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Results for “structure preservation”
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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A reduced-order model for nonlinear radiative transfer problems based on moment equations and POD-Petrov-Galerkin projection of the normalized Boltzmann transport equation
A data-driven projection-based reduced-order model (ROM) for nonlinear thermal radiative transfer (TRT) problems is presented. The TRT ROM is formulated by (i) a hierarchy of low-order quasidiffusion (aka variable Eddington factor) equations for moments of the radiation intensity and (ii) the normalized Boltzmann transport equation (BTE). The multilevel system of moment equations is derived by projection of the BTE onto a sequence of subspaces which represent elements of the phase space of the problem. Exact closure for the moment equations is provided by the Eddington tensor. A Petrov-Galerkin (PG) projection of the normalized BTE is formulated using a proper orthogonal decomposition (POD) basis representing the normalized radiation intensity over the whole phase space and time. The Eddington tensor linearly depends on the solution of the normalized BTE. By linear superposition of the POD basis functions, a low-rank expansion of the Eddington tensor is constructed with coefficients defined by the PG projected normalized BTE. The material energy balance (MEB) equation is coupled with the effective gray low-order equations which exist on the same dimensional scale as the MEB equation. The resulting TRT ROM is structure and asymptotic preserving. A detailed analysis of the ROM is performed on the classical Fleck-Cummings (F-C) TRT multigroup test problem in 2D geometry. Numerical results are presented to demonstrate the ROM's effectiveness in the simulation of radiation wave phenomena. Importantly, the ROM is shown to produce solutions with sufficiently high accuracy while using low-rank approximation of the normalized BTE solution. Essential physical characteristics of supersonic radiation wave are preserved in the ROM solutions.
Reduced order models for thermal radiative transfer problems based on moment equations and data-driven approximations of the Eddington tensor
Here a new group of structure and asymptotic preserving reduced-order models (ROMs) for multidimensional nonlinear thermal radiative transfer (TRT) problems is presented. They are formulated by means of the nonlinear projective approach and data compression techniques. The nonlinear projection is applied to the Boltzmann transport equation (BTE) to derive a hierarchy of low-order moment equations. Approximation of the Eddington tensor that provides exact closure for the system of moment equations is found with projection-based data-driven methodologies. These include the (i) proper orthogonal decomposition (POD), (ii) dynamic mode decomposition (DMD) and (iii) a variant of the DMD. A parameterization is derived for this ROM for the temperature of radiation incoming to the problem domain (the radiation drive temperature). This parameterization is informed from results of a dimensionless study of the TRT problem. Analysis of the ROMs is performed on the classical Fleck-Cummings TRT multigroup test problem in 2D geometry with a radiation-driven Marshak wave. Numerical results are presented to demonstrate the performance of these ROMs for the simulation of evolving radiation and heat waves. Results show these models to be sufficiently accurate for practical computations with rather low-rank representations of the Eddington tensor. As the rank of the approximation is increased, the errors of solutions generated by the ROMs gradually decreases.
Geometric electrostatic particle-in-cell algorithm on unstructured meshes
We present a geometric particle-in-cell (PIC) algorithm on unstructured meshes for studying electrostatic perturbations with frequency lower than electron gyrofrequency in magnetized plasmas. In this method, ions are treated as fully kinetic particles and electrons are described by the adiabatic response. The PIC method is derived from a discrete variational principle on unstructured meshes. To preserve the geometric structure of the system, the discrete variational principle requires that the electric field is interpolated using Whitney 1-forms, the charge is deposited using Whitney 0-forms and the electric field is computed by discrete exterior calculus. The algorithm has been applied to study the ion Bernstein wave (IBW) in two-dimensional magnetized plasmas. The simulated dispersion relations of the IBW in a rectangular region agree well with theoretical results. In a two-dimensional circular region with fixed boundary condition, the spectrum and eigenmode structures of the IBW are obtained from simulations. We compare the energy conservation property of the geometric PIC algorithm derived from the discrete variational principle with that of previous PIC methods on unstructured meshes. The comparison shows that the new PIC algorithm significantly improves the energy conservation property.
Effect of Annealing on Direct Recycled NMC Cathodes
A substantial number of electric vehicle batteries are poised to reach end-of-life conditions in the next decade. Direct recycling has advantages over typical recycling processes because it preserves the chemical structure of the material. One key step of direct recycling materials like nickel manganese cobalt oxide (NMC) cathodes is relithiation, which includes replacing the depleted lithium inventory in the cathode and annealing the material to fix crystallographic degradation. This work uses multiple characterization techniques (synchrotron X-ray diffraction, Ni X-ray absorption near edge structure, scanning transmission electron microscopy) to understand the lithiation mechanism of degraded and chemically relithiated NMC 622. Despite the necessary reconstruction after relithiation being limited to the surface of the degraded NMC 622, a high annealing temperature of 720 °C is still necessary to restore the NMC 622 structure back to pristine condition after relithiation. This work also finds that treating degraded NMC 622 with an annealing step is sufficient to restore key electrochemical and structural properties, other essential features of pristine NMC 622 material such as particle porosity and morphology are largely unaffected. Understanding the effect of this annealing step has important implications on defining the degree of success of any given direct recycling strategy.
Addition of Chloroform in a Solvent-in-Salt Electrolyte: Outcomes in the Microscopic Dynamics in Bulk and Confinement
Solvent-in-salt electrolytes (SISEs) are a promising alternative to the electrolytes currently used in commercial devices. Despite the SISEs’ advantages, their utilization is not yet realized due to the poor mobility of their chemical species. Here, we explore this problem by adding chloroform to a SISE formed by acetonitrile and a Li-salt. First, we performed illustrative cycling experiments to highlight the potential of this approach. Then, we focused on the description of the microscopic dynamics of the electrolytes and exposed the relevant aspects to be considered for their optimal performance. While the conductivity at low temperatures may be enhanced by the addition of chloroform, only subtle changes occur at room temperature. As revealed by molecular dynamics simulations and quasielastic neutron scattering (QENS) experiments, this effect is related to the preservation of the structure expected for a highly concentrated solution and promotion of the formation of ionic aggregates. These outcomes occur despite the increase in the overall mobility of the chemical species. The dynamics of the electrolytes in porous carbon was also investigated using QENS. In these circumstances, low concentrations of chloroform lead to diffusivities of the molecular species higher than those observed for the bulk electrolytes. As chloroform’s concentration increases, no further changes in the diffusivities are observed. Nonetheless, chloroform is mostly immobilized on the carbon surfaces and this behavior may be intensified at compositions closer to the eutectic mixture.
Use of Renewable Alcohols in Autocatalytic Production of Aspen Organosolv Lignins
This study aimed to investigate the intrinsic efficiency of renewable alcohols, applied under autocatalytic conditions, for removing lignin from aspen and hot-water-extracted aspen while substantially preserving the lignin structure so as to facilitate various valorization strategies. Ethylene glycol (EG), propylene glycol (PG), 1,4-butanediol (BDO), ethanol (EtOH), and tetrahydrofurfuryl alcohol (THFA) were evaluated based on their lignin solubilization ability, expressed as the relative energy difference (RED) following the principles of the Hansen solubility theory. The findings indicate that alcohols with a higher lignin solubilization potential lead to increased delignification, almost 90%, and produce a lignin with a higher content of β-O-4 bonds, up to 68% of those found in aspen milled wood lignin, thereby indicating their potential for valorization through depolymerization. However, these alcohols also produce lignin with a higher content of β-β and β-5 bonds, resulting in a higher molecular weight and polydispersity, due to readily occurring homolytic reactions. Hot-water extraction (HWE) conducted prior to alcohol treatment reduced the delignification efficiency and resulted in a lignin with a lower β-O-4 bond content. The lignins produced in these experiments exhibited a superior UV-A absorption capacity compared with synthetic benzophenone, as well as a greater radical quenching ability than synthetic butylated hydroxytoluene, indicating their potential for use in the protection of polymers against degradation.
Evolution of Mass Spectrometers for High m / z Biological Ion Formation, Transmission, Analysis and Detection: A Personal Perspective
Mass spectrometry (MS) has become an essential tool in virtually all academic, pharmaceutical, and biopharmaceutical analytical laboratories. The specialized and bespoke area of MS research and application of high m / z ion (> m / z 6000 and high mass, >150 kDa) formation, transmission, analysis, and detection is a relatively new area of focus for MS that has seen dramatic acceleration in interest over the last two decades. Herein we delve into this exciting aspect of MS, discussing how MS instrumentation has been refined and evolved for native-MS analysis. We cover the early groundbreaking experiments showing high m / z ion formation, transmission, and preservation of protein structure in the gas phase. Additionally, we discuss specific instrument optimizations and modifications that have advanced high m / z ion generation, transmission, analysis, and detection, contributing to the research area known as gas-phase structural biology. Native-MS sample introduction methods, emerging technologies, and future perspectives are also examined. Finally, we share personal opinions, observations, and experiences that are new to the community or previously unpublished.
Minimally disruptive optical control of protein tyrosine phosphatase 1B
Protein tyrosine phosphatases regulate a myriad of essential subcellular signaling events, yet they remain difficult to study in their native biophysical context. Here we develop a minimally disruptive optical approach to control protein tyrosine phosphatase 1B (PTP1B)—an important regulator of receptor tyrosine kinases and a therapeutic target for the treatment of diabetes, obesity, and cancer—and we use that approach to probe the intracellular function of this enzyme. Our conservative architecture for photocontrol, which consists of a protein-based light switch fused to an allosteric regulatory element, preserves the native structure, activity, and subcellular localization of PTP1B, affords changes in activity that match those elicited by post-translational modifications inside the cell, and permits experimental analyses of the molecular basis of optical modulation. Findings indicate, most strikingly, that small changes in the activity of PTP1B can cause large shifts in the phosphorylation states of its regulatory targets.
Flash healing of laser-induced graphene
The advancement of laser-induced graphene (LIG) technology has streamlined the fabrications of flexible graphene devices. However, the ultrafast kinetics triggered by laser irradiation generates intrinsic amorphous characteristics, leading to high resistivity and compromised performance in electronic devices. Healing graphene defects in specific patterns is technologically challenging by conventional methods. Herein, we report the rapid rectification of LIG’s topological defects by flash Joule heating in milliseconds (referred to as F-LIG), whilst preserving its overall structure and porosity. The F-LIG exhibits a decreased I D /I G ratio from 0.84 – 0.33 and increased crystalline domain from Raman analysis, coupled with a 5-fold surge in conductivity. Pair distribution function and atomic-resolution imaging delineate a broader-range order of F-LIG with a shorter C-C bond of 1.425 Å. The improved crystallinity and conductivity of F-LIG with excellent flexibility enables its utilization in high-performance soft electronics and low-voltage disinfections. Notably, our F-LIG/polydimethylsiloxane strain sensor exhibits a gauge factor of 129.3 within 10% strain, which outperforms pristine LIG by 800%, showcasing significant potential for human-machine interfaces.
Extracellular filaments revealed by affinity capture cryogenic-electron tomography
Cryogenic-electron tomography (cryo-ET) has provided an unprecedented glimpse into the nanoscale architecture of cells by combining cryogenic preservation of biological structures with electron tomography. Micropatterning of extracellular matrix proteins is increasingly used as a method to prepare adherent cell types for cryo-ET as it promotes optimal positioning of cells and subcellular regions of interest for vitrification, cryo-focused ion beam (cryo-FIB) milling, and data acquisition. Here we demonstrate a micropatterning workflow for capturing minimally adherent cell types, human T cells and Jurkat cells, for cryo-FIB and cryo-ET. Our affinity capture system facilitated the nanoscale imaging of Jurkat cells, revealing extracellular filamentous structures. It improved workflow efficiency by consistently producing grids with a sufficient number of well-positioned cells for an entire cryo-FIB session. Affinity capture can be extended to facilitate high-resolution imaging of other adherent and non-adherent cell types with cryo-ET.
Scalable method for micro-CT analysis enables large scale quantitative characterization of brain lesions and implants
Anatomic evaluation is an important aspect of many studies in neuroscience; however, it often lacks information about the three-dimensional structure of the brain. Micro-CT imaging provides an excellent, nondestructive, method for the evaluation of brain structure, but current applications to neurophysiological or lesion studies require removal of the skull as well as hazardous chemicals, dehydration, or embedding, limiting their scalability and utility. Here we present a protocol using eosin in combination with bone decalcification to enhance contrast in the tissue and then employ monochromatic and propagation phase-contrast micro-CT imaging to enable the imaging of brain structure with the preservation of the surrounding skull. Instead of relying on descriptive, time-consuming, or subjective methods, we develop simple quantitative analyses to map the locations of recording electrodes and to characterize the presence and extent of hippocampal brain lesions.
Partitioning of Large-Scale Power Electronics-Based Power Systems for Small-Signal Stability Analysis
The nodal admittance matrix (NAM)-based approach is suitable for analyzing the small-signal stability of large-scale power electronics-based power systems (PEPSs) as it preserves the system structure by utilizing the admittance matrix. Previously, NAM-based area partition has been proposed, which divides the system into various subareas and interconnections for easier analysis of the low-dimension matrix compared to the entire system-based high-dimension matrix. However, no partition algorithm has been presented for the NAM-based area partition method. This paper focuses on implementing the spectral partitioning algorithm for partitioning large-scale PEPSs into a low-dimension matrix to reduce the computation complexity of the analysis. These spectral components facilitate data transformation into a new space, enabling the application of traditional clustering methods like k-means. To evaluate the performance of the partitioning method, the subareas and interconnections obtained from the spectral clustering algorithm are incorporated into the NAM-based area partition method for a large system with 140 buses. The computational times of the original method, where the NAM-based criterion is directly applied to the entire system, are compared with those of the NAM-based partition method in MATLAB. PSCAD simulations of the whole system and the obtained subareas are conducted to validate the effectiveness of the proposed algorithm.
A Generalized Copula-Polynomial Chaos Expansion for Probabilistic Power Flow Considering Nonlinear Correlations of PV Injections
This paper develops a generalized Copula-polynomial chaos expansion (PCE) framework for power system probabilistic power flow that can handle both linear and nonlinear correlations of uncertain power injections, such as wind and PVs. A data-driven Copula statistical model is used to capture the correlations of uncertain power injections. This allows us to resort to the Rosenblatt transformation to transform correlated variables into independent ones while preserving the dependence structure. This paves the way of leveraging the PCE for surrogate modeling and uncertainty quantification of power flow results, i.e., achieving the probabilistic distributions of power flows. Simulations carried out on the IEEE 57-bus system show that the proposed framework can get much more accurate results than other alternatives with different linear and nonlinear power injection correlations.
Spectral Clustering-Based Partitioning of Large-Scale Power Electronics-Based Power Systems for Small-Signal Stability Analysis
The nodal admittance matrix (NAM)-based approach is well-suited for small-signal stability analysis of large-scale power electronics-based power systems (PEPSs), as it preserves the system structure through its admittance matrix. Previous studies have explored partitioning such systems into subareas and interconnections to reduce computational burden; however, they lacked a formal algorithmic procedure for determining feasible partitions. While several grid partitioning methods, such as those based on graph theory or machine learning, exist in the literature, they cannot be directly applied to NAM-based analysis due to differing objectives and constraints. Here, this paper addresses this gap by presenting a systematic, step-by-step procedure for applying a spectral partitioning algorithm that yields a division of the system into subareas suitable for NAM-based analysis. The computational complexity of the proposed method is also derived to demonstrate its efficiency and justify the practicality of the resulting subarea decomposition. The performance of the partitioning method is evaluated by applying the spectral clustering-derived subareas and interconnections to the NAM-based partitioning approach on a 140-bus system. Computational times for the full-system and partitioned NAM analyses are compared using MATLAB. Additionally, PSCAD simulations of the complete system and partitioned subareas are carried out to verify the effectiveness of the proposed method.
Open-Air Manufacturing of Efficient Large-Area Perovskite Solar Cells to Meet Stability and Cost Targets
This SETO-funded project (DE-EE0009516) developed a fully open-air manufacturing pathway for perovskite solar cells and modules, eliminating vacuum-based processing steps while improving device stability. Open-air ultrasonic spray deposition, solution combustion synthesis, rapid thermal processing, and atmospheric plasma curing were developed and optimized for all functional device layers — perovskite absorber, hole transport layers (HTLs), electron transport layers (ETLs), transparent conducting oxides (TCOs), and rear electrodes — without reliance on vacuum. Sprayed organic ETLs preserved perovskite crystal structure and enabled power conversion efficiencies exceeding 20%, and open-air processed TCOs and rear electrodes achieved optoelectronic performance comparable to sputtered alternatives at substantially lower manufacturing cost. Device stability was assessed through accelerated aging protocols aligned with IEC and ISOS standards, combined with high-throughput optical diagnostics that identified key degradation mechanisms and antagonistic interactions among heat, humidity, and illumination stressors. A comprehensive technoeconomic analysis quantified the cost and throughput advantages of open-air manufacturing over conventional vacuum-based processes, identifying vacuum deposition as the dominant cost driver and demonstrating a clear pathway toward the $0.02/kWh target. The project produced five peer-reviewed journal publications, eleven conference presentations, two patents/applications, and five Ph.D. dissertations.
A model for radar images and its application to adaptive digital filtering of multiplicative noise
Standard image processing techniques which are used to enhance noncoherent optically produced images are not applicable to radar images due to the coherent nature of the radar imaging process. A model for the radar imaging process is derived in this paper and a method for smoothing noisy radar images is also presented. The imaging model shows that the radar image is corrupted by multiplicative noise. The model leads to the functional form of an optimum (minimum MSE) filter for smoothing radar images. By using locally estimated parameter values the filter is made adaptive so that it provides minimum MSE estimates inside homogeneous areas of an image while preserving the edge structure. It is shown that the filter can be easily implemented in the spatial domain and is computationally efficient. The performance of the adaptive filter is compared (qualitatively and quantitatively) with several standard filters using real and simulated radar images.
Conditionally-averaged structures in wall-bounded turbulent flows
The quadrant-splitting and the wall-shear detection techniques were used to obtain ensemble-averaged wall layer structures. The two techniques give similar results for Q4 events, but the wall-shear method leads to smearing of Q2 events. Events were found to maintain their identity for very long times. The ensemble-averaged structures scale with outer variables. Turbulence producing events were associated with one dominant vortical structure rather than a pair of counter-rotating structures. An asymmetry-preserving averaging scheme was devised that allowed a picture of the average structure which more closely resembles the instantaneous one, to be obtained.