-dimensional to two-dimensional parameter domain, are presented to demonstrate the efficacy of reduced basis method in handling parametric variations in boundary conditions and coefficient fields to achieve significant computational savings while maintaining high accuracy, making them promising tools for practical applications in large-scale eigenvalue computations.

Eigenvalue problems↗
DOE OSTI2019

Tailor-made trees: engineering lignin for ease of processing and tomorrow’s bioeconomy

Lignocellulosic biomass represents an abundant source of cellulosic fibres and fermentable sugars. Yet, lignin, a polyphenolic constituent of secondary-thickened plant cell walls significantly contributes to biomass recalcitrance during industrial processing. Efforts to reduce plant total lignin content through genetic engineering have improved processing efficiency, but often incur an agronomic penalty. Alternatively, modifications that alter the composition of lignin and/or its interaction with other cell wall polymers display improved processing efficiency without compromising biomass yield. We propose that future efforts to improve woody feedstocks should focus on altering lignin composition and cell wall ultrastructure. Here, we describe potential future modifications to lignin and/or other cell wall characteristics that may serve as strategic targets in the production of trees that are tailor-made for specific pretreatments and end-product applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Capillary-Enhanced Two-Phase Micro-Cooler Using Copper-Inverse-Opal Wick with Silicon Microchannel Manifold for High-Heat-Flux Cooling Application

In this work, we demonstrate a two-phase capillary-fed boiling micro-cooler that consists of a ~ 25-..mu..m-thick copper inverse opal (CIO) porous wicking structure for high-heat-flux boiling and a silicon 3D-manifold for distributed liquid delivery and vapor extraction across a 0.5 cm x 0.5 cm heated area. At low inlet water mass flow rates of 1.5 to 1.9 g(min)-1, the micro-cooler displays nearly two-phase boiling with exit vapor quality ~ 1 and a high critical heat flux (CHF) of 253 to 320 W cm-2 with low superheat of ~ 10 degrees C resulting in a thermal resistance of boiling ~ 0.025 cm2 degrees C W-1 or heat transfer coefficient of 0.4 MW m-2 degrees C-1. For higher flow rates of 5, 10, and 15 g(min)-1, the micro-cooler exhibits a hybrid single-phase and two-phase cooling regime where the contribution of the sensible heat (single-phase) cooling is linearly added to that of the two-phase cooling. For the highest flow rate of 15 g(min)-1, the CHF is increased to ~ 500 W cm-2 resulting in an overall thermal resistance of ~ 0.18 cm2 degrees C W-1. However, the two-phase heat transfer effectiveness, which estimates the utilization level of the inlet mass flow rate for two-phase boiling, is reduced to ~ 0.11. To achieve the best cooling system performances, the micro-cooler must operate entirely within the two-phase boiling regime (exit vapor quality or two-phase heat transfer effectiveness ~ 1). Ideally, the "coolant" should be delivered near its saturation temperature (~ 100 degrees C for water), which provides significant advantages for the energy-efficient operation of data centers and power electronics. We present detailed analysis with Infrared and high speed camera images at various inlet flow rates and heat fluxes to understand complex heat transfer in the micro-cooler. Furthermore, a conjugate thermofluidic simulation model, which incorporates the physics of capillary-fed boiling in a porous copper layer, agrees well with the experimental data.

capillary-enhanced boiling↗
DOE OSTI2018

Record-Low and Anisotropic Thermal Conductivity of a Quasi-One-Dimensional Bulk ZrTe 5 Single Crystal

Zirconium pentatelluride (ZrTe 5 ) has recently attracted renewed interest owing to many of its newly discovered extraordinary physical properties, such as 2D and 3D topological-insulator behavior, pressure-induced superconductivity, Weyl semimetal behavior, Zeeman splitting, and resistivity anomaly. The quasi-one-dimensional structure of single-crystal ZrTe 5 also promises large anisotropy in its thermal properties, which have not yet been studied. In this work, via time-domain thermoreflectance measurements, ZrTe 5 single crystals are discovered to possess a record-low thermal conductivity along the b-axis (through-plane), as small as 0.33 ± 0.03 W m –1 K –1 at room temperature. This ultralow b-axis thermal conductivity is 12 times smaller than its a-axis thermal conductivity (4 ± 1 W m –1 K –1 ) owing to the material’s asymmetrical crystalline structure. First-principles calculations are further conducted to reveal the physical origins of the ultralow b-axis thermal conductivity, which can be attributed to: (1) the resonant bonding and strong lattice anharmonicity induced by electron lone pairs, (2) the weak interlayer van der Waals interactions, and (3) the heavy mass of Te atoms, which results in low phonon group velocity. This work sheds light on the design and engineering of high-efficiency thermal insulators for applications such as thermal barrier coatings, thermoelectrics, thermal energy storage, and thermal management.

36 MATERIALS SCIENCE↗
DOE OSTI2017

CRISPR-Cpf1 mediates efficient homology-directed repair and temperature-controlled genome editing

Cpf1 is a novel class of CRISPR-Cas DNA endonucleases, with a wide range of activity across different eukaryotic systems. Yet, the underlying determinants of this variability are poorly understood. Here, we demonstrate that LbCpf1, but not AsCpf1, ribonucleoprotein complexes allow efficient mutagenesis in zebrafish and Xenopus. We show that temperature modulates Cpf1 activity by controlling its ability to access genomic DNA. This effect is stronger on AsCpf1, explaining its lower efficiency in ectothermic organisms. We capitalize on this property to show that temporal control of the temperature allows post-translational modulation of Cpf1-mediated genome editing. Finally, we determine that LbCpf1 significantly increases homology-directed repair in zebrafish, improving current approaches for targeted DNA integration in the genome. Together, we provide a molecular understanding of Cpf1 activity in vivo and establish Cpf1 as an efficient and inducible genome engineering tool across ectothermic species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Reconfigurable training and reservoir computing in an artificial spin-vortex ice via spin-wave fingerprinting

Strongly interacting artificial spin systems are moving beyond mimicking naturally occurring materials to emerge as versatile functional platforms, from reconfigurable magnonics to neuromorphic computing. Typically, artificial spin systems comprise nanomagnets with a single magnetization texture: collinear macrospins or chiral vortices. Here, by tuning nanoarray dimensions we have achieved macrospin–vortex bistability and demonstrated a four-state metamaterial spin system, the ‘artificial spin-vortex ice’ (ASVI). ASVI can host Ising-like macrospins with strong ice-like vertex interactions and weakly coupled vortices with low stray dipolar field. Vortices and macrospins exhibit starkly differing spin-wave spectra with analogue mode amplitude control and mode frequency shifts of Δf = 3.8 GHz. The enhanced bitextural microstate space gives rise to emergent physical memory phenomena, with ratchet-like vortex injection and history-dependent non-linear fading memory when driven through global magnetic field cycles. We employed spin-wave microstate fingerprinting for rapid, scalable readout of vortex and macrospin populations, and leveraged this for spin-wave reservoir computation. ASVI performs non-linear mapping transformations of diverse input and target signals in addition to chaotic time-series forecasting.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Bioinspiration in light harvesting and catalysis

Capturing and converting solar energy into fuels and feedstocks is a global challenge that spans numerous disciplines and fields of research. Billions of years of evolution have allowed natural organisms to hone strategies for harvesting light from the sun and storing energy in the form of carbon–carbon and carbon–hydrogen bonds. Photosynthetic antenna proteins capture solar photons and funnel photoexcitations to reaction centres with high yields, and enzymes catalyze multi-electron reactions, facilitating chemical transformations not yet efficiently implemented using artificially engineered catalysts. Researchers in renewable energy often look to nature to understand the mechanisms at work and, if possible, to explore their translation into artificial systems. Here, we review advances in bioinspiration across the fields of biological light harvesting and chemical energy conversion. We examine how multi-photon and multi-electron reactions in biology can inspire new methods in photoredox chemistry to achieve novel, selective and complex organic transformations; how carbonic-dehydrogenase-inspired design principles enable catalytic reactions such as the conversion of CO 2 into useful products such as fuels; and how concepts from photosynthetic antenna complexes and reaction centres can benefit artificial light-harvesting materials. We then consider areas in which bioinspiration could enable advances in the rational design of molecules and materials, the expansion of the synthetic capabilities of catalysts and the valorization of molecular building blocks. Here, we highlight the challenges that must be overcome to realize these advances and propose new directions that may use bioinspiration to achieve them.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Methane utilization in Methylomicrobium alcaliphilum 20Z R : a systems approach

Biological methane utilization, one of the main sinks of the greenhouse gas in nature, represents an attractive platform for production of fuels and value-added chemicals. Despite the progress made in our understanding of the individual parts of methane utilization, our knowledge of how the whole-cell metabolic network is organized and coordinated is limited. Attractive growth and methane-conversion rates, a complete and expert-annotated genome sequence, as well as large enzymatic, 13 C-labeling, and transcriptomic datasets make Methylomicrobium alcaliphilum 20Z R an exceptional model system for investigating methane utilization networks. Here we present a comprehensive metabolic framework of methane and methanol utilization in M. alcaliphilum 20Z R . A set of novel metabolic reactions governing carbon distribution across central pathways in methanotrophic bacteria was predicted by in-silico simulations and confirmed by global non-targeted metabolomics and enzymatic evidences. Our data highlight the importance of substitution of ATP-linked steps with PPi-dependent reactions and support the presence of a carbon shunt from acetyl-CoA to the pentose-phosphate pathway and highly branched TCA cycle. The diverged TCA reactions promote balance between anabolic reactions and redox demands. As a result, the computational framework of C 1 -metabolism in methanotrophic bacteria can represent an efficient tool for metabolic engineering or ecosystem modeling.

09 BIOMASS FUELS↗
DOE OSTI2021

A Practical Analysis Framework for Assessment of Printed Circuit Heat Exchangers in High-Temperature Nuclear Service

Abstract Printed circuit heat exchangers (PCHEs) have high thermal efficiency because of the numerous minuscule channels. These minuscule channels result in a high thermal exchange area per unit volume, making PCHE a top contender for an intermediate heat exchanger (IHX) in high-temperature reactors. Thousands of minuscule channels make finite element analysis of the PCHE computationally infeasible. A two-dimensional analysis is usually performed for the PCHE core, which cannot simulate the local channel level responses reasonably because of the absence of global constraint influence. At present, there is no analysis technique available in the ASME Code or literature that is computationally efficient and suitable for engineers to estimate PCHE local responses. A novel but practical two-step analysis framework is proposed for performing PCHE analysis. In the first step, the channeled core is replaced by orthotropic solids with similar stiffness to simulate the global thermomechanical elastic responses of the PCHE. In the second step, local submodel analysis with detailed channel geometry and loading is performed using the elastic-perfectly plastic (EPP) material model. The proposed two-step analysis technique provides a unique capability to estimate the channel corner responses to be used for PCHE performance assessment. This study first developed a methodology for calculating the elastic orthotropic properties of the PCHE core. Next, the two-step analysis is performed for a realistic size PCHE core, and different issues observed in the results are scrutinized and resolved. Finally, a practical finite element analysis framework for PCHEs in high-temperature nuclear service is recommended.

Engineering↗
DOE OSTI2024

Learning Nonlinear Reduced Models from Data with Operator Inference

This review discusses Operator Inference, a nonintrusive reduced modeling approach that incorporates physical governing equations by defining a structured polynomial form for the reduced model, and then learns the corresponding reduced operators from simulated training data. The polynomial model form of Operator Inference is sufficiently expressive to cover a wide range of nonlinear dynamics found in fluid mechanics and other fields of science and engineering, while still providing efficient reduced model computations. The learning steps of Operator Inference are rooted in classical projection-based model reduction; thus, some of the rich theory of model reduction can be applied to models learned with Operator Inference. This connection to projection-based model reduction theory offers a pathway toward deriving error estimates and gaining insights to improve predictions. Furthermore, through formulations of Operator Inference that preserve Hamiltonian and other structures, important physical properties such as energy conservation can be guaranteed in the predictions of the reduced model beyond the training horizon. This review illustrates key computational steps of Operator Inference through a large-scale combustion example.

Mechanics↗
DOE OSTI2021

Effect of Catalyst and Catalyst Layer Composition on Catalyst Support Durability

Polymer electrolyte membrane fuel cells (PEMFCs) are efficient, zero-emission engines for the automotive sector. However, cost and durability are major barriers for the commercialization of PEMFCs. Degradation of the carbon support in the cathode catalyst layer due to high potential excursions caused by unmitigated events like H 2 starvation, or start-up/shutdown are still a major durability issue in PEMFCs. Catalyst support durability was studied by accelerated stress tests (ASTs) that included repeated potential cycling from 1.0 to 1.5 V. The effect of catalyst layer composition on carbon corrosion was studied using membrane electrode assemblies with different catalysts (Pt, PtCo), catalyst composition (catalyst wt.%, supports), ionomer composition (loading, and equivalent weights). The corrosion of the carbon support is similar between Pt and PtCo catalysts. However, the performance degradation rate is higher for the alloy catalysts due to differences in catalyst particle size and the transition metal’s leaching accelerating the performance degradation. The carbon loss is lower for catalysts with lower initial carbon loading (or higher catalyst wt.%), which is better for durability. However, the cumulative loss of carbon is identical for electrodes with the same catalyst support irrespective of catalyst and ionomer composition in the catalyst layer.

25 ENERGY STORAGE↗
DOE OSTI2025

Effect of Carbon Support Heat Treatment on the Performance of Ion-Pair High-Temperature PEM Fuel Cells

Heat treatment can significantly alter the physical and chemical properties of carbon supports, thereby influencing the performance of proton exchange membrane (PEM) fuel cells. This study explores how varying carbon heat treatment temperatures—from 1,000 °C to 2,200 °C—affect the structure and performance of platinum-based catalysts in high-temperature PEM fuel cells. Increasing the heat treatment temperature led to a notable decrease in surface area, along with increases in carbon grain size and hydrophobicity. Although the catalyst supported on carbon treated at 1,000 °C exhibited the highest catalyst activity, the MEA using carbon treated at 1,500 °C delivered the best overall fuel cell performance. This is attributed to an optimized balance between hydrophobicity and accessible surface area, which enhances water management and catalyst utilization. These findings underscore the importance of carbon support engineering in improving the efficiency of ion-pair high-temperature PEM fuel cells.

08 HYDROGEN↗
DOE OSTI2023

Considerations for Electrochemical Phosphorus Precipitation: A Figures of Merit Approach

Electrochemical phosphorus precipitation (EPP) from wastewater is a promising emerging technology for recovering valuable nutrients. While there are significant advantages of EPP compared to traditional phosphorus recovery, large gaps in reported performance exist between EPP methods and between EPP and industrial methods. Herein we discuss Figures of Merit (FOM) to normalize and report EPP performance at low-to-intermediate technology readiness levels (TRLs). Here, the appropriate use of FOM in electrochemical engineering enables better comparison between technologies, enhanced understanding of electrochemical and mass transport phenomena, and faster scale-up and adoption of nascent technologies.¬ FOM specific to EPP are discussed along with important considerations and adaptations from traditional electrochemical engineering FOM. Importantly, this FOM approach may be adapted for many different electrochemical processes and technologies, aiding in the push toward and adoption of electrification in chemical processing.

42 ENGINEERING↗
DOE OSTI2016

RetSynth v. 1.0

This software uses a database of existing biological pathways to determine efficient routes for genetic engineering.

Whitmore, LeanneS.↗
DOE OSTI2025

ALchemist (Active Learning Toolkit for Chemical and Materials Research) [SWR-25-102]

ALchemist is a modular Python toolkit that brings active learning and Bayesian optimization to experimental design in chemical and materials research. It is designed for scientists and engineers who want to efficiently explore or optimize high-dimensional variable spaces—without writing code—using an intuitive graphical interface.

Coatney, Caleb [National Renewable Energy Laborato↗
DOE OSTI2019

Building Benchmark Data Platform

This project is a three-year, four-laboratory collaboration to collect and curate a handful of high-resolution building systems datasets that have broad applicability to address highest-impact use cases. We will collect and curate high-resolution, well-calibrated time series of building operational and indoor/outdoor environmental data, which are crucial to understanding and optimizing building energy efficiency performance and demand flexibility capabilities as well as benchmarking energy algorithms.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Joint Optimization of Well Completions and Controls for CO 2 Enhanced Oil Recovery and Storage

CO 2 storage through CO 2 enhanced oil recovery (EOR) is considered as one of the technologies to help promote larger scale deployment of CO 2 storage because of associated economic benefits through oil recovery, 45Q tax credits and the utilization of existing infrastructure. The objective of this study is to demonstrate how optimal reservoir management and operation strategies (including well completions and controls) can be used to optimize both CO 2 storage and oil recovery. The optimization problem was focused on jointly estimating the well completions (i.e., fraction of injection/production well perforations in each reservoir layer) and CO 2 injection/oil production controls that maximize the net present value (NPV) in a CO 2 EOR and storage operation. We utilized the newly developed StoSAG algorithm, one of the most efficient optimization algorithms in the reservoir management community, to solve the optimization problem. The performance of joint optimization approach was compared with the performance of well control only optimization approach. In addition, the performance of co-optimization of CO 2 storage and oil recovery approach was compared with the performances of maximization of only CO 2 storage and maximization of only oil recovery approaches. The optimization results showed that a joint optimization of well completions and well controls can achieve an 8.84% higher final NPV than the one obtained from the optimization of only well controls. It was observed that the NPV incremental for joint optimization is mainly due to the fact that the optimal well completions and controls approach results in efficient CO 2 storage and oil production from different reservoir layers depending on the differences in individual layer properties. Comparison of co-optimization (i.e., maximization of NPV) and maximization of only CO 2 storage or only oil recovery showed that the co-optimization and maximization of only oil recovery result in significantly higher final NPV than that obtained through maximization of only CO 2 storage approach while maximization of only CO 2 storage can achieve significantly higher CO 2 storage in the reservoir compared to the other two scenarios. The similar results for co-optimization and maximization of oil production are obtained because of the difference in oil revenue compared to CO 2 storage tax credit. To the best of our knowledge, this is the first study in oil/gas industry and CO 2 storage community to perform joint optimization of well completions and well controls in the fields. We expect that the proposed optimization framework will be a useful and efficient tool for field engineers to optimally manage CO 2 EOR projects to maximize revenue through oil recovery as well as CO 2 storage by taking advantage of the new 45Q tax law.

Artificial intelligence↗