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At least 235 records · Page 13

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DOE OSTI2019

Understanding the Interactions of Seawater Ions with Amidoxime through X-Ray Crystallography

Insoluble polymer substrates functionalized with the amidoxime (R-C(NH 2 )=NOH) functional group have been demonstrated as a technically feasible platform for extracting uranium from seawater, a potential source of extremely abundant uranium for use as nuclear fuel. While it is possible to isolate macroscopic amounts of uranium from the ocean with a positive energy return on investment using these materials, both the economic and energetic costs are many times greater than those of terrestrial uranium mining. Currently, the major contribution to this cost is the production of the sorbent itself, so being able to recycle the sorbent even a small number of times will have a huge impact on lowering the cost of their use. However, amidoxime resins show capacity fading when stripped by strong acids, presently limiting their recyclability. Both alternative extractants and alternative elution chemistries are under development with promising results but are yet at too early a stage to make predictions about their ultimate success. Given the potentially huge impact of a successful recycling process on the viability of seawater extraction of uranium, there is a strong need to pursue additional routes to elution chemistry. During the course of this project, we studied the interactions of amidoxime-containing small molecules with the abundant metal ions in seawater, including Li, Na, K, Mg, Ca, Fe, Cu, and V, to understand the interactions of [UO 2 ] 2+ with amidoxime. By using small molecules with multiple adjacent functional groups, we crystallized the resulting metal complexes and used single crystal X-ray diffraction (SCXRD) as our primary tool for structural characterization. We also investigated the use of solutions of hydroxylammonium salts in weak acids as eluents for stripping and recycling amidoxime-based sorbents. The replacement of strong acids, which react with and destroy the amidoxime functional groups, with weak acids based on hydroxylammonium, a reagent that is actually used to make the amidoxime groups, is expected to avoid capacity loss on recycling and possibly even regenerate functionality that was lost due to exposure to the marine environment.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2021

H 2 production in the 10 B(n,α) 7 Li reaction in water

Herein we demonstrate a method for measuring the H2 produced in water from the 10 B(n,α) 7 Li fission reaction. Low energy neutrons from the NIST Center for Neutron Research interact with borate-containing water in a temperature-controlled high pressure cell made from titanium. After exposure for one to several hours, the water is extracted and sparged with argon. H 2 entrained in the sparging gas is sampled with a small mass spectrometer. To determine the neutron exposure, a small amount of sodium is included in the borate solution. The water is collected and 24 Na activation is measured in a counting apparatus on the following day. The G-value for H 2 at room temperature is found to be (1.18 ± 0.10) molecules H 2 /100eV, in good agreement with previous estimates and recent modeling calculations.

10B↗

DOE OSTI2024

Nondestructive flash cathode recycling

Effective recycling of end-of-life Li-ion batteries (LIBs) is essential due to continuous accumulation of battery waste and gradual depletion of battery metal resources. The present closed-loop solutions include destructive conversion to metal compounds, by destroying the entire three-dimensional morphology of the cathode through continuous thermal treatment or harsh wet extraction methods, and direct regeneration by lithium replenishment. Here, we report a solvent- and water-free flash Joule heating (FJH) method combined with magnetic separation to restore fresh cathodes from waste cathodes, followed by solid-state relithiation. The entire process is called flash recycling. This FJH method exhibits the merits of milliseconds of duration and high battery metal recovery yields of ~98%. After FJH, the cathodes reveal intact core structures with hierarchical features, implying the feasibility of their reconstituting into new cathodes. Relithiated cathodes are further used in LIBs, and show good electrochemical performance, comparable to new commercial counterparts. Life-cycle-analysis highlights that flash recycling has higher environmental and economic benefits over traditional destructive recycling processes.

25 ENERGY STORAGE↗

DOE OSTI2023

DQ Admittance Model Extraction for IBRs via Gaussian Pulse Excitation

While $dq$ admittance models have shown to be very useful for stability analysis, extracting admittance models of inverter-based resources (IBRs) from the electromagnetic transient (EMT) simulation environment using frequency scans takes time. In this letter, a new perturbation method based on Gaussian pulses in combination with the system identification algorithms shows great promise for parametric $dq$ admittance model extraction. We present the $dq$ admittance model extracting method for a type-4 wind turbine. Challenges in implementing Gaussian pulse excitation are also pointed out. In conclusion, the extracted $dq$ admittance model via the new method shows to have a high matching degree with the measurements obtained from frequency scans.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Machine learning enabled lineshape analysis in optical two-dimensional coherent spectroscopy

Optical two-dimensional (2D) coherent spectroscopy excels in studying coupling and dynamics in complex systems. The dynamical information can be learned from lineshape analysis to extract the corresponding linewidth. However, it is usually challenging to fit a 2D spectrum, especially when the homogeneous and inhomogeneous linewidths are comparable. We implemented a machine learning algorithm to analyze 2D spectra to retrieve homogeneous and inhomogeneous linewidths. The algorithm was trained using simulated 2D spectra with known linewidth values. The trained algorithm can analyze both simulated (not used in training) and experimental spectra to extract the homogeneous and inhomogeneous linewidths. Finally, this approach can be potentially applied to 2D spectra with more sophisticated spectral features.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Advances in hexagon mesh-based flow direction modeling

Watershed delineation and flow direction representation are the foundations of streamflow routing in spatially distributed hydrologic modeling. A recent study showed that hexagon-based watershed discretization has several advantages compared to the traditional Cartesian (latitude–longitude) discretization, such as uniform connectivity and compatibility with other Earth system model components based on unstructured mesh systems (e.g., oceanic models). Despite these advantages, hexagon-based discretization has not been widely adopted by the current generation of hydrologic models. One major reason is that there is no existing model that can delineate hexagon-based watersheds while maintaining accurate representations of flow direction across various spatial resolutions. In this study, we explored approaches such as spatial resampling and hybrid breaching-filling stream burning techniques to improve watershed delineation and flow direction representation using a newly developed hexagonal mesh watershed delineation model (HexWatershed). We applied these improvements to the Columbia River basin and performed 16 simulations with different configurations. The results show that (1) spatial resampling modulates flow direction around headwaters and provides an opportunity to extract subgrid information; and (2) stream burning corrects the flow directions in mountainous areas with complex terrain features.

58 GEOSCIENCES↗

DOE OSTI2022

Seamless Wireless Communication Platform for Internet of Things Applications

The rapid growth of the Internet of Things (IoT) devices resulted in the proliferation of wireless technologies to cater to their increasing data rate requirements and support multiple applications. However, such ever-increasing wireless technologies present numerous challenges such as incompatible wireless standards, increased energy consumption, and insecure communication. The traditional gateways proposed in the literature suffers from limitations such as computational complexity, resource requirements, increased cost, and device size. We vision an era of seamless wireless communication to alleviate the aforementioned challenges in IoT applications. through three inter-dependent functionalities namely detection and identification of wireless technologies, energy-efficient transmit power control, and secure end-to-end communication. To prove the concept, a new gateway is proposed to achieve these three functionalities with only physical layer measurements so that the different communication protocols in the higher layers can be avoided. Novel schemes are conceptualized for resource-limited seamless IoT applications. Moreover, the conceptual seamless IoT platform is validated through software-based computer simulation and software-defined radio-based testbed implementation. Finally, the preliminary analysis demonstrates that the proposed platform has great potential in advancing seamless IoT applications.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Functionalized Mesoporous Carbon and Silica for Effective Recovery of Rare Earth Elements from Magnet Scrap

The dependence on international supplies of rare earth elements (REEs) has prompted the US to explore alternative sources and sustainable technologies for domestic REE production. One potential source is the secondary electronic and industrial wastes across the US. These hazardous wastes require high costs for the maintenance and remediation, while their high-REE contents offer unique opportunities for REE recovery. However, current hydrometallurgical technologies for REE extraction are energy intensive and costly, with low REE recovery efficiency and the generation of hazardous secondary wastes. Thus, it is beneficial to develop environmentally friendly technologies for REE extraction from the secondary wastes. This project aims to develop novel functionalized mesoporous carbon fiber (MCF) and silica materials for effective recovery of REEs from NdFeB magnet scrap.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Carrier Dynamics of Polar, Semipolar, and Nonpolar InGaN/GaN LEDs Measured by Small-Signal Electroluminescence

The carrier dynamics in InGaN/GaN LEDs are directly tied to their efficiency and maximum modulation speed, which are important metrics for solid-state lighting, displays, and optical communication. We measure the carrier dynamics of nonpolar, semipolar, and commercial c-plane InGaN/GaN LEDs using small-signal electroluminescence methods. Rate equations and a small-signal circuit are used to model the carrier dynamics. The model is fit to the optical frequency response and input impedance of the LEDs to extract the carrier lifetimes and the recombination rates. The results offer insight into the underlying causes of efficiency droop and the green gap, and inform device design strategies.

42 ENGINEERING↗

DOE OSTI2026

Signatures of Thermoreversible Associations in X-ray and Neutron Scattering from Dilute Polyzwitterion Solutions

In aqueous solutions of polyzwitterions (PZs), an interplay between dipole–dipole interactions and hydration of zwitterionic groups can lead to thermoreversible associations, which have been difficult to detect in experiments. Here, in this study, we investigated dilute aqueous solutions of poly(1-(3-sulphonatopropyl)-2-vinylpyridinium) (P2VPPS) using small-angle X-ray and neutron scattering (SAXS and SANS) to probe the structure and neutron spin-echo (NSE) spectroscopy to probe dynamics. The SAXS and SANS data show that the correlation length increases with an increase in the concentration of P2VPPS for three different molecular weights. The addition of 0.1 M NaCl to one of the solutions led to almost no dependence of the correlation length on the concentration. Such a concentration dependence of the correlation length suggests the formation of clusters driven by thermoreversible associations in the solutions. The NSE measurements show that the solutions with a larger correlation length display slower relaxation, reflecting the reduced mobility of larger clusters. These results should be considered as signatures of thermoreversible associations in the solutions of P2VPPS. To establish a quantitative link between local structure (clusters) and dynamics in dilute solutions of P2VPPS, we combined a thermoreversible gelation theory for the structure of PZ solutions (Li, S.-F.; Muthukumar, M. Theory of Thermoreversible Gelation and Anomalous Concentration Fluctuations in Polyzwitterion Solutions. J. Chem. Phys. 2024, 161, 024903) with a model for the dynamics of the clusters (generalized Zimm model), developed in this work. Using such a theoretical framework, we have predicted the distribution of clusters in the solutions probed with SANS and SAXS. With the distributions, the generalized Zimm model has been used to extract the diffusion constant of the clusters and their characteristic size from the NSE data, where the latter agrees with the values estimated from the SAXS/SANS data. These findings confirm the presence of thermoreversible associations and establish a quantitative link between local structure (clusters) and dynamics in dilute solutions of P2VPPS. Furthermore, with growing interest in technological applications, this work can provide useful insights into the structural and dynamical properties of other PZ solutions.

field theory↗

DOE OSTI2024

MedNAS: Multiscale Training-Free Neural Architecture Search for Medical Image Analysis

Deep neural networks have demonstrated impressive results in medical image analysis, but designing suitable architectures for each specific task is expertise dependent and time consuming. Neural architecture search (NAS) offers an effective means of discovering architectures. It has been highly successful in numerous applications, particularly in natural image classification. Yet, medical images possess unique characteristics, such as small regions and a wide variety of lesion sizes, that differentiate them from natural images. Furthermore, most current NAS methods struggle with high computational costs, especially when dealing with high-resolution image datasets. In this article, we present a novel evolutionary NAS method called multiscale training-free neural architecture search (MSTF-NAS) to address these challenges. Specifically, to accommodate the broad range of lesion region sizes in disease diagnosis, we develop a new reduction cell search space that enables the search algorithm to explicitly identify the optimal scale combination for multiscale feature extraction. Further, to overcome the issue of high computational costs, we utilize training-free indicators as performance measures for candidate architectures, which allows us to search for the optimal architecture more efficiently. More specifically, by considering the capability and simplicity of various networks, we formulate a multiobjective optimization problem that involves two training-free indicators and model complexity for candidate architectures. Extensive experiments on a large medical image benchmark and a publicly available breast cancer detection dataset are conducted. The empirical results demonstrate that our MSTF-NAS outperforms both human-designed architectures and current state-of-the-art NAS algorithms on both datasets, indicating the effectiveness of our proposed method.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Constraining AGN Torus Sizes with Optical and Mid-infrared Ensemble Structure Functions

We propose a new method to constrain the size of the dusty torus in broad-line active galactic nuclei (AGNs) using optical and mid-infrared (MIR) ensemble structure functions (SFs). Because of the geometric dilution of the torus, the MIR response to optical continuum variations has suppressed variability with respect to the optical that depends on the geometry (e.g., size, orientation, opening angle) of the torus. More extended tori have steeper MIR SFs with respect to the optical SFs. We demonstrate the feasibility of this SF approach using simulated AGN light curves and a geometric torus model. While it is difficult to use SFs to constrain the orientation and opening angle due to the insensitivity of the SF on these parameters, the size of the torus can be well determined. Applying this method to the ensemble SFs measured for 587 SDSS quasars, we measure a torus R–L relation of $\mathrm{log}\,{R}_{\mathrm{eff}}(\mathrm{pc})={0.51}_{-0.04}^{+0.04}\times \mathrm{log}({{L}}_{\mathrm{bol}}/{10}^{46}\,\mathrm{erg}\ {{\rm{s}}}^{-1})-{0.38}_{-0.01}^{+0.01}$ in the WISE W1 band and sizes ~1.4 times larger in the W2 band, which are in good agreement with dust reverberation mapping measurements. Compared with the reverberation mapping technique, the SF method is much less demanding in data quality and can be applied to any optical+MIR light curves for which a lag measurement may not be possible, as long as the variability process and torus structure are stationary. While this SF method does not extract all information contained in the light curves (i.e., the transfer function), it provides an intuitive interpretation for the observed trends of AGN MIR SFs compared with optical SFs.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2004

Torque Transient of Magnetically Drive Flow for Viscosity Measurement

Viscosity is a good indicator of structural changes for complex liquids, such as semiconductor melts with chain or ring structures. This paper discusses the theoretical and experimental results of the transient torque technique for non-intrusive viscosity measurement. Such a technique is essential for the high temperature viscosity measurement of high pressure and toxic semiconductor melts. In this paper, our previous work on oscillating cup technique was expanded to the transient process of a magnetically driven melt flow in a damped oscillation system. Based on the analytical solution for the fluid flow and cup oscillation, a semi-empirical model was established to extract the fluid viscosity. The analytical and experimental results indicated that such a technique has the advantage of short measurement time and straight forward data analysis procedures

Ban, Heng↗

DOE OSTI2021

Expanding the Ambient-Pressure Phase Space of CaFe 2 O 4 -Type Sodium Postspinel Host–Guest Compounds

CaFe 2 O 4 -type sodium postspinels (Na-CFs), with Na + occupying tunnel sites, are of interest as prospective battery electrodes. While many compounds of this structure type require high-pressure synthesis, several compounds are known to form at ambient pressure. Here we report a large expansion of the known Na-CF phase space at ambient pressure, having successfully synthesized NaCrTiO 4 , NaRhTiO 4 , NaCrSnO 4 , NaInSnO 4 , NaMg 0.5 Ti 1.5 O 4 , NaFe 0.5 Ti 1.5 O 4 , NaMg 0.5 Sn 1.5 O 4 , NaMn 0.5 Sn 1.5 O 4 , NaFe 0.5 Sn 1.5 O 4 , NaCo 0.5 Sn 1.5 O 4 , NaNi 0.5 Sn 1.5 O 4 , NaCu 0.5 Sn 1.5 O 4 , NaZn 0.5 Sn 1.5 O 4 , NaCd 0.5 Sn 1.5 O 4 , NaSc 1.5 Sb 0.5 O 4 , Na 1.16 In 1.18 Sb 0.66 O 4 , and several solid solutions. In contrast to earlier reports, even cations that are strongly Jahn–Teller active (e.g., Mn 3+ and Cu 2+ ) can form Na-CFs at ambient pressure when combined with Sn 4+ rather than with the smaller Ti 4+ . Order and disorder are probed at the average and local length-scales with synchrotron powder X-ray diffraction and solid-state NMR spectroscopy. Strong ordering of framework cations between the two framework sites is not observed, except in the case of Na 1.16 In 1.18 Sb 0.66 O 4 . This compound is the first example of an Na-CF that contains Na + in both the tunnel and framework sites, reminiscent of Li-rich spinels. Trends in the thermodynamic stability of the new compounds are explained on the basis of crystal-chemistry and density functional theory (DFT). Further DFT calculations examine the relative stability of the CF versus spinel structures at various degrees of sodium extraction in the context of electrochemical battery reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Deep-Learning-Enabled Crack Detection and Analysis in Commercial Lithium-Ion Battery Cathodes

We report in Li-ion batteries, the mechanical degradation initiated by micro cracks is one of the bottlenecks for enhancing the performance. Quantifying the crack formation and evolution in complex composite electrodes can provide important insights into electrochemical behaviors under prolonged and/or aggressive cycling. However, observation and interpretation of the complicated crack patterns in battery electrodes through imaging experiments are often time-consuming, labor intensive, and subjective. Herein, a deep learning-based approach is developed to extract the crack patterns from nanoscale hard X-ray holo-tomography data of a commercial 18650-type battery cathode. Efficient and effective quantification of the damage heterogeneity with automation and statistical significance is demonstrated. The crack characteristics are further associated with the active particles’ packing densities and a potentially viable architectural design is discussed for suppressing the structural degradation in an industry-relevant battery configuration.

25 ENERGY STORAGE↗

DOE OSTI2022

Plot2Spectra: an automatic spectra extraction tool

Scientists cannot easily make use of numerical data encoded in plot images, such as of spectroscopy data, in scientific literature. Plot2Spectra was developed to use computer vision tools to automatically digitize plot images.

Jiang, Weixin↗

DOE OSTI2024

Impact of the MARATHON data on F 2⁢n⁡ /F 2⁢p and off-shell effects in light nuclei

The neutron structure function, F 2⁢n⁡ , has historically been extracted from measurements of the deuteron structure function, which is limited by our understanding of the nuclear effects on the bound proton and neutron. The MARATHON Collaboration recently extracted F 2⁢n⁡ from the comparison of 3 H and 3 He targets, where the nuclear effects are larger but nearly identical, yielding a precise extraction of F 2⁢n⁡ /F 2⁢p . Here, to ensure that this comparison is not biased by the specific model of nuclear effects used by MARATHON, we examine a range of models of the nuclear effects to obtain a more conservative, but more model-independent, extraction of F 2⁢n⁡ /F 2⁢p for comparison with deuteron extractions. Even with this approach, the results are precise enough to compare to deuteron extractions, providing new constraints on the nuclear effects in the deuteron and indicating the need for larger nuclear corrections than those included in most models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

Modeling Multi-View Impedance-Based Cross-Geometry SOH Estimator for Li-ion Batteries

Abstract: Accurately estimating battery’s State of Health (SOH) remains challenging when models must generalize across cell designs and operating conditions. Most Electrochemical Impedance Spectroscopy (EIS)-based approaches either (i) hand-engineer a few Nyquist-plot features for shallow models—fast but does not generalize across geometries—or (ii) learn directly from Nyquist plots with deep networks, which removes manual feature extraction, yet still limited to a single plot type. As a result, cross-geometry robustness and deployability on constrained Internet of Things (IoT) devices remain open problems. We propose a compact Convolutional Neural Network (CNN) (∼ 10k parameters) that takes multi-representation EIS inputs—Nyquist (real/imaginary) and phase–magnitude (|Z|/ϕ) stacked as four channels, so the model can learn complementary degradation signatures while remaining small enough for fast inference. We build a dataset from cyclic aging of two geometries (LG INR18650MJ1 cylindrical cells and LIR2032 coin cells), acquire EIS every ten cycles from 10 kHz to 10 mHz (10 points/decade), and evaluate with leave-one-cell-out testing strategy. We further study fusion vs. single-representation inputs and assess feasibility for on-device deployment (e.g., NVIDIA Jetson device). The results show that training on multiple EIS representations improves SOH estimation accuracy and cross-geometry generalization compared to single-representation models, which uses only Nyquist or phase–magnitude plots. This design targets accurate, generalizable SOH prediction without manual feature engineering while enabling practical real-time use.

Bakr, Ahmed [The University of Alabama (UA)]↗