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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 451 records · Page 25

Simple Hybrid Sea Ice Nudging Method for Improving Control Over Partitioning of Sea Ice Concentration and Thickness

Abstract To assess the effect of ocean‐atmosphere coupling in the climate response to forced sea ice loss, the Polar Amplification Model Intercomparison Project protocol includes centennial coupled atmosphere‐ocean general circulation model simulations with imposed sea ice loss. The protocol, which specifies sea ice concentration and thickness distribution targets, does not prescribe a method for achieving them. Although different methods for imposing sea ice loss (or growth) in models have been documented, testing of the method‐dependence of the resulting climate responses has been limited. Achieving the targeted sea ice state has proven to be challenging using the so‐called ghost‐flux nudging method, which induces ice melt from below, as this method does not constrain the partitioning between thickness and concentration. We propose, describe and test a simple method that combines the advantages of direct sea ice nudging and ghost‐flux nudging. The hybrid nudging method better captures the partitioning between thickness and concentration while conserving total water content. We document how this novel sea ice constraining method reaches specific targets, enhances surface turbulent heat flux responses to sea ice loss, and induces tropospheric warming for both polar regions.

54 ENVIRONMENTAL SCIENCES↗

Influence of crossover on capacity fade of symmetric redox flow cells

Volumetrically unbalanced compositionally symmetric cell cycling with potentiostatic (CV) or galvanostatic-with-potential-hold (CCCV) protocols is a rigorous technique for evaluating the calendar lifetime of reactants for redox flow batteries. Here, we evaluate the influence of reactant crossover through the membrane on symmetric cell cycling behavior. We tested symmetric cells of anthraquinone disulfonic acid (AQDS) with Nafion membranes of varied thickness and manufacture (NR211, NR212, N115, and N117, ranging 25–183 μm). Membranes were tested both as-received and pretreated with a common procedure of soaking in water at elevated temperature and then in dilute hydrogen peroxide. We found no significant difference in capacity fade rates of symmetric cells with any of the membranes as-received, indicating a negligible influence of crossover. However, we observed increased capacity fade with increased permeability through pretreated membranes. Supported by zero-dimensional modeling and operando UV-vis spectrophotometry, we propose a mechanism for net crossover in AQDS symmetric cells based on a higher time-averaged concentration of quinhydrone dimers in the non-capacity limiting side (NCLS) compared to the capacity limiting side (CLS), driving net crossover of AQDS reactants out of the CLS. Further, we illustrate other hypothetical scenarios of net crossover using the zero-dimensional model. Overall, many membrane–electrolyte systems used in symmetric cell studies have sufficiently low crossover flux as to avoid the influence of crossover on capacity fade, but under conditions of higher crossover flux, complex interactions of crossover and chemical reactions may result in diverse capacity fade trajectories, the mechanisms of which may be untangled with operando characterization and modeling.

25 ENERGY STORAGE↗

I/O performance studies of analysis workloads on production and dedicated resources at CERN

The recent evolutions of the analysis frameworks and physics data formats of the LHC experiments provide the opportunity of using central analysis facilities with a strong focus on interactivity and short turnaround times, to complement the more common distributed analysis on the Grid. In order to plan for such facilities, it is essential to know in detail the performance of the combination of a given analysis framework, of a specific analysis and of the installed computing and storage resources. This contribution describes performance studies performed at CERN, using the EOS disk-based storage, either directly or through an XCache instance, from both batch resources and highperformance compute nodes which could be used to build an analysis facility. A variety of benchmarks, both synthetic and based on real-world physics analyses and their corresponding input datasets, are utilized. In particular, the RNTuple format from the ROOT project is put to the test and compared to the latest version of the TTree format, and the impact of caches is assessed. In addition, we assessed the difference in performance between the use of storage system specific protocols, like XRootd, and FUSE. The results of this study are intended to be a valuable input in the design of analysis facilities, at CERN and elsewhere.

Sciabà, Andrea↗

Identification and Evaluation for Fueling of NRIC DOME Reactors Report

The National Reactor Innovation Center (NRIC) has designed a testbed for advanced microreactor experiments that enables and encourages technology developers to bring advanced designs closer to commercial availability. The test bed, Demonstration of Microreactor Experiments (DOME), will be used to facilitate much of the operation experimentation process of the each advanced microreactor including fueling and operational power experiments. This report identifies and evaluates the options for initial fueling the microreactors in DOME. This report also discusses the optional locations that were considered for the initial fueling of microreactor; namely the Transient Reactor Test (TREAT) reactor building, and an unspecified temporary location. But various logistical and construction issues essentially eliminated these other options from further consideration. A brief discussion in this report outlines potential equipment and protocol associated with fueling in DOME.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Fine-scale evaluation of two standard 16S rRNA gene amplicon primer pairs for analysis of total prokaryotes and archaeal nitrifiers in differently managed soils

The advance of high-throughput molecular biology tools allows in-depth profiling of microbial communities in soils, which possess a high diversity of prokaryotic microorganisms. Amplicon-based sequencing of 16S rRNA genes is the most common approach to studying the richness and composition of soil prokaryotes. To reliably detect different taxonomic lineages of microorganisms in a single soil sample, an adequate pipeline including DNA isolation, primer selection, PCR amplification, library preparation, DNA sequencing, and bioinformatic post-processing is required. Besides DNA sequencing quality and depth, the selection of PCR primers and PCR amplification reactions arguably have the largest influence on the results. This study tested the performance and potential bias of two primer pairs, i.e., 515F (Parada)-806R (Apprill) and 515F (Parada)-926R (Quince) in the standard pipelines of 16S rRNA gene Illumina amplicon sequencing protocol developed by the Earth Microbiome Project (EMP), against shotgun metagenome-based 16S rRNA gene reads. The evaluation was conducted using five differently managed soils. We observed a higher richness of soil total prokaryotes by using reverse primer 806R compared to 926R, contradicting to in silico evaluation results. Both primer pairs revealed various degrees of taxon-specific bias compared to metagenome-derived 16S rRNA gene reads. Nonetheless, we found consistent patterns of microbial community variation associated with different land uses, irrespective of primers used. Total microbial communities, as well as ammonia oxidizing archaea (AOA), the predominant ammonia oxidizers in these soils, shifted along with increased soil pH due to agricultural management. In the unmanaged low pH plot abundance of AOA was dominated by the acid-tolerant NS-Gamma clade, whereas limed agricultural plots were dominated by neutral-alkaliphilic NS-Delta/NS-Alpha clades. This study stresses how primer selection influences community composition and highlights the importance of primer selection for comparative and integrative studies, and that conclusions must be drawn with caution if data from different sequencing pipelines are to be compared.

16S rRNA gene amplicon Illumina sequencing↗

SITCOMTN-148: LSST Camera Electro-Optical Test (Run 7) Results

This note collects results from the LSST Camera electro-optical testing prior to installation on the TMA. We describe the focal plane characterization, optimization, and the resulting default settings. Results from eo-pipe are shown for standard runs such as B-protocols, Dense and SuperDense PTCs, gain stability, OpSim runs of Darks, and Darks with variable delays. We also describe features such as e2v Persistence, ITL phosphorescence in coffee stains, remnant charge near Serial register following saturated images, vampire pixels, ITL dips, and other sensor features.

79 ASTRONOMY AND ASTROPHYSICS↗

Rapid and high-throughput determination of sorghum ( Sorghum bicolor ) biomass composition using near infrared spectroscopy and chemometrics

Compositional characterization of biomass is vital for the biofuel industry. Traditional wet chemistry-based methods for analyzing biomass composition are laborious, time-consuming, and require extensive use of chemical reagents as well as highly skilled personnel. In this study, near-infrared (NIR) spectroscopy was used to quickly assess the composition of above-ground vegetative biomass from 113 diverse, photoperiod-sensitive, biomass-type sorghum (Sorghum bicolor) accessions cultivated under field conditions in Central Illinois. Biomass samples were analyzed using NIR spectra collected in the spectral range of 867–2536 nm, with their chemical compositions determined following the National Renewable Energy Laboratory (NREL) protocol. Advanced spectral pre-treatment and band selection techniques were utilized to develop calibration models using partial least squares regression (PLSR). The models’ effectiveness was assessed through cross-validation and independent data tests. The predictions for moisture, ash, extractives, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin were accurate and reliable, demonstrating the capability of NIR spectroscopy to provide rapid and precise characterization of sorghum biomass. The results demonstrated that NIR spectroscopy is an efficient tool for rapidly characterizing sorghum biomass, making it a sustainable option for screening desirable feedstock for biofuel or bioproduct production.

09 BIOMASS FUELS↗

Data for Rapid and High-Throughput Determination of Sorghum ( Sorghum bicolor ) Biomass Composition using Near Infrared Spectroscopy and Chemometrics

Compositional characterization of biomass is vital for the biofuel industry. Traditional wet chemistry-based methods for analyzing biomass composition are laborious, time-consuming, and require extensive use of chemical reagents as well as highly skilled personnel. In this study, near-infrared (NIR) spectroscopy was used to quickly assess the composition of above-ground vegetative biomass from 113 diverse, photoperiod-sensitive, biomass-type sorghum ( Sorghum bicolor ) accessions cultivated under field conditions in Central Illinois. Biomass samples were analyzed using NIR spectra collected in the spectral range of 867–2536 nm, with their chemical compositions determined following the National Renewable Energy Laboratory (NREL) protocol. Advanced spectral pre-treatment and band selection techniques were utilized to develop calibration models using partial least squares regression (PLSR). The models’ effectiveness was assessed through cross-validation and independent data tests. The predictions for moisture, ash, extractives, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin were accurate and reliable, demonstrating the capability of NIR spectroscopy to provide rapid and precise characterization of sorghum biomass. The results demonstrated that NIR spectroscopy is an efficient tool for rapidly characterizing sorghum biomass, making it a sustainable option for screening desirable feedstock for biofuel or bioproduct production.

Biomass Analytics↗

Stress Relaxation Cracking of Alloys at Temperatures Higher Than 540°C

Type 347H stainless steel (347H SS), used in commercial concentrating solar power (CSP) thermal energy storage to store solar-salt at a temperature of 565°C, has been reported in the literature to be susceptible to stress-relaxation cracking (SRC). The welded heat-affected zone (HAZ) and fusion zone (FZ) of 347H SS, particularly in thick sections, are known to be susceptible to failure during post-weld heat treatment (reheat cracking). SRC could also occur after months or years under an elevated-temperature service environment. Two conditions must be present for failure to occur in the HAZ and/or FZ: 1) a modified or sensitized microstructure and 2) sufficiently high tensile residual stresses present at the elevated service temperature. The overarching goal of this project is to recommend SRC mitigation protocols to avoid susceptibility to fail through SRC at temperatures relevant for CSP. Post weld heat treatment conditions and alternative alloys are investigated as potential mitigation solutions to SRC. We used Gleeble thermomechanical simulation tests and finite element (FE) models to understand the susceptibility of 347H SS to SRC as a function of temperature, stress, and microstructure. We started with a literature review of weldability issues with 347H SS and techniques to mitigate SRC in 347H SS weldments. Next, we used Gleeble experiments to determine reheat cracking susceptibility in the simulated HAZ of 347SS weldments and an alternative alloy, 316L SS (NUCL 167 SPH) with boron added. We also performed Gleeble experiments to compare the reheat cracking susceptibility of 347H cross welded with two different fillers: E347, which is used in some commercial CSP TES tanks, and E16.8.2. We validated the experimental results with FE models of the residual stresses. We found that although the 316L (NUCL 167 SPH) is less susceptible to reheat cracking, it is slightly weaker than 347H and ASME BP&V codes limit its use to a service condition of 565°C. We also found that welds using E16.8.2 as the weld filler are less susceptible to failure than those using E347, likely due to the higher creep ductility of E16.8.2, and that it may be used as an alternative filler for repair welding of 347H welds or as the primary choice of filler for newly developed weld joints. We also found that post weld heat treatment could be a viable solution for mitigating stress in E347-347H SS thick, constrained welds, like those found in CSP tanks, and propose several options for mitigating SRC in existing and future TES tanks.

14 SOLAR ENERGY↗

Combining genome-wide association studies and expression quantitative trait nucleotide mapping with molecular and genetic validations to identify transcriptional networks regulating drought tolerance in Populus

Objectives: (i). To deploy a large-scale experimental drought trial for up to 1000 unique genotypes of Populus equipping the sites with controlled irrigation and drought treatments that are fully automated and monitored. FULLY COMPLETED (ii) To test the hypothesis that a suite of traits identified for drought tolerance in P. nigra can be measured in drought and control treatments in the wide germplasm collection of P. trichocarpa. FULLY COMPLETED (iii) To use established and novel GWAS model approaches to identify gene loci linked to drought tolerance traits on interest in P. trichocarpa. FULLY COMPLETED (iv) To undertake comparative analysis of GWAS results for drought tolerance traits in P. nigra and P. trichocarpa. PARTIALLY COMPLETED – remains active (v) Using RNAseq in P. trichocarpa, in droughted and control treatments to identify cis- and trans-regulated eQTN. FULLY COMPLETED (vi) Validate up to 50 cis-QTNs, from network hubs using transient protoplast assays. FULLY COMPLETED (vii) To establish Agrobacterium-based gene editing protocols in Populus. FULLY COMPLETED (viii) To utilize early leads from previous research to investigate at least 6 candidate genes for drought tolerance in Populus. FULLY COMPLETED (ix) To validate up to 20 candidate genes for drought tolerance in P. trichocarpa refined from the long-list tested in the transient assays for cis-acting hub gene targets. PARTIALLY COMPLETED- remains active.

60 APPLIED LIFE SCIENCES↗

Estimating uncertainty: A Bayesian approach to modelling photosynthesis in C3 leaves

The Farquhar-von Caemmerer-Berry (FvCB) model is extensively used to model pho-tosynthesis from gas exchange measurements. Since its publication, many methods have been developed to measure, or more accurately estimate, parameters of this model. Here, we have created a tool that uses Bayesian statistics to fit photosyn-thetic parameters using concurrent gas exchange and chlorophyll fluorescence mea-surements whilst evaluating the reliability of the parameter estimation. We have tested this tool on synthetic data and experimental data from rice leaves. Our results indicate that reliable parameter estimation can be achieved whilst only keeping one parameter, Km, that is, Michaelis constant for CO2 by Rubisco, prefixed. Additionally, we show that including detailed low CO2 measurements at low light levels increases reliability and suggests this as a new standard measurement protocol. By providing an estimated distribution of parameter values, the tool can be used to evaluate the quality of data from gas exchange and chlorophyll fluorescence measurement proto-cols. Compared to earlier model fitting methods, the use of a Bayesian statistics-based tool minimizes human interaction during fitting, reducing the subjectivity which is essential to most existing tools. A user friendly, interactive Bayesian tool script is provided.

Bayesian statistics, leaf photosynthesis, mesophyl↗

Understanding the Stability of Manganese Chromium Antimonate Electrocatalysts through Multimodal In Situ and Operando Measurements

Herein, we utilize an on-line electrochemical flow cell coupled with an inductively coupled plasma-mass spectrometer (ICP-MS) to characterize the impact of composition and reactant gas on the multielement dissolution of Mn(-Cr)-Sb-O electrocatalysts. Compared to Mn 2 O 3 and Cr 2 O 3 oxides, we find that the antimonate framework stabilizes Mn at OER potentials and Cr at both ORR and OER potentials. Furthermore, dissolution of Mn and Cr from Mn(-Cr)-Sb-O is found to be driven by ORR reaction rate, with minimal dissolution under N 2 . We observe preferential dissolution of Cr totaling 13% over 10 minutes at 0.3, 0.6, and 0.9 V vs RHE, with only 1.5% loss of Mn, indicating an enrichment of Mn at the surface of the particles. Despite this asymmetric dissolution, in situ X-ray absorption spectroscopy (XAS) showed no measurable changes in the Mn K-edge at comparable potentials. This lack of change could suggest that modification to the Mn oxidation state in the surface layer is too small or that layer is too thin to be measured with the bulk XAS measurement. Lastly, on-line ICP-MS was used to assess the effects of applied potential, scan rate, and current of Mn-Cr-Sb-O during cyclic voltammetry and accelerated stress tests. With this deeper understanding of the interplay between oxygen reduction and dissolution, testing procedures were identified to maximize both activity and stability. This work highlights the use of multi-modal in situ characterization techniques in tandem to build a more complete model of stability and develop protocols for optimizing catalyst performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Data Exchange Interface for a Standards Based Data Integration Platform

The modern electrical grid is a complex and a data rich system, requiring several sub-systems to provide the capability and support needed to perform functions such as distributed energy resource management, outage management, and fault location and isolation, to name a few. There is a need to develop software solutions and platforms that provide an integrated infrastructure to allow interoperability between these subsystems, while leveraging the abundant data available from today’s grid. In this paper, we present the development and deployment of an application service to integrate GridAPPS-D which is an open source, standards-based software platform with SurvalentONE, a commonly used DNP3 based ADMS platform that allows operation, monitoring, analysis, restoration, and optimization of network operations. We present details of the integration architecture, including its implementation, and provide results from functional testing of the architecture on a 13 bus IEEE system. The results validate that the integration is successful and is able to provide a two-way exchange of communication and translation between different communication protocols.

Singh, Alka↗

Cy-Phy ADS: Cyber Physical Anomaly Detection Framework for EV Charging Systems

Today’s large-scale Electric Vehicle (EV) infrastructures are heavily dependent on information communication technologies to maintain their operation and to support communication within sub-system components as well as the outside world. These technologies are vulnerable to various cyber and physical threats. Timely identification and mitigation of these threats are critical for improving human safety, avoiding economic losses, and preventing catastrophic system failures. By addressing this, our work presents a ResNet Autoencoder (AE) based Cyber-Physical Anomaly Detection System (Cy-Phy ADS) for detecting anomalies in EV Controller Area Network (CAN) protocol communication. It consists of four main components: Cyber-Physical Feature Extractor, ResNet AE-based Anomaly Detection Framework, Cyber-Physical Health Metric (CPHM), and Visualization Dashboard. The presented framework was trained and tested using CAN data collected from the EV charging system testbed at the Idaho National Laboratory. The presented Cy-Phy ADS compared against six widely used unsupervised anomaly detection algorithms: One Class Support Vector Machine (OCSVM), Variational Autoencoder (VAE), LSTM Autoencoder (LSTM AE), Isolation Forest (IForest), Principle Component Analysis (PCA) and Local Outlier Factor (LOF). Here the presented approach showed the highest accuracy among the compared methods. Further, the proposed approach showed comparable performance in terms of precision, F1, and False positive rate. It also showed the lowest training and inference time compared to the neural network-based baseline algorithms compared against with. Additionally, the Cy-Phy ADS has advantages such as unsupervised training, the ability to provide a holistic metric for system health characterization, and non-linear feature extraction.

99 GENERAL AND MISCELLANEOUS↗

Influences of North Pacific Ocean Domain Extent on the Western U.S. Winter Hydroclimatology in Variable-Resolution CESM

Variable-resolution global climate models (VRGCMs) are a dynamical downscaling method that can reach spatiotemporal scales needed for regional climate assessments. Over the years, several users of VRGCMs have assumed where the location and extent of the refinement domain should be based on knowledge of the prevailing storm tracks and resolution dependence of important regional climate processes (e.g., atmospheric rivers [ARs] and orographic uplift), but the effect of high-resolution domain size and extent on the simulation of downstream hydroclimatic phenomena has not been systematically evaluated. Here, we use variable resolution in the Community Earth System Model (VR-CESM) to perform such a test. To do this, three VR-CESM grids were generated that span the entire, two thirds, and one third of the North Pacific and evaluated for a 30-year climatology using Atmospheric Model Intercomparison Project protocols. Simulations are compared with reanalysis products offshore (fifth-generation of the European Centre for Medium-Range Weather Forecasts atmospheric reanalysis [ERA5]) and onshore (Livneh, 2015, https://doi.org/10.1038/sdata.2015.42, and Parameter-elevation Regressions on Independent Slopes Model [PRISM]) of the western United States. The westward expansion of refinement domain influenced integrated vapor transport (IVT), which was generally high biased but minimally impacted AR characteristics. Due to slight differences in landfalling AR counts in the western United States, California winter precipitation generally improved with westward expansion of the refinement domain. Western U.S. mountain snowpack and surface temperatures were insensitive to refinement domain size and were more influenced by changes in topographic resolution and/or land surface model version. Here, given minimal dependence of simulated western U.S. hydroclimate on refinement domain size over the North Pacific, we advise future VR-CESM studies to focus grid resolution on better resolving land surface heterogeneity.

54 ENVIRONMENTAL SCIENCES↗

A scalable method of applying heat and humidity for decontamination of N95 respirators during the COVID-19 crisis

A lack of N95 Filtering Facepiece Respirators (FFRs) during the COVID-19 crisis has placed healthcare workers at risk. It is important for any N95 reuse strategy to determine the effects that proposed protocols would have on the physical functioning of the mask, as well as the practical aspects of implementation. Here we propose and implement a method of heating N95 respirators with moisture (85°C, 60-85% humidity). We test both mask filtration efficiency and fit to validate this process. Our tests focus on the 3M 1860, 3M 1870, and 3M 8210 Plus N95 models. After five cycles of the heating procedure, all three respirators pass both quantitative fit testing (score of >100) and show no degradation of mask filtration efficiency. We also test the Chen Heng V9501 KN95 and HKYQ N95 finding no degradation of mask filtration efficiency, however even for unheated masks these scored <50 for every fit test. The heating method presented here is scalable from individual masks to over a thousand a day with a single industrial convection oven, making this method practical for local application inside health-care facilities.

59 BASIC BIOLOGICAL SCIENCES↗

SuperLab 2.0 Showcase: Connecting Five Labs to Tackle Grid Complexity and Unlock Unique Grid Asset Potential

SuperLab 2.0 (5-Lab Demo) is a collaborative, national-scale experiment showcasing the coordination of geographically distributed energy assets in real time. The demonstration integrates 25 physical and digital assets, spanning wind, PV, batteries, electrolyzers, DC fast chargers, microgrid controllers, building automation systems, small modular reactor (SMR), control centers, and gas turbines, across five DOE national laboratories-NLR, INL, NETL, LBNL, and SNL. These assets are unified using Energy Sciences Network (ESnet), a low-latency, high-performance U.S. Department of Energy's (DOE) network, and controlled via a centralized energy controller hosted at NLR's ARIES facility. The demonstration validates the ability to stress-test hybrid energy systems under dynamic scenarios to de-risk advanced control strategies for greater resilience and flexibility. SuperLab 2.0 (5-Lab Demo) showcased a major advancement in federated national laboratory collaboration, enabling real-time, cross-laboratory experimentation to coordinate geographically dispersed distributed energy resources (DERs) using various communication protocols and networks. SuperLab 2.0 (5-Lab Demo) built on previous demonstrations conducted between NLR-PNNL and NLR-INL connecting diverse assets including distant protection devices, a SMR simulator, and a high temperature electrolyzer (HTE). Previous demos were based on a single connection between two labs with minimal coordination challenges. The 5-Lab demo with a centralized controller, distributed testbeds across different geographical locations, and use of protocols-based communication represents a scenario closer to real-world grid operations that coordinate resources across a region to meet system needs. This experiment studied how local DER controllers interact with a centralized energy controller during normal and abnormal events to maintain reliability. The SuperLab team across the five labs implemented a notional power system model equivalent of transmission and distribution lines, represented by the data networks interconnecting the labs. Each lab continuously exchanged local parameters (such as P and Q) from its Hardware-In-Loop (CHIL) and Power Hardware-In-Loop (PHIL) assets through centralized energy controller at NLR, enabling real-time interaction and coordination across sites. By leveraging ESnet as the communication backbone, the team successfully operated the distributed assets as a unified power system, with each bus represented by a different laboratory. This setup mirrors how assets interact in real-world power systems across dispersed locations with various protocols and latencies. At each lab site, assets were operated using their own local controllers which were coordinated through an overarching operation and control layer of centralized energy controller, equivalent to how an energy management system (EMS) orchestrates assets across a regional or national grid. SuperLab's federated connectivity utilized a Digital Real-Time Simulators (DRTS)-type gateway to connect Controller Hardware-In-Loop (CHIL) and PHIL assets between labs. To enable this federated connection through ESnet, a deterministic network was established where latency variations were consistent. This consistency allowed the development of digital filters for the power system assets across CHIL and PHIL interfaces to avoid unstable and unreliable grid conditions. This report provides an overview of the cross-laboratory configuration and offers insights into interconnecting geographically distributed research assets to test them as if they were co-located. This experiment represents a step toward linking nine DOE national laboratories, enabling nation-wide simulations that can address utility-driven challenges with grid resilience, flexibility, and modernization.

24 POWER TRANSMISSION AND DISTRIBUTION↗

An Accelerated Testing and Analysis Framework for Qualification of Battery Materials

The continuously growing demand for batteries used within automotive, aviation, and grid applications has exacerbated the need to supplement critical battery material feedstocks, such as those for anode and cathode active materials. New or supplementary material sources, however, universally comprise unique material properties that can significantly affect the lifetime and performance of resultant batteries. As such, the influence of composition, microstructure, and morphology on electrochemical performance should be characterized quickly and accurately to accelerate commercialization of new material sources. This work introduces a tiered framework to quickly assess new material viability and understand the influence of physicochemical properties on battery performance. The Tier 1 testing described here is rapid and lower-effort to quickly recognize materials with fundamental flaws and potentially disqualify them. Later testing would require more time and effort but provide higher fidelity information with a goal of validating materials for specific applications. A case study examining various commercial sources of LiFePO4 (LFP) is presented, using Tier 1 of the protocol to identify rapid electrochemical and physicochemical signals that correlate with performance and to provide early go/no-go decisions on LFP materials without the need for long-term cycling data.

25 - ENERGY STORAGE↗