氮化硼纳米管-纳米片分级结构的制备及光学和吸附特性

将五硼酸铵、 氨硼烷络合物和氧化镁混合, 球磨均匀后, 在1200 ℃及0.6 L/min流动氨气保护条件下退火6 h, 即可在氧化铝基片上收集到白色毛状产物. 采用X射线衍射(XRD), 红外光谱(FTIR)、 扫描电子显微镜(SEM)、 透射电子显微镜(TEM)、 拉曼光谱(Raman)、 紫外-可见吸收光谱(UV-Vis)和荧光光谱(PL)对产物进行了表征. 结果表明, 样品呈一维线状分级结构, 长度大于5 mm, 中间为竹节状空心结构, 内部管径为50~350 nm, 外径范围为200~800 nm. 分级结构表面负载了大量氮化硼(BN)纳米薄片, 单个薄片厚度约为13 nm. 薄片弯曲褶皱, 相互交织, 构成1个氮化硼片层, 其厚度约为50~200 nm. UV-Vis和PL光谱测试结果表明, 氮化硼纳米管(BNNT)分级结构在紫外光材料领域具有一定的应用潜力, 且对亚甲基蓝具有良好的吸附能力(7 min即可吸附71%, 107 min时可吸附96%). 对比实验结果表明, BNNT的生长机理遵循气-液-固相(VLS)模型, 而表面负载的超薄BN片的生长机理遵循气-固相(VS)模型.     

静电纺丝制备多级结构TiO_2微纳米纤维

通过对共轴电纺内流体溶液浓度和流速的调控得到4种具有不同内部结构的TiO₂微纳米纤维, 即具有“微孔”、“囊泡”、“竹节”和“管”状结构的TiO₂微纳米纤维, 实现了对纤维内部结构的有效控制, 对于新型仿生中空纤维的研究具有重要意义.     

蛋白质折叠类型的分类建模与识别

蛋白质的氨基酸序列如何决定空间结构是当今生命科学研究中的核心问题之一. 折叠类型反映了蛋白质核心结构的拓扑模式, 折叠识别是蛋白质序列-结构研究的重要内容. 我们以占Astral 1.65序列数据库中α, β和α/β三类蛋白质总量41.8%的36个无法独立建模的折叠类型为研究对象, 选取其中序列一致性小于25%的样本作为训练集, 以均方根偏差(RMSD)为指标分别进行系统聚类, 生成若干折叠子类, 并对各子类建立基于多结构比对算法(MUSTANG)结构比对的概形隐马尔科夫模型(profile-HMM). 将Astral 1.65中序列一致性小于95%的9505个样本作为检验集, 36个折叠类型的平均识别敏感性为90%, 特异性为99%, 马修斯相关系数(MCC)为0.95. 结果表明: 对于成员较多, 无法建立统一模型的折叠类型, 基于RMSD的系统分类建模均可实现较高准确率的识别, 为蛋白质折叠识别拓展了新的方法和思路, 为进一步研究奠定了基础.     

Evaluation of nutritional parameters in infant formulas and powdered milk by Raman spectroscopy

It has been made a critical evaluation of the application of near infrared Fourier transform-Raman spectroscopy for the simultaneous determination of the most important nutritional parameters such as energetic value, carbohydrate, protein and fat contents of infant formula and powdered milk samples based on the use of partial least squares (PLS) regression analysis. A highly heterogeneous population of 23 samples, covering a wide range of infant food formula and powdered milk, were obtained from the Spanish market. Raman spectra, obtained by excitation with a Nd:YAG laser at 1064 nm, show no disturbing fluorescence effects; therefore sample spectra can be recorded without any previous preparation step. After correcting the spectra, hierarchical cluster analysis was performed in order to select a representative calibration set and the corresponding validation sample set. Different PLS models and several spectral windows were tested in order to evaluate their prediction capabilities for the validation set. Considering a calibration set comprised of three replicate spectra of 15 samples and a validation data set of eight samples, the procedure developed provided figures of merit which complied with the statutory values declared by the United States Food and Drug Administration (US FDA).     

Differentiation of opium and poppy straw using capillary electrophoresis and pattern recognition techniques

Opium samples from four different locations and poppy straw from different plant varieties have been assayed using micellar capillary electrophoresis incorporating a sweeping technique. Individual alkaloids (morphine, codeine, papaverine, noscapine, thebaine, oripavine, reticuline and narceine) were quantitatively determined in the different samples by a validated capillary electrophoresis method. Unsupervised pattern recognition of the opium samples and the poppy straw samples using hierarchical cluster analysis (HCA) and principal component analysis (PCA), showed distinct clusters. Supervised pattern recognition using soft independent modelling of class analogy (SIMCA) was performed to show individual groupings and allow unknown samples to be classified according to the models built using the CZE assay results.     

Coal analysis by diffuse reflectance near-infrared spectroscopy: Hierarchical cluster and linear discriminant analysis

An extensive study was carried out in coal samples coming from several origins trying to establish a relationship between nine coal properties (moisture (%), ash (%), volatile matter (%), fixed carbon (%), heating value (kcal/kg), carbon (%), hydrogen (%), nitrogen (%) and sulphur (%)) and the corresponding near-infrared spectral data. This research was developed by applying both quantitative (partial least squares regression, PLS) and qualitative multivariate analysis techniques (hierarchical cluster analysis, HCA; linear discriminant analysis, LDA), to determine a methodology able to estimate property values for a new coal sample. For that, it was necessary to define homogeneous clusters, whose calibration equations could be obtained with accuracy and precision levels comparable to those provided by commercial online analysers and, study the discrimination level between these groups of samples attending only to the instrumental variables. These two steps were performed in three different situations depending on the variables used for the pattern recognition: property values, spectral data (principal component analysis, PCA) or a combination of both. The results indicated that it was the last situation what offered the best results in both two steps previously described, with the added benefit of outlier detection and removal.     

Identification of Earth Pigments by Applying Hierarchical Cluster Analysis to Solid State Voltammetry. Application to Severely Damaged Frescoes

Multivariate chemometric methods are applied for identifying earth pigments from square‐wave voltammetric measurements performed at pigment‐modified paraffin‐impregnated graphite electrodes allowing for a separation between hematite‐based earths, French ochres, Spanish ochres, siennas, umbers and green earths. This methodology is applied to the identification of the pigments in samples from the ceiling frescoes of Antonio Palomino (dated 1707) in the vaulted nave of the Sant Joan del Mercat church in Valencia (Spain). These frescoes suffered considerable damage by fire during the Spanish Civil War in 1936, resulting in severe chemical and chromatic alterations. Electrochemical data, supported by scanning electron microscopy/energy dispersive X‐ray microanalysis and Raman spectroscopy, indicate that thermal stress induced the transformation of goethite‐based yellow ochres into hematite and magnetite.     

多层次炭结构对膨胀阻燃聚丙烯性能的调控作用研究

将具有封闭空心结构的酚醛微球(HPMs)引入到聚丙烯/膨胀阻燃剂(PP/IFR)体系,燃烧时一方面依托PP/IFR形成膨胀多孔炭,另一方面通过HPMs形成空心炭微球,嵌入到前面多孔炭的骨架中,形成具有多层次孔的炭结构,从而调控膨胀炭层,进而调节材料的阻燃性能.通过极限氧指数(LOI)、垂直燃烧(UL-94)等研究了材料的阻燃性能;通过热失重分析(TGA)测试其热稳定性;采用红外热成像仪监测燃烧过程材料的表面温度,用扫描电镜(SEM)观察IFR、HPMs在基体中的分散行为及炭层结构.结果表明,少量HPMs在聚合物中分散得比较均匀.HPMs调控了膨胀炭层,使PP/IFR形成了表层炭致密,内层具有多层次孔的炭结构.这种优质的炭结构可以使样品表面温度迅速降低,从而有效提高PP/IFR体系的阻燃效率,使得PP在添加18 wt%IFR和1 wt%HPMs就可以通过UL-94 V0级别.     

分级结构氮掺杂碳纳米笼担载的铂基高效甲醇氧化电催化剂

高性能低成本的担载型铂基催化剂是直接甲醇燃料电池(DMFC)实用化过程中的一大挑战.利用高比表面积、高稳定性、容易负载金属的载体实现 Pt颗粒的高度分散,既可提高催化剂的催化性能,又可提高 Pt的利用率以降低成本,是担载型 Pt基催化剂实用化的有效途径.碳材料是一种常用的催化剂载体,近年来我们课题组发展了一种高性能的碳纳米笼材料,并可通过异原子掺杂调变其表面性能,提高其活性和负载能力.我们采用原位氧化镁模板法制备氮掺杂碳纳米笼：以具有多级结构的碱式碳酸镁作为氧化镁模板的前体,吡啶为碳源和氮源,经高温热解沉积,在原位形成的氧化镁模板表面形成氮掺杂的石墨化碳纳米薄层;经稀盐酸浸泡并洗涤,获得高纯度的氮掺杂碳纳米笼.氮掺杂碳纳米笼具有分等级的微纳米结构、高导电性、高比表面积和可调变的孔结构,结合表面氮原子的锚钉作用,氮掺杂碳纳米笼有望成为电化学催化剂 Pt的优良载体.
　　在前期研究基础上,本文探索多级结构氮掺杂碳纳米笼(hNCNC)作为新型载体负载 Pt的能力,并评价所构建的负载型催化剂 Pt/hNCNC的电催化性能.通过简便的微波辅助多元醇还原法,将氯铂酸还原成 Pt纳米粒子负载于 hNCNC的表面.为了揭示氮掺杂的效应,我们对比研究了具有相似分级结构但无掺杂的碳纳米笼(hCNC)以及商业化活性炭(Val-can XC-72)作为载体的情况.经热重(TG)和 X射线光电子能谱(XPS)分析,三种催化剂 Pt/hNCNC、Pt/hCNC和 Pt/XC-72的负载量均接近理论负载量(23.1 wt%),都主要以金属态存在.然而,扫描电子显微镜(SEM)和透射电子显微镜(TEM)结果表明, Pt/hNCNC的 Pt分散状态优于 Pt/hCNC,更远优于 Pt/XC-72. Pt/hNCNC的平均 Pt粒径最小,仅约3.3 nm.这种良好的分散状态主要得益于氮原子掺杂,高负电性的氮原子改变了局域的表面极性,有利于 Pt颗粒的成核,也有利于固定 Pt颗粒.
　　由于 hNCNC对 Pt的优异分散能力, Pt/hNCNC表现出高的电化学活性面积.氢吸附和一氧化碳溶出伏安曲线表明, Pt/hNCNC的电化学活性面积高于 Pt/hCNC和 Pt/XC-72,这与显微观察和 X射线衍射(XRD)结果相吻合. Pt/hNCNC展现出优异的甲醇电催化氧化活性和高稳定性,其催化电流明显高于 Pt/hCNC和 Pt/XC-72,电流衰减亦慢于 Pt/hCNC和 Pt/XC-72. hNCNC的分级微纳米结构有利于孔内传质和电子输运,从而提高反应速度. hNCNC的氮掺杂有利于 Pt在载体表面的分散,增强了载体-金属相互作用,提高了电化学活性面积和催化活性.为了进一步考察 hNCNC对 Pt的负载能力,本文还考察了高负载量 Pt/hNCNC的性能.在负载量高达60 wt%时, Pt/hNCNC中的 Pt颗粒仍无明显聚集,其甲醇氧化电流增加了30%,可以有效提高 DMFC的输出电流密度.
　　综上可见, hNCNC可以有效分散并稳定 Pt颗粒,从而提高电化学活性面积和甲醇电催化氧化活性,优于未掺杂的碳纳米笼和传统碳材料,展示了 hNCNC高分散 Pt颗粒用作 DMFC的高效阳极催化剂的重要前景,也表明 hNCNC有望成为应用广泛的新型载体.     

氧化锆担载镍甲烷干重整催化剂的载体形貌效应

煤层气是储量十分丰富的煤炭伴生资源,也是煤炭开采中最大的安全隐患之一,同时还是重要的温室气体.研究煤层气的高效、清洁资源化利用具有资源和环境双重意义.因此,世界主要产煤国均十分重视煤层气的开发和利用.煤层气的主要成分是甲烷,目前主要通过两种方式实现其资源化利用:(1)直接转化,主要通过氧化偶联、催化氧化官能团化或脱氢芳构化等途径将其转化为高碳烃、含氧化合物及芳烃等;(2)间接转化,甲烷首先经催化重整反应制取合成气,而后再经Fischer-Tropsch合成、甲醇化和氢甲酰化等过程来合成饱和烃、烯烃、甲醇及其他含氧化物.对于前者,由于热力学限制,反应收率很低,应用前景较差,而经由合成气这一平台产物的间接转化路线被认为是一条甲烷资源化利用颇具工业前景的转化路线.因此,甲烷催化重整制合成气备受关注.研究表明,贵金属具有较好的甲烷重整催化性能,但其储量有限、价格昂贵的内在缺陷不利于甲烷大规模转化和资源化利用.Ni基催化剂具有与贵金属可比的催化活性和选择性,且其储量丰富,价格低廉,因此在甲烷重整反应中备受青睐.但是,相对于贵金属,Ni基催化剂易于积碳和烧结失活,这已成为制约其大规模工业化应用的瓶颈.迄今,大量文献报道关注如何提高Ni基催化剂的催化稳定性.而载体形貌调控是调节负载型催化剂的有效途径.本文开展了用作载Ni催化剂的氧化锆载体的形貌调控研究,以期可以有效调节载Ni催化剂的物化性质,进而调控载Ni催化剂的甲烷重整催化性能.采用水热法成功制备了松球状和鹅卵石状的单斜相氧化锆载体,进一步负载镍,制备了载镍催化剂,用于甲烷重整制合成气反应.具有分级结构的松球状氧化锆载Ni催化剂(Ni/ZrO2-ipch)展示出比鹅卵石状氧化锆和常规氧化锆纳米粒子载Ni催化剂显著好的催化活性和稳定性.采用XRD、N2吸附、TEM、H2-TPR、CO化学吸附、CO2-TPD、XPS和TGA等手段研究了松球状氧化锆载Ni催化剂高催化活性和稳定性的原因和机制.发现,其较高的催化活性主要归因于高的Ni分散度、改善的可还原性、促进的氧流动性以及较多的碱性位和较强的碱性,这些物化性质依赖于氧化锆载体的独特形貌.分级结构的松球状氧化锆载Ni催化剂高的甲烷重整催化稳定性主要源于催化剂的高抗烧结、抗积碳性能.加强的金属载体效应和介孔限域效应可以阻止金属Ni的高温烧结,而优良的抗积碳稳定性主要源于催化剂良好的氧流动性、较多的碱性位、较强的碱性以及小的Ni粒子尺寸.鉴于分级结构松球状氧化锆载Ni催化剂高的催化活性和优良的抗积碳、抗烧结稳定性,该催化剂用于甲烷重整制合成气具有广阔前景.而所制备的分级结构松球状氧化锆由于具有独特的结构和优良的热稳定性,可以作为性能优良的载体用于其他反应,尤其对于高温转化过程可望表现出明显优势.