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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Regulating Gas Transport in Molecularly Engineered Polymer Membranes (Final Technical Report)

Energy-efficient separation processes are essential for a wide range of applications ranging from clean fuels (e.g., hydrogen purification) and petroleum refining (e.g., natural gas processing) to water purification and carbon capture. Membrane-mediated separations have shown tremendous promise in providing high productivity and high separation efficiency at significantly lower energy consumption, e.g., up to 90% less energy cost than traditional thermally driven processes such as distillation. Polymeric membranes–the dominant separation membrane materials–have yet to reach their full potential due to their limitations in long-term durability (e.g., productivity loss over the period of their lifetime due to physical aging) or insufficient stability under harsh conditions (e.g., high temperature, chemically complex feeds). This research seeks to establish a new paradigm in polymer membrane material design by harnessing crosslinked model networks with well-defined yet finely tailorable microstructure to facilitate fast and selective gas transport and simultaneously enhance membrane stability. Unlike traditional randomly crosslinked polymers, which suffer from structural inconsistencies and consequently suboptimal gas separation performance, crosslinked model network membranes prepared via a precisely controlled end-linking process enables the creation of previously unattainable microstructure tunability, which, in turn, results in versatile crosslinked membranes with high separation performance that meet the needs of various challenging gas separations. Using model network framework as a fundamental tool by applying this concept in diverse polymer categories, this work has led to the development of various innovative crosslinked membrane structures such as unimodal, bimodal and clustered model networks. These advanced crosslinked polymer membranes not only demonstrate exceptional gas separation performance that significantly outperform existing randomly crosslinked membranes, but also possess excellent long-term durability and robust stability under complex operating conditions. From a fundamental perspective, results from this research provide critical mechanistic insights into gas separation in crosslinked polymer membranes, addressing key knowledge gaps and opening new avenues for membrane design to meet various separation needs. The new membrane materials produced from this research enable the use of polymeric membranes for high temperature gas separations, offering substantial energy and cost savings by eliminating the need for repeated cooling-heating cycles in industrial processes.

02 PETROLEUM↗
DOE OSTI2024

Recommendations for an Applicant to Calculate Activity Data for Greenhouse Gases Estimates

In 2009, the U.S. Nuclear Regulatory Commission (NRC) directed the NRC staff to address climate change issues and consider the impacts of the emissions of carbon dioxide (CO 2 ) and other greenhouse gases (GHGs) in its environmental reviews for major licensing actions (NRC 2009b). To implement this direction from the Commission, the staff issued guidance in 2011 and updated guidance in 2014 in Attachment 1 to Interim Staff Guidance COL/ESP-ISG-026 (NRC 2011; NRC 2014). This guidance provides a simpler method than the method described in RG 4.2 Rev. 3, that an applicant can use to meet the plant parameter envelope (PPE) value from the Generic Environmental Impact Statement for Licensing of New Nuclear Reactors (NR GEIS). NRC staff estimated the 97-year lifecycle GHG emissions from a reference 1000 megawatt electrical (MWe) light-water reactor (LWR) for various activities associated with construction, operation (including uranium fuel cycle), and decommissioning of nuclear power plants and presented the results in Appendix H of the NR GEIS. Appendix H of the NR GEIS includes estimates of direct emissions from construction equipment and emergency diesel engines in a nuclear facility and indirect emissions from workforce vehicular traffic, fuel transportation and the uranium fuel cycle. The NR GEIS Section 3.3 extended the estimates in Appendix H for the installation of two 1000 MWe nuclear reactors on the same site. Scaling factors were used to extrapolate the GHG emissions of a reference 1000 MWe reactor to a two-unit nuclear reactor plant (each reactor unit generating 1000 MWe). GHG emission estimates for building, operation, decommissioning and safe storage (SAFSTOR) for a two-unit nuclear reactor plant would be based on the plant’s physical size, and therefore estimates for these source categories were assumed to be twice the value of the reference 1000 MWe reactor. However, GHG emissions from the fuel cycle (including fuel transportation) were scaled upward by a factor of 3, based on plant efficiencies greater than the 80 percent assumption in Appendix H. Table 1 below shows the PPE emissions for two 1000 MWe nuclear reactors as provided in NR GEIS. The total GHG emissions for two 1000 MWe reactors were calculated as 2,534,000 metric tons (MT) of CO 2 equivalent (CO 2 (e)) based on a 97 year GHG life cycle period. The GHG emissions lifetime of 97 years for a reference nuclear reactor includes a 7-year building phase, 40 years of operation, 10 years of active decommissioning, and 40 years of SAFSTOR operations (NRC 2024). Construction equipment and vehicular traffic from workers commute would contribute to the GHG emissions during a 7-year building phase. Uranium fuel cycle, vehicular traffic, fuel and waste transportation, and testing of standby diesel generators would contribute to GHG emissions during the 40-year operations phase. While NRC’s regulations allow up to 60 years of reactor facility decommissioning, Appendix H estimated that most of the GHGs would occur over an estimated 10-year period during which to the licensee would engage in significant demolition and earth-moving activities, as discussed in Supplement 1 to NUREG-0586 (NRC 2002). Vehicular traffic by the workforce during a 40-year SAFSTOR period would additionally contribute GHG emissions. The carbon footprint for a 40-year SAFSTOR period was separately analyzed from the decommissioning activities as provided in Table YYYY-2 of the staff issued guidance in 2011 (NRC 2011).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Customs: Inspect and Report Python Imports (customs) v1.0.0

We have developed a simple, minimally invasive monitoring framework that enables us to capture key metrics from Python user processes. This is part of a larger effort to collect data across our entire data-intensive science workload at NERSC. The approach for Python is inspired by a similar framework developed for Blue Waters at NCSA. Both frameworks leverage standard Python features, sitecustomize and atexit, to capture Python imports of interest and other job data. The customs package decomposes the information capture into separate inspection and reporting interfaces.

Thomas, Rollin↗
DOE OSTI2024

GPU-enabled extreme-scale turbulence simulations: Fourier pseudo-spectral algorithms at the exascale using OpenMP offloading

Fourier pseudo-spectral methods for nonlinear partial differential equations are of wide interest in many areas of advanced computational science, including direct numerical simulation of three-dimensional (3-D) turbulence governed by the Navier-Stokes equations in fluid dynamics. This paper presents a new capability for simulating turbulence at a new record resolution up to 35 trillion grid points, on the world's first exascale computer, Frontier, comprising AMD MI250x GPUs with HPE's Slingshot interconnect and operated by the US Department of Energy's Oak Ridge Leadership Computing Facility (OLCF). Key programming strategies designed to take maximum advantage of the machine architecture involve performing almost all computations on the GPU which has the same memory capacity as the CPU, performing all-to-all communication among sets of parallel processes directly on the GPU, and targeting GPUs efficiently using OpenMP offloading for intensive number-crunching including 1-D Fast Fourier Transforms (FFT) performed using AMD ROCm library calls. With 99% of computing power on Frontier being on the GPU, leaving the CPU idle leads to a net performance gain via avoiding the overhead of data movement between host and device except when needed for some I/O purposes. Memory footprint including the size of communication buffers for MPI_ALLTOALL is managed carefully to maximize the largest problem size possible for a given node count. Detailed performance data including separate contributions from different categories of operations to the elapsed wall time per step are reported for five grid resolutions, from 2048 3 on a single node to 32768 3 on 4096 or 8192 nodes out of 9408 on the system. Both 1D and 2D domain decompositions which divide a 3D periodic domain into slabs and pencils respectively are implemented. The present code suite (labeled by the acronym GESTS, GPUs for Extreme Scale Turbulence Simulations) achieves a figure of merit (in grid points per second) exceeding goals set in the Center for Accelerated Application Readiness (CAAR) program for Frontier. The performance attained is highly favorable in both weak scaling and strong scaling, with notable departures only for 2048 3 where communication is entirely intra-node, and for 32768 3 , where a challenge due to small message sizes does arise. Communication performance is addressed further using a lightweight test code that performs all-to-all communication in a manner matching the full turbulence simulation code. Performance at large problem sizes is affected by both small message size due to high node counts as well as dragonfly network topology features on the machine, but is consistent with official expectations of sustained performance on Frontier. Overall, although not perfect, the scalability achieved at the extreme problem size of 32768 3 (and up to 8192 nodes — which corresponds to hardware rated at just under 1 exaflop/sec of theoretical peak computational performance) is arguably better than the scalability observed using prior state-of-the-art algorithms on Frontier's predecessor machine (Summit) at OLCF. New science results for the study of intermittency in turbulence enabled by this code and its extensions are to be reported separately in the near future.

3D fast Fourier transform↗
DOE OSTI2022

Co-transport of water and p-xylene through carbon molecular sieve membranes

Carbon molecular sieve (CMS) materials are a potential candidate for scalable and high-performance reverse osmosis membranes due to their impressive chemical and thermal stabilities. Moreover, they have the potential to enable impressive rejections of small neutral solutes from water based on their known ability to separate small organic molecules. CMS has been extensively examined for gas and organic solvent separations, but the transport of organic and aqueous mixtures through CMS microstructures is poorly understood. In this work, we investigated the sorption, diffusion, and permeation behavior of organic compounds and water in poly(vinylidene fluoride)(PVDF)-derived CMS (PVDF-CMS). Experimental observations of diffusion, sorption, and permeation shows how the properties of penetrants such as polarity and molecular size affect the transport rates and selectivity. These basic transport and sorption parameters are utilized in sorption-diffusion models to permeation rates of water-organic mixtures in CMS membranes. The transport of water and p-xylene in CMS was experimentally confirmed to follow the sorption-diffusion mechanism. The sorption-diffusion model ideal permselectivity indicates that the CMS is p-xylene selective over water. Water/p-xylene mixture permeation experiments revealed an increased selectivity of p-xylene over water, thus providing tentative evidence for a competitive sorption-selective separation mechanism. Furthermore, this work suggests that CMS membranes exhibit organic-permeable separation properties in water/organic separations. The results presented here highlight the potential for the removal of dilute organics in water via CMS pervaporation membranes.

02 PETROLEUM↗
DOE OSTI2022

Machine learning prediction on the fractional free volume of polymer membranes

Fractional free volume (FFV) characterizes the microstructural level features of polymers and affects their properties including thermal, mechanical, and separation performance. Experimental measurements and theoretical analyses have been used to quantify the FFV of polymers, but challenges remain because of their limitations. Experimental measurements are laborious and based on semi empirical equations, while Bondi’s group contribution theory involves ambiguities like the determination of van der Waals volume and the choice of factor values in the theoretical equation. To efficiently evaluate the FFV of polymers, this study utilizes high-throughput molecular dynamics (MD) simulations to build a large dataset regarding polymer’s FFV. Based on this large dataset, we further build machine learning (ML) models to establish the composition-structure relation. Inspired by group contribution theory which correlates polymer’s functional groups to FFV, our ML models correlate polymer’s substructures or physico-chemical indexes to FFV. Here, our study first benchmarks the MD simulation protocol to obtain reliable FFV of polymers and then carries out high-throughput MD simulations for more than 6,500 homopolymers and 1,400 polyamides. Such a large and diverse dataset makes the well-trained ML models more generalizable, compared with the group contribution theory. The efficiency of a feed forward neural network model is further demonstrated by applying it to a hypothetical polyimide dataset of more than 8 million chemical structures. The predicted FFVs of hypothetical polyimides are further validated by MD simulations. The obtained FFVs of the 8 million polymers, plus their previously reported gas separation performances, demonstrate the promising capability of ML virtual screening for the discovery of polymer membranes with exceptional permeability/selectivity.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Glassy polymers: Historical findings, membrane applications, and unresolved questions regarding physical aging

Polymers below their glass transition temperature (Tg) are non-equilibrium glasses because excess free volume “frozen” between kinetically-restricted polymer chains slowly relaxes over time towards equilibrium via local, segmental chain motion. This process, known as physical aging, is observed through time-dependent decreases in a polymer's specific volume, enthalpy, etc. This article focuses on the history of glassy polymers in membrane separation applications. Open questions regarding the influence of thickness (e.g., membrane geometry) and temperature on physical aging in glassy polymers are highlighted.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Spatial proteomics reveals signal sequence characteristics correlated with localization in cyanobacteria

Abstract Cyanobacteria have an inner and outer cell membrane enclosing the periplasm and cell wall and an additional set of internal membranes (called the thylakoid membranes) enclosing the thylakoid lumen. The periplasm and thylakoid lumen have unique proteomes, but the mechanisms regulating protein sorting to these locations have remained elusive. Here, proximity-based proteomics using the engineered peroxidase APEX2 was performed in the cyanobacteria Synechococcus sp. PCC 7002 to profile the proteomes of the cytoplasm, thylakoid lumen, and the periplasm and outer membrane (P-OM). Our analyses revealed specific roles for the thylakoid lumen in photosynthesis and energy generation, as well as roles for the periplasm in metabolite transport and binding, cell motility, and cell wall maintenance. Forty proteins localized to both the thylakoid lumen and the P-OM; however, their biological functions remain unclear. We also analyzed the correlation between signal sequence characteristics and differential protein localization to either the thylakoid lumen or the P-OM. In PCC 7002, as well as Synechocystis sp. PCC 6803 and Nostoc sp. PCC 7120, thylakoid lumen proteins translocated across membranes via the Secretory (Sec) system possessed more hydrophobic and alpha-helical signal sequence H-regions than P-OM proteins. The signal sequences of homologous proteins in Gloeobacter violaceus PCC 7421, a cyanobacterial species with a combined thylakoid lumen and periplasmic space, did not exhibit such differences. Therefore, the pattern of increased H-region hydrophobicity and alpha helix content is specific to cyanobacteria with a separate thylakoid lumen space and likely contributes to proper protein sorting between the thylakoid lumen and periplasm.

Plant Sciences↗
DOE OSTI2024

Topological Green’s Function Zeros in an Exactly Solved Model and Beyond

The interplay of topological electronic band structures and strong interparticle interactions provides a promising path towards the constructive design of robust, long-range entangled many-body systems. As a prototype for such systems, we here study an exactly integrable, local model for a fractionalized topological insulator. Using a controlled perturbation theory about this limit, we demonstrate the existence of topological bands of zeros in the exact fermionic Green’s function and show that in this model they do affect the topological invariant of the system, but not the quantized transport response. Close to (but prior to) the Higgs transition signaling the breakdown of fractionalization, the topological bands of zeros acquire a finite “lifetime.” We also discuss the appearance of edge states and edge zeros at real space domain walls separating different phases of the system. This model provides a fertile ground for controlled studies of the phenomenology of Green’s function zeros and the underlying exactly solvable lattice gauge theory illustrates the synergetic cross pollination between solid-state theory, high-energy physics, and quantum information science.

Bollmann, Steffen↗
DOE OSTI2020

Hierarchical morphologies in co-sputter deposited thin films

Co-depositions of immiscible alloy films at specific processing conditions have yielded hierarchical microstructures which consist of distinct features at multiple length scales, often agglomerates and concentration modulations on the sub-micrometer-scale and fine nanoprecipitates in a matrix on the nanoscale. The present work examined a series of immiscible alloy systems: Cu-Mo, Cu-Ag, Cu-Fe, Cu-Ta, Mo-Ag, Cu-Mo-Ag, to determine the kinetic conditions favorable for hierarchical organization and the formation mechanism of such structures. Thin films of six immiscible systems were sputter co-deposited over a range of deposition rates from 0.12 to 2 nm/s and various temperatures from 400 to 800°C. The resulting microstructures indicate that hierarchical structures form with sufficient disparity in kinetic energy between the constituent atoms, one species being highly mobile (A) and the other relatively immobile (B). This condition arises typically at elevated deposition temperatures and reduced deposition rates but is also alloy dependent. The hierarchical structures form during deposition via phase separation and self-organization processes across the multiple length scales. The adatoms diffuse on the film surface with the highly mobile species swiftly agglomerating into A-rich domains within which B-rich nanoprecipitates form, often self-organizing into periodic arrays. The smallest B-rich nanoprecipitates in the A-rich domains are found to be coherent and in a metastable crystal structure (B taking the structure of A), but coarser precipitates that exhibit the equilibrium structure of B element. The A-rich domains are surrounded by a B-rich matrix that phase-separates into a concentration modulated structure. In conclusion, the observations are interpreted via a model incorporating material properties and process parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2021

3D-Printable Inks for Energy and Environmental Applications

Partnering additive manufacturing (3D printing) with functional nanomaterial-based inks has the potential to push the properties and performance of advanced materials beyond previous capabilities. This is particularly true in energy and environmental applications. Graphene, 2D materials, and ceramic-based inks, when coupled with 3D printing technologies like Direct Ink Writing (DIW), also called “robocasting,” have shown promise to greatly enhance the performance of batteries, supercapacitors, reactors, and separator devices. Robocasting enables the printing of large-scale electrodes for energy applications with micron resolution by using high concentration viscous inks.

36 MATERIALS SCIENCE↗
DOE OSTI2021

University of Minnesota, Twin Cities Final Scientific/Technical Report Small Scale Ammonia Synthesis Using Stranded Wind Energy

Ammonia absorber columns offer an alternative separation unit to replace condensation in the Haber-Bosch synthesis loop. Metal halide salts can selectively separate ammonia from the reactor outlet gas mixture and incorporate it into their crystal lattice with remarkably high thermodynamic capacity. While the salts’ working capacity can be limited and unstable when they are in their pure form, the capacity is stable and can be high when using a porous ceramic support. In this project, we found optimal conditions for sorbent fabrication, we demonstrated benchmark levels of uptake and release of ammonia, and we fabricated and demonstrated a prototype at a scale of 1 kg/day ammonia. This task allowed us to assess improvement in the techno-economic prospects for this new separation approach, making viable more distributed production of green ammonia from geographically dispersed renewable energy sources.

08 HYDROGEN↗
DOE OSTI2023

Crystalline versus Glassy Nature of Iron Phosphate Waste Forms Subjected to Different Slow Cooling Curves

This report provides experimental details and associated results on the elemental distributions (compositions), crystalline/amorphous phase distributions, and microstructures for iron phosphate reference materials (DPF5-336) made with different cooling curves and starting from different temperatures (i.e., 1050°C and 1200°C). The primary goal of this work was to evaluate the properties of the DPF5- 336 reference material after it was melted and cooled at different rates to simulate the cooling profile of different types of canisters. Crystal fractions across the SCC#2, SCC#3, and SCC#5 samples were all similar ranging in crystal content of 35.66–41.14 mass% with amorphous fractions being the balance (64.34–58.86 mass%, respectively). This shows that the heat treatment profile did not seems to greatly affect either the total crystal content or the phase distributions. The quenched sample was almost completely amorphous (99.55 mass%) with very small peaks identified as Li 3 Fe 2 (PO 4 ) 3 whereas the SCC-treated materials showed peaks for what appear to be ten separate phases present in various concentrations. Another goal of these experiments was to see how the phase distribution affected chemical durability of these waste forms, but that information is being collected at Argonne National Laboratory and will be published in a separate report

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Waste-to-Energy (WTE)-derived Low-Carbon-Footprint Concrete (LCFC)

The construction industry is estimated to generate around 600 million tons of concrete and demolition waste annually in the US. In comparison, Waste-To-Energy (WTE) plants generate about 6.6 million tons of ash from the combustion of municipal solid waste.1–4 Research has been ongoing for decades to upcycle WTE-ash and C&D waste.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Designing an Optimal Sensor Network via Minimizing Information Loss

Optimal experimental design is a classic topic in statistics, with many well-studied problems, applications, and solutions. The design problem we study is the placement of sensors to monitor spatiotemporal processes, explicitly accounting for the temporal dimension in our modeling and optimization. We observe that recent advancements in computational sciences often yield large datasets based on physics-based simulations, which are rarely leveraged in experimental design. We introduce a novel model-based sensor placement criterion, along with a highly-efficient optimization algorithm, which integrates physics-based simulations and Bayesian experimental design principles to identify sensor networks that “minimize information loss” from simulated data. Our technique relies on sparse variational inference and (separable) Gauss-Markov priors, and thus may adapt many techniques from Bayesian experimental design. We validate our method through a case study monitoring air temperature in Phoenix, Arizona, using state-of-the-art physics-based simulations. Our results show our framework to be superior to random or quasi-random sampling, particularly with a limited number of sensors. We conclude by discussing practical considerations and implications of our framework, including more complex modeling tools and real-world deployments.

54 ENVIRONMENTAL SCIENCES↗