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At least 523 records · Page 29

Discovery of charge density wave in a kagome lattice antiferromagnet

A hallmark of strongly correlated quantum materials is the rich phase diagram resulting from competing and intertwined phases with nearly degenerate ground state energies. A well-known example is the copper oxides, where a charge density wave (CDW) is ordered well above and strongly coupled to the magnetic order to form spin-charge separated stripes that compete with superconductivity. Recently, such rich phase diagrams have also been revealed in correlated topological materials. In two-dimensional kagome lattice metals consisting of corner-sharing triangles, the geometry of the lattice can produce flat bands with localized electrons, non-trivial topology, chiral magnetic order, superconductivity and CDW order. While CDW has been found in weakly electron correlated nonmagnetic AV 3 Sb 5 (A = K, Rb, Cs), it has not yet been observed in correlated magnetic ordered kagome lattice metals. Here we report the discovery of CDW within the antiferromagnetic (AFM) ordered phase of kagome lattice FeGe. The CDW in FeGe occurs at wavevectors identical to that of AV 3 Sb 5 , enhances the AFM ordered moment, and induces an emergent anomalous Hall effect. Furthermore, our findings suggest that CDW in FeGe arises from the combination of electron correlations-driven AFM order and van Hove singularities-driven instability possibly associated with a chiral flux phase, in stark contrast to strongly correlated copper oxides and nickelates, where the CDW precedes or accompanies the magnetic order.

36 MATERIALS SCIENCE↗

Gapless spin liquid and pair density wave of the Hubbard model on three-leg triangular cylinders

We study the ground state properties of the Hubbard model on three-leg triangular cylinders using large-scale density-matrix renormalization group simulations. At half-filling, we identify an intermediate gapless spin liquid phase, which has one gapless spin mode and algebraic spin–spin correlations but exponential decay scalar chiral–chiral correlations, between a metallic phase at weak coupling and Mott insulating dimer phase at strong interaction. Upon light doping the gapless spin liquid, the system exhibits power-law charge-density-wave (CDW) correlations but short-range single-particle, spin–spin, and chiral–chiral correlations. Similar to CDW correlations, the superconducting correlations also decay in power-law but oscillate in sign as a function of distance, which is consistent with the striped pair-density wave. When further doping the gapless spin liquid phase or doping the dimer order phase, another phase takes over, which has similar CDW correlations but all other correlations decay exponentially.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Imaging Light‐Induced Migration of Dislocations in Halide Perovskites with 3D Nanoscale Strain Mapping

Abstract In recent years, halide perovskite materials have been used to make high‐performance solar cells and light‐emitting devices. However, material defects still limit device performance and stability. Here, synchrotron‐based Bragg coherent diffraction imaging is used to visualize nanoscale strain fields, such as those local to defects, in halide perovskite microcrystals. Significant strain heterogeneity within MAPbBr 3 (MA = CH 3 NH 3 + ) crystals is found in spite of their high optoelectronic quality, and both 〈100〉 and 〈110〉 edge dislocations are identified through analysis of their local strain fields. By imaging these defects and strain fields in situ under continuous illumination, dramatic light‐induced dislocation migration across hundreds of nanometers is uncovered. Further, by selectively studying crystals that are damaged by the X‐ray beam, large dislocation densities and increased nanoscale strains are correlated with material degradation and substantially altered optoelectronic properties assessed using photoluminescence microscopy measurements. These results demonstrate the dynamic nature of extended defects and strain in halide perovskites, which will have important consequences for device performance and operational stability.

36 MATERIALS SCIENCE↗

Isolating the Electrocatalytic Activity of a Confined NiFe Motif within Zirconium Phosphate

Unique classes of active-site motifs are needed for improved electrocatalysis. Herein, the activity of a new catalyst motif is engineered and isolated for the oxygen evolution reaction (OER) created by nickel–iron transition metal electrocatalysts confined within a layered zirconium phosphate matrix. It is found that with optimal intercalation, confined NiFe catalysts have an order of magnitude improved mass activity compared to more conventional surface-adsorbed systems in 0.1 m KOH. Interestingly, the confined environments within the layered structure also stabilize Fe-rich compositions (90%) with exceptional mass activity compared to known Fe-rich OER catalysts. Through controls and by grafting inert molecules to the outer surface, it is evidenced that the intercalated Ni/Fe species stay within the interlayer during catalysis and serve as the active site. After determining a possible structure (wycherproofite), density functional theory is shown to correlate with the observed experimental compositional trends. It is further demonstrated that the improved activity of this motif is correlated to the Fe and water content/composition within the confined space. This work highlights the catalytic enhancement possibilities available through zirconium phosphate and isolates the activity from the intercalated species versus surface/edge ones, thus opening new avenues to develop and understand catalysts within unique nanoscale chemical environments.

36 MATERIALS SCIENCE↗

A Multi-Region SEIR Model Incorporating Inter-County Mobility and Time-Dependent Transmission Dynamics: Application to COVID-19 Disease Outbreak Data in North Carolina.

Classical infectious disease compartmental models typically do not incorporate spatial heterogeneity or mobility. We develop a multi-region susceptible-exposed-infected-recovered (SEIR) model in which disease dynamics are coupled via inter-region mobility and the transmission rate is both region and time dependent. We calibrate the model using rolling averages of daily COVID-19 data in all 100 North Carolina counties. Mobility parameters are prescribed using daily inter-county commuter data. The number of transmission rate parameters is substantially reduced by hypothesizing that the dynamics correlate with county-level population density. Parameter estimation is carried out using several objective functions with error terms at different scales. An additive combination of least squares error at the county-level and the state-level, along with a quadratic transmission rate polynomial, yields the lowest overall error at both spatial scales. The calibrated model is used to simulate regional effects of perturbing disease transmission rates in adjacent counties and to illustrate effects of the state’s mobility infrastructure on disease dynamics and spread for a new disease outbreak.

COVID-19 modeling↗

A Review of the Influence of Processing Parameters on ODS Steels Produced via Additive Manufacturing Techniques

Abstract This paper reviews current observations regarding processing conditions for oxide dispersion-strengthened steels consolidated through additive manufacturing techniques. Variations in ODS steels observed across process parameters include changes in grain size, grain texture, oxide size, density of oxides, porosity, melt pool characteristics, and mechanical properties. These properties were then compared across techniques to understand which techniques and processing conditions lead to the highest strength, ductility, and oxide density. Current literature suggests that a mix of grain types, in the form of either morphology or phase, can significantly increase the strength of printed ODS steels. Meanwhile, the most ductile samples, regardless of consolidation technique or matrix material, were made from feedstock with oxide additions located on the powder surface. Reported grain and oxide sizes were plotted against the ratio of laser power to scan speed, volumetric energy density, and normalized enthalpy. No strong correlation between these values and microstructural features was observed. The plots that were made suggest that a larger data set, more in-depth representative equations, and more defined material properties as a function of specific feedstock used are necessary to determine a value that can be correlated to the printed ODS steel microstructure.

deJong, Matthew↗

A high throughput assay to detect enzymatic polyethylene oxidation

Biological plastics deconstruction and upcycling have emerged as sustainable alternatives to traditional recycling technologies for plastics waste. The discovery and engineering of efficient thermostable poly(ethylene terephthalate) (PET) hydrolases have made biological PET recycling possible at scale; however, enzymes for non-PET plastics, which account for approximately 70% of all plastics produced, remain largely undiscovered. To accelerate the discovery of such enzymes, we develop a high-throughput screen to detect initial polymer oxidation, specifically that of the C-H bond to an aldehyde. We test 4-hydrazino-7-nitro-2,1,3-benxoxadiozole hydrazine (NBD-H), which reacts with generated aldehydes to form a fluorescent hydrazone on plasma oxidized low-density polyethylene (LDPE) films. Hydrazone generation correlated well with the area of aldehyde peaks as measured by Fourier Transform Infrared Spectroscopy (FTIR) (R2 = 0.92). Moreover, we demonstrate that the probe reliably identifies LDPE-active dye decolorizing peroxidases (DyPs) that generate aldehydes on LDPE films (1.7 – 3.0 fold change relative to background), serving as an effective screen as demonstrated by receiver operating characteristic area under the curve of 0.95. Furthermore, this assay offers an LDPE oxidation screening platform that can be readily parallelized and automated for accelerated discovery of enzymes involved in polyolefin deconstruction.

biocatalysis↗

Tailoring catalyst layer structures for anion exchange membrane fuel cells by controlling the size of ionomer aggreates in dispersion

The development of anion exchange membranes and ionomers plays a critical role in performance of anion exchange membrane fuel cells. However, the optimal design of catalyst layer structures still remains unexplored despite its significance. Herein, the rational design guide is presented for cathode and anode catalyst layers using m-TPN1 ionomer by controlling the size of ionomer aggregates in dispersion and comparing various catalyst layer structures. The size of m-TPN1 aggregates decreases, creating a more uniform ionomer distribution and a larger triple-phase-boundary. As ionomer distribution of the cathode catalyst layer becomes more uniform, the power density of membrane-electrode-assembly is enhanced. Also, the power density at fully humidified condition strongly correlates with the porosity of anode catalyst layer due to the limitation of hydrogen transport at anode by water flooding.

42 ENGINEERING↗

Centroidal Voronoi tessellation based methods for optimal rain gauge location prediction

With more satellite and model precipitation data becoming available, new analytical methods are needed that can take advantage of emerging data patterns to make well informed predictions in many hydrological applications. Herein we propose a new strategy where we extract precipitation variability patterns and use correlation map to build the resulting density map that serves as an input to centroidal Voronoi tessellation construction that optimizes placement of precipitation gauges. We provide results of numerical experiments based on the data from the Alto-Adige region in Northern Italy and Oklahoma and compare them against actual gauge locations. This method provides an automated way for choosing new gauge locations and can be generalized to include physical constraints and to tackle other types of resource allocation problems.

54 ENVIRONMENTAL SCIENCES↗

Mechanisms of Three-Dimensional Solid-Phase Epitaxial Crystallization of Strontium Titanate

Strontium titanate (SrTiO 3 , STO) is a complex metal oxide with a cubic perovskite crystal structure. Due to its easily described and understood crystal structure in the cubic phase, STO is an ideal model system for exploring the mechanistic details of solid-phase epitaxy (SPE) in complex oxides. SPE is a crystallization approach that aims to guide crystal growth at low homologous temperatures to achieve targeted microstructures. Beyond planar thin films, SPE can also exploit the addition of a chemically inert, noncrystallizing, amorphous obstacle in the path of crystallization to generate complex three-dimensional structures. The introduction of this mask fundamentally alters the SPE process, inducing a transition from two- to three-dimensional geometries and from vertical to lateral crystal growth under the influence of the crystal/mask/amorphous boundary. Using a combination of molecular dynamics simulations and experiments, we identify several unique phenomena in the nanoscale growth behaviors in both conventional (unmasked) and masked SPE. Examining conventional SPE of STO, we find that crystallization at the interface is strongly correlated to, and potentially driven by, density fluctuations in the region of the amorphous STO near the crystalline/amorphous interface with a strong facet dependence. In the masked case, we find that the crystalline growth front becomes nonplanar near contact with the mask. We also observe a minimum vertical growth requirement prior to lateral crystallization. Both phenomena depend on the relative bulk and interfacial free energies of the three-phase (crystal/mask/amorphous) system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

In Situ XAFS, XRD, and DFT Characterization of the Sulfur Adsorption Sites on Cu and Ce Exchanged Y Zeolites

Adsorptive desulfurization with Cu and Ce ion-exchanged Y zeolite (CuCeY) has proven to be an effective method for the removal of sulfur compounds from hydrocarbon fuels. In this study, Cu and Ce exchanged Y materials including CuY, CeY, and CuCeY were prepared and examined to investigate the mechanism behind the superior sulfur adsorption and selectivity of CuCeY. In situ conditions were used to study the materials as prepared for optimal desulfurization. X-ray diffraction (XRD) confirmed the absence of large well-ordered crystalline phases from metallic or oxide Cu and Ce after the reduction of the samples. The oxidation states and local environments of Cu and Ce were determined using X-ray adsorption fine structure (XAFS) analysis and correlated to theoretical findings obtained from density functional theory (DFT) calculations. XAFS data indicate the successful reduction of Cu species to Cu + and Cu o , and Ce to Ce 3+ . Analysis of XAFS spectra located Cu and Ce within the Y zeolite framework with Cu cations in the six-member ring sites and as small metallic Cu clusters. Ce cations were found to occupy both six-member ring and hexagonal prism sites. Furthermore, these results reveal the structure of CuCeY as prepared for desulfurization and provide insight into its superior sulfur adsorption performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantitative Imaging of Cobalt Phthalocyanine Distribution on Carbon Nanotubes: A Deep Learning Approach to Catalyst Characterization

Electrochemical reduction of carbon dioxide (CO 2 ) offers a pathway to valuable products, with catalysts playing a crucial role. This study investigates the distribution of cobalt tetraaminophthalocyanine (CoPc-NH 2 ) immobilized on carbon nanotubes (CNTs), utilizing high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) to characterize CoPc-NH 2 distribution. A challenge in the quantitative HAADF-STEM analysis is the introduction of bias from manual Co atom identification. To address this, we developed and trained a convolutional neural network (CNN) using a data set generated from images of CoPc-NH 2 /CNT samples with varying Co loadings. The CNN, implemented in TensorFlow and Keras, facilitated Co atom detections. Analysis of the CNN-generated data confirmed a correlation between Co loading and surface density, consistent with findings from UV–vis spectroscopy. Furthermore, the application of Ripley’s L(d) function highlighted the presence of slight Co atom clustering. Furthermore, this work demonstrates the utility of the combined HAADF-STEM and CNN approach for providing spatially resolved information about catalyst distribution on nonplanar supports, revealing structural details that are typically lost through other characterization methods.

HAADF-STEM↗

Overdestabilization vs Overstabilization in the Theoretical Analysis of f-Orbital Covalency

The complex nature of the f-orbital electronic structures and their interaction with the chemical environment pose significant computational challenges. Advanced computational techniques that variationally include scalar relativities and spin–orbit coupling directly at the molecular orbital level have been developed to address this complexity. Among these, variational relativistic multiconfigurational multireference methods stand out for their high accuracy and systematic improvement in studies of f-block complexes. Additionally, these advanced methods offer the potential for calibrating low-scaling electronic structure methods such as density functional theory. However, studies on the Cl K-edge X-ray absorption spectra of the [Ce(III)Cl 6 ] 3– and [Ce(IV)Cl 6 ] 2– complexes show that time-dependent density functional theory with approximate exchange–correlation kernels can lead to inaccuracies, resulting in an overstabilization of 4f orbitals and incorrect assessments of covalency. In contrast, approaches utilizing small active space wave function methods may understate the stability of these orbitals. The results herein demonstrate the need for large active space, multireference, and variational relativistic methods in studying f-block complexes.

chemical calculations↗

Octupole moment driven free charge generation in partially chlorinated subphthalocyanine for planar heterojunction organic photodetectors

In this study, high-performance organic photodetectors are presented which utilize a pristine chlorinated subphthalocyanine photoactive layer. Optical and optoelectronic analyses indicate that the device photocurrent is primarily generated through direct charge generation within the chlorinated subphthalocyanine layer, rather than exciton separation at layer interfaces. Molecular modelling suggests that this direct charge generation is facilitated by chlorinated subphthalocyanine high octupole moment (-80 DÅ 2 ), which generates a 200 meV shift in molecular energetics. Increasing the thickness of chlorinated subphthalocyanine leads to faster response time, correlated with a decrease in trap density. Notably, photodetectors with a 50 nm thick chlorinated subphthalocyanine photoactive layer exhibit detectivities approaching 10 13 Jones, with a dark current below 10 -7 A cm -2 up to -5 V. Based on these findings, we conclude that high octupole moment molecular semiconductors are promising materials for high-performance organic photodetectors employing single-component photoactive layer.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Diagnostic development for parallel wave-number measurement of lower hybrid waves in EAST

In this study, an eight-channel magnetic probe diagnostic system has been designed and installed adjacent to the 4.6 GHz lower hybrid (LH) grill antenna in the low-field side of the Experimental Advanced Superconducting Tokamak (EAST) in order to study the n ∥ evolution of LH waves in the first pass from the launcher to the core plasma. The magnetic probes are separated by 6.6 mm, which allows measurement of the dominant parallel refractive index n ∥ up to n ∥ = 5 for 4.6 GHz LH waves. The magnetic probes are designed to be sensitive to the magnetic field component perpendicular to the background magnetic field with a slit on the casing that encloses the probe. The intermediate frequency stage, which consists of two mixing stages, down-coverts the frequency of the measured wave signals at 4.6 GHz to 20 MHz. A bench test demonstrates the phase stability of the magnetic probe diagnostic system. By evaluating the phase variation of the measured signals along the background magnetic field, the dominant n ∥ of the LH wave in the scrape-off layer has been deduced during the 2019 experimental campaign. In the low density plasma, the measured dominant n ∥ of the LH waves is about 2.1, corresponding to the main peak 2.04 of the launched n ∥ spectrum. n ∥ deduced by the least-squares linear fit method remains near this value in the low density plasma with a high spatial correlation magnitude of 0.9. With an eight-channel probe system, a wave-number spectrum has also been deduced, which has a peak near to the measured dominant n ∥ .

47 OTHER INSTRUMENTATION↗

Examining the order-of-limits problem and lattice constant performance of the Tao–Mo functional

In their recent communication a semi-local density functional derived from the density matrix expansion of the exchange hole localised by a general coordinate transformation. We show that the order-of-limits problem present in the functional, dismissed as harmless in the original publication, causes severe errors in predicted phase transition pressures. We also show that the claim that lattice volume prediction accuracy exceeds that of existing similar functionals was based on comparison to reference data that misses anharmonic zero-point expansion and consequently overestimates accuracy. Here, by highlighting these omissions, we give a more accurate assessment of the Tao-Mo functional and show a possible direction for resolving the order-of-limits problem.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

GPU acceleration of local and semilocal density functional calculations in the SPARC electronic structure code

We present a Graphics Processing Unit (GPU)-accelerated version of the real-space SPARC electronic structure code for performing Kohn–Sham density functional theory calculations within the local density and generalized gradient approximations. In particular, we develop a modular math-kernel based implementation for NVIDIA architectures wherein the computationally expensive operations are carried out on the GPUs, with the remainder of the workload retained on the central processing units (CPUs). Here, using representative bulk and slab examples, we show that relative to CPU-only execution, GPUs enable speedups of up to 6× and 60× in node and core hours, respectively, bringing time to solution down to less than 30 s for a metallic system with over 14 000 electrons and enabling significant reductions in computational resources required for a given wall time.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗