Ligand Design in Atomically Precise Copper Nanoclusters and Their Application in Electrocatalytic Reactions

Metal nanoclusters (MNCs) are compositionally well-defined and also structurally precise materials with unique molecule-like properties and discrete electronic energy levels. Atomically precise ligand-protected Cu nanoclusters (LP-CuNCs) are one category of typical MNCs that usually demonstrate unique geometric and electronic structures to serve as electrocatalysts. However, the synthesis, application, as well as structure-performance relationship of LP-CuNCs are not adequately studied. Significantly, the ligands are essential to the geometric structure, crystal structure, size, and electronic structure of LP-CuNCs, which determine their physiochemical properties and applications. In this review, significant progress in the ligand design of LP-CuNCs, and their application in electrocatalytic reactions is introduced. The general basics of ligand-protected MNCs (LP-MNCs) are first introduced and the functions of ligands are emphasized. Subsequently, a series of different ligands for LP-CuNCs including thiolates, phosphines, alkynyl, polymers, and biomolecules are highlighted. Thereafter, their applications in different electrocatalytic reactions are discussed. It is believed that this review will not only inspire the design and synthesis of novel LP-CuNCs, but also contribute to the extension of their applications in electrocatalytic reactions and the establishment of accurate structure-performance relationships.     

Composite bending-dominated hollow nanolattices: A stiff,cyclable mechanical metamaterial

Manufacturing ultralight and mechanical reliable materials has been a long-time challenge. Ceramic-based mechanical metamaterials provide significant opportunities to reverse their brittle nature and unstable mechanical properties and have great potential as strong, ultralight, and ultrastiff materials. However, the failure of ceramics nanolattice and degradation of strength/modulus with decreasing density are caused by buckling of the struts and failure of the nodes within the nanolattices, especially during cyclic loading. Here, we explore a new class of 3D ceramic-based metamaterials with a high strength–density ratio, stiffness, recoverability, cyclability, and optimal scaling factor. Deformation mode of the fabricated nanolattices has been engineered through the unique material design and architecture tailoring. Bending-dominated hollow nanolattice (B-H-Lattice) structure is employed to take advantages of its flexibility, while a few nanometers of carbonized mussel-inspired bio-polymer (C-PDA) is coherently deposited on ceramics’ nanolayer to enable non-buckling struts and bendable nodes during deformation, resulting in reliable mechanical properties and outperforming the current bending-dominated lattices (B-Lattices) and carbon-based cellulose materials. Meanwhile, the structure has comparable stiffness to stretching-dominated lattices (S-Lattices) while with better cyclability and reliability. The B-H-Lattices exhibit high specific stiffness (>10⁶?Pa·kg^?1·m^?3), low-density (～30?kg/m³), buckling-free recovery at 55% strain, and stable cyclic loading behavior under up to 15% strain. As one of the B-Lattices, the modulus scaling factor reaches 1.27, which is lowest among current B-Lattices. This study suggests that non-buckling behavior and reliable nodes are the key factors that contribute to the outstanding mechanical performance of nanolattice materials. A new concept of engineering the internal deformation behavior of mechanical metamaterial is provided to optimize their mechanical properties in real service conditions.     

造纸过程水分智能控制

针对造纸过程的复杂性、工艺特点及要求，本文对造纸过程的水分控制，提出模糊控制和专家系统结合的智能控制方法。实践证明该控制器满足了造纸过程对水分的工艺要求，且具有良好的鲁棒性。     

新型多苯并咪唑环芳识别氨基酸甲酯的分子动力学和密度泛函研究

采用Gaussian 03在B3LYP/6-31G(d)水平上分别优化新型多苯并咪唑环芳(MBICP)受体和氨基酸甲酯(AAME)配体,再用基于模拟退火的分子动力学方法 CDOCKER将配体与受体对接,对每一个复合物获得了一组最低能量的初始构象。最后用Turbomole在BLYP/def-TZVP水平对初始构象进一步优化,并对收敛后的复合物最低能量构象作NBO分析。以密度泛函理论计算获得的相互作用能作为核心参数,采用组合策略建立了表达MBICP-AAME复合物结合常数的定量关系模型,计算了该类复合物的结合常数。对MBICP受体和AAME配体间的作用模式以及影响MBICP受体识别AAME配体的主要因素,作了深入讨论。     

引入信息预处理的多状态二进制改进算法

针对多状态二进制防碰撞算法通讯数据存在冗余的情况,引入信息预处理与阅读器部分接收机制。在识别过程只处理冲突位,阅读器只接收并记录标签部分数据,尽量避免数据重复发送与接收,状态标志根据不同指令做变化,减少交互次数,从而降低通讯数据量。采用Java进行算法模拟仿真,结果表明,在碰撞位不连续,碰撞位冲突率低于25%时,算法在减少通讯量方面,具有明显优势。若不计入预处理过程,该算法在任何碰撞位冲突率下通讯数据量都有较大优势。     

模铸连浇中间包控流装置优化的水模实验

通过水力学模拟实验,优化了模铸连浇中间包控流装置。结果表明,安装控流装置,并将开孔设于挡墙下部正中间时,流体在中间包内的停留时间较长,死区体积最小,夹杂物上浮率也较高,而且不存在短路流。因此,经过控流装置优化,流体在中间包内的流场也得到明显改善,流动模式较合理,有利于钢中夹杂物的上浮去除,可以保证浇注大钢锭的质量。     

视场非完全重叠的分布式雷达多目标跟踪方法

在探测能力、波形设计及天线指向等因素制约下,分布式雷达视场并非完全重合,由此造成的观测信息差异给后续信息融合带来了巨大挑战。该文基于高斯混合实现的集势概率假设密度(CPHD)滤波器,提出了一种视场部分重叠下的分布式雷达多目标跟踪方法。首先,利用多目标密度乘积切分出概率假设密度(PHD)中表征共同观测信息的部分;之后,标准的分布式融合(算术平均或几何平均融合)方法作用于切分出的共同观测目标信息以提升跟踪性能,补偿融合则作用于雷达单独观测目标信息以扩展视场范围。该文方法无须视场先验信息,能够适应雷达视场未知时的分布式融合多目标跟踪场景。仿真实验验证了所提出方法在未知、时变雷达视场下跟踪多目标的性能,表明了该文方法比基于高斯混合的聚类方法性能更好。      

基于多尺度卷积特征融合的癫痫脑电信号识别

脑电信号(electroencephalography,EEG)已成为医生诊断神经系统疾病最 广泛使用的工具,实现癫痫EEG的自动识别对 于癫痫患者的临床诊断和治疗具有重要意义。为了提高癫痫EEG的识别精度,提出了一 种基于多尺 度卷积特征融合的癫痫EEG自动识别模型。首先采用多尺度卷积特征融合方法提取多粒 度数据特征, 实现卷积神经网络(convolutional neural network,CNN)中不同层次的信息互补;然后经过长短期记忆网络(long short-term memory network,LSTM)提取时间 特征,利用 softmax分类器给出最终的识别结果。为了评估提出方法的识别性能,在波恩大学癫痫病研 究中心数据集 中进行实验,并与CNN-LSTM模型、单一的LSTM等模型的识别性能进行了比较,实验结果表 明,提出 方法的识别精度明显高于其余方法, 平均可达到99.19%。该模型能够 有效识别癫痫EEG类别,具有较高的识别性能和临床应用潜力。     

A New Strategy to Effectively Suppress the Initial Capacity Fading of Iron Oxides by Reacting with LiBH4

In this work, a new facile and scalable strategy to effectively suppress the initial capacity fading of iron oxides is demonstrated by reacting with lithium borohydride (LiBH₄) to form a B‐containing nanocomposite. Multielement, multiphase B‐containing iron oxide nanocomposites are successfully prepared by ball‐milling Fe₂O₃ with LiBH₄, followed by a thermochemical reaction at 25–350 °C. The resulting products exhibit a remarkably superior electrochemical performance as anode materials for Li‐ion batteries (LIBs), including a high reversible capacity, good rate capability, and long cycling durability. When cycling is conducted at 100 mA g^?1, the sample prepared from Fe₂O₃–0.2LiBH₄ delivers an initial discharge capacity of 1387 mAh g^?1. After 200 cycles, the reversible capacity remains at 1148 mAh g^?1, which is significantly higher than that of pristine Fe₂O₃ (525 mAh g^?1) and Fe₃O₄ (552 mAh g^?1). At 2000 mA g^?1, a reversible capacity as high as 660 mAh g^?1 is obtained for the B‐containing nanocomposite. The remarkably improved electrochemical lithium storage performance can mainly be attributed to the enhanced surface reactivity, increased Li⁺ ion diffusivity, stabilized solid‐electrolyte interphase (SEI) film, and depressed particle pulverization and fracture, as measured by a series of compositional, structural, and electrochemical techniques.