Improved hydrogen evolution on glassy carbon electrode modified with novel Pt/cetyltrimethylammonium bromide nanoscale aggregates

A novel, cost‐effective, and simple electrocatalyst based on a Pt‐modified glassy carbon electrode (GCE), using cetyltrimethylammonium bromide (CTAB) as a cationic surfactant, is reported. Am‐phiphilic...     

纳米壳聚糖修饰的开管毛细管电色谱柱的制备及对碱性蛋白质的分离

采用离子交联法制得纳米壳聚糖粒子溶液,通过静电吸附作用将其修饰于石英毛细管内表面形成涂层毛细管柱.通过场发射扫描电子显微镜观察到毛细管内壁有小丘状突起,表明纳米壳聚糖粒子已吸附于柱内层.检测了不同p H值下的电渗流变化趋势并与裸柱比较,结果显示修饰后的柱电渗流受到明显抑制,并在p H4.7的环境中能产生反向电渗流,该柱在不同p H值下电渗流的相对标准偏差(RSD)6%,日内、日间和柱间的RSD分别为1.46%,4.64%和14.43%,表明柱稳定性较好.通过分离3种中性物质甲苯、苯酚和硫脲考察了该柱的色谱行为,出峰顺序与其极性大小顺序一致,表明纳米涂层起到极性固定相的作用.用该柱成功分离了3种碱性蛋白质溶菌酶、细胞色素c和核糖核酸酶A,柱效分别为39481,42610和245373Plate/m,重现性良好,表明纳米涂层可有效抑制碱性蛋白质的吸附作用.     

KIT-6负载CeO2催化CO2和甲醇合成碳酸二甲酯

采用不同老化温度(80、100、120和150℃)合成了一系列KIT-6载体,并通过浸渍法制备了相应的CeO_2/KIT-6催化剂。结合X射线衍射、N_2物理吸附、NH_3程序升温脱附、CO_2程序升温脱附、透射电子显微镜、傅里叶变换红外光谱和X射线光电子能谱等表征结果,详细考察了老化温度对KIT-6结构以及CeO_2/KIT-6催化剂直接催化CO_2和甲醇合成碳酸二甲酯(DMC)反应活性的影响。结果表明,不同老化温度下制备的KIT-6均保持其独特的三维孔道结构。随着老化温度升高,KIT-6比表面积先增大后减小,当老化温度为100℃时,KIT-6比表面积达到最大(683 m~2·g~(-1))。KIT-6较高的比表面积有利于提高CeO_2分散度,进而提高暴露的活性位点数量,催化活性随催化剂表面中等碱/酸性吸附位数量和Ce~(3+)含量的增加而逐渐提高。其中,CeO_2/100-KIT-6催化剂中CeO_2颗粒尺寸最小(5.9 nm),暴露的活性位数量最高,催化活性最佳。随后,考察了反应温度和压力对CeO_2/100-KIT-6催化活性的影响。随着反应温度提高,催化活性先升高后降低,当反应温度为140℃时,催化活性最高;且催化活性随反应压力的提高而逐渐增加。在反应温度为140℃、压力为6.8 MPa条件下,催化剂经6次循环后,DMC收率由15 mmol·g_(CeO_2)~(-1)逐渐降低至2.8 mmol·g_(CeO_2)~(-1),原因归结为反应过程中CeO_2纳米颗粒发生团聚,使暴露出的活性位数量减少。     

Accessing the spatiotemporal heterogeneities of single nanocatalysts by optically imaging gas nanobubbles

Catalysts that catalyze the generation of products in the gas phase, especially those involved in the hydrogen evolution reaction (HER), hold great promise for ecofriendly and sustainable energy development. In general, gas chromatography is widely used to measure catalytic activity. Unfortunately, it gives an averaged output that washes out the heterogeneities among individuals. To assess the unique catalytic properties at the single nanoparticle level, various methods based on single particle catalysis have been proposed. Over the past fifteen years, tremendous breakthroughs have been achieved, which uncovered hidden spatial and temporal heterogeneities. Although powerful, effectively quantifying the activities of single HER nanocatalysts remains challenging because of the fast diffusion of hydrogen (H₂). In 2017, a novel approach based on a nanobubble indicator was proposed to correlate the kinetics of gas bubble evolution with the catalytic activities of individual nanoentities during the HER process. Since then, a plethora of optical microscopy techniques have been utilized to monitor dynamically evolved nanobubbles and to measure the catalytic activities of single HER catalysts. In this minireview, we summarized state-of-the-art optical microscopy for in operando imaging of dynamic nanobubbles involved in gas-generating reactions while highlighting some important discoveries, including the blinking photocatalytic activity and heterogeneous distribution of active sites. Finally, challenges and future perspectives in this promising field were identified.     

单颗粒光散射显微成像技术在生化医药分析中的应用

等离子体纳米颗粒(PNPs)具有体积小、易表面修饰、生物相容性好、毒性低等优点,在生物传感、生物成像、疾病诊断、肿瘤治疗、材料科学等领域得到了广泛的应用。PNPs的光散射光学性质可以通过调节其大小、组成、形貌和微环境来控制,可用于生化和药物分析。此外,由于单粒子散射显微技术具有高空间分辨率和高灵敏度,借助PNPs具有的独特局域表面等离子体共振(LSPR)特性,可在单颗粒水平进行实时成像。根据PNPs的大小、组成、形态、微环境或耦合变化引起的信号变化,研究人员发展了多种显微成像分析方法,主要分为4种,包括散射光谱的波长位移、单粒子散射强度的变化、高通量RGB分析和计数方法。基于纳米颗粒LSPR散射光谱位移变化的方法准确、灵敏,但需要昂贵的单颗粒散射光谱仪和复杂的操作。基于纳米颗粒散射强度变化的方法简单可行,但易受纳米颗粒粒径和曝光时间等因素的影响。高通量RGB分析方法灵敏度高、成本低,但不适用于颜色变化不明显的单颗粒分析,且重复性差。单粒子计数法灵敏度高,但有时粒子分布不均匀,背景杂质的干扰限制了方法的准确度。因此,这4种定量方法各有优缺点。此外,近年来逐渐发展了一些新的定量方法。例如,研究人员开发了新的时间分辨分析定量方法,并将暗场显微镜与偏振器、滤光片等光学器件相结合以消除背景干扰,以及与电化学、拉曼等仪器相结合以扩大应用范围。此外,为提高分析方法的准确度和灵敏度,暗场显微镜与深度学习、云计算、人工智能等现代计算机科学技术的结合,越来越受到人们的欢迎。基于以上原因,该文重点介绍了单粒子光散射显微镜在生化和药物分析领域的应用,总结了近年来的最新研究进展,讨论了单粒子光散射显微镜在定量分析中的几种主要定量方法,提出了未来的发展趋势,以期为相关研究领域的新人提供一定的学术参考。     

Convergence of a non-failable mean-field particle system

The existing literature contains many examples of mean-field particle systems converging to the distribution of a Markov process conditioned to not hit a given set. In many situations, these mean-field particle systems are failable, meaning that they are not well defined after a given random time. Our first aim is to introduce an original mean-field particle system, which is always well defined and whose large number particle limit is, in all generality, the distribution of a process conditioned to not hit a given set. Under natural conditions on the underlying process, we also prove that the convergence holds uniformly in time as the number of particles goes to infinity. As an illustration, we show that our assumptions are satisfied in the case of a piece-wise deterministic Markov process.     

A correlative classifiers approach based on particle filter and sample set for tracking occluded target

Target tracking is one of the most important issues in computer vision and has been applied in many fields of science, engineering and industry. Because of the occlusion during tracking, typical approaches with single classifier learn much of occluding background information which results in the decrease of tracking performance, and eventually lead to the failure of the tracking algorithm. This paper presents a new correlative classifiers approach to address the above problem. Our idea is to derive a group of correlative classifiers based on sample set method. Then we propose strategy to establish the classifiers and to query the suitable classifiers for the next frame tracking. In order to deal with nonlinear problem, particle filter is adopted and integrated with sample set method. For choosing the target from candidate particles, we define a similarity measurement between particles and sample set. The proposed sample set method includes the following steps. First, we cropped positive samples set around the target and negative samples set far away from the target. Second, we extracted average Haar-like feature from these samples and calculate their statistical characteristic which represents the target model. Third, we define the similarity measurement based on the statistical characteristic of these two sets to judge the similarity between candidate particles and target model. Finally, we choose the largest similarity score particle as the target in the new frame. A number of experiments show the robustness and efficiency of the proposed approach when compared with other state-of-the-art trackers.     

Crosslinking network structure governing particle shape and size distribution by one-step emulsion polymerization in the presence of particle coagulation

In this study, sub-200?nm, crosslinked latex particles with a narrow particle size distribution were prepared by one-step emulsion polymerization in the presence of particle coagulation. The relationship between the particle shape and particle coagulation was investigated by varying the time of crosslinking network structure formation and particle coagulation. Particles with irregular shapes such as doublet, triplet, and ellipsoid were obtained using divinylbenzene (DVB) and ethylene glycol dimethacrylate (EGDMA) as the crosslinking agents, because the crosslinking network structure of particles was formed before the particle coagulation. In contrast, latex particles with a uniform spherical shape were also prepared using triallyl isocyanurate (TAIC) or dihydrodicyclopentadienyl acrylate (DCPA) as the crosslinking agents by delaying the time of crosslinking network structure formation. Alternatively, uniform spherical latex particles were prepared by bringing forward the particle coagulation time using cationic initiator, 2, 2′-azobis (2-methylpropionamidine) dihydrochloride (AAPH). This study presents a new idea that would further broaden the application of particle coagulation in emulsion polymerization.