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At least 1,549 records · Page 86

Modeling Ni redistribution in the hydrogen electrode of solid oxide cells through Ni(OH) 2 diffusion and Ni-YSZ wettability change

Ni redistribution in the hydrogen electrodes of solid oxide cells is an important degradation mechanism. Its driving force is still under debate. This work focuses on the interplay between Ni(OH) 2 diffusion and Ni-YSZ wettability change. With a Ni(OH) 2 diffusion model developed in our previous work, we further employ three models for the Ni-YSZ contact angle to quantify the Ni-YSZ wettability change. The microstructure evolutions in a reconstructed Ni-YSZ electrode are simulated under selected experimental operating conditions. It is shown that the phenomenological model can capture the driving force of Ni spreading/detachment on YSZ surface and the Ni migration reported in experiments can be qualitatively reproduced through the competition between Ni(OH) 2 diffusion and Ni-YSZ wettability change. It is also found that the initial microstructure of the active layer and the microstructure characteristics in the support layer can strongly affect the distribution of steam partial pressure and overpotential, hence the Ni redistribution, in the active layer, which may explain the inconsistencies in experiments. Further, our results show that there are two missing pieces in current theory of Ni redistribution: a mechanism of fast Ni diffusion under humid atmosphere and the physical reason behind the Ni spreading/detachment.

25 ENERGY STORAGE↗

Statistical analysis of HAADF-STEM images to determine the surface coverage and distribution of immobilized molecular complexes

The surface immobilization of molecular catalysts is attractive because it combines the benefits of homogeneous and heterogeneous catalysis. However, determining the surface coverage and distribution of a molecular catalyst on a solid support is often challenging, inhibiting our ability to design improved catalytic systems. Here, in this work, we demonstrate that the combination of scanning transmission electron microscopy (STEM) and image analysis of the individual positions of heavy atoms in transition metal complexes via a convolutional neural network (CNN) allows statistically robust determination of the surface coverage and distribution of immobilized molecular catalysts. These observations provide information about how changes in the functionalization conditions, attachment group, and structure of the molecular catalyst affect the surface coverage and distribution, providing insight into the chemical mechanism of surface immobilization. The method could be generally valuable for correlating the surface coverage and distribution to the activity, selectivity, and stability of a catalytic system.

HAADF-STEM↗

Monte Carlo simulation of the passage of $\gamma$-rays and $\alpha$-particles in CsI

In this work, theoretical and computational methods for simulating the creation of ionization tracks by fast ions in solids were applied to the passage of a-particles in CsI, an inorganic scintillator commonly used for radiation detection. The methods were implemented in a Monte Carlo program to simulate the interaction of $\alpha$-particles, with incident energies of up to 1 MeV, with CsI. The simulations followed the fate of individual electron-hole pairs and thus allowed for a detailed description of the microscopic structure of ionization tracks created by incident radiation. Simulations were also performed with $\gamma$-rays of the same energy to compare and contrast the ionization tracks obtained with both types of particle. Intrinsic properties such as the mean energy per electron-hole pair, Fano factor, maximum theoretical light yield, and spatial distributions of electron-hole pairs were computed for both $\alpha$-particles and $\gamma$-rays. $\alpha$-particles created cylindrical tracks that were initially aligned with the incident direction and with initial radii of a few nanometers, whereas $\gamma$-rays showed significant scattering, resulting in probability distributions with lower intensities and much greater radial extents.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Effective Li-Ion Transport Quantification in Composite Cathodes for All-Solid-State Batteries via Multiscale Modeling and Experiments

The tortuosity factor of composite cathodes significantly affects the rate performance of all-solid-state batteries (ASSBs) and has significant differences from systems with liquid electrolytes. Here, in this work, we report a simulation-experiment combined approach that quantifies the effective Li-ion transport in an ASSB composite cathode, which links tortuosity factor on ∼ μm scale to terminal voltage during cycling at the cell level (on ∼ cm scale). Two independent approaches of tortuosity factor quantification are considered: fitting electrochemical cycling data and verifying at different cycling rates and calculating from segmented tomography images, with the tortuosity factor quantified from both methods reaching self-consistency. The simulated terminal voltage using the quantified tortuosity factor has a small relative error of <3% compared to the experimental measurements. We find a significantly reduced value of the Bruggeman exponent of the catholyte phase (1.75), and using shape analysis, we show that rod-shaped catholyte particles play an important role in lowering the tortuosity factor.

Yao, Archie Mingze [Univ. of Michigan, Ann Arbor, ↗

The New Semiconductor Cs 4 Cu 3 Bi 9 S 17

In this work, new quaternary chalcogenide Cs 4 Cu 3 Bi 9 S 17 has been synthesized by solid state reaction in a vacuum-sealed silica tube. Cs 4 Cu 3 Bi 9 S 17 adopts monoclinic space group P 2 1 / m , with the following dimensions: a = 20.006(4) Å, b = 4.0556(8) Å, c = 22.279(5) Å, and β = 96.921°. The crystal structure of Cs 4 Cu 3 Bi 9 S 17 features a unique three-dimensional framework consisting of interconnected Bi 2 Te 3 - and CdI 2 -type fragments forming three different-sized tunnels running parallel to the b -axis. The tunnels are filled with different numbers (1, 2, or 4) of Cs atoms. Cs 4 Cu 3 Bi 9 S 17 is stable in air at room temperature, and differential thermal analysis showed that it decomposes at elevated temperatures. Cs 4 Cu 3 Bi 9 S 17 is a semiconductor with a direct optical band gap of 0.9 eV, which is in agreement with density functional theory calculations. Electrical conductivity and Seebeck coefficient measurements show n-type semiconductor behavior. The electrical conductivity is 10 –4 S/cm at 300 K and increases to 0.9 S/cm at 773 K. Cs 4 Cu 3 Bi 9 S 17 possesses a very low thermal conductivity of 0.71 W m –1 K –1 at room temperature that decreases linearly with an increase in temperature to 0.46 W m –1 K –1 at 773 K. The low thermal conductivity shows the promise of Cs 4 Cu 3 Bi 9 S 17 as a new thermoelectric material with appropriate doping.

36 MATERIALS SCIENCE↗

Cationic Dependence of X-ray Induced Damage in Strontium and Barium Nitrate

The response of solids to x-ray irradiation is not well understood, in part, because the interactions between x-rays and molecules in solids depend on the intra- and/or inter-molecular electronic properties of the material. Our previous work demonstrated that x-ray induced damage of certain ionic salts depends on the irradiating photon energy, especially when irradiated with photons of energy near the cation’s K-edge. To advance understanding of the cationic dependence of x-ray photochemistry, we present studies of x-ray induced damage of barium nitrate and strontium nitrate. Polycrystalline samples of barium and strontium nitrate were irradiated with high flux monochromatic synchrotron x-rays at selected energies near the K-edge of the respective cations. The damage processes were studied with powder x-ray diffraction, and irradiation products, NO 2 and O 2 , were characterized via Raman spectroscopy. Our results demonstrate that irradiating barium and strontium nitrate with photons of energy greater than the K-edge of the cation promotes high rate of decomposition compared to that observed when irradiating with photons of energy below the K-edge. Additionally, differences in x-ray induced damage between the two compounds are examined and discussed, and evidence of the diffusion of irradiation products is presented.

36 MATERIALS SCIENCE↗

Multiplex Detection of Multiple-Quantum/Single-Quantum NMR Correlation Spectra

High-ordered multiple-quantum coherences have been used to gauge the size of coupled networks of nuclear spins but are seldom used in modern high-resolution solid-state NMR spectroscopy due to the low resolution of earlier techniques. Herein, we extend this work to the third dimension by designing an MQ spin counting experiment with full chemical resolution of the nuclei involved in the coherences. The technique uses multiplex processing to simultaneously acquire MQ/1Q correlation 2D spectra, with all even-ordered values of M, in the same amount of time it would take to acquire the 2Q/1Q spectrum alone. Further, we apply this multiplexed MQ/1Q correlation method to probe site clustering on functionalized silica surfaces and find the first evidence of clusters involving three or more functionalities. When applied to a supported zirconium metallocene, the observation of a 6Q coherence between six cyclopentadienyl proton nuclei confirms the colocation of two cyclopentadienyl ligands on a single metal center.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Harnessing Neural Networks for Elucidating X-ray Absorption Structure–Spectrum Relationships in Amorphous Carbon

Improved understanding of structural and chemical properties through local experimental probes, such as X-ray absorption near-edge structure (XANES) spectroscopy, is crucial for the understanding and design of functional materials. In recent years, significant advancements have been made in the development of data science approaches for the automated interpretation of XANES structure–spectrum relationships. However, existing studies have primarily focused on crystalline solids and small molecules, while fewer efforts have been devoted to disordered systems. Thus, in this work, we demonstrate the development of neural network models for predicting and interpreting XANES spectra of amorphous carbon (a-C) from local structural descriptors. Comparison between different structural descriptors expectedly shows that the inclusion of both bond length and bond angle information is necessary for an accurate prediction of the spectra. Among the descriptors considered in this work, we find that the local many-body tensor representation yields the highest accuracy and greatest interpretability so that it can be leveraged to understand the importance of structural motifs in determining XANES spectra. Furthermore, we also discuss performance of neural network models for predicting both local structure features, such as bond lengths and bond angles, and global chemical composition, such as the sp:sp 2 :sp 3 ratio.

36 MATERIALS SCIENCE↗

Rational Electrolyte Design for Elevated-Temperature and Thermally Stable Lithium-Ion Batteries with Nickel-Rich Cathodes

As the energy density of lithium-ion batteries (LIBs) increases, the shortened cycle life and the increased safety hazard of LIBs are drawing increasing concerns. To address such challenges, a series of localized high-concentration electrolytes (LHCEs) based on a solvating-solvent mixture of tetramethylene sulfone and trimethyl phosphate and a high flash-point diluent 1H,1H,5H-octafluoropentyl 1,1,2,2-tetrafluoroethyl ether were designed. The LHCEs exhibited non-flammability and greatly suppressed heat release at high temperatures, which would potentially improve the safety performance of the LIBs. Moreover, the optimal LHCE achieved capacity retentions of 87.1% and 81.7% in graphite||LiNi 0.8 Mn 0.1 Co 0.1 O 2 cells after 500 cycles at 25 °C and 45 °C, respectively, which were significantly better than the conventional electrolyte, whose capacity retentions were only 75.2% and 38.5% under the same condition. Mechanistic studies revealed that the LHCE not only formed a more robust solid electrolyte interphase, but also exhibited improved anodic stability, compared with the conventional electrolyte. Further, this work sheds light in rational electrolyte design for high energy density LIBs with high battery performance and low safety concerns.

25 ENERGY STORAGE↗

Impact of Microstructure on MoS 2 Oxidation and Friction

In this work, we demonstrate the role of microstructure in the friction and oxidation behavior of the lamellar solid lubricant molybdenum disulfide (MoS 2 ). We report on systematic investigations of oxidation and friction for two MoS 2 films with distinctively different microstructures—amorphous and planar/highly-ordered—before and after exposure to atomic oxygen (AO) and high-temperature (250 °C) molecular oxygen. A combination of experimental tribology, molecular dynamics simulations, X-ray photoelectron spectroscopy (XPS), and high-sensitivity low-energy ion scattering (HS-LEIS) was used to reveal new insights about the links between structure and properties of these widely utilized low-friction materials. Initially, ordered MoS 2 films showed a surprising resistance to both atomic and molecular oxygens (even at elevated temperature), retaining characteristic low friction after exposure to extreme oxidative environments. Finally, XPS shows comparable oxidation of both coatings via AO; however, monolayer resolved compositional depth profiles from HS-LEIS reveal that the microstructure of the ordered coatings limits oxidation to the first atomic layer.

36 MATERIALS SCIENCE↗

Mesoporous Amorphous High-Entropy Oxide Films: Unlocking Enhanced Redox Activity

High-entropy oxides (HEOs) represent a frontier in catalyst design via entropy-stabilized solid solution formation. However, their catalytic efficiency is limited by their bulk and dense nature. This work presents a strategic approach to tackle this challenge by fabricating mesoporous amorphous HEO films (MA-HEOF) possessing maximized active site utilization efficiency. The success hinges on the as-developed geometric engineering strategy via controlled deposition–precipitation to confine the amorphous HEO thin film on the surface of mesoporous channels. The unique structure of MA-HEOF was elucidated via microscopy-, X-ray-, and neutron-based techniques, which were manifested by enriched surface-activated lattice oxygen and enhanced redox activity, as confirmed by isotope studies. Besides, the MA-HEOF could stabilize and modulate the properties of integrated noble metal sites, enhancing their redox activity in diverse reactions. In conclusion, the approaches and insights presented herein provide guidance on maximizing the utilization efficiency of high-entropy materials in catalysis and beyond.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Concerted Formation of Reversibly Precipitated Sulfur Species and Its Importance for Lean Electrolyte Lithium–Sulfur Batteries

Achieving high energy densities for lithium-sulfur batteries remain elusive. Largely limited by the volume of electrolyte used, lean electrolyte conditions (electrolyte/sulfur mass ratio <3) present enormous challenges that have led to very poor specific capacity and rate performance. Previous studies have identified that the high concentration of polysulfide is responsible for the poor discharge voltage. However, there still lacks sufficient understanding of the processes occurring at lean electrolyte conditions. Here, in this work we uncovered a polysulfide concentration regulating mechanism that operates through the precipitation and redissolution of solid sulfur-based species (reversibly precipitated sulfur species, RPSS). This occurs in a concerted manner in a global sense through the cathode and can be measured using impedance spectroscopy. It was found that the more RPSS that is formed, the higher the energy density of discharge. We propose that high concentration of polysulfide tends to supersaturate, which impeded the formation of RPSS. Employing an electrolyte with low Li ion concentration along with using poorly dissociating lithium salts allowed for more RPSS formation and ultimately enabled discharge at >2.0 V at 0.05 C, at E/S = 2.5, and at room temperature without the use of an engineered cathode.

25 ENERGY STORAGE↗

Application of a High-Throughput Analyzer in Evaluating Solid Adsorbents for Post-Combustion Carbon Capture via Multicomponent Adsorption of CO2, N-2, and H2O

Despite the large number of metal-organic frameworks that have been studied in the context of post-combustion carbon capture, adsorption equilibria of gas mixtures including CO2, N-2, and H2O, which are the three biggest components of the flue gas emanating from a coal- or natural gas-fired power plant, have never been reported. Here, we disclose the design and validation of a high-throughput multicomponent adsorption instrument that can measure equilibrium adsorption isotherms for mixtures of gases at conditions that are representative of an actual flue gas from a power plant. This instrument is used to study 15 different metal-organic frameworks, zeolites, mesoporous silicas, and activated carbons representative of the broad range of solid adsorbents that have received attention for CO2 capture. While the multicomponent results presented in this work provide many interesting fundamental insights, only adsorbents functionalized with alkylamines are shown to have any significant CO2 capacity in the presence of N-2 and H2O at equilibrium partial pressures similar to those expected in a carbon capture process. Most significantly, the amine-appended metal organic framework mmen-Mg-2(dobpdc) (mmen = N,N'-dimethylethylenediamine, dobpdc (4-) = 4,4'-dioxido-3,3'-biphenyldicarboxylate) exhibits a record CO2 capacity of 4.2 +/- 0.2 mmol/g (16 wt %) at 0.1 bar and 40 degrees C in the presence of a high partial pressure of H2O.

Mason, JA↗

A Decision-Relevant Factor-Fixing Framework: Application to Uncertainty Analysis of a High-Dimensional Water Quality Model

Factor Fixing (FF) is a common method for reducing the number of model parameters to lower computational cost. FF typically starts with distinguishing the insensitive parameters from the sensitive and pursues uncertainty quantification (UQ) on the resulting reduced-order model, fixing each insensitive parameter at a fixed value. There is a need, however, to expand such a common approach to consider the effects of decision choices in the FF-UQ procedure on metrics of interest. Therefore, to guide the use of FF and increase confidence in the resulting dimension-reduced model, we propose a new adaptive framework consisting of four principles: (a) re-parameterize the model first to reduce obvious non-identifiable parameter combinations, (b) focus on decision relevance especially with respect to errors in quantities of interest (QoI), (c) conduct adaptive evaluation and robustness assessment of errors in the QoI across FF choices as sample size increases, and (d) reconsider whether fixing is warranted. The framework is demonstrated on a spatially-distributed water quality model. The error in estimates of QoI caused by FF can be estimated using a Polynomial Chaos Expansion (PCE) surrogate model. Built with 70 model runs, the surrogate is computationally inexpensive to evaluate and can provide global sensitivity indices for free. For the selected catchment, just two factors may provide an acceptably accurate estimate of model uncertainty in the average annual load of Total Suspended Solids (TSS), suggesting that reducing the uncertainty in these two parameters is a priority for future work before undertaking further formal uncertainty quantification.

54 ENVIRONMENTAL SCIENCES↗

Alloy-assisted deposition of three-dimensional arrays of atomic gold catalyst for crystal growth studies

Large-scale assembly of individual atoms over smooth surfaces is difficult to achieve. A configuration of an atom reservoir, in which individual atoms can be readily extracted, may successfully address this challenge. In this work, we demonstrate that a liquid gold-silicon alloy established in classical vapor-liquid-solid growth can deposit ordered and three-dimensional rings of isolated gold atoms over silicon nanowire sidewalls. Here, we perform ab initio molecular dynamics simulation and unveil a surprising single atomic gold-catalyzed chemical etching of silicon. Experimental verification of this catalytic process in silicon nanowires yields dopant-dependent, massive and ordered 3D grooves with spacing down to similar to 5 nm. Finally, we use these grooves as self-labeled and ex situ markers to resolve several complex silicon growths, including the formation of nodes, kinks, scale-like interfaces, and curved backbones.

36 MATERIALS SCIENCE↗

Using a physics-informed neural network and fault zone acoustic monitoring to predict lab earthquakes

Abstract Predicting failure in solids has broad applications including earthquake prediction which remains an unattainable goal. However, recent machine learning work shows that laboratory earthquakes can be predicted using micro-failure events and temporal evolution of fault zone elastic properties. Remarkably, these results come from purely data-driven models trained with large datasets. Such data are equivalent to centuries of fault motion rendering application to tectonic faulting unclear. In addition, the underlying physics of such predictions is poorly understood. Here, we address scalability using a novel Physics-Informed Neural Network (PINN). Our model encodes fault physics in the deep learning loss function using time-lapse ultrasonic data. PINN models outperform data-driven models and significantly improve transfer learning for small training datasets and conditions outside those used in training. Our work suggests that PINN offers a promising path for machine learning-based failure prediction and, ultimately for improving our understanding of earthquake physics and prediction.

42 ENGINEERING↗

Electroreduction of Er 3+ in nonaqueous solvents

Here, the electroreduction of Er 3+ in propylene carbonate, N,N-dimethylformamide, or a variety of quaternary ammonium ionic liquids (ILs) was investigated using [Er(OTf) 3 ] and [Er(NTf 2 ) 3 ]. Systematic variation of the ILs' cation and anion, Er 3+ salt, and electrode material revealed a disparity in electrochemical interactions not previously seen. For most ILs at a platinum electrode, cyclic voltammetry exhibits irreversible interactions between Er 3+ salts and the electrode at potentials significantly less than the theoretical reduction potential for Er 3+ . Throughout all solvent–salt systems tested, a deposit could be formed on the electrode, though obtaining a high purity, crystalline Er 0 deposit is challenging due to the extreme reactivity of the deposit and resulting chemical interactions, often resulting in the formation of a complex, amorphous solid–electrolyte interface that slowed deposition rates. Comparison of platinum, gold, nickel, and glassy carbon (GC) working electrodes revealed oxidation processes unique to the platinum surface. While no appreciable reduction current was observed on GC at the potentials investigated, deposits were seen on platinum, gold, and nickel electrodes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗