直接进样气相色谱法分析有机芳香酸

用实验室合成的十二烷基苯磺酸甲铵配成固定液溶液,以汞塞动态法制备成毛细管色谱柱。讨论了该毛细管柱的制备方法,对有机芳香酸的分离以及定量分析问题。     

Spatiotemporal Utilization of Latent Heat in Erythritol-based Phase Change Materials as Solar Thermal Fuels

Solar thermal fuels (STFs) have been particularly concerned as sustainable future energy due to their impressive ability to store solar energy in chemical bonds and controllably release thermal energy. However, currently studied STFs mainly focus on molecule-based materials with high photochemical activity, toxicity, and compromised features, which greatly restricts their applications in practical scenarios of solar energy utilization. Herein, we present a novel erythritol-based composite phase change material (PCM) as a new type of STFs with an outstanding capability to store solar energy as latent heat in its stable supercooling state and release thermal energy as needed. This composite PCM with stored thermal energy can be maintained stably at room temperature and subsequently release latent heat as high as 224.9 J/g during the crystallization process triggered by thermal stimuli. Remarkably, solar energy can be converted into latent heat stored in the composite PCM over months. Through mechanical stimulations, the released latent heat can increase the temperature of the composite up to 91 °C. This work presents a new concept of using spatiotemporal storage and release of latent heat in PCMs for solar energy utilization, making it a potential candidate as STFs for developing future clean energy techniques.     

Highly Selective Catalytic Conversion of Phenolic Bio‐Oil to Alkanes

Oil and water : A new energy‐efficient and atom‐economical catalytic route for the production of alkanes and methanol by upgrading the phenolic fraction of bio‐oil has been developed. The one‐pot aqueous‐phase hydrodeoxygenation process is based on two catalysts facilitating consecutive hydrogenation, hydrolysis, and dehydration reactions.

     

A selective view of stochastic inference and modeling problems in nanoscale biophysics

Advances in nanotechnology enable scientists for the first time to study biological processes on a nanoscale molecule-by-molecule basis. They also raise challenges and opportunities for statisticians and applied probabilists. To exemplify the stochastic inference and modeling problems in the field, this paper discusses a few selected cases, ranging from likelihood inference, Bayesian data augmentation, and semi- and non-parametric inference of nanometric biochemical systems to the utilization of stochastic integro-differential equations and stochastic networks to model single-molecule biophysical processes. We discuss the statistical and probabilistic issues as well as the biophysical motivation and physical meaning behind the problems, emphasizing the analysis and modeling of real experimental data. This work was supported by the United States National Science Fundation Career Award (Grant No. DMS-0449204)     

One-step conversion of cellobiose to C6-alcohols using a ruthenium nanocluster catalyst

The one-step conversion of cellulose to C6-alcohols via green and energy efficient approaches has, as far as we are aware, not been reported. Such a process presents a considerable challenge, the two key problems being (1) finding a suitable solvent that dissolves the cellulose, and (2) the development of advanced catalytic chemistry for selective cleavage of the C-O-C bonds (glycosidic bonds) connecting glucose residues. The dissolution of cellulose has been recently realized by using ionic liquids as green solvents; there is still no efficient method, such as selective hydrogenation, for the precise C-O-C cleavage under mild conditions, however. Cellobiose is a glucose dimer connected by a glycosidic bond and represents the simplest model molecule for cellulose. We disclose in this communication that the one-step conversion of cellobiose to C6-alcohols can be realized by selectively breaking the C-O-C bonds via selective hydrogenation using a water-soluble ruthenium nanocluster catalyst under 40 bar H2 pressure.     

A study of density of states and ground states in hydrophobic-hydrophilic protein folding models by equi-energy sampling

We propose an equi-energy (EE) sampling approach to study protein folding in the two-dimensional hydrophobic-hydrophilic (HP) lattice model. This approach enables efficient exploration of the global energy landscape and provides accurate estimates of the density of states, which then allows us to conduct a detailed study of the thermodynamics of HP protein folding, in particular, on the temperature dependence of the transition from folding to unfolding and on how sequence composition affects this phenomenon. With no extra cost, this approach also provides estimates on global energy minima and ground states. Without using any prior structural information of the protein the EE sampler is able to find the ground states that match the best known results in most benchmark cases. The numerical results demonstrate it as a powerful method to study lattice protein folding models.     

Polymer-Solvent Interactions in Solutions of Thermoresponsive Polymers Studied by NMR and IR Spectroscopy

Summary: NMR relaxation and diffusion coefficient measurements revealed that a portion of water molecules is bound in mesoglobules formed in poly(N-isopropylmethacrylamide) (PIPMAm) and poly(vinyl methyl ether) (PVME) aqueous solutions above the LCST, with fast exchange between bound and free states (residence time ∼1 ms). Two types of bound water molecules were assigned to water bound inside mesoglobules and on their surface. For highly concentrated PVME/D₂O solutions (c ≥ 20 wt%) a slow exchange was detected by NMR for bound water (residence time = 2.1 s). For PIPMAm aqueous solution IR spectra indicate a two-steps character of the phase transition. For PIPMAm in D₂O/ethanol (EtOH) mixtures the globular structures were observed by NMR at 298 K for certain compositions of the mixed solvent (cononsolvency effect). Virtually no EtOH is bound in these globular structures, in contrast to the temperature-induced globular structures.     

可用于产生微波信号的间隔可调双波长光纤激光器

为了获得不同间隔双波长信号输出,提出一种基于受激布里渊效应产生双波长激光的实验装置,利用不同间隔双波长输出信号进行拍频实验可获得可调的微波信号输出;利用一段10 km长普通单模光纤（SMF）作为布里渊增益介质,一个线宽为5 kHz分布反馈激光器（DFB）作为布里渊抽运源,一段未泵浦的保偏掺铒光纤用作饱和吸收体抑制边模,通过改变未泵浦保偏掺铒光纤的长度,可获得不同间隔输出的双波长光纤激光器,实验获得波长间隔为0.170 nm和0.085 nm的激光信号输出,分别对应20 GHz和10 GHz的微波信号。     

中心刚体-旋转悬臂板耦合系统碰摩动力特性解析法研究

针对大型旋转机械叶片与机壳间发生的碰摩故障,建立了中心刚体-旋转悬臂板耦合系统碰摩动力学模型,考虑了离心刚化效应,利用Hamilton原理推导出运动微分方程。基于实验和有限元分析碰摩力的结果,给出了碰摩力的近似数学表达式,得到了系统振动响应解析解,通过与文献中实验结果的对比,验证了模型及方法的准确性,讨论了叶片梁模型和薄板模型在不同点碰摩及线碰摩情况下各自的适用范围,分析了转速对碰摩动力响应的影响。结果表明：论文解析解具有较高精度;薄板模型能够更全面地反映叶片各种不同碰摩情况下的动力特性,比梁模型更准确、可靠;随着转速的增大,碰摩力导致薄板自由端幅值突变,这是引发工程中叶片掉角,甚至折断的重要原因。     

光控DNA可逆杂交/解链及其应用

通过光敏分子与DNA相互作用,可以实现光控DNA杂交与解链,这种光控DNA有望成为下一代DNA功能构筑材料和纳米机械能量输入模式。本文总结了可逆光控DNA杂交/解链的各种途径及其作用机理,并分析其使用条件和光控效果。已有实验结果的对比和归纳表明,从DNA骨架上楔入含侧链偶氮苯官能团的单元,通过顺反异构实现DNA双链解链与杂交的可逆光控最具应用潜力,并且仍有一定的改进空间。本文介绍了这种骨架楔入偶氮苯光控DNA材料在纳米技术和生物技术方面的应用,并对其进一步的研究方向进行了展望。