不稳定燃烧主动控制系统的设计与实现

为了满足发展不稳定燃烧的主动控制技术的需求,针对发动机不稳定燃烧主动控制需要处理大量数据且处理速度较高要求的问题,利用DSP强大的数据处理能力,设计和实现了基于TMS320F2812的发动机不稳定燃烧主动控制系统。     

Future Event Prediction Based on Temporal Knowledge Graph Embedding

Accurate prediction of future events brings great benefits and reduces losses for society in many domains, such as civil unrest, pandemics, and crimes. Knowledge graph is a general language for describing and modeling complex systems. Different types of events continually occur, which are often related to historical and concurrent events. In this paper, we formalize the future event prediction as a temporal knowledge graph reasoning problem. Most existing studies either conduct reasoning on static knowledge graphs or assume knowledges graphs of all timestamps are available during the training process. As a result, they cannot effectively reason over temporal knowledge graphs and predict events happening in the future. To address this problem, some recent works learn to infer future events based on historical event-based temporal knowledge graphs. However, these methods do not comprehensively consider the latent patterns and influences behind historical events and concurrent events simultaneously. This paper proposes a new graph representation learning model, namely Recurrent Event Graph ATtention Network (RE-GAT), based on a novel historical and concurrent events attention-aware mechanism by modeling the event knowledge graph sequence recurrently. More specifically, our RE-GAT uses an attention-based historical events embedding module to encode past events, and employs an attention-based concurrent events embedding module to model the associations of events at the same timestamp. A translation-based decoder module and a learning objective are developed to optimize the embeddings of entities and relations. We evaluate our proposed method on four benchmark datasets. Extensive experimental results demonstrate the superiority of our RE-GAT model comparing to various baselines, which proves that our method can more accurately predict what events are going to happen.     

基于云端充电数据的锂电池组一致性评价方法

在电动汽车(electric vehicle,EV)的使用过程中,电池组内单体间的不一致性增加趋势是不可避免的。电池成组后的单体不一致可能导致电池组提前失效,甚至引发安全问题。随着云端数据的广泛应用,EV的数据可被监测,这些数据能用来评估EV的安全性和电池组一致性。虽然EV上的数据采样频率较高,但云端数据的记录频率较低(约为10～30s),而充电数据采样时间间隔可达到10s以内,因此,云端的充电数据更适合用来评估EV的电池组一致性。以锂离子电池组为研究对象,提出了一种基于云端充电数据的电池组一致性评价方法。基于云端的充电数据,对5项指标进行分析和评价,包括电压一致性、温度一致性、内阻一致性、容量一致性和电量一致性。为了对电池组一致性综合评分,提出了一种加权评分体系,进一步利用模糊层次分析法(fuzzy analytic hierarchy process,FAHP)确定权重系数。最后,基于此评分体系将3个电池组进行实验并进行评分,实验结果表明所提评价方法能有效地区分和定量描述各电池组的一致性。此外,EV数据分析结果表明,该方法可有效地应用于工程中,并能在事故发生前检测出一致性问题,从而...     

The Electrochemical Response of Single Crystalline Copper Nanowires to Atmospheric Air and Aqueous Solution

In this paper, single crystalline copper nanowires (CuNWs) have been electrochemically grown through anodic aluminum oxide template. The environmental stability of the as‐obtained CuNWs in both 40% relative humidity (RH) atmosphere and 0.1 m NaOH aqueous solution has been subsequently studied. In 40% RH atmosphere, a uniform compact Cu₂O layer is formed as a function of exposure time following the logarithmic law and epitaxially covers the CuNW surfaces. It is also found that the oxide layers on CuNWs are sequentially grown when subjected to the cyclic voltammetry measurement in 0.1 m NaOH solution. An epitaxially homogeneous Cu₂O layer is initially formed over the surface of the CuNW substrates by solid‐state reaction (SSR). Subsequently, the conversion of Cu₂O into epitaxial CuO based on the SSR takes place with the increase of applied potential. This CuO layer is partially dissolved in the solution forming Cu(OH)₂, which then redeposited on the CuNW surfaces (i.e., dissolution‐redeposition (DR) process) giving rise to a mixed polycrystalline CuO/Cu(OH)₂ layer. The further increase of applied potential allows the complete oxidation of Cu₂O into CuO to form a dual‐layer structure (i.e., CuO inner layer and Cu(OH)₂ outer layer) with random orientations through an enhanced DR process.     

NiCo-selenide as a novel catalyst for water oxidation

The design and fabrication of sustainable and efficient electrocatalyst for water splitting are crucial for rechargeable metal-air batteries and regenerative fuel cells. In this report, a highly stable and active NiCo-selenide electrocatalyst was successfully prepared by a facile two-step solvothermal approach. In 0.1 M KOH alkaline electrolyte solution, the novel NiCo-selenide electrocatalyst afforded the current density of 10 mA cm^?2 at a lower overpotential of 393 mV, a smaller Tafel slope of ~89 mV dec^?1 and better stability, compared with NiCo-based oxide and sulfide.     

超声换能器检测方法的研究

超声检测技术广泛使用在无损检测领域中,而换能器是超声工程中极其重要的技术和分支领域。超声换能器是一种电声能量转换器件,是超声检测技术中的关键,直接影响无损检测结果的可靠性,本文阐述了超声换能器的原理和测量接触换能器的检测方法,分析了A型换能器脉冲回波灵敏度校准的不确定度。     

一种在硅材料表面组装金纳米颗粒的新方法

以氯金酸、L-半胱氨酸为反应试剂,利用内电流和金硫自组装效应,在硅材料表面组装了较为均一的金纳米颗粒,并利用荧光分析与硅纳米线场效应晶体管对该方法进行了相关验证。结果表明:经氢氟酸处理后的硅材料,在氯金酸和L-半胱氨酸混合溶液中反应3min可在硅表面得到较为均匀、稳定的金纳米颗粒层,其中,氯金酸浓度为0.5mmol/L,氯金酸和L-半胱氨酸浓度比为3∶1。荧光分析表明该方法组装的金颗粒表面已氨基功能化,使得金纳米颗粒修饰的硅材料在应用于生物检测时可直接醛基化修饰蛋白,简化了实验操作。同时,该方法可以在硅纳米线场效应晶体管中特异性组装金纳米颗粒,有力地支持了相关器件在疾病检测方面的应用。     

Ultrathin 2D Zirconium Metal–Organic Framework Nanosheets: Preparation and Application in Photocatalysis

Synthesizing ultrathin 2D metal–organic framework nanosheets in high yields has received increasing research interest but remains a great challenge. In this work, ultrathin zirconium‐porphyrinic metal–organic framework (MOF) nanosheets with thickness down to ≈1.5 nm are synthesized through a pseudoassembly–disassembly strategy. Owing to the their unique properties originating from their ultrathin thickness and highly exposed active sites, the as‐prepared ultrathin nanosheets exhibit far superior photocatalysis performance compared to the corresponding bulk MOF. This work highlights new opportunities in designing ultrathin MOF nanosheets and paves the way to expand the potential applications of MOFs.     

Three-dimensional macroscale assembly of Pd nanoclusters

Construction of macro-materials with highly oriented microstructures and well-connected interfaces between building blocks is significant for a variety of applications. However, it is still challenging to confine the desired structures. Thus, well-defined building blocks would be crucial to address this issue. Herein, we present a facile process based on 1.8 nm Pd nanoclusters (NCs) to achieve centimeter-size assemblages with aligned honeycomb structures, where the diameter of a single tubular moiety is ～4 μm. Layered and disordered porous assemblages were also obtained by modulating the temperature in this system. The reconciled interactions between the NCs were crucial to the assemblages. As a comparison, 14 nm Pd nanoparticles formed only aggregates. This work highlights the approach of confining the size of the building blocks in order to better control the assembly process and improve the stability of the structures.

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