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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Radio frequency sensing and its innovative applications in diverse sectors: A comprehensive study

Recent advancements in radio frequency (RF) sensing technology can be attributed to the development of the Internet of Things (IoT), healthcare, RF-identification, and communication applications. RF sensing is a multidisciplinary research field that requires expertise in computing, electronics, and electromagnetics to cover all system features, including protocol development, antenna design, sensor integration, algorithm formulation, interconnection, data, and analytics. The overarching aim of this work is to present detailed information about RF technologies and their innovations and application diversity from the novel work carried out at CSI Lab1, together in one platform with an extensive survey. This study presents state-of-the art applications and RF sensing that include W-Fi, radar, and SDR and RFID-based sensing. A comprehensive survey and study of the advantages and limitations of each non-contact technology is discussed. Additionally, open research gaps have been identified as well. Decades of knowledge and experience have been put to use to meet new challenges and demands. The development and study of RF systems, IoT, RFID sensing, and research and deployment activities, are briefly discussed. The emerging research projects with industry, institutional research centers, and academic studies are also addressed. Finally, an outline of identified potential future research areas is provided, emphasizing opportunities and challenges.

47 OTHER INSTRUMENTATION↗
DOE OSTI2016

Nanoconfinement Inside Molecular Metal Oxide Clusters: Dynamics and Modified Encapsulation Behavior

Abstract Encapsulation behavior, as well as the presence of internal catalytically active sites, has been spurring the applications of a 3 nm hollow spherical metal oxide cluster {Mo 132 } as an encapsulation host and a nanoreactor. Due to its well‐defined and tunable cluster structures, and nanoscaled internal void space comparable to the volumes of small molecules, this cluster provides a good model to study the dynamics of materials under nanoconfinement. Neutron scattering studies suggest that bulky internal ligands inside the cluster show slower and limited dynamics compared to their counterparts in the bulk state, revealing the rigid nature of the skeleton of the internal ligands. NMR studies indicate that the rigid internal ligands that partially cover the interfacial pore on the molybdenum oxide shells are able to block some large guest molecules from going inside the capsule cluster, which provides a convincing protocol for size‐selective encapsulation and separation.

Wang, Zhe↗
DOE OSTI2019

An Effective Protocol for Proteome Analysis of Medaka (Oryzias latipes) after Acute Exposure to Ionizing Radiation

All terrestrial organisms are subject to evolutionary pressures associated with natural sources of ionizing radiation (IR). The legacy of human-induced IR associated with energy, weapons production, medicine, and research has changed the distribution and magnitude of these evolutionary pressures. To date, no study has systematically examined the effects of environmentally relevant doses of radiation exposure across an organismal proteome. This void in knowledge has been due, in part, to technological deficiencies that have hampered quantifiable environmentally relevant IR doses and sensitive detection of proteomic responses. Here, we describe a protocol that addresses both needs, combining quantifiable IR delivery with a reliable method to yield proteomic comparisons of control and irradiated Medaka fish. Exposures were conducted at the Savannah River Ecology Laboratory (SREL, in Aiken, SC), where fish were subsequently dissected into three tissue sets (carcasses, organs and intestines) and frozen until analysis. Tissue proteins were extracted, resolved by Sodium Dodecyl Sulfate-Polyacrylamide Gel Electrophoresis (SDS-PAGE), and each sample lane was divided into ten equal portions. Following in-gel tryptic digestion, peptides released from each gel portion were identified and quantified by Liquid Chromatography-Mass Spectrometry (LC-MS/MS) to obtain the most complete, comparative study to date of proteomic responses to environmentally relevant doses of IR. This method provides a simple approach for use in ongoing epidemiologic studies of chronic exposure to environmentally relevant levels of IR and should also serve well in physiological, developmental, and toxicological studies.

Pérez-Gélvez, Yeni (ORCID:0000000218120049)↗
DOE OSTI2018

Blood lead levels and hypothalamic-pituitary-adrenal function in middle-aged individuals

Highlights: • We assessed cortisol secretions (CS) in adults aged 50–67 years. • We reported changes in CS in relation to blood lead levels. • At low-levels, lead does not impact the global trend of salivary CS. Experimental and epidemiological studies suggested that exposure to lead (Pb) may influence the hypothalamic-pituitary-adrenal (HPA) axis. However, previous studies have yielded mixed results. We evaluated changes in basal salivary cortisol levels and acute cortisol responsivity to psychological stress in relation with blood Pb levels (BPb), in Caucasian individuals 50–67 years of age. Data were collected through the Study of Genetics, Stress and Cognitive Development (2004–2006). Diurnal basal and stress-reactive salivary cortisol levels were collected and BPb levels were determined using inductively coupled plasma mass spectroscopy. A total of 65 participants were included in the current study. General linear mixed models were used to assess the association between BPb level and change in cortisol secretion over time, for diurnal basal pattern and stress-reactive pattern, respectively. The geometric mean BPb was 2.70 μg/dL (± 1.44) and two exposure groups were created based on the median value of 2.48 µg/dL. No difference in geometric mean of salivary cortisol (µg/dL) at awakening was observed between High and Low BPb groups (0.23 (± 0.11) vs 0.20 (± 0.11), p = 0.36). The overall pattern of change in both diurnal basal (from the awakening to bedtime) and reactive salivary cortisol (during the stress induction protocol) did not differ between groups. In these middle-aged and older adults, we concluded that Pb exposure, within the range observed in the current study, was associated with neither diurnal nor stress-reactive cortisol secretion. Further investigation with larger datasets are needed to confirm our observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

iVirus 2.0: Cyberinfrastructure-supported tools and data to power DNA virus ecology

Microbes drive myriad ecosystem processes, but under strong influence from viruses. Because studying viruses in complex systems requires different tools than those for microbes, they remain underexplored. To combat this, we previously aggregated double-stranded DNA (dsDNA) virus analysis capabilities and resources into ‘iVirus’ on the CyVerse collaborative cyberinfrastructure. Here we substantially expand iVirus’s functionality and accessibility, to iVirus 2.0, as follows. First, core iVirus apps were integrated into the Department of Energy’s Systems Biology KnowledgeBase (KBase) to provide an additional analytical platform. Second, at CyVerse, 20 software tools (apps) were upgraded or added as new tools and capabilities. Third, nearly 20-fold more sequence reads were aggregated to capture new data and environments. Finally, documentation, as “live” protocols, was updated to maximize user interaction with and contribution to infrastructure development. Together, iVirus 2.0 serves as a uniquely central and accessible analytical platform for studying how viruses, particularly dsDNA viruses, impact diverse microbial ecosystems.

Bolduc, Benjamin (ORCID:0000000324200755)↗
DOE OSTI2026

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↗
DOE OSTI2023

Permethylation as a strategy for high–molecular–weight polysaccharide structure analysis by nuclear magnetic resonance—Case study of Xylella fastidiosa extracellular polysaccharide

Current practices for structural analysis of extremely large-molecular-weight polysaccharides via solution-state nuclear magnetic resonance (NMR) spectroscopy incorporate partial depolymerization protocols that enable polysaccharide solubilization in suitable solvents. Non-specific depolymerization techniques utilized for glycosidic bond cleavage, such as chemical degradation or ultrasonication, potentially generate structural fragments that can complicate complete and accurate characterization of polysaccharide structures. Utilization of appropriate enzymes for polysaccharide degradation, on the other hand, requires prior structural knowledge and optimal enzyme activity conditions that are not available to an analyst working with novel or unknown compounds. Herein, we describe an application of a permethylation strategy that allows the complete dissolution of intact polysaccharides for NMR structural characterization. This approach is utilized for NMR analysis of Xylella fastidiosa extracellular polysaccharide (EPS), which is essential for the virulence of the plant pathogen that affects multiple commercial crops and is responsible for multibillion dollar losses each year.

13C↗
DOE OSTI2017

An exactly solvable quench protocol for integrable spin models

Quantum quenches in continuum field theory across critical points are known to display different scaling behaviours in different regimes of the quench rate. We extend these results to integrable lattice models such as the transverse field Ising model on a one-dimensional chain and the Kitaev model on a two-dimensional honeycomb lattice using a nonlinear quench protocol which allows for exact analytical solutions of the dynamics. Our quench protocol starts with a finite mass gap at early times and crosses a critical point or a critical region, and we study the behaviour of one point functions of the quenched operator at the critical point or in the critical region as a function of the quench rate. For quench rates slow compared to the initial mass gap, we find the expected Kibble-Zurek scaling. In contrast, for rates fast compared to the mass gap, but slow compared to the inverse lattice spacing, we find scaling behaviour similar to smooth fast continuum quenches. For quench rates of the same order of the lattice scale, the one point function saturates as a function of the rate, approaching the results of an abrupt quench. The presence of an extended critical surface in the Kitaev model leads to a variety of scaling exponents depending on the starting point and on the time where the operator is measured. We discuss the role of the amplitude of the quench in determining the extent of the slow (Kibble-Zurek) and fast quench regimes, and the onset of the saturation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2011

RXIO: Design and implementation of high performance RDMA-capable GridFTP

For its low-latency, high bandwidth, and low CPU utilization, Remote Direct Memory Access (RDMA) has established itself as an effective data movement technology in many networking environments. However, the transport protocols of grid run-time systems, such as GridFTP in Globus, are not yet capable of utilizing RDMA. In this study, we examine the architecture of GridFTP for the feasibility of enabling RDMA. An RDMA-capable XIO (RXIO) framework is designed and implemented to extend its XIO system and match the characteristics of RDMA. Our experimental results demonstrate that RDMA can significantly improve the performance of GridFTP, reducing the latency by 32% and increasing the bandwidth by more than three times. In achieving such performance improvements, RDMA dramatically cuts down CPU utilization of GridFTP clients and servers. In conclusion, these results demonstrate that RXIO can effectively exploit the benefits of RDMA for GridFTP. It offers a good prototype to further leverage GridFTP on wide-area RDMA networks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Using Generalized Equivalent Uniform Dose Atlases to Combine and Analyze Prospective Dosimetric and Radiation Pneumonitis Data From 2 Non-Small Cell Lung Cancer Dose Escalation Protocols

Purpose: To demonstrate the use of generalized equivalent uniform dose (gEUD) atlas for data pooling in radiation pneumonitis (RP) modeling, to determine the dependence of RP on gEUD, to study the consistency between data sets, and to verify the increased statistical power of the combination. Methods and Materials: Patients enrolled in prospective phase I/II dose escalation studies of radiation therapy of non-small cell lung cancer at Memorial Sloan-Kettering Cancer Center (MSKCC) (78 pts) and the Netherlands Cancer Institute (NKI) (86 pts) were included; 10 (13%) and 14 (17%) experienced RP requiring steroids (RPS) within 6 months after treatment. gEUD was calculated from dose-volume histograms. Atlases for each data set were created using 1-Gy steps from exact gEUDs and RPS data. The Lyman-Kutcher-Burman model was fit to the atlas and exact gEUD data. Heterogeneity and inconsistency statistics for the fitted parameters were computed. gEUD maps of the probability of RPS rate {>=}20% were plotted. Results: The 2 data sets were homogeneous and consistent. The best fit values of the volume effect parameter a were small, with upper 95% confidence limit around 1.0 in the joint data. The likelihood profiles around the best fit a values were flat in all cases, making determination of the best fit a weak. All confidence intervals (CIs) were narrower in the joint than in the individual data sets. The minimum P value for correlations of gEUD with RPS in the joint data was .002, compared with P=.01 and .05 for MSKCC and NKI data sets, respectively. gEUD maps showed that at small a, RPS risk increases with gEUD. Conclusions: The atlas can be used to combine gEUD and RPS information from different institutions and model gEUD dependence of RPS. RPS has a large volume effect with the mean dose model barely included in the 95% CI. Data pooling increased statistical power.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

Insight into SEI Growth in Li-Ion Batteries using Molecular Dynamics and Accelerated Chemical Reactions

The performance of lithium-ion batteries (LIB) using organic electrolytes strongly depends on the formation of a stable solid electrolyte interphase (SEI) film. Elucidating the dynamic evolution and spatial composition of the SEI can be very useful to study the stability of SEI components and help optimize the formation cycles of LIB. We propose a classical molecular dynamics simulation protocol for predicting the first stages of SEI formation using a reaction method involving the decomposition of EC and LiPF 6 molecules in the electrolyte. We accelerate the formation of SEI components near the anode surface by increasing the probability of reactions, implemented through a geometry matching scheme, followed by a force-field reconfiguration. We observe the formation of gases (C 2 H 4 ), inorganic (Li 2 CO 3 and LiF) and organic (LEDC) components. Finally, this protocol shows promise to be able to evaluate the effects of varying electrolyte compositions and additives on SEI layer structure and composition.

25 ENERGY STORAGE↗
DOE OSTI2018

Comprehensive High Throughput One‐Pot Analysis of Glycoproteins through Tool for Rapid Analysis of Glycopeptide by Permethylation (TRAP) Method.

Glycoproteins plays key roles in various cellular functions such as protein folding, protein targeting, receptor function, cell–cell recognition, protein stability, signaling, and other cellular functions. Currently a comprehensive and universal tool for the automated analysis of glycopeptides through their tandem mass spectrometry and data processing is a tedious process. We recently developed a method, Tool for Rapid Analysis of glycopeptide by Permethylation (TRAP), that simplifies glycoprotein analysis by integrating glycan sequencing and glycopeptide analysis in a single experiment. We employed this approach for the detailed analysis of glycosidic linkages, composition, glycan sequencing, glycosylation site mapping and sequencing of peptide moiety of glycopeptides of glycoproteins from both prokaryotes and eukaryotes. Here we are presenting an easy to use, robust, suitable for large as well as small sample sets and also cost‐effective glycoprotein analysis tool through TRAP approach. A permethylation protocol which can be automated and suitable for reliable permethylation of glycopeptides from the protease digest of glycoproteins was developed. Initial studies on glycopeptides from a model glycoprotein bovine RNAse B indicates that improved sensitivity and throughput of permethylation reactions can be achieved in conducting the reaction in microscale. This approach would enable convenient, rapid, and reliable high‐throughput screening of protein glycosylation and can be employed as a cost‐effective kit for glycosylated biomarker discoveries. In order to improvise the comprehensive glycosylation analysis and throughput, we have also developed an LC‐MS/MS platform for the analysis of glycopeptides processed through TRAP. We have conducted the analysis of standard glycoproteins such as bovine RNase B, human transferrin, and bovine fetuin and our preliminary results indicate that TRAP hyphened with LC‐MS/MS enables characterization of isomers of each glycoform at each glycosylation sites of complex glycoprotein mixtures. Support or Funding Information This research was supported by the National Institutes of Health (NIH) funded research, Grant R21GM122633; resource for biomedical glycomics, Grant P41GM103490; instrument grant, Grant S10OD018530; and U.S. Department of Energy grant, Grant DE‐SC0015662, to the Complex Carbohydrate Research Center. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Shajahan, Asif↗
DOE OSTI2017

Optimization of the crystal growth of the superconductor CaKFe 4 As 4 from solution in the FeAs - CaFe 2 As 2 - KFe 2 As 2 system

Measurements of the anisotropic properties of single crystals play a crucial role in probing the physics of new materials. Determining a growth protocol that yields suitable high-quality single crystals can be particularly challenging for multicomponent compounds. Here we present a case study of how we refined a procedure to grow single crystals of CaKFe 4 As 4 from a high temperature, quaternary liquid solution rich in iron and arsenic (“FeAs self-flux”). Temperature dependent resistance and magnetization measurements are emphasized, in addition to the x-ray diffraction, to detect intergrown CaKFe 4 As 4 , CaFe 2 As 2 , and KFe 2 As 2 within what appear to be single crystals. Guided by the rules of phase equilibria and these data, we adjusted growth parameters to suppress formation of the impurity phases. The resulting optimized procedure yielded phase-pure single crystals of CaKFe 4 As 4 . In conclusion, this optimization process offers insight into the growth of quaternary compounds and a glimpse of the four-component phase diagram in the pseudoternary FeAs–CaFe 2 As 2 –KFe 2 As 2 system.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Spectroscopic Demarcation of Emergent Photons and Spinons in a Dipolar-Octupolar Quantum Spin Liquid

The identification of fractionalized excitations in quantum spin liquids (QSLs) remains a central challenge in condensed matter physics. In dipolar-octupolar (DO) pyrochlores, such as Ce 2⁢ Zr 2 ⁢O 7 , the candidate 𝜋-flux quantum spin ice (QSI) state is predicted to host both gapless emergent photons and a continuum of spinons. However, resolving these modes at zero field is complicated by their spectral overlap and the presence of nonmagnetic scattering near zero energy. Here, in this study, we report neutron scattering experiments on Ce 2 ⁢Zr 2 ⁢O 7 under a magnetic field along the [1, 1, 1] direction. In contrast to previous unpolarized studies at zero field that relied on high-temperature subtraction, we use a same-temperature high-field subtraction protocol to isolate the photon and spinon modes. Leveraging the selective coupling of the magnetic field to the dipolar degrees of freedom, we demonstrate the spectroscopic demarcation of these excitations. We observe that weak fields (≈ 0.15 T) suppress the low-energy photon weight while leaving the high-energy spinon continuum robust, albeit hardened. Our results, supported by gauge mean-field theory and exact diagonalization calculations, provide strong evidence for the 𝜋-flux QSI state and introduce a powerful field-tuning protocol for investigating DO-QSLs.

Gao, Bin [Rice University, Houston, TX (United Sta↗
DOE OSTI2024

A Deep Learning Approach for In-Network Synchrophasor Missing Data Recovery Using Programmable Network Switches

Phasor measurement unit (PMU) networks deliver accurate and timely measurements, which is essential for managing today’s electric power systems. To ensure data quality and enhance the cyber-resilience of PMU networks against malicious attacks and data errors, this study presents an online PMU missing data recovery scheme by leveraging P4 programmable switches. The data plane incorporates a customized PMU protocol parser that abstracts the necessary payload data for recovery. Recovery processes are executed in the control plane using a pre-trained machine learning model. Both traditional and advanced ML models, such as transformer and TimeGPT, are explicitly employed for data prediction. This approach ensures rapid and precise data recovery. Performance evaluations focus on recovery speed and accuracy, using a real dataset from a campus microgrid. With 20% missing PMU data, the mean absolute percentage error for voltage magnitude is 0.0384%, and the phase angle error discrepancy is approximately 0.4064%.

Phasor Measurement Unit, Machine Learning, Program↗
DOE OSTI2017

Durability Testing of Biomass Based Oxygenated Fuel Components in a Compression Ignition Engine

Blending cellulosic biofuels with traditional petroleum-derived fuels results in transportation fuels with reduced carbon footprints. Many cellulosic fuels rely on processing methods that produce mixtures of oxygenates which must be upgraded before blending with traditional fuels. Complete oxygenate removal is energy-intensive and it is likely that such biofuel blends will necessarily contain some oxygen content to be economically viable. Previous work by our group indicated that diesel fuel blends with low levels (<4%-vol) of oxygenates resulted in minimal negative effects on short-term engine performance and emissions. However, little is known about the long-term effects of these compounds on engine durability issues such as the impact on fuel injection, in-cylinder carbon buildup, and engine oil degradation. In this study, four of the oxygenated components previously tested were blended at 4%-vol in diesel fuel and tested with a durability protocol devised for this work consisting of 200 hrs of testing in a stationary, single-cylinder, Yanmar diesel engine operating at constant load. Oil samples, injector spray patterns, and carbon buildup from the injector and cylinder surfaces were analyzed. It was found that, at the levels tested, these fuels had minimal impact on the overall engine operation, which is consistent with our previous findings.

09 BIOMASS FUELS↗
DOE OSTI2015

Reduced dose measurement of absolute myocardial blood flow using dynamic SPECT imaging in a porcine model

Purpose: Absolute myocardial blood flow (MBF) and myocardial flow reserve (MFR) measurements provide important additional information over traditional relative perfusion imaging. Recent advances in camera technology have made this possible with single-photon emission tomography (SPECT). Low dose protocols are desirable to reduce the patient radiation risk; however, increased noise may reduce the accuracy of MBF measurements. The authors studied the effect of reducing dose on the accuracy of dynamic SPECT MBF measurements. Methods: Nineteen 30–40 kg pigs were injected with 370 + 1110 MBq of Tc-99m sestamibi or tetrofosmin or 37 + 111 MBq of Tl-201 at rest + stress. Microspheres were injected simultaneously to measure MBF. The pigs were imaged in list-mode for 11 min starting at the time of injection using a Discovery NM 530c camera (GE Healthcare). Each list file was modified so that 3/4, 1/2, 1/4, 1/8, 1/16, and 1/32 of the original counts were included in the projections. Modified projections were reconstructed with CT-based attenuation correction and an energy window-based scatter correction and analyzed with FlowQuant kinetic modeling software using a 1-compartment model. A modified Renkin-Crone extraction function was used to convert the tracer uptake rate K1 to MBF values. The SPECT results were compared to those from microspheres. Results: Correlation between SPECT and microsphere MBF values for the full injected activity was r ≥ 0.75 for all 3 tracers and did not significantly degrade over all count levels. The mean MBF and MFR and the standard errors in the estimates were not significantly worse than the full-count data at 1/4-counts (Tc99m-tracers) and 1/2-counts (Tl-201). Conclusions: Dynamic SPECT measurement of MBF and MFR in pigs can be performed with 1/4 (Tc99m-tracers) or 1/2 (Tl-201) of the standard injected activity without significantly reducing accuracy and precision.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Parameter Estimation for Electrode Degradation: Learning in the Face of Model-Experiment Discrepancies

Use of physics-based models to interpret battery degradation data over the course of cycling can provide deeper physical insight into the internal states of the system and how they evolve. We present a neural network trained on simulations generated by a previously published physics-based model for a lithium trivanadate (LVO) cathode to estimate parameters that evolve over the course of cycling. We focus on the robustness of the neural network through two case studies that probe different kinds of discrepancies between model and experiment: nonideal data and imperfect model. In the former, the experimental protocols do not meet the assumption made in the training data generated by the physics-based model, while in the latter, the physics-based model fails to describe all of the measured cathode behavior even under ideal conditions. When there is total model-experiment agreement, a neural network estimates parameters with improved accuracy compared to a maximum likelihood analysis using the same set of simulations. However, in both types of model-experiment discrepancy, the neural network returned biased parameter estimates. We introduce a data augmentation procedure into the neural network training to mitigate these effects and improve robustness, and employ it to estimate parameters for a cycling LVO cathode.

Mayilvahanan, Karthik S. (ORCID:0000000316282332)↗