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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Reinforcement Learning-Based Oscillation Dampening: Scaling Up Single-Agent Reinforcement Learning Algorithms to a 100-Autonomous-Vehicle Highway Field Operational Test

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. Here, we explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Absolute electron density fluctuation reconstruction for two-dimensional hydrogen beam emission spectroscopy

Scrape-off layer (SOL) and edge plasma turbulence significantly contribute to the radial particle and heat transport, lowering the plasma confinement and increasing the heat load on the plasma facing components. SOL turbulence is predominantly intermittent, which manifests in the occurrence of isolated density filaments or blobs. Filaments propagate radially outward toward plasma facing components, limiting their lifetime by erosion and sputtering. To characterize this phenomenon in detail, few diagnostic techniques are available. Beam emission spectroscopy is a diagnostic capable of measuring plasma turbulence in both SOL and edge plasmas. Due to the finite lifetime of the excitation states during the beam–plasma interaction and the misalignment between the optics and the magnetic field, spatial smearing is introduced in the measurement. In this paper, a novel method is introduced to overcome this hindering effect by inverting the fluctuation response matrix on an optimally smoothed signal. We show that this method is fast and provides significantly more accurate absolute density fluctuation reconstruction than the direct inversion technique. Here, the presented method is usable for all types of beam emission diagnostics where the spatial resolution is higher than the combined smearing of the atomic physics and the observation.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

"Reinforcement Learning Based Oscillation Dampening: Scaling up Single-Agent RL algorithms to a 100 AV highway field operational test"

In this article, we explore the technical details of the reinforcement learning (RL) algorithms that were deployed in the largest field test of automated vehicles designed to smooth traffic flow in history as of 2023, uncovering the challenges and breakthroughs that come with developing RL controllers for automated vehicles. We delve into the fundamental concepts behind RL algorithms and their application in the context of self-driving cars, discussing the developmental process from simulation to deployment in detail, from designing simulators to reward function shaping. We present the results in both simulation and deployment, discussing the flow-smoothing benefits of the RL controller. From understanding the basics of Markov decision processes to exploring advanced techniques such as deep RL, our article offers a comprehensive overview and deep dive of the theoretical foundations and practical implementations driving this rapidly evolving field. We also showcase real-world case studies and alternative research projects that highlight the impact of RL controllers in revolutionizing autonomous driving. From tackling complex urban environments to dealing with unpredictable traffic scenarios, these intelligent controllers are pushing the boundaries of what automated vehicles can achieve. Furthermore, we examine the safety considerations and hardware-focused technical details surrounding deployment of RL controllers into automated vehicles. As these algorithms learn and evolve through interactions with the environment, ensuring their behavior aligns with safety standards becomes crucial. We explore the methodologies and frameworks being developed to address these challenges, emphasizing the importance of building reliable control systems for automated vehicles.

Jang, Kathy↗
DOE OSTI2024

GalaxyFlow: upsampling hydrodynamical simulations for realistic mock stellar catalogues

ABSTRACT Cosmological N-body simulations of galaxies operate at the level of ‘star particles’ with a mass resolution on the scale of thousands of solar masses. Turning these simulations into stellar mock catalogues requires ‘upsampling’ the star particles into individual stars following the same phase-space density. In this paper, we introduce two new upsampling methods. First, we describe GalaxyFlow, a sophisticated upsampling method that utilizes normalizing flows to both estimate the stellar phase-space density and sample from it. Secondly, we improve on existing upsamplers based on adaptive kernel density estimation (KDE), using maximum likelihood estimation to fine-tune the bandwidth for such algorithms in a way that improves both the density estimation accuracy and upsampling results. We demonstrate our upsampling techniques on a neighbourhood of the Solar location in two simulated galaxies: Auriga 6 and h277. Both yield smooth stellar distributions that closely resemble the stellar densities seen in the Gaia DR3 catalogue. Furthermore, we introduce a novel multimodel classifier test to compare the accuracy of different upsampling methods quantitatively. This test confirms that GalaxyFlow more accurately estimates the density of the underlying star particles than methods based on KDE, at the cost of being more computationally intensive.

Lim, Sung Hak (ORCID:0000000330981092)↗
DOE OSTI2024

Experimental and numerical investigation of fracture conductivity between non-smooth rock surfaces with and without proppant

The enhancement of fracture conductivity is vital for the efficient recovery of subsurface resources, such as geothermal energy and petroleum hydrocarbons. Proppants, granular materials injected into hydraulic fractures to maintain their conductivity, have been studied primarily in the context of smooth fractures (i.e., fractures between smooth rock surfaces). However, non-smooth fractures (i.e., fractures between rough rock surfaces) are common in geoenergy reservoirs and thus require further investigations. In this study, we conducted laboratory measurements of fracture conductivity on shale slabs with non-smooth surfaces and carried out numerical simulation using the lattice Boltzmann (LB) method, which aimed to investigate the conductivity of non-smooth fractures with and without proppants placement. When ceramic proppant with an areal concentration of 2 lb/ft 2 was placed in the fracture, the conductivity was enhanced by roughly 3-8 times compared to fractures without proppant. In fractures with proppant, gas-measured conductivity was higher than that measured with water due to proppant embedment caused by water. The experiments demonstrate the advantages of using proppant in fractures, even if the rock surface roughness can provide certain fracture conductivity via the self-propping mechanism. For fractures without proppants, high rock surface roughness is not necessarily favorable for enhancing fracture conductivity because the self-propping mechanism requires shear slip along the fracture surface. If there is no shear slip, high rock surface roughness can cause a detrimental effect on the fracture conductivity due to the interlocking effect. Utilizing advanced experimental equipment and LB modeling, this research explores the interplays between proppant placement, fracture geometry, and stress conditions to develop a comprehensive understanding of the productivity in non-smooth fractures. Further, the outcomes of this investigation indicate the importance of creating fractures with surface roughness during hydraulic fracturing and will contribute to the development of more efficient stimulation techniques for subsurface energy extraction.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Inverse design of pore wall chemistry and topology through active learning of surface group interactions

Design of next-generation membranes requires a nanoscopic understanding of the effect of biologically inspired heterogeneous surface chemistries and topologies (roughness) on local water and solute behavior. In particular, the rejection of small, neutral solutes, such as boric acid, poses a heretofore unsolved challenge. In prior work, a computational inverse design technique using an evolutionary optimization successfully uncovered new surface design strategies for optimized transport of water over solutes in smooth, model pores consisting of two surface chemistries. However, extending such an approach to more complex (and realistic) scenarios involving many surface chemistries as well as surface roughness is challenging due to the expanded design space. In this work, we develop a new approach that uses active learning to optimize in a reduced feature space of surface group interactions, finding parameters that lead to their assembly into ordered, optimal patterns. This approach rapidly identifies novel surface functionalizations that maximize the difference in water and boric acid transport through the nanopore. Moreover, we find that the roughness of the nanopore wall, independent of its chemistry, can be leveraged to enhance transport selectivity: oscillations in the pore wall diameter optimally inhibit boric acid transport by creating energetic wells from which the solute must escape to transport down the pore. Furthermore, this proof-of-concept demonstrates the potential for active learning strategies, in concert with molecular simulations, to rapidly navigate complex design spaces of aqueous interfaces and is promising as a tool for engineering water-mediated surface interactions for a broad range of applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Combined Dimensional and Topology Optimization of Interior Permanent Magnet Synchronous Machine Rotors Using a Permanent Magnet Function Interpolation Method

This paper presents a magneto-structural combined dimensional and topology optimization technique for interior permanent magnet synchronous machine (IPMSM) rotors. Dimensional changes to the permanent magnet (PM) location or size are accomplished by interpolating or projecting a smoothed Heaviside rectangular function representing the presence of PM material onto the IPMSM rotor design domain mesh. A density based Solid Isotropic with Material Penalization (SIMP) topology optimization approach is then used to vary the presence of electrical steel in mesh elements to form flux barriers around the PM. The proposed method enforces a defined shape for the PM without requiring the mesh in the design domain to be deformed. Three examples are presented to demonstrate the technique: two flat bar IPMSM and one V-shaped IPMSM.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

A Method to Probe the Interfaces in La2−xSrxCuO4-LaSrAlO4-La2−xSrxCuO4 Trilayer Junctions

C-axis trilayer cuprate Josephson junctions are essential for basic science and digital circuit applications of high-temperature superconductors. We present a method for probing the interface perfection in La2−xSrxCuO4 (LSCO)-LaSrAlO4 (LSAO)-La2−xSrxCuO4 trilayer junctions. A series of LSCO-LSAO superlattices with atomically smooth surfaces and sharp interfaces were grown by the atomic-layer-by-layer molecular beam epitaxy (ALL-MBE) technique. We have systematically varied the thickness of LSCO and LSAO layers with monolayer precision. By studying the mutual inductance and electrical transport in these superlattices, we detect the non-superconducting (“dead”) layers at the interfaces and quantify their thicknesses. Our results indicate that two optimally doped LSCO monolayers just above and below the one monolayer LSAO barrier are no longer superconducting, rendering the actual barrier thickness of five monolayers. Next, we have shown that introducing a protective highly-overdoped LSCO layer reduces the thickness of dead layers by one or two monolayers.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Temperature Uncertainty Modeling with Proxy Structural Data as Geostatistical Constraints for Well Siting: An Example Applied to Granite Springs Valley, NV, USA

Utilizing existing temperature and structural information around Granite Springs Valley, Nevada, we build 3D stochastic temperature models with the aim of evaluating the 3D uncertainty of temperature and choosing between candidate exploration well locations . The data used to support the modeling are measured temperatures and structural proxies from 3D geologic modeling, the latter considered "secondary" data. Two stochastic geostatistical techniques are explored for incorporating the structural proxies: cosimulation and local varying mean. With both the cosimulation and local varying mean methods, many equally likely temperature models (i.e., realizations) are produced, from which temperature probability profiles are calculated at candidate well locations. To aid in choosing between the candidate locations, two quantities summarize the temperature probabilities: Vprior and entropy. Vprior quantifies the likelihood for economic temperatures at each candidate location, whereas entropy identifies where new information has the most potential to reduce uncertainty. In general, the cosimulation realizations have smoother spatial structure, and extrapolate high temperatures at candidate locations that are located along the direction of the longest spatial correlation, which are down dip from existing temperature logs. The smooth realizations result in tight temperature probability profiles that are easier to interpret, but they have unrealistic temperature reversals in some locations because the cosimulation technique does not enforce a conductive geothermal gradient as a baseline (i.e., linearly increasing temperature with depth). The local varying mean results produce realizations with more realistic geothermal gradients, with temperatures increasing downward since a depth-temperature relationship is included. However, because they have much noisier spatial nature compared to cosimulation, it is harder to interpret the temperature probability profiles. The different local varying mean results allow the geologist to determine which proxy (e.g., dilation versus distance to fault termination) should be used given the specific geothermal system. In general, Vprior from local varying mean results identify locations that are close to high values for the structural proxies: areas with highe r probabilities for higher temperatures. The entropy results identify where uncertainty is greatest and therefore new drilling information could be most useful. Though these techniques provide useful information, even when applied to areas of sparse data, our comp arison of these two techniques demonstrates the need for new geothermal geostatistics techniques that combine the advantages of these two methods and that are tailored to the spatial uncertainty issues inherent in geothermal exploration.

3D temperature modeling↗
DOE OSTI2023

Growth interface study of CdTeSe crystals grown by the THM technique

The Traveling Heater Method (THM) is a widely accepted technique to grow high-quality detector grade CdTe and CdZnTe ingots, especially for X-ray and gamma-ray detector applications. Unlike melt-growth techniques, the growth interface for ingots produced by the THM technique consists of two different compounds, viz. the solidified region (just below the interface) consists of the compound to be grown (e.g., CdZnTe for CdZnTe growth), while the molten zone just above the growth interface consists of Te-rich CdZnTe. Thus, optimization of the growth parameters is critical to obtain a clean growth interface with the required shape and presence of minimal Te-rich inclusions. Here, in this study, CdTeSe ingots were grown employing the THM technique to investigate the growth interface. Both macroscopic and microscopic behavior of the interface were studied. The study revealed that a microscopically smooth growth interface can be achieved by optimizing the growth parameters, which is essential for obtaining high-quality, inclusion-free ingots.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

On-Demand Selection of the Latent Domain Orientation in Spray-Deposited Block Copolymer Thin Films

With their ability to self-assemble spontaneously into well-defined nanoscale morphologies, block copolymer (BCP) thin films are a versatile platform to fabricate functional nanomaterials. An important challenge to wider deployment of BCPs in nanofabrication is combining precise control over the nanoscale domain orientation in BCP assemblies with scalable deposition techniques that are applicable to large-area, curved, and flexible substrates. Here, in this study, we show that spray-deposited smooth films of a nominally disordered BCP exhibit latent orientations, which can be prescriptively selected by controlling solvent evaporation during spray casting. Subsequent solvent vapor annealing triggers assembly toward highly ordered cylindrical morphologies along the pathway determined by solvent evaporation in the prior spray deposition stage. Faster evaporation promotes assembly of vertically oriented cylinders spanning the entire film thickness (100–300 nm). In comparison, slow solvent evaporation permits intermicellar aggregation and incipient cylinder formation in solution, which induces horizontal cylinder assembly upon annealing. The evaporatively controlled latent orientation mechanism presented herein elucidates how nonequilibrium phenomena during casting govern successive self-assembly pathways and facilitates a versatile method to dictate the domain orientation of BCP thin films on demand on flexible and highly curved substrates or in distinct pattern areas on the same substrate.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Area-Preserving Mapping of 3D Carotid Ultrasound Images Using Density-Equalizing Reference Map

Carotid atherosclerosis is a focal disease at the bifurcations of the carotid artery. To quantitatively monitor the local changes in the vessel-wall-plus-plaque thickness (VWT) and compare the VWT distributions for different patients or for the same patients at different ultrasound scanning sessions, a mapping technique is required to adjust for the geometric variability of different carotid artery models. In this work, we propose a novel method called density-equalizing reference map (DERM) for mapping 3D carotid surfaces to a standardized 2D carotid template, with an emphasis on preserving the local geometry of the carotid surface by minimizing the local area distortion. The initial map was generated by a previously described arc-length scaling (ALS) mapping method, which projects a 3D carotid surface onto a 2D non-convex L-shaped domain. A smooth and area-preserving flattened map was subsequently constructed by deforming the ALS map using the proposed algorithm that combines the density-equalizing map and the reference map techniques. This combination allows, for the first time, one-to-one mapping from a 3D surface to a standardized non-convex planar domain in an area-preserving manner. Evaluations using 20 carotid surface models show that the proposed method reduced the area distortion of the flattening maps by over 80% as compared to the ALS mapping method.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

SURFACE FINISHING AND ELECTROLESS NICKEL PLATING OF ADDITIVELY MANUFACTURED (AM) METAL COMPONENTS

This study investigates the application of electroless nickel deposition on additively manufactured stainless steel samples. Current additive manufacturing (AM) technologies produce metal components with a rough surface. Rough surfaces generally exhibit fatigue characteristics, increasing the probability of initiating a crack or fracture to the printed part. For this reason, the direct use of as-produced parts in a finished product cannot be actualized, which presents a challenge. Post-processing of the AM parts is therefore required to smoothen the surface. This study analyzes chempolish (CP) and electropolish (EP) surface finishing techniques for post-processing AM stainless steel components CP has a great advantage in creating uniform, smooth surfaces regardless of size or part geometry EP creates an extremely smooth surface, which reduces the surface roughness to the sub-micrometer level. In this study, we also investigate nickel deposition on EP, CP, and as-built AM components using electroless nickel solutions. Electroless nickel plating is a method of alloy treatment designed to increase manufactured component's hardness and surface resistance to the unrelenting environment. The electroless nickel plating process is more straightforward than its counterpart electroplating.. We use low-phosphorus (2-5% P), medium-phosphorus (6-9% P), and high-phosphorus (10-13% P). These Ni deposition experiments were optimized using the L9 Taguchi design of experiments (TDOE), which compromises the prosperous content in the solution, surface finish, plane of the geometry, and bath temperature. The pre-and post-processed surface of the AM parts was characterized by KEYENCE Digital MicroscopeVHX-7000 and Phenom XL Desktop SEM. The experimental results show that electroless nickel deposition produces uniform Ni coating on the additively manufactured components up to 20 μm per hour. Mechanical properties of as-built and Ni coated AM samples were analyzed by applying a standard 10 N scratch test. Nickel coated AM samples were up to two times scratch resistant compared to the as-built samples. This study suggests electroless nickel plating is a robust viable option for surface hardening and finishing AM components for various applications and operating conditions.

Keywords: additive manufacturing, fatigue, chempol↗
DOE OSTI2020

Estimation of distributions via multilevel Monte Carlo with stratified sampling

We design and implement a novel algorithm for computing a multilevel Monte Carlo (MLMC) estimator of the joint cumulative distribution function (CDF) of a vector-valued quantity of interest in problems with random input parameters and initial conditions. Our approach combines MLMC with stratified sampling of the input sample space by replacing standard Monte Carlo at each level with stratified Monte Carlo initialized with proportionally allocated samples. We show that the resulting stratified MLMC (sMLMC) algorithm is more efficient than its standard MLMC counterpart due to the additional variance reduction provided by the stratification of the random parameter's domain, especially at the coarsest levels. Additional computational cost savings are obtained by smoothing the indicator function with a Gaussian kernel, which proves to be an efficient and robust alternative to recently developed polynomial-based techniques.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Enhancement of operational Flexibility of Power Plants Using IN740

Headers are crucial components within diverse industries, especially in the energy sector, as they enable the efficient transfer of fluids. The selection of materials for headers is determined by their specific applications; for example, Grade 91 and Grade 92 steels are commonly utilized. In our research, we recommend the adoption of INCONEL alloy 740 due to its exceptional robustness and heat-resistant characteristics. One critical parameter in header systems is the heat transfer coefficient, which directly influences the efficiency of heat exchange processes and can thereby impact the structural integrity of the headers. This coefficient is closely linked with factors such as the Nusselt number, which is influenced by fluid flow characteristics and thermal properties. The flow direction within headers, whether unidirectional or multidirectional—significantly affects the overall dynamics of heat transfer. This research focuses on exploring the behavior of headers, a specific pipeline system component, using ANSYS simulation software. The study aims to predict heat transfer and mechanical behavior within headers under various conditions through steady-state and transient simulations (parts 1 and 2 of the report). Key parameters such as heat transfer coefficient, velocity, and temperature are examined with the goal of optimizing header design. Part 3 of the report addresses the critical yet underexplored relationship between pressure drop and heat transfer coefficients in the transient flow regime within headers, specifically focusing on smooth horizontal circular tubes. Limited experimental work has been conducted in this area, prompting the need for comprehensive analysis. By leveraging machine learning techniques, this research aims to establish a correlation between pressure drop and heat transfer across various flow conditions, including laminar, transient, quasi-turbulent, and turbulent regimes. The data utilized for this analysis were meticulously gathered from existing literature, capturing simultaneous measurements of pressure drops and heat transfer. Part 4: In the context of power plants, header pipes are essential components that significantly influence system performance by facilitating the collection and distribution of steam. This report highlights the critical role of header pipes in enhancing reliability, efficiency, and overall power plant performance. A key aspect of this investigation is shape optimization, which aims to maximize performance while minimizing material usage. By focusing on shape optimization, this research contributes to improved efficiency and a reduced environmental footprint for power plant installations. The methodology developed in this study emphasizes optimizing header shapes to decrease reliance on expensive alloy materials and lower maintenance costs. Furthermore, a case study was conducted using a header from an operational power plant to validate the proposed optimization techniques. Finally, part 5 addresses the challenges associated with flexible operations in boiler systems, the study outlines several strategies for enhancing the durability and reliability of steam headers. Key approaches include material selection, which involves utilizing advanced materials with superior high-temperature properties and enhanced fatigue resistance to extend the lifespan of steam headers. Design modifications are also recommended, focusing on implementing changes that mitigate thermal stress and cyclic loading to reduce the likelihood of failures under varying operating conditions. Additionally, the study emphasizes the importance of regular inspection and monitoring by establishing rigorous protocols to detect early signs of damage, allowing for timely maintenance and minimizing the risks of catastrophic failures. Furthermore, operational guidelines are developed to minimize the frequency and severity of thermal transients, ensuring stable and efficient operations. Collectively, these strategies provide a robust framework for overcoming the unique challenges posed by flexible operation in boiler systems, ultimately contributing to improved reliability and performance in power plant operations. Through this comprehensive approach, the study not only enhances the understanding of pressure drop and heat transfer relationships but also promotes advancements in design and operation that will benefit the entire power generation industry.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Pick-and-Place Transfer of Arbitrary-Metal Electrodes for van der Waals Device Fabrication

Van der Waals electrode integration is a promising strategy to create nearly perfect interfaces between metals and 2D materials, with advantages such as eliminating Fermi-level pinning and reducing contact resistance. However, the lack of a simple, generalizable pick-and-place transfer technology has greatly hampered the wide use of this technique. Here, we demonstrate the pick-and-place transfer of prefabricated electrodes from reusable polished hydrogenated diamond substrates without the use of any sacrificial layers due to the inherent low-energy and dangling-bond-free nature of the hydrogenated diamond surface. The technique enables transfer of arbitrary-metal electrodes and an electrode array, as demonstrated by successful transfer of eight different elemental metals with work functions ranging from 4.22 to 5.65 eV. We also demonstrate the electrode array transfer for large-scale device fabrication. The mechanical transfer of metal electrodes from diamond to van der Waals materials creates atomically smooth interfaces with no interstitial impurities or disorder, as observed with cross-section high-resolution transmission electron microscopy and energy-dispersive X-ray spectroscopy. As a demonstration of its device application, we use the diamond transfer technique to create metal contacts to monolayer transition metal dichalcogenide semiconductors with high-work-function Pd, low-work-function Ti, and semimetal Bi to create n- and p-type field-effect transistors with low Schottky barrier heights. We also extend this technology to air-sensitive materials (trilayer 1T’ WTe 2 ) and other applications such as ambipolar transistors, Schottky diodes, and optoelectronics. This highly reliable and reproducible technology paves the way for new device architectures and high-performance devices.

2D materials↗
DOE OSTI2023

Regulating Li Nucleation and Growth Heterogeneities via Near-Surface Lithium-Ion Irrigation for Stable Anode-Less Lithium Metal Batteries

The inhomogeneous nucleation and growth of Li dendrite combined with the spontaneous side reactions with the electrolytes dramatically challenge the stability and safety of Li metal anode (LMA). Despite tremendous endeavors, current success relies on the use of significant excess of Li to compensate the loss of active Li during cycling. Herein, a near-surface Li + irrigation strategy is developed to regulate the inhomogeneous Li deposition behavior and suppress the consequent side reactions under limited Li excess condition. The conformal polypyrrole (PPy) coating layer on Cu surface via oxidative chemical vapor deposition technique can induce the migration of Li + to the interregional space between PPy and Cu, creating a near-surface Li + -rich region to smooth diffusion of ion flux and uniform the deposition. Moreover, as evidenced by multiscale characterizations including synchrotron high-energy X-ray diffraction scanning, a robust N-rich solid-electrolyte interface (SEI) is formed on the PPy skeleton to effectively suppress the undesired SEI formation/dissolution process. Strikingly, stable Li metal cycling performance under a high areal capacity of 10 mAh cm -2 at 2.0 mA cm -2 with merely 0.5 × Li excess is achieved. The findings not only resolve the long-standing poor LMA stability/safety issues, but also deepen the mechanism understanding of Li deposition process.

25 ENERGY STORAGE↗
DOE OSTI2021

An Enhanced Virtual Crack Closure Technique for Stress Intensity Factor Calculation along Arbitrary Crack Fronts and the Application in Hydraulic Fracturing Simulation

The virtual crack closure technique (VCCT) is widely used for calculating energy release rates along crack fronts and modeling the propagation of cracks in solid materials. Although the VCCT formulation for smooth crack fronts has been sufficiently addressed in the literature, the application of VCCT to a nonsmoothed crack front with sharp corners warrants further investigation. In this study, we describe an enhanced VCCT to calculate energy release rates and stress intensity factors for cracks with arbitrary shapes in 3D domains discretized on structured grids. The formulations of the enhanced VCCT were developed and implemented into a multiphysics simulation environment capable of simulating crack propagation in the framework of linear elastic fracture mechanics. Comparisons with existing analytical/numerical solutions and other VCCT approaches were performed to verify the enhanced VCCT in terms of SIF calculation along nonsmoothed crack fronts. We then applied the enhanced VCCT to a hydraulically driven penny-shaped fracture problem to further demonstrate its capability to simulate nonsmoothed fracture propagation.

02 PETROLEUM↗