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Anion-dependent phase behavior of methylimidazolium-based ionic liquids mixed with water: Correlation between local molecular structure and mesoscale behaviors

The mesoscopic phase behavior of decylmethylimidazolium (C 10 mim) ionic liquids (ILs) bearing three monovalent anions—thiocyanate (SCN − ), nitrate (NO 3 − ), and chloride (Cl − )—mixed with water at relatively high IL contents (50–95 wt%) was investigated. Small-angle and wide-angle X-ray scattering (SAXS/WAXS) were employed to follow the evolution of both local and mesoscale structures across this composition range. In the absence of water, C 10 mimSCN and C 10 mimCl behaved as disordered liquids, whereas C 10 mimNO 3 spontaneously formed a hexagonally ordered cylindrical mesophase and displayed a sticky-solid macroscopic appearance. Upon addition of water, C 10 mimSCN remained a viscous liquid and only weakly ordered lamellar domains were observed. This limited ordering is attributed to the lack of hydrogen bonding and weak interaction energy between SCN − anions and C 10 mim + cations. In contrast, the trigonal-planar NO 3 − and point-like Cl − anions promoted the formation of well-defined hexagonal mesophases up to 35–45 wt% water. The formation of hydrogen bonding of the two anions with imidazolium ring protons likely enabled the creation of compact ion clusters that effectively exclude water molecules from the immediate vicinity of the IL aggregates. These findings demonstrate that the interaction energy between ion pairs dictate IL-water interactions and therefore control the transition from disordered liquids to ordered mesophases in IL/water mixtures with high IL contents. In conclusion, the combined SAXS/WAXS analysis reveals a correlation between local intermolecular structure and the emergence of mesoscopic order, providing a systematic framework for tailoring mesoscale structures in alkylimidazolium-based IL/water systems.

36 MATERIALS SCIENCE

Modeling for Battery Prognostics

For any battery-powered vehicles (be it unmanned aerial vehicles, small passenger aircraft, or assets in exoplanetary operations) to operate at maximum efficiency and reliability, it is critical to monitor battery health as well performance and to predict end of discharge (EOD) and end of useful life (EOL). To fulfil these needs, it is important to capture the battery's inherent characteristics as well as operational knowledge in the form of models that can be used by monitoring, diagnostic, and prognostic algorithms. Several battery modeling methodologies have been developed in last few years as the understanding of underlying electrochemical mechanics has been advancing. The models can generally be classified as empirical models, electrochemical engineering models, multi-physics models, and molecular/atomist. Empirical models are based on fitting certain functions to past experimental data, without making use of any physicochemical principles. Electrical circuit equivalent models are an example of such empirical models. Electrochemical engineering models are typically continuum models that include electrochemical kinetics and transport phenomena. Each model has its advantages and disadvantages. The former type of model has the advantage of being computationally efficient, but has limited accuracy and robustness, due to the approximations used in developed model, and as a result of such approximations, cannot represent aging well. The latter type of model has the advantage of being very accurate, but is often computationally inefficient, having to solve complex sets of partial differential equations, and thus not suited well for online prognostic applications. In addition both multi-physics and atomist models are computationally expensive hence are even less suited to online application An electrochemistry-based model of Li-ion batteries has been developed, that captures crucial electrochemical processes, captures effects of aging, is computationally efficient, and is of suitable accuracy for reliable EOD prediction in a variety of operational profiles. The model can be considered an electrochemical engineering model, but unlike most such models found in the literature, certain approximations are done that allow to retain computational efficiency for online implementation of the model. Although the focus here is on Li-ion batteries, the model is quite general and can be applied to different chemistries through a change of model parameter values. Progress on model development, providing model validation results and EOD prediction results is being presented.

Prognostics

Mechanics of Preloaded Bolt Tensile Loading With Focus on Load Introduction Factor

The bolt tensile and joint separation loads are directly influenced by the locations at which the external loads enter the clamped members of a preloaded bolted joint (PBJ) and the associated load-paths through the joint. This physical load introduction mechanism affecting the bolt tensile loading is typically represented in the bolt tensile load equation, in part, by a load introduction factor (LIF), which was shown by H.M. Lee of Marshall Spaceflight Center to be a natural product of the bolt tensile load equation using a linear spring stiffness model. This LIF, being a function of load-path stiffness, has subsequently been denoted as the stiffness-based LIF (SBLIF), providing a framework to calculate the LIF using whatever load-path stiffness approximations are appropriate. Expanding upon the work of Lee, it is shown that the SBLIF and the joint stiffness factor are functions of the stiffnesses of the same load-paths and regions within a PBJ, and thus they should not be treated as independent variables. Mathematical expressions for the SBLIF are presented. Comparisons are shown between the analytically calculated SBLIF, the analytically calculated geometric LIF (GLIF), which is a simple clamped-member thickness ratio, the experimentally derived LIF, and the LIF determined by finite element analysis (FEA). Using experiment and FEA as a benchmark, the SBLIF, using traditional load-path stiffness approximations, enables a more accurate prediction of bolt tensile loading than the GLIF, although it can be unconservative near joint separation. The GLIF generally attributes more of the externally applied tensile load to the bolt than does the SBLIF, potentially resulting in heavier and/or more costly bolted joints. Mathematical relationships between the SBLIF and the GLIF are developed. Supplemental material is provided in the appendixes where the historical practice of using the joint compressive stiffness in place of the joint tensile stiffness is evaluated. The appendixes include step-by-step examples demonstrating the calculation of the SBLIF using traditional stiffness approximations and conclude with the development of the joint diagram in terms of the SBLIF, culminating into formulas for the key features of a joint diagram, which is useful for programming.

Load Path

Hybrid Bio-Based Composites: Enabling Cellulose Nanofiber (CNF) Incorporation into Composites via Macroscale Natural Fiber Carriers

Cellulose nanofibers (CNFs) have significant potential in composites as additives to improve mechanical properties, melt rheology, and more. However, agglomeration of CNFs is a key challenge in composite melt processing as obtaining nano-level dispersion of CNFs often requires cost- and energy-intensive processes (e.g., solvent exchange or freeze drying) due to the strong hornification tendencies of CNF. Herein, we avoid these challenges by using a natural fiber carrier method to integrate CNF into thermoplastic composites. Fibers are co-dried to create a hybrid fiber feedstock for compounding in which natural fibers are decorated with dispersed nanofibers. The hybridized fibers result in up to a 24% increase in tensile strength and up to a 35% increase in Young’s modulus compared to composites only containing natural fibers. The lignocellulosic nanofibers are found to outperform their purely cellulosic counterpart, which is theorized to be due to either an increased propensity for fibrillation of the lignocellulosic fibers or the increased hydrophobicity of the fibers due to the presence of lignin. Surface analysis of fiber feedstocks, via streaming potential measurements and dynamic light scattering (DLS), confirmed a significant change in the feedstock hydrophobicity before and after hybridization. While mild additions of CNF (1 wt.% on the macroscale fiber) do not impact the composite melt viscosity, the viscosity is found to increase at higher CNF loadings (5 wt.% on the macroscale fiber), indicating its utility as a rheology modifier. Lastly, use of these materials as novel feedstocks for medium-scale additive manufacturing in high-fidelity part production was demonstrated.

bio-based

Cost-effective valorization of 2,3-butanediol to high-value chemicals and jet fuel

Here, this work outlines an optimized process for converting 2,3-butanediol (BDO) into sustainable aviation fuel (SAF) and C4 chemicals. BDO is reactively separated from fermentation broth by forming dioxolanes, which are converted to isobutyraldehyde, methyl ethyl ketone (MEK), and 1,3-butadiene. These intermediates are reduced and dehydrated over Cu/ZSM-5 to form alkenes, which can be oligomerized and hydrotreated to jet-range alkanes. Previous BDO-dioxolane-alkene processes are limited by the requirement for a continuous aldehyde source for dioxolane formation. Brønsted acidic zeolites catalyze dioxolane deacetalization to form isobutyraldehyde and MEK in a >2:1 molar ratio, providing an internal, recyclable aldehyde source. Dioxolane formation optimization was performed to achieve >95% dioxolane yields over Amberlyst-15 and minimize isobutyraldehyde recycle. The overall BDO-dioxolane-fuel process yields an alkane mixture that enables at least a 50% v/v blend with Jet-A. Techno-economic analyses and life cycle assessments for this BDO-dioxolane-fuel process yield scenarios with <$2.50 per gallon gas equivalent and >58% reduction in CO2 emissions.

2,3-butanediol

The operational environment and rotational acceleration of asteroid (101955) Bennu from OSIRIS-REx observations

During its approach to asteroid (101955) Bennu, NASA's Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer (OSIRIS-REx) spacecraft surveyed Bennu's immediate environment, photometric properties, and rotation state. Discovery of a dusty environment, a natural satellite, or unexpected asteroid characteristics would have had consequences for the mission's safety and observation strategy. Here we show that spacecraft observations during this period were highly sensitive to satellites (sub-meter scale) but reveal none, although later navigational images indicate that further investigation is needed. We constrain average dust production in September 2018 from Bennu's surface to an upper limit of 150g s −1 averaged over 34 min. Bennu's disk-integrated photometric phase function validates measurements from the pre-encounter astronomical campaign. We demonstrate that Bennu's rotation rate is accelerating continuously at 3.63+- 0.52 x10 −6 degrees A day -2 , likely due to the Yarkovsky-O'Keefe-Radzievskii-Paddack (YORP) effect, with evolutionary implications.

Carl William Hergenrother

SAVY-4000 Finite-Element Drop Test Analysis

PFE Auxiliary Systems conducted drop testing on SAVY-4000 containers to evaluate structural response under 12-foot drop conditions. In support of that effort, a finite-element modeling capability was developed to simulate drop response across multiple container sizes and impact orientations. The purpose of this work was to provide a consistent analysis framework that could support interpretation of testing, compare response trends across multiple configurations, and generate quantities of interest for later comparison with experimental data. More broadly, the analysis and testing were intended to assess whether the containers continued to perform their primary function after a 12-foot drop, namely maintaining structural integrity and containment of the contents. The modeling approach combined an implicit preload analysis with an explicit drop simulation so that each drop event began from a mechanically realistic assembled condition, including compression of the silicone O-ring. Separate models were developed for 2-quart, 5-quart, 12-quart, and 10-gallon containers. The results were evaluated in terms of strain-gauge response, collar-lid gap behavior, and accumulated plastic strain. In addition, parametric studies were performed on the 2-quart container to assess sensitivity to O-ring stiffness, friction, canister thickness, geometry tolerance, and mesh density. The simulations showed that predicted drop responses depended strongly on both container size and drop orientation. Gap metrics identified cases in which the predicted collar-lid opening exceeded the nominal O-ring cross-section threshold, while plastic strain metrics identified localized regions of elevated permanent deformation. Parametric studies showed that the predicted response was especially sensitive to the assumed O-ring stiffness and contact friction, while the geometry tolerance study produced smaller changes in the cases examined. The main value of this work was that it established a repeatable modeling and simulation workflow to support drop-test implementation, evaluate effects of future configuration changes, and understand modeling assumptions that most influenced predicted response. At the current stage, the results were viewed as preliminary model predictions rather than validated predictions. The next step would be to compare drop-test data to the model so that predictive values of the workflow could be refined and used with greater confidence to assess whether the containers maintained structural integrity and containment of the contents after a 12-foot drop.

42 ENGINEERING

Modeling Flow in a Microreactor Core: From High-Fidelity CFD to Subchannel Analysis

The accurate prediction of pressure drop in tightly packed, low–Reynolds number (Re) bare rod bundles is essential for the thermal-hydraulic design of the Microreactor Applications Research Validation and EvaLuation (MARVEL) reactor and other microreactor concepts. However, existing friction factor correlations, particularly the upgraded Cheng-Todreas (UCTD) correlation, have limited validation for the small pitch-to-diameter ratios (P/Ds) and transitional flow conditions characteristic of these systems. In this work, we perform high-fidelity large-eddy simulations (LESs) of both an infinite bare rod bundle and a finite bare 37-pin scalloped rod bundle across the range 1000≤ 𝑅𝑒 ≤5500. The simulations reveal strong gap vortex–driven transitional behavior and indicate that the UCTD may underpredict the friction factor by up to 28% at 𝑃/𝐷 = 1.05. Using the LES-calculated pressure drops, we formulate a new friction factor correlation that follows the Cheng-Todreas functional form but is calibrated for low-Re and tightly packed geometries representative of a MARVEL-like reactor. The correlation is implemented in the MOOSE (Multiphysics Object-Oriented Simulation Environment) subchannel module and compared against both the LES and UCTD predictions. Across all subchannel types, the proposed model reduces the streamwise velocity differences from as high as 44% (UCTD) to below 9%, and decreases the pressure gradient differences from 13% to 25% (UCTD) to 0.7% to 7% relative to the LES results. These results suggest that the new correlation has the potential to improve the pressure drop and flow field predictions for such geometries, highlighting the importance of high-fidelity simulations in supporting microreactor thermal-hydraulic model development and motivating future pressure drop experiments for compact rod bundles to further validate these findings.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN

Innovations Driven by Advanced Characterization to Strategize Critical Mineral Production and Beneficial Reuse from Fossil Energy Waste

Critical minerals (CM), such as rare earth elements (REE), cobalt, nickel, and lithium, have important uses in modern electronics and advanced manufacturing, yet are vulnerable to potential supply chain disruptions. Relatively abundant and readily available fossil energy (FE) wastes, such as coal combustion ash, acid mine drainage (AMD) and treatment solids (AMD solids), and Oil and Gas (O&G) drilling wastes (drill cuttings and produced waters) are under consideration as CM feedstocks. The National Energy Technology Laboratory (NETL) has studied CM resources for various FE wastes as part of the U.S. Department of Energy’s mission of bolstering the domestic CM supply, and makes the data available to the public on EDX at sites such as the NEWTS group. Advanced characterization utilizing synchrotron x-ray techniques coupled with laboratory extractions has been performed to identify CM hosting phases in these FE wastes to inform CM recoverability mechanisms. Novel methods to selectively recover CMs while co-producing other valuable byproducts have been developed. Successful examples discussed here include: (1) The identification of REE/Co/Ni/Sc binding and hosting phases in select FE waste (coal combustion ash and AMD solids), resulting in the development of a patented CM step-extraction process, (2) coupled production of functional sorbents from these extraction wastes and for CM recovery. A pilot-scale testing to evaluate the patent’s technical feasibility for extracting REE from coal ash on a barrel scale has been successfully performed. Additionally, (3) evaluation and measurements of brine geochemistry from U.S. O&G produced waters has informed a high Li recovery potential from Marcellus Shale produced water. NETL researchers have been developing tailored pre-treatment processes, an innovative and highly durable lithium sorbent, and geochemical model guided precipitation to accelerate Li production from the Marcellus Shale produced waters. These innovations driven by characterization are integral for maximizing and advancing the potential for CM recovery while offsetting the cost and environmental footprint for FE waste management.

critical mineral processing

Generation of 3.3-mJ, 2.45-µm, sub-2-cycle laser pulses via hollow-core fiber pulse compression

We demonstrate nonlinear compression of mid-infrared pulses from a Cr:ZnSe chirped-pulse amplifier using a gas-filled stretched hollow-core fiber followed by bulk-material compression. Starting from 90 fs, 2.45 µm pulses with 5.3 mJ energy, spectral broadening in the gas-filled capillary combined with optimized dispersion management enables compression to 15 fs, less than two optical cycles at 2.45 µm, with 3.3 mJ pulse energy, corresponding to a peak power of approximately 0.12 TW. The simplicity of the approach, based on a single hollow-core fiber stage and bulk dispersion compensation, makes it scalable to higher energies and establishes a robust route to mid-infrared drivers for high harmonic generation and attosecond applications.

Britton, Mathew [SLAC National Accelerator Laborat

Evaluation of Fatigue Damage Accumulation Functions for Delamination Initiation and Propagation

The present report follows on the cohesive fatigue damage model methodology proposed in NASA-TP-2018-219838. In that report, an empirical function describing the incremental damage due to cyclic loading was used to calculate fatigue damage within a cohesive formulation. The form of the function was developed such that, when integrated at a constant stress amplitude from no damage to failure, it produces a life versus load response that is consistent with an S-N diagram. Therefore, the parameters of the damage model could be obtained by fitting the model predictions to an S-N diagram. The finite element analyses performed demonstrate that the cohesive fatigue accumulation function provides a link between the S-N diagram that describes crack initiation, and the Paris law that characterizes the rate of crack propagation. However, when the model was proposed, it was not known whether the form of the damage accumulation function associated with a desired S-N diagram is unique and, if not, if the link between S-N and the Paris law is unique and independent of the fatigue function selected. In the effort described herein, several alternative forms of the damage function that reproduce the desired features of S-N diagrams were found and evaluated. The effects of each of these functions on the predicted parameters of the Paris law and the propagation threshold are discussed. The results indicate that the predicted exponent m of the Paris law is indeed independent of the damage accumulation function. However, different functions predict different values for the pre-factor C of the Paris law. Therefore, the proper damage accumulation function must be selected by comparison with experiments. One of the new damage accumulation functions proposed herein was found to be particularly useful for analysis because of the ease with which the model parameters can be determined with a minimal amount of experimental information. The effectiveness of the proposed methodology and damage function was demonstrated by conducting analyses of a double cantilever beam test, a mixed-mode bending test, and a three-point bending test of a skin/doubler specimen. The results indicate that the same set of model parameters can provide accurate predictions of the rate of fatigue crack propagation for a variety of material interfaces, mode mixities, load levels, and stress ratios.

DKIN/Stiffener Debonding

Evaluation of Anomaly Detection Capability for Ground-Based Pre-Launch Shuttle Operations

This chapter will provide a thorough end-to-end description of the process for evaluation of three different data-driven algorithms for anomaly detection to select the best candidate for deployment as part of a suite of IVHM (Integrated Vehicle Health Management) technologies. These algorithms were deemed to be sufficiently mature enough to be considered viable candidates for deployment in support of the maiden launch of Ares I-X, the successor to the Space Shuttle for NASA's Constellation program. Data-driven algorithms are just one of three different types being deployed [3],[5]. The other two types of algorithms being deployed include a "rule-based" expert system, and a "model-based" system. Within these two categories, the deployable candidates have already been selected based upon qualitative factors such as flight heritage. For the rile-based system, SHINE (Spacecraft High-speed Inference Engine) has been selected for deployment, which is a component of BEAM (Beacon-based Exception Analysis for Multimissions) [4], a patented technology developed at NASA's JPL (Jet Propulsion Laboratory) and serves to aid in the management and identification of operational modes. For the "model-based" system, a commercially available package developed by QSI (Qualtech Systems, Inc.), TEAMS (Testability Engineering and Maintenance System) [1] has been selected for deployment to aid in diagnosis. In the context of this particular deployment, distinctions among the use of the terms "data-driven," "rule-based," and "model-based," call found in [5]. Although there are three different categories of algorithms that have been selected for deployment, our main focus in this chapter will be on the evaluation of three candidates for data-driven anomaly detection. These algorithms will be evaluated upon their capability for robustly detecting incipient faults or failures in the ground-based phase of pre-launch space shuttle operations, rather than based oil heritage as performed in previous studies [5]. Robust detection will allow for the achievement of pre-specified minimum false alarm and/or missed detection rates in the selection of alert thresholds. All algorithms will also be optimized with respect to all of these same criteria. Our study relies upon the use of Shuttle data to act as was a proxy for and in preparation for application to Ares I-X data, which uses a very similar hardware platform for the subsystems that are being targeted (TVC - Thrust Vector Control subsystem for the SRB (Solid Rocket Booster)).

False Alarms

Dynamic asymmetric strain imprinted into substrates by an oxide thin film

In film-substrate systems, the substrate role is often considered to be limited to providing static mechanical constraints. Dynamic film-substrate interactions when a structural change in the film modifies the substrate are generally disregarded. Here, using combined x-ray and electron microscopies, we observed that an electrically induced filament in a vanadium dioxide film created strong asymmetric strain in an underlying sapphire substrate. This asymmetric substrate strain fed back into the film and defined the filament expansion direction, revealing the importance of film-substrate dynamic interactions in determining film functionality. Furthermore, the strain imprint propagated at least tens of micrometers deep into the substrate, exceeding the film thickness by more than 200-fold, potentially enabling substrate functionalization as an active mechanical coupling media in three-dimensional integrated microelectronic architectures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Exposure of Highly Reflective Far-Ultraviolet Coatings to LEO Environment for TRL Advancement for the Habitable Worlds Observatory

Over the past several years, our team at the NASA Goddard Space Flight Center (GSFC), in collaboration with the Jet Propulsion Laboratory (JPL) and the Naval Research Laboratory (NRL), have developed several new protected Al coating technologies with improved Far-Ultraviolet (FUV) reflectance performance and more robust environmental stability. These include Al protected with lithium-based fluoride (LiF) coatings such as hot deposited LiF (eLiF), XeF 2 -passivated LiF coatings (XeLiF), Li 3 AlF 6 overcoats, AlF 3 (plasma passivated), and XeF 2 passivated MgF 2 coatings (XeMgF 2 ). However, despite these developments, relatively little experimental information exists regarding the long-term stability of these coatings after simultaneous exposure to the Low Earth Orbit (LEO) environment. To evaluate their environmental durability and advance their Technology Readiness Level (TRL), representative samples of these coating technologies, Al+XeLiF, Al+eLiF, Al+Li 3 AlF 6 , Al+AlF 3 , Al+XeMgF 2 , and bare Al as reference samples, were flown onboard the International Space Station (ISS) as part of the Materials International Space Station Experiment 20 (MISSE-20). The MISSE platform is operated by Aegis Aerospace for relatively long-duration (e.g. 6 months) external exposure experiments in a space environment. The coatings were deposited on ULE and Zerodur substrates, and witness samples deposited on the same coatings runs, but on glass slides were left on Earth as control. A subset of the flight samples were fitted with MgF 2 windows to reduce direct exposure to atomic oxygen (AO) and charged particles, and still let through UV and other types of radiation on these samples. After approximately 6 months of exposure in the forward-facing (RAM) direction, the samples were returned to Earth and characterized by performing FUV/NUV/VIS/NIR reflectance measurements to quantify degradation, spectroscopic ellipsometry to evaluate coating thickness and optical constants, atomic force microscopy (AFM) to quantify surface roughness evolution during the flight in the ISS. The MgF 2 protective windows were also analyzed through FUV transmission measurements. Comparison with the witness samples left on the ground and with the flown bare Al samples (with just the naturally occurring Al 2 O 3 layer) provided a quantitative assessment of coating thickness variations, optical performance degradation, and morphological changes induced by prolonged exposure to the LEO environment.

Far Ultraviolet (FUV)

The S-PLUS Fornax Project (S+FP): A first 12-band glimpse of the Fornax galaxy cluster

ABSTRACT The Fornax galaxy cluster is the richest nearby (D ∼ 20 Mpc) galaxy association in the southern sky. As such, it provides a wealth of opportunities to elucidate on the processes where environment holds a key role in transforming galaxies. Although it has been the focus of many studies, Fornax has never been explored with contiguous homogeneous wide-field imaging in 12 photometric narrow and broad bands like those provided by the Southern Photometric Local Universe Survey (S-PLUS). In this paper, we present the S-PLUS Fornax Project (S+FP) that aims to comprehensively analyse the galaxy content of the Fornax cluster using S-PLUS. Our data set consists of 106 S-PLUS wide-field frames (FoV∼1.4 × 1.4 deg2) observed in five Sloan Digital Sky Survey-like ugriz broad bands and seven narrow bands covering specific spectroscopic features like [O ii], Ca ii H+K, Hδ, G band, Mg b triplet, Hα, and the Ca ii triplet. Based on S-PLUS specific automated photometry, aimed at correctly detecting Fornax galaxies and globular clusters in S-PLUS images, our data set provides the community with catalogues containing homogeneous 12-band photometry for ∼3 × 106 resolved and unresolved objects within a region extending over ∼208 deg2 (∼5 Rvir in RA) around Fornax’ central galaxy, NGC 1399. We further explore the eagle and IllustrisTNG cosmological simulations to identify 45 Fornax-like clusters and generate mock images on all 12 S-PLUS bands of these structures down to galaxies with M⋆ ≥ 108 M⊙. The S+FP data set we put forward in this first paper of a series will enable a variety of studies some of which are briefly presented.

Astronomy & Astrophysics

Understanding Discharge‐Driven Growth of Cathode Impedance in Ni‐Rich NMC Cathodes

Degradation of LiNi x Mn y Co 1-x-y O 2 (NMC)-based lithium-ion batteries depends strongly on cut-off voltage ranges. In addition to the high upper cut-off voltage, a high depth of discharge (i.e., lower cut-off voltage) significantly worsens cathode impedance growth and capacity fade during long-term cycling. However, there is currently no consensus on the mechanism behind the negative role of a deep discharge. Here, this phenomenon was investigated in graphite||NMC cells with single-crystal cathodes (LiNi 0.6 Co 0.2 Mn 0.2 O 2 (NMC622) or LiNi 0.76 Co 0.14 Mn 0.10 O 2 (NMC76)) using targeted aging protocols (constant high-voltage holds vs. charge–discharge cycling), while monitoring transition-metal (TM) dissolution, cathode-electrolyte interface (CEI) impedance, and NMC surface composition. We demonstrate a correlation between discharge-driven CEI impedance growth and increased TM dissolution. Furthermore, this degradation pathway is more pronounced in lower-Ni NMC622 than in higher-Ni (NMC76) under comparable delithiation states at charge, with both compositions undergoing the H2→H3 phase transition. X-ray photoelectron spectroscopy (XPS) reveals NMC composition-dependent evolution of surface lattice oxygen and restructured surface layer composition between charged and discharged states. These findings add mechanistic depth to the role of discharge as an active driver of interfacial degradation and provide new insights into its composition dependence.

25 ENERGY STORAGE

Weibel-mediated filamentary structures observed in the ICF context

Here, in light of novel and past experimental results, we demonstrate how Weibel-mediated filamentary structures can develop in the expanding plasma plume of a laser-irradiated foil. The transverse ballistic cooling that occurs during the quasi-spherical plasma expansion naturally drives an electron pressure anisotropy, resulting in the growth of electron current filaments. This effect competes with electron–ion Coulomb collisions, which tend to isotropize the electron distribution function. Based on theoretical and particle-in-cell modeling, we provide estimates of the dominant wavelength and amplitude of the self-generated magnetic fluctuations, which are found to explain experimental data obtained at the OMEGA and Laser Megajoule facilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

Dynamic Interfacial Design in Adaptive Hybrid Materials Enables Reversible and Tunable Mechano-Optic Smart Responses

Next-generation polymeric materials are shifting toward adaptive and interactive behaviors of living systems; however, designing materials that can reversibly modulate optical properties under mechanical deformation while maintaining mechanical robustness remains a key challenge. Here, we report a mechanically robust vitrimer-based adaptive hybrid material (AHM) that exhibits a stretch-induced reversible transparency-to-opacity transition, enabled by the integration of dynamic interactions at the polymer–silica nanoparticle interface and controlled nanoparticle self-assembly. The AHM combines boronic ester–functionalized polystyrene-b-poly(ethylene-co-butylene)-b-polystyrene (S-Bpin) with diol-functionalized silica nanoparticles (diol-SiNPs) to form a hybrid network hosting both dynamic boronic ester and hydrogen-bonding interactions. These reversible linkages facilitate controlled nanoparticle self-assembly and enable strain-induced nanoparticle alignment/aggregation. Upon stretching, SiNP-rich domains align and aggregate within the polymer matrix, while local modulus mismatch between stiff aggregated SiNP/borylated-styrene-rich regions and the softer elastomeric midblock induces surface microwrinkle formation. These internal aggregates and surface wrinkles cooperatively enhance light scattering, producing the opaque state under strain. Furthermore, the tailored AHM exhibits high toughness, thermomechanical stability, reprocessability, and programmable shape-memory behavior. This work presents a dynamic interfacial design strategy for mechanically robust, optically reconfigurable, and reusable soft materials for adaptive optics, smart windows, sensing, soft robotics, and circular smart-material platforms.

adaptive hybrid materials