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At least 1,333 records · Page 74

Rapid macrovoid characterization in membranes prepared via nonsolvent-induced phase separation: A comparison between 2D and 3D techniques

Optimizing the performance of asymmetric membranes prepared via nonsolvent-induced phase separation (NIPS) requires a quantitative understanding of how processing variables influence membrane morphology. Presently, the most useful structural quantification techniques require 3D visualization of the membrane structure and are best suited for studies seeking detailed information on small datasets. This study proposes and validates a rapid and accurate technique for quantifying macroporosity (i.e., D m ), a simple descriptor of sublayer macrovoid content in asymmetric membranes D m . values measured from segmented cross-sectional imaging performed via X-ray computed tomography (XCT) and scanning electron microscopy (SEM) are presented and compared for three asymmetric membranes prepared from commercial polymers. Importantly, analyses of 3D XCT membrane reconstructions reveal that D m is described by a single, centralized mean, which demonstrates that macrovoid content is spatially homogenous. Thus, D m can be approximated from limited sampling of the 2D cross-sectional membrane structure via SEM. A proposed 2D SEM sampling method provides D m estimates within ±6% of corresponding 3D XCT values with 30 independent measurements for the three membranes. Further sensitivity is achieved using complementary descriptors such as macrovoid count density (i.e., C m ). This technique is thus a useful tool for characterizing macroporosity from a broad selection of membrane samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural modification of fentanyls for their retrospective identification by gas chromatographic analysis using chloroformate chemistry

Abstract The one-step breakdown and derivatization of a panel of nine fentanyls to yield uniquely tagged products that can be detected by Electron Ionization Gas Chromatography-Mass Spectrometry (EI-GC-MS) is presented. The method involves the treatment of the synthetic opioids with 2,2,2-trichloroethoxycarbonyl chloride (TrocCl) at 60 °C for 3 h in dichloromethane and furnishes two products from one fentanyl molecule that can be used to retrospectively identify the original opioid. Parameters that were studied and fully optimized for the method included temperature, solvent, nature of scavenging base and reaction time. One of the two resulting products from the reaction bears the trichloroethoxycarbonyl (Troc) tag attached to the norfentanyl portion of the original opioid and greatly aids in the opioid detection and identification process. The methodology has been applied to the chemical modification of a panel of nine fentanyls and in all cases the molecular ion peak for the Troc-norfentanyl product bearing the distinctive trichloroethyl isotopic signature can be clearly observed. The method’s LLOD was determined to be 10 ng/mL while its LLOQ was found to be 20 ng/mL. This methodology represents the first application of chloroformates in the chemical modification of this class of synthetic opioids that are notoriously inert to common derivatization strategies available for GC–MS analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Automated Crystal Orientation Mapping in py4DSTEM using Sparse Correlation Matching

Crystalline materials used in technological applications are often complex assemblies composed of multiple phases and differently oriented grains. Robust identification of the phases and orientation relationships from these samples is crucial, but the information extracted from the diffraction condition probed by an electron beam is often incomplete. We have developed an automated crystal orientation mapping (ACOM) procedure which uses a converged electron probe to collect diffraction patterns from multiple locations across a complex sample. We provide an algorithm to determine the orientation of each diffraction pattern based on a fast sparse correlation method. We demonstrate the speed and accuracy of our method by indexing diffraction patterns generated using both kinematical and dynamical simulations. We have also measured orientation maps from an experimental dataset consisting of a complex polycrystalline twisted helical AuAgPd nanowire. From these maps we identify twin planes between adjacent grains, which may be responsible for the twisted helical structure. All of our methods are made freely available as open source code, including tutorials which can be easily adapted to perform ACOM measurements on diffraction pattern datasets.

36 MATERIALS SCIENCE↗

Capturing the sequence of events during the water oxidation reaction in photosynthesis using XFELs

Ever since the discovery that Mn was required for oxygen evolution in plants by Pirson in 1937 and the period-four oscillation in flash-induced oxygen evolution by Joliot and Kok in the 1970s, understanding of this process has advanced enormously using state-of-the-art methods. The most recent in this series of innovative techniques was the introduction of X-ray free-electron lasers (XFELs) a decade ago, which led to another quantum leap in the understanding in this field, by enabling operando X-ray structural and X-ray spectroscopy studies at room temperature. This review summarizes the current understanding of the structure of Photosystem II (PS II) and its catalytic centre, the Mn 4 CaO 5 complex, in the intermediate S i ( i = 0-4)-states of the Kok cycle, obtained using XFELs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Deformation Mechanism Transition in Additively Manufactured Compositionally Graded Fe-Base Alloys

Microstructure-dependent deformation and fracture behavior was investigated for an additively manufactured compositionally graded alloy (CGA) printed using the laser-directed energy deposition (L-DED) method to explore an alternative approach for dissimilar metal joints in nuclear energy systems. The electron backscatter diffraction (EBSD) maps from scanning electron microscopy (SEM) display a clear microstructural transition with decreasing austenite-forming elements (Ni and Mn), from an austenite (γ) dominant structure, to a complex composite structure containing ferrite (α), martensite (α') and retained austenite, and then to a fully ferritic structure. EBSD data were recorded in situ during tensile testing in SEM, and the evolution of the deformation mechanism and microstructure was characterized using Kikuchi diffraction pattern analysis. Complementary analysis for high-resolution features was also performed using scanning transmission electron microscopy (STEM). The Ni/Mn-rich austenite-dominant microstructures showed a complex deformation mechanism of two-step martensitic transformation (γ→ε→α'), whereas the minor austenite phase retained in the ferrite and/or martensite matrix showed a single transformation route (γ→α'). Ordinary dislocation glide and twinning via partial dislocation glide were observed in the austenite deformation. Meanwhile, the ferrite and martensite grains deformed mainly by ordinary dislocation slips and grain rotation. Furthermore, static tensile fracture was also highly dependent on local composition and phase constituents.

36 MATERIALS SCIENCE↗

A comprehensive experimental and kinetic modeling study of di-isobutylene isomers: Part 2

A wide variety of high temperature experimental data obtained in this study complement the data on the oxidation of the two di-isobutylene isomers presented in Part I and offers a basis for an extensive validation of the kinetic model developed in this study. Due to the increasing importance of unimolecular decomposition reactions in high-temperature combustion, we have investigated the di-isobutylene isomers in high dilution utilizing a pyrolysis microflow reactor and detected radical intermediates and stable products using vacuum ultraviolet (VUV) synchrotron radiation and photoelectron photoion coincidence (PEPICO) spectroscopy. Additional speciation data at oxidative conditions were also recorded utilizing a plug flow reactor at atmospheric pressure in the temperature range 725-1150 K at equivalence ratios of 1.0 and 3.0 and at residence times of 0.35 s and 0.22 s, respectively. Combustion products were analyzed using gas chromatography (GC) and mass spectrometry (MS). Ignition delay time measurements for di-isobutylene were performed at pressures of 15 and 30 bar at equivalence ratios of 0.5, 1.0, and 2.0 diluted in 'air' in the temperature range 900-1400 K using a high-pressure shock-tube facility. New measurements of the laminar burning velocities of di-isobutylene/air flames are also presented. The experiments were performed using the heat flux method at atmospheric pressure and initial temperatures of 298-358 K. Moreover, data consistency was assessed with the help of analysis of the temperature and pressure dependencies of laminar burning velocity measurements, which was interpreted using an empirical power-law expression. Electronic structure calculations were performed to compute the energy barriers to the formation of many of the product species formed. The predictions of the present mechanism were found to be in adequate agreement with the wide variety of experimental measurements performed.

09 BIOMASS FUELS↗

Direct Evidence of Photoinduced Charge Transport Mechanism in 2D Conductive Metal Organic Frameworks

Conductive metal organic frameworks (MOFs) represent a promising class of porous crystalline materials that have demon-strated potential in photo-electronics and photocatalytic applications. However, the lack of fundamental understanding on charge transport (CT) mechanism as well as the correlation of CT mechanism with their structure hampered their further development. Herein, we report the direct evidence of CT mechanism in 2D Cu-THQ MOFs and the correlation of temporal and spatial behaviors of charge carriers with their photoconductivity by combining three advanced spectroscopic methods including time resolved optical and X-ray absorption spectroscopy and terahertz spectroscopy. In addition to Cu-THQ, the CT in Cu/Zn-THQ after incorporating Zn2+ guest metal was also examined to uncover the contribution of through space pathway as the presence of the redox inactive 3d10 Zn2+ is expected to perturb the long range in-plane CT. We show that the hot carriers in Cu-THQ generated after photoexcitation are highly mobile and undergo fast localization to a lower energy state (cool carriers) with electrons occupying Cu center and holes in ligands. The cool carriers, which have super long lifetime (> 17 ns) are responsible for the long-term photoconductivity in Cu-THQ and transport through O-Cu-O motif with negligible contribution from interlayer ligand π-π stacking as incorporation of Zn2+ in Cu-THQ significantly reduced photoconductivi-ty. These unprecedent results not only demonstrate the capability to experimentally probe CT mechanism but also provide important insight in the rational design of 2D MOFs for photoelectronic and photocatalytic applications.

14 SOLAR ENERGY↗

Applying Bayesian inference and deterministic anisotropy to retrieve the molecular structure ∣Ψ(R)∣2 distribution from gas-phase diffraction experiments

Abstract Currently, our general approach to retrieving molecular structures from ultrafast gas-phase diffraction heavily relies on complex ab initio electronic or vibrational excited state simulations to make conclusive interpretations. Without such simulations, inverting this measurement for the structural probability distribution is typically intractable. This creates a so-called inverse problem. Here we address this inverse problem by developing a broadly applicable method that approximates the molecular frame structure ∣Ψ( R , t )∣ 2 distribution independent of these complex simulations. We retrieve the vibronic ground state ∣Ψ( R )∣ 2 for both simulated stretched NO 2 and measured N 2 O. From measured N 2 O, we observe 40 mÅ coordinate-space resolution from 3.75 Å −1 reciprocal space range and poor signal-to-noise, a 50X improvement over traditional Fourier transform methods. In simulated NO 2 diffraction experiments, typical to high signal-to-noise levels predict 100–1000X resolution improvements, down to 0.1 mÅ. By directly measuring the width of ∣Ψ( R )∣ 2 , we open ultrafast gas-phase diffraction capabilities to measurements beyond current analysis approaches. This method has the potential to effectively turn gas-phase ultrafast diffraction into a discovery-oriented technique to probe systems that are prohibitively difficult to simulate.

74 ATOMIC AND MOLECULAR PHYSICS↗

Validation of galvanomagnetic and thermomagnetic transport measurements using Standard Reference Material 3451

In the “method of four coefficients,” electrical resistivity (ρ), Seebeck coefficient (S), Hall coefficient (RH), and Nernst coefficient (Q) of a material are measured and typically fit or modeled with theoretical expressions based on Boltzmann transport theory to glean experimental insights into features of electronic structure and/or charge carrier scattering mechanisms in materials. Although well-defined and readily available reference materials exist for validating measurements of ρ and S, none currently exists for R H or Q. We show that measurements of all four transport coefficients—ρ, S, R H , and Q—can be validated using a single reference sample, namely, the low-temperature Seebeck coefficient Standard Reference Material® (SRM) 3451 (composition Bi 2 Te 3+x ) available from the National Institute for Standards and Technology (NIST) without the need for inter-laboratory sample exchange. Here, R H and Q data for NIST SRM 3451 reported here for the temperature range 80–400 K complement the data already available for ρ and S and will therefore be of interest to researchers desiring to validate new or existing galvanomagnetic and thermomagnetic transport properties measurement systems.

47 OTHER INSTRUMENTATION↗

Synergy of Graphene Nanoribbons and Graphene Sheets for High-Rate Lithium-Sulfur Batteries

According to the increasing demands for shortening the battery charging time, high current rate (C-rate) performances become more significant in practical applications. With a higher theoretical capacity, lithium-sulfur batteries are treated as promising candidates for the next-generation batteries. In this work, the utilization of graphene nanoribbons (GNRs) exhibits the benefits in conductivity and other electrochemical performances, especially for high-rate applications. With air-controlled electrospray as the method, carbon encapsulated sulfur particles, poly(acrylic acid), reduced graphene oxide (rGO) sheets, and GNRs are mixed and directly deposited onto the carbon coated aluminum collector, to employ as the cathode. The scanning electron microscopy (SEM) imaging exhibits that the two-dimensional structure of GNRs helps construct inter-connected networks. This improved structure of cathode can increase the electroconductivity, confirmed by the electrochemical impedance spectroscopy (EIS), and modify the porosity, indicated through pore size distribution profiles. In this way, the polysulfides can be more efficiently trapped and utilized, realizing the promising behavior with faster charge transfer. In terms of the cycling performance at 0.2 C, the batteries with GNRs can perform 18% higher in capacity than those without GNRs, without decreasing the charge retention. According to the rate-capability tests, systems with GNRs can achieve enhanced performance compared to batteries with precursor carbon nanotubes (CNTs), especially at high C-rates. At 2 C, with 80 wt % of graphene-based materials as GNRs, batteries can achieve an increase in capacity by 78% and 41% compared with systems without GNRs and those with CNTs, respectively. Accordingly, the results testify the synergy of GNRs and rGO sheets in Li-S batteries.

25 ENERGY STORAGE↗

Synthesis and Crystal Structure of the Zintl Phases NaSrSb, NaBaSb and NaEuSb

This work details the synthesis and the crystal structures of the ternary compounds NaSrSb, NaBaSb and NaEuSb. They are isostructural and adopt the hexagonal ZrNiAl-type structure (space group P6¯2m; Pearson code hP9). The structure determination in all three cases was performed using single-crystal X-ray diffraction methods. The structure features isolated Sb3– anions arranged in layers stacked along the crystallographic c-axis. In the interstices, alkali and alkaline-earth metal cations are found in tetrahedral and square pyramidal coordination environments, respectively. The formal partitioning of the valence electrons adheres to the valence rules, i.e., Na+Sr2+Sb3–, Na+Ba2+Sb3– and Na+Eu2+Sb3– can be considered as Zintl phases with intrinsic semiconductor behavior. Electronic band structure calculations conducted for NaBaSb are consistent with this notion and show a direct gap of approx. 0.9 eV. Additionally, the calculations hint at possible inverted Dirac cones, a feature that is reminiscent of topological quantum materials.

36 MATERIALS SCIENCE↗

Silver Nanoparticles Functionalized Nanosilica Grown over Graphene Oxide for Enhancing Antibacterial Effect

The continuous growth of multidrug-resistant bacteria due to the overuse of antibiotics and antibacterial agents poses a threat to human health. Silver nanoparticles, silica-based materials, and graphene-based materials have become potential antibacterial candidates. In this study, we developed an effective method of enhancing the antibacterial property of graphene oxide (GO) by growing nanosilica (NS) of approximately 50 nm on the graphene oxide (GO) surface. The structures and compositions of the materials were characterized through powdered X-ray diffraction (P-XRD), transmission electron microscopy (TEM), scanning electron microscopy coupled with energy dispersive X-ray spectroscopy (SEM-EDS), ultraviolet–visible spectroscopy (UV–VIS), dynamic light scattering (DLS), Raman spectroscopy (RM), Fourier-transform infrared spectroscopy (FTIR), Brunauer–Emmet–Teller (BET) surface area, and pore size determination. The silver nanoparticles (AgNPs) with an average diameter of 26 nm were functionalized on the nanosilica (NS) surface. The composite contained approximately 3% of silver nanoparticles. The silver nanoparticles on nanosilica supported over graphene oxide (GO/NS/AgNPs) exhibited a 7-log reduction of Escherichia coli and a 5.2-log reduction of Bacillus subtilis within one hour of exposure. Both GO/NS and GO/NS/AgNPs exhibited substantial antimicrobial effects against E. coli and B. subtilis.

36 MATERIALS SCIENCE↗

Characterizing Dynamic Structure in Battery Electrodes by Time-Resolved Cryo-TEM

In recent years, cryogenic transmission electron microscopy (cryo-TEM) has enabled high-resolution characterization of sensitive battery materials by minimizing electron beam-induced artifacts and damage. Success of this technique relies on the preparation of thin, rapidly frozen samples, generally by disassembling batteries under inert atmosphere, transferring materials of interest to a TEM grid, and finally plunge freezing into a cryogen. In material degradation studies, this extensive time between electrochemical cycling and cryo-TEM characterization leaves room for structural relaxation, diffusion, and other dynamic processes that make it difficult to precisely correlate the imaged structure with the native structure that evolves during battery cycling or aging. Here, we present a method to integrate battery cycling with fast preparation of electrode samples for cryo-TEM. This enables higher fidelity between the structures characterized and the electrochemical state of interest, which we use to study deformation in silicon nanoparticle anodes for lithium-ion batteries.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS↗

Benchmarking materials property prediction methods: the Matbench test set and Automatminer reference algorithm

Abstract We present a benchmark test suite and an automated machine learning procedure for evaluating supervised machine learning (ML) models for predicting properties of inorganic bulk materials. The test suite, Matbench, is a set of 13 ML tasks that range in size from 312 to 132k samples and contain data from 10 density functional theory-derived and experimental sources. Tasks include predicting optical, thermal, electronic, thermodynamic, tensile, and elastic properties given a material’s composition and/or crystal structure. The reference algorithm, Automatminer, is a highly-extensible, fully automated ML pipeline for predicting materials properties from materials primitives (such as composition and crystal structure) without user intervention or hyperparameter tuning. We test Automatminer on the Matbench test suite and compare its predictive power with state-of-the-art crystal graph neural networks and a traditional descriptor-based Random Forest model. We find Automatminer achieves the best performance on 8 of 13 tasks in the benchmark. We also show our test suite is capable of exposing predictive advantages of each algorithm—namely, that crystal graph methods appear to outperform traditional machine learning methods given ~10 4 or greater data points. We encourage evaluating materials ML algorithms on the Matbench benchmark and comparing them against the latest version of Automatminer.

36 MATERIALS SCIENCE↗

Reconfigurable Pinwheel Artificial-Spin-Ice and Superconductor Hybrid Device

The ability to control the potential landscape in a medium of interacting particles could lead to intriguing collective behavior and innovative functionalities. In this work, we utilize spatially reconfigurable magnetic potentials of a pinwheel artificial-spin-ice (ASI) structure to tailor the motion of superconducting vortices. The reconstituted chain structures of the magnetic charges in the pinwheel ASI and the strong interaction between magnetic charges and superconducting vortices allow significant modification of the transport properties of the underlying superconducting thin film, resulting in a reprogrammable resistance state that enables a reversible and switchable vortex Hall effect. Our results highlight an effective and simple method of using ASI as an in situ reconfigurable nanoscale energy landscape to design reprogrammable superconducting electronics, which could also be applied to the in situ control of properties and functionalities in other magnetic particle systems, such as magnetic skyrmions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Application of electron backscatter diffraction techniques to quantify effects of aging on sub-grain and spatial heterogeneity in NMC cathodes

Identification and evaluation of structural heterogeneity in spent cathode materials is crucial to developing appropriate remediation strategies for novel recycling processes. Native heterogeneities may be exacerbated during the cell's operational lifetime, as sub-particle-scale variations induce anisotropic expansion and contraction upon cycling. Structural transformations resulting from repeated cycling and calendar aging predominantly occur at the secondary particle surface and at the grain boundaries (GBs) between primary particles. However, the diffusion and stress build up around and across GBs are poorly understood. In this study, electron backscatter diffraction (EBSD) is employed to track sub-grain lattice structure across a statistically relevant number of Li(Ni0.33Mn0.33Co0.33)O2 (NMC-111) particles. Specifically, differences in lattice misorientation – measured as the deviation from the grain's average orientation – are tracked as a function of position within the electrode (near current collector, middle, and near separator) and as a function of electrochemical cycling. Further, a novel method of structural analysis is developed, offering insight into sub-grain diffusion behavior by comparing lattice misorientation near the grain boundary versus in the grain bulk. The present results suggest that electrode-scale spatial heterogeneity in lattice structure is induced by initial manufacturing conditions, and that radial gradients in lattice misorientation evolve at the primary particle scale with repeated electrochemical cycling.

25 ENERGY STORAGE↗

Crystallographic variant mapping using precession electron diffraction data

In this work, we developed three methods to map crystallographic variants of samples at the nanoscale by analyzing precession electron diffraction data using a high-temperature shape memory alloy and a VO2 thin film on sapphire as the model systems. The three methods are (I) a user-selecting-reference pattern approach, (II) an algorithm-selecting-reference-pattern approach, and (III) a k-means approach. In the first two approaches, Euclidean distance, Cosine, and Structural Similarity (SSIM) algorithms were assessed for the diffraction pattern similarity quantification. We demonstrated that the Euclidean distance and SSIM methods outperform the Cosine algorithm. We further revealed that the random noise in the diffraction data can dramatically affect similarity quantification. Denoising processes could improve the crystallographic mapping quality. With the three methods mentioned above, we were able to map the crystallographic variants in different materials systems, thus enabling fast variant number quantification and clear variant distribution visualization. The advantages and disadvantages of each approach are also discussed. We expect these methods to benefit researchers who work on martensitic materials, in which the variant information is critical to understand their properties and functionalities.

Crystallographic variant mapping↗

Physics Discovery in Nanoplasmonic Systems via Autonomous Experiments in Scanning Transmission Electron Microscopy

Abstract Physics‐driven discovery in an autonomous experiment has emerged as a dream application of machine learning in physical sciences. Here, this work develops and experimentally implements a deep kernel learning (DKL) workflow combining the correlative prediction of the target functional response and its uncertainty from the structure, and physics‐based selection of acquisition function, which autonomously guides the navigation of the image space. Compared to classical Bayesian optimization (BO) methods, this approach allows to capture the complex spatial features present in the images of realistic materials, and dynamically learn structure–property relationships. In combination with the flexible scalarizer function that allows to ascribe the degree of physical interest to predicted spectra, this enables physical discovery in automated experiment. Here, this approach is illustrated for nanoplasmonic studies of nanoparticles and experimentally implemented in a truly autonomous fashion for bulk‐ and edge plasmon discovery in MnPS 3 , a lesser‐known beam‐sensitive layered 2D material. This approach is universal, can be directly used as‐is with any specimen, and is expected to be applicable to any probe‐based microscopic techniques including other STEM modalities, scanning probe microscopies, chemical, and optical imaging.

42 ENGINEERING↗