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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Influence of the Anionic Zinc-Adeninate Metal–Organic Framework Structure on the Luminescent Detection of Rare Earth Ions in Aqueous Streams

Rare earth elements (REEs) are critical to numerous technologies; however, a combination of increasing demand, environmental concerns, and monopolistic marketplace conditions has spurred interest in boosting the domestic REE production from sources such as coal utilization byproducts. The economic viability of this approach requires rapid, inexpensive, and sensitive analytical techniques capable of characterizing the REE content during resource exploration and downstream REE processing (e.g., analyzing REE separation, concentration, and purification production steps). Luminescence-based sensors are attractive because many REEs may be sensitized to produce element-specific emission. Hence, a single material may simultaneously detect and distinguish multiple REEs. Metal–organic frameworks (MOFs) can sensitize multiple REEs, but their viability has been hindered by sensitivity and selectivity challenges. Understanding how the MOF structure impacts the REE sensing efficacy is critical to the rational design of new sensors. Here, we evaluate the sensing performance of seven different anionic zinc-adeninate MOFs with different organic linkers and/or structures for the visible-emitting REEs Tb, Dy, Sm, and Eu. The choice of a linker determines which REEs are sensitized and significantly influences their sensitivity and selectivity against competing species (here, Fe(II) and HCl). For a given linker, structural changes to the MOF can further fine-tune the performance. The MOFs produce some of the lowest detection limits (sub-10 ppb for Tb) reported for the aqueous sensitization-based REE detection. Importantly, the most selective MOFs demonstrated the ability to sensitize the REE signal at sub-ppm levels in a REE-spiked acid mine drainage matrix, highlighting their potential for use in real-world sensing applications.

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

FY23 Progress on Computational Modeling of the Water-Based NSTF

This report summarizes the system-level modeling effort by Argonne National Laboratory (Argonne) of the Natural convection Shutdown heat removal Test Facility (NSTF) in FY23. As a continuation of the modeling effort from FY22, this year’s work focuses on improving the RELAP5-3D model developed previously for two-phase flow simulations. The RELAP5-3D model is updated to more accurately capture the heat loss experienced by the facility. The updated model is compared against experimental data for benchmarking purposes of the RELAP5-3D input model. By correctly accounting for heat loss, the updated RELAP5-3D model can now predict the two-phase baseline case more accurately. The onset and the duration of instability are captured well by the model. Furthermore, analyses are performed to better understand the instability mechanism experienced by the flow where the expansion of the boiling boundary in the chimney is studied in details and the fundamental frequencies of the oscillations are obtained. The updated RELAP5-3D model is further compared against four fault conditions, namely the reduction of riser header inlet flow area, depletion of system inventory, blocked riser channels, and static boiling scenario. For each fault condition, minor modifications and tuning are performed to improve the predictions of the model. The purpose of the analyses is to investigate the capability of RELAP5-3D in predicting complex two-phase flows in possible accident scenarios in actual Reactor Cavity Cooling System (RCCS). Overall, the model is able to capture the behaviors and trends of these fault conditions relatively well. Some discrepancies remain between the experimental data and the predictions, many of which are likely due to the differences in the predicted and experimental vapor generation rate. Future work will focus on the continued development of the current RELAP5-3D input model of the NSTF to both improve the accuracy of the model’s predictive capability and continue supporting the experimental program needs. The mutually beneficial relationship between analysis and experimental efforts has become integral to the parent NSTF program, and the greater objective to fully understand and accurately predict the heat removal performance of a full scale RCCS concept.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

MatCal Users Guide: Release 1.3.0

Any continuum mechanics model will require three components: (1) a discretized geometry of the boundary value problem being studied, (2) the partial differential equations to be solved, and (3) the initial conditions and boundary conditions for the problem. To describe material behavior in these computational models, material models contribute to (2) the underlying equations and, occasionally, to (3) the initial conditions for the simulation. These material models can exhibit a mathematical form that is empirically based, based on first principles, or developed from both empirical observations and known physics. In general, these models are meant to represent a class of materials with well understood behavior. As a result, material models have parameters that must be tuned or calibrated so that the model response matches characterization data available for the specific material it is intended to represent when used to simulate a specific system. For simple models, such as isotropic, linear elastic materials in solid mechanics, this calibration process can be a simple analytical calculation directly extracting the parameters from experimental measurements. For complex models that have many inputs and require many characterization datasets to adequately identify the material behavior, the model calibration process can require an inverse problem approach where an optimization is performed to tune the model parameters to the available data.

36 MATERIALS SCIENCE↗
NASA NTRS2017

Dual Extended Kalman Filter for the Identification of Time-Varying Human Manual Control Behavior

A Dual Extended Kalman Filter was implemented for the identification of time-varying human manual control behavior. Two filters that run concurrently were used, a state filter that estimates the equalization dynamics, and a parameter filter that estimates the neuromuscular parameters and time delay. Time-varying parameters were modeled as a random walk. The filter successfully estimated time-varying human control behavior in both simulated and experimental data. Simple guidelines are proposed for the tuning of the process and measurement covariance matrices and the initial parameter estimates. The tuning was performed on simulation data, and when applied on experimental data, only an increase in measurement process noise power was required in order for the filter to converge and estimate all parameters. A sensitivity analysis to initial parameter estimates showed that the filter is more sensitive to poor initial choices of neuromuscular parameters than equalization parameters, and bad choices for initial parameters can result in divergence, slow convergence, or parameter estimates that do not have a real physical interpretation. The promising results when applied to experimental data, together with its simple tuning and low dimension of the state-space, make the use of the Dual Extended Kalman Filter a viable option for identifying time-varying human control parameters in manual tracking tasks, which could be used in real-time human state monitoring and adaptive human-vehicle haptic interfaces.

manual control↗
NASA NTRS1987

Space lab system analysis

An analytical analysis of the HOSC Generic Peripheral processing system was conducted. The results are summarized and they indicate that the maximum delay in performing screen change requests should be less than 2.5 sec., occurring for a slow VAX host to video screen I/O rate of 50 KBps. This delay is due to the average I/O rate from the video terminals to their host computer. Software structure of the main computers and the host computers will have greater impact on screen change or refresh response times. The HOSC data system model was updated by a newly coded PASCAL based simulation program which was installed on the HOSC VAX system. This model is described and documented. Suggestions are offered to fine tune the performance of the ETERNET interconnection network. Suggestions for using the Nutcracker by Excelan to trace itinerate packets which appear on the network from time to time were offered in discussions with the HOSC personnel. Several visits to the HOSC facility were to install and demonstrate the simulation model.

Ingels, F. M.↗
DOE OSTI2021

Improved Time-Stepping Methods in Global to Regional Ocean Modeling (Annual Status Report 2020)

Time stepping algorithms are an important part of ocean models, and strongly influence both the accuracy of solution and performance. There have been a number of projects investigating various improvements for ocean time-stepping schemes in the Model for Prediction Across Scales-Ocean (MPAS-Ocean), a component of the DOE Energy Exascale Earth System Model. Ocean dynamics include fast surface gravity waves, which are two-dimensional, and slower internal waves, which are three-dimensional, so ocean models use a split time-stepping scheme that separates these barotropic and baroclinic modes for efficiency. MPAS-Ocean runs on variable-resolution horizontal meshes, and must scale to tens of thousands of cores and millions of horizontal gridcells. Ocean models require time stepping algorithms that are customized to these needs, and which are tuned for performance on various resolutions and architectures.

58 GEOSCIENCES↗
DOE OSTI2022

Improved Time-Stepping Methods in Global to Regional Ocean Modeling (Annual Status Report)

Time stepping algorithms are an important part of ocean models, and strongly influence both the accuracy of solution and performance. There have been a number of projects investigating various improvements for ocean time-stepping schemes in the Model for Prediction Across Scales-Ocean (MPAS-Ocean), a component of the DOE Energy Exascale Earth System Model. Ocean dynamics include fast surface gravity waves, which are two-dimensional, and slower internal waves, which are three-dimensional, so ocean models use a split time-stepping scheme that separates these barotropic and baroclinic modes for efficiency. MPAS-Ocean runs on variable-resolution horizontal meshes, and must scale to tens of thousands of cores and millions of horizontal gridcells. Ocean models require time stepping algorithms that are customized to these needs, and which are tuned for performance on various resolutions and architectures.

58 GEOSCIENCES↗
DOE OSTI2024

Hyperconjugation-controlled molecular conformation weakens lithium-ion solvation and stabilizes lithium metal anodes

Tuning the solvation structure of lithium ions via electrolyte engineering has proven effective for lithium metal (Li) anodes. Further advancement that bypasses the trial-and-error practice relies on the establishment of molecular design principles. Expanding the scope of our previous work on solvent fluorination, we report here an alternative design principle for non-fluorinated solvents, which potentially have reduced cost, environmental impact, and toxicity. By studying non-fluorinated ethers systematically, we found that the short-chain acetals favor the [gauche, gauche] molecular conformation due to hyperconjugation, which leads to weakened monodentate coordination with Li + . The dimethoxymethane electrolyte showed fast activation to >99% coulombic efficiency (CE) and high ionic conductivity of 8.03 mS cm -1 . The electrolyte performance was demonstrated in anode-free Cu$∥$LFP pouch cells at current densities up to 4 mA cm -2 (70 to 100 cycles) and thin-Li$∥$high-loading-LFP coin cells (200–300 cycles). Overall, we demonstrated and rationalized the improvement in Li metal cyclability by the acetal structure compared to ethylene glycol ethers. We expect further improvement in performance by tuning the acetal structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Detecting Unclassified Electromagnetic Signals for Secure Wireless Communication Using Open Set Recognition

We developed multiple machine learning methods for the detection and classification of new wireless communication waveforms, which is critical for targeted attacks in wireless networks and electronic warfare. Our machine learning models are capable of dynamically detecting security threats in near real time through our advanced open set recognition (OSR) approach. This model has demonstrated significant improvements in the detection of unknown waveforms, thereby enhancing the security and reliability of mission critical communications. Our approach to detecting uncertain security threats is novel; we advanced OSR techniques by incorporating domain knowledge of wireless signals. Specifically, we combined time and frequency domain model features to enhance the model’s performance. Utilizing an OSR approach eliminates the need for training data to be distributed similarly to the deployment environment and removes the requirement for the training set to contains all possible threat classes. This is crucial because it is often infeasible to determine and characterize all potential security threats in advance. Our model were trained on simulated data, generated in partnership with the University at Albany, State of New York. The data set contained a diverse array of wireless signals, including those with additive white Gaussian noise and multipath signals, with and without line of sight. This comprehensive training set allowed us to optimize our models to detect unknown waveforms under various challenging scenarios, such as low signal-to-noise ratios. By training on various waveforms, varying signal-to-noise ratio, and different sample sizes under normal conditions, our models were fine tuned to perform effectively in challenging environments.

99 - GENERAL AND MISCELLANEOUS↗
NASA NTRS2012

Vehicle Detection for RCTA/ANS (Autonomous Navigation System)

Using a stereo camera pair, imagery is acquired and processed through the JPLV stereo processing pipeline. From this stereo data, large 3D blobs are found. These blobs are then described and classified by their shape to determine which are vehicles and which are not. Prior vehicle detection algorithms are either targeted to specific domains, such as following lead cars, or are intensity- based methods that involve learning typical vehicle appearances from a large corpus of training data. In order to detect vehicles, the JPL Vehicle Detection (JVD) algorithm goes through the following steps: 1. Take as input a left disparity image and left rectified image from JPLV stereo. 2. Project the disparity data onto a two-dimensional Cartesian map. 3. Perform some post-processing of the map built in the previous step in order to clean it up. 4. Take the processed map and find peaks. For each peak, grow it out into a map blob. These map blobs represent large, roughly vehicle-sized objects in the scene. 5. Take these map blobs and reject those that do not meet certain criteria. Build descriptors for the ones that remain. Pass these descriptors onto a classifier, which determines if the blob is a vehicle or not. The probability of detection is the probability that if a vehicle is present in the image, is visible, and un-occluded, then it will be detected by the JVD algorithm. In order to estimate this probability, eight sequences were ground-truthed from the RCTA (Robotics Collaborative Technology Alliances) program, totaling over 4,000 frames with 15 unique vehicles. Since these vehicles were observed at varying ranges, one is able to find the probability of detection as a function of range. At the time of this reporting, the JVD algorithm was tuned to perform best at cars seen from the front, rear, or either side, and perform poorly on vehicles seen from oblique angles.

Brennan, Shane↗
DOE OSTI2023

Toughening Brittle Bio‐P3HB with Synthetic P3HB of Engineered Stereomicrostructures

Abstract Poly(3‐hydroxybutyrate) (P3HB), a biologically produced, biodegradable natural polyester, exhibits excellent thermal and barrier properties but suffers from mechanical brittleness, largely limiting its applications. Here we report a mono‐material product design strategy to toughen stereoperfect, brittle bio or synthetic P3HB by blending it with stereomicrostructurally engineered P3HB. Through tacticity ([ mm ] from 0 to 100 %) and molecular weight ( M n to 788 kDa) tuning, high‐performance synthetic P3HB materials with tensile strength to ≈30 MPa, fracture strain to ≈800 %, and toughness to 126 MJ m −3 (>110× tougher than bio‐P3HB) have been produced. Physical blending of the brittle P3HB with such P3HB in 10 to 90 wt % dramatically enhances its ductility from ≈5 % to 95–450 % and optical clarity from 19 % to 85 % visible light transmittance while maintaining desirably high elastic modulus (>1 GPa), tensile strength (>35 MPa), and melting temperature (160–170 °C). This P3HB‐toughening‐P3HB methodology departs from the traditional approach of incorporating chemically distinct components to toughen P3HB, which hinders chemical or mechanical recycling, highlighting the potential of the mono‐material product design solely based on biodegradable P3HB to deliver P3HB materials with diverse performance properties.

Zhang, Zhen↗
DOE OSTI2023

Toughening Brittle Bio‐P3HB with Synthetic P3HB of Engineered Stereomicrostructures

Abstract Poly(3‐hydroxybutyrate) (P3HB), a biologically produced, biodegradable natural polyester, exhibits excellent thermal and barrier properties but suffers from mechanical brittleness, largely limiting its applications. Here we report a mono‐material product design strategy to toughen stereoperfect, brittle bio or synthetic P3HB by blending it with stereomicrostructurally engineered P3HB. Through tacticity ([ mm ] from 0 to 100 %) and molecular weight ( M n to 788 kDa) tuning, high‐performance synthetic P3HB materials with tensile strength to ≈30 MPa, fracture strain to ≈800 %, and toughness to 126 MJ m −3 (>110× tougher than bio‐P3HB) have been produced. Physical blending of the brittle P3HB with such P3HB in 10 to 90 wt % dramatically enhances its ductility from ≈5 % to 95–450 % and optical clarity from 19 % to 85 % visible light transmittance while maintaining desirably high elastic modulus (>1 GPa), tensile strength (>35 MPa), and melting temperature (160–170 °C). This P3HB‐toughening‐P3HB methodology departs from the traditional approach of incorporating chemically distinct components to toughen P3HB, which hinders chemical or mechanical recycling, highlighting the potential of the mono‐material product design solely based on biodegradable P3HB to deliver P3HB materials with diverse performance properties.

Chemistry↗
DOE OSTI2024

Cobalt‐Doped Bismuth Nanosheet Catalyst for Enhanced Electrochemical CO 2 Reduction to Electrolyte‐Free Formic Acid

Electrochemical carbon dioxide (CO 2 ) reduction reaction (CO 2 RR) to valuable liquid fuels, such as formic acid/formate (HCOOH/HCOO − ) is a promising strategy for carbon neutrality. Enhancing CO 2 RR activity while retaining high selectivity is critical for commercialization. To address this, we developed metal-doped bismuth (Bi) nanosheets via a facile hydrolysis method. These doped nanosheets efficiently generated high-purity HCOOH using a porous solid electrolyte (PSE) layer. Among the evaluated metal-doped Bi catalysts, Co-doped Bi demonstrated improved CO 2 RR performance compared to pristine Bi, achieving ~90 % HCOO − selectivity and boosted activity with a low overpotential of ~1.0 V at a current density of 200 mA cm −2 . In a solid electrolyte reactor, Co-doped Bi maintained HCOOH Faradaic efficiency of ~72 % after a 100-hour operation under a current density of 100 mA cm −2 , generating 0.1 M HCOOH at 3.2 V. Density functional theory (DFT) results revealed that Co-doped Bi required a lower applied potential for HCOOH generation from CO 2 , due to stronger binding energy to the key intermediates OCHO* compared to pure Bi. In conclusion, this study shows that metal doping in Bi nanosheets modifies the chemical composition, element distribution, and morphology, improving CO 2 RR catalytic activity performance by tuning surface adsorption affinity and reactivity.

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

Building Durable Multimetallic Electrocatalysts from Intermetallic Seeds

When combined with earth-abundant metals, Pt-based alloy nanoparticles (NPs) can be cost-effective electrocatalysts. However, these NPs can experience leaching of non-noble-metal components under harsh electrocatalytic conditions. In this work, the Skrabalak group has demonstrated a novel NP construct in which Pt-based random alloy surfaces are stabilized against non-noble-metal leaching by their deposition onto intermetallic seeds. These core@shell NPs are highly durable electrocatalysts, with the ability to tune catalytic performance by the core@shell architecture, surface alloy composition, and NP shape. This versatility was demonstrated in a model system in which random alloy (ra-) PtM surfaces were deposited onto ordered intermetallic (i-) PdCu seeds using seed-mediated co-reduction (SMCR). In the initial demonstration, ra-PtCu shells were deposited on i-PdCu seeds, with these core@shell NPs exhibiting higher specific and mass activities for the oxygen reduction reaction (ORR) when compared to similarly sized ra-PtCu NPs. These NPs also showed outstanding durability, maintaining ~85% in specific activity after 5000 cycles. Characterization of the NPs after use revealed minimal loss of Cu. The activity enhancement was attributed to the strained surface that arises from the lattice mismatch between the intermetallic core and random alloy surface. The outstanding durability was attributed to the ordered structure of the intermetallic core. The origin of this durability enhancement was investigated by classical molecular dynamics simulations, where Pt atoms were found to have a lower potential energy when deposited on an intermetallic core than when deposited on a random alloy core. Also, ordering of Cu atoms at the core@shell interface appears to enhance the overall binding between the core and the shell materials. Inspired by this initial demonstration, SMCR has been used to achieve shells of different random alloy compositions, PtM (M = Ni, Co, Cu, or Fe). This advance is significant because ligand effects vary as a function of PtM identity and Pt/M ratio. These features also influence the degree of surface strain imparted from the lattice mismatch between the core and shell materials. Like the initial demonstration, standout features of these core@shell NPs were high durability and resistance to non-noble metal leaching. Moving forward, efforts have been directed toward integrating shape-control to this core@shell NP construct. This integration is motivated by the shape-dependent catalytic performance of NPs derived from the selective expression of specific facets. Considering the initial i-PdCu@ra-PtCu system, NPs with a cubic shape have been achieved by judicious selection of capping ligands during SMCR. Evaluation of these NPs as catalysts for the electrooxidation of formic acid found that the nanocubic shape enhances catalytic performance compared to similar core@shell NPs with a spherical morphology. We envision that SMCR can be applied to other NP systems to achieve highly durable catalysts as the syntheses of monodisperse and shape-controlled intermetallic seeds are advanced. This Account highlights the role of intermetallic cores in providing more durable electrocatalysts. More broadly, the versatility of SMCR is highlighted as a route to integrate architecture, alloy surfaces, and shape within one NP system, and how this achievement is inspiring new high-performance and robust catalysts is discussed.

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

Influence of Linker Identity on the Photochemistry of Uranyl-Organic Frameworks

While uranyl-based metal–organic frameworks (MOFs) boast impressive photocatalytic abilities, significant questions remain regarding their excitation pathways and methods to fine-tune their performance due to the lack of information regarding heterogeneous uranyl catalysis. Herein, we investigated how linker identity and photoexcitation impact uranyl photocatalysis when the uranyl coordination environment remains constant. Toward this end, we prepared three uranyl-based MOFs (NU-1301, NU-1307, and ZnTCPP-U2) and then examined the structural and photochemical properties of each through X-ray diffraction, X-ray absorption, and photoluminescence. We then correlated our observations to the photocatalytic performance for fluorination of cyclooctane. The excitation profile from NU-1301 and NU-1307 exhibited spin-forbidden linker transitions and uranyl vibronic progressions, with uranyl excitation and emission being most dominant in NU-1301. Consequently, NU-1301 was a more active photocatalyst than NU-1307. In contrast, the excitation profile from ZnTCPP-U2 contained transitions associated with the porphyrin linker exclusively. Photocatalytic activity from ZnTCPP-U2 significantly underperformed in comparison to that of the other two MOFs. Furthermore, these data suggest that linkers’ photophysical properties can be used to predict the photocatalytic behavior of uranyl-containing MOFs.

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

Enhanced rare-earth separation with a metal-sensitive lanmodulin dimer

Technologically critical rare-earth elements are notoriously difficult to separate, owing to their subtle differences in ionic radius and coordination number. The natural lanthanide-binding protein lanmodulin (LanM) is a sustainable alternative to conventional solvent-extraction-based separation. Here we characterize a new LanM, from Hansschlegelia quercus (Hans-LanM), with an oligomeric state sensitive to rare-earth ionic radius, the lanthanum(III)-induced dimer being >100-fold tighter than the dysprosium(III)-induced dimer. X-ray crystal structures illustrate how picometre-scale differences in radius between lanthanum(III) and dysprosium(III) are propagated to Hans-LanM’s quaternary structure through a carboxylate shift that rearranges a second-sphere hydrogen-bonding network. Comparison to the prototypal LanM from Methylorubrum extorquens reveals distinct metal coordination strategies, rationalizing Hans-LanM’s greater selectivity within the rare-earth elements. Finally, structure-guided mutagenesis of a key residue at the Hans-LanM dimer interface modulates dimerization in solution and enables single-stage, column-based separation of a neodymium(III)/dysprosium(III) mixture to >98% individual element purities. This work showcases the natural diversity of selective lanthanide recognition motifs, and it reveals rare-earth-sensitive dimerization as a biological principle by which to tune the performance of biomolecule-based separation processes.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Scalable, biologically sourced depolymerizable polydienes with intrinsically weakened carbon–carbon bonds

Currently, there are few examples of circularly recyclable polymers with all-carbon backbones, probably owing to the challenge of using selective C–C bond cleavage to efficiently produce monomers in recycling processes. Furthermore, here we demonstrate a series of biologically sourced polymuconate polymers synthesized via simple free-radical polymerization that exhibit intrinsically weakened C–C bonds and controlled chemical recycling to monomers. Modifying the side chains and copolymerization ratios allows a wide range of mechanical property tuning, achieving performances comparable to those of commercial plastics such as polystyrene, polymethyl methacrylate and polybutadiene. Techno-economic analysis and life cycle assessment for production at a scale of 100 kilotons per year show that the materials are currently slightly more expensive and environmentally intensive compared with conventional rubbers. However, use of recycled materials via depolymerization can greatly decrease the cost and environmental impacts of polymuconate production (for example, down to US$1.59 per kilogram) to outperform its commercial counterparts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗