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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Simulations of edge and SOL turbulence in diverted negative and positive triangularity plasmas

Optimizing the performance of magnetic confinement fusion devices is critical to achieving an attractive fusion reactor design. Negative triangularity (NT) scenarios have been shown to achieve excellent levels of energy confinement, while avoiding edge localized modes. Modeling turbulent transport in the edge and SOL is key in understanding the impact of NT on turbulence and extrapolating the results to future devices and regimes. Previous gyrokinetic turbulence studies have reported beneficial effects of NT across a broad range of parameters. However, most simulations have focused on the inner plasma region, neglecting the impact of NT on the outermost edge. In this work, we investigate the effect of NT in edge and scrape-off layer simulations, including the magnetic X-point and separatrix. For the first time, we employ a multi-fidelity approach, combining global, non-linear gyrokinetic simulations with drift-reduced fluid simulations, to gain a deeper understanding of the underlying physics at play. First-principles simulations using the GENE-X code demonstrate that in comparable NT and PT geometries, similar profiles are achieved, while the turbulent heat flux is reduced by more than 50% in NT. Comparisons with results from the drift-reduced fluid turbulence code GRILLIX suggest that the turbulence is driven by trapped electron modes. The parallel heat flux width on the divertor targets is reduced in NT, primarily due to a lower spreading factor S.

GENE-X↗
DOE OSTI2024

Fault-Tolerant Decentralized Control for Large-Scale Inverter-Based Resources for Active Power Tracking

Integration of inverter-based resources (IBRs) which lack the intrinsic characteristics such as the inertial response of the traditional synchronous-generator (SG)-based sources presents a new challenge in the form of analyzing the grid stability under their presence. While the dynamic composition of IBRs differs from that of the SGs, the control objective remains similar in terms of tracking the desired active power. This letter presents a decentralized primal-dual-based fault-tolerant control framework for the power allocation in IBRs. Overall, a hierarchical control algorithm is developed with a lower level addressing the current control and the parameter estimation for the IBRs and the higher level acting as the reference power generator to the low level based on the desired active power profile. The decentralized network-based algorithm adaptively splits the desired power between the IBRs taking into consideration the health of the IBRs transmission lines. The proposed framework is tested through a simulation on the network of IBRs and the high-level controller performance is compared against the existing framework in the literature. The proposed algorithm shows significant performance improvement in the magnitude of power deviation and settling time to the nominal value under faulty conditions as compared to the algorithm in the literature.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Predicting plug loads with occupant count data through a deep learning approach

Predictive control has gained increasing attention for its ability to reduce energy consumption and improve occupant comfort in buildings. The plug loads prediction is a key component for the predictive building controls, as plug loads is a major source of internal heat gains in buildings. This study proposed a novel method to apply the Long-Short-Term-Memory (LSTM) Network, a special form of Recurrent Neural Network, to predict plug loads. The occupant count and the time have been confirmed to drive the plug load profile and thus selected as the features for the plug load prediction. The LSTM network was trained and tested with ground truth occupant count data collected from a real office building in Berkeley, California. Results from the LSTM network markedly improve the prediction accuracy compared with traditional linear regression methods and the classical Artificial Neural Network. 95% of 1-hour predictions from LSTM network are within ±1 kW of the actual plug loads, given the average plug loads during the office hour is 8.6 kW. The CV(RMSE) of the predicted plug load is 11% for the next hour, and 20% for the next eight hours. Lastly, we compared four prediction approaches with the office building we monitored: LSTM vs. ARIMA, with occupant counts vs. without occupant counts. It was found, the prediction error of the LSTM approach is around 4% less than the ARIMA approach. Using occupant counts as an exogenous input could further reduce the prediction error by 5%-6%. The findings of this paper could shed light on the plug load prediction for building control optimizations such as model-predictive control.

Occupant count↗
DOE OSTI2025

Final Report for CSP Tower Public Opinion and Education Project

As part of the CSP Plant Optimization Study for the California Power Market (DE-EE0009809) the project wanted to understand the public’s opinion of the technology and and explore the types of community engagement that is needed to support such development. The initial objectives for the public perception activities were twofold. The primary objective was to gather public opinion and feedback from the communities living near the two operating solar power tower plants, Ivanpah and Crescent Dunes, and to distill lessons learned from the community engagement conducted before, during, and after the plants were developed to inform future development. This included outreach to nearby airports. The other objective was to gauge public opinion about large-scale solar, specifically CSP towers, to start educating the public on the benefits and to begin building relationships with communities of interest, initially targeting the Kingman, Arizona area. The objectives shifted after the first exploratory trip to Ivanpah and Kingman, however, as it became apparent that it would be challenging to gather public opinion from the community surrounding Ivanpah that could be useful for other community profiles, and the company wasn’t ready to address the concerns in Kingman. Another area was chosen, therefore, to represent those where future development is possible. The recently published Lawrence Berkeley National Lab Perceptions of Large-Scale Solar Project Neighbors Study exemplified public perception polling based on social science and served as the foundation for the survey questions taken to the field. The intent was to ensure that people knew their input was valued and that the time they spent was valuable for the participant as well. It has been noted in the literature that in-person interaction has greater benefits than activities online or via mail, as well as limits the expense.

14 SOLAR ENERGY↗
DOE OSTI2019

Economic analysis of a nuclear hybrid energy system in a stochastic environment including wind turbines in an electricity grid

The electricity market in the U.S. is moving toward an energy mix including more variable renewable energy (VRE) sources like wind and solar. This increasing VRE penetration is altering the profile of the net electricity demand. Normally, flexible generators (e.g. gas turbines) are used to absorb fluctuations in the electricity demand. Therefore, an increase in VRE also leads to an increase in installed capacity for such flexible generators which, in turn, may increase the price of electricity. Nuclear-Renewable Hybrid Energy Systems (N-R HES) are seen as a solution to this problem. The N-R HES contains a nuclear power plant electrically and/or thermally linked to an industrial process (IP). This paper demonstrates a new methodology and presents the corresponding RAVEN/Modelica-based software framework to evaluate the financial performance of N-R HES. The novelty of the method is that it explicitly incorporates the stochastic nature of N-R HES inputs such as electricity demand and wind speeds. The method is applied to a generic (rather than region-specific) N-R HES. The analysis shows that under the right market conditions, economic benefits can be achieved by adding a suitable IP to the base-load generator. In particular, there exists an optimal relationship between the IP capacity and the demand. Furthermore, global trends indicate VRE penetration raises the cost of electricity due to the added volatility, an issue only mitigated when operating with high profit margins for the IP.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

An experimental characterization of core turbulence regimes in Wendelstein 7-X

First results from the optimized helias Wendelstein 7-X stellarator (W7-X) have shown that core transport is no longer mostly neoclassical, as is the case in previous kinds of stellarators. Instead, power balance analysis has shown that turbulent transport poses a serious limitation to the global performance of the machine. Furthermore, several studies have found this particularly relevant for ion transport, with core ion temperatures becoming clamped at relatively low values of T i ≃ 1.7 keV, except in the few scenarios in which turbulence can be suppressed. In order to understand the precise turbulent mechanisms at play and thus design improved performance scenarios, it is important to have a clear understanding of the parametric dependencies of turbulent fluctuations, and the relation between them and turbulent transport. As a first step in this direction, in this work we use Doppler reflectometry measurements carried out during a number of relevant operational scenarios to provide a systematic characterization of ion-scale ( k ⊥ ρ i ≃ 1) density fluctuations in the core of W7-X. Then, we study the relation between fluctuation amplitude and plasma profiles and show how distinct regimes can be defined for the former, depending on normalized gradients and . Furthermore, we discuss the importance of other potentially relevant parameters such as T e / T i , E r or collisionality. Comparing the different regimes, we find that turbulence amplitude depends generally on the gradient ratio η i = , as would be expected for ITG modes, with the exception of a range of discharges, for which turbulence suppression may be better explained by an ITG to TEM transition triggered by a drop in collisionality. Finally, we show a number of scenarios under which T i,core > 1.7 keV is achieved and how core fluctuations are suppressed in all of them, thus providing experimental evidence of microturbulence being the main responsible for the limited ion confinement in W7-X.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Acute Stent-Induced Endothelial Denudation: Biomechanical Predictors of Vascular Injury

Recent concern for local drug delivery and withdrawal of the first Food and Drug Administration-approved bioresorbable scaffold emphasizes the need to optimize the relationships between stent design and drug release with imposed arterial injury and observed pharmacodynamics. In this study, we examine the hypothesis that vascular injury is predictable from stent design and that the expanding force of stent deployment results in increased circumferential stress in the arterial tissue, which may explain acute injury poststent deployment. Using both numerical simulations and ex vivo experiments on three different stent designs (slotted tube, corrugated ring, and delta wing), arterial injury due to device deployment was examined. Furthermore, using numerical simulations, the consequence of changing stent strut radial thickness on arterial wall shear stress and arterial circumferential stress distributions was examined. Regions with predicted arterial circumferential stress exceeding a threshold of 49.5 kPa compared favorably with observed ex vivo endothelial denudation for the three considered stent designs. In addition, increasing strut thickness was predicted to result in more areas of denudation and larger areas exposed to low wall shear stress. We conclude that the acute arterial injury, observed immediately following stent expansion, is caused by high circumferential hoop stresses in the interstrut region, and denuded area profiles are dependent on unit cell geometric features. Such findings when coupled with where drugs move might explain the drug–device interactions.

Conway, Claire↗
DOE OSTI2021

Normal Tissue Injury Induced by Photon and Proton Therapies: Gaps and Opportunities

Despite technological advances in radiation therapy (RT) and cancer treatment, patients still experience adverse effects. Proton therapy (PT) has emerged as a valuable RT modality that can improve treatment outcomes. Normal tissue injury is an important determinant of the outcome; therefore, for this review, we analyzed 2 databases: (1) clinical trials registered with ClinicalTrials.gov and (2) the literature on PT in PubMed, which shows a steady increase in the number of publications. Most studies in PT registered with ClinicalTrials.gov with results available are nonrandomized early phase studies with a relatively small number of patients enrolled. From the larger database of nonrandomized trials, we listed adverse events in specific organs/sites among patients with cancer who are treated with photons and protons to identify critical issues. The present data demonstrate dosimetric advantages of PT with favorable toxicity profiles and form the basis for comparative randomized prospective trials. A comparative analysis of 3 recently completed randomized trials for normal tissue toxicities suggests that for early stage non-small cell lung cancer, no meaningful comparison could be made between stereotactic body RT and stereotactic body PT due to low accrual (NCT01511081). In addition, for locally advanced non-small cell lung cancer, a comparison of intensity modulated RT with passive scattering PT (now largely replaced by spot-scanned intensity modulated PT), PT did not provide any benefit in normal tissue toxicity or locoregional failure over photon therapy. Finally, for locally advanced esophageal cancer, proton beam therapy provided a lower total toxicity burden but did not improve progression-free survival and quality of life (NCT01512589). The purpose of this review is to inform the limitations of current trials looking at protons and photons, considering that advances in technology, physics, and biology are a continuum, and to advocate for future trials geared toward accurate precision RT that need to be viewed as an iterative process in a defined path toward delivering optimal radiation treatment. A foundational understanding of the radiobiologic differences between protons and photons in tumor and normal tissue responses is fundamental to, and necessary for, determining the suitability of a given type of biologically optimized RT to a patient or cohort.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

Regional surrogates for predictive control of digital twins

Digital twins of complex systems must involve a model that is fast, generalizable, and usable for real-time control. For example, high-fidelity nonlinear multiphysics simulations can capture laser-material interactions, but are too slow for optimization or model predictive control (MPC). Reduced-order models, used to accelerate such computation, frequently fail to generalize to unseen inputs or control states. We show theoretically that this failure is intrinsic, i.e., that a learned model is non-unique outside the sampled subspace when its low-rank structure arises from limited excitation and clustered eigenvalues, rather than from a user-imposed truncation alone. Motivated by this result, we propose a control-ready regional surrogate-construction framework for both autonomous and nonautonomous dynamics; it employs Koopman lifting to represent nonlinearities, while preserving spatial locality. We illustrate our approach by constructing a control-ready surrogate for the digital twin of a thermal component of additive-manufacturing process. Our surrogate, localized in space through a von Neumann stencil, is learned from noisy high-fidelity simulations that emulate thermal-camera images collected during the manufacturing. It is linear in thermo-physically augmented states so that MPC reduces to a convex quadratic program. The surrogate requires no online correction, generalizes to unseen scan paths and power profiles of the laser, and is more than three orders of magnitude faster than a finite-difference solver. Furthermore, when the MPC sequence computed on the digital twin is applied to this solver, closed-loop temperature regulation is recovered, showing that the surrogate preserves control-relevant input-output behavior.

Data-driven model↗
DOE OSTI2024

Predictive modeling of NSTX discharges with the updated multi-mode anomalous transport module

Abstract The objective of this study is twofold: firstly, to demonstrate the consistency between the anomalous transport results produced by updated Multi-Mode Model (MMM) version 9.0.4 and those obtained through gyrokinetic simulations; and secondly, to showcase MMM’s ability to predict electron and ion temperature profiles in low aspect ratio, high beta NSTX discharges. MMM encompasses a range of transport mechanisms driven by electron and ion temperature gradients, trapped electrons, kinetic ballooning, peeling, microtearing, and drift resistive inertial ballooning modes. These modes within MMM are being verified through corresponding gyrokinetic results. The modes that potentially contribute to ion thermal transport are stable in MMM, aligning with both experimental data and findings from linear CGYRO simulations. The isotope effects on these modes are also studied and higher mass is found to be stabilizing, consistent with the experimental trend. The electron thermal power across the flux surface is computed within MMM and compared to experimental measurements and nonlinear CGYRO simulation results. Specifically, the electron temperature gradient modes (ETGM) within MMM account for 2.0 MW of thermal power, consistent with experimental findings. It is noteworthy that the ETGM model requires approximately 5.0 ms of computation time on a standard desktop, while nonlinear CGYRO simulations necessitate 8.0 h on 8 K cores. MMM proves to be highly computationally efficient, a crucial attribute for various applications, including real-time control, tokamak scenario optimization, and uncertainty quantification of experimental data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Subdominant modes and optimization trends of DIII-D reverse magnetic shear configurations

Alfvén Eigenmodes (AE) and magneto-hydrodynamic (MHD) modes are destabilized in DIII-D reverse magnetic shear configurations and may limit the performance of the device. We use the reduced MHD equations in a full 3D system, coupled with equations of density and parallel velocity moments for the energetic particles as well as the geodesic acoustic wave dynamics, to study the properties of instabilities observed in DIII-D reverse magnetic shear discharges, with the purpose of discovering ways to avoid or minimize MHD and AE activity for different magnetic field configurations and neutral beam injector (NBI) operation regimes. The simulations show at the beginning of the discharge, before the reverse shear region is formed, a plasma AE unstable and marginally MHD stable. As soon as the reverse shear region appears, ideal MHD modes are destabilized with larger growth rate than the AE. Both MHD modes and AE coexist along the discharge, although the MHD modes are more unstable as the reverse shear region deepens. AE stability can be improved if the NBI injection is off axis, because on-axis injection leads to AE with larger growth rate and frequency. In addition, decreasing the beam energy or increasing the NBI injection lead to an AE with larger growth rate and frequency, so a NBI operation in the weakly resonant regime requires higher beam energies than in the experiment (V th,ƒ /V A0 > 0.3). The MHD linear stability can be also improved if the reverse shear region and the q profile near the magnetic axis are in between the rational surfaces q = 2 and q = 1, specifically if there is a region in the core with negative shear, avoiding a flat q profile near the magnetic axis. The simulations also shows a smooth transition between MHD modes and low frequency AE, no critical β ƒ , pointing out an overlap between MHD and AE activity for modes with frequency lower than 30 kHz. This is in the range of Beta Acosutic Alfvén Eigenmodes (BAAE) and Beta induced Alfvén Eigenmodes (BAE).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Systems Level Regulation of Rhythmic Growth Rate and Biomass Accumulation in Grasses

Objectives: Several breakthroughs have been recently made in our understanding of plant growth and biomass accumulation. It was found that plant growth is rhythmically controlled throughout the day by the circadian clock through a complex interplay of light and phytohormone signaling pathways. While plants such as the C4 energy crop sorghum (Sorghum bicolor (L.) Moench) and possibly the C3 grass Brachypodium distachyon also exhibit daily rhythms in growth rate, the molecular details of its regulation remain to be explored. A better understanding of diurnally regulated growth behavior in grasses may lead to species-specific mechanisms highly relevant to future strategies to optimize energy crop biomass yield. Here we propose to devise a systems approach to identify, in parallel, regulatory hubs associated with rhythmic growth in C3 and C4 plants. We propose to use rhythmicity in daily growth patterns to drive the discovery of regulatory network modules controlling biomass accumulation. Description: The project is divided in three main parts: 1) Performing time-lapse imaging and growth measurement in B. distachyon and S. bicolor to determine growth rate dynamic during the day/night cycle. Identifying growth-associated genes whose expression patterns follow the observed growth dynamics using deep sequencing technology, 2) identifying regulators of these genes by screening for DNA-binding proteins interacting with the growth-associated gene promoters identified in Aim 1. Screens will be performed using a validated yeast-one hybrid strategy paired with a specifically designed B. distachyon and S. bicolor transcription factor libraries (1000 clones each), and 3) Selecting 50 potential growth regulators from the screen for downstream characterization. The selection will be made by using a sytems biology approach by calculating the connectivity between growth rate, rhythmic gene expression profiles and TF expression profile and determine which TF is likely part of a hub and a potential regulator of plant growth. We will confirme the 50 DNA-protein interactions using transient transcriptional assays in B. distachyon and S. bicolor, and perform further testing in vivo by measuring growth parameters in transgenic loss- or gain-of-function lines for the selected transcription factors (25 B. distachyon and 3 S. bicolor lines). In 2016 the Principal Investigator relocated the laboratory to The Scripps Research Institute (TSRI) where the project has continued with an end date of 08/31/17. Accomplishments: We successfully collected large datasets of gene expression form the model grass Brachypodium. We used and developed bioinformatics analysis tools to investigate the structure, dynamics and robustness of circadian regulated gene expression in Brachypodium. Relevant Discoveries: We were able to determine that the endogenous circadian clock appears to play a much more subdued role in growth regulation in Brachypodium, that has been demonstrated in either Arabidopsis, or crop plants like Rice, Corn and Soybean. This led to our conclusion that Brachypodium unfortunately is unlikely to serve as an informative model for understanding how growth regulation in plants is under the control of circadian network circuitry. However, we were able to leverage our datasets in Brachypodium to inform us and reinforce a large collaborative study on gene networks governing cell wall deposition in Arabidopsis. This led to a major and highly cited publication relevant to improving biomass production.

09 BIOMASS FUELS↗
DOE OSTI2025

EVs@Scale Next-Gen Profiles - Fleet Utilization 2024

As part of the U.S. Department of Energy’s EVs@Scale initiative, the Next-Gen Profiles (NGP) project provides a comprehensive, data-driven analysis of electric vehicle (EV) and electric vehicle supply equipment (EVSE) operations across real-world fleet deployments. This paper presents findings from the NGP’s Fleet Utilization study, which investigates operational behavior and asset usage across seventeen EV fleets and two EVSE fleets, encompassing a wide range of vehicle types and use cases. Data collected from diverse sources—varying in format and temporal resolution—are first reformatted into a unified structure. From this harmonized dataset, a suite of rigorously defined performance metrics is calculated at an hourly cadence, enabling consistent cross-comparison of charging, routing, and other key operational behaviors. Amid rapidly increasing EV adoption and growing demands for energy-efficient fleet operations, the analysis reveals clear utilization trends—including diurnal and weekly activity cycles, differences in short versus long charging session dependencies, and route-specific energy usage patterns. These findings highlight the need for tailored infrastructure strategies and the deployment of advanced energy management systems, such as Distributed Energy Resource Management Systems (DERMS) and Site Energy Management Systems (SEMS), which can optimize charging schedules and mitigate peak loads. By leveraging anonymized, harmonized datasets and standardized metrics, this study offers critical insights into fleet behavior and performance, providing a foundation to improve operational efficiency, reduce costs, and enable the scalable deployment of electrified transportation.

Wells, Landon↗
DOE OSTI2026

Correlating Surface Processing of Nb Superconducting RF Cavities with the Evolution of Surface Electronic States

Superconducting-radio frequency (RF) cavities provide an efficient way to accelerate particle beams with extremely high acceleration gradients while generating very small power dissipation. The few nanometers of the surface play a critical role in defining the RF performance of superconducting Nb based cavities. Over the past two decades, several pioneering surface treatment and processing methods have emerged, enabling remarkable improvements in superconducting cavity performance by simultaneously achieving high quality factors with increasing maximum acceleration gradients. These processing approaches include chemical polishing, distinct multi-step thermal treatments under ultra-high vacuum (UHV) conditions over low to high temperature regimes, as well as high-temperature treatments under controlled nitrogen atmospheres. Beyond their macroscopic impact on RF performance, these methods produce distinct surface oxide configurations characterized by different valence states, oxide thicknesses, chemical uniformity, and oxygen concentration profiles extending into the near-surface bulk of niobium. In this work, we are trying to understand how the surface-processing methods and the resulting oxide/oxygen profiles affect the electronic structure of surface and the mechanism of superconductivity. Using a combination of X-ray photoemission and X-ray absorption spectroscopies, we investigate how the valence-band structure and the electronic density of states (DoS) near the Fermi level evolve under different surface treatments. By employing tunable photon energies across multiple elemental absorption edges, we use resonant photoemission to disentangle and identify the elemental contributions to specific valence-band features. Our observations show that different surface-processing methods lead to distinct temperature evolutions of the DoS and valence-band states near the Fermi level. Our results suggest variations in different Nb-O orbital hybridizations in distinct processes and point towards the possibility of different underlying mechanisms of superconductivity governed by surface chemistry and oxide configuration. We also correlate these distinct superconducting mechanisms with RF cavity performance, specifically focusing on measured surface resistance, the nature of the Q-slope, and quench fields observed in superconducting RF measurements. These results will enable us to identify the potential limiting factors and relevant controllable parameters that can be further optimized to improve the performance of superconducting RF cavities.

Tripathi, Malvika [Fermilab] (ORCID:00000001989251↗
DOE OSTI2023

Development of a Heavy-Duty Electric Vehicle Integration and Implementation (HEVII) Tool

As demand for consumer electric vehicles (EVs) has drastically increased in recent years, manufacturers have been working to bring heavy-duty EVs to market to compete with Class 6-8 diesel-powered trucks. Many high-profile companies have committed to begin electrifying their fleet operations, but have yet to implement EVs at scale due to their limited range, long charging times, sparse charging infrastructure, and lack of data from in-use operation. Thus far, EVs have been disproportionately implemented by larger fleets with more resources. To aid fleet operators, it is imperative to develop tools to evaluate the electrification potential of heavy-duty fleets. However, commercially available tools, designed mostly for light-duty vehicles, are inadequate for making electrification recommendations tailored to a fleet of heavy-duty vehicles. The main challenge is that light-duty tools do not estimate real-time vehicle mass, a factor that has a disproportionate impact on the energy consumption of large commercial vehicles. The Heavy-Duty Electric Vehicle Integration and Implementation (HEVII) tool advances the state of the art in evaluating electrification potential and infrastructure requirements for fleets of commercial vehicles. In this work, the HEVII tool is demonstrated with non-uniformly sampled telematics data from an existing fleet to assess the suitability for electrification of each individual vehicle, determine optimal locations for charging infrastructure to support a fleet of EVs and analyze associated costs. Payload mass is predicted using sparse ground-truth data for all input drive cycles and an initial data analysis is conducted to assess the characteristics driving behaviors and energy consumption of the fleet using an adaptable vehicle model. Battery size requirements are determined by applying a novel charger placement algorithm to maximize routes that are viable for EVs and balance time delays with infrastructure development costs. This work details and demonstrates the different aspects of the HEVII tool, presenting preliminary results from an example use case.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Magnetic Field Vector Measurements Using Doppler-Free Saturation Spectroscopy

Experimentally measuring the magnetic-field vector topology in low-cost fusion-concept devices will provide critical information required to optimize and accelerate the development of those concepts for economical fusion energy. The magnetic-field measurement techniques most commonly used in modern tokamaks, i.e., beam-emission spectroscopy and optical emission spectroscopy, are not suitable below 5000 Gauss due to a lack of sensitivity. To diagnose magnetic field relevant to some of the ARPA-E-supported fusion concepts (50 to 1000 Gauss), a novel approach is required. Doppler-free saturation spectroscopy (DFSS) is a pump/probe laser-based technique and has been successfully demonstrated in the laboratory to provide a magnetic-field measurement accuracy of <10 Gauss. DFSS is implemented to obtain ultra-high-resolution spectra at a localized point in space. The spectral data is then fit to the Schrödinger equation for determination of the magnetic-field vector. To obtain the magnetic-field topology, the measurement spatial location is scanned over the desired region of space by steering the DFSS pump laser beam. The goal of this project is to assemble and commission a portable DFSS diagnostic capable of 2-D magnetic-field vector measurements utilizing the Hα spectral line profile.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

DLR Calculation Engine Interoperability Profile: A Project for the TOGETs Task Force

This document contains a detailed interoperability profile outlining how the components of the CIM can be used to implement DLR in support of the two use cases identified in the Use Case Document. An interoperability profile is defined by the Smart Electric Power Alliance (SEPA) as a document that “specifies standards-based requirements for interfaces or applications that are accepted by the user-community, testing authorities, and other stakeholders. It specifies configuration options within a standard’s requirements sufficient to deliver the desired level of interoperability and functionality.” To that end, this document is not in itself a standard, nor has it been approved by any formal body. Rather, it is an example of how to implement the CIM standard and has been reviewed by industry, including transmission operators and DLR vendors.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Exploring Oxygen Activity in the High Energy P2-Type Na 0.78 Ni 0.23 Mn 0.69 O 2 Cathode Material for Na-Ion Batteries

Large-scale electric energy storage is fundamental to the use of renewable energy. Recently, research and development efforts on room-temperature sodium-ion batteries (NIBs) have been revitalized, as NIBs are considered promising, low-cost alternatives to the current Li-ion battery technology for large-scale applications. Herein, we introduce a novel layered oxide cathode material, Na 0.78 Ni 0.23 Mn 0.69 O 2 . This new compound provides a high reversible capacity of 138 mAh g -1 and an average potential of 3.25 V vs Na + /Na with a single smooth voltage profile. Its remarkable rate and cycling performances are attributed to the elimination of the P2-O2 phase transition upon cycling to 4.5 V. The first charge process yields an abnormally excess capacity, which has yet to be observed in other P2 layered oxides. Metal K-edge XANES results show that the major charge compensation at the metal site during Na-ion deintercalation is achieved via the oxidation of nickel (Ni 2+ ) ions, whereas, to a large extent, manganese (Mn) ions remain in their Mn 4+ state. Interestingly, electron energy loss spectroscopy (EELS) and soft X-ray absorption spectroscopy (sXAS) results reveal differences in electronic structures in the bulk and at the surface of electrochemically cycled particles. At the surface, transition metal ions (TM ions) are in a lower valence state than in the bulk, and the O K-edge prepeak disappears. On the basis of previous reports on related Li-excess LIB cathodes, it is proposed that part of the charge compensation mechanism during the first cycle takes place at the lattice oxygen site, resulting in a surface to bulk transition metal gradient. We believe that by optimizing and controlling oxygen activity, Na layered oxide materials with higher capacities can be designed.

25 ENERGY STORAGE↗