Atomic-scale simulations for lithium dendrite growth driven by strain gradient

Dendrite formation is a major obstacle, e.g., capacity loss and short circuit, to the next-generation high-energy-density lithium (Li)-metal batteries. The development of successful Li dendrite mitigation strategies is impeded by an insufficient understanding in Li dendrite growth mechanisms. The Li-plating-induced internal stress in Li-metal and its effects on dendrite growth have been widely studied, but the underlying microcosmic mechanism is elusive. In the present study, the role of the plating-induced stress in dendrite formation is analyzed through first-principles calculations and ab initio molecular dynamic (AIMD) simulations. It is shown that the deposited Li forms a stable atomic nanofilm structure on the copper (Cu) substrate, and the adsorption energy of Li atoms increases from the Li-Cu interface to the deposited Li surface, leading to more aggregated Li atoms at the interface. Compared with the pristine Li-metal, the deposited Li in the early stage becomes compacted and suffers the in-plane compressive stress. Interestingly, there is a giant strain gradient distribution from the Li-Cu interface to the deposited Li surface, making the deposited atoms adjacent to the Cu surface tend to press upwards with perturbation and causing the dendrite growth. This provides an insight into the atomicscale origin of Li dendrite growth, and may be useful for suppressing the Li dendrite in Li-metal-based rechargeable batteries.     

新型4-羟色胺类化合物的合成及生物活性

以4-羟基吲哚为原料,经吲哚环4位乙酰基化、3位亲电取代、酰胺化和还原加氢等反应合成目标化合物7.通过核磁共振氢谱及碳谱对化合物进行结构表征,并对目标化合物进行体外抗氧化生物活性测试.初步生物活性测试结果表明,化合物7a,7b,7c和7d对DPPH·均有很强的清除作用(清除率为85.25%~90.73%),7e,7f,7g,7h作用较差;目标化合物与Vc相比,对·OH的清除作用稍差,最高清除率25.66%(Vc的最高清除率为34.67),但各化合物整体水平相当;在清除O-2·能力上化合物7a,7d,7g,7h最大清除率(分别为19.34,35.35,27.93和31.74)均强于同等浓度的Vc(17.58).     

Controlled Synthesis of Ni-Doped MoS2 Hybrid Electrode for Synergistically Enhanced Water-Splitting Process

The development of high-efficiency, low-cost, and earth-abundant electrocatalysts for overall water splitting remains a challenge. In this work, Ni-modified MoS₂ hybrid catalysts are grown on carbon cloth (Ni-Mo-S@CC) through a one-step hydrothermal treatment. The optimized Ni-Mo-S@CC catalyst shows excellent hydrogen evolution reaction (HER) activity with a low overpotential of 168 mV at a current density of 10 mA cm⁻² in 1.0 m KOH, which is lower than those of Ni-Mo-S@CC (1:1), Ni-Mo-S@CC (3:1), and pure MoS₂. Significantly, the Ni-Mo-S@CC hybrid catalyst also displays outstanding oxygen evolution reaction (OER) activity with a low overpotential of 320 mV at a current density of 10 mA cm⁻², and remarkable long-term stability for 30 h at a constant current density of 10 mA cm⁻². Experimental results and theoretical analysis based on density functional theory demonstrate that the excellent electrocatalytic performance can be attributed mainly to the remarkable conductivity, abundant active sites, and synergistic effect of the Ni-doped MoS₂. This work sheds light on a unique strategy for the design of high-performance and stable electrocatalysts for water-splitting electrolyzers.     

CLASSROOM DEMONSTRATION OF EXPERIMENT IN STRUCTURAL MECHANICS TEACHING1)

实验教学是很多理工科课程的重要教学环节,但是很多课程的实验教学模式还不够成熟,且开设困难。针对这一问题,本文以结构力学课程为例,分析当前高校结构力学实验开设难、开设少的原因,对比了几种典型实验方式的优劣。重点讨论了课堂演示实验的优势和实施办法,探索并列举了诸多简便易行的课堂演示实验案例。实践表明,课堂演示模型用日常简易材料制成,易于调动学生的参与积极性,同时增强学生的动手能力及理论联系实际的能力。最终提出了多种实验方式相结合的结构力学实验模式,可为当前高校结构力学和相关课程的课堂教学及实验环节提供借鉴。     

Cutoff Phenomenon for Nearest Lamperti’s Random Walk

Methodology and Computing in Applied Probability - We consider transient neighbor random walks on the positive part of the real line, the transition probability is state dependent being a special...     

Ultra-broadband piezoelectric energy harvesting via bistable multi-hardening and multi-softening

Nonlinear Dynamics - An electromechanical coupled distributed parameter model is derived for a broadband piezoelectric energy harvester with nonlinear magnetic interaction and...     

Liquid Fluxional Ga Single Atom Catalysts for Efficient Electrochemical CO2 Reduction

Precise design and tuning of the micro-atomic structure of single atom catalysts (SACs) can help efficiently adapt complex catalytic systems. Herein, we inventively found that when the active center of the main group element gallium (Ga) is downsized to the atomic level, whose characteristic has significant differences from conventional bulk and rigid Ga catalysts. The Ga SACs with a P, S atomic coordination environment display specific flow properties, showing CO products with FE of ≈92 % at −0.3 V vs. RHE in electrochemical CO₂ reduction (CO₂RR). Theoretical simulations demonstrate that the adaptive dynamic transition of Ga optimizes the adsorption energy of the *COOH intermediate and renews the active sites in time, leading to excellent CO₂RR selectivity and stability. This liquid single atom catalysts system with dynamic interfaces lays the foundation for future exploration of synthesis and catalysis.     

基于机器学习的直接电离质谱爆炸物检测方法

直接电离质谱系统在现场快速检测中的应用日益广泛,主要用于爆炸物、毒品、食品添加剂等的检测。然而,直接电离质谱系统中质谱信号波动大且同一浓度样品峰强呈现对数正态分布,严重影响了检出限附近低浓度样品的检测准确性。该研究将乙酰水杨酸(115个样品)作为爆炸物模拟物,利用介质阻挡放电离子源与质谱系统,研究了基于机器学习的直接电离质谱数据预处理和分类算法,以提高低浓度样品的检测准确率。对两种浓度为1 ng/mL的常见爆炸物样本(三硝基甲苯和硝酸铵分别为110、90个)及空白对照样本(366个)开展了应用实验。结果表明,与传统提取离子流方法和高斯混合模型方法相比,采用随机森林算法可将F_score从0.74、0.89提升至0.96,显著提高了检测准确率,且单个样本数据分析时间远少于0.1 s,满足实时检测需求。     

普适的基于能量的分块局域激发态聚类算法

在普适的基于能量的分块(GEBF)方法的框架下, 大体系的局域激发(LE)能可通过一系列活性子体系激发能的线性组合近似得到, 从而有效降低了计算的时间标度. 然而, 在体系的局域激发具有多个激发态的情形下, 如何有效识别所有活性子体系的激发特征并将其组合是一个挑战. 提出了一种基于局域激发态聚类的算法. 该方案基于空穴-电子分析和基于密度的聚类(DBSCAN)机器学习算法, 可以自动地聚合不同子体系中最相似的激发态并组合得到相应的局域激发态能量或激发能. 结合该算法改进的LE-GEBF方法在荧光分子衍生物、 荧光染料-水团簇及绿色荧光蛋白模型体系的计算中均获得了令人满意的结果. 该算法有望大大提升LE-GEBF方法在计算局域激发时的稳定性和准确性, 并可以有效处理吸收光谱具有多重峰的大体系.