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At least 37 records · Page 2

Mechanistic origin of solvent-dependent thermal stability in sodiated Sn anodes for sodium-ion batteries

Understanding the thermal stability of high-energy density alloy anodes is critical for the safe deployment of sodium-ion batteries (SIBs). Here, accelerating rate calorimetry (ARC), post-mortem characterizations, and density functional theory (DFT) calculations are combined to understand the thermal reactivity of fully sodiated Sn, Sn-hard carbon (HC) blends, and HC anodes in carbonate- and ether-based electrolytes. ARC measurements show that propylene carbonate (PC) causes earlier self-heating rate (SHR) onset and higher reactivity than tetraethylene glycol dimethyl ether (TEGDME), indicating inferior thermal stability. Sodiated Sn exhibits better thermal stability than sodiated HC, while Sn-HC blends show intermediate behavior that improves with increasing Sn content. Post-ARC analyses reveal desodiation of Na15Sn4 to metallic Sn with particle coalescence, whereas Sn-HC blends and HC retain finer morphologies. PC promotes Sn oxidation to SnO, while TEGDME suppresses oxide formation; NaPF6-containing electrolytes additionally form NaF. DFT calculations show that PC adsorption lowers Na extraction energy and enhances interfacial electronic interactions, facilitating Na release and reductive decomposition. These results establish a direct correlation between solvent-dependent reaction pathways and thermal stability in SIB alloy anodes.

Accelerating rate calorimetry↗

The Role of Cloud Radiative Effects in the Propagating Southern Annular Mode

Abstract The Southern Annular Mode (SAM) is the most dominant natural mode of variability in the mid‐latitudes of the Southern Hemisphere (SH). However, both the sign and magnitude of the feedbacks from the diabatic processes, especially those associated with clouds, onto the SAM remain elusive. By applying the cloud locking technique to the Energy Exascale Earth System Model (E3SM) atmosphere model, this study isolates the positive feedback from the cloud radiative effect (CRE) to the SAM. Feedback analysis based on a wave activity‐zonal momentum interaction framework corroborates this weak but positive feedback. While the magnitude of the CRE feedback appears to be secondary compared to the feedbacks from the dry and other diabatic processes, the indirect CRE effects through the interaction with other dynamical and thermodynamical processes appear to play as important a role as the direct CRE in the life cycle of the SAM. The cross‐EOF analysis further reveals the obstructive effect of the interactive CRE on the propagation mode of the SH zonal wind directly through the CRE wave source and/or indirectly through modulating other diabatic processes. As a result, the propagation mode becomes more persistent and the SAM it represents becomes more predictable when the interactive CRE is disabled by cloud locking. Future efforts on inter‐model comparisons of CRE‐denial experiments are important to build consensus on the dynamical feedback of CRE.

58 GEOSCIENCES↗

Direct measurement of fluorocarbon radicals in the thermal destruction of perfluorohexanoic acid using photoionization mass spectrometry

Thermal destruction is a critical cornerstone of addressing the rampant contamination of natural resources with per- and polyfluoroalkyl substances (PFAS). However, grave concerns associated with stack emissions from incineration exist because mechanistic studies have thus far relied on ex situ analyses of end products and theoretical calculations. Here, we used synchrotron-based vacuum ultraviolet photoionization mass spectrometry to study the pyrolysis of a representative PFAS-perfluorohexanoic acid-and provide direct evidence of fluorocarbon radicals and intermediates. A key reaction pathway from perfluorocarboxylic acids to ketenes via acyl fluorides is proposed. We furthermore propose CF2/CF3 radical-centered pyrolysis mechanisms and explain their roles in the formation of other products that may form in full-scale incinerators. These results have not only unveiled the role of radicals and intermediates in thermal PFAS decomposition and recombination mechanisms but also provide unique insight into improving the safety and viability of industrial PFAS incineration.

Xu, Ming-Gao↗

Spray coating for washout tooling by binder jet additive manufacturing

We report washout tooling is a process in which a removable mold or fixture is disintegrated using a solvent. Binder Jet (BJ) additive manufacturing holds promise for creating customized washout molds from common materials. BJ-based washout tooling provides an advanced strategy in manufacturing fiber-reinforced composites (FRCs), especially for customized hollow FRCs. However, washout tools formed by BJ require an impermeable barrier between the porous tooling surface and the parts laid up on the surface to prevent the resin from infiltrating the tooling surface and bonding the tool to the FRC. The conventional method for preventing resin migration into the washout mold from the FRC is winding Teflon® tape over the entire surface, which is labor-intensive and very difficult to deploy for specific geometries. Here, we report the development of a polymer spray coating method to seal the tooling surface and prevent resin infiltration without affecting the washout properties needed for sacrificial tooling. Two water-soluble polymers, poly(sodium 4-styrenesulfonate) (PSS–Na) and poly(vinylsulfonic acid, sodium salt) (PVS–Na), were investigated for spray coating. PVS-Na maintained tighter geometric tolerances and provided excellent thermal stability with the onset of decomposition at 320 °C and glass transition temperature of 280 °C. Spray coating with PVS-Na streamlines the process of forming a protective layer for the washout molds by BJ, reduces migration of the resins from the FRC, and significantly improves the production efficiency of complex washout tools.

42 ENGINEERING↗

Efficient Oxidative Decomposition of Jet-Fuel exo -Tetrahydrodicyclopentadiene (JP-10) by Aluminum Nanoparticles in a Catalytic Microreactor: An Online Vacuum Ultraviolet Photoionization Study

The oxidation of gas-phase exo-tetrahydrodicyclopentadiene (JP-10, C 10 H 16 ) over aluminum nanoparticles (AlNP) has been explored between a temperature range of 300 and 1250 K with a novel chemical microreactor. The results are compared with those obtained from chemical microreactor studies of helium-seeded JP-10 and of helium–oxygen-seeded JP-10 without AlNP to gauge the effects of molecular oxygen and AlNP, respectively. Vacuum ultraviolet (VUV) photoionization mass spectrometry reveals that oxidative decomposition of JP-10 in the presence of AlNP is lowered by 350 and 200 K with and without AlNP, respectively, in comparison with pyrolysis of the fuel. Overall, 63 nascent gas-phase products are identified through photoionization efficiency (PIE) curves; these can be categorized as oxygenated molecules and their radicals as well as closed-shell hydrocarbons along with hydrocarbon radicals. Quantitative branching ratios of the products reveal diminishing yields of oxidized species and enhanced branching ratios of hydrocarbon species with the increase in temperature. While in the low-temperature regime (300–1000 K), AlNP solely acts as an efficient heat transfer medium, in the higher-temperature regime (1000–1250 K), chemical reactivity is triggered, facilitating the primary decomposition of the parent JP-10 molecule. Furthermore, this enhanced reactivity of AlNP could plausibly be linked to the exposed reactive surface of the aluminum (Al) core generated upon the rupture of the alumina shell material above the melting point of the metal (Al).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fluorination Enables Simultaneous Improvements of a Dialkoxybenzene-Based Redoxmer for Nonaqueous Redox Flow Batteries

Redoxmers or redox-active organic materials, arc one critical component for nonaqueous redox flow batteries (RFBs), which hold high promise in enabling the time domain of the grid. While tuning redox potentials of redoxmers is a very effective way to enhance energy densities of NRFBs, those improvements often accompany accelerated kinetics of the charged species, undermining stability and cycling performance. In this paper, a strategy for designing redoxmers with simultaneous improvements in redox potential and stability is proposed. Specifically, the redoxmer 1,4-di-tert-butyl-2,5-bis(2,2,2-trifluoroethoxy)benzene (ANL-C46) is developed by incorporating fluorinated substitutions into the dialkoxybenzene-based platform. Compared to the non-fluorinated analogue, ANL-C46 demonstrates not only an increased (similar to 0.41 V) redox potential but also much enhanced stability (1.6 times) and cyclability (4 times) evidenced by electron paramagnetic resonance kinetic study, H-cell and flow cell cycling. In fact, the cycling performance of ANL-C46 is among the best of high potential (>1.0 V vs Ag/Ag + ) redoxmers ever reported. Density functional theory calculations suggest that while the introduced fluorine substitutions elevate the redox potentials, they also help to depress the decomposition reactions of the charged redoxmers, affording excellent stability. The findings represent an interesting strategy for simultaneously improving energy density and stability, which could further prompt the development of high-performance redoxmers.

25 ENERGY STORAGE↗

Additive engineering for robust interphases to stabilize high-Ni layered structures at ultra-high voltage of 4.8 V

Nickel-rich layered cathode materials promise high energy density for next-generation batteries when coupled with lithium metal anodes. However, the practical capacities accessible are far less than the theoretical values due to their structural instability during cycling, especially when charged at high voltages. Here we demonstrate that stable cycling with an ultra-high cut-off voltage of 4.8 V can be realized by using an appropriate amount of lithium difluorophosphate in a common commercial electrolyte. The Li||LiNi 0.76 Mn 0.14 Co 0.10 O 2 cell retains 97% of the initial capacity (235 mAh g -1 ) after 200 cycles. The cycling stability is ascribed to the robust interphase on the cathode. It is formed by lithium difluorophosphate decomposition, which is facilitated by the catalytic effect of transition metals. The decomposition products (Li 3 PO 4 and LiF) form a protective interphase. This suppresses transition metal dissolution and cathode surface reconstruction. It also facilitates uniform Li distribution within the cathode, effectively mitigating the strain and crack formation.

25 ENERGY STORAGE↗

Quantum Solver Using Singular Value Decomposition for Computational Fluid Dynamics

Numerical solutions for fluid flow problems are challenging and have been focus of Computational Fluid Dynamics (CFD) research for past several decades. The advent of quantum computing promises exponential speedup in comparison to existing classical methods and alleviate computational constraints posed by CFD problems. Although solutions for most problems of interest in fluid dynamics using quantum computing are distant, recent advances in algorithms, software and hardware provide a path towards realizing this goal. Quantum linear solver algorithms (QLSA) such as Harrow–Hassidim–Lloyd (HHL) and Variational Quantum Linear Solver (VQLS) have been successfully implemented to solve for canonical problems such as Hele-Shaw flow. However, these algorithms still suffer to scale and address problems with ill-conditioned Jacobians. In the current paper, we alleviate these restrictions with a new quantum solver based on Singular Value Decomposition (SVD) and simulate flow past a 2D cylinder. The fidelity of the SVD based quantum solver in predicting the flow past 2D cylinder is computed along with an assessment of errors. Classical and quantum solutions for the flow are compared for different resolutions. Finally, we discuss variation in the solutions based on number of shots used.

Gottiparthi, Kalyan [ORNL] (ORCID:0000000213540255↗

Enhancing carbon nanotube production from carbon dioxide and ethane using bimetallic catalysts

Converting CO 2 into carbon nanotubes (CNTs) offers a promising way for CO 2 utilization and sequestration, potentially mitigating environmental impacts from anthropogenic emissions. This study reports that bimetallic CoFe catalysts can increase CNT production from the reaction of CO 2 and C 2 H 6 by an order of magnitude compared to their monometallic counterparts. The active sites and CNT morphologies are composition-dependent: Co-rich catalysts (Co/Fe ratio ≥ 5) form stable face-centered cubic (fcc) CoFe alloys, producing cylindrical CNTs; Fe-containing catalysts (Co/Fe ≤ 2) favor body-centered cubic (bcc) CoFe alloy upon reduction, which transforms into carbides, resulting in bamboo-like CNTs. Experimental evidence and DFT calculations reveal that adjacent Fe and Co atoms modulate CO and C x H y adsorption, regulating CNT production pathways through the CO Boudouard reaction and C 2 H 6 decomposition. In conclusion, these results highlight the dual benefits of bimetallic catalysts in enhancing CNT yield and controlling CNT morphology through adjustment of catalyst compositions.

58 GEOSCIENCES↗

Regularization by denoising diffusion models for solving inverse PDE problems with application to full waveform inversion

Partial differential equation (PDE)-governed inverse problems are fundamental across various scientific and engineering applications; yet they face significant challenges due to nonlinearity, ill-posedness, and sensitivity to noise. Here, we introduce a computational framework, regularization by denoising using diffusion models for partial differential equations (RED-DiffEq), by integrating physics-driven inversion and data-driven learning. RED-DiffEq leverages pretrained diffusion models as a regularization mechanism for PDE-governed inverse problems. We apply RED-DiffEq to solve the full waveform inversion problem in geophysics, a challenging seismic imaging technique that seeks to reconstruct high-resolution subsurface velocity models from seismic measurement data. Our method shows enhanced accuracy and robustness compared to benchmark methods. Additionally, it exhibits strong generalization and domain decomposition capacity, enabling the inversion of more complex velocity models with larger domains than those used in training the diffusion model. Our framework can also be directly applied to diverse PDE-governed inverse problems.

Shan, Siming [Yale University, New Haven, CT (Unit↗

Matrix Approach to Accelerate Spin-Up of CLM5

Numerical models have been developed to investigate and understand responses of biogeochemical cycle to global changes. Steady state, when a system is in dynamic equilibrium, is generally required to initialize these model simulations. However, the spin-up process that is used to achieve steady state pose a great burden to computational resources, limiting the efficiency of global modeling analysis on biogeochemical cycles. This study introduces a new Semi-Analytical Spin-Up (SASU) to tackle this grand challenge. We applied SASU to Community Land Model version 5 and examined its computational efficiency and accuracy. At the Brazil site, SASU is computationally 7 times more efficient than (or saved up to 86% computational cost in comparison with) the traditional native dynamics (ND) spin-up to reach the same steady state. Globally, SASU is computationally 8 times more efficient than the accelerated decomposition spin-up and 50 times more efficient than ND. In summary, SASU achieves the highest computational efficiency for spin-up on site and globally in comparison with other spin-up methods. It is generalizable to wide biogeochemical models and thus makes computationally costly studies (e.g., parameter perturbation ensemble analysis and data assimilation) possible for a better understanding of biogeochemical cycle under climate change.

54 ENVIRONMENTAL SCIENCES↗

Spontaneous formation of robust two-dimensional perovskite phases

The two-dimensional on three-dimensional (2D/3D) perovskite bilayer heterostructure can improve the stability and performance of perovskite solar cells. We show that the 2D/3D perovskite stack in a device evolves dynamically during its end-of-life decomposition. Initially phase-pure 2D interlayers can evolve differently, resulting in different device stabilities. We show that a robust 2D interlayer can be formed using mixed solvents to regulate its crystallinity and phase purity. The resulting 2D/3D devices achieved 25.9% efficiency and had good durability, retaining 91% of their initial performance after 1074 hours at 85°C using maximum power point tracking.

14 SOLAR ENERGY↗

Thermal responses of dissolved organic matter under global change

The diversity of intrinsic traits of different organic matter molecules makes it challenging to predict how they, and therefore the global carbon cycle, will respond to climate change. Here we develop an indicator of compositional-level environmental response for dissolved organic matter to quantify the aggregated response of individual molecules that positively and negatively associate with warming. We apply the indicator to assess the thermal response of sediment dissolved organic matter in 480 aquatic microcosms along nutrient gradients on three Eurasian mountainsides. Organic molecules consistently respond to temperature change within and across contrasting climate zones. At a compositional level, dissolved organic matter in warmer sites has a stronger thermal response and shows functional reorganization towards molecules with lower thermodynamic favorability for microbial decomposition. The thermal response is more sensitive to warming at higher nutrients, with increased sensitivity of up to 22% for each additional 1 mg L -1 of nitrogen loading. The utility of the thermal response indicator is further confirmed by laboratory experiments and reveals its positive links to greenhouse gas emissions.

54 ENVIRONMENTAL SCIENCES↗

Distance preserving machine learning for uncertainty aware accelerator capacitance predictions

Abstract Accurate uncertainty estimations are essential for producing reliable machine learning models, especially in safety-critical applications such as accelerator systems. Gaussian process models are generally regarded as the gold standard for this task; however, they can struggle with large, high-dimensional datasets. Combining deep neural networks with Gaussian process approximation techniques has shown promising results, but dimensionality reduction through standard deep neural network layers is not guaranteed to maintain the distance information necessary for Gaussian process models. We build on previous work by comparing the use of the singular value decomposition against a spectral-normalized dense layer as a feature extractor for a deep neural Gaussian process approximation model and apply it to a capacitance prediction problem for the High Voltage Converter Modulators in the Oak Ridge Spallation Neutron Source. Our model shows improved distance preservation and predicts in-distribution capacitance values with less than 1% error.

43 PARTICLE ACCELERATORS↗

Efficient data-driven regression for reduced-order modeling of spatial pattern formation

We present an efficient data-driven regression approach for constructing reduced-order models (ROMs) of reaction-diffusion systems exhibiting pattern formation. The ROMs are learned non-intrusively from available training data of physically accurate numerical simulations. The method can be applied to general nonlinear systems through the use of polynomial model form, while not requiring knowledge of the underlying physical model, governing equations, or numerical solvers. The process of learning ROMs is posed as a low-cost least-squares problem in a reduced-order subspace identified via Proper Orthogonal Decomposition (POD). Numerical experiments on classical pattern-forming systems–including the Schnakenberg and Mimura–Tsujikawa models–demonstrate that higher-order surrogate models significantly improve prediction accuracy while maintaining low computational cost. The proposed method provides a flexible, non-intrusive model reduction framework, well suited for the analysis of complex spatio-temporal pattern formation phenomena.

Data-driven modeling↗

Kinetic Control over Disproportionation Stabilizes Wurster’s Blue Catholyte for Nonaqueous Redox Flow Batteries

Redoxmers are organic molecules that serve as charge carriers in redox flow batteries. While these materials are affordable and easy to source, insufficient stability of their charged states (radical ions) remains a challenge. A common reaction of these species is their disproportionation. Furthermore, this reversible reaction yields unstable multiply charged states, shifting the overall charge transfer equilibrium toward the decomposition products. Here we show how kinetic controls can be engineered into a redoxmer molecule to suppress these unwanted charge transfer reactions. This approach is used to transform Wurster's blue, which is historically the first example of a stable radical ion in organic chemistry, into an exceptionally durable redoxmer molecule that persists over thousands of electrochemical cycles.

Cations↗

Optimizing the Solvent Reorganization Free Energy by Metal Substitution for Nanocage Catalysis

The supramolecular capsule Ga 4 L 6 12– has been found to catalyze a number of important chemical reactions, but the close proximity of a poorly organized external solvent environment can serve as an impediment to the reaction chemistry. Here, using ab initio molecular dynamic calculations and electric field analyses, we find that metal substitution of indium for gallium lowers the total and electrostatic activation barriers by ~3–4 kcal/mol in water solvent. Using an energy decomposition analysis of the interaction of water solvent with the metal vertices, we find that Pauli repulsion between the metal and water decreases, allowing the water coordination with the metal to increase, upon substitution of In for Ga. We therefore determine that the stabilization of the transition state is due to a better arrangement of water molecules around the metal vertices of In 4 L 6 12– and provides a proof of concept of how to redesign the nanocage scaffold in order to reduce the solvent reorganization energy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Trends in Warm Season Mesoscale Convective Systems Over Asia in 2001–2020

Mesoscale convective systems (MCSs) frequently occur over Asia during the warm season, often producing intense precipitation with associated socioeconomic impacts. Here we reveal significant trends in MCS occurrence frequency and related precipitation in Asia during the warm season (March–September) in 2001–2020, using a tracking method that combines cloud and precipitation criteria with high-resolution satellite data from the Global Precipitation Measurement mission. To examine whether there are differences between MCSs of different scales, both meso-α scales (MαCSs) and meso-β scales (MβCSs), with horizontal scales of 200–2,000 km and 20–200 km, are tracked. The distribution pattern of frequency and related precipitation of both MαCSs and MβCSs are quite similar and manifest positive trends over East Asia (EA) and Northeast Asia, and negative trend over Southeast Asia (SEA). The MCS precipitation trend contributes significantly to total precipitation trend, with MαCSs contributing the most. Our analysis indicates the trend in lower-tropospheric water vapor flux convergence has a similar spatial pattern to the MCS frequency and related precipitation trend. Based on an atmospheric moisture flux decomposition analysis, the water vapor flux convergence trend can largely be explained by the change in horizontal wind convergence, while the specific humidity trend driven largely by temperature change plays a minor role. In conclusion, the trend in wind convergence in EA and SEA is possibly related to the evident trend in the lower-tropospheric anticyclone over the western North Pacific and SEA, which might be due to the relatively stronger warming in the Indian Ocean during the past two decades.

54 ENVIRONMENTAL SCIENCES↗