Chalcogenide Ovonic Threshold Switching Selector

Today’s explosion of data urgently requires memory technologies capable of storing large volumes of data in shorter time frames,a feat unattain-able with Flash or DRAM.Intel Optane,commonly referred to as three-dimensional phase change memory,stands out as one of the most promising candidates.The Optane with cross-point architecture is constructed through layering a storage element and a selector known as the ovonic threshold switch(OTS).The OTS device,which employs chalcogenide film,has thereby gathered increased attention in recent years.In this paper,we begin by providing a brief introduction to the discovery process of the OTS phenomenon.Subsequently,we summarize the key elec-trical parameters of OTS devices and delve into recent explorations of OTS materials,which are categorized as Se-based,Te-based,and S-based material systems.Furthermore,we discuss various models for the OTS switching mechanism,including field-induced nucleation model,as well as several carrier injection models.Additionally,we review the progress and innovations in OTS mechanism research.Finally,we highlight the successful application of OTS devices in three-dimensional high-density memory and offer insights into their promising performance and extensive prospects in emerging applications,such as self-selecting memory and neuromorphic computing.

The Analysis of the Correlation between SPT and CPT Based on CNN-GA and Liquefaction Discrimination Research

The objective of this study is to investigate themethods for soil liquefaction discrimination. Typically, predicting soilliquefaction potential involves conducting the standard penetration test (SPT), which requires field testing and canbe time-consuming and labor-intensive. In contrast, the cone penetration test (CPT) provides a more convenientmethod and offers detailed and continuous information about soil layers. In this study, the feature matrix based onCPT data is proposed to predict the standard penetration test blow count N. The featurematrix comprises the CPTcharacteristic parameters at specific depths, such as tip resistance qc, sleeve resistance f s, and depth H. To fuse thefeatures on the matrix, the convolutional neural network (CNN) is employed for feature extraction. Additionally,Genetic Algorithm (GA) is utilized to obtain the best combination of convolutional kernels and the number ofneurons. The study evaluated the robustness of the proposed model using multiple engineering field data sets.Results demonstrated that the proposed model outperformed conventional methods in predicting N values forvarious soil categories, including sandy silt, silty sand, and clayey silt. Finally, the proposed model was employedfor liquefaction discrimination. The liquefaction discrimination based on the predicted N values was comparedwith the measured N values, and the results showed that the discrimination results were in 75% agreement. Thestudy has important practical application value for foundation liquefaction engineering. Also, the novel methodadopted in this research provides new ideas and methods for research in related fields, which is of great academicsignificance.

Development of a Novel Feedforward Neural Network Model Based on Controllable Parameters for Predicting Effluent Total Nitrogen

The problem of effluent total nitrogen(TN)at most of the wastewater treatment plants(WWTPs)in China is important for meeting the related water quality standards,even under the condition of high energy consumption.To achieve better prediction and control of effluent TN concentration,an efficient prediction model,based on controllable operation parameters,was constructed in a sequencing batch reactor process.Compared with previous models,this model has two main characteristics:①Superficial gas velocity and anoxic time are controllable operation parameters and are selected as the main input parameters instead of dissolved oxygen to improve the model controllability,and②the model prediction accuracy is improved on the basis of a feedforward neural network(FFNN)with algorithm optimization.The results demonstrated that the FFNN model was efficiently optimized by scaled conjugate gradient,and the performance was excellent compared with other models in terms of the correlation coefficient(R).The optimized FFNN model could provide an accurate prediction of effluent TN based on influent water parameters and key control parameters.This study revealed the possible application of the optimized FFNN model for the efficient removal of pollutants and lower energy consumption at most of the WWTPs.

LaBr_(3)(Ce)-CsI(Tl)紧凑式叠层反康伽马探测器研制

本工作研制了一套由圆柱形LaBr_(3)(Ce)主晶体和井形CsI(Tl)次晶体组成的叠层伽马探测器,该探测器主要用于鉴别来自LaBr_(3)(Ce)主晶体的康普顿散射光子并进行反符合测量。两种不同的晶体耦合到同一个光电倍增管上。入射辐射沉积在每一层探测器的能量,可以通过PMT给出的信号脉冲形状差异进行识别。利用Geant4模拟结果,验证了脉冲形状甄别性能和康普顿散射抑制效果。利用^(60)Co伽马源对探测器进行了实验测试,测试结果表明,该探测器本底抑制系数为2.33(1),达到了康普顿本底抑制两倍以上的预期目标。

Fast UV-vis-NIR photoresponse of self-oriented F_(16)CuPc nanoribbons

Controlling the vapor-deposited nanoribbons to grow along a consistent orientation will enable the desired in situ integration of functional devices,representing a major technological advance compared to post-growth processing strategies.In this work,ntype F_(16)CuPc molecules are self-assembled into horizontally-oriented nanoribbons with a consistent growth axis after creating periodic hydrophobic nanogrooves on a sapphire surface.Consequently,electrodes are deposited directly on the growth substrate to enable in situ fabrication of photodetectors.Depending on the deposited electrodes,these horizontally-oriented nanoribbons are connected to form a monolithic photodetector with a large sensing area or an on-chip array of photodetectors with multiple detector units.This in situ integration strategy avoids potential structural damage and contamination from impurities associated with post-growth processing steps.Therefore,the vapor-deposited nanoribbons can retain their high quality during the device manufacturing process,which contributes to performance improvement.As a result,the in-situ integrated F_(16)CuPc photodetectors exhibit a sensitive response in the ultraviolet-visible-near-infrared(UV-vis-NIR)region.The response time is on the order of tens of milliseconds,the fastest record ever for the F_(16)CuPc-based photodetectors.Furthermore,statistics from an array of 6×6 photodetectors show little variation in their sensitivity and response time,and hence this in situ fabrication scheme will contribute to the implementation of on-chip integrated photodetectors with consistent performance based on bottom-up nanoribbons.Overall,this self-oriented growth provides a versatile option to achieve desired in-situ integrated functional devices based on bottom-up nanoribbons.

Clustering-triggered phosphorescence of nonconventional luminophores

Nonconventional luminophores have attracted significant attention for their unique photophysical properties and potential applications in different areas.Unlike classic luminogens consisting of remarkably conjugated segments,nonconventional luminophores generally possess merely nonconjugated or short-conjugated structures based on electron-rich units.Fluorescence,phosphorescence,and even color tunable room temperature phosphorescence(RTP)could be readily obtained from these unique luminophores.Herein,we summarized recent advances in the phosphorescence of nonconventional luminophores,with focus on RTP and color tunable RTP.The clustering-triggered emission(CTE)mechanism could be applied to explain the luminescence as clustering-triggered phosphorescence(CTP).Furthermore,strategies toward the RTP regulation are summarized,and corresponding applications are demonstrated.

聚集诱导发光

聚集诱导发光(AIE)是唐本忠院士于2001年提出的一个科学概念,是指一类在溶液中不发光或者发光微弱的分子聚集后发光显著增强的现象。高效固态发光的AIE材料有望从根本上解决有机发光材料面临的聚集导致发光猝灭难题,具有重大的实际应用价值。从分子内旋转受限到分子内运动受限,从聚集诱导发光到聚集体科学,AIE领域已经取得了许多原创性的成果。在本综述中,我们从AIE材料的分类、机理、概念衍生、性能、应用和挑战等方面讨论了AIE领域最近取得的显著进展。希望本综述能激发更多关于分子聚集体的研究,并推动材料、化学和生物医学等学科的进一步交叉融合和更大发展。

Study of Pressure Balance for Press-Pack IGBTs and Its Influence on Temperature Distribution

Pressure balance is a key technology for Press-Pack IGBT packaging,and is studied in this paper with its influence on the temperature distribution discussed in further when the device is turned on.By establishing the physical model of the Press-Pack IGBT device in the finite element simulation software,the influence of the internal flatness condition on the pressure balance is analyzed,and the variation of the average pressure difference with the flatness in different parallel scale of the chips is obtained.The thermal contact resistance and the electrical contact resistance parameters,which are dependent on the pressure,are then imported to perform the multi-field coupling,further investigating the effect of different pressure distributions on temperature distribution.The junction-case thermal resistance of the device with different flatness is compared experimentally.The results have demonstrated the influence of the flatness on the thermal resistance of the Press-Pack IGBT device.