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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Rapid Development of Hybrid Perovskites and Novel Tandem Architectures

Multijunction solar cells based on epitaxially grown III-V materials hold the record for solar energy power conversion efficiency (PCE). However, due to the high cost of fabricating these devices, they are typically only used for concentrator cells and space applications. The overarching goal of this project was to develop low-cost printable hybrid perovskite (HP) materials appropriate and optimized for tandem solar cells with high power conversion efficiency under “1 Sun” illumination. Key results and findings over the course of the project we: Developed higher-performance high-bandgap (1.75 eV) perovskite materials and devices. In particular, we explored tens-of-thousands of compositions for high bandgap perovskites, achieving quasi-Fermi level splitting of 1.35 eV for a 1.75 eV bandgap material. We achieved World-record open circuit voltages from single junction p-i-n devices, 1.24 V from 1.75 eV bandgap material, which is what is preferable for tandems with a PCE of 14.3% using a guanidinium/formanadinium/ cesium alloyed lead iodobromide. We also developed a series of World-record efficiency devices at higher band-gaps based on 2D/3D perovskites using PEA. Developed higher-performance low-bandgap (1.35 eV) perovskite materials and devices. In particular, we developed a 1.35 eV bandgap perovskite of composition MAPb0.5Sn0.5(I0.8Br0.2)3 and showed its superiority to MAPb0.75Sn0.25I3. High efficiency solar cells were fabricated using PEDOT:PSS and doped-ICBA as HTL and ETL, respectively. Short circuit currents of 25.7 mA/cm2 and PCEs of 17.1% were obtained. Developed mechanically stacked 4-terminal CIGS-Perovskite tandems with PCE of 18.8% and monolithic 2-terminal CIGS-Perovskite tandems with PCE of 8.5%. The low efficiency of the monolithic device is a result of the high surface roughness of the solution processed CIGS bottom cells. This is not an intrinsic problem for CIGS-perovskite tandems, but does mean that smooth evaporated or sputtered CIGS films likely need to be used, unless a polishing step is employed. Developed monolithic 2-terminal Perovskite-Perovskite tandems with a stabilized PCE of 18.5%. This was the World-record perovskite-perovskite monolithic tandems for over a year in 2017-2018. Revealed that light is not an essential component of the so-called “light-induced” phase segregation. By using charge injection in the dark and electroluminescence, we showed that the presence of electrons in the conduction band and hole in the valence band is sufficient to drive the nearly ubiquitously observed phase segregation in high bandgap perovskites. Developed a new method to simultaneously measure absolute intensity photoluminescence and photoconductivity and use them to obtain simultaneous in-situ measurement of quasi-Fermi level splitting and diffusion length. This is important since it provides a proxy for device Voc and device Jsc. In addition, 67 papers were published with support from this award that detail many more advances in the field, including numerous publications in high impact journals such as Nature Photonics, Advanced Materials, ACS Energy Letters, and Energy and Environmental Science.

14 SOLAR ENERGY↗
DOE OSTI2023

High Performance Pd/4H-SiC Epitaxial Schottky Barrier Radiation Detectors for Harsh Environment Applications

Although many refractory metals have been investigated as the choice of contact metal in 4H-SiC devices, palladium (Pd) as a Schottky barrier contact for 4H-SiC radiation detectors for harsh environment applications has not been investigated adequately. Pd is a refractory metal with high material weight-to-thickness ratio and a work function as high as nickel, one of the conventional metal contacts for high performing 4H-SiC Schottky barrier detectors (SBDs). In this article, Pd/4H-SiC epitaxial SBDs have been demonstrated for the first time as a superior self-biased (0 V applied bias) radiation detector when compared to benchmark Ni/4H-SiC SBDs. The Pd/4H-SiC SBD radiation detectors showed a very high energy resolution of 1.9% and 0.49% under self- and optimized bias, respectively, for 5486 keV alpha particles. The SBDs demonstrated a built-in voltage (V bi ) of 2.03 V and a hole diffusion length (L d ) of 30.8 µm. Such high V bi and L d led to an excellent charge collection efficiency of 76% in the self-biased mode. Capacitance mode deep level transient spectroscopy (DLTS) results revealed that the “lifetime-killer” Z 1/2 trap centers were present in the 4H-SiC epilayer. Another deep level trap was located at 1.09 eV below the conduction band minimum and resembles the EH5 trap with a concentration of 1.98 × 10 11 cm –3 and capture cross-section 1.7 × 10 –17 cm –2 ; however, the detector performance was found to be limited by charge trapping in the Z 1/2 center. The results presented in this article revealed the unexplored potential of a wide bandgap semiconductor, SiC, as high-efficiency self-biased radiation detectors. Such high performance self-biased radiation detectors are poised to address the longstanding problem of designing self-powered sensor devices for harsh environment applications e.g., advanced nuclear reactors and deep space missions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Atomistic simulations and machine learning of solute grain boundary segregation in Mg alloys at finite temperatures

Understanding solute segregation thermodynamics is the first step in investigating grain boundary (GB) properties, such as strong yttrium (Y) effects on grain growth and texture evolution in micro-scale polycrystalline magnesium (Mg) alloys. To estimate the average GB segregation behavior in low-solute-concentration Mg alloys (e.g., 2 at.% Y), a state-of-the-art spectral approach is applied based on a per-site segregation energy spectrum for Y solute atoms at zero K obtained from molecular statistics (MS) simulations of ~10 4 GB sites in Mg symmetric tilt GBs (STGBs). Although selected MS simulation results are consistent with verification by density functional theory (DFT) calculations, estimates of average segregation tendency based on the zero-K energy spectrum deviate from experimental observations. To resolve this problem, thermodynamic integration (TI) methods based on molecular dynamics (MD) simulations are used to determine the per-site segregation free energies of Y at representative GB sites, which show contributions beyond harmonic approximations can be important for certain GB sites at high temperatures. A surrogate model of per-site segregation free energy is constructed from a small set of TI data points using stacking cross-validation regressors and physics-informed descriptors. This model is applied to predict the Y segregation free energy spectra for thousands of GB sites in Mg STGBs with uncertainty quantification. Finally, the average segregation tendency predicted by the spectral approach based on the free energy spectra agrees well (within the uncertainty range) with experimental observations for micro-scale polycrystalline Mg alloys at typical thermomechanical processing temperatures (500 ~ 800 K), where thermodynamic equilibrium states are likely to be achieved due to fast diffusion.

Atomistic simulations↗
DOE OSTI2017

Scalable domain decomposition solvers for stochastic PDEs in high performance computing

Stochastic spectral finite element models of practical engineering systems may involve solutions of linear systems or linearized systems for non-linear problems with billions of unknowns. For stochastic modeling, it is therefore essential to design robust, parallel and scalable algorithms that can efficiently utilize high-performance computing to tackle such large-scale systems. Domain decomposition based iterative solvers can handle such systems. And though these algorithms exhibit excellent scalabilities, significant algorithmic and implementational challenges exist to extend them to solve extreme-scale stochastic systems using emerging computing platforms. Intrusive polynomial chaos expansion based domain decomposition algorithms are extended here to concurrently handle high resolution in both spatial and stochastic domains using an in-house implementation. Sparse iterative solvers with efficient preconditioners are employed to solve the resulting global and subdomain level local systems through multi-level iterative solvers. We also use parallel sparse matrix–vector operations to reduce the floating-point operations and memory requirements. Numerical and parallel scalabilities of these algorithms are presented for the diffusion equation having spatially varying diffusion coefficient modeled by a non-Gaussian stochastic process. Scalability of the solvers with respect to the number of random variables is also investigated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Dynamical chemistry: non-equilibrium effective actions for reactive fluids

Abstract We present two approaches for describing chemical reactions taking place in fluid phase. The first method mirrors the usual derivation of the hydrodynamic equations of motion by relating conserved—or to account for chemical reactions, non-conserved—currents to local-equilibrium parameters. The second method involves a higher-brow approach in which we attack the same problem from the perspective of non-equilibrium effective field theory (EFT). Non-equilibrium effective actions are defined using the in–in formalism on the Schwinger–Keldysh contour and are therefore capable of describing thermal fluctuations and dissipation as well as quantum effects. The non-equilibrium EFT approach is especially powerful as all terms in the action are fully specified by the symmetries of the system; in particular the second law of thermodynamics does not need to be included by hand, but is instead derived from the action itself. We find that the equations of motion generated by both methods agree, but the EFT approach yields certain advantages. To demonstrate some of these advantages we construct a quadratic action that is valid to very small distance scales—much smaller than the scales at which ordinary hydrodynamic theories break down. Such an action captures the full thermodynamic and quantum behavior of reactions and diffusion at quadratic order. Finally, taking the low-frequency and low-wavenumber limit, we reproduce the linearized version of the well-known reaction–diffusion equations as a final coherence check.

Mechanics↗
DOE OSTI2021

Microbubble dynamics and heat transfer in boiling droplets

Dissipating large heat fluxes from a surface is critically important in numerous industrial and natural applications. Boiling based spray cooling and surface texturing are two of the most promising methods being investigated to address this problem. Although our understanding on these topics has significantly improved over past decades, critical gaps remain in the knowledgebase stymieing the realization of their full potential. As an example, while bubble growth in pool boiling have been investigated in detail, comparatively little is known about how the bubbles evolve inside boiling drops. In the present work, we have investigated for the first time, the microbubble dynamics inside water droplets boiling on superhydrophilic textured substrates using high-speed X-ray phase contrast imaging (XRPCI). Our observations show that the transient bubble density variation follows similar characteristics irrespective of the texture spacing at a given surface temperature. For an example microstructure, we found that the number of discrete bubbles on the surface decreases as temperature is increased although their growth rate increases. Here, we observe that bubble growth is highly non-uniform during the lifetime of a drop on the surface. Initially, bubbles grow under diffusion-limited regime, but at later times they grow as ~t 1.45 due to combined effects of coalescence and evaporation. In some conditions, we found that bubbles shrink dramatically af- ter the initial growth spurt presumably due to severe quenching of the surface, and migration of bubbles on the surface. Using the bubble sizes, for the first time we analyzed the heat flux removed by a single bubble and also by all the bubbles at a given time. We find that the highest dissipation through latent- heat component (~600 W/cm 2 ) occurs just in the beginning and thereafter it decreases. We expect that our findings and the analysis would guide further work on the topic and will aid in the overarching goal of engineering surfaces that are more efficient in boiling heat transfer.

42 ENGINEERING↗
DOE OSTI2021

Realization of a high luminosity muon beam at the Jefferson Lab

The proton is the major component of the visible matter of our universe, so being able to determine its fundamental properties, such as its charge radius, is of vital importance. In recent years, several experiments have been performed for the accurate measurement of the proton radius with different experimental techniques. The main and most common are based on two different techniques: ep scattering and Lamb shift spectroscopy of regular hydrogen atoms. The latter can also be performed on muonic hydrogen atoms with a significant improvement in accuracy. Recent measurements that use this method have highlighted a discrepancy between the results obtained with the diffusion of electrons and those obtained with the spectroscopic technique leading to the so-called ?proton radius puzzle?. The explanation of why this difference between the measured values exists is still a matter of discussion. The last attempt to address the puzzle was the PRad Experiment. It was performed with a unique experimental setup that gave the scientists an excellent control on the systematic errors that are usually present in electron-proton scattering experiments. This has significantly increased the precision of the measurement, bringing it in the same area as the spectroscopic ones done on muonic hydrogen atoms, which are considered the most precise. However, to solve the puzzle once and for all, even more precise electron scattering measurements are needed. Alternatively, new methods can be used, such as eg. muon-proton scattering at low transferred momenta in order to lower the systematic errors that comes with the measurement. This thesis tries to address this problem by studying the set up of an intense muon beam at the Jefferson Laboratory (JLab) that can be used to carry out a high-precision m ? p scattering experiment. Using Montecarlo simulations I studied the muon production resulting from the interaction of the primary electron beam with the beam-dump at JLab Hall-A. The simulations were performed using the FLUKA package via the FLAIR graphical interface. In this study, I modified an existing geometry (built for the ?Beam Dump eXperiment?) and performed several studies in order to optimize the muon beam parameters. In order to estimate the beam intensity, I studied the muon generation and transportation through the concrete bunker surrounding the Hall-A beam-dump. Detailed studies on muon attenuation and dispersion at different depth allowed me to track the beam profile in space and momentum as a function of the distance from the beam-dump. Last, but not least, I studied a possible tagging system for the muon beam. The tagging system will allow us to know with good precision (O(1=1000)) the energy of each muon of the beam. Based on the results obtained, I created an event generator that incorporates the detailed description of the muon beam (energy, position, emittance) useful to define and optimize the experimental setup for a future measurement of the proton radius at the JLab.

Fulci, Antonino↗
DOE OSTI2021

Mixing Cell Model: A One-Dimensional Numerical Model for Assessment of Water Flow and Contaminant Transport in the Unsaturated Zone

This report describes the Mixing Cell Model code, a one dimensional model for water flow and solute transport in the unsaturated zone under steady state or transient flow conditions. The model is based on the principles and assumptions underlying mixing-cell model formulations. The unsaturated zone is discretized into a series of independent mixing cells. Each cell may have unique hydrologic, lithologic, and sorptive properties. Ordinary differential equations describe the material (water and solute) balance within each cell. Water-flow equations are derived from the continuity equation, assuming that unit gradient conditions exist at all times in each cell. Pressure gradients are considered implicitly through model discretization. Unsaturated hydraulic conductivity and moisture contents are determined by the material specific moisture-characteristic curves. Solute-transport processes include explicit treatment of advective processes, first order chain decay, and linear sorption reactions. Dispersion is addressed through implicit and explicit dispersion. Implicit dispersion is an inherent feature of all mixing-cell models and originates from the formulation of the problem in terms of mass balance around fully mixed volume elements. Expressions are provided that relate implicit dispersion to the physical dispersion of the system. Two FORTRAN codes were developed to solve the water flow and solute-transport equations: (1) the Mixing Cell Model for Flow (MCMF) solves transient water-flow problems and (2) the Mixing Cell Model for Transport (MCMT) solves the solute-transport problem. The transient water-flow problem is typically solved first by estimating the water flux through each cell in the model domain as a function of time using the MCMF code. These data are stored in either ASCII or binary files that are later read by the solute transport code (MCMT). Code output includes solute pore water concentrations, water and solute inventories in each cell and at each specified output time, and water and solute fluxes through each cell and specified output time. Computer run times for coupled transient water flow and solute transport were typically several seconds on a 2 GHz Intel Pentium IV desktop computer. The model was benchmarked against analytical solutions and finite element approximations to the partial differential equations (PDE) describing unsaturated flow and transport. Differences between the maximum solute flux estimated by the mixing cell model and the PDE models were typically less than two percent. This revision includes an option for a fixed concentration lower boundary condition for diffusive fluxes for versions 020321 and later.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

A dynamical weak scale from inflation

Dynamical scanning of the Higgs mass by an axion-like particle during inflation may provide a cosmological component to explaining part of the hierarchy problem. We propose a novel interplay of this cosmological relaxation mechanism with inflation, whereby the backreaction of the Higgs vacuum expectation value near the weak scale causes inflation to end. As Hubble drops, the relaxion's dissipative friction increases relative to Hubble and slows it down enough to be trapped by the barriers of its periodic potential. Such a scenario raises the natural cut-off of the theory up to ∼ 10{sup 10} GeV, while maintaining a minimal relaxion sector without having to introduce additional scanning scalars or new physics coincidentally close to the weak scale.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Phosphides or nitrides for better NLO properties? A detailed comparative study of alkali metal doped nano-cages

Highlights: • Alkali metal doped boron and aluminum phosphide nano-cages are evaluated for NLO properties. • The NLO response of phosphide nano-cages is compared with nitride nano-cages. • Phosphide nano-cages show better NLO properties than the corresponding nitride nano-cages. • Conductivity of doped nano-cages is much higher than pristine nano-cages. • MAl{sub 11}P{sub 12} and MB{sub 11}P{sub 12} show monotonic increase in hyperpolarizability with size of alkali metal. - Abstract: Phosphide nano-cages of MX{sub 12}P{sub 11} and MX{sub 11}P{sub 12} (where X = B or Al, M = Li, Na, K) are investigated theoretically for geometric, electronic and nonlinear optical (NLO) properties. Alkali metal is doped by replacing (a) aluminum or boron atom and (b) phosphorus atom. Alkali metal doping can remarkably alter the electronic and NLO properties of the nano-cages, regardless of doping site. HOMO-LUMO gap is decreased whereas first hyperpolarizability is enhanced significantly in doped AlP and BP nano-cages. PDOS (partial density of states) analysis suggests that diffuse excess electrons from alkali metal play important role in boosting NLO properties of phosphide nano-cages. TD-DFT calculations are performed to study the effect of alkali metal doping on absorption spectra. Red shift is observed in the UV–vis spectra of all considered nano-cages. Comparison of phosphide nano-cages with nitride nano-cages indicated that doping nitride nano-cages with alkali metal leads to greater hyperpolarizability and NLO response than doping phosphide nano-cages.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Development of Diffusion-type Hydrogen Meters for Steam Generator Leak Detection System of Sodium-cooled Fast Reactors

The goal of this project is to develop and demonstrate diffusion-type hydrogen meters (DTHMs) for hydrogen concentration in cover gas or in molten sodium. Prompt detection of steam-to-sodium leaks of a sodium-heated steam generator (SHSG) is one of the most important economic and safety issues to be addressed in designing and operating a sodium-cooled fast reactor (SFR). A water-to-sodium leak causes a violent exothermic sodium-water reaction (SWR) resulting in local temperature rise (>1,200°C) and produces hydrogen gas and highly corrosive chemicals. The SWR often induces self-enlargement (self-wastage) of the leak and rapid propagation of wastage to adjacent tubes, leading to secondary or multiple tube failures. If it is unmitigated, the hydrogen gas formation could cause a pressure increase in the reactor and may cause a SHSG blowdown, and ultimately result in shutdown of the reactor. In addition, if their effects are unmitigated, the highly corrosive chemicals formed could lead to and accelerate the corrosion problems of the SHSG and sodium piping.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A weighted state redistribution algorithm for embedded boundary grids

State redistribution is an algorithm that stabilizes cut cells for embedded boundary grid methods. This work extends the earlier algorithm in several important ways. First, state redistribution is extended to three spatial dimensions. Second, we discuss several algorithmic changes and improvements motivated by the more complicated cut cell geometries that can occur in higher dimensions. In particular, we introduce a weighted version with less dissipation in an easily generalizable framework. Third, we demonstrate that state redistribution can also stabilize a solution update that includes both advective and diffusive contributions. Notably, the stabilization algorithm is shown to be effective for incompressible as well as compressible reacting flows. Finally, we discuss the implementation of the algorithm for several exascale-ready simulation codes based on AMReX, demonstrating ease of use in combination with domain decomposition, hybrid parallelism and complex physics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Fast Multigrid Reduction-in-Time for Advection via Modified Semi-Lagrangian Coarse-Grid Operators

Many iterative parallel-in-time algorithms have been shown to be highly efficient for diffusion-dominated partial differential equations (PDEs) but are inefficient or even divergent when applied to advection-dominated PDEs. We consider the application of the multigrid reduction-in-time (MGRIT) algorithm to linear advection PDEs. Here, the key to efficient time integration with this method is using a coarse-grid operator that provides a sufficiently accurate approximation to the so-called ideal coarse-grid operator. For certain classes of semi-Lagrangian discretizations, we present a novel semi-Lagrangian-based coarse-grid operator that leads to fast and scalable multilevel time integration of linear advection PDEs. The coarse-grid operator is composed of a semi-Lagrangian discretization followed by a correction term, with the correction designed so that the leading-order truncation error of the composite operator is approximately equal to that of the ideal coarse-grid operator. Parallel results show substantial speed-ups over sequential time integration for variable-wave-speed advection problems in one and two spatial dimensions, and using high-order discretizations up to order five. The proposed approach establishes the first practical method that provides small and scalable MGRIT iteration counts for advection problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Morphology and Transport of Multivalent Cation-Exchanged Ionomer Membranes Using Perfluorosulfonic Acid–Ce Z+ as a Model System

Perfluorosulfonic acids (PFSAs) are commonly used as solid polymer electrolyte membranes (PEMs) in electrochemical energy devices, where they are vulnerable to attack by radical species during operation. A popular strategy to combat this problem is to introduce radical scavengers like cerium (Ce) ions that neutralize these species before they attack the PFSA. Such cation doping creates a multi-ion system, in which understanding the mechanisms of cation solvation and transport becomes important for the effective design and utilization of PFSA–cation systems. Ce ions also provide a representative model system for multication-exchanged ionomers in electrochemical systems. In this study, hydration and conductivity measurements, along with X-ray fluorescence and scattering, are employed to elucidate how Ce ion exchange alters PFSA’s ionic solvation, as well as nano- and mesoscale morphologies, which ultimately control its ion transport properties. A molecular transport model is used to deconvolute the impact of Ce ions on the local solvation structure of water in the membrane from mesoscale changes of the transport pathways. The combined experimental and theoretical analysis reveals a nonlinear decrease in conductivity driven by cation solvation at the molecular level and morphological changes at longer length scales. Migration–diffusion coupling, its nonlinear dependence on ion exchange and hydration, and its overall implications for ionomer performance are also discussed. Finally, these findings have the potential to be translated into other mixed cation–ionomer systems for a wide range of energy and environmental devices.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Final Report: In-Situ TEM Observations of Degradation Mechanisms in Next-Generation High-Energy Density Lithium-Ion Battery Systems

This project originally sought to characterize nanoscale processes associated with the degradation of next-generation high energy density lithium-ion battery electrodes via in-situ transmission electron microscopy (TEM). The research also focused on developing the experimental techniques necessary for investigating electrochemical systems by in-situ transmission electron microscopy and providing a framework for understanding and quantifying electron beam effects that influence experimental results. In line with these goals, this project demonstrated and published the first in-situ TEM cycling of a Li-ion battery electrode in commercially relevant non-aqueous electrolyte: a technique subsequently adopted by a number of researchers in the field. Experiments performed on Sn anodes, demonstrated porosity evolution during Li dealloying as a mechanism for strain accommodation during the first cycle, and observed partially reversible crystalline to amorphous phase transitions associated with Li insertion and extraction in subsequent cycles. Complementary study of in-situ dealloying in a simple model, Au-Cu, was also performed. We also published the earliest quantitative measurements of electron beam effects in aqueous and non-aqueous liquids. Specifically, we utilized a model system to quantify the fraction of incident electron beam that contributed to charge transfer mediated reactions in non-aqueous liquid, since such liquids are primarily dose sensitive. We also quantified the evolution of model aqueous chemistries as a function of dose rate and chemical potential to better understand the reaction mechanisms active in liquids exposed to electron beams. The original project goals included the use of controlled environments to simulate different battery operational conditions. To aid such experiments, we developed new experimental apparatuses and techniques to perform in-situ liquid cell TEM under controlled temperature, including heating and cooling. We demonstrated this capability in aqueous systems; specifically understanding phase selection and solid-liquid interface interactions with particles during water crystallization and hydrothermal precipitation kinetics of ZnO. We also published the first demonstration of in-situ TEM based high-field (plasma) experiments and in-situ TEM of aqueous photochemistry, which demonstrated an previously unrecognized early growth mode transition during Au sputtering and delocalization of gas bubble nucleation during water splitting, respectively. In addition to the scientific results, this portion of the project greatly expanded the range of systems that can be characterized in realistic environments at the nanoscale via in-situ TEM. Unfortunately, commercial battery electrolytes are quite sensitive to electron dose. This limits the time of acquisition and/or the spatial resolution of the experiments. The same problem has been encountered in all subsequent publications in the field. The major problem, relative to the project original goals, is that long term cycling is challenging to characterize and the desired high resolution or analytical capabilities are limited. In line with our original goals to characterize battery reaction and degradation mechanisms under controlled electrochemical cycling, we developed a completely new type of Li-ion electrochemical cell that has been useful for both structural and analytical characterization. To date, we have demonstrated this platform for in-situ cycling of Li-ion batteries during scanning electron microscopy (SEM), Auger electron spectroscopy (AES), and x-ray photoelectron spectroscopy (XPS). In-situ AES has been found to be a quite powerful tool to characterize the chemical evolution of Li-ion batteries cycled in-situ and much of our effort in the final project period has focused on charactering Li-ion cathodes using the technique. We utilized in-situ SEM to propose a new mechanism for Li whisker/dendrite formation and show the importance of diffusion mediated stress relaxation in fracture of Sn anode particles. A combination of in-situ XPS and AES was used to clarify the CuO anode reaction mechanism. In the final project period, we have gained new insights into surface reactions occurring on cathodes at high voltage using in-situ AES. Specifically, we have discovered that many of the SEI formation reactions typically attributed to electrolyte decomposition are actually more fundamental to the electrode material surface thermodynamics in the presence of an arbitrary carbon source. These insights greatly affect how we understand and control surface degradation induced capacity fade at cathodes. Finally, we have made some effort to apply this novel in-situ platform to TEM characterization and believe this is a fruitful avenue for future research.

25 ENERGY STORAGE↗
DOE OSTI2021

Distributed State Estimation Over Time-Varying Graphs: Exploiting the Age-of-Information

Here, we study the problem of designing a distributed observer for an LTI system over a time-varying communication graph. The limited existing work on this topic imposes various restrictions either on the observation model or on the sequence of communication graphs. In contrast, we propose a single-time-scale distributed observer that works under mild assumptions. Specifically, our communication model only requires strong-connectivity to be preserved over non-overlapping, contiguous intervals that are even allowed to grow unbounded over time. We show that under suitable conditions that bound the growth of such intervals, joint observability is sufficient to track the state of any discrete-time LTI system exponentially fast, at any desired rate. We also develop a variant of our algorithm that is provably robust to worst-case adversarial attacks, provided the sequence of graphs is sufficiently connected over time. The key to our approach is the notion of a "freshness-index" that keeps track of the age-of-information being diffused across the network. Such indices enable nodes to reject stale estimates of the state, and, in turn, contribute to stability of the error dynamics.

42 ENGINEERING↗
DOE OSTI2020

PPINN: Parareal physics-informed neural network for time-dependent PDEs

Physics-informed neural networks (PINNs) encode physical conservation laws and prior physical knowledge into the neural networks, ensuring the correct physics is represented accurately while alleviating the need for supervised learning to a great degree. While effective for relatively short-term time integration, when long time integration of the time-dependent PDEs is sought, the time–space domain may become arbitrarily large and hence training of the neural network may become prohibitively expensive. To this end, we develop a parareal physics-informed neural network (PPINN), hence decomposing a long-time problem into many independent short-time problems supervised by an inexpensive/fast coarse-grained (CG) solver. In particular, the serial CG solver is designed to provide approximate predictions of the solution at discrete times, while initiate many fine PINNs simultaneously to correct the solution iteratively. There is a two-fold benefit from training PINNs with small-data sets rather than working on a large-data set directly, i.e., training of individual PINNs with small-data is much faster, while training the fine PINNs can be readily parallelized. Consequently, compared to the original PINN approach, the proposed PPINN approach may achieve a significant speed-up for long-time integration of PDEs, assuming that the CG solver is fast and can provide reasonable predictions of the solution, hence aiding the PPINN solution to converge in just a few iterations. To investigate the PPINN performance on solving time-dependent PDEs, we first apply the PPINN to solve the Burgers equation, and subsequently we apply the PPINN to solve a two-dimensional nonlinear diffusion–reaction equation. Furthermore, our results demonstrate that PPINNs converge in a few iterations with significant speed-ups proportional to the number of time-subdomains employed.

42 ENGINEERING↗