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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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67 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Sequential multidimensional heteroepitaxy of chalcogen-sharing 3D ZnSe and 2D MoSe 2 with quasi van der Waals interface engineering

Two-dimensional (2D) materials are emerging as a promising platform for epitaxial growth, largely free from the constraints of lattice constant and thermal expansion coefficient mismatches. Among them, transition metal dichalcogenides (TMDs), known for their superior electrical properties, are ideal for ultrathin semiconductor applications. Their unique epitaxial characteristics enable seamless integration with 3D materials, facilitating the development of gate stacks and heterojunction devices. In this regard, developing a process for growing high-quality 3D epitaxial materials before and after the growth of 2D TMDs and understanding the 2D/3D interface are crucial. This study demonstrates the sequential growth of fully epitaxial ZnSe/MoSe 2 /ZnSe heterostructures using metal-organic chemical vapor deposition. ZnSe and MoSe 2 , sharing chalcogen elements, enable large-area quasi van der Waals epitaxy with sharp interfaces without intermediate phase. Multiscale analysis involving transmission electron microscopy and density functional theory calculation reveals lattice commensurability, van der Waals gaps, termination, and interfacial reconstruction. Understanding these interactions is crucial for advancing multidimensional integration of 2D and 3D materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

PERKS: a Locality-Optimized Execution Model for Iterative Memory-bound GPU Applications

Iterative memory-bound solvers commonly occur in HPC codes. Typical GPU implementations have a loop on the host side that invokes the GPU kernel as much as time/algorithm steps there are. The termination of each kernel implicitly acts the barrier required after advancing the solution every time step. We propose an execution model for running memory-bound iterative GPU kernels: PERsistent KernelS (PERKS). In this model, the time loop is moved inside persistent kernel, and device-wide barriers are used for synchronization. We then reduce the traffic to device memory by caching subset of the output in each time step in the unused registers and shared memory. PERKS can be generalized to any iterative solver: they largely independent of the solver's implementation. We explain the design principle of PERKS and demonstrate effectiveness of PERKS for a wide range of iterative 2D/3D stencil benchmarks (geomean speedup of 2.12x for 2D stencils and 1.24x for 3D stencils over state-of-art libraries), and a Krylov subspace conjugate gradient solver (geomean speedup of 4.86x in smaller SpMV datasets from SuiteSparse and 1.43x in larger SpMV datasets over a state-of-art library). All PERKS-based implementations available at: https://github.com/neozhang307/PERKS.

Zhang, Lingqi↗
DOE OSTI2021

Solid-state NMR of unlabeled plant cell walls: high-resolution structural analysis without isotopic enrichment

Abstract Background Multidimensional solid-state nuclear magnetic resonance (ssNMR) spectroscopy has emerged as an indispensable technique for resolving polymer structure and intermolecular packing in primary and secondary plant cell walls. Isotope ( 13 C) enrichment provides feasible sensitivity for measuring 2D/3D correlation spectra, but this time-consuming procedure and its associated expenses have restricted the application of ssNMR in lignocellulose analysis. Results Here, we present a method that relies on the sensitivity-enhancing technique Dynamic Nuclear Polarization (DNP) to eliminate the need for 13 C-labeling. With a 26-fold sensitivity enhancement, a series of 2D 13 C– 13 C correlation spectra were successfully collected using the unlabeled stems of wild-type Oryza sativa (rice). The atomic resolution allows us to observe a large number of intramolecular cross peaks for fully revealing the polymorphic structure of cellulose and xylan. NMR relaxation and dipolar order parameters further suggest a sophisticated change of molecular motions in a ctl1 ctl2 double mutant: both cellulose and xylan have become more dynamic on the nanosecond and microsecond timescale, but the motional amplitudes are uniformly small for both polysaccharides. Conclusions By skipping isotopic labeling, the DNP strategy demonstrated here is universally extendable to all lignocellulose materials. This time-efficient method has landed the technical foundation for understanding polysaccharide structure and cell wall assembly in a large variety of plant tissues and species.

09 BIOMASS FUELS↗
DOE OSTI2024

Community Geothermal: Soil Conductivity, Borehole Design, Energy Models, and Load Data for a Residential System Development - Hinesburg, VT

This dataset contains materials from the Coalition for Community-Supported Affordable Geothermal Energy Systems (C2SAGES) project, which evaluated the techno-economic feasibility of a community geothermal system for a residential development in Hinesburg, VT. The dataset includes detailed soil conductivity test reports, energy models, borehole design reports, hourly energy loads for heating, cooling, and hot water, and design layouts. EnergyPlus was used to model building energy loads, and Modelica software was applied for geothermal loop sizing based on these loads and soil conductivity results. Python scripts for network design further refined the models. Key files include PDF reports on borehole design (with projections for 1-year, 15-year, and 30-year systems), soil conductivity test results, EnergyPlus modeling outputs, and 2D/3D design drawings in PDF, DWG, and DXF formats. Python notebooks for network design and OnePipe model files are also provided, with Modelica required for viewing certain files. Outputs and modeling data are in various formats including CSV, JPG, HTML, and IDF, with units and data clearly labeled to support understanding of system design and performance for the proposed geothermal solution.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

ECP Report: Update on Proxy Applications and Vendor Interactions

The ExaLearn miniGAN team (Ellis and Rajamanickam) have released miniGAN, a generative adversarial network(GAN) proxy application, through the ECP proxy application suite. miniGAN is the first machine learning proxy application in the suite (note: the ECP CANDLE project did previously release some benchmarks) and models the performance for training generator and discriminator networks. The GAN's generator and discriminator generate plausible 2D/3D maps and identify fake maps, respectively. miniGAN aims to be a proxy application for related applications in cosmology (CosmoFlow, ExaGAN) and wind energy (ExaWind). miniGAN has been developed so that optimized mathematical kernels (e.g., kernels provided by Kokkos Kernels) can be plugged into to the proxy application to explore potential performance improvements. miniGAN has been released as open source software and is available through the ECP proxy application website (https://proxyapps.exascaleproject.ordecp-proxy-appssuite/) and on GitHub (https://github.com/SandiaMLMiniApps/miniGAN). As part of this release, a generator is provided to generate a data set (series of images) that are inputs to the proxy application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

AOI [1]: Passive Wireless Sensor Systems Fabricated by Direct-Writing for Temperature and Health Monitoring of Energy Systems in Harsh-Environments (Final Report)

Researchers at West Virginia University (WVU) propose to demonstrate a wireless, high-temperature sensor system for monitoring the temperature and health of energy-system components. The active sensor and electronics for wireless communication will be composed entirely of an electroceramic materials (conductive ceramics) which are capable of withstanding the harsh-environments required for fossil energy-based technologies. This work will focus primarily on the fabrication and testing of temperature (thermocouples and thermistors) and health (strain/stress and crack propagation sensors) that function at extreme temperatures (up to 700-1700ºC). The electronics will accompany the high-temperature sensor, which will include a passive wireless communication circuit that allows the transmission of the data based on the LCR resonance principle to a near-by reader antenna. This passive transmission of data will reduce the need for interconnect wires near the active, and possibly rotating, energy-system component. The research will include process development to permit the 2D/3D direct-writing of the entire sensor and communication circuit onto the energy-system component. The direct-writing will be facilitated by using silicon-based polymer-derived precursors to form the high-temperature, stable electroceramic compositions. In addition, methods for direct-writing the circuit onto a fugitive carrier substrate will be completed, which will permit a “peel-and-stick”-like transfer of the sensor circuit to the energy-system component. This feature will allow the economical and precise placement of the sensor circuit onto components of various shapes and locations, without altering the geometry and active features of the manufactured component, or the removal (or decommissioning) of the component for installation. The proposed work will be directed at the following areas: 1) Investigation of phase formation, sintering/grain growth, and electrical properties of polymer-derived electroceramic composites; 2) Definition of processes to direct-write through ink-jet and robo-casting the polymer-derived electroceramic composites onto oxide and polymer surfaces; 3) Development of methods to form monolithic "peel-and-stick" preforms that will efficiently transfer the sensor circuit to ceramic surfaces after thermal treatment; 4) Design of passive wireless LCR circuits and receiver (reader) antennas for communication and testing at high temperatures; 5) Investigation of the passive wireless sensor system developed (and method of transferring sensor system) for temperature and stress/strain measurements on a SOFC repeat unit and a singular gas turbine blade prototype as example applications.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

3-D Printed Electro-Magnetic Objects for THz Communications

Advanced materials and manufacturing techniques will pave the path towards high quality electro-magnetic circuits that operate up through THz and into optics regime. Digital additive manufacturing (AM) techniques offer game-changing potential for large scale manufacturing of Radio-frequency (RF) circuits and system in custom 2D/3D geometries. The technical collaboration will explore the design flexibility and product customization capabilities of additive manufacturing techniques to process magnetic materials in custom 3D geometries with tailored dielectric properties and frequency response characteristics. Transformation of an RF circuit design idea into a 3D printed system using additive manufacturing techniques will bring together the elements of advanced materials, additive integration, and low-cost manufacturing for future advanced wireless communication systems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

CRN Modeling of Ammonia RQL Combustion using a Partially-Stirred Reactor Approach

Ammonia is a promising alternative to hydrogen with high energy density and favorable storage and transport characteristics. However low flammability and a propensity for high nitrogen oxide (NOx) emissions make direct utilization challenging. Recently, two-stage rich-quench-lean (RQL) combustion strategies have shown promise in achieving low NOx emissions with ammonia. In this approach, the rich stage serves to oxidize a portion of the fuel, while thermally decomposing as much of the remaining ammonia as possible, generating hydrogen. In the second (lean) stage, air is rapidly introduced, burning out the hydrogen and residual ammonia. Two-stage RQL combustion of ammonia has been investigated in the open literature both experimentally and numerically. In general, idealized chemical reactor network (CRN) models predict NOx concentrations below that of 2D/3D computational fluid dynamics models and experiments. The primary drivers of these discrepancies may be largely attributed to finite rate mixing non-adiabatic operation. The typical CRN model is comprised of a perfectly-stirred-reactor (PSR), followed by a plug-flow-reactor (PFR), meant to represent the flame, and post-flame zones, respectively. In the two-stage RQL approach two PSR-PFR networks are arranged sequentially, corresponding to the rich and lean stages, with secondary air injection in between. In the authors’ past work, this arrangement has demonstrated the significant sensitivity of exit NOx to the rich stage equivalence ratio, while the amount of secondary air injection was shown to be less critical. In this paper, the CRN model is extended to (1) include the impacts of heat loss and (2) utilize a partially-stirred-reactor (PaSR) approach to study the impacts of mixing on emissions performance. Varying amounts of heat loss are applied to the rich relaxation zone to understand emissions performance and changes to optimization of equivalence ratio and residence time. Premixed and non-premixed configurations are considered in the rich stage PaSR, with varying degrees of mixing intensity to study the interaction between mixing, transport, and kinetic timescales. Critically, the impact of mixing between hot products and secondary air injection is studied to understand practical injector needs. Results show unburnt ammonia leaving the rich stage as a primary contributor to NOx emissions – driven both by increased heat loss and reduced mixing rates. Furthermore, heat losses have shown to create conditions which are conducive to increased N2O formation in the lean stage. The results of this study will be considered in the context of developing optimized two-stage RQL combustors for ammonia..

advanced gas turbines↗
DOE OSTI2025

Block Island Noise Modeling Data

Noise propagation near Block Island was simulated to assess environmental impacts of impact pile driving during wind turbine construction. Computational models complement field-recorded acoustic data, providing insights into sound attenuation, spectral variability, and propagation dynamics. The dataset includes: 1. Propagation Models: Simulated underwater sound fields documenting sound pressure and directional variability across frequency bands and distances. 2. Spectral Analysis (LTSA): Long-term averages and processed outputs calculating acoustic intensity over time. 3. Visualization Files: Graphs, 2D/3D simulation results, and reference calculations used in sound modeling.

17 WIND ENERGY↗
DOE OSTI2021

A REDUCED ORDER MODELING APPROACH TO PROBABILISTIC CREEP-DAMAGE PREDICTIONS IN FINITE ELEMENT ANALYSIS

This paper introduces a computationally efficient Reduced Order Modeling (ROM) approach for the probabilistic prediction of creep-damage failure. Component-level probabilistic simulations are needed to assess the reliability and safety of high-temperature components. Full-scale probabilistic creep-damage modeling in finite element (FE) approach is computationally expensive requiring many hundreds of simulations to replicate the uncertainty of component failure. To that end, ROM is proposed to minimize the elevated computational cost while controlling the loss of accuracy. It is proposed that full-scale probabilistic simulations can be completed in 1D at a reduced cost, the extremum conditions extracted, and those conditions applied for lower-cost 2D/3D probabilistic simulations of components that capture the mean and uncertainty of failure. The probabilistic Sine-hyperbolic (Sinh) model is selected which in previous work was calibrated to alloy 304 stainless steel. The Sinh model includes probability density functions (pdfs) for test condition (stress and temperature), initial damage (i.e. microstructure), and material properties uncertainty. The Sinh model is programmed into ANSYS finite element software using the USERCREEP.F material subroutine. First, the Sinh model and FE code are subject to verification and validation to ensure the accuracy of the simulations. Numerous Monte Carlo simulations are executed in a 1D model to generate probabilistic creep deformation, damage, and rupture data. This data is analyzed and the probabilistic parameters corresponding to extreme creep response are extracted. The ROM concept is applied where only the extreme conditions are applied in the 2D probabilistic prediction of a component. The probabilistic predictions between the 1D and 2D geometry is compared to assess ROM for creep. The accuracy of the probabilistic prediction employing the ROM approach will potentially reduce the time and cost of simulating complex engineering systems. Future studies will introduce multi-stage Sinh, stochasticity, and spatial uncertainty for improved prediction.

36 MATERIALS SCIENCE↗
DOE OSTI2020

HOSS: an implementation of the combined finite-discrete element method

Nearly thirty years since its inception, the combined finite-discrete element method (FDEM) has made remarkable strides in becoming a mainstream analysis tool within the field of Computational Mechanics. FDEM was developed to effectively “bridge the gap” between two disparate Computational Mechanics approaches known as the finite and discrete element meth-ods. At Los Alamos National Laboratory (LANL) researchers developed the Hybrid Optimization Software Suite (HOSS) as a hybrid multi-physics platform, based on FDEM, for the simulation of solid material behavior complemented with the latest technological enhancements for full fluid–solid interaction. Furthermore, in HOSS, several newly developed FDEM algorithms have been implemented that yield more accurate material deformation formulations, inter-particle interaction solvers, and fracture and fragmentation solutions. Additionally, an explicit computational fluid dynamics solver and a novel fluid–solid interaction algorithms have been fully integrated (as opposed to coupled) into the HOSS’ solid mechanical solver, allowing for the study of an even wider range of problems. Advancements such as this are leading HOSS to become a tool of choice for multi-physics problems. Finally, HOSS has been successfully applied by a myriad of researchers for analysis in rock mechanics, oil and gas industries, engineering application (structural, mechanical and biomedical engineering), mining, blast loading, high velocity impact, as well as seismic and acoustic analysis. This paper intends to summarize the latest development and application efforts for HOSS.

58 GEOSCIENCES↗