Enhanced dielectric nonlinearity in epitaxial Pb0.92La0.08Zr0.52Ti0.48O3 thin films

This is the published version. Copyright 2014 American Institute of PhysicsHigh quality c-axis oriented epitaxial Pb 0.92La0.08Zr0.52Ti0.48O3 films were fabricated using pulsed laser deposition on (001) LaAlO3 substrates with conductive LaNiO3 buffers. Besides confirmation of the in-plane and out-of-plane orientations using X-ray diffraction, transmission electron microscopy study has revealed columnar structure across the film thickness with column width around 100 nm. Characterization of ferroelectric properties was carried out in comparison with polycrystalline Pb 0.92La0.08Zr0.52Ti0.48O3 films to extract the effect of epitaxial growth. It is found that the ratio between the irreversible Rayleigh parameter and reversible parameter increased up to 0.028 cm/kV at 1 kHz on epitaxial samples, which is more than twice of that on their polycrystalline counterparts. While this ratio decreased to 0.022 cm/kV with increasing frequency to100 kHz, a much less frequency dependence was observed as compared to the polycrystalline case. The epitaxial Pb 0.92La0.08Zr0.52Ti0.48O3 films exhibited a higher mobility of domain wall and the higher extrinsic contribution to the dielectric properties, as well as reduced density of defects, indicating that it is promising for tunable and low power consumption devices

Enhanced energy density with a wide thermal stability in epitaxial Pb0.92La0.08Zr0.52Ti0.48O3 thin films

High-quality epitaxial Pb0.92La0.08Zr0.52Ti0.48O3 (PLZT) films of thickness of 880 nm were fabricated using pulsed laser deposition on (001) Nb doped SrTiO3 (Nb:STO) substrates. Besides a confirmation of the epitaxial relationship [100]PLZT//[100]Nb:STO and (001)PLZT//(001)Nb:STO using X-ray diffraction, a transmission electron microscopy study has revealed a columnar structure across the film thickness. The recoverable energy density (Wrec) of the epitaxial PLZT thin film capacitors increases linearly with the applied electric field and the best value of 31 J/cm3 observed at 2.27 MV/cm is considerably higher by 41% than that of the polycrystalline PLZT film of a comparable thickness. In addition to the high Wrec value, an excellent thermal stability as illustrated in a negligible temperature dependence of the Wrec in the temperature range from room temperature to 180 C is achieved. The enhanced Wrec and the thermal stability are attributed to the reduced defects and grain boundaries in epitaxial PLZT thin films, making them promising for energy storage applications that require both high energy density, power density, and wide operation temperatures

Ferroelectric BaTiO3/SrTiO3 multilayered thin films for room-temperature tunable microwave elements

Ferroelectric BaTiO3/SrTiO3 with optimized c-axis-oriented multilayered thin films were epitaxially fabricated on (001) MgO substrates. The microstructural studies indicate that the in-plane interface relationships between the films as well as the substrate are determined to be (001)SrTiO3//(001)BaTiO3//(001)MgO and [100]SrTiO3//[100]BaTiO3//[100]MgO. The microwave (5 to 18 GHz) dielectric measurements reveal that the multilayered thin films have excellent dielectric properties with large dielectric constant, low dielectric loss, and high dielectric tunability, which suggests that the as-grown ferroelectric multilayered thin films can be developed for room-temperature tunable microwave elements and related device applications

DreamLLM: Synergistic Multimodal Comprehension and Creation

This paper presents DreamLLM, a learning framework that first achieves versatile Multimodal Large Language Models (MLLMs) empowered with frequently overlooked synergy between multimodal comprehension and creation. DreamLLM operates on two fundamental principles. The first focuses on the generative modeling of both language and image posteriors by direct sampling in the raw multimodal space. This approach circumvents the limitations and information loss inherent to external feature extractors like CLIP, and a more thorough multimodal understanding is obtained. Second, DreamLLM fosters the generation of raw, interleaved documents, modeling both text and image contents, along with unstructured layouts. This allows DreamLLM to learn all conditional, marginal, and joint multimodal distributions effectively. As a result, DreamLLM is the first MLLM capable of generating free-form interleaved content. Comprehensive experiments highlight DreamLLM's superior performance as a zero-shot multimodal generalist, reaping from the enhanced learning synergy.Comment: see project page at https://dreamllm.github.io

A Matrix Method for Determining Eigenvalues and Stability of Singular Neutral Delay-Differential Systems

The eigenvalues and the stability of a singular neutral differential system with single delay are considered. Firstly, by applying the matrix pencil and the linear operator methods, new algebraic criteria for the imaginary axis eigenvalue are derived. Second, practical checkable criteria for the asymptotic stability are introduced

Resin content calculation of carbon fiber/poly (ether ether ketone) by thermogravimetric analysis

Resin content of composites is a dominant factor of macroscopic properties and essential to study. Taking carbon fiber/poly (ether ether ketone) (CF/PEEK) composites molded by various means as examples, a method for resin content calculation obtained along with thermogravimetric analysis (TGA) for thermal properties analyzation was introduced. According to results of resin mass contents, TGA curves and differential thermogravimetric analysis (DTG) curves were divided to four stages, including non-decomposition stage of 25–500 °C, rapid decomposition stage of 500–600 °C, transitional stage of 600–700 °C and the stable stage of 700–800 °C. And resin contents were accurate obtained from the transitional stage and stable stage. Results tested by acid digestion method, ignition loss method and TGA methods were compared and it was proved that the TGA method was suitable for resin fraction calculation with a slight difference below 3% compared to results from the other two methods. By comparing results of different composites, we found that TGA methods can also be applied to other composites including reinforcements not disintegrate such as graphite, carbon nanotubes and matrix of thermosetting and thermoplastic decompose under inert gas in testing condition

A Power Load Forecasting Model Based on FA-CSSA-ELM

Accurate and stable power load forecasting methods are essential for the rational allocation of power resources and grid operation. Due to the nonlinear nature of power loads, it is difficult for a single forecasting method to complete the forecasting task accurately and quickly. In this study, a new combined model for power loads forecasting is proposed. The initial weights and thresholds of the extreme learning machine (ELM) optimized by the chaotic sparrow search algorithm (CSSA) and improved by the firefly algorithm (FA) are used to improve the forecasting performance and achieve accurate forecasting. The early local optimum that exists in the sparrow algorithm is overcome by Tent chaotic mapping. A firefly perturbation strategy is used to improve the global optimization capability of the model. Real values from a power grid in Shandong are used to validate the prediction performance of the proposed FA-CSSA-ELM model. Experiments show that the proposed model produces more accurate forecasting results than other single forecasting models or combined forecasting models