Synthesis of dual-doped non-precious metal electrocatalysts and their electrocatalytic activity for oxygen reduction reaction

The pyrolyzed carbon supported ferrum polypyrrole(Fe-N/C) catalysts are synthesized with or without selected dopants, p-toluenesulfonic acid(TsOH), by a facile thermal annealing approach at desired temperature for optimizing their activity for the oxygen reduction reaction(ORR) in O2-saturated 0.1 mol/L KOH solution. The electrochemical techniques such as cyclic voltammetry(CV) and rotating disk electrode(RDE) are employed with the Koutecky-Levich theory to quantitatively obtain the ORR kinetic constants and the reaction mechanisms. It is found that catalysts doped with TsOH show significantly improved ORR activity relative to the TsOH-free one. The average electron transfer numbers for the catalyzed ORR are determined to be 3.899 and 3.098, respectively, for the catalysts with and without TsOH-doping. The heat-treatment is found to be a necessary step for catalyst activity improvement, and the catalyst pyrolyzed at 600℃ gives the best ORR activity. An onset potential and the potential at the current density of-1.5 mA/cm2 for TsOH-doped catalyst after pyrolysis are 30 mV and 170 mV, which are more positive than those without pyrolized. Furthermore, the catalyst doped with TsOH shows higher tolerance to methanol compared with commercial Pt/C catalyst in 0.1 mol/L KOH. To understand this TsOH doping and pyrolyzed effect, X-ray diffraction(XRD), scanning electron microscope(SEM) and X-ray photoelectron spectroscopy(XPS) are used to characterize these catalysts in terms of their structure and composition. XPS results indicate that the pyrrolic-N groups are the most active sites, a finding that is supported by the correspondence between changes in pyridinic-N content and ORR activity that occur with changing temperature. Sulfur species are also structurally bound to carbon in the forms of C–Sn–C, an additional beneficial factor for the ORR.     

玉米芯生物质灰的物理化学特性

采用X射线荧光光谱、X射线衍射、扫描电镜、粒度分析等实验方法研究了不同灰化温度(600℃和815℃)下制得的玉米芯灰的理化特性.利用马弗炉灼烧实验考察了灰化温度和保温时间对灰分量的影响,并通过扫描电镜-能谱联用技术对生物质气化站现场采集的玉米芯灰的灰成分和灰形态进行了分析.研究发现,灰化温度对灰粒度、灰分量、灰成分、灰形态和物相变化均有明显影响,但对积灰结渣特性影响不明显;灰的主要组成元素为钾和氯,玉米芯热解气化排放钾的主要形式是氯化钾;灰表面的形态各异,600℃灰化时形成絮状的大颗粒,815℃时灰表面发生软化熔融,絮状物减少.该研究可为生物质燃料经热化学转化后的燃气净化及生物质灰的综合利用提供指导.     

不同农业生物质废弃物的热解特性及动力学对比

为了充分利用农业生物质废弃物进行热解气化,以玉米芯、花生壳、稻壳和稻秸为研究对象,以高纯氮气为载气,通过热重分析和质谱分析联用技术,考察了其热解过程的失重机制、热流变化规律、小分子可燃气体(CO,H_2和CH_4)的释放规律及综合热解特性.结果表明,生物质的热解失重主要发生在220~410℃,玉米芯在该区间的失重最高,占总失重的80%~90%;挥发分综合释放指数D:玉米芯稻秸稻壳花生壳,活化能:稻壳玉米芯稻秸花生壳,固体剩余物:稻壳花生壳稻秸玉米芯,总体上看,玉米芯和稻秸的热稳定性较差,而稻壳和花生壳的热稳定性较好;通过Coats-Redfern法计算得到了相应的活化能和频率因子,计算结果与热重试验基本一致.     

光生物反应器和跑道式循环生物反应器对荒漠藻类生物量和多糖产量的影响

采用光生物反应器和跑道式循环生物反应器对荒漠藻类进行规模化培养,对比研究了两种规模化培养系统对荒漠藻类生物量和多糖产量的影响,探讨了温度、酸碱度、生长周期以及氮、磷含量对荒漠藻类生长和多糖积累的作用.结果表明,在光生物反应器和跑道式循环生物反应器两种培养系统中,藻类的生长呈现出不同的变化趋势,而藻多糖含量则呈现相同的波动性变化趋势,并且藻类生物量和多糖分泌受培养条件的影响并不同步.此外,在两种规模化培养模式中,温度、酸碱度、营养盐以及生长周期等都对荒漠藻类的生长和多糖产量产生重要影响.     

A Chemically Fuelled Molecular Automaton Displaying Programmed Migration of Zn2+ Between Alternative Binding Sites

A molecular system comprising a cationic zinc complex and an amino acid-derived ambident ligand having phosphate and carboxylate binding sites undergoes a series of rearrangements in which the metal cation migrates autonomously from one site to another. The location of the metal is identified by the circular dichroism spectrum of a ligated bis(2-quinolylmethyl)-(2-pyridylmethyl)amine (BQPA) chromophore, which takes a characteristic shape at each binding site. Migration is fuelled by the decomposition of trichloroacetic acid to CO₂ and CHCl₃, which progressively neutralises the acidity of the system as a function of time, revealing in sequence binding sites of increasing basicity. The migration rate responds to control by variation of the temperature, water content and triethylamine concentration, while an excess of fuel controls the duration of an induction period before the migration event.     

分散溶剂对PEMFC催化层中超薄Nafion离聚物质子传导的影响

质子交换膜燃料电池(PEMFC)商业化应用的瓶颈仍然是贵金属催化剂导致的成本问题。然而,目前对于催化层中纳米尺度全氟磺酸离聚物(以Nafion为代表)薄膜中质子传导的问题研究不足,无法完善三相界面的成型规律,进而指导催化层设计。在催化层浆料制备过程中,分散溶剂对Nafion的分散形态有直接影响,可能对催化层成型后附着在催化剂颗粒表面Nafion薄膜的微观结构有潜在影响,进而影响Nafion薄膜的质子传导能力。因此,在本文中利用分子自组装技术模拟催化层离聚物薄膜的聚集过程,于模型基底上制备厚度精确可控的纳米尺度Nafion薄膜,并通过微观测试表征技术探索并建立纳米尺度Nafion离聚物的微观结构模型,阐明分散溶剂对Nafion薄膜微观结构及质子传导的影响。研究发现Nafion薄膜在纳米尺度下的质子电导率比体相膜的质子电导率低一个数量级,使用介电常数较小的醇类溶剂可以使Nafion薄膜形成更有利于质子传导的微观结构,使Nafion薄膜的质子电导率得到提高。相关研究结果为优化PEMFC催化层结构,改善PEMFC催化层中质子传导问题提供给了依据。     

Atom-economic Approach to the Synthesis of α-(Hetero)aryl-substituted Furan Derivatives from Biomass

An atom-economic ring construction approach to the synthesis of α-(hetero)arylfurans based on renewable furanic platform chemicals has been developed. Corresponding compounds have been prepared in good to excellent yields via [2+2+2] and [4+2] cycloaddition reactions using metal-catalyzed or photoredox protocols. Easily available HMF-based 2-hydroxymethyl-5-ethynylfuran and 2-hydroxymethyl-5-cyanofuran were used as starting materials. A synthetic route with an improved carbon economy factor has been implemented to achieve sustainability aim. The possible application of arylfurans as molecular conductors has been investigated by DFT calculations, which revealed excellent charge transfer properties. As a future perspective, integration of biomass processing strategy into manufacturing of molecular electronics was pointed out to achieve the aim of sustainability.     

Machine learning as an online diagnostic tool for proton exchange membrane fuel cells

Proton exchange membrane fuel cells are considered a promising power supply system with high efficiency and zero emissions. They typically work within a relatively narrow range of temperature and humidity to achieve optimal performance; however, this makes the system difficult to control, leading to faults and accelerated degradation. Two main approaches can be used for diagnosis, limited data input which provides an unintrusive, rapid but limited analysis, or advanced characterisation that provides a more accurate diagnosis but often requires invasive or slow measurements. To provide an accurate diagnosis with rapid data acquisition, machine learning methods have shown great potential. However, there is a broad approach to the diagnostic algorithms and signals used in the field. This article provides a critical view of the current approaches and suggests recommendations for future methodologies of machine learning in fuel cell diagnostic applications.     

Recent advances in microbial fuel cell-based toxicity biosensors: Strategies for enhanced toxicity response

Microbial fuel cells (MFCs) have been extensively studied as self-powered toxicity biosensors; however, their applications are limited by the relatively poor toxicity responses. The toxicity responses are known to be related to the factors such as the resistance of species to toxicants, the bioavailability of toxicants and the type of sensing elements. Accordingly, some strategies have already been proposed to enhance the toxicity responses in the past several years, including the external resistance tuning, quorum sensing effect, shear stress control, nutrient level control, electrode material choice, sensing element choice, and cell configuration design. This work introduces and discusses these strategies, and the suggestion for future work is also provided finally.