碳纤维增强环氧树脂基复合材料低温改性研究进展

随着航天、应用超导技术和大型低温工程等高科技的迅猛发展,高性能碳纤维增强环氧树脂基复合材料在低温下的应用愈来愈受到人们的重视。论文综述了近年来碳纤维增强环氧树脂基复合材料低温改性的研究进展,并展望了其未来的发展方向。     

石化企业挥发性有机物无组织排放监测技术进展

无组织排放占石化企业挥发性有机物（VOCs）排放的主导地位,排放点多、面广、量大、分散、无规则,总体表现为大型面源或体积源,监测难度很大。本文评述了点、线和面(通量)等VOCs无组织排放监测技术及应用进展,总结了石化企业VOCs无组织排放监测存在的主要问题与难点,提出了石化企业VOCs无组织排放监测体系及适用监测技术。总体上,石化企业VOCs无组织排放监控存在排放清单质量不高、源头监测及溯源困难、排放烟羽及其迁移扩散途径无定形、厂界等开放空间难以封闭监测、常规监测的时间和空间覆盖有限等问题或技术难点,可复合应用点、线、面及通量监测技术,结合常规离线、实时在线、排放通量、移动快速响应等监测设计,构建覆盖排放与环境影响的多元化、网络化、立体化监控体系。未来石化企业VOCs无组织排放监控将向多层级、智能化和大数据应用发展。     

仓储电子标签辅助拣货系统的研究与设计

介绍了一种电子标签辅助拣货系统,提出了分层分级的设计思想,为大型仓储快速拣货的需要提供了可行的解决方案.设计了中间控制层和终端电子标签,系统通过RS485通信,指令数据传输稳定,通信距离远.     

面向大规模天线系统的稀布阵技术研究与评估

通过大量天线数服务用户,大规模天线技术可有效提升频谱效率。然而,大规模天线将带来射频链路数量的大幅增加,进而带来成本的急剧提升,所以大规模天线的设计需要综合考虑性能和成本的折中。稀布阵技术通过优化天线阵元位置分布、激励幅度,可实现以更少的天线数逼近均匀阵列的性能,从而带来射频链路数量的降低和成本的控制,取得较好的性价比平衡。介绍了稀布阵关键技术的实现方案,评估分析了稀布阵的链路级性能以及在面向6G的大规模天线系统中应用稀布阵的系统性能。数据分析表明,稀布阵在小幅性能损失的情况下,可以显著降低天线阵元数,节约基站设备成本。     

Artificial Intelligence-Empowered Resource Management for Future Wireless Communications: A Survey

How to explore and exploit the full potential of artificial intelligence(AI)technologies in future wireless communications such as beyond 5G(B5G)and 6G is an extremely hot inter-disciplinary research topic around the world.On the one hand,AI empowers intelligent resource management for wireless communications through powerful learning and automatic adaptation capabilities.On the other hand,embracing AI in wireless communication resource management calls for new network architecture and system models as well as standardized interfaces/protocols/data formats to facilitate the large-scale deployment of AI in future B5G/6G networks.This paper reviews the state-of-art AI-empowered resource management from the framework perspective down to the methodology perspective,not only considering the radio resource(e.g.,spectrum)management but also other types of resources such as computing and caching.We also discuss the challenges and opportunities for AI-based resource management to widely deploy AI in future wireless communication networks.     

低磨料浓度的碱性铜抛光液平坦化性能的研究

A novel alkaline copper slurry that possesses a relatively high planarization performance is investigated under a low abrasive concentration.Based on the action mechanism of CMP,the feasibility of using one type of slurry in copper bulk elimination process and residual copper elimination process,with different process parameters,was analyzed.In addition,we investigated the regular change of abrasive concentration effect on copper and tantalum removal rate and within wafer non-uniformity(WIWNU) in CMP process.When the abrasive concentration is 3 wt%,in bulk elimination process,the copper removal rate achieves 6125 °/min,while WIWNU is 3.5%,simultaneously.In residual copper elimination process,the copper removal rate is approximately 2700°/min,while WIWNU is 2.8%.Nevertheless,the tantalum removal rate is 0 °/min,which indicates that barrier layer isn’t eliminated in residual copper elimination process.The planarization experimental results show that an excellent planarization performance is obtained with a relatively high copper removal rate in bulk elimination process.Meanwhile,after residual copper elimination process,the dishing value increased inconspicuously,in a controllable range,and the wafer surface roughness is only 0.326 nm(sq < 1 nm) after polishing.By comparison,the planarization performance and surface quality of alkaline slurry show almost no major differences with two kinds of commercial acid slurries after polishing.All experimental results are conducive to research and improvement of alkaline slurry in the future.     

A Centimeter‐Scale Inorganic Nanoparticle Superlattice Monolayer with Non‐Close‐Packing and its High Performance in Memory Devices

Due to the near‐field coupling effect, non‐close‐packed nanoparticle (NP) assemblies with tunable interparticle distance (d) attract great attention and show huge potential applications in various functional devices, e.g., organic nano‐floating‐gate memory (NFGM) devices. Unfortunately, the fabrication of device‐scale non‐close‐packed 2D NPs material still remains a challenge, limiting its practical applications. Here, a facile yet robust “rapid liquid–liquid interface assembly” strategy is reported to generate a non‐close‐packed AuNP superlattice monolayer (SM) on a centimeter scale for high‐performance pentacene‐based NFGM. The d and hence the surface plasmon resonance spectra of SM can be tailored by adjusting the molecular weight of tethered polymers. Precise control over the d value allows the successful fabrication of photosensitive NFGM devices with highly tunable performances from short‐term memory to nonvolatile data storage. The best performing nonvolatile memory device shows remarkable 8‐level (3‐bit) storage and a memory ratio over 10⁵ even after 10 years compared with traditional devices with a AuNP amorphous monolayer. This work provides a new opportunity to obtain large area 2D NPs materials with non‐close‐packed structure, which is significantly meaningful to microelectronic, photovoltaics devices, and biochemical sensors.     

脂肪酸甲酯的合成及综合应用

脂肪酸甲酯作为一种新型环保可再生资源而受到广泛的关注。分析介绍了脂肪酸甲酯在不同领域的应用。重点阐述了脂肪酸甲酯在表面活性剂、树脂的合成、农药助剂方面以及化工领域方面的应用。同时,还介绍了合成脂肪酸甲酯的制备工艺及催化方法,包括传统液体酸碱催化、固体酸碱催化剂、离子液体催化、生物酶催化及新型催化技术。     

Iterative Identification Algorithms for Bilinear-in-parameter Systems by Using the Over-parameterization Model and the Decomposition

This paper focuses on the identification problem for a class of bilinear-in-parameter systems with an additive noise modeled by an autoregressive moving average process. By using the over-parameterization model, the special form of the bilinear term can be obtained by the model equivalent transformation. Then, we use a decomposition of the model into two synthetic models in order to separate the effect of the two sets of parameters, i.e., the coefficients of the nonlinear basis functions from the parameters of the colored noise. Moreover, two decomposition based iterative algorithms are proposed to identify the unknown parameters. A numerical example is presented to confirm the effectiveness of the proposed methods.     

On selection of optimal cuts in complete multi-scale decision tables

In this paper, a novel optimal scale selection method in complete multi-scale decision tables has been proposed. Unlike the existing approaches in the literature, we employ the tools of granularity trees and cuts for each attribute. Each granularity tree has many different local cuts, which represent various scale selection methods under a specific attribute. Different local cuts collectively forms a global cut of a multi-scale information table, which in turn induces an information table with a mixed scale. One distinct feature of such tables is that the attribute values of different objects may be obtained at different scales for the same attribute. By keeping maximal consistency of the derived mixed-scale decision table, we introduce the notions of optimal cuts in multi-scale decision tables. Then, a comparative study between different types of optimal scale selection methods is performed. Finally, an algorithm is designed to verify the validity of the proposed approach.