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ZnSnN2 has potential applications in photocatalysis and photovoltaics. However, the difficulty in preparing nondegenerate ZnSnN2 hinders its device application. Here, the preparation of low-electron-density nanocrystalline ZnSnN2 and its device application are demonstrated. Nanocrystalline ZnSnN2 was prepared with reactive sputtering. Nanocrystalline ZnSnN2 with an electron density of approximately 1017 cm−3 can be obtained after annealing at 300 °C. Nanocrystalline ZnSnN2 is found to form Schottky contact with Ag. Both the current I vs. voltage V curves and the capacitance C vs. voltage V curves of these samples follow the related theories of crystalline semiconductors due to the limited long-range order provided by the crystallites with sizes of 2–10 nm. The I−V curves together with the nonlinear C−2−V curves imply that there are interface states at the Ag-nanocrystalline ZnSnN2 interface. The application of nanocrystalline ZnSnN2 to heterojunction solar cells is also demonstrated.

In this article we consider using a class of α-stable processes, which can be regarded as generalizations of the Gaussian processes, as the surrogate models for uncertainty quantification. We introduce a class of α-stable processes, whose finite-dimensional distributions can be represented using independent stable random variables. This representation allows for Bayesian inference for the proposed statistical model. We can obtain the posterior distributions for the untried points as well as the model parameters through an MCMC algorithm. The computation for the representation requires some geometrical information given by the design points. We propose an efficient algorithm to solve this computational geometry problem. Two examples are given to illustrate the proposed method and its potential advantages.

Computer simulation has increasingly become popular for analysis of systems that cannot be feasibly changed because of costs or scale. This work proposes a method to construct an emulator for stochastic simulations by performing a designed experiment on the simulator and developing an emulative distribution. Existing emulators have focused on estimation of the mean of the simulation output, but this work presents an emulator for the distribution of the output. This construction provides both an explicit distribution and a fast sampling scheme. Beyond the emulator description, this work demonstrates the emulator's efficiency, that is, its convergence rate is the asymptotically optimal among all possible emulators using the same sample size (under certain conditions). An example of its practical use is demonstrated using a stochastic simulation of fracture mechanics. Supplementary materials for this article are available online.

Many computer models contain unknown parameters which need to be estimated using physical observations. Tuo and Wu (2014) show that the calibration method based on Gaussian process models proposed by Kennedy and O'Hagan [J. R. Stat. Soc. Ser. B. Stat. Methodol. 63 (2001) 425-464] may lead to an unreasonable estimate for imperfect computer models. In this work, we extend their study to calibration problems with stochastic physical data. We propose a novel method, called the L₂ calibration, and show its semiparametric efficiency. The conventional method of the ordinary least squares is also studied. Theoretical analysis shows that it is consistent but not efficient. Numerical examples show that the proposed method outperforms the existing ones.

The thin plate spline smoother is a classical model for finding a smooth function from the knowledge of its observation at scattered locations which may have random noises. We consider a nonconforming Morley finite element method to approximate the model. We prove the stochastic convergence of the finite element method which characterizes the tail property of the probability distribution function of the finite element error. We also propose a self-consistent iterative algorithm to determine the smoothing parameter based on our theoretical analysis. Numerical examples are included to confirm the theoretical analysis and to show the competitive performance of the self-consistent algorithm for finding the smoothing parameter.

Filled high thermal conductivity epoxy composite solves the problem of the low thermal conductivity of the epoxy resin itself, but the addition of the thermal conductive filler reduces the mechanical properties of the composite, which limits its application in the field of high voltage insulation. In this work, carboxyl-terminated butadiene nitrile liquid rubber (CTBN) was used to toughen the boron nitride-epoxy hybrid system, and the effects of different contents of CTBN on the mechanical properties, thermal conductivity, glass transition temperature, thermal stability, and dielectric properties of the composites were investigated. The results showed that when the content of CTBN was 5–15 wt.%, the CTBN formed a dispersed island structure in the epoxy resin matrix. The toughness of the composite increased by about 32%, the breakdown strength was improved, and the thermal conductivity was about 160% higher than that of pure epoxy resin. As the CTBN content increased, the glass transition temperature and thermal stability of the composite decreased and the dielectric constant and the dielectric loss increased. When the CTBN content is 10–15 wt.%, a toughened epoxy composite material with better comprehensive properties is obtained.

Markov chain Monte Carlo ( MCMC) methods require a large number of samples to approximate a posterior distribution, which can be costly when the likelihood or prior is expensive to evaluate. The number of samples can be reduced if we can avoid repeated samples and those that are close to each other. This is the idea behind deterministic sampling methods such as quasi-Monte Carlo (QMC). However, the existing QMC methods aim at sampling from a uniform hypercube, which can miss the high probability regions of the posterior distribution and thus the approximation can be poor. Minimum energy design (MinED) is a recently proposed deterministic sampling method, which makes use of the posterior evaluations to obtain a weighted space-filling design in the region of interest. However, the existing implementation of MinED is inefficient because it requires several global optimizations and thus numerous evaluations of the posterior. In this article, we develop an efficient algorithm that can generate MinED samples with few posterior evaluations. We also make several improvements to the MinED criterion to make it perform better in high dimensions. The advantages of MinED over MCMC and QMC are illustrated using an example of calibrating a friction drilling process.

[目的 /意义]探索政务新媒体的传播特点能够对政务新媒体未来发展方向提供更深层的洞见,有助于相关机构或部门在未来的社会治理中更及时地传播信息并且更好地服务民生.[方法 /过程]研究工作选取微博、微信、抖音三大政务新媒体信息平台,爬取平台发布的信息内容以及对应的用户点赞量、评论量、转发量.基于各平台的信息传播影响力指标,并结合发布时间、内容类型、推送形式,分析不同政务新媒体平台信息传播影响力.[结果 /结论]研究结果表明,短视频政务新媒体平台在信息传播活性方面具有优异的表现;信息内容以及事件类型等差异使其适合不同的推送形式;各类政务新媒体应该形成多平台渠道互补.

The detection of platelet-specific antibodies plays an important role  in the clinical diagnosis of primary immune thrombocytopenia (ITP). MAIPA assay and PakAuto assay are the two main methods for this purpose. However, a comprehensive comparative evaluation of these techniques in clinical practice remains lacking. In this study, we collected 48 patients with thrombocytopenia. MAIPA and PakAuto are used to examine platelet-specific  antibodies synchronously. Based on methodologies and analysis of experimental results, we conclude that PakAuto assay with a high sensitivity and accuracy can offer higher throughput and broader human platelet antibodies detection capabilities, making it more suitable for screening.