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At least 955 records · Page 53

Exciton–Polaritons in CsPbBr 3 Crystals Revealed by Optical Reflectivity in High Magnetic Fields and Two-Photon Spectroscopy

Cesium lead bromide (CsPbBr3) is a representative material of the emerging class of lead halide perovskite semiconductors that possess remarkable optoelectronic properties. Its optical properties in the vicinity of the bandgap energy are greatly contributed by excitons, which form exciton polaritons due to strong light–matter interactions. Exciton–polaritons in solution-grown CsPbBr 3 crystals are examined by means of circularly polarized reflection spectroscopy measured in high magnetic fields up to 60 T. The excited 2P exciton state is measured by two-photon absorption. Comprehensive modeling and analysis provides detailed quantitative information about the exciton–polariton parameters: exciton binding energy of 32.5 meV, oscillator strength characterized by longitudinal–transverse splitting of 5.3 meV, damping of 6.7 meV, reduced exciton mass of 0.18$m$ 0 , exciton diamagnetic shift of 1.6 μeV T -2 , and exciton Landé factor $g$ x = + 2.35. It is shown that the exciton states can be described within a hydrogen-like model with an effective dielectric constant of 8.7. From the measured exciton longitudinal–transverse splitting, Kane energy of E p = 15 eV is evaluated, which is in reasonable agreement with values of 11.8–12.5 eV derived from the carrier effective masses.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Investigation of Interlayer Dielectric in BaTiO 3 /III–Nitride Transistors

In this paper, the impact of varying the thickness of the Al 2 O 3 interlayer dielectric on the electrical characteristics of BaTiO 3 /III-nitride transistors is investigated. In the findings, it is revealed that a minimum thickness of 8 nm for the Al 2 O 3 layer is crucial to maintain high device performance and protect against sputtering-induced damage during BaTiO 3 deposition. The fabricated BaTiO 3 /Al 2 O 3 /AlGaN/GaN high electron mobility transistors exhibit exceptional electrical properties, including a maximum current density of 700 mA mm –1 , an on-resistance of 5 Ω mm, an I ON /I OFF ratio of 10 7 , a subthreshold slope of 119 mV dec –1 , and significantly reduced gate leakage current. The devices with the optimal 8 nm Al 2 O 3 thickness demonstrates excellent agreement between theoretical and experimental values for effective mobility, achieving a value of 1188 cm 2 V –1 ·s at a 2D electron gas density of 10 13 cm –2 . Furthermore, in the study, it is confirmed that increasing the Al 2 O 3 thickness also improves the quality of interface charge density, as evidenced by the results obtained from capacitance–voltage measurements. In these findings, the critical role of controlling the Al 2 O 3 thickness in optimizing the electrical characteristics and overall performance of BaTiO 3 /III-nitride transistors are highlighted.

42 ENGINEERING↗

Quantum Sensing of Insulator‐to‐Metal Transitions in a Mott Insulator

Nitrogen vacancy (NV) centers, optically active atomic defects in diamond, have attracted tremendous interest for quantum sensing, network, and computing applications due to their excellent quantum coherence and remarkable versatility in a real, ambient environment. Taking advantage of these strengths, this paper reports on NV-based local sensing of the electrically driven insulator-to-metal transition (IMT) in a proximal Mott insulator. The resistive switching properties of both pristine and ion-irradiated VO 2 thin film devices are studied by performing optically detected NV electron spin resonance measurements. These measurements probe the local temperature and magnetic field in electrically biased VO 2 devices, which are in agreement with the global transport measurement results. In pristine devices, the electrically driven IMT proceeds through Joule heating up to the transition temperature while in ion-irradiated devices, the transition occurs nonthermally, well below the transition temperature. Here, the results provide direct evidence for nonthermal electrically induced IMT in a Mott insulator, highlighting the significant opportunities offered by NV quantum sensors in exploring nanoscale thermal and electrical behaviors in Mott materials.

McLaughlin, Nathan J.↗

Electronic Structure of InAs and InSb Surfaces: Density Functional Theory and Angle-Resolved Photoemission Spectroscopy

The electronic structure of surfaces plays a key role in the properties of quantum devices. However, surfaces are also the most challenging to simulate and engineer. Here, in this work, the electronic structure of InAs(001), InAs(111), and InSb(110) surfaces is studied using a combination of density functional theory (DFT) and angle-resolved photoemission spectroscopy (ARPES). Large-scale first principles simulations are enabled by using DFT calculations with a machine-learned Hubbard U correction [npj Comput. Mater. 6, 180 (2020)]. To facilitate direct comparison with ARPES results, a “bulk unfolding” scheme is implemented by projecting the calculated band structure of a supercell surface slab model onto the bulk primitive cell. For all three surfaces, a good agreement is found between DFT calculations and ARPES. For InAs(001), the simulations clarify the effect of the surface reconstruction. Different reconstructions are found to produce distinctive surface states, which may be detected by ARPES with low photon energies. For InAs(111) and InSb(110), the simulations help elucidate the effect of oxidation. Owing to larger charge transfer from As to O than from Sb to O, oxidation of InAs(111) leads to significant band bending and produces an electron pocket, whereas oxidation of InSb(110) does not. The combined theoretical and experimental results may inform the design of quantum devices based on InAs and InSb semiconductors, for example, topological qubits utilizing the Majorana zero modes.

42 ENGINEERING↗

Efficient Simulation of Open Quantum Systems on NISQ Trapped‐Ion Hardware

Abstract Simulating open quantum systems, which interact with external environments, presents significant challenges on noisy intermediate‐scale quantum (NISQ) devices due to limited qubit resources and noise. In this study, an efficient framework is proposed for simulating open quantum systems on NISQ hardware by leveraging a time‐perturbative Kraus operator representation of the system's dynamics. This approach avoids the computationally expensive Trotterization method and exploits the Lindblad master equation to represent time evolution in a compact form, particularly for systems satisfying specific commutation relations. The efficiency of this method is demonstrated by simulating quantum channels, such as the continuous‐time Pauli channel and damped harmonic oscillators, on NISQ trapped‐ion hardware, including IonQ Harmony and Quantinuum H1‐1. Additionally, hardware‐agnostic error mitigation techniques are introduced, including Pauli channel fitting and quantum depolarizing channel inversion, to enhance the fidelity of quantum simulations. These results show strong agreement between the simulations on real quantum hardware and exact solutions, highlighting the potential of Kraus‐based methods for scalable and accurate simulation of open quantum systems on NISQ devices. This framework opens pathways for simulating more complex systems under realistic conditions in the near term.

Burdine, Colin [Department of Electrical and Compu↗

Investigation of Uranyl Perchlorate Anion Complexes in the Gas Phase via Infrared Multiphoton Dissociation and Collision‐Induced Dissociation

The infrared multiphoton dissociation spectrum of the gas-phase uranyl perchlorate anion ([UO 2 (ClO 4 ) 3 ] − ) was measured. Here, the asymmetric uranyl stretch lies somewhere between 930 and 1030 cm −1 , though it could not be deconvoluted from a closely located perchlorate stretching mode. The experimentally measured spectrum was in good agreement with spectra calculated using density functional theory with the B3LYP and TPSSh functionals and Grimme's D3 dispersion corrections with Becke–Johnson damping. The calculations suggest that the asymmetric uranyl stretch lies in the range of 970–980 cm −1 , about 20–30 cm −1 higher than for the analogous uranyl trinitrato complex and consistent with perchlorate as a weaker ligand than nitrate. Like the uranyl trinitrato anion, fragmentation of [UO 2 (ClO 4 ) 3 ] − by collision-induced dissociation resulted in loss of a ClO 3 • radical to form [UO 3 (ClO 4 ) 2 ] − . Infrared multiphoton dissociation measurements of [UO 3 (ClO 4 ) 2 ] − indicate that the structure of the product ion has an O − ligand bound to the uranyl in a T-arrangement and two perchlorate ligands, matching the findings from uranyl nitrato complexes. The uranyl stretch in this complex was slightly separated from the perchlorate modes and was measured at 906 cm −1 , slightly higher than for the analogous nitrate complex, again consistent with perchlorate as a weaker ligand than nitrate in the gas phase.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗

Comparison of experimental and computational methods for discharge measurements from tidal wetlands

This short communication describes the use and comparison of three methods used to calculate the flow discharge from a tidal wetland stream. The techniques presented are a) bottom-mounted ADCP deployments, b) vessel-mounted ADCP transects, and c) a volume inundation spatial model that relies on a high-resolution LiDAR dataset and time-series of water surface elevation data. The relative agreement between these three methods is used to build confidence in the application of these techniques to the challenge of deducing flow discharge from tidal wetlands.

54 ENVIRONMENTAL SCIENCES↗

Effect of wavelength and filter set choices on fluorogenic thrombin generation assay: Considerations for interlaboratory differences

Insufficient agreement between results of various in–house and commercial thrombin generation (TG) assays complicates TG adoption and use. can be caused by different assay variables, for example, volumes and concentrations of reagents. Although most modern assays employ the same fluorogenic thrombin substrate Z–Gly–Gly–Arg 7–amino–4–methylcoumarin (ZGGR–AMC), the excitation (Ex) and emission (Em) wavelengths used for fluorescence signal measurements can be different.

60 APPLIED LIFE SCIENCES↗

Identifying Nuclear Data Correlated Through Predicting Bias in Integral Experiments via Applying Principal Component Analysis to Random Forest

ABSTRACT Nuclear data (ND) are the input data for neutron‐transport simulations to answer questions related to nuclear technologies. Subsets of ND, here > 20,000 data points, are validated with respect to thousands of criticality experiments that represent various applications on a small scale. The aim of validation with these experiments is to find errors in ND or methods. The key challenge here is that several hundreds of ND are used to simulate one integral value. Hence, one cannot clearly identify what ND are leading to bias in criticality measurements. In fact, a mistake in one nuclear‐data observable can be compensated with an error in another, and the predicted criticality value would still be predicted in agreement with experimental data. Random forest (RF) was previously employed to predict bias in criticality measurements using sensitivities of simulated criticality experiments to ND. The SHapley Additive exPlanations (SHAP) metric was then applied to attribute the importance of each ND experiment and observable to bias prediction. This, however, did not highlight what ND were jointly related to predicting bias. This is important as it could inform us about where compensating errors in ND could hide. We tackle this shortcoming here by first decomposing the ND sensitivities to integral‐experiment simulations into principal components. Then we use principal component projections to predict bias via the RF and SHAP. The SHAP values and principal components are employed to reconstruct detailed SHAP values for each ND observable. We demonstrate that these extended SHAP bias predictions are more robust, less noisy, and more efficient. In addition, we show that this approach accounts for covariance in ND sensitivities and automates the identification of where compensating errors could hide in ND.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Persistent Structure and Frustrated Magnetism in High Entropy Rare-Earth Zirconates

The configurational complexity and distinct local atomic environments of high entropy oxides remain largely unexplored, leaving structure-property relationships and the hypothesis that the family offers rich tunability for applications ambiguous. This work investigates the influence of cation size and materials synthesis in determining the resulting structure and magnetic properties of a family of high entropy rare-earth zirconates (HEREZs, nominal composition RE 2 Zr 2 O 7 with RE = rare-earth element combinations including Eu, Gd, Tb, Dy, Ho, La, or Sc). Here, the structural characterization of the series is examined through synchrotron X-ray diffraction and pair distribution function analysis, and electron microscopy, demonstrating average defect-fluorite structures with considerable local disorder, in all samples. The surface morphology and particle sizes are found to vary significantly with preparation method, with irregular micron-sized particles formed by high temperature sintering routes, spherical nanoparticles resulting from chemical co-precipitation methods, and porous nanoparticle agglomerates resulting from polymer steric entrapment synthesis. In agreement with the disordered cation distribution found across all samples, magnetic measurements indicate that all synthesized HEREZs show frustrated magnetic behavior, as seen in a number of single-component RE 2 Zr 2 O 7 pyrochlore oxides. These findings advance the understanding of the local structure of high entropy oxides and demonstrate strategies for designing nanostructured morphologies in the class.

36 MATERIALS SCIENCE↗

Entrapped Molecule‐Like Europium‐Oxide Clusters in Zinc Oxide with Nearly Unaffected Host Structure

Abstract Nanocrystalline ZnO sponges doped with 5 mol% EuO 1.5 are obtained by heating metal–salt complex based precursor pastes at 200–900 °C for 3 min. X‐ray diffraction, transmission electron microscopy, and extended X‐ray absorption fine structure (EXAFS) show that phase separation into ZnO:Eu and c ‐Eu 2 O 3 takes place upon heating at 700 °C or higher. The unit cell of the clean oxide made at 600 °C shows only ≈0.4% volume increase versus undoped ZnO, and EXAFS shows a ZnO local structure that is little affected by the Eu‐doping and an average Eu 3+ ion coordination number of ≈5.2. Comparisons of 23 density functional theory‐generated structures having differently sized Eu‐oxide clusters embedded in ZnO identify three structures with four or eight Eu atoms as the most energetically favorable. These clusters exhibit the smallest volume increase compared to undoped ZnO and Eu coordination numbers of 5.2–5.5, all in excellent agreement with experimental data. ZnO defect states are crucial for efficient Eu 3+ excitation, while c ‐Eu 2 O 3 phase separation results in loss of the characteristic Eu 3+ photoluminescence. The formation of molecule‐like Eu‐oxide clusters, entrapped in ZnO, proposed here, may help in understanding the nature of the unexpected high doping levels of lanthanide ions in ZnO that occur virtually without significant change in ZnO unit cell dimensions.

36 MATERIALS SCIENCE↗

Modifying the Reactivity of Single Pd Sites in a Trimetallic Sn‐Pd‐Ag Surface Alloy: Tuning CO Binding Strength

Abstract Improving control over active‐site reactivity is a grand challenge in catalysis. Single‐atom alloys (SAAs) consisting of a reactive component doped as single atoms into a more inert host metal feature localized and well‐defined active sites, but fine tuning their properties is challenging. Here, a framework is developed for tuning single‐atom site reactivity by alloying in an additional inert metal, which this work terms an alloy‐host SAA. Specifically, this work creates about 5% Pd single‐atom sites in a Pd 33 Ag 67 (111) single crystal surface, and then identifies Sn based on computational screening as a suitable third metal to introduce. Subsequent experimental studies show that introducing Sn indeed modifies the electronic structure and chemical reactivity (measured by CO desorption energies) of the Pd sites. The modifications to both the electronic structure and the CO adsorption energies are in close agreement with the calculations. These results indicate that the use of an alloy host environment to modify the reactivity of single‐atom sites can allow fine‐tuning of catalytic performance and boost resistance against strong‐binding adsorbates such as CO.

Mohrhusen, Lars↗

Noncovalent Immobilization of Pentamethylcyclopentadienyl Iridium Complexes on Ordered Mesoporous Carbon for Electrocatalytic Water Oxidation

The attachment of molecular catalysts to conductive supports for the preparation of solid-state anodes is important for the development of devices for electrocatalytic water oxidation. The preparation and characterization of three molecular cyclopentadienyl iridium(III) complexes, Cp*Ir(1-pyrenyl(2-pyridyl)ethanolate-κO,κN)Cl (1) (Cp* = pentamethylcyclopentadienyl), Cp*Ir(diphenyl(2-pyridyl)methanolate-κO,κN)Cl (2), and [Cp*Ir(4-(1-pyrenyl)-2,2'-bipyridine)Cl]Cl (3), as precursors for electrochemical water oxidation catalysts, are reported. These complexes contain aromatic groups that can be attached via noncovalent π-stacking to ordered mesoporous carbon (OMC). The resulting iridium-based OMC materials (Ir-1, Ir-2, and Ir-3) were tested for electrocatalytic water oxidation leading to turnover frequencies (TOFs) of 0.9–1.6 s -1 at an overpotential of 300 mV under acidic conditions. The stability of the materials is demonstrated by electrochemical cycling and X-ray absorption spectroscopy analysis before and after catalysis. Theoretical studies on the interactions between the molecular complexes and the OMC support provide insight onto the noncovalent binding and are in agreement with the experimental loadings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Supercooling of Alaskan Beetle Larvae as a Winter Survival Strategy

Insects are able to survive subfreezing temperatures by either limiting ice crystal formation in their bodies or through freeze avoidance. Beetle larvae are able to avoid freezing in winter by dehydrating in the fall months and replacing their body water content with high concentrations of glycerol. This enables the body fluid of the insect to supercool, and even vitrify, recovering unharmed when the temperature warms in the spring. Using nondestructive, high‐energy X‐ray synchrotron diffraction experiments, direct insight into how cryopreservation occurs at the atomic level within the beetle larvae has been obtained. The results shed light on the molecular‐level interactions associated with the mechanism responsible for surviving freezing temperatures. The molecular models of severely dehydrated Alaskan beetle larvae, based on glycerol‐water mixtures, yield a total of 4.2 ± 1.2 intermolecular hydrogen bonds per glycerol molecule at 275 K, in good agreement with existing molecular dynamics simulations. Most importantly, they show that if just over half the body fluid content is water, the water clusters are too small to form ice crystals that cause cellular damage.

Benmore, Chris J. [X‐Ray Science Division Advanced↗

Statistical learning for predicting density–matrix-based electron dynamics

In this study, we consider the problem of learning density-dependent molecular Hamiltonian matrices from time series of electron density matrices, all in the context of Hartree–Fock theory. Prior work developed a solution to this problem for small molecular systems with density and Hamiltonian matrices of size at most 6 × 6. Here, using a battery of techniques, we scale prior methods to larger molecular systems with, for example, 29 × 29 matrices. This includes systems that either have more electrons or are expressed in large basis sets such as 6-311++G**. Scaling the method to larger systems enhances its relevance for realistic applications in chemistry and physics. To achieve this scaling, we apply dimensionality reduction, ridge regression and analytic computation of Hessians. Through the combination of these techniques, we are able to learn Hamiltonians by minimizing an objective function that encodes local propagation error. Importantly, these learned Hamiltonians can then be used to predict electron dynamics for thousands of steps: When we use our learned Hamiltonians to numerically solve the time-dependent Hartree–Fock equation, we obtain predicted dynamics that are in close quantitative agreement with ground truth dynamics. This includes field-off trajectories similar to the training data and field-on trajectories outside of the training data.

59 BASIC BIOLOGICAL SCIENCES↗

Changes in the Regional Water Cycle and Their Impact on Societies

ABSTRACT Changes in “blue water”, which is the total supply of fresh water available for human extraction over land, are quite closely related to changes in runoff or equivalently precipitation minus evaporation, . This article examines how climate change‐driven recent past and future changes in the regional water cycle relate to blue water availability and changes in human blue water demand. Although at the largest scales theoretical and numerical model predictions are in broad agreement with observations, at continental scales and below models predict large ranges of possible future and runoff especially at the scale of individual river catchments and for shorter timescale subseasonal floods and droughts. Nevertheless, it is expected that the occurrence and severity of floods will increase and that of droughts may increase, possibly compounded by human‐driven non‐climatic changes such as changes in land use, dam water impoundment, irrigation and extraction of groundwater. Contemporary assessments predict that increases in 21st century human water extraction in many highly‐populated regions are unlikely to be sustainable given projections of future . To reduce uncertainty in future predictions, there is an urgent need to improve modeling of atmospheric, land surface and human processes and how these components are coupled. This should be supported by maintaining the observing network and expanding it to improve measurements of land surface, oceanic and atmospheric variables. This includes the development of satellite observations stable over multiple decades and suitable for building reanalysis datasets appropriate for model evaluation.

54 ENVIRONMENTAL SCIENCES↗

RANS simulations of neutral atmospheric boundary layer flow over complex terrain with comparisons to field measurements

Micro-scale Reynolds-averaged Navier-Stokes (RANS) simulations of the neutral atmospheric boundary layer (ABL) over complex terrain and a comparison of the results with conditionally averaged met-tower data are presented. A robust conditional sampling procedure for the meteorological tower (met-tower) data to identify near-neutral conditions based on a criterion for the turbulence intensity is developed. The conditionally averaged wind data on 14 met-towers are used for the model validation. The ABL flow simulations are conducted over complex terrain which includes a prominent hill using the OpenFOAM-based simulator for on/offshore wind farm applications (SOWFA) with the k-ϵ and the SST k-ω turbulence models. The discretization of the production term in the transport equation for the turbulent kinetic energy (TKE) is modified to greatly reduce the commonly observed nonphysical near surface TKE peak. The driving inflow is generated through an iterative approach using a precursor method to reproduce the measured wind statistics at the reference tower. Both of the RANS models are able to capture the flow behavior windward of the hill. The SST k-ω model predicts more intense flow separation than the k-ϵ model downstream of the steepest sections of the hill. The wind statistics predicted at the location of the met-towers by both of the RANS models are fairly consistent. Overall, the comparisons of the direction, mean, and standard deviation of the wind between the simulations and the tower data show reasonable agreement except for the differences of the mean wind speeds at four met-towers located closer to the main ridge of the hill in a region of strong terrain variations.

17 WIND ENERGY↗

A Green's Function Wind Turbine Induction Model That Incorporates Complex Inflow Conditions

ABSTRACT In this work, we develop a new analytical turbine induction model that can incorporate complex inflow conditions including cases where the wind velocity and temperature profiles can vary as functions of height. This induction model is derived from the linearized Navier–Stokes and leads to a second‐order ODE that can be solved using a Green's function formulation. The corresponding Green's function for several configurations are found including the infinite domain, semi‐infinite domain with ground plane, and a power law velocity inflow profile. The results of this approach are then compared with simulations of the turbine induction field using the AMR‐Wind CFD solver with a uniformly loaded actuator disk model. These comparisons show that the Green's function approach captures the centerline blockage, three‐dimensional blockage flow field, and streamwise velocity slow down, with very good agreement for lower thrust conditions and at larger distances away from rotor disk. The effects of shear on the turbine blockage were also compared using a power law inflow profile, and we show that this approach matches the CFD predictions for the cases considered.

17 WIND ENERGY↗