Modeling of nucleic acid adsorption on 3D prisms in microchannels

Understanding nucleic acid adsorption in microchannels is critical to improve the efficiency of purifying and extracting nucleic acid (NA) from sample solutions by microfluidic technologies. Using a microchannel with 3D prismatic silica elements on the wall can dramatically increase the surface area-to-volume ratio, and hence facilitate the nucleic acid adsorption on the wall. In this study a theoretical model for modeling adsorption in a microchannel with a designed 3D surface structure was developed, and five dimensionless numbers were found to be the key parameters in the adsorption process. Extensive numerical simulations were conducted. Two flow modes, the electroosmotic flow (EOF) and pressure-driven flow (PDF), were investigated for their effect on the adsorption. It was found that the EOF is more desirable than PDF. The 3D prismatic elements can increases the NA molecule adsorption not only by providing more surface areas, but also by the induced pressure resisting the central bulk electroosmotic flow. Finally, the effects of adsorption kinetic parameters (i.e., the kinetic association/dissociation constants, the diffusion coefficient, the total site density, the loading concentration, and the channel height), on the adsorption process were discussed in detail.     

Isolation and structure determination of a new lasso peptide subterisin from Sphingomonas subterranea

A new lasso peptide named subterisin was isolated from the culture broth of Sphingomonas subterranea NBRC 16086^T. The molecular formula of subterisin was established as C₇₈H₁₂₁O₂₂N₂₁ based on accurate mass analysis. The chemical structure of subterisin was determined by 2D NMR experiments. The presence of macrolactam ring of Gly1–Glu8 was indicated by NOESY experiment and MS/MS analysis. The three-dimensional structure of subterisin in solution was established by calculation based on NMR data. The proposed biosynthetic gene cluster of subterisin was found on the genome of S. subterranea.     

三维介孔钴酸锌立方体的制备及其优异的储锂性能

采用简易、温和、实际耐用的水热方法制备了新型三维介孔立方体结构的钴酸锌纳米材料。每个钴酸锌立方体的边长大约在3-4μm之间,并由大量的纳米粒子和密集的孔隙所构成。通过氮吸附/脱附手段测试发现所制备的钴酸锌纳米材料具有较大的比表面积(41.4 m2?g~(-1))和介孔(6.32 nm)特性。使用钴酸锌纳米材料作为锂离子电池负极,金属锂作为正极组装锂电池并测试了材料的储锂性能。研究发现该电极材料在较高的电流密度下循环100周后,仍能呈现较高的可逆容量和超强的循环稳定性。这种优异的储锂性能主要归因于钴酸锌纳米材料的新型结构,这种介孔立方体结构能够加速锂离子的扩散,增加电极与电解液的接触面积并缓解锂离子嵌入/嵌出期间产生的体积膨胀。     

激光诱导三维网状石墨烯的一步法制备及应用

三维多孔石墨烯作为一种优异的石墨烯碳材料, 其独特的多孔结构使得材料在具有较大比表面积的同时还保持着足够高的电子迁移率和机械稳定性, 在电子器件中得到了广泛的应用. 本文介绍的激光诱导石墨烯是一种以一步法直接制备得到的三维网状石墨烯材料, 该技术将三维石墨烯的制备和图案化相结合, 无需进行湿化学反应处理, 制作方法更简便, 材料性能更优异. 目前研究主要集中在通过掺杂提高性能和利用转移法实现不同基底器件的制备. 激光诱导石墨烯自身特有的属性如多孔微纳米结构和大的比表面积等使其在超级电容器和传感器等领域拥有较高的应用价值.     

Three-dimensional bundle-like multiwalled carbon nanotubes composite for supercapacitor electrode application

Bundle-type mutil-walled carbon nanotubes (MWCNTs) composite electrode is the first investigation and publication for the supercapacitor application. According to the thermogravimetric analysis results, as-synthesized BCNTs are considered as the electrode materials for supercapacitors and electrochemical double-layer capacitor in this study. The Brunauer–Emmett–Teller specific surface area of as-prepared bundled carbon nanotubes (BCNTs) is 95.29 m²/g given to a type III isotherm and H3 hysteresis loops. Slow scanning rates promote and enhance to achieve high C_b because of the superior conductivity of CNT bundles and one side close-layered Ni/Mg/Mo alloy inside the BCNT-based electrode and facile electron diffusivity between electrolyte and electrode. The specific capacitance C_s (1,560 F/g) is nearly equal to the maximum specific capacitance, which the BCNT-based composite electrode can actually be able to charge or fill in. The maximum energy density value is 195 Wh/kg with corresponding power density values of 0.21 kW/kg. Furthermore, the active 3D BCNTs material fabricated electrode enhances to contact the electrolyte directly and decreases the ion diffusion limitation. Electrochemical impedance spectroscopy spectrum summarized as the low-frequency area controls by mass transfer limitation, and the high-frequency area dominates by charge transfer of kinetic control. After 2,000 consecutive cyclic voltammetry sacnings and galvanostatic charge-discharge cycles at a current density of 1.67 A/g performs, the specific capacitance retentions of 3D BCNTs electrodes achieved 128.2 and 77.3%, respectively. Three-dimensional BCNT composite electrodes exhibit good conductivity and low charge transfer resistance, which is beneficial to fast charge transfer between the BCNTs electrode materials and electrolytes.     

A Novel Non-enzymatic Selective and Sensitive Glucose Sensor Based on Nickel-Copper Oxide@3D-rGO/MWCNTs

In this work, a modified 3D-rGO/MWCNT with nickel and copper oxide nanoparticles were synthesized. The structural properties of this nanocomposite were investigated by several techniques. The fabricated sensor at optimum condition potential of +0.60 V (vs. Ag/AgCl) and a rotational rate of 1800 rpm gave a detection limit of 0.04 μmol L⁻¹ with two dynamic ranges of 0.10–300 and 300–900 μmol L⁻¹ glucose with high stability. The good accuracy of the fabricated sensor was proved in the determination of glucose in a blood sample (with recoveries between 95 % to 105 % and RSDs of 1.2 to 2.5 %).     

Highly Sensitive Electrochemical Immunosensor Based on Mesoporous PdPt Nanoparticles Anchored on a Three-dimensional PANI@CNTs Network as Nanozyme Labels

In this study, a novel strategy to amplify electrochemical signals by mesoporous PdPt nanoparticles with core-shell structures anchored on a three-dimensional PANI@CNTs network as nanozyme labels (PdPt/PANI@CNTs) was proposed for the sensitive monitoring of α-fetoprotein (AFP, Ag). First, the mesoporous PdPt nanoparticles prepared by a facile chemical reduction method had excellent biocompatibility with biomolecules, which could capture a large amount of AFP-Ab₂ (Ab₂) and exhibit plentiful pores to entrap more thionine (Thi) into mesoporous PdPt nanoparticles with enhanced loading and abundant active sites. Furthermore, the resulting mesoporous PdPt nanoparticles were abundantly dotted on the surface of a three-dimensional PANI@CNTs network with excellent conductivity and a high specific surface area through the bonding of the amino group to form PdPt/PANI@CNTs nanozyme labels. Most importantly, the as-prepared PdPt/PANI@CNTs nanozyme labels exhibited unexpected enzyme-like activity towards the reduction of hydrogen peroxide owing to the highly indexed facets, enhancing the current response to realize signal amplification. In view of the advantages of nanozyme labels and the involvement of gold nanoparticles (AuNPs, which behave as electrode materials) for the sensitive determination of AFP, the as-developed immunosensor could obtain a dynamic working range of 0.001 ng mL^−1–100.0 ng mL⁻¹ at a detection limit of 0.33 pg mL⁻¹ via DPV (at 3σ). Furthermore, the nanozyme-based electrochemical immunosensor exhibited remarkable analytical performance, which brought about feasible ideas for disease diagnosis in the future.     

Parameter space of the Rulkov chaotic neuron model

The parameter space of the two dimensional Rulkov chaotic neuron model is taken into account by using the qualitative analysis, the co-dimension 2 bifurcation, the center manifold theorem, and the normal form. The goal is intended to clarify analytically different dynamics and firing regimes of a single neuron in a two dimensional parameter space. Our research demonstrates the origin that there exist very rich nonlinear dynamics and complex biological firing regimes lies in different domains and their boundary curves in the two dimensional parameter plane. We present the parameter domains of fixed points, the saddle-node bifurcation, the supercritical/subcritical Neimark–Sacker bifurcation, stability conditions of non hyperbolic fixed points and quasiperiodic solutions. Based on these parameter domains, it is easy to know that the Rulkov chaotic neuron model can produce what kinds of firing regimes as well as their transition mechanisms. These results are very useful for building-up a large-scale neuron network with different biological functional roles and cognitive activities, especially in establishing some specific neuron network models of neurological diseases.     

An explicit recursive formula for computing the normal forms associated with semisimple cases

This paper presents an explicit, computationally efficient, recursive formula for computing the normal forms, center manifolds and nonlinear transformations for general n-dimensional systems, associated with semisimple singularities. Based on the formula, we develop a Maple program, which is very convenient for an end-user who only needs to prepare an input file and then execute the program to “automatically” generate the result. Several examples are presented to demonstrate the computational efficiency of the algorithm.     

Stability of hyperbolic manifolds with cusps under Ricci flow

We show that every finite volume hyperbolic manifold of dimension greater than or equal to 3 is stable under rescaled Ricci flow, i.e. that every small perturbation of the hyperbolic metric flows back to the hyperbolic metric again. Note that we do not need to make any decay assumptions on this perturbation.