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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 1,045 records · Page 58

Nonintrusive thermal-wave sensor for operando quantification of degradation in commercial batteries

Abstract Monitoring real-world battery degradation is crucial for the widespread application of batteries in different scenarios. However, acquiring quantitative degradation information in operating commercial cells is challenging due to the complex, embedded, and/or qualitative nature of most existing sensing techniques. This process is essentially limited by the type of signals used for detection. Here, we report the use of effective battery thermal conductivity ( k eff ) as a quantitative indicator of battery degradation by leveraging the strong dependence of k eff on battery-structure changes. A measurement scheme based on attachable thermal-wave sensors is developed for non-embedded detection and quantitative assessment. A proof-of-concept study of battery degradation during fast charging demonstrates that the amount of lithium plating and electrolyte consumption associated with the side reactions on the graphite anode and deposited lithium can be quantitatively distinguished using our method. Therefore, this work opens the door to the quantitative evaluation of battery degradation using simple non-embedded thermal-wave sensors.

25 ENERGY STORAGE↗

Dynamic control and quantification of active sites on ceria for CO activation and hydrogenation

Ceria (CeO 2 ) is a widely used oxide catalyst, yet the nature of its active sites remains elusive. This study combines model and powder catalyst studies to elucidate the structure-activity relationships in ceria-catalyzed CO activation and hydrogenation. Well-defined ceria clusters are synthesized on planar CeO 2 (111) and exhibit dynamic and tunable ranges of Ce coordination numbers, which enhance their interaction with CO. Reduced ceria clusters (e.g., Ce 3 O 3 ) bind CO strongly and facilitate its dissociation, while near-stoichiometric clusters (e.g., Ce 3 O 7 ) adsorb CO weakly and promote oxidation via carbonate formation. Unlike planar ceria surfaces, supported ceria clusters exhibit dynamic properties and enhanced catalytic activity, that mimic those of powder ceria catalysts. Insight from model studies provide a method to quantify active sites on powder ceria and guide further optimization of ceria catalysts for syngas conversion. This work marks a leap toward model-guided catalyst design and highlights the importance of site-specific catalysis.

03 NATURAL GAS↗

Uncertainty quantification for misspecified machine learned interatomic potentials

The use of high-dimensional regression techniques from machine learning has significantly improved the quantitative accuracy of interatomic potentials. Atomic simulations can now plausibly target quantitative predictions in a variety of settings, which has brought renewed interest in robust means to quantify uncertainties. In many practical settings where model complexity is constrained (e.g., due to performance considerations), misspecification — the inability of any one choice of model parameters to exactly match all training data — is a key contributor to errors that is often disregarded. Here, we employ a recent misspecification-aware regression technique to quantify parameter uncertainties, which is then propagated to a broad range of phase and defect properties in tungsten. The propagation is performed through both brute-force resampling and implicit Taylor expansion. The propagated misspecification uncertainties robustly quantify and bound errors on a broad range of material properties. We demonstrate application to recent foundational machine learning interatomic potentials, accurately predicting and bounding errors in MACE-MPA-0 energy predictions across the diverse materials project database.

36 MATERIALS SCIENCE↗

High-throughput Li plating quantification for fast-charging battery design

Fast charging of most commercial lithium-ion batteries is limited due to fear of lithium plating on the graphite anode, which is difficult to detect and poses considerable safety risk. In this report we demonstrate the power of simple, accessible and high-throughput cycling techniques to quantify irreversible Li plating spanning data from over 200 cells. We first observe the effects of energy density, charge rate, temperature and state of charge on lithium plating, use the results to refine a mature physics-based electrochemical model and provide an interpretable empirical equation for predicting the plating onset state of charge. We then explore the reversibility of lithium plating and its connection to electrolyte design for preventing irreversible Li accumulation. Finally, we design a method to quantify in situ Li plating for commercially relevant graphite|LiNi 0.5 Mn 0.3 Co 0.2 O 2 (NMC) cells and compare with results from the experimentally convenient Li|graphite configuration. The hypotheses and abundant data herein were generated primarily with equipment universal to the battery researcher, encouraging further development of innovative testing methods and data processing that enable rapid battery engineering.

25 ENERGY STORAGE↗

In situ quantification of interphasial chemistry in Li-ion battery

The solid-electrolyte-interphase (SEI) is probably the least understood component in Li-ion batteries. Considerable effort has been put in the understanding of its formation and electrochemistry under realistic battery conditions, but mechanistic insights have been inferred mostly indirectly. Here we show the formation of the SEI between a graphite anode and a carbonate electrolyte using combined atomic scale microscopy and in-situ and operando techniques. In particular, we weigh the graphitic anode during its initial lithiation process with electrochemical quartz crystal microbalance, which unequivocally identifies lithium fluoride (LiF) and lithium alkylcarbonates as the main chemical components at different potentials. In-situ gas analysis confirmed the preferential reduction of cyclic over acyclic carbonate molecules, making its reduction product the major component in SEI. We find that SEI formation starts at graphite edge-sites with dimerization of solvated Li + -intercalation between graphite-layers. As a result, we also show that this lithium salt, at least in its nascent form, is re-oxidizable, despite the general belief that an SEI is electrochemically inert and its formation irreversible.

25 ENERGY STORAGE↗

Single-cell quantification of ribosome occupancy in early mouse development

Translation regulation is critical for early mammalian embryonic development. However, previous studies had been restricted to bulk measurements, precluding precise determination of translation regulation including allele-specific analyses. Here, to address this challenge, we developed a novel microfluidic isotachophoresis (ITP) approach, named RIBOsome profiling via ITP (Ribo-ITP), and characterized translation in single oocytes and embryos during early mouse development. We identified differential translation efficiency as a key mechanism regulating genes involved in centrosome organization and N 6 -methyladenosine modification of RNAs. Our high-coverage measurements enabled, to our knowledge, the first analysis of allele-specific ribosome engagement in early development. These led to the discovery of stage-specific differential engagement of zygotic RNAs with ribosomes and reduced translation efficiency of transcripts exhibiting allele-biased expression. By integrating our measurements with proteomics data, we discovered that ribosome occupancy in germinal vesicle-stage oocytes is the predominant determinant of protein abundance in the zygote. The Ribo-ITP approach will enable numerous applications by providing high-coverage and high-resolution ribosome occupancy measurements from ultra-low input samples including single cells.

59 BASIC BIOLOGICAL SCIENCES↗

Uncertainty Quantification of Extratropical Forest Biomass in CMIP5 Models over the Northern Hemisphere

Abstract Simplified representations of processes influencing forest biomass in Earth system models (ESMs) contribute to large uncertainty in projections. We evaluate forest biomass from eight ESMs outputs archived in the Coupled Model Intercomparison Project Phase 5 (CMIP5) using the biomass data synthesized from radar remote sensing and ground-based observations across northern extratropical latitudes. ESMs exhibit large biases in the forest distribution, forest fraction, and mass of carbon pools that contribute to uncertainty in forest total biomass (biases range from −20 Pg C to 135 Pg C). Forest total biomass is primarily positively correlated with precipitation variations, with surface temperature becoming equally important at higher latitudes, in both simulations and observations. Relatively small differences in forest biomass between the pre-industrial period and the contemporary period indicate uncertainties in forest biomass were introduced in the pre-industrial model equilibration (spin-up), suggesting parametric or structural model differences are a larger source of uncertainty than differences in transient responses. Our findings emphasize the importance of improved (1) models of carbon allocation to biomass compartments, (2) distribution of vegetation types in models, and (3) reproduction of pre-industrial vegetation conditions, in order to reduce the uncertainty in forest biomass simulated by ESMs.

54 ENVIRONMENTAL SCIENCES↗

Quantification of Dissolved O 2 in Bulk Aqueous Solutions and Porous Media Using NMR Relaxometry

Effects of dissolved paramagnetic oxygen (O 2 ) in water on 1 H nuclear magnetic resonance (NMR) Carr-Purcell-Meiboom-Gill (CPMG) experiments is evaluated at a 1 H Larmor frequency of 2 MHz. Dissolution of O 2 into water significantly reduces the 1 H transverse relaxation coefficient (T 2 ). For deoxygenated water, T 2 is 3388 ms, water at ambient atmospheric conditions (7.4 mg/L O2) exhibits a T2 of 2465 ms, and dissolution of 2710 mg/L O 2 further reduces T 2 to 36 ms. The results were fit with an empirical model to facilitate prediction of T 2 times for bulk water as a function of paramagnetic oxygen concentrations in solution. Dissolved O 2 also greatly influences 1 H NMR CPMG experiments of confined water in a model system composed of Berea sandstone. For this system, 90 mg/L O 2 in H 2 O enhances T 2 relaxation of bulk water such that the relaxation time is comparable to physically confined water in the sandstone pores. Given the sensitivity of NMR T 2 coefficients to paramagnetic oxygen, low-field NMR-based characterization of fluid and porous media structure requires control of dissolved oxygen, as geospatial variation in the partial pressure of O 2 alone is expected to perturb fluid and pore relaxation times by up to 60 and 36%, respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Detection and quantification of γ-H2AX using a dissociation enhanced lanthanide fluorescence immunoassay

Phosphorylation of the histone protein H2AX to form γ-H2AX foci directly represents DNA double-strand break formation. Traditional γ-H2AX detection involves counting individual foci within individual nuclei. The novelty of this work is the application of a time-resolved fluorescence assay using dissociation-enhanced lanthanide fluorescence immunoassay for quantitative measurements of γ-H2AX. For comparison, standard fluorescence detection was employed and analyzed either by bulk fluorescent measurements or by direct foci counting using BioTek Spot Count algorithm and Gen 5 software. Etoposide induced DNA damage in A549 carcinoma cells was compared across all test platforms. Time resolved fluorescence detection of europium as a chelated complex enabled quantitative measurement of γ-H2AX foci with nanomolar resolution. Comparative bulk fluorescent signals achieved only micromolar sensitivity. Lanthanide based immunodetection of γ-H2AX offers superior detection and a user-friendly workflow. These approaches have the potential to improve screening of compounds that either enhance DNA damage or protect against its deleterious effects.

59 BASIC BIOLOGICAL SCIENCES↗

Uncertainty quantification for Bayesian active learning in rupture life prediction of ferritic steels

Abstract Three probabilistic methodologies are developed for predicting the long-term creep rupture life of 9–12 wt%Cr ferritic-martensitic steels using their chemical and processing parameters. The framework developed in this research strives to simultaneously make efficient inference along with associated risk, i.e., the uncertainty of estimation. The study highlights the limitations of applying probabilistic machine learning to model creep life and provides suggestions as to how this might be alleviated to make an efficient and accurate model with the evaluation of epistemic uncertainty of each prediction. Based on extensive experimentation, Gaussian Process Regression yielded more accurate inference ( $$Pearson\;correlation\;coefficent> 0.95$$ P e a r s o n c o r r e l a t i o n c o e f f i c e n t > 0.95 for the holdout test set) in addition to meaningful uncertainty estimate (i.e., coverage ranges from 94 to 98% for the test set) as compared to quantile regression and natural gradient boosting algorithm. Furthermore, the possibility of an active learning framework to iteratively explore the material space intelligently was demonstrated by simulating the experimental data collection process. This framework can be subsequently deployed to improve model performance or to explore new alloy domains with minimal experimental effort.

20 FOSSIL-FUELED POWER PLANTS↗

Theoretical and experimental quantification of Suzuki segregation enthalpy and strengthening mechanisms in a binary alloy

Solute segregation to planar defects in metallic alloys has been shown to drastically alter mechanical properties. While various works using first-principles and thermodynamic calculations have studied the fundamental driving forces for solute segregation via the Suzuki criterion, planar defect energy, or a comparison of energies of the HCP-like phase and FCC matrix, a quantitative experimental and computational comparison of equilibrium composition and segregation enthalpies has not yet been reported. In this work, we predict the equilibrium composition and segregation enthalpy to intrinsic stacking faults in a Ni-60Co (at.%) alloy and compare the results to two independent experimental methods. We observed that Co segregates to the innermost two planes of the intrinsic stacking fault, and we found that the experimental segregation enrichment, measured from transmission electron microscopy energy dispersive X-ray spectroscopy, of the faults is 6.8 at.% Co, which is 2.2 at.% less than the predicted value at the same temperature. We also find that the segregation enthalpy measured from the composition profile is −21.1 ± 6.4 meV/atom and separately from differential scanning calorimetry segregation enthalpy is −33.2 meV/atom, whereas the predicted enthalpy is −31 ± 1 meV/atom. Based on these results, we determine that segregation occurs very rapidly, within 8 min at temperatures as low as 36% of the homologous solidus temperature. Furthermore, this analysis provides an overview of the possible dislocation mechanisms responsible for strengthening effects due to solute segregation, and concludes that changes in room temperature hardness from local phase transformation is likely tied to post-segregation room temperature equilibrium partial separation distance.

Ab initio calculation↗

Real-time Crystal Growth Visualization and Quantification by Energy-Resolved Neutron Imaging

Energy-resolved neutron imaging is investigated as a real-time diagnostic tool for visualization and in-situ measurements of "blind" processes. This technique is demonstrated for the Bridgman-type crystal growth enabling remote and direct measurements of growth parameters crucial for process optimization. The location and shape of the interface between liquid and solid phases are monitored in real-time, concurrently with the measurement of elemental distribution within the growth volume and with the identification of structural features with a ~100 μm spatial resolution. Such diagnostics can substantially reduce the development time between exploratory small scale growth of new materials and their subsequent commercial production. This technique is widely applicable and is not limited to crystal growth processes.

36 MATERIALS SCIENCE↗

Quasi-operando quantification of Cu(ii) ions in Cu-SSZ-13 catalyst by an NH 3 temperature-programmed reduction method

In this work, a quasi-operando NH3 temperature-programmed reduction method (NH 3 -TPR), with N 2 :Cu = 1:1, is developed to quantify total Cu(II) ions in Cu-SSZ-13 quenched from SCR-relevant reactions, and its accuracy is confirmed by in situ EPR. [Cu(OH)] + -Z and Cu 2+ -2Z can be further distinguished by NH 3 reduction temperatures, and their different reducibility in SCR is revealed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗