21 research outputs found

    Spin Coherence and Spin Relaxation in Hybrid Organic-Inorganic Lead and Mixed Lead-Tin Perovskites

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    Metal halide perovskites make up a promising class of materials for semiconductor spintronics. Here we report a systematic investigation of coherent spin precession, spin dephasing and spin relaxation of electrons and holes in two hybrid organic-inorganic perovskites MA0.3FA0.7PbI3 and MA0.3FA0.7Pb0.5Sn0.5I3 using time-resolved Faraday rotation spectroscopy. With applied in-plane magnetic fields, we observe robust Larmor spin precession of electrons and holes that persists for hundreds of picoseconds. The spin dephasing and relaxation processes are likely to be sensitive to the defect levels. Temperature-dependent measurements give further insights into the spin relaxation channels. The extracted electron Land\'e g-factors (3.75 and 4.36) are the biggest among the reported values in inorganic or hybrid perovskites. Both the electron and hole g-factors shift dramatically with temperature, which we propose to originate from thermal lattice vibration effects on the band structure. These results lay the foundation for further design and use of lead- and tin-based perovskites for spintronic applications

    Revealing unusual bandgap shifts with temperature and bandgap renormalization effect in phase-stabilized metal halide perovskites

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    Hybrid organic-inorganic metal halide perovskites are emerging materials in photovoltaics, whose bandgap is one of the most crucial parameters governing their light harvesting performance. Here we present temperature and photocarrier density dependence of the bandgap in two phase-stabilized perovskite thin films (MA0.3FA0.7PbI3 and MA0.3FA0.7Pb0.5Sn0.5I3) using photoluminescence and absorption spectroscopy. Contrasting bandgap shifts with temperature are observed between the two perovskites. By utilizing X-ray diffraction and in situ high pressure photoluminescence spectroscopy, we show that the thermal expansion plays only a minor role on the large bandgap blueshift due to the enhanced structural stability in our samples. Our first-principles calculations further demonstrate the significant impact of thermally induced lattice distortions on the bandgap widening and reveal that the anomalous trends are caused by the competition between the static and dynamic distortions. Additionally, both the bandgap renormalization and band filling effects are directly observed for the first time in fluence-dependent photoluminescence measurements and are employed to estimate the exciton effective mass. Our results provide new insights into the basic understanding of thermal and charge-accumulation effects on the band structure of hybrid perovskites

    Large expert-curated database for benchmarking document similarity detection in biomedical literature search

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    Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

    Robust estimation of bacterial cell count from optical density

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    Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

    Response of Near-Surface Meteorological Conditions to Advection under Impact of the Green Roof

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    Due to rapid urbanization, the near-surface meteorological conditions over urban areas are greatly modulated. To capture such modulations, sophisticated urban parameterizations with enhanced hydrological processes have been developed. In this study, we use the single-layer urban canopy model (SLUCM) available within the Weather Research and Forecasting (WRF) model to assess the response of near-surface temperature, wind, and moisture to advection under the impact of the green roof. An ensemble of simulations with different planetary boundary layer (PBL) schemes is conducted in the presence (green roof (GR)) and absence (control (CTL)) of green roof systems. Our results indicate that the near-surface temperature is found to be driven primarily by the surface heat flux with a minor influence from the zonal advection of temperature. The momentum budget analysis shows that both zonal and meridional momentum advection during the evening and early nighttime plays an important role in modulating winds over urban areas. The near-surface humidity remains nearly unchanged in GR compared to CTL, although the physical processes that determine the changes in humidity were different, in particular during the evening when the GR tends to have less moisture advection due to the reduced temperature gradient between the urban areas and the surroundings. Implications of our results are discussed

    Reed Quintet (oboe, clarinet, bass clarinet, saxophone, bassoon)

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    Students will give a brief description of the pieces they have compose

    Computational Modeling of Hibiscone C Reactivity

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    Cooperative Operation Model of Wind Turbine and Carbon Capture Power Plant Considering Benefit Distribution

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    Increasing systematic carbon sinks and clean energy generation proportion are the main ways to reduce the carbon emission of power system. In order to promote wind power accommodation and reduce system carbon emissions, a cooperative operation model of wind turbine and carbon capture power plant (CCPP) is constructed. Then, the model is equivalently transformed into two sub-problems. One is the operation optimization sub-problem of cooperative alliance with the goal of maximizing the alliance benefit. The other is the benefit distribution sub-problem with the goal of fair distributing cooperative benefit. To protect participants’ privacy, the alternating direction method of multipliers (ADMM) is used to realize the distributed solution of the two sub-problems. Finally, the effectiveness of the proposed model is verified by an example, and the sensitivity analysis of the alliance benefit and system carbon emission is carried out with carbon price and carbon capture cost as the sensitivity factors. The example results show that: (1) By providing up and down regulation services to wind turbines, CCPP can obtain ancillary service income and help to reduce the declaration deviation of wind turbines, which can realize multi-win-win situation. (2) Carbon price affects both thermal power units and carbon capture equipment. So, compared with carbon costs, the carbon emissions and the alliance benefit are both more sensitive to carbon price. The model of the paper is constructed under the deviation punishment mechanism, and subsequent research can be expanded in combination with a more detailed imbalance settlement mechanism

    Fast Trajectory Generation with a Deep Neural Network for Hypersonic Entry Flight

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    Optimal entry flight of hypersonic vehicles requires achieving specific mission objectives under complex nonlinear flight dynamics constraints. The challenge lies in rapid generation of optimal or near-optimal flight trajectories with significant changes in the initial flight conditions during entry. Deep Neural Networks (DNNs) have shown the capability to capture the inherent nonlinear mapping between states and optimal actions in complex control problems. This paper focused on comprehensive investigation and evaluation of a DNN-based method for three-dimensional hypersonic entry flight trajectory generation. The network is designed using cross-validation to ensure its performance, enabling it to learn the mapping between flight states and optimal actions. Since the time-consuming training process is conducted offline, the trained neural network can generate a single optimal control command in about 0.5 milliseconds on a PC, facilitating onboard applications. With the advantages in mapping capability and calculating speed of DNNs, this method can rapidly generate control action commands based on real-time flight state information from the DNN model. Simulation results demonstrate that the proposed method maintains a high level of accuracy even in scenarios where the initial flight conditions (including altitude, velocity, and flight path angle) deviate from their nominal values, and it has certain generalization ability
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