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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

NiAl–MoO 2 S 2 Nanoparticles: Structural Evolution and Mechanistic Insights into High-Performance Selenium Oxyanion Removal across Diverse pH Conditions

Advancing sorbent materials for the selective removal of toxic oxyanions from water requires synthetic control, tunable chemistry, and an atomic-level understanding of structure–function relationships. Here, we report the synthesis and detailed characterization of NiAl–MoO 2 S 2 , a novel layered double hydroxide (LDH) nanomaterial designed for the efficient sequestration of selenium oxoanions (SeO 3 2– and SeO 4 2– ) from complex aqueous environments. The material is synthesized through a room-temperature ion-exchange process, wherein interlayer NO 3 – anions in NiAl–LDH are replaced with MoO 2 S 2 2– clusters, forming high-surface-area, flower-like nanoparticles. Comprehensive structural analysis using the synchrotron X-ray pair distribution function, X-ray absorption spectroscopy, and X-ray photoelectron spectroscopy reveals a distinct chemical transformation of intercalated [MoO 2 S 2 ] 2– into [Mo 2 O 2 S 6 ] 2– -like clusters, generating redox-active interlayers that drive selenium capture. This tailored interfacial chemistry underpins the material’s exceptional sorption performance, achieving distribution coefficients (K d ) ≥ 10 6 mL/g and maximum capacities of 343 mg/g for SeO 4 2– and 514 mg/g for SeO 3 2– , outperforming state-of-the-art inorganic sorbents. Importantly, NiAl–MoO 2 S 2 maintains high selectivity and capacity across acidic, neutral, and alkaline pH, efficiently removing selenium from ppm to sub-10 ppb trace levels, even in the presence of competing ions typical of natural and industrial waters. The selenium uptake proceeds via reductive precipitation coupled with the oxidation of molybdenum and sulfide within the LDH framework. This study highlights the power of strategic synthetic modification and interlayer functionalization in LDHs to unlock new structural motifs and redox chemistries, offering a scalable route to advanced materials for environmental remediation.

Adsorption↗
DOE OSTI2024

Bulk flow and correlation measurements at LHCb

Particle correlations are a powerful tool to study the properties of the bulk nuclear matter produced in relativistic heavy ion collisions. The momentum correlations between identical particles originating from the same particle-emitting source, referred to as the Bose-Einstein correlations, measure scales that are related to the geometrical size of the source. The two-particle azimuthal angular correlations measure the spatial anisotropy of produced particles, providing information on collective phenomena arising in the dense nuclear medium. This contribution will discuss new LHCb measurements of Bose- Einstein correlations and, for the first time, the collective flow coefficients in the far forward rapidity region.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Updated Thermofluid Performance of the Simplified Flat Variant of the HEMJ

Our group has recently developed and studied “finger”-type divertors that are a simplified version of the helium-cooled modular divertor with multiple jets (HEMJ) using coupled computational fluid dynamics and thermal stress simulations. Such a simplified geometry could reduce complexity and cost given the large number of fingers required to cover the total divertor target area. Previous experimental studies for this simplified flat design reported lower heat transfer coefficients and higher pressure drops than the HEMJ, contrary to numerical predictions. Subsequent measurements determined that the original test section had significant dimensional variations in the jet exit holes. A new test section was therefore manufactured and tested in the Georgia Tech (GT) helium loop. The experimental results presented here for this test section at maximum heat flux of 7.1 MW/m 2 are in good agreement with numerical predictions. Correlations developed from these experimental data are extrapolated to predict the maximum heat flux that can be accommodated by the flat design and the coolant pumping power requirements under prototypical conditions. Lastly, numerical simulations are used to estimate the sensitivity of the flat design to geometric variations typical of manufacturing tolerances and variations in the gap width.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Robust and Spectrally Selective Aerogels for Solar Receivers

The development of next generation concentrated solar thermal (CST) plants requires solar receivers to reach high temperatures (> 600°C) while minimizing costs. Efficiently generating such high temperatures using a line-focusing collector and an air-stable receiver has the potential to change the current CSP paradigm because it would: (1) result in large improvements in system-level efficiency of line-focusing systems by enabling the use of high-efficiency supercritical CO 2 power cycles; (2) decrease the LCOE of line-focusing systems to meet SETO 2030 goals; (3) maintain performance over the lifetime of the CSP plant by avoiding issues related to breakdown of vacuum. The use of aerogels as transparent insulating materials (TIMs) in solar thermal receivers has the potential to enable such improvements. Specifically, aerogels can be placed in front of a black (or partially selective) high-temperature absorber to allow sunlight to transmit to the absorber but block heat from escaping. These materials can improve the efficiency and simplify the complexity of thermal transport systems by enabling operation at moderate or no vacuum levels. These potential benefits have been explicitly identified by SETO as ‘high impact’. The use of mesoporous silica as a TIM has already led to large improvements in solar collection efficiency. Nevertheless, these materials inherently lose structural integrity and the ability to suppress radiation losses at high temperatures. Here, we address these challenges by leveraging 1-cycle atomic layer deposition of aluminum oxide onto a silica aerogel to form a thermally stable interfacial layer that is transparent to sunlight but broadly absorbs in the mid-infrared. This interfacial absorption results in a two-fold reduction in measured heat losses from an absorber at 700°C and solar thermal efficiency of 81% at 700°C under 60 Suns, based on measurements of heat loss and solar transmittance. Extended-duration heat treatment reveals that the multicomponent aerogel is stable at high temperatures relative to a silica aerogel. Furthermore, we experimentally demonstrate the concept of using infrared plasmon resonances to selectively enhance the thermal absorption coefficient of TIMs in order to strongly suppress thermal radiative losses at high temperatures. We term this mechanism plasmon-enhanced greenhouse selectivity (PEGS). Unlike silica aerogels, where much of the IR absorption is lost at high temperatures, local surface plasmon resonances (LSPRs) in doped oxide nanoparticles overlap a significant portion of the blackbody spectrum and are maintained at high temperatures. Overall, this work paves the way for next-generation solar thermal energy using thermally robust transparent insulating materials.

14 SOLAR ENERGY↗
DOE OSTI2020

Robust and Spectrally Selective Aerogels for Solar Receivers (Final Technical Report)

The development of next generation concentrated solar thermal (CST) plants requires solar receivers to reach high temperatures (> 600°C) while minimizing costs. Efficiently generating such high temperatures using a line-focusing collector and an air-stable receiver has the potential to change the current CSP paradigm because it would: (1) result in large improvements in system-level efficiency of line-focusing systems by enabling the use of high-efficiency supercritical CO2 power cycles; (2) decrease the LCOE of line-focusing systems to meet SETO 2030 goals; (3) maintain performance over the lifetime of the CSP plant by avoiding issues related to breakdown of vacuum. The use of aerogels as transparent insulating materials (TIMs) in solar thermal receivers has the potential to enable such improvements. Specifically, aerogels can be placed in front of a black (or partially selective) high-temperature absorber to allow sunlight to transmit to the absorber but block heat from escaping. These materials can improve the efficiency and simplify the complexity of thermal transport systems by enabling operation at moderate or no vacuum levels. These potential benefits have been explicitly identified by SETO as ‘high impact’. The use of mesoporous silica as a TIM has already led to large improvements in solar collection efficiency. Nevertheless, these materials inherently lose structural integrity and the ability to suppress radiation losses at high temperatures. Here, we address these challenges by leveraging 1-cycle atomic layer deposition of aluminum oxide onto a silica aerogel to form a thermally stable interfacial layer that is transparent to sunlight but broadly absorbs in the mid-infrared. This interfacial absorption results in a two-fold reduction in measured heat losses from an absorber at 700°C and solar thermal efficiency of 81% at 700°C under 60 Suns, based on measurements of heat loss and solar transmittance. Extended-duration heat treatment reveals that the multicomponent aerogel is stable at high temperatures relative to a silica aerogel. Furthermore, we experimentally demonstrate the concept of using infrared plasmon resonances to selectively enhance the thermal absorption coefficient of TIMs in order to strongly suppress thermal radiative losses at high temperatures. We term this mechanism plasmon-enhanced greenhouse selectivity (PEGS). Unlike silica aerogels, where much of the IR absorption is lost at high temperatures, local surface plasmon resonances (LSPRs) in doped oxide nanoparticles overlap a significant portion of the blackbody spectrum and are maintained at high temperatures. Overall, this work paves the way for next-generation solar thermal energy using thermally robust transparent insulating materials.

14 SOLAR ENERGY↗
DOE OSTI2020

Piezoresponse amplitude and phase quantified for electromechanical characterization

Piezoresponse force microscopy (PFM) is a powerful characterization technique to readily image and manipulate the ferroelectric domains. PFM gives an insight into the strength of local piezoelectric coupling and polarization direction through PFM amplitude and phase, respectively. Converting measured arbitrary units into units of effective piezoelectric constant remains a challenge, and insufficient methods are often used. While most quantification efforts have been spent on quantifying the PFM amplitude signal, little attention has been given to the PFM phase, which is often arbitrarily adjusted to fit expectations. This is problematic when investigating materials with unknown or negative sign of the probed effective electrostrictive coefficient or strong frequency dispersion of electromechanical responses, because assumptions about the PFM phase cannot be reliably made. The PFM phase can, however, provide important information on the polarization orientation and the sign of the effective electrostrictive coefficient probed by PFM. Most notably, the orientation of the PFM hysteresis loop is determined by the PFM phase. Moreover, when presenting PFM data as a combined signal, the resulting response can be artificially lowered or asymmetric if the phase data have not been correctly processed. Here, we explain the PFM amplitude quantification process and demonstrate a path to identify the phase offset required to extract correct meaning from the PFM phase data. We explore different sources of phase offsets including the experimental setup, instrumental contributions, and data analysis. We discuss the physical working principles of PFM and develop a strategy to extract physical meaning from the PFM amplitude and phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

The crystal structure of TlMgCl 3 from 290 K to 725 K

The title compound, thallium magnesium trichloride, has been identified as a scintillator with both moderate gamma-stopping power and moderate light yield. Knowledge of its crystal structure is needed for further development. This work determines the crystal structure of TlMgCl 3 to be hexa­gonal P6 3 /mmc (No. 194) and isostructural with RbMgCl 3 , contrary to previously reported data. This structure was obtained by single-crystal X-ray diffraction and was further confirmed by neutron diffraction measurements. Extending neutron diffraction measurements to high temperature, the data show that TlMgCl 3 maintains this crystal structure from 290 K up through 725 K, approaching the melting point of 770 K. Anisotropic thermal expansion coefficients increase over this temperature range, from 31 to 38 × 10 –6 K –1 along the a axis and from 19 to 34 × 10 –6 K –1 along the c axis.

36 MATERIALS SCIENCE↗
DOE OSTI2022

GLUE Code: A framework handling communication and interfaces between scales

Many scientific applications are inherently multiscale in nature. Such complex physical phenomena often require simultaneous execution and coordination of simulations spanning multiple time and length scales. This is possible by combining expensive small-scale simulations (such as molecular dynamics simulations) with larger scale simulations (such continuum limit/hydro solvers) to allow for considerably larger systems using task and data parallelism. However, the granularity of the tasks can be very large and often leads to load imbalance. Traditionally, we use approximations to streamline the computation of the more costly interactions and this introduces trade-offs between simulation cost and accuracy. In recent years, the available computational power and the advances in machine learning have made computing these scale-bridging interactions and multiscale simulations more feasible. One driving application has been plasma modeling in inertial confinement fusion (ICF), which is fundamentally multiscale in nature. This requires deep understanding of how to extrapolate microscopic information into macroscopically relevant scales. For example, in ICF one needs an accurate understanding of the connection between experimental observables and the underlying microphysics. The properties of the larger scales are often affected by the microscale behavior incorporated usually into the equations of state and ionic and electronic transport coefficients (Liboff, 1959; Rinderknecht et al., 2014; Rosenberg et al., 2015; Ross et al., 2017). Instead of incorporating this information using reliable molecular dynamics (MD) simulations, one often needs to use theoretical models, due to the inability of MD to reach engineering scales (Glosli et al., 2007; Marinak et al., 1998). One approach to resolve this issue is by coupling two MD simulations of different scales via force interpolation, e.g., the AdResS method (Krekeler et al., 2018; Nagarajan et al., 2013). Another approach, which we will pursue in the scope of this work, is by enabling scale bridging between MD simulations and meso/macro-scale models through the development and support of application programming interfaces that these different applications can interact through.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Cloud based tool for analysis of chemical kinetic mechanisms

The size and complexity of chemical kinetic models used to simulate combustion of hydrocarbon fuels continue to increase with our improved understanding of the underlying physical mechanisms, along with the improved ability to utilize such models as the result of increased computational power and efficiency. As mechanisms grow beyond thousands of species and tens of thousands of reactions, it becomes increasingly difficult to manually check for errors and physical inconsistencies. In this work, we present several automated methods to check for such issues in the specification of chemical reaction models. First, we demonstrate how discontinuities in thermodynamic data can cause simulation difficulties manifested as long wall-clock times and convergence failures. To correct this type of problem, we describe an automated method for refitting thermodynamic parameters. We also outline several methods to check the timescales of reaction rate coefficients to ensure physical consistency. All the methods are made available through a web-based tool (https://combustiontools.llnl.gov) intended to aid mechanism developers and users to improve the accuracy and performance of fuel models used by the combustion community.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Autonomous sputter synthesis of thin film nitrides with composition controlled by Bayesian optimization of optical plasma emission

Autonomous experimentation has emerged as an efficient approach to accelerate the pace of material discovery. Although instruments for autonomous synthesis have become popular in molecular and polymer science, solution processing of hybrid materials, and nanoparticles, examples of autonomous tools for physical vapor deposition are scarce yet important for the semiconductor industry. Here, we report the design and implementation of an autonomous workflow for sputter deposition of thin films with controlled composition, leveraging a highly automated sputtering reactor custom-controlled by Python, optical emission spectroscopy (OES), and a Bayesian optimization algorithm. We modeled film composition, measured by x-ray fluorescence, as a linear function of plasma emission lines monitored during co-sputtering from elemental Zn and Ti targets in an N 2 and Ar atmosphere. A Bayesian control algorithm, informed by OES, navigates the space of sputtering power to fabricate films with user-defined compositions by minimizing the absolute error between desired and measured optical emission signals. We validated our approach by autonomously fabricating Zn x Ti 1-x N y films that deviate from the targeted cation composition by a relative ±3.5%, even for 15 nm thin films, demonstrating that the proposed approach can reliably synthesize thin films with a specific composition and minimal human interference. Moreover, the proposed method can be extended to more difficult synthesis experiments where plasma intensity lines depend non-linearly on pressure, or the elemental sticking coefficients strongly depend on the substrate temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2024

In situ electric-field control of ferromagnetic resonance in the low-loss organic-based ferrimagnet V[TCNE] x ∼2

We demonstrate indirect electric-field control of ferromagnetic resonance (FMR) in devices that integrate the low-loss, molecule-based, room-temperature ferrimagnet vanadium tetracyanoethylene (V[TCNE]x∼2) mechanically coupled to PMN-PT piezoelectric transducers. Upon straining the V[TCNE]x films, the FMR frequency is tuned by more than 6 times the resonant linewidth with no change in Gilbert damping for samples with α = 6.5 × 10−5. We show this tuning effect is due to a strain-dependent magnetic anisotropy in the films and find the magnetoelastic coefficient |λs| ∼ (1–4.4) ppm, backed by theoretical predictions from density-functional theory calculations and magnetoelastic theory. Noting the rapidly expanding application space for strain-tuned FMR, we define a new metric for magnetostrictive materials, magnetostrictive agility, given by the ratio of the magnetoelastic coefficient to the FMR linewidth. This agility allows for a direct comparison between magnetostrictive materials in terms of their comparative efficacy for magnetoelectric applications requiring ultra-low loss magnetic resonance modulated by strain. With this metric, we show V[TCNE]x is competitive with other magnetostrictive materials, including YIG and Terfenol-D. This combination of ultra-narrow linewidth and magnetostriction, in a system that can be directly integrated into functional devices without requiring heterogeneous integration in a thin film geometry, promises unprecedented functionality for electric-field tuned microwave devices ranging from low-power, compact filters and circulators to emerging applications in quantum information science and technology.

Materials Science↗
DOE OSTI2021

Dynamic and weak electric double layers in ultrathin nanopores

The unique properties of aqueous electrolytes in ultrathin nanopores have drawn a great deal of attention in a variety of applications, such as power generation, water desalination, and disease diagnosis. Inside the nanopore, at the interface, properties of ions differ from those predicted by the classical ionic layering models (e.g., Gouy–Chapman electric double layer) when the thickness of the nanopore approaches the size of a single atom (e.g., nanopores in a single-layer graphene membrane). Here, using extensive molecular dynamics simulations, the structure and dynamics of aqueous ions inside nanopores are studied for different thicknesses, diameters, and surface charge densities of carbon-based nanopores [ultrathin graphene and finite-thickness carbon nanotubes (CNTs)]. The ion concentration and diffusion coefficient in ultrathin nanopores show no indication of the formation of a Stern layer (an immobile counter-ionic layer) as the counter-ions and nanopore atoms are weakly correlated in time compared to the strong correlation observed in thick nanopores. The weak correlation observed in ultrathin nanopores is indicative of a weak adsorption of counter-ions onto the surface compared to that of thick pores. The vanishing counter-ion adsorption (ion–wall correlation) in ultrathin nanopores leads to several orders of magnitude shorter ionic residence times (picoseconds) compared to the residence times in thick CNTs (seconds). The results of this study will help better understand the structure and dynamics of aqueous ions in ultrathin nanopores.

2D materials↗
DOE OSTI2025

Hydrophobic Carbon Nanosheets as Passivation Layer for Perovskite Solar Cells with High Efficiency and Stability (Final Technical Report)

Hybrid organic-inorganic metal halide perovskites have continually demonstrated competitive advantages for photovoltaic applications due to their high light absorption coefficient, tunable bandgaps, ambipolar charge mobility and high tolerance of defects. However, there are many challenges yet to overcome to bring this technology to the market. For instance, bridging the ‘scaling gap’ and transitioning PSCs from a lab scale to an industrial scale is a serious challenge. This project developed a high stability and inexpensive perovskite solar cell (PSC) by incorporating hydrophobic carbon nanosheets as counter electrodes (CEs). We demonstrated that the hydrogenated carbon nanosheets with tunable hydrophobic properties as CEs can improve life-time stability of PSCs in operating conditions (i.e. humid air) while achieving impressive power conversion efficiency (PCE).

14 SOLAR ENERGY↗
DOE OSTI2020

Validation of the High-Resolution Salish Sea Tidal Hydrodynamic Model

In this study, a tidal hydrodynamic model was developed and validated to simulate tidal currents in Puget Sound, Washington, to support tidal energy resource characterization using the unstructured-grid, Finite Volume Community Ocean Model (FVCOM). The Salish Sea tidal hydrodynamic model was driven by tides along two open boundaries at the entrance of the Strait of Juan de Fuca and north end of Georgia Strait, and river flows from 19 major rivers in the Salish Sea. To simulate the tidal current in Puget Sound, a high-resolution model grid is required to accurately represent the complex coastlines and bathymetry. The spatial resolution of the model grid varies from ~10 m near river boundaries and ~30 m in small tidal channels and estuaries to near 1000 m inside Georgia Strait and at the open boundaries. Model validation was carried out by comparing simulated and observed water levels at 12 tidal stations and currents at 135 Acoustic Doppler Current Profiler stations in the model domain. A set of model performance metrics, including root mean square error, scatter index, bias, and linear correlation coefficient, were used to quantify the model skills in simulating the tidal hydrodynamics in Puget Sound. Error statistics showed an overall good agreement between simulated and observed tidal elevations and currents, which demonstrated that the Puget Sound tidal model can be used to accurately characterize the tidal stream energy resource in Puget Sound.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

SCALE Modeling of the Fast Spectrum Heat Pipe Reactor

As part of the severe accident analysis collaboration with Sandia National Laboratories (SNL) and the Nuclear Regulatory Commission (NRC), SCALE models were developed for a fast-spectrum heat pipe reactor. These models were based on the Idaho National Laboratory (INL) Design A concept, which is an alternative design to the Los Alamos National Laboratory (LANL) Special Purpose Reactor (SPR), also known as the Megapower reactor. The model contains 1,134 heat pipes, surrounded by hexagonal fuel elements, with a potassium working fluid; the fuel is UO 2 with 19.75 wt% 235 U enrichment. The model contains axial beryllium oxide (BeO) reflectors above and below the active fuel region along with a radial alumina reflector containing 12 B 4 C control drums. The center of the core is left unfueled to make room for two shutdown control rods, one annular and one solid. The active region of the core was discretized into twenty axial and five radial zones to analyze spatial variations in power and burnup. Infinite lattice unit cell sensitivity studies were used to perform verification between the SCALE and INL models. The eigenvalue results agreed well with the reported results to within roughly 50 percent mille (pcm). Full-core model verification was performed by analyzing system eigenvalues with differing configurations of control drum and shutdown rod positions. These full core results all had eigenvalue differences less than 310 pcm. Control drum and shutdown rod worths were also compared, with differences of 3.2% or less. Using the verified model, the isotopic inventory and decay heat, as well as temperature feedback coefficients, were calculated and provided to SNL as input to the MELCOR severe accident code to analyze potential releases from this class of reactor. The results of the MELCOR analysis are provided in a different report.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Physics-Informed and Data-Driven Prediction of Residual Stress in Three-Dimensional Machining

Efficient and reliable prediction of machining-induced residual stress (RS) is a key requirement for truly integrated computational materials engineering (ICME). Currently available process modeling approaches, including empirical, analytical, and numerical methodologies lack predictive power and require substantial calibration and validation data. Moreover, most model-based approaches consider only two-dimensional (2D) (i.e., orthogonal), cutting processes. Meanwhile, industrial processes such as milling, turning, and drilling are inherently three-dimensional (3D). The present work attempts to bridge the gap between 2D and 3D through careful consideration of the process physics, including geometric, kinematic, and size-effect constraints to realize robust prediction of how RS develops in 3D machining. Using a novel in-situ experimental technique and digital image correlation (DIC) to determine equivalent Hertzian contact widths, contact pressures, and friction coefficients, the proposed methodology leverages a discretized conversion algorithm that includes multi-pass shakedown effects. This paper presents a semi-analytical model to predict machining-induced RS in 3D turning operations, which are used representatively for 3D processes more generally. Rather than follow a ‘brute force’ 3D FEM approach or conduct countless experiments to train a purely data-driven machine learning algorithm, the proposed approach builds on previous 2D modeling work. Through careful consideration of the process physics, including complex geometry/kinematic considerations of 3D turning, the authors demonstrated an experimentally calibrated approach, as well as validation based on published RS data. Model predictions and previously published measurement data of RS depth profiles for turning of Inconel 718 were compared for a range of process parameters. Correlation between the proposed 3D model and validation data was found to be within the margin of experimental error for most conditions. The proposed model appears to capture the overall behavior of 3D RS depth profiles with acceptable accuracy, particularly the key metrics of near-surface stress, peak stress magnitude and location, as well as overall stress profile depth. This report presents a physics-informed, data-driven approach for efficient calibration of a 2D model for machining-induced RS through DIC analysis of in-situ characterized subsurface displacement fields.

42 ENGINEERING↗
DOE OSTI2022

Neutron tomography of porous aluminum electrodes used in electrocoagulation of groundwater

In this work, neutron computed tomography (CT) is employed to investigate the dissolution of porous aluminum electrodes during electrocoagulation (EC). Porous electrodes were chosen in efforts to reduce electric power requirements by using larger surface-area electrodes, having both inner and outer surface, for the EC process. Neutron CT allowed 3D reconstruction of the porous electrodes, and image analysis provided the volume of each electrode vs. thickness, which can indicate whether the inner surface is effectively involved in EC reactions. For the anode, the volume decreased uniformly throughout the thickness of the electrode, indicating that both the outer and inner surface participated in electrochemical dissolution, while the volume of the cathode increased uniformly vs. thickness, indicating deposition of material on both the outer and inner surface. The attenuation coefficient vs. thickness, increased for both anode and cathode, indicating surface chemistry changes. For the anode, the attenuation coefficient increased slightly but uniformly, probably due to aluminum oxide formation on the surface of the anode. For the cathode, the attenuation coefficient increased more than for the anode and nonuniformly. The higher increase in the attenuation coefficient for the cathode is due to precipitation of aluminum hydroxide on the electrode surface, which added hydrogen. Image analysis also showed that, although the attenuation coefficient increased throughout the thickness of the electrode, most of the hydroxide deposition occurred on the outer surface. Energy analysis showed that porous electrodes can be used to reduce process energy requirements by as much as 4 times compared to solid electrodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Single crystal cathodes enabling high-performance all-solid-state lithium-ion batteries

All-solid-state lithium-ion batteries (ASSLIBs) are receiving significant attention owing to their improved safety and energy density over liquid counterparts. However, single-crystal cathodes have never been investigated in ASSLIBs. In this work, single-crystal Li(Ni 0.5 Mn 0.3 Co 0.2 )O 2 (SC-NMC532) is used as the cathode material for ASSLIBs, which exhibits 6~14 times higher Li + diffusion coefficient than polycrystalline Li(Ni 0.5 Mn 0.3 Co 0.2 )O 2 (PC-NMC532). As a result, SC-NMC532 exhibits an initial specific capacity of 156.4 mAh.g -1 while PC-NMC532 shows an initial capacity of only 127.5 mAh.g -1 . After 150 cycles, SC-NMC532 retains the capacity of 94.5 mAh.g -1 . More impressively, under a high current density of 1.3 mA.cm -2 , SC-NMC532 exhibits a capacity of 82 mAh.g -1 , much higher than that of PC-NMC532 (2.1 mAh.g -1 ). This work demonstrates that single-crystal NMC cathodes could enable both high power density and high energy density of ASSLIBs.

25 ENERGY STORAGE↗