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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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Radio Frequency Spectrum Audit to Inventory Private Cellular Base Station Infrastructure
The ever-changing cellular communication landscape makes it difficult to identify, map, and localize cellular base stations. Localizing cellular base stations provides various advantages, including information security, cybersecurity, spectrum management, and interference detection. For example, the MITRE ATT&CK® (Adversarial Tactics, Techniques, and Common Knowledge architecture) [1] and Common Attack Pattern Enumeration and Classification [2] emphasize the importance of being able to minimize the cyber security threat presented by unregulated private cellular base stations (PCBS). The majority of published research looks at the malicious use of PCBSs and focuses on using data retrieved from user equipment (UE), data obtained from an application on the UE, or data shared between the UE and a mobile network to locate it. This innovative strategy, however, focuses on the passively discovered uniqueness of radio frequency (RF) transmissions from commercial cellular infrastructure received in a designated monitoring position (DMP).
Gray-Box Modeling for Distribution Systems With Inverter-Based Resources: Integrating Physics-Based and Data-Driven Approaches
Here, in this paper, we develop a novel gray-box modeling approach for distribution systems with inverter-based resources (IBRs). The proposed gray-box modeling method aims to improve estimation accuracy by taking advantages of both physics-based (white-box) and data-driven (black-box) modeling approaches. To this end, we utilize partial physical knowledge of the system, including the inverters’ structures and control diagrams, as well as the equivalent network model simplified through Kron reduction. The white-box model containing unknown parameters is then constructed with mathematical equations and an optimization-based method is subsequently employed to identify these unknown parameters within the white-box model. Next, the graybox modeling framework is then constructed by embedding the output variables of the white-box model into the input vector of a black-box model (represented using a neural network). Finally, the black-box section is trained using the collected input-output datasets and the gray-box model is then obtained. Furthermore, case studies demonstrate that our gray-box modeling approach effectively improves estimation accuracy compared to purely physics-based or data-driven methods.
Re-investigation of high-temperature phase equilibria in Fe-rich Sm–Fe–Ti alloys
Recently renewed attempts to develop high-performance rare-earth-lean permanent magnets based on the Sm(Fe,Ti) 12 compound have drawn attention to the limited knowledge about the high-temperature phase equilibria in the Sm–Fe–Ti system. Experimental investigation of equilibrated alloys with electron probe microanalysis, X-ray diffraction and thermomagnetic analysis revealed several inaccuracies in the currently accepted phase relations at 1000°C and allowed for a revision of the Fe-rich corner of the Sm–Fe–Ti phase diagram. The Sm(Fe,Ti) 12 and Sm 3 (Fe,Ti) 29 phases were found to have more extended Ti ranges of 5.1–9.7 at% and 2.8–6.9 at%, respectively. With increasing of the Ti content, the Curie temperature of the Sm(Fe,Ti) 12 remains nearly constant at 306–312°C, whereas that of the Sm 3 (Fe,Ti) 29 increases from 188°C to 207°C. The low-titanium Sm 3 (Fe,Ti) 29 phase equilibrates not only with the Sm(Fe,Ti) 12 and Sm2(Fe,Ti) 17 phases, but also with (α-Fe) solid solution. Newly demonstrated equilibrium between Sm 2 (Fe,Ti) 17 and TiFe 2 phases makes impossible the earlier reported equilibrium between the Sm 3 (Fe,Ti) 29 and Sm(Fe,Ti) 11 phases. Because of an invariant reaction at 1000 °C, the revised phase diagram also features a class II four-phase equilibrium Sm 3 (Fe,Ti) 29 + TiFe 2 + Sm(Fe,Ti) 12 + Sm 2 (Fe,Ti) 17 . Peritectic decomposition of the Sm(Fe,Ti) 11 phase, which occurs either at 1075°C or at 1087°C, was found to have among its products the Sm(Fe,Ti) 12 phase. Although no such equilibration was attempted, it must be possible to obtain above 1087°C a two-phase state composed of the Sm(Fe,Ti) 12 phase and a liquid – which is important for manufacturing of the Sm(Fe,Ti) 12 - based permanent magnets via the liquid-phase sintering.
Durable and High-Performance SOECs Based on Proton Conductors for Hydrogen Production
Proton-conducting solid oxide electrolysis cells (P-SOECs) are a promising technology for cost-effective and efficient production of green hydrogen. Breakthroughs in materials development, optimization of cell structure, and achievement of high performance and durability are essential to significantly increase the commercial competitiveness of these technologies. The main objective of this project is to gain scientific knowledge for the rational design, fabrication, and demonstration of a robust, highly efficient, and low-cost SOEC technology based on a proton-conducting electrolyte membrane for hydrogen production. We focused on better understanding the degradation mechanisms of proton-conducting electrolytes, air electrodes, and catalyst materials under electrolysis mode to develop an effective strategy for rationalizing new materials that are vital for enhancing cell performance and durability. The scope includes enhancing the performance and durability of the electrolyte and electrode materials under realistic operating conditions, developing highly active and robust catalysts to minimize electrode losses while improving tolerance to contaminant poisoning, revealing the mechanism of enhanced activity and stability of the catalyst, and understanding the underlying degradation mechanisms. In addition, various characterization techniques were employed to gain a fundamental understanding of the materials’ behavior and their impact on cell performance, providing vital information to guide materials discovery and cell design. After defect chemistry engineering, the optimized donor and acceptor co-doped electrolytes BaMo/W 0.03 Ce 0.71 Yb 0.26 O 3-δ (BM/W03) showed substantially improved chemical stability against high concentrations of CO 2 and H 2 O compared to the state-of-the-art electrolyte (BaZr 0.1 Ce 0.7 Y 0.1 Yb 0.1 O 3-δ , BZCYYb1711) while maintaining comparable ionic conductivity and ionic transference number. To bypass the inherent trade-off between conductivity and chemical stability, we fabricated a bi-layer electrolyte composed of BZCYYb1711 coated with a highly-stable thin layer of BaHf 0.83 Yb 0.17 O 3-δ (BHYb). This bi-layer electrolyte displayed excellent chemical stability against high concentration CO 2 ; there was no detectable formation of BaCO 3 after exposure to 97% CO 2 (with 3% H 2 O) at 500 °C for 1000 hours and the rate of degradation in resistance was about 0.4% per 1,000 hours (kh). In contrast, the same BZCYYb1711 electrolyte without a BHYb coating degraded significantly under the same testing conditions; the degradation rate was increased to 5.1%/kh. In addition, a triple conducting air electrode Ba 0.9 Pr 0.1 Hf 0.1 Y0.1Co 0.8 O 3-δ (BPHYC) was developed by heavily doping transition metal ions into a proton-conducting material. This air electrode material, composed of 3 distinct phases, exhibits superior electrocatalytic activity due to the synergistic effect from the three component phases. Moreover, an active and durable catalyst, La 2 Ni 0.5 Fe 0.5 O 4+δ (LNF), was developed, showing excellent catalytic activity and contaminant tolerance, with a degradation rate of only 0.49%/kh when exposed to high concentrations of steam and Cr. Finally, single cells were constructed from the best electrolytes, electrodes, and catalyst coatings developed in this project. These cells demonstrated superior high current density at a given cell voltage, high roundtrip efficiency, and remarkable durability (up to 1000 hours of operation).
Achieving Highly Reproducible Results in Graphite-based Li-ion Full Coin Cells
Electrode materials, cathodes or anodes, are mostly evaluated in half coin cells where lithium (Li) metal is used. However, due to the instability nature of Li metal, the cycling performances of the half cells is more likely reflecting Li anode stability instead of the coupled electrodes, questioning the conclusions. Full coin cells utilizing graphite as the anode effectively assesses materials. But the key factors of preparing full coin cells with reproducible performances have rarely been discussed and overlooked leading to many inconsistent results. This work discusses the scientific gap between cell preparation and observed electrochemical performances to unveil the key parameters for achieving consistent and reliable results in full coin cells, critical for effective evaluation of any new materials tested under relevant conditions. The knowledge from this work is broadly applicable in other full cells systems such as Si-based full cells or Na-ion batteries.
Synthesis, characterization, and thermodynamic study of selected K-based zeolites
Potassium-rich zeolites often occur in cementitious systems, as K{sup +} is widespread in various cementitious materials, such as Portland, blended and alkali-activated cements. The knowledge of their stability and of thermodynamic models for solid solutions with Na{sup +} and Ca{sup 2+} are critical to understand long-term development and durability in such cements. Completing previous studies on Na- and Ca-based zeolites, the current work aims to determine the thermodynamic data of 14 types of K-based zeolites, which could possibly form in cementitious systems. The zeolites were synthesized hydrothermally, exchanged with K{sup +}, and characterized thoroughly with respect to framework structures, elemental compositions, water contents, and bond variations. Their thermodynamic properties were derived from the experimental solubility data, which allowed establishing predominance diagrams in the K{sub 2}O-SiO{sub 2}-Al{sub 2}O{sub 3}-H{sub 2}O system. The K-based zeolites typically showed the lowest solubility between 0 and 100 °C, with the notable exception of Ca-gismondine and two Na-based zeolites: natrolite and Na-mordenite.
The Archaeal Proteome Project advances knowledge about archaeal cell biology through comprehensive proteomics
Abstract While many aspects of archaeal cell biology remain relatively unexplored, systems biology approaches like mass spectrometry (MS) based proteomics offer an opportunity for rapid advances. Unfortunately, the enormous amount of MS data generated often remains incompletely analyzed due to a lack of sophisticated bioinformatic tools and field-specific biological expertise for data interpretation. Here we present the initiation of the Archaeal Proteome Project (ArcPP), a community-based effort to comprehensively analyze archaeal proteomes. Starting with the model archaeon Haloferax volcanii , we reanalyze MS datasets from various strains and culture conditions. Optimized peptide spectrum matching, with strict control of false discovery rates, facilitates identifying > 72% of the reference proteome, with a median protein sequence coverage of 51%. These analyses, together with expert knowledge in diverse aspects of cell biology, provide meaningful insights into processes such as N-terminal protein maturation, N -glycosylation, and metabolism. Altogether, ArcPP serves as an invaluable blueprint for comprehensive prokaryotic proteomics.
Risk-informed Predictive Analytics To Achieve Cost-effective Condition-based Monitoring And Maintenance Strategy
The research involves developing risk-informed predictive analytic capabilities to achieve condition-based monitoring and maintenance strategies to reduce overall maintenance costs. The research utilizes data (real-time data, periodic data, and institutional knowledge) related to a particular plant asset from a specific nuclear plant site to develop risk-informed predictive analytic algorithms. The developed algorithms and codes are used to optimize the maintenance strategy and estimate/forecast generation costs based on the state of health of the plant asset. Developed codes specifically include 1. Parameter estimation code based on Bayesian inference 2. Statistical data analysis code 3. Feature engineering code 4. Health classifier code 5. Diagnosis code 6. Prognosis code 7. Hazard code 8. Generation risk code 9. Economic code
Elucidating Arsenic and Selenium Speciation in Coal Fly Ashes
Coal fly ash (CFA) is produced during the coal combustion process and contains trace elements (<100 ppm) including selenium (Se) and arsenic (As), both detrimental for environmental and human health. Existing management strategies for CFAs involve disposal in landfills and ash ponds, as well as beneficial usage in other applications such as in concrete. Both the direct disposal and beneficial usage of CFA raise concerns for environmental hazards due to the potential leaching of Se and As. CFAs were classified as reusable material by the U.S. Environmental Protection Agency (EPA) with the first federal regulation (Disposal of Coal Combustion Residuals from Electric Utilities, CCR) for its disposal established six years ago. During coal combustion process, parameters such as furnace firing type, emissions controls, coal rank, use of additives, and particulate matter controls, could contribute to significant variability in As/Se concentrations and their speciation. Although there have been a handful of studies on As/Se speciation on small sets of samples, they do not fully represent the current state of coal-fired electrical generating units. Little information exists on the detailed speciation (e.g. oxidation state, complexation state) of As/Se in large set of fly ash samples. To better investigate the role of the potential contributing parameters, a large-scale survey study with representative samples of typical coal source and combustion conditions is highly desired. The overall goal of this research is to systematically characterize As and Se speciation of representative coal fly ash samples using state-of-the-art synchrotron based spectroscopic and microscopic techniques, in order to develop a correlation between coal source/type, operation condition, As/Se speciation, and As/Se mobility. A detailed survey study was conducted documenting the current state-of-knowledge on fossil power generating units as a function of coal type/source, operating conditions, environmental control systems, additive use, and fly ash handling methods. Based on this survey, a matrix of fly ash samples representing a range of conditions were chosen and collected. The collected ash samples were analyzed for bulk characteristics such as elemental composition, microstructure, chemical and mineralogical composition, surface area, and particle size distribution. State-of-the-art synchrotron X-ray microscopy and spectroscopy techniques were applied to reveal the molecular scale speciation information of As and Se, such as oxidation state, association with other elements/minerals, and complexation states.
Effect of Polymer Chain Length on the Superlattice Assembly of Functionalized Gold Nanoparticles
We report on the assembly of gold nanoparticle (AuNPs) superlattices at the liquid/vapor interface and in the bulk of their suspensions. Interparticle distances in the assemblies are achieved on multiple length scales by varying chain lengths of surface grafted AuNPs by polyethylene glycol (PEG) with molecular weights in the range 2000–40,000 Da. Crystal structures and lattice constants in both 2D and 3D assemblies are determined by synchrotron-based surface-sensitive and small-angle X-ray scattering. Here, assuming knowledge of grafting density, we show that experimentally determined interparticle distances are adequately modeled by spherical brushes close to the θ point (Flory–Huggins parameter, x ≈ 1/2) for 2D superlattices at a liquid interface and a nonsolvent (χ = ∞) for the 3D dry superlattices.
Decentralized digital twins of complex dynamical systems
Abstract In this article, we introduce a decentralized digital twin (DDT) modeling framework and its potential applications in computational science and engineering. The DDT methodology is based on the idea of federated learning, a subfield of machine learning that promotes knowledge exchange without disclosing actual data. Clients can learn an aggregated model cooperatively using this method while maintaining complete client-specific training data. We use a variety of dynamical systems, which are frequently used as prototypes for simulating complex transport processes in spatiotemporal systems, to show the viability of the DDT framework. Our findings suggest that constructing highly accurate decentralized digital twins in complex nonlinear spatiotemporal systems may be made possible by federated machine learning.
Detecting Anomalies in Time Series Using Kernel Density Approaches
This paper introduces a novel anomaly detection approach tailored for time series data with exclusive reliance on normal events during training. Our key innovation lies in the application of kernel-density estimation (KDE) to scrutinize reconstruction errors, providing an empirically derived probability distribution for normal events post-reconstruction. This non-parametric density estimation technique offers a nuanced understanding of anomaly detection, differentiating it from prevalent threshold-based mechanisms in existing methodologies. In post-training, events are encoded, decoded, and evaluated against the estimated density, providing a comprehensive notion of normality. In addition, we propose a data augmentation strategy involving variational autoencoder-generated events and a smoothing step for enhanced model robustness. The significance of our autoencoder-based approach is evident in its capacity to learn normal representation without prior anomaly knowledge. Through the KDE step on reconstruction errors, our method addresses the versatility of anomalies, departing from assumptions tied to larger reconstruction errors for anomalous events. Our proposed likelihood measure then distinguishes normal from anomalous events, providing a concise yet comprehensive anomaly detection solution. The extensive experimental results support the feasibility of our proposed method, yielding significantly improved classification performance by nearly 10% on the UCR benchmark data.
A Radiative Transfer Model for Patchy Landscapes Based on Stochastic Radiative Transfer Theory
The availability of global high-resolution land cover maps provides promising a priori knowledge for characterizing subpixel heterogeneity and improving predictions of directional reflectance of coarse-resolution pixels. Due to mutual shadowing and sheltering effects between the adjacent forest and cropland patches, the spectral nonlinear mixing of patchy ecotones is significant, especially when the sun illuminates the ecotone from the forest side with high solar zenith angle. The spectral linear mixture (SLM) approach leads to overestimation of the bidirectional reflectance factor (BRF) in the red band in the principal plane (PP), with a maximum absolute error (MAE) of 0.0063 and a maximum relative error (MRE) of 52.5%, and to underestimation in the near-infrared band in PP with an MAE of 0.0940 and an MRE of 14.5%. In a scenario with randomly distributed boundary orientations, the overestimation of SLM increases with the degree of fragmentation and the view zenith angle. We propose a Radiative Transfer model for patchy ECotones (RTEC). which improves R² from 0.61 to 0.94 in the red band of Landsat-8 directional reflectance at the validation site. The RTEC model provides an efficient and analytical approach for directional reflectance predictions over heterogeneous patchy landscapes at coarse resolution and will be used for biophysical parameter retrievals [e.g., the leaf area index (LAI)] in future applications.
Design principles for heterointerfacial alloying kinetics at metallic anodes in rechargeable batteries
How surface chemistry influences reactions occurring thereupon has been a long-standing question of broad scientific and technological interest. Here, we consider the relation between the surface chemistry at interfaces and the reversibility of electrochemical transformations at rechargeable battery electrodes. Using Zn as a model system, we report that a moderate strength of chemical interaction between the deposit and the substrate—neither too weak nor too strong—enables highest reversibility and stability of the plating/stripping redox processes. Focused ion beam and electron microscopy were used to directly probe the morphology, chemistry, and crystallography of heterointerfaces of distinct natures. Analogous to the empirical Sabatier principle for chemical heterogeneous catalysis, our findings arise from competing interfacial processes. Using full batteries with stringent negative electrode–to–positive electrode capacity (N:P) ratios, we show that such knowledge provides a powerful tool for designing key materials in highly reversible battery systems based on Earth-abundant, low-cost metals such as Zn and Na.
MatLab Package for Whispering Gallery Mode Data
Dye-doped whispering gallery mode resonator (WGMR) microspheres yield highly structured emission spectra that are extremely sensitive to their environment and are of intense interest for use in a variety of sensing applications. Efforts to leverage the unique sensitivities of WGMRs have relied on stringent experimental requirements to correlate specific spectral shifts/changes to an analyte/stimulus such as 1) precise positional knowledge, 2) reference spectra for each microsphere, and 3) high mechanical stability. Consequently, these can hinder adequate mixing or incorporation of analytes and creates challenges for remote sensing. The MATLAB codes provided here are to be used in conjunction with a continuous flow technique for measuring WGM spectra of dye-doped microspheres suspended in solution. One MATLAB script, smooths the data, automatically baseline corrects it to isolate the whispering gallery modes (WGM) from the unwanted bulk emission, and assesses the similarity of each spectrum to aid in selecting a set of unique WGM spectra for further analysis. The next script is designed to analyze WGM spectra to determine the size of the resonator and the refractive index (RI) of its local environment without a priori knowledge of the individual microsphere. The final script allows the user to cluster spheres based on the product of their RI and radius and the contrast ratio of the RI of the sphere material and that of its environment by using a shared nearest neighbor spectral clustering algorithm.
Direct Radiative Effects of Aerosols at the ARM SGP and TWP Sites (DOE ASR Final Report)
This effort has examined and quantified aerosol direct radiative effects (DREs) and associated uncertainties at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plain (SGP) and Tropical Western Pacific (TWP) sites under both clear and all sky conditions by taking advantage of the advanced ARM long-term comprehensive measurements of aerosol, cloud, radiation, and atmospheric state. This effort has filled the knowledge gap in aerosol DREs at the SGP and TWP under all sky conditions based on the ARM observations.
Quantifying Lithium Ion Exchange in Solid Electrolyte Interphase (SEI) on Graphite Anode Surfaces
Solid Electrolyte Interphase (SEI) has been identified as the most important and least understood component in lithium-ion batteries. Despite extensive studies in the past two decades, a few mysteries remain: what is the chemical form of and degree of mobility of Li + in the interphase? What fraction of Li + is permanently immobilized in the SEI, while the rest are still able to participate in the cell reactions via the ion-exchange process with Li + in the electrolyte? This study attempted to answer, in part, these questions by using 6 Li and 7 Li-isotopes to label SEIs and electrolytes, and then quantifying the distribution of permanently immobilized and ion-exchangeable Li + with solid-state NMR and ToF-SIMS. The results showed that the majority of Li + were exchanged after one SEI formation cycle, and a complete exchange after 25 cycles. Ion exchange by diffusion based on concentration gradient in the absence of applied potential also occurred simultaneously. This knowledge will provide a foundation for not only understanding but also designing better SEIs for future battery chemistries.