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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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286 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Structural complexity of γ-Al 2 O 3 : The nature of vacancy ordering and the structure of complex antiphase boundaries

The structure of γ-Al2O3 remains largely undetermined despite decades of research. This is due to the high degree of disorder, which poses significant challenges for structural analysis using conventional crystallographic approaches. Herein, we study the structure of γ-Al2O3 with Scanning Transmission Electron Microscopy (STEM) and ab-initio calculations to provide a complete structural description. We show that the microstructure can be understood in terms of two key structural features of nanoscale spinel domains and finite thickness segments termed as complex antiphase boundaries (cAPB) that provide the domain interconnectivity. The spinel domains have a distinctive preference for vacancy ordering, which can be rationalized in terms of a structure with a stacking disorder. Tetragonal P4 1 2 1 2 or monoclinic P2 1 models, all based on the identical motif, can be considered as representative ordered forms. Individual spinel domains are interconnected via cAPBs, which adopt a distinct non-spinel bonding environment of δ-Al 2 O 3 . The most common cAPB consists of a single delta motif with thickness of just 0.6 nm on (001), with the resulting displacement a/4 [101]. Remarkably, the cAPBs are shown to energetically stabilize the spinel domains of γ-Al 2 O 3 explaining their high abundance. We demonstrate how the tetragonal distortions naturally arise in this intricate microstructure and place the proposed model in the context of phase transformations to high temperature transition aluminas.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Towards automating structural discovery in scanning transmission electron microscopy *

Abstract Scanning transmission electron microscopy is now the primary tool for exploring functional materials on the atomic level. Often, features of interest are highly localized in specific regions in the material, such as ferroelectric domain walls, extended defects, or second phase inclusions. Selecting regions to image for structural and chemical discovery via atomically resolved imaging has traditionally proceeded via human operators making semi-informed judgements on sampling locations and parameters. Recent efforts at automation for structural and physical discovery have pointed towards the use of ‘active learning’ methods that utilize Bayesian optimization with surrogate models to quickly find relevant regions of interest. Yet despite the potential importance of this direction, there is a general lack of certainty in selecting relevant control algorithms and how to balance a priori knowledge of the material system with knowledge derived during experimentation. Here we address this gap by developing the automated experiment workflows with several combinations to both illustrate the effects of these choices and demonstrate the tradeoffs associated with each in terms of accuracy, robustness, and susceptibility to hyperparameters for structural discovery. We discuss possible methods to build descriptors using the raw image data and deep learning based semantic segmentation, as well as the implementation of variational autoencoder based representation. Furthermore, each workflow is applied to a range of feature sizes including NiO pillars within a La:SrMnO 3 matrix, ferroelectric domains in BiFeO 3 , and topological defects in graphene. The code developed in this manuscript is open sourced and will be released at github.com/nccreang/AE_Workflows .

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Stabilization of high-performance rock-salt LiMnSbTe3 thermoelectrics with embedded van der Waals-like gaps

Rock-salt-structured compounds like lead chalcogenides are promising thermoelectrics, as their high symmetry, strong anharmonicity, and favorable phase behavior collectively lead to high performance by enabling large power factors and ultralow thermal conductivity. Here, we report LiMnSbTe 3 , a new rock-salt semiconductor stabilized through targeted chemical design by combining hexagonal MnTe with cubic LiSbTe 2 . Embedded in the highsymmetry matrix, van der Waals-like gaps form due to Sb 2 Te 3 nanoscale segregation, which acts as effective phonon-scattering centers, leading to a low lattice thermal conductivity of 0.37Wm- 1 K -1 at 873 K with alloy scattering from disordered cations. The ordered local structure of Sb2Te 3 -type vdW-like gaps and the cross-gap interaction facilitate the carrier transport. Aided by energyconverged valence bands and a paramagnon drag effect, high Seebeck coefficients and enhanced power factor can be achieved, leading to a high ZT of 1.2 at 873 K. Furthermore, introducing Mn deficiency increases ZT to 1.5, highlighting the potential for higher performance through optimized doping or alloying. A segmented single-leg thermoelectric module achieves an output power density of 0.52 Wcm -2 and an efficiency of 8.7% under ΔT of 478 K, further demonstrating its promising thermoelectric applications.

42 ENGINEERING↗
DOE OSTI2025

Genetic control of morphological transitions in a coacervating protein template

Nature routinely exploits liquid–liquid phase separation (LLPS) of proteins to control the assembly and mineralization of hybrid materials. Here, we show that fusion of the Car9 silica-binding peptide to an elastin-like polypeptide (ELP) yields temperature- and sequence-programmable soft matter templates for the synthesis of silicified architectures ranging in size from nanometers to micrometers. Specifically, we demonstrate unprecedented control over the diameter of silica nanoparticles (SiNP) in the 30–60 nm range with 4 nm precision, show that a single arginine residue (R4) in the Car9 sequence underpins the transition from micelles to proteinosomes, and find that substitutions in other basic residues modulate electrostatic repulsion and solvation to enable access to kinetically trapped species. These structures, which include interconnected micelles, small (∼200 nm) and large (>5 µm) vesicles, are readily visualized by SEM imaging following silicification. Molecular dynamics (MD) simulations and AlphaFold predictions reveal that mutations in positively charged residues alter interfacial packing, hydration, and conformational freedom of the silica-binding segments. Overall, our results establish sequence and thermal energy as synergistic levers for morphological control across length scales using solid-binding ELPs and establish mineralization as a powerful tool to visualize the structure of dynamic soft matter assemblies.

hierarchy↗
DOE OSTI2026

Quasi‐Steady State Supersaturation: Do High Values Derived From ESCAPE Represent Real High Supersaturations and the Potential for Condensational Invigoration?

Deep convective clouds were intensively sampled during the Experiment of Sea Breeze Convection, Aerosols, Precipitation, and Environment (ESCAPE) with coordinated flights of the NRC Convair-580 and SPEC Learjet. A total of 219 updraft core segments were sampled over coastal Texas and Louisiana under diverse meteorological conditions. Median updraft properties included widths of ∼1 km, velocities of 4.8 m s −1 , droplet number concentrations of ∼400 cm −3 , and liquid water contents of 0.9 g m −3 . The limitations of using the quasi-steady state approximation to derive supersaturations were explored. Supersaturation (S QSS ) estimated from in situ observations under a quasi-steady state assumption averaged 0.4% but occasionally exceeded 2%, with values >1% (high supersaturations) identified as statistical outliers. Two case studies illustrated the conditions linked to high supersaturations. In a storm over the Gulf, median core S QSS reached 2.46% in the developing stage compared to 2.17% in the mature stage under similar thermodynamic conditions. In a storm over coastal Louisiana, S QSS peaked near 11% within a 13.7-m s −1 updraft, accompanied by predominantly supercooled liquid droplets at −13°C and exceptionally low diameter concentrations of 0.29 mm cm −3 . Bootstrap analysis of all sampled cores showed that high supersaturations are most probable in cold and mixed-phase regimes with moderate to strong updrafts and are strongly influenced by vertical velocity and droplet number concentrations. In conclusion, while extreme supersaturations (∼10%) were rare, their occurrence underscores the need for targeted multiplatform observations to resolve their spatiotemporal variability and assess their potential role in deep convective invigoration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Global centroid moment tensor solutions in a heterogeneous earth: the CMT3D catalogue

SUMMARY For over 40 yr, the global centroid-moment tensor (GCMT) project has determined location and source parameters for globally recorded earthquakes larger than magnitude 5.0. The GCMT database remains a trusted staple for the geophysical community. Its point-source moment-tensor solutions are the result of inversions that model long-period observed seismic waveforms via normal-mode summation for a 1-D reference earth model, augmented by path corrections to capture 3-D variations in surface wave phase speeds, and to account for crustal structure. While this methodology remains essentially unchanged for the ongoing GCMT catalogue, source inversions based on waveform modelling in low-resolution 3-D earth models have revealed small but persistent biases in the standard modelling approach. Keeping pace with the increased capacity and demands of global tomography requires a revised catalogue of centroid-moment tensors (CMT), automatically and reproducibly computed using Green's functions from a state-of-the-art 3-D earth model. In this paper, we modify the current procedure for the full-waveform inversion of seismic traces for the six moment-tensor parameters, centroid latitude, longitude, depth and centroid time of global earthquakes. We take the GCMT solutions as a point of departure but update them to account for the effects of a heterogeneous earth, using the global 3-D wave speed model GLAD-M25. We generate synthetic seismograms from Green's functions computed by the spectral-element method in the 3-D model, select observed seismic data and remove their instrument response, process synthetic and observed data, select segments of observed and synthetic data based on similarity, and invert for new model parameters of the earthquake’s centroid location, time and moment tensor. The events in our new, preliminary database containing 9382 global event solutions, called CMT3D for ‘3-D centroid-moment tensors’, are on average 4 km shallower, about 1 s earlier, about 5 per cent larger in scalar moment, and more double-couple in nature than in the GCMT catalogue. We discuss in detail the geographical and statistical distributions of the updated solutions, and place them in the context of earlier work. We plan to disseminate our CMT3D solutions via the online ShakeMovie platform.

58 GEOSCIENCES↗
DOE OSTI2022

The BREKTRIA 500 – A Breakthrough in Technology and Power Density for an Advanced 500kW Utility-Scale String Inverter (Final Technical Report)

The primary goal of this development project, planned to be 36 months in duration, was to create a 500kW utility-scale string inverter, demonstrating an advanced hybrid architecture that would achieve unprecedented high power density, and bring the inverter to the stage of production readiness. Specific key objectives for the 500kW utility-scale string inverter were: Create a 500kW 3-phase 600Vac inverter that was similar in overall size to the existing 250kW string inverters in the market, thereby demonstrating dramatically increased power density; Achieve a cost of goods, including all manufacturing-related costs and overheads, at or below 2.5¢/Wac ($12,500); Demonstrate full-power operation at a 45-50C ambient temperature with no power de-rating; Accommodate a PV array DC input of up to 1MWdc, aka a DC/AC Ratio of 2.0; Demonstrate peak efficiency greater than 99% at any operating dc voltage, and a CEC weighted average efficiency greater than or equal to 98.5%. The motivation for this project was to leapfrog the competition by creating the world’s most powerful string inverter, utilizing an innovative topology and achieving a step change increase in power density. Achieving the goals of the project would have enabled Yaskawa Solectria Solar to demonstrate its technology leadership, manufacture the utility-scale string inverter in the company’s facilities in Illinois, and bring to the market a highly-differentiated and compelling product to help the company grow its share in the large and growing utility market segment. During the course of this project, BREK Electronics’ hybrid architecture inverter was taken from an early-stage 125kW prototype, to a more mature and successfully demonstrated power stage at twice the power. Two 250kW power stages were planned to build the 500kW inverter. Significant progress was made in the inverter controls, achieving a clean AC sinewave and closed-loop operation into the grid, and improved efficiency by control of the high-speed switching. Further, the updated 250kW power stage was on track to achieve full power operation at an ambient temperature of 50C. At the time of the project’s closure in September 2022, global semiconductor supply remained limited, with shortages creating dramatic swings in both availability and price. Given this situation, our ability to predict cost-of-goods two years out with any accuracy or confidence was limited. As a result, the probability of attaining the target cost of 2.5¢/Wac for the 500kW inverter remained uncertain at the closure of the project. This project successfully demonstrated the potential for the advanced hybrid architecture inverter that emerged from a decade of university research on Si IGBTs and SiC mosfets, leading to this unique inverter topology. The team has taken the first steps toward an evolutionary advancement in inverter technology that remains to be fully realized.

14 SOLAR ENERGY↗
DOE OSTI2023

Understanding hadronic interactions using advanced reconstruction techniques

ProtoDUNE-SP served as the prototype of the future Deep Underground Neutrino Experiment (DUNE). With a total liquid argon mass of 0.77 kt, it stood as the most extensive monolithic single-phase Liquid Argon Time Projection Chamber (LArTPC) ever constructed. Strategically located and operated at CERN, ProtoDUNE-SP benefited from a specialized charged-particle test beam, offering a momentum range of 0.3 - 7 GeV/c. This setup provided a unique opportunity to conduct in-depth studies on hadronic interactions within argon. Hadronic interactions play a fundamental role in neutrino physics, particularly in the intricacies of neutrino detection. We depend on analyzing the outcomes of these interactions to accurately determine both the flavor and energy of the interacting neutrinos. Pions, as one of the primary byproducts of neutrino interactions, are crucial for understanding the overall dynamics and kinematics of these processes. Accurately characterizing and understanding the interaction of pions with argon can significantly enhance the precision of neutrino simulations and measurements.Being a Liquid Argon Time Projection Chamber (LArTPC), ProtoDUNE-SP is distinguished by its ability to produce high-definition images of charged particles as they traverse through the detector's active volume. Yet, accurately reconstructing these particle interactions and determining their kinematic attributes remains a challenging task. The successes of deep learning in diverse domains, especially in image recognition, provide a promising approach for addressing this challenge in ProtoDUNE. This thesis discusses a measurement of the Piplus - argon inelastic cross section in the energy range of 2400 to 3000 MeV, using data taken by protoDUNE during the fall of 2018. Additionally, panoptic segmentation, a machine learning technique, is introduced and validated through its application in the reconstruction of the neutral pion rest mass. The aim is to showcase how these advanced methods can enhance the quality of event reconstruction.

Sarasty Segura, Carlos Eduardo↗
DOE OSTI2024

Hyperspectral Detection of the Fluorescence Shift between Chirality-Sorted Empty and Water-Filled Single-Wall Carbon Nanotube Enantiomers

Single-wall carbon nanotubes (SWCNTs) have extraordinary electronic and optical properties that depend strongly on their exact chiral structure and their interaction with their inner and outer environment. The fluorescence (PL) of semiconducting SWCNTs, for instance, will shift depending on the molecules with which the SWCNT’s hollow core is filled. These interaction-induced shifts are challenging to resolve on the ensemble level in samples containing a mixture of different filling contents due to the relatively large inhomogeneous line width of the ensemble SWCNT PL compared to the size of these shifts. To circumvent this inhomogeneous broadening, single-tube spectroscopy and hyperspectral imaging are often applied, which until now required time-consuming statistical studies. Here, we present hyperspectral PL microscopy combined with automated SWCNT segmenting based on either principal component analysis or a convolutional neural network, capable of both spatially and spectrally resolving the PL along the length of many individual SWCNTs at the same time and automatically fitting peak positions and line widths of individual SWCNTs. The methodology is demonstrated by accurately determining the emission shifts and line widths of thousands of left- and right-handed empty and water-filled SWCNTs coated with a chiral surfactant, resulting in four statistical distributions which cannot be resolved in ensemble spectroscopy of unsorted samples. The results demonstrate a robust method to quickly probe ensemble properties with single-enantiomer spectral resolution. Moreover, it promises to be an absolute quantitative method to characterize the relative abundances of SWCNTs with different handedness or filling content in macroscopic samples, simply by counting individual species.

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

A fine pore-preserved deep neural network for porosity analytics of a high burnup U-10Zr metallic fuel

Abstract U-10 wt.% Zr (U-10Zr) metallic fuel is the leading candidate for next-generation sodium-cooled fast reactors. Porosity is one of the most important factors that impacts the performance of U-10Zr metallic fuel. The pores generated by the fission gas accumulation can lead to changes in thermal conductivity, fuel swelling, Fuel-Cladding Chemical Interaction (FCCI) and Fuel-Cladding Mechanical Interaction (FCMI). Therefore, it is crucial to accurately segment and analyze porosity to understand the U-10Zr fuel system to design future fast reactors. To address the above issues, we introduce a workflow to process and analyze multi-source Scanning Electron Microscope (SEM) image data. Moreover, an encoder-decoder-based, deep fully convolutional network is proposed to segment pores accurately by integrating the residual unit and the densely-connected units. Two SEM 250 × field of view image datasets with different formats are utilized to evaluate the new proposed model’s performance. Sufficient comparison results demonstrate that our method quantitatively outperforms two popular deep fully convolutional networks. Furthermore, we conducted experiments on the third SEM 2500 × field of view image dataset, and the transfer learning results show the potential capability to transfer the knowledge from low-magnification images to high-magnification images. Finally, we use a pre-trained network to predict the pores of SEM images in the whole cross-sectional image and obtain quantitative porosity analysis. Our findings will guide the SEM microscopy data collection efficiently, provide a mechanistic understanding of the U-10Zr fuel system and bridge the gap between advanced characterization to fuel system design.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Electrolyte and Cutoff Potential Effects on Cycle Life of Li4Ti5O12/LiNi0.9Mn0.1O2 Batteries for Behind-the-Meter Storage Applications

Behind-the-Meter Storage (BTMS) is a stationary battery energy storage system that is connected to the electrical distribution system on the customer's side of the utility's service meter. BTMS systems are used to store electrical energy from the grid as well as inconstant, renewable energy, such as local solar and wind generation. A successful BTMS system will allow the customer to pair their energy generation and storage to optimize electrical consumption from the grid, improving reliability and minimizing cost. For BTMS applications, batteries must be designed and optimized with different set of criteria from other leading segments of the Li-ion battery market, like transportation, due the system being stationary and proximal to the residential or commercial building it's benefitting. BTMS applications prioritize safety, cost (low/no-critical materials), reliability (20-year calendar life), and durability (10,000 cycle life), while having the ability to (minimally) compromise energy density and rate capability. Lithium titanate (Li4Ti5O12-, LTO) is a promising anode candidate for BTMS applications due to its high safety and capacity retention, while maintaining a reasonable 160 mAhg-1 reversable capacity and composition of relatively abundant materials. (1) Specifically, LTO has a high working voltage which helps to prevent Li dendrite formation, improving safety. Furthermore, LTO also has negligible lithiation-based volume change, leading to less mechanical pulverization, or loss of active material, upon cycling. For the cathode, materials with little or no Co are of high interest due to the high cost and low abundance of Co. LiMn2O4 (LMO) has been paired with LTO for BTMS applications in the past due to its safety, low cost (abundancy), and reasonably high operating voltage. (2-4) However, the low capacity of LMO limits energy density and specific energy. While not the highest priority for BTMS applications, increasing energy density will enable deployment in space constrained BTMS applications and decrease total cost. LiNi0.9Mn0.1O2 (LN-MO) is a recently developed material with promise due to its high operating voltage and relatively low price. (5) However, Ni-rich layered oxides, including LNMO, tend to struggle with capacity retention during high-voltage cycling due to mechanical pulverization, irreversible phase transitions, and unstable solid-electrolyte interphase. The study presented here focuses on building an understanding of how electrolyte solvent and varied cutoff potentials will impact the cycle life of LTO/LN-MO cells. Specifically, a comparison is provided between ethylene carbonate (EC), ethyl methyl carbonate (EMC), fluoroethylene carbonate (FEC), and Gen2 electrolyte solvents with 1M Lithium hexafluorophosphate (LiPF6) salt, cycling to two upper termination potentials, 2.6V and 2.7V. Electrochemical testing and diagnostics (e.g., differential capacity analysis, area specific impedance, constant voltage hold, and rate capability) and post-mortem characterization will be used to understand the aging behavior and failure mechanisms of the 8 cell combinations (four electrolytes and two voltage cutoffs). Cells with FEC electrolyte showed a lower initial capacity compared to cells with Gen2, EMC, and EC cycling at both voltages; however, the cells with FEC showed consistent trends in capacity retention with 2.6V and 2.7V termination potentials, while the cells with the other electrolytes showed much higher rates of capacity loss when cycling to the higher voltage. These results indicate that FEC may play a role in improving durability of high-voltage, Ni-rich electrode systems for use in high-cycle applications, such as BTMS.

electrolyte↗
DOE OSTI2020

An Investigation of Liquefaction in Irradiated TRIGA Fuel Exposed to Relatively High Temperatures

This report presents the findings of an investigation into high temperature fuel cladding chemical interactions (FCCI) in Training, Research, Isotopes, General Atomics (TRIGA) fuel rods. A TRIGA fuel-rod core or meat is principally composed of uranium (U) particles dispersed in a zirconium hydride (Zr H) matrix. The fuel is clad in sealed 304SS or Incoloy 800 tubes. At high temperatures, the fuel will interact with the cladding, resulting in FCCI. To investigate the FCCI (in this case, liquefaction), irradiated TRIGA fuel rods were exposed to relatively high temperatures in furnace tests. The tests were performed at different temperatures using segments from an irradiated TRIGA fuel rod at the Hot Fuel Examination Facility located at Idaho National Laboratory (INL). The data from this study is important for developing a better understanding of the performance of U-ZrH fuel type during transient events (e.g., a Loss of Coolant Accident (LOCA) event) that may result in high temperatures while operating a TRIGA reactor. Furnace tests were run for 6 hours at 730, 800, 900, 950, and 1,000°C. One test was run for 12 hours at 950°C. Post-test microstructural characterization was performed on the heat-treated samples using optical metallography to look for evidence of liquefaction. Additionally, microstructural characterization was performed using scanning electron microscopy to investigate the microstructure of the as-irradiated fuel before heat treatment and the microstructural changes that occurred after heat treating for the 730 and 950°C heat treatments for 6 hours. Results of the analysis were compared to those produced during diffusion studies performed using unirradiated TRIGA fuel meat and type 304 stainless steel. A gap is typically present in as-irradiated fuel that limits any possibility for chemical interaction between the fuel and cladding. Optical metallography (OM) was used to identify areas in the specimens heat treated at 950 and 1000°C where fuel and cladding contact was satisfactory for the FCCI to transpire. The bulk of the interaction zones that form due to FCCI developed in the fuel meat and not as much in the cladding. Even in the sample tested at 1,000°C, no evidence was found that gross fuel meat or cladding melting had occurred. Only limited porosity was found in the fuel meat that possibly could have been due to melting of a particular precipitate phase or phases that had formed during FCCI. These results agreed with those reported for the unirradiated diffusion couple studies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Activating Opportunity Zones for Rapid Solar+Storage Deployment in Low Income Communities (Final Report)

Millions of Texans choose their own power provider, giving them the option to have low-cost and even renewable energy delivered through their retail electric plan. However, Texans with less disposable income often pay more for electricity and have limited access to green energy and emergency backup power even though the costs of solar and wind power are at record lows and continue to decline. The Powered for Good initiative aimed to help deliver clean, affordable, 100% renewable electricity to low-income households in Texas’s Competitive Retail Areas, where households can choose their electricity provider. Objectives: The primary goal of this project was to develop and validate one or more affordable solar+storage products (i.e., priced less than of $0.14/kWh) that Retail Electricity Providers (REP) can offer to LI households. The team achieved three objectives: 1. Investigate how to best reduce electricity costs and increase availability of emergency power for LI customers; 2. Build momentum for, and facilitate an approach to, a Texas-based pilot deployment of such solar+storage products, with a goal of greatly expanding this approach to a large segment of the LI population in Texas; 3. Provide the structural framework, finance model, and roadmap to potentially increase investment of solar+storage projects in LI communities across U.S. states when modified to meet their state-specific laws and regulations. The team evaluated the market of viable solutions for low-income Texans through interviews and focus groups with professionals and residents with lived experience. The team then piloted a low-cost retail electric product. Following the pilot, the team developed educational materials, including fact sheets, a Go Green Save Green interactive guide, and an Electricity Bill Analysis Tool. The team is now working to increase power resilience and reduce energy insecurity with micro solar and storage in partnership with local entities in the Harris County area. Key Findings: Informed by Powered for Good research, including the experiences on Texas residents and electricity system experts, the Powered for Good team developed a pilot that was implemented by Energy Well Texas, a new company formed in late 2020. The pilot featured a combination of a 100% clean residential energy offering delivered through the electrical grid plus a selection of batteries, lights and a solar panel that provided participants with varying levels of backup power. For the 8 customers who submitted previous bills, the Energy Well Texas pilot reduced energy bills by about 30%. In Houston, residents earning less than 30% of Area median Income (AMI) spend an average 13% of their income on energy or about $1,555 per year. Repeating the pilot results for these residents could yield $466 in savings per customer or about 4% of their income. While this will not end energy poverty, it is a big step toward that goal. The Powered for Good and Energy Well Texas teams are currently planning their post-pilot phase of service offerings.

14 SOLAR ENERGY↗
DOE OSTI2023

Influence of the Graft Length on Nanocomposite Structure and Interfacial Dynamics

Both the dispersion state of nanoparticles (NPs) within polymer nanocomposites (PNCs) and the dynamical state of the polymer altered by the presence of the NP/polymer interfaces have a strong impact on the macroscopic properties of PNCs. In particular, mechanical properties are strongly affected by percolation of hard phases, which may be NP networks, dynamically modified polymer regions, or combinations of both. In this article, the impact on dispersion and dynamics of surface modification of the NPs by short monomethoxysilanes with eight carbons in the alkyl part (C 8 ) is studied. As a function of grafting density and particle content, polymer dynamics is followed by broadband dielectric spectroscopy and analyzed by an interfacial layer model, whereas the particle dispersion is investigated by small-angle X-ray scattering and analyzed by reverse Monte Carlo simulations. NP dispersions are found to be destabilized only at the highest grafting. The interfacial layer formalism allows the clear identification of the volume fraction of interfacial polymer, with its characteristic time. The strongest dynamical slow-down in the polymer is found for unmodified NPs, while grafting weakens this effect progressively. The combination of all three techniques enables a unique measurement of the true thickness of the interfacial layer, which is ca. 5 nm. Finally, the comparison between longer (C 18 ) and shorter (C 8 ) grafts provides unprecedented insight into the efficacy and tunability of surface modification. It is shown that C 8 -grafting allows for a more progressive tuning, which goes beyond a pure mass effect.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Monte Carlo Simulation and Reconstruction: Assessment of Myocardial Perfusion Imaging of Tracer Dynamics With Cardiac Motion Due to Deformation and Respiration Using Gamma Camera With Continuous Acquisition

Purpose: Myocardial perfusion imaging (MPI) with single photon emission computed tomography (SPECT) is routinely used for stress testing in nuclear medicine. Recently, our group extended its potential going from 3D visual qualitative image analysis to 4D spatiotemporal reconstruction of dynamically acquired data to capture the time variation of the radiotracer concentration and the estimated myocardial blood flow (MBF) and coronary flow reserve (CFR). However, the quality of reconstructed image is compromised due to cardiac deformation and respiration. The work presented here develops an algorithm that reconstructs the dynamic sequence of separate respiratory and cardiac phases and evaluates the algorithm with data simulated with a Monte Carlo simulation for the continuous image acquisition and processing with a slowly rotating SPECT camera. Methods: A clinically realistic Monte Carlo (MC) simulation is developed using the 4D Extended Cardiac Torso (XCAT) digital phantom with respiratory and cardiac motion to model continuous data acquisition of dynamic cardiac SPECT with slowly rotating gamma cameras by incorporating deformation and displacement of the myocardium due to cardiac and respiratory motion. We extended our previously developed 4D maximum-likelihood expectation-maximization (MLEM) reconstruction algorithm for a data set binned from a continuous list mode (LM) simulation with cardiac and respiratory information. Our spatiotemporal image reconstruction uses splines to explicitly model the temporal change of the tracer for each cardiac and respiratory gate that delineates the myocardial spatial position as the tracer washes in and out. Unlike in a fully list-mode data acquisition and reconstruction the accumulated photons are binned over a specific but very short time interval corresponding to each cardiac and respiratory gate. Reconstruction results are presented showing the dynamics of the tracer in the myocardium as it continuously deforms. These results are then compared with the conventional 4D spatiotemporal reconstruction method that models only the temporal changes of the tracer activity. Mean Stabilized Activity (MSA), signal to noise ratio (SNR) and Bias for the myocardium activities for three different target-to-background ratios (TBRs) are evaluated. Dynamic quantitative indices such as wash-in (K1) and wash-out (k2) rates at each gate were also estimated. Results: The MSA and SNR are higher with higher TBRs while biases were improved with higher TBRs to less than 10%. The correlation between exhalation-inhalation sequence with the ground truth during respiratory cycle was excellent. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Estimated values of K1 and k2 were also consistent with the ground truth. Conclusion: The continuous image acquisition for dynamic scan using conventional two-head gamma cameras can provide valuable information for MPI. Our study demonstrated the viability of using a continuous image acquisition method on a widely used clinical two-head SPECT system. Our reconstruction method showed better resolved myocardial walls during diastole to systole as compared to the ungated 4D image. Precise implementation of reconstruction algorithms, better segmentation techniques by generating images of different tissue types and background activity would improve the feasibility of the method in real clinical environment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Simplex‐based model for nanoparticle grain identification in four‐dimensional scanning transmission electron microscopy data

Grain identification in polycrystalline nanoparticles, for example, determining which crystal phases are present at each spatial location, is fundamental to materials characterisation. This is particularly challenging when grains overlap extensively, as commonly occurs in four-dimensional scanning transmission electron microscopy (4D-STEM) datasets. We propose a simplex-based model (SBM) in which each simplex vertex represents the diffraction pattern (DP) of a pure grain, and the simplex edges and interior represent overlapping grains. Our SBM grain identification algorithm operates on the Bragg disk (BD) data matrix distilled from the 4D-STEM data to identify the grain membership at each scan position, together with a BD feature matrix whose columns represent the DPs for each constituent grain, which is important for identifying the crystal structure of each grain. We solve the model using a two-stage algorithm. In Stage 1, we adapt a linear mixing algorithm to estimate an initial BD feature matrix whose columns represent DPs of potentially overlapping grains. Our Stage 2 algorithm incorporates sparsity considerations to transform the initial BD feature matrix so that its columns represent DPs of pure grains. Using simulated datasets with various grain configurations, we demonstrate that SBM recovers both the BD feature matrix and membership maps more accurately than existing methods, even when a grain lacks any pure region and completely overlaps with other grains.

4D-STEM segmentation↗