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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The right conditions for high-precision dynamic temperature and heat capacity measurement via pyrometry and conductivity

The pursuit of accurate bulk temperature T under extreme conditions has been a long-standing goal of the high pressure science community, complicated by a lack of data to inform models. To reach these extremely high-pressure, high-temperature (high P − T) conditions, a combination of dynamic and heated static experiments (e.g., diamond or gem anvil cel experiments) are used. For example, in a diamond anvil cell (DAC) experiment, a sample placed in the DAC is first pressurized. Following pressurization, the sample T is increased either by heating the entire DAC (usually using resistive heating, and limited to ∼1000K) or by applying intense laser power to the sample surfaces. In a dynamic experiment, the process of pressurizing the sample also heats it. In the case of shock physics experiments, such heating is substantial, easily reaching thousands of Kelvin; in our work we have seen T ∼17000K. Most methods of measuring temperature at ambient are not compatible with experiments under these high-pressure, high-temperature conditions: thermocouples break, melt, or have conductivity properties that differ from ambient where they are calibrated; thermometers would melt; both are too slow. As a result most methods are based on non-contact techniques such as x-ray diffraction broadening, neutron scattering, or optical methods. Of these, optical methods using the visible and near-infrared region of the spectrum are the most commonly used as the sources and detectors are readily available. In the case of optical methods the optical depth, and therefore the measurement location, is limited to the surface. When a window or anvil material is used, heat flows from the sample into the window/anvil. Likewise, if the sample undergoes a change in thermodynamic state, such as expansion upon release, different T may be expected. As a result, the surface or apparent temperature T app measurement will differ from the bulk or interior temperature that is desired. This surface measurement must be related to the bulk measurement using thermal transport models and material models. While it is tempting to conclude that one should just use x-ray methods that directly probe the interior, even these methods have been shown to depend on thermal transport and material models. Regardless of the method used to create the high P − T condition, therefore, we must understand the role of thermal transport and material models upon our interpretation of the T measurement, as well as the errors and uncertainties associated with the choice of models used in the analysis. This is a substantial area of research and this paper is by no means a complete survey of the relevant sources of uncertainty. For example, we have yet to begin to address alternate transport models in a detailed manner (e.g., Tan-Ahrens), or the many models that use additional layers to approximate melting, turbulence, or epitaxial phenomena). Likewise, we have not explored the impact upon uncertainty of thermal models that use temperature-dependent thermal transport coefficients, or the wide range of material models that can be applied. Instead, this paper focuses on using one simple model, the Urtiew-Grover model, to understand the sources of error in T measurement so that we may identify how best to focus future research efforts to return the best improvements and avoid working on over-optimizing a single type of measurement. To this end, we work through some of the best and worst case scenarios for T measurement.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

A laser powder bed fusion system for operando synchrotron x-ray imaging and correlative diagnostic experiments at the Stanford Synchrotron Radiation Lightsource

Laser powder bed fusion (LPBF) is a highly dynamic multi-physics process used for the additive manufacturing (AM) of metal components. Improving process understanding and validating predictive computational models require high-fidelity diagnostics capable of capturing data in challenging environments. Synchrotron x-ray techniques play a vital role in the validation process as they are the only in situ diagnostic capable of imaging sub-surface melt pool dynamics and microstructure evolution during LPBF-AM. In this article, a laboratory scale system designed to mimic LPBF process conditions while operating at a synchrotron facility is described. The system is implemented with process accurate atmospheric conditions, including an air knife for active vapor plume removal. Significantly, the chamber also incorporates a diagnostic sensor suite that monitors emitted optical, acoustic, and electronic signals during laser processing with coincident x-ray imaging. The addition of the sensor suite enables validation of these industrially compatible single point sensors by detecting pore formation and spatter events and directly correlating the events with changes in the detected signal. Experiments in the Ti–6Al–4V alloy performed at the Stanford Synchrotron Radiation Lightsource using the system are detailed with sufficient sampling rates to probe melt pool dynamics. X-ray imaging captures melt pool dynamics at frame rates of 20 kHz with a 2 µm pixel resolution, and the coincident diagnostic sensor data are recorded at 470 kHz. Furthermore, this work shows that the current system enables the in situ detection of defects during the LPBF process and permits direct correlation of diagnostic signatures at the exact time of defect formation.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dynamic control of ferroionic states in ferroelectric nanoparticles

The polar states of uniaxial ferroelectric nanoparticles interacting with a surface system of electronic and ionic charges with a broad distribution of mobilities is explored, which corresponds to the experimental case of nanoparticles in solution or ambient conditions. The nonlinear interactions between the ferroelectric dipoles and surface charges with slow relaxation dynamics in an external field lead to the emergence of a broad range of paraelectric-like, antiferroelectric-like ionic, and ferroelectric-like ferroionic states. The crossover between these states can be controlled not only by the static characteristics of the surface charges, but also by their relaxation dynamics in the applied field. Obtained results are not only promising for advanced applications of ferroelectric nanoparticles in nanoelectronics and optoelectronics, they also offer strategies for experimental verification.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Imaging Field–Driven Melting of a Molecular Solid at the Atomic Scale

Solid–liquid phase transitions are basic physical processes, but atomically resolved microscopy has yet to capture their full dynamics. A new technique is developed for controlling the melting and freezing of self–assembled molecular structures on a graphene field–effect transistor (FET) that allows phase–transition behavior to be imaged using atomically resolved scanning tunneling microscopy. This is achieved by applying electric fields to 2,3,5,6–tetrafluoro–7,7,8,8–tetracyanoquinodimethane–decorated FETs to induce reversible transitions between molecular solid and liquid phases at the FET surface. Nonequilibrium melting dynamics are visualized by rapidly heating the graphene substrate with an electrical current and imaging the resulting evolution toward new 2D equilibrium states. An analytical model is developed that explains observed mixed–state phases based on spectroscopic measurement of solid and liquid molecular energy levels. The observed nonequilibrium melting dynamics are consistent with Monte Carlo simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Solution‐Like Water Transport Across Molecular to Macroscopic Length Scales in Crosslinked Poly(Ethylene Glycol Diacrylate) Networks With Tailored Sidechains

Poly(ethylene glycol) (PEG)‐based materials, like PEG‐diacrylate (PEGDA), are prized for their hydrophilic, inert properties, and leveraged in hydrogels and as membrane mimics. While network chemistry is often tuned for selective transport and antifouling, fundamental understanding of water dynamics at the network surface and the impact on bulk transport is limited. We utilize Overhauser dynamic nuclear polarization (ODNP) to measure nanoscale water diffusivity near a tethered spin label at the water‐polymer surface and compare it to bulk water diffusivity from pulsed field gradient (PFG) NMR. Via active ester chemistry, spin labels and varied sidechain chemistries are introduced, modulating network hydrophilicity. Tuning network hydration through crosslinker content and functional groups further impacts water diffusivity. Results show rapid nanoscale water transport at the polymer surface, reflecting network volumetric water content, with further modulation by sidechain functionality. These findings demonstrate PEGDA's utility as a membrane mimic and the critical impact of network chemistry on water transport.

hydrogels↗
DOE OSTI2024

Percheron Power Archimedes Screw Turbine Analysis (Abstract)

The development of the Percheron Power (Percheron) composite Archimedes screw turbine (AST) is based upon employing newly developed theoretical mathematical models for optimizing the water volume carried through the AST for a given diameter, combined with minimizing efficiency losses due to bypass flow and friction. The key feasibility issues associated with producing the composite blades will be to understand the strength, fatigue, and wear performance of the AST blades and associated components, and how these factors change along the length of the turbine. To get to this understanding of material property requirements, Percheron needs free-surface computational fluid dynamics (CFD) models of the AST designs and to perform interactive modeling between the turbine blade optimization and component design based on finite element method stress analysis (FEA). The workscope and analyses requested by Percheron in the Small Business Voucher (SBV) program are well aligned with PNNL capability and recent work experience in performing CFD and FEA analysis for hydropower and marine energy turbines. The CFD analysis will provide estimates of power, efficiency, and surface forces on the blades. The forces on the blade will be transferred to the FEA analysis that will be used to evaluate the material stresses. The CFD and FEA analyses will be repeated for different AST designs provided to PNNL by Percheron. The work conducted in this SBV project will complement the existing Percheron FOA project by providing better defined parameters for design and material selection for the turbine unit prior to manufacture of initial test units.

42 ENGINEERING↗
DOE OSTI2021

Unraveling the Intermediate Reaction Complexes and Critical Role of Support-Derived Oxygen Atoms in CO Oxidation on Single-Atom Pt/CeO 2

CeO 2 -supported Pt single-atom catalysts have been extensively studied due to their relevance in automobile emission control and for the fundamental understanding of CeO 2 -based catalysts. Though CeO 2 -supported Pt nanoparticles are often more active than their single-atom counterparts, the former could easily redisperse to Pt single atom under oxidizing diesel conditions. Therefore, to maximize the reactivity of every Pt atom, it is important to fully understand the reaction mechanism of CeO 2 -supported Pt single atoms. Here, we report a CO oxidation study on a Pt/CeO 2 single-atom catalyst, where we can account for all of the neighbors using in situ and operando spectroscopy techniques and microcalorimetric measurements. Coupled with density functional theory calculations, we present a comprehensive picture of the dynamics of the surface species, the role of surface intermediates, and explain the observed reaction kinetics. We started with a catalyst containing exclusively single atoms and used in situ/operando spectroscopy to provide evidence for their stability during the reaction and to identify the Pt 1 complexes before and during the reaction and their binding to CO. The results reveal that in the precatalyst, Pt is present as Pt(O) 4 on the CeO 2 (111) step edge sites, but during CO oxidation, we find that two Pt 1 complexes coexist, representing two states of the same active site in the reaction cycle. The dominant state/complex remains Pt(O) 4 , which adsorbs CO very weakly as shown by CO microcalorimetry. The second, minority state/complex, Pt(CO)(O) 3 is generated through the reaction of Pt(O) 4 with CO, and CO is bound strongly to Pt 1 . Labile oxygen adatoms from the CeO 2 surface play a major role in the regeneration of Pt(O) 4 either directly from Pt(O) 3 or by reaction with the strongly adsorbed CO in Pt(CO)(O) 3 . We show that the formation of an oxygen vacancy and generation of a labile O* are not barrierless, which explains the long lifetime of Pt(CO)(O) 3 and its detectability despite being a minority complex. The results help to develop a comprehensive view of the dynamic evolution of Pt 1 complexes along the reaction cycle and provide mechanistic insights to guide the design of Pt-based single-atom catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Xanthos-Lake Model Source Code

This repository contains the source code for Xanthos-Lake, a lake-modeling extension of the Xanthos framework that introduces a coupled lake component comprising the Xanthos-Lake Snow and Ice Model (xLSIM) and the Xanthos-Lake Water Balance Model (xLWBM). xLSIM is a basin-aware machine-learning model for lake snow, ice, and thermal conditions. It predicts monthly lake ice thickness, snow depth, snow-cover fraction, mixing-layer temperature, and lake ice fraction from meteorological forcing and lake surface-area information. It uses sequence-based deep-learning architectures, including Transformer and hybrid Long Short-Term Memory–Transformer (LSTM–Transformer) models, together with seasonal encoding, multi-lake learning, physical masking, and basin-level cryospheric and non-cryospheric classification. The training workflow uses Ray for scalable execution and includes optional Ray Tune hyperparameter optimization. Model predictions, observations, diagnostics, and feature-importance outputs are written in NetCDF. xLWBM is the water-balance component of the new lake framework. It simulates monthly lake storage, surface area, evaporation, inflow, outflow, and lake–groundwater exchange. It combines physical water-balance equations with calibrated bathymetric relationships, weir-based outlet flow, modified Penman open-water evaporation, groundwater head relaxation, Penman–Monteith snow and ice sublimation, and snow, ice, and thermal conditions supplied by xLSIM. The model calibrates lake parameters against satellite-derived surface-area data, using evaporation-based calibration where surface-area data are unavailable, and supports small, medium, and large lake classes. For large lakes, xLWBM is integrated with the managed-routing workflow so that lake storage and outflow interact directly with downstream river routing and reservoir operations. Together, xLSIM and xLWBM provide Xanthos with a coupled lake-modeling capability. xLSIM supplies the snow, ice, and thermal conditions that affect lake evaporation and snow- and ice-related water exchanges, while xLWBM translates those conditions into dynamic lake storage, surface area, evaporation, and discharge. In return, xLWBM supplies evolving lake surface area to xLSIM. This coupling enables Xanthos to represent lakes as active hydrologic components within basin-scale water-availability and routing simulations.

Machine Learning↗
DOE OSTI2023

Detailed studies of the processes in low energy H irradiation of Li and Li-compound surfaces

We have used a combination of pico-to-nano temporal/spatial scale computational physics and chemistry modeling of plasma–material interfaces in the tokamak fusion plasma edges to unravel the evolving characteristics, not readily accessible by empirical means, of lithium-, oxygen-, and hydrogen-containing materials of plasma-facing components under irradiation by hydrogen and its isotopes. In the present calculation, amorphous lithium compound surfaces containing oxygen, Li 2 O, and LiOH were irradiated by 1-100 eV particles at incident angles on the surface ranging from perpendicular to almost grazing angles. Consequential surface processes, reflection, retention, and sputtering were studied at “the same footing” and compared to earlier results from amorphous Li and LiH surfaces. In conclusion, the critical role of charging dynamics of lithium, oxygen, and hydrogen atoms in the surface chemistry during hydrogen-fuel irradiation was found to drive the kinetics and dynamics of these surfaces in unexpected ways that ultimately could have profound effects on fusion plasma confinement behavior and surface erosion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Development of a plant carbon–nitrogen interface coupling framework in a coupled biophysical-ecosystem–biogeochemical model (SSiB5/TRIFFID/DayCent-SOM v1.0)

Plant and microbial nitrogen (N) dynamics and N availability regulate the photosynthetic capacity and capture, allocation, and turnover of carbon (C) in terrestrial ecosystems. Studies have shown that a wide divergence in representations of N dynamics in land surface models leads to large uncertainties in the biogeochemical cycle of terrestrial ecosystems and then in climate simulations as well as the projections of future trajectories. In this study, a plant C–N interface coupling framework is developed and implemented in a coupled biophysical-ecosystem–biogeochemical model (SSiB5/TRIFFID/DayCent-SOM v1.0). The main concept and structure of this plant C–N framework and its coupling strategy are presented in this study. This framework takes more plant N-related processes into account. The dynamic ratio (CNR) for each plant functional type (PFT) is introduced to consider plant resistance and adaptation to N availability to better evaluate the plant response to N limitation. Furthermore, when available N is less than plant N demand, plant growth is restricted by a lower maximum carboxylation capacity of RuBisCO (V c,max ), reducing gross primary productivity (GPP). In addition, a module for plant respiration rates is introduced by adjusting the respiration with different rates for different plant components at the same N concentration. Since insufficient N can potentially give rise to lags in plant phenology, the phenological scheme is also adjusted in response to N availability. All these considerations ensure a more comprehensive incorporation of N regulations to plant growth and C cycling. This new approach has been tested systematically to assess the effects of this coupling framework and N limitation on the terrestrial carbon cycle. Long-term measurements from flux tower sites with different PFTs and global satellite-derived products are employed as references to assess these effects. The results show a general improvement with the new plant C–N coupling framework, with more consistent emergent properties, such as GPP and leaf area index (LAI), compared to the observations. The main improvements occur in tropical Africa and boreal regions, accompanied by a decrease in the bias in global GPP and LAI by 16.3 % and 27.1 %, respectively.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Modeling the small-scale deposition of snow onto structured Arctic sea ice during a MOSAiC storm using snowBedFoam 1.0.

The remoteness and extreme conditions of the Arctic make it a very difficult environment to investigate. In these polar regions covered by sea ice, the wind is relatively strong due to the absence of obstructions and redistributes a large part of the deposited snow mass, which complicates estimates for precipitation hardly distinguishable from blowing or drifting snow. Moreover, the snow mass balance in the sea ice system is still poorly understood, notably due to the complex structure of its surface. Quantitatively assessing the snow distribution on sea ice and its connection to the sea ice surface features is an important step to remove the snow mass balance uncertainties (i.e., snow transport contribution) in the Arctic environment. In this work we introduce snowBedFoam 1.0., a physics-based snow transport model implemented in the open-source fluid dynamics software OpenFOAM. We combine the numerical simulations with terrestrial laser scan observations of surface dynamics to simulate snow deposition in a MOSAiC (Multidisciplinary Drifting Observatory for the Study of Arctic Climate) sea ice domain with a complicated structure typical for pressure ridges. The results demonstrate that a large fraction of snow accumulates in their vicinity, which compares favorably against scanner measurements. However, the approximations imposed by the numerical framework, together with potential measurement errors (precipitation), give rise to quantitative inaccuracies, which should be addressed in future work. The modeling of snow distribution on sea ice should help to better constrain precipitation estimates and more generally assess and predict snow and ice dynamics in the Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Uncertainty-driven dynamics for active learning of interatomic potentials

Machine learning (ML) models, if trained to data sets of high-fidelity quantum simulations, produce accurate and efficient interatomic potentials. Active learning (AL) is a powerful tool to iteratively generate diverse data sets. In this approach, the ML model provides an uncertainty estimate along with its prediction for each new atomic configuration. If the uncertainty estimate passes a certain threshold, then the configuration is included in the data set. Here we develop a strategy to more rapidly discover configurations that meaningfully augment the training data set. The approach, uncertainty-driven dynamics for active learning (UDD-AL), modifies the potential energy surface used in molecular dynamics simulations to favor regions of configuration space for which there is large model uncertainty. The performance of UDD-AL is demonstrated for two AL tasks: sampling the conformational space of glycine and sampling the promotion of proton transfer in acetylacetone. The method is shown to efficiently explore the chemically relevant configuration space, which may be inaccessible using regular dynamical sampling at target temperature conditions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Impact of Forest Canopy Structure on Buoyant Plume Dynamics During Wildland Fires

Heterogeneous forest canopies can generate complex turbulent structures, but in the presence of a fire plume, these interactions are not fully understood. This study investigates the influence of forest canopy heterogeneity on buoyant plume dynamics resulting from surface thermal anomalies representing wildland fires, utilizing Large Eddy Simulation (LES). The Parallelized Large-Eddy Simulation Model (PALM) was employed to simulate six canopy configurations: no canopy, homogeneous canopy, external plume-edge canopy, internal plume-edge canopy, 100 m gap canopy, and 200 m gap canopy. Each configuration was analyzed with and without a static surface heat flux patch of 5000 W ∙ m -2 , resulting in a resting buoyant plume. Simulations were conducted under three crosswind speeds: 0, 5, and 10 m ∙ s -1 . Results show that canopy structure significantly modifies plume behavior, mean flow, and turbulent kinetic energy (TKE) budgets. Plume updraft speed and tilt varied with canopy configuration and crosswind speed. Horizontal pressure gradients associated with plume-atmosphere interaction were modified based on the canopy configuration, resulting in varying crosswind speed reductions at the plume region. Strong momentum absorption was observed above the canopy for the crosswind cases, with the greatest enhancement in the gap canopies. Momentum injection from below the canopy due to the heat source was also observed, resulting in plume structure modulation based on canopy configuration. TKE was found to be the largest in the gap canopy configurations. TKE budget analysis revealed that buoyant production dominated over shear production. At the center of the heat patch, the gap canopy configurations showed enhanced buoyancy within the gap. These results improve our knowledge of fire-canopy-atmosphere interactions that can inform fire models on the impacts of canopy heterogeneity on plume dynamics and ember ejections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Primary biomolecular adsorption energetics of core–shell nanocomplexes: Implications for biological interactions

Molecular organization at the nano-bio interface governing the colloidal stability, reactivity, immune recognition, and drug delivery performance of nanoparticles remains difficult to predict. Quantifying the primary hydration energetics of biomolecule-coated nanomaterials can determine those interactions and provide a basis for engineered nanocarriers with tailored behavior in biological systems. Here, we measured the thermodynamics of water adsorption on patchy dry magnetite (Fe 3 O 4 ) nanoparticles coated with three model biomolecules, bovine serum albumin, potato starch, and lauric acid and compared these properties to the hydration energetics of the corresponding free dry biomolecules. The results demonstrate how the surface functionalization alters the hydrophilicity, the accessible hydrophilic surface, and the interaction potential of the nanocomplex surface with biological media. The protein coating increases the interaction potential of the surface of the nanocomplex. The weaker interaction potential of the polysaccharide coating and the relatively large hydrophilic surface area allow dynamic and reversible binding, while the fatty acid rearranges into a partial bilayer with very strong hydrophilicity. The findings establish the hydration enthalpy as a quantitative basis to determine and interpret nanoparticle interactions with proteins, membranes, and biological fluids, and provide a thermodynamic foundation for designing nanocarriers with predictable biological reactivity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Enhancement of Photoemission on p-Type GaAs Using Surface Acoustic Waves

We demonstrate that photoemission properties of p-type GaAs can be altered by surface acoustic waves (SAWs) generated on the GaAs surface due to dynamical piezoelectric fields of SAWs. Multiphysics simulations indicate that charge-carrier recombination is greatly reduced, and electron effective lifetime in p-doped GaAs may increase by a factor of 10× to 20×. It implies a significant increase, by a factor of 2× to 3×, of quantum efficiency (QE) for GaAs photoemission applications, like GaAs photocathodes. Conditions of different SAW wavelengths, swept SAW intensities, and varied incident photon energies were investigated. Essential steps in SAW device fabrication on a GaAs substrate are demonstrated, including deposition of an additional layer of ZnO for piezoelectric effect enhancement, measurements of current–voltage (I–V) characteristics of the SAW device, and ability to survive high-temperature annealing. Results obtained and reported in this study provide the potential and basis for future studies on building SAW-enhanced photocathodes, as well as other GaAs photoelectric applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

In-Situ FTIR Detection of Transition Metal (TM)-Ion Dissolution From Cathodes in Li-Ion Batteries

Transition metal (TM) ions, commonly Ni and Mn, play a crucial role in Li-ion battery cathodes as the reaction centers for rapid redox reactions. A major challenge with TM-based cathodes is capacity degradation, particularly at higher operating voltages. This degradation is closely linked to the dissolution of TMs from the cathode materials and their subsequent deposition on the anode. This process not only modifies the surface structure of the cathode but, more significantly, alters the SEI composition on the anode [1-2]. The dissolution of TMs cations into a liquid electrolyte from cathode materials, such as Mn-ion dissolution from Mn-rich cathode (LMR), is detrimental to the cycling performance of Li-ion batteries [3-4]. Much attention has been paid to this issue but there remains a lack of characterization techniques which can detect the TM-ion dissolution from the cathode during electrochemical measurements. In our study, we use in-situ ATR-FTIR as an effective technique to probe the TM-ion dissolution from the cathode. We have first demonstrated the detrimental effects of TM ions on the electrochemical performance of Li-ion batteries by adding a small amount of TM salt (50 mM Mn(PF6)) to the electrolyte of a Li-ion coin cell with LFP and graphite electrode. We observed a rapid capacity fade after the first delithiation cycle. To investigate TM ion dissolution, we established a baseline IR spectrum for various TM solvation states (such as Mn and Ni) by measuring concentration-dependent IR spectra. This baseline spectrum helps us detect TM ion dissolution during battery cycling. In this work, we discuss in detail the effect of TM ions on the electrochemical performance of Li-ion batteries and the detection of TM ions during battery cycling using in-situ FTIR spectroscopy. We will compare TM dissolution between coated and uncoated cathodes to examine the effect of cathode coatings to mitigate degradation due to TM dissolution and cross-over from cathode to anode. References: (1) Zhan, C.; Wu, T.; Lu, J.; Amine, K. Dissolution, migration, anddeposition of transition metal ions in Li-ion batteries exemplified byMn-based cathodes - a critical review. Energy Environ. Sci. 2018, 11,243-257. (2) Jung, R.; Linsenmann, F.; Thomas, R.; Wandt, J.; Solchenbach,S.; Maglia, F.; Stinner, C.; Tromp, M.; Gasteiger, H. A. Nickel,Manganese, and Cobalt Dissolution from Ni-Rich NMC and TheirEffects on NMC622-Graphite Cells. J. Electrochem. Soc. 2019, 166,A378-A389. (3) Zhao, L.; Chenard, E.; Capraz, O. O.; Sottos, N. R.; White, S.R. Direct Detection of Manganese Ions in Organic Electrolyte by UV-Vis Spectroscopy. J. Electrochem. Soc. 2018, 165, A345-A348 (4) Zhang, Y.; Hu, A.; Xia, D.; Hwang, S.; Sainio, S.; Nordlund, D.;Michel, F. M.; Moore, R. B.; Li, L.; Lin, F. Operando characterization and regulation of metal dissolution and redeposition dynamics nearbattery electrode surface. Nat. Nanotechnol. 2023, 18, 790.

25 ENERGY STORAGE↗
DOE OSTI2020

Advanced grazing-emission X-ray fluorescence spectroscopy with small-angle neutron scattering for in-vivo surface composition and defect/morphology surface evolution in tokamak PMI

The dynamic and extreme conditions of thermonuclear fusion tokamak plasmas render material surfaces almost impossible to examine in real-time, surface-sensitive conditions. However, combining particle-probe techniques that are not charge-state dependent open the possibilities of in-vivo diagnosis of the plasma-material interface. The reconstituted surfaces of plasma-facing components ranging from first-wall to divertor-component regions in the device vary depending on the complex plasma transport characteristics of the device. For example, in ITER it is predicted that fluxes of the order 10 22 to 10 24 and incident charged-particle energies of 100’s to 1000’s of eV will reach the surface while in the divertor regions within the private-flux and near the inner and outer-strike points would vary from a few eV to 100’s of eV governed by the complex Chodura magnetic sheath dynamics. This means that the penetration range of most charged-particle fluxes would range between 1-100’s of nm (e.g. for fuel particles of D and T and He).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Hydrodynamic instability at impact interfaces and planetary implications

Abstract Impact-induced mixing between bolide and target is fundamental to the geochemical evolution of a growing planet, yet aside from local mixing due to jetting – associated with large angles of incidence between impacting surfaces – mixing during planetary impacts is poorly understood. Here we describe a dynamic instability of the surface between impacting materials, showing that a region of mixing grows between two media having even minimal initial topography. This additional cause of impact-induced mixing is related to Richtmyer-Meshkov instability (RMI), and results from pressure perturbations amplified by shock-wave refraction through the corrugated interface between impactor and target. However, unlike RMI, this new impact-induced instability appears even if the bodies are made of the same material. Hydrocode simulations illustrate the growth of this mixing zone for planetary impacts, and predict results suitable for experimental validation in the laboratory. This form of impact mixing may be relevant to the formation of stony-iron and other meteorites.

58 GEOSCIENCES↗