Superb thermal stability purple-blue phosphor through synergistic effect of emission compensation and nonradiative transition restriction of Eu2+

Phosphors with outstanding luminescence thermal stability are desirable for high-power phosphor-converted light-emitting diode (pc-LED) lightings. High structural rigidity and large bandgap of phosphor hosts are helpful to suppress nonradiative relaxation of optical centers and realize excellent thermal stability. Unfortunately, few host materials simultaneously possess aforementioned structural features. Herein, we confirm that Sr₃(PO₄)₂ (SPO) phosphate possesses high structural rigidity (Debye temperature, Θ_D = 559 K) and large bandgap (E_g = 8.313 eV) by density functional theory calculations. As expected, Eu²⁺-doped SPO purple-blue phosphors show extraordinary thermal stability. At 150/300 °C, SPO:5%Eu²⁺ presents emission loss of only 4%/8% and a predicated ultrahigh thermal quenching temperature of 973 °C. The most strikingly discoveries here are that thermal-induced emission compensation appears within two distinct Eu²⁺ sites of SPO host. The outstanding thermal stability, on one hand, is attributed to rigid structure and large bandgap of host that inhibits nonradiative relaxation of Eu²⁺ and on the other hand, the emission self-compensation of Eu²⁺. Benefiting from synergistic effect of emission compensation and nonradiative transition restriction of Eu²⁺, as-prepared SPO:5%Eu²⁺ purple-blue phosphor not only presents superior thermal stability but also high internal quantum efficiency of 95.1% and excellent hydrolysis resistant. Some advanced applications are explored including white LED lighting and wide-color-gamut display. Our work provides in-deep insights into structure-property relationships of thermally stable phosphors.     

多种超分辨荧光成像技术比较和进展评述

所见即所得是生命科学研究的中心哲学,贯穿在不断认识单个分子、分子复合体、分子动态行为和整个分子网络的历程中。活的动态的分子才是有功能的,这决定了荧光显微成像在生命科学研究中成为不可替代的工具。但是当荧光成像聚焦到分子水平的时候,所见并不能给出想要得到的。这个障碍是由于受光学衍射极限的限制,荧光显微镜无法在衍射受限的空间内分辨出目标物。超分辨荧光成像技术突破衍射极限的限制,在纳米尺度至单分子水平可视化生物分子,以前所未有的时空分辨率研究活细胞结构和动态过程,已成为生命科学研究的有力工具,并逐渐应用到材料科学、催化反应过程和光刻等领域。超分辨成像技术原理不同,其具有的技术性能各异,限制了各自特定的技术特色和应用范围。目前主流的超分辨成像技术包括3种:结构光照明显微镜技术(structured illumination microscopy, SIM)、受激发射损耗显微技术(stimulated emission depletion, STED)和单分子定位成像技术(single molecule localization microscopy, SMLM)。这些显微镜采用不同的复杂技术,但是策略却是相同和简单的,即通过牺牲时间分辨率来提升衍射受限的空间内相邻两个发光点的空间分辨。该文通过对这3种技术的原理比较和在生物研究中的应用进展介绍,明确了不同超分辨成像技术的技术优势和适用的应用方向,以方便研究者在未来研究中做合理的选择。     

Large scale synthesis of red emissive carbon dots powder by solid state reaction for fingerprint identification

Red emissive carbon dots(CDs) powder was synthesized on a large scale from phloroglucinol and boric acid by a novel solid state reaction with yield up to 75%. This method is safe and convenient, for it needs neither high pressure reactors nor complicated post-treatment procedures. The as-prepared carbon dots powder exhibited strong red fluorescence with excitation-independent behavior. XPS measurement and PL spectra suggest that such red fluorescence arise from boron-doped structures in CDs, which increases along with the boron concentration on CDs surface but decreases when the concentration quenching effect takes place. To overcome the aggregation induced fluorescence quenching of the solid CDs powder,the conventional methods are dispersing CDs into a large amount of inert substrates. But our present work provides a new strategy to realize strong red fluorescence of CDs in solid state. As a result, such carbon dots powder works well for latent fingerprint identification on various material surfaces.     

过渡态理论在化学体系中的2个应用实例*

在大学本科一二年级的物理化学教学中,化学动力学章节的学习涉及到对不同时间尺度的认识。本文利用过渡态理论得到的速率常数表达公式,以乙烷分子碳/碳单键旋转和水分子氢键交换的动力学过程为例,对这2个应用实例的动力学过程所发生的时间尺度做出估算。这些时间尺度的估算对于学生理解不同动力学过程的物理图像至关重要,同时也有助于加强学生对重要公式的理解并能够将这些公式在化学体系中灵活运用。     

考虑损伤的修正梯度弹性理论

梯度弹性理论在描述材料微结构起主导作用的力学行为时具有显著优势,将其与损伤理论相结合,可在材料破坏研究中考虑微结构的影响.基于修正梯度弹性理论,将应变张量、应变梯度张量和损伤变量作为Helmholtz自由能函数的状态变量,并在自然状态附近对自由能函数作Taylor展开,进而由热力学基本定律,推导出修正梯度弹性损伤理论本构方程的一般形式.编制有限元程序,模拟土样损伤局部化带的发展演化过程.结果表明,修正梯度弹性损伤理论消除了网格依赖性;损伤局部化带不是与损伤同时发生,而是在损伤发展到一定程度后再逐渐显现出来.     

Coupling of CFD Simulations and Population Balance Modeling to Predict Brownian Coagulation in an Emulsion Polymerization Reactor

In this study a framework consisting of a computational fluid dynamics simulation coupled to a population balance model for the modeling of emulsion polymerizations is proposed. The combined approach is used to understand the impact of changing length and time scales, as well as mixing conditions on the particle size distribution (PSD) of a polymer latex under different conditions. It is shown that the effect of agitation rate can have a profound impact on the distribution of ionic species in the reactor, and thus on the evolution of the PSD.

     

Bounded stationary reflection II

Bounded stationary reflection at a cardinal λ is the assertion that every stationary subset of λ reflects but there is a stationary subset of λ that does not reflect at arbitrarily high cofinalities. We produce a variety of models in which bounded stationary reflection holds. These include models in which bounded stationary reflection holds at the successor of every singular cardinal $\mu >{\mathrm{?}}_{\omega }$ and models in which bounded stationary reflection holds at ${\mu }^{+}$ but the approachability property fails at μ.     

应用图论分析与最优化理论来数据挖掘大规模水牛普里昂蛋白结构数据

图论、最优化理论显然在蛋白质结构的研究中大有用场. 首先, 调查/回顾了研究蛋白质结构的所有图论模型. 其后, 建立了一个图论模型: 让蛋白质的侧链来作为图的顶点, 应用图论的诸如团、 $k$-团、 社群、 枢纽、聚类等概念来建立图的边. 然后, 应用数学最优化的现代摩登数据挖掘算法/方法来分析水牛普里昂蛋白结构的大数据. 成功与令人耳目一新的数值结果将展示给朋友们.     

Maximum likelihood estimation for stochastic volatility in mean models with heavy‐tailed distributions

In this article, we introduce a likelihood‐based estimation method for the stochastic volatility in mean (SVM) model with scale mixtures of normal (SMN) distributions. Our estimation method is based on the fact that the powerful hidden Markov model (HMM) machinery can be applied in order to evaluate an arbitrarily accurate approximation of the likelihood of an SVM model with SMN distributions. Likelihood‐based estimation of the parameters of stochastic volatility models, in general, and SVM models with SMN distributions, in particular, is usually regarded as challenging as the likelihood is a high‐dimensional multiple integral. However, the HMM approximation, which is very easy to implement, makes numerical maximum of the likelihood feasible and leads to simple formulae for forecast distributions, for computing appropriately defined residuals, and for decoding, that is, estimating the volatility of the process. Copyright © 2017 John Wiley & Sons, Ltd.