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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Design and Simulation of a MEMS Structure for Electrophoretic and Dielectrophoretic Separation of Particles by Contactless Electrodes

Rapid identification of pathogenic bacterial species is an important factor in combating public health problems such as E. coli contamination. Food and waterborne pathogens account for sickness in 76 million people annually (CDC). Diarrheagenic E. coli is a major source of gastrointestinal illness. Severe sepsis and Septicemia within the hospital environment are also major problems. 75 1,000 cases annually with a 30-50% mortality rate (Crit Care Med, July '01, Vol. 29, 1303-10). Patient risks run the continuum from fever to organ failure and death. Misdiagnosis or inappropriate treatment increases mortality. There exists a need for rapid screening of samples for identification of pathogenic species (Certain E. coli strains are essential for health). Critical to the identification process is the ability to isolate analytes of interest rapidly. This poster discusses novel devices for the separation of particles on the basis of the dielectric properties, mass and surface charge characteristics is presented. Existing designs involve contact between electrode surfaces and analyte medium resulting in contamination of the electrode bearing elements Two different device designs using different bulk micromachining MEMS processes (PolyMUMPS and a PyrexBIGold electrode design) are presented. These designs cover a range of particle sizes from small molecules through eucaryotic cells. The application of separation of bacteria is discussed in detail. Simulation data for electrostatic and microfluidic characteristics are provided. Detailed design characteristics and physical features of the as fabricated PolyMUMPS design are provided. Analysis of the simulation data relative to the expected performance of the devices will be provided and subsequent conclusions discussed.

Shaw, Harry C.↗
NASA NTRS2003

Coordination of Lower Limb Joints During Locomotion: The Effects of Vestibulo-Ocular Reflex Adaptation

Controlling locomotion while maintaining a stable gaze requires precise coordination between several, interdependent full-body sensorimotor subsystems (Bloomberg and Mulavara, 2003; McDonald, et al., 1997). The overall goal of this study is to determine how this full-body gaze stabilization system responds to adaptive changes in vestibuloocular reflex (VOR) function. Locomotion involves cyclical physical interactions (impacts) with the environment. Hence, focusing on a target and maintaining visual acuity during this activity may require mechanisms to manage the energy flow, so it does not disrupt the visual and vestibular sensory information processing that stabilizes gaze. It has been shown that increasing the difficulty of a gaze task (reading numbers on a screen as opposed to simply focusing on a central dot pattern) resulted in an increase in the amount of knee flexion movement during the critical phase immediately following the heel strike event (Mulavara and Bloomberg, 2003). The increase in knee flexion during the stance phase of the gait cycle has been suggested to function as a shock absorbing mechanism associated with the rapid weight transfer from the trailing to the leading leg during walking. To understand this full-body coordination, the relative contributions of each component and the resulting effects should be assessed. In this study, we hypothesized that VOR adaptation would result in a reorganization of the lower limb joint coordination during treadmill walking in a manner to facilitate the gaze stabilization task and preserve locomotor function.

Miller, Chris↗
NASA NTRS2009

One NASA PEM qualification standard : comparison of JPL and GSFC standards

Although use of Plastic Encapsulated Microelectronics (PEMs) in space applications is discouraged, their use is mandatory for selected applications involving the need for advanced technology and small packages. Various space systems designers and manufacturers have developed methods to qualify and screen PEMs. In general, each procedure is different. The purpose of this fiscal year’s investigation is to initiate a process to coordinate the efforts at various NASA centers to eventually develop a One NASA method. Part of this activity includes sharing of test data and PEM qualification methodologies. Various experts in the NASA community were identified and contacted to support this effort. We were successful in finding such experts at GSFC, APL and the Constellation office (Orion and Ares). All these experts provided typical qualification program plans. Since funding was severely restricted, it was decided to concentrate on coordination activity with GSFC. GSFC is planning a new version of IEEE-INST-002 section applying to PEMs. The GSFC expert (Dr. Alexander Teverovsky) provided a detailed assessment of the differences between the planned new version of IEEE-INST-002 and the JPL-D-19426 (JPL guideline) as well as a summary rationale for the decisions within the IEEE-INST-002. It should be noted that GSFC’s assessment of IEEE-INST-002 in the area of PEMs is not finalized. JPL is also considering changes in PEM qualification methodologies based on test data from recent qualification testing for their newer Projects (MSL, Grail, Juno). A spreadsheet delineating the differences between the JPL standard and the GSFC standard is presented.

Cooper, Mark↗
DOE OSTI2025

Energy Scheduling-based Operating Envelopes including a Distribution System Branch Screening Algorithm

This paper presents an energy scheduling-based formulation for computing operating envelopes including a distribution branch screening algorithm, termed DBS-ES. The contribution of the paper is two-fold: firstly, it presents an innovative methodology for calculating operating envelopes using energy scheduling (baseline), and secondly, it enhances this methodology by incorporating a custom distribution branch screening algorithm (DBS-ES). The custom algorithm leverages power system knowledge to reduce both model build time and total processing time while maintaining the same scheduling results as the baseline. The effectiveness of the proposed approach is demonstrated through experiments on the IEEE13, IEEE123, and EPRI Secondary test feeders. Results highlight a 24.5% decrease in model build time and an 8.17% decrease in total processing time when using DBS-ES compared to the baseline, specifically for the IEEE123 test feeder. Additionally, the paper briefly discusses the influence of utility-controlled storage on computing operating envelopes, noting a general incre

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Integrated Computational Materials and Mechanical Modeling for Additive Manufacturing of Alloys with Graded Structure Used in Fossil Fuel Power Plants

Wire-arc additive manufacturing (WAAM) has demonstrated its unique capability of producing large-size alloy components with a significantly reduced fabrication time and enhanced geometry design freedom. In this project, the team has developed an ICME (Integrated Computational Materials Engineering) modeling framework, which supports the WAAM of the AUSC (Advanced Ultra-Supercritical) power plant components. The manufacturing design has been applied to Inconel 740H, steel P91, as well as the dissimilar alloy components between steel P91 and Inconel 740H. The ICME model framework is developed by considering two types of modeling. First, mechanistic modeling has been applied to control the printing quality and understand the sequence of the dissimilar printing of the wall structure. The following models have been included in the developed ICME framework: finite element thermal model, grain structure model, residual stress simulation, crystal plasticity model, CALPHAD-based precipitation kinetic model, phase stability prediction, thermal expansion predictive model, and heuristic creep model. Secondary, a physics-based machine learning model has also been developed based on the ICME model structure. The machine learning model development is based on the ICME model prediction with calibration of the experiments. In addition, the WAAM has been utilized as a high-throughput experimental tool rapidly generating a gradient of alloy composition to facilitate experimental database generation for process-structure-property relationships. Such a database directly supported the ICME-enhanced machine learning, which further assisted in intermediate composition block design between P91 and 740H. A high-throughput screening study of the oxidation resistance has been performed based on such high-throughput experimentation. Based on the computational design, several dissimilar alloy manufacturing with post-heat treatment have been performed with a comprehensive evaluation of mechanical performance, including hardness mapping, yield strength, creep resistance. In this project, the single component of P91 and 740H processed by WAAM after heat treatment designed by ICME has demonstrated higher performance in yield strength and creep resistance than the wrought materials. The P91 sample prepared by WAAM with ICME-designed heat treatment performs better than P92 in creep resistance. The designed graded alloy printing with intermediate block shows a promising performance that exceeds the traditional welding. Moreover, the current research indicates the high need for location-specific design analysis with uncertainty quantification, an important topic that deserves more dedicated research. The achievement of this project demonstrated the promising future of WAAM in structural alloy manufacturing for energy power plant development. Successful printing requires synergetic efforts made by manufacturing, mechanical, and materials sciences.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Screening Analysis of Terrestrial Enhanced Rock Weathering of Igneous Rocks and Industrial Waste Materials

This poster, presented at the 17th Greenhouse Gas Control Technology Conference, reports on an NETL screening level techno-economic assessment of enhanced weathering (EW). EW is a promising emerging carbon dioxide removal approach that involves harnessing and accelerating the natural weathering process by which atmospheric CO2 passively reacts with exposed alkaline minerals and is removed from the atmosphere. Two primary cases utilizing different sources of alkaline material are considered: (1) utilizing naturally occurring mined igneous rocks, and (2) utilizing industrial waste materials. The analysis highlights that utilizing materials with high weathering potential in suitable locations may result in relatively low levelized cost of captured. NETL is publishing a detailed and transparent report titled “Enhanced Weathering: Techno-Economic and Life Cycle Screening Analysis” that includes more detail on the screening level techno-economic analysis and includes a life cycle analysis.

carbon dioxide removal↗
DOE OSTI2026

Benchtop Autonomous Electrochemical Characterization System for Combinatorial Thin-Film Solid Oxide Electrodes

The design of materials for electrochemical energy conversion is complicated by a vast search space of candidate materials and multifaceted property requirements: multicarrier conductivity, stability, and catalytic activity are all necessary but rarely intersect. Although self-driving laboratories are rapidly rising to address such material optimization problems, the required infrastructure for integrated, large-scale robotic facilities can be cost-prohibitive. Here we develop and evaluate a closed-loop measurement system for efficient screening of proton-conducting oxide electrodes for ceramic fuel cells and electrolyzers, building on top of an existing benchtop instrument and integrating techniques for rapid impedance measurement and automated analysis. This system exemplifies a “minimum viable” self-driving implementation that can deliver substantial benefits with relatively simple infrastructure. Combinatorial thin-film microelectrode libraries are characterized with a recently developed joint time-domain and frequency-domain impedance measurement technique, which provides an order-of-magnitude acceleration relative to conventional impedance spectroscopy. The distribution of relaxation times is extracted from impedance data and analyzed without human intervention. These results feed an active learning and Bayesian optimization process that learns to predict electrochemical impedance as a function of material composition, measurement temperature, oxygen partial pressure, and electrical bias, which further reduces the screening time by tenfold with optimized experimental sequences. We apply this system to Ba⁡(Co,Fe,Zr,Y)⁢O 3−𝛿 combinatorial libraries and evaluate its effectiveness for learning material property trends and optimizing expensive-to-evaluate properties such as activation energy. This offers insights into key methodological aspects of practical autonomous experimentation, including surrogate model validation, cost-aware acquisition functions, and high-throughput data interpretation. Our results demonstrate the efficacy of the system for rapidly gathering information, but also highlight real-world experimental challenges of thin-film degradation and numerical instability in surrogate models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Algal Biomass Conversion to Fuels via Combined Algae Processing (CAP): 2019 State of Technology and Future Research

NREL’s algae state of technology benchmarking efforts focus both on front-end algal biomass production and separately on back-end conversion to fuels through NREL’s “combined algae processing” (CAP) pathway. The production model is based on outdoor long-term cultivation data, enabled by comprehensive algal biomass production trials conducted under the Development of Integrated Screening, Cultivar Optimization, and Verification Research consortium (DISCOVR) efforts, driven by data furnished by Arizona State University (ASU) at the Arizona Center for Algae Technology and Innovation (AzCATI) testbed site. The CAP model is based on experimental efforts conducted under NREL research and development projects. This report focuses on back-end conversion of algal biomass through the CAP pathway, highlighting the 2019 updates to minimum fuel selling price (MFSP). This milestone reports on key process sustainability indicators for the CAP conversion stage including mass and carbon yields to fuels and coproducts, freshwater consumption, and facility power balances/natural gas demands.

09 BIOMASS FUELS↗
DOE OSTI2023

Performance of hydrophobic physical solvents for pre-combustion CO 2 capture at a pilot scale coal gasification facility

Here, in this paper, we present the first pilot plant data for hydrophobic physical solvents for CO 2 and H 2 S removal from coal-derived H 2 -rich syngas. Four physical solvents were tested under pre-combustion CO 2 capture conditions at bench scale and pilot plant scale: one baseline hydrophilic solvent and three hydrophobic solvents. The solvents were: (1) polyethylene-glycol-dimethyl ether (PEGDME), a hydrophilic solvent analog for the commercial process Selexol, (2) tributyl- phosphate (TBP), a commercially available hydrophobic solvent, (3) polyethylene glycol-poly(dimethylsiloxane) (PEG-PDMS-3), and (4) diethyl sebacate (CASSH-1), a novel, computationally screened hydrophobic solvent developed by the National Energy Technology Laboratory (NETL). All solvents were studied under pure gas (CO 2 /N 2 /H 2 /CH 4 ) equilibrium conditions at NETL followed by pilot plant testing with syngas at the University of North Dakota Energy & Environmental Research Center (UND EERC). Long term performance of CASSH-1 and PEDGME was then assessed with results compared to process simulation predictions. Within experimental uncertainties, all solvents showed comparable CO 2 absorption performance at above room temperature operation while the hydrophobic solvents had limited water uptake and low vapor pressure, which alleviates concerns related to corrosion, water absorption, and solvent loss to evaporation. These results indicate low viscosity, low vapor pressure hydrophobic solvents are a promising option for lower cost CO 2 capture from high pressure syngas applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Supercomputing Pipelines Search for Therapeutics Against COVID-19

The urgent search for drugs to combat SARS-CoV-2 has included the use of supercomputers. The use of general-purpose graphical processing units (GPUs), massive parallelism, and new software for high-performance computing (HPC) has allowed researchers to search the vast chemical space of potential drugs faster than ever before. We developed a new drug discovery pipeline using the Summit supercomputer at Oak Ridge National Laboratory to help pioneer this effort, with new platforms that incorporate GPU-accelerated simulation and allow for the virtual screening of billions of potential drug compounds in days compared to weeks or months for their ability to inhibit SARS-COV-2 proteins. Here, this effort will accelerate the process of developing drugs to combat the current COVID-19 pandemic and other diseases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Topographic hydro-conditioning to resolve surface depression storage and ponding in a fully distributed hydrologic model

Land surface depressions play a central role in the transformation of rainfall to ponding, infiltration and runoff, yet digital elevation models (DEMs) used by spatially distributed hydrologic models that resolve land surface processes rarely capture land surface depressions at spatial scales relevant to this transformation. Methods to generate DEMs through processing of remote sensing data, such as optical and light detection and ranging (LiDAR) have favored surfaces without depressions to avoid adverse slopes that are problematic for many hydrologic routing methods. Here, in this study, we present a new topographic conditioning workflow, Depression-Preserved DEM Processing (D2P) algorithm, which is designed to preserve physically meaningful surface depressions for depression-integrated and efficient hydrologic modeling. D2P includes several features: (1) an adaptive screening interval for delineation of depressions, (2) the ability to filter out anthropogenic land surface features (e.g., bridges), (3) the ability to blend river smoothing (e.g., a general downslope profile) and depression resolving functionality. From a case study in the Goodwin Creek Experimental Watershed, D2P successfully resolved 86% of the ponds at a DEM resolution of 10 m. Topographic conditioning was achieved with minimum impact as D2P reduced the number of modified cells from the original DEM by 51% compared to a conventional algorithm. Furthermore, hydrologic simulation using a D2P processed DEM resulted in a more robust characterization on surface water dynamics based on higher surface water storage as well as an attenuated and delayed peak streamflow.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Computational Discovery of Active and Selective Metal‐Nitrogen‐Graphene Catalysts for Electrooxidation of Water to H 2 O 2

A direct electrosynthesis of H 2 O 2 from either O 2 or H 2 O is an attractive strategy to replace the energy-intensive industrial anthraquinone process. Two-electron water oxidation reaction (2e-WOR) offers several advantages over the oxygen reduction reaction such as better mass transfer due to the absence of gas-phase reactants. However, 2e-WOR is a more challenging and less studied process with only a handful of metal oxides exhibiting reasonable activity/selectivity properties. Herein, we employ density-functional-theory calculations to screen a variety of metal-nitrogen-graphene structures for 2e-WOR. As a consequence of scaling between the adsorption energies of reaction intermediates, we determine a linear relation between selectivities for the first and second reaction steps of 2e-WOR, viz. that if selectivity toward adsorbed OH is improved, then selectivity toward H 2 O 2 at the subsequent step is decreased. We also find that selectivity and activity are linearly scaled in such a way that a higher activity (i.e., a lower overpotential) leads to a lower selectivity for the H 2 O 2 formation step. Based on the obtained results several chemistries, e.g., containing NiN x -C moieties, are predicted to rival the best-performing metal oxides such as ZnO and CaSnO 3 in terms of combination of their activity/selectivity characteristics for 2e-WOR.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Frhodo: A program for simulating chemical kinetic measurements and optimizing kinetic mechanisms

Chemical kinetic simulations are frequently used to extract kinetic and mechanistic information from experimental data by fitting simulations to the data. For simple systems of consecutive single channel reactions this is a relatively straightforward task. However, as the complexity of the system increases and particularly for systems involving competitive multi-channel reactions manually optimizing a mechanism to obtain the best fits to a range of experimental data quickly becomes a time-intensive and challenging process, especially when rate coefficients have pressure and temperature dependencies. There is considerable potential for exploiting automated optimization methods to rapidly screen reaction mechanisms and optimize the fit by adjusting rate coefficients within well-defined constraints. A new chemical kinetics simulation program, Frhodo, has been developed for this purpose. The program allows either manual simulation of individual experiments or fully automated optimization against a range of experimental data by adjusting user selected reactions within user defined constraints. Frhodo incorporates machine learning-based optimization routines that work by either minimizing standardized residuals or through Bayesian parameter estimation. Frhodo's optimization capabilities are demonstrated by reexamining two previously studied systems of relevance to combustion. Dissociation of diacetyl followed by recombination of methyl radicals is an example of a sequence of single channel, consecutive reactions. Pyrolysis of 2-methyl furan exemplifies multi-channel, unimolecular reactions that are often encountered and have temperature and pressure dependencies in the rate coefficients of the channels and branching ratios between them. For both systems the optimization routines resulted in solutions similar to the original studies. Finally, comments are made on the strengths and limitations of the approach.

0D simulation↗
DOE OSTI2025

Expediting field-effect transistor chemical sensor design with neuromorphic spiking graph neural networks

Improving the sensitive and selective detection of analytes in a variety of applications requires accelerating the rational design of field-effect transistor (FET) chemical sensors. Achieving high-performance detection relies on identifying optimal probe materials that can effectively interact with target analytes, a process traditionally driven by chemical intuition and time-consuming trial-and-error methods. To address the difficulties in probe screening for FET sensor development, this work presents a methodology that combines neuromorphic machine learning (ML) architectures, specifically a hybrid spiking graph neural network (SGNN), with an enriched dataset of physicochemical properties through semi-automated data extraction using large language models. Achieving a classification accuracy of 0.89 in predicting sensor sensitivity categories, the SGNN model outperformed traditional ML techniques by leveraging its ability to capture both global physicochemical properties and sparse topological features through a hybrid modeling framework. Next-generation sensor design was informed by the actionable insights into the connections between material properties and sensing performance offered by the SGNN framework. Through virtual screening for the detection of per- and polyfluoroalkyl substances (PFAS) as a use case, the effectiveness of the SGNN model was further validated. Density functional theory simulations confirmed graphene as a promising active material for PFAS detection as suggested by the SGNN framework. By bridging gaps in predictive modeling and data availability, this integrated approach provides a strong foundation for accelerating advancements in FET sensor design and innovation.

Ferreira, Rodrigo Pires [Univ. of Chicago, IL (Uni↗
DOE OSTI2021

REopt ® Lite Overview - Resilience Analysis: Clear Sky Tampa Bay [Slides]

Through the Solar Energy Innovation Network (SEIN), the Clear Sky Tampa Bay team, led by the Tampa Bay Regional Planning Council (TBRPC), developed a toolkit to help local governments prioritize sites for solar photovoltaics (PV) and battery energy storage in the context of resilience and emergency management. At a high level, the Clear Sky Tampa Bay process involves: (1) Identifying sites based on community resilience needs and priorities ("Where do we need a resilient energy solution?"); (2) Screening and prioritizing sites for solar PV and storage suitability based on site conditions and other factors; and (3) Using REopt Lite to screen down-selected facilities to prioritize sites based on resilience project economics. This slide deck focuses on Step 3 above, and provides a general overview of REopt Lite and suggestions and examples tailored to the Clear Sky Tampa Bay team about how to use REopt Lite for additional analysis.

14 SOLAR ENERGY↗
DOE OSTI2023

U328 Electrical Reliability Project Soil Sampling and Analysis Plan

Lawrence Livermore National Laboratory's (LLNL’s) Project Management Office (PMO) is planning to install an underground electrical duct bank at the 3200 block of the Livermore Site (project). The proposed project will include a new electrical substation and feeders, demolition and replacement of the U328C utility building with a new structure to the west, re-routing of utilities, and update of the parking lot. This Sampling and Analysis Plan (SAP) outlines the procedures to collect and evaluate environmental samples for disposition of the excavated soil during the project and geotechnical samples for pavement design. This SAP has been prepared and is organized to be consistent with LLNL's Soils Screening and Management Plan (SSMP) (LLNL, 2022), as well as the U.S. Environmental Protection Agency's (EPA) Data Quality Objectives (DQO) process (EPA, 2006). In addition to the environmental samples, geotechnical samples will be collected by Consolidated Engineering Laboratories (CEL) on behalf of PMO. Geotechnical samples will be collected from a dedicated geotechnical boring location or co-located with environmental samples. Collection and evaluation of the geotechnical samples is determined by CEL and is therefore not discussed in this SAP.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

Research study on stellar X-ray imaging experiment, volume 1

The use of microchannel plates as focal plane readout devices and the evaluation of mirrors for X-ray telescopes applied to stellar X-ray imaging is discussed. The microchannel plate outputs were either imaged on a phosphor screen which was viewed by a low light level vidicon or on a wire array which was read out by digitally processing the output of a charge division network attached to the wires. A service life test which was conducted on two image intensifiers is described.

Wilson, H. H.↗
NASA NTRS1991

Improved silicon nitride for advanced heat engines

The results of a four year program to improve the strength and reliability of injection-molded silicon nitride are summarized. Statistically designed processing experiments were performed to identify and optimize critical processing parameters and compositions. Process improvements were monitored by strength testing at room and elevated temperatures, and microstructural characterization by optical, scanning electron microscopes, and scanning transmission electron microscope. Processing modifications resulted in a 20 percent strength and 72 percent Weibull slope improvement of the baseline material. Additional sintering aids screening and optimization experiments succeeded in developing a new composition (GN-10) capable of 581.2 MPa at 1399 C. A SiC whisker toughened composite using this material as a matrix achieved a room temperature toughness of 6.9 MPa m(exp .5) by the Chevron notched bar technique. Exploratory experiments were conducted on injection molding of turbocharger rotors.

Yeh, Harry C.↗