Temperature and metal composition dependence of lateral photovoltaic effect in Al-Alq3/SiO2/Si structures

A series of Al=-（Alq3）l-x granular films is prepared on Si wafer with native oxide layer using co-evaporation technique. Large lateral photovoltaic effect （LPE） is observed, with an optimal LPV sensitivity of 75 mV/mm in x=0.35 sample. The dependence of LPE on temperature and A1 composition is investigated, and the possible mechanism is discussed.     

Gadolinium‐Decorated Silica Microspheres as Redox‐Responsive MRI Probes for Applications in Cell Therapy Follow‐Up

The redox microenvironment within a cell graft can be considered as an indicator to assess whether the graft is metabolically active or hypoxic. We present a redox‐responsive MRI probe based on porous silica microparticles whose surface has been decorated with a Gd‐chelate through a disulphide bridge. Such microparticles are designed to be interspersed with therapeutic cells within a biocompatible hydrogel. The onset of reducing conditions within the hydrogel is paralleled by an increased clearance of Gd, that can be detected by MRI.     

Electrochemical Characteristics of “Polyaniline” Cathodes and Anodes in Aqueous Electrolytes

The quinoid-benzenoid-diimine form, (=(C₆H₄)=N-(C₆H₄)-N=)_x of “polyaniline” shows excellent cathode characteristics including recyclability when used in conjunction with a zinc anode in an aqueous electrolyte of (l. 0M ZnCl₂ + 0. 5M NH₄Cl) having a pH of ～ 4. The reduced form of this material, (-(C₆H₄)-N(H)-(C₆H₄)-N(H)-)_x can be used as an anode in conjunction with a Pb0₂ cathode in an aqueous 0.5M Pb(BF₄)₂ electrolyte.     

Electrostatic Interactions Leading to Hierarchical Interpenetrating Electroconductive Networks in Silicon Anodes for Fast Lithium Storage

Recently, the frequency of combining MXene, which has unique properties such as metal-level conductivity and large specific surface area, with silicon to achieve excellent electrochemical performance has increased considerably. There is no doubt that the introduction of MXene can improve the conductivity of silicon and the cycling stability of electrodes after elaborate structure design. However, most exhaustive contacts can only improve the electrode conductivity on the plane. Herein, a MXene@Si/CNTs (HIEN-MSC) composite with hierarchical interpenetrating electroconductive networks has been synthesized by electrostatic self-assembly. In this process, the CNTs are first combined with silicon nanoparticles and then assembled with MXene nanosheets. Inserting CNTs into silicon nanoparticles can not only reduce the latter‘s agglomeration, but also immobilizes them on the three-dimensional conductive framework composed of CNTs and MXene nanosheets. Therefore, the HIEN-MSC electrode shows superior rate performance (high reversible capacity of 280 mA h⁻¹ even tested at 10 A g⁻¹), cycling stability (stable reversible capacity of 547 mA h g⁻¹ after 200 cycles at 1 A g⁻¹) and applicability (a high reversible capacity of 101 mA h g⁻¹ after 50 cycles when assembled with NCM622 into a full cell). These results may provide new insights for other electrodes with excellent rate performance and long-cycle stability.     

Resolving overlapping peaks in ARXPS data: The effect of noise and fitting method

Peak-fitting of X-ray photoelectron spectroscopy (XPS) data can be very sensitive to noise when the difference on the binding energy among the peaks is smaller than the width of the peaks. This sensitivity depends on the fitting algorithm. Angle-resolved XPS (ARXPS) analysis offers the opportunity of employing the combined information contained in the data at the various angles to reduce the sensitivity to noise. The assumption of shared peak parameters (center and width) among the spectra for the different angles, and how it is introduced into the analysis, plays a basic role. Sequential fitting is the usual practice in ARXPS data peak-fitting. It consist on first estimating the center and width of the peaks from the data acquired at one of the angles, and then using those parameters as a starting approximation for fitting the data for each of the rest of the angles. An improvement of this method consists of averaging the centers and widths of the peaks obtained at the different angles, and then employing these values to assess the areas of the peaks for each angle. Another strategy for using the combined information is by assessing the peak parameters from the sum of the experimental data. The complete use of the combined information contained in the data-set is optimized by the simultaneous fitting method. It consists of the assessment of the center and width of the peaks by fitting the data at all the angles simultaneously. Computer-generated data was employed to compare the sensitivity with respect to noise between the sequential, averaged-sequential, sum, and simultaneous fitting methods. It is shown that the latter is significantly more robust and could provide reliable results even for noisy data and small peak separation. The fundamentals for the robustness of the simultaneous method are discussed, as well as the possibility of fitting many parameters at the same time. As an added feature of ARXPS, it was found that the estimation of the error intervals on the peak parameters is done remarkably more precisely by employing XPS data at various angles.     

Analysis of financial stock markets through multidimensional scaling based on information measures

In this paper, a novel multidimensional scaling (MDS) based on information measures method is proposed to analyze financial stock markets. In order to examine the effectiveness of this method, we applied it to the classification of two types of artificial series, the logistic map model and the cubic map model, as well as stock time series. Moreover, the traditional MDS using Euclidean dissimilarity is also provided as a reference for comparisons. The results show that the MDS based on information measures can give us more detailed, exact and clearer information on the classification of simulation series and stock time series than the MDS using Euclidean dissimilarity. In addition, the proposed graphical method may also assist in the construction of multivariate econometric models.     

Assembly of peptide–thiophene conjugates: the influence of peptide content and location

Biomolecule-directed self-assembly of π-conjugated oligomers has attracted great attention in the past decade. In this contribution, two conjugates composed of quaterthiophene and tetrapeptide (Gly-Val-Gly-Val) were synthesised, namely peptide–thiophene–peptide (PTP) and thiophene–peptide–thiophene (TPT), to investigate the influence of peptide content ratio and its location in the molecular structures on the nanostructures and properties of the assemblies. Both conjugates formed organogels consisting of left-handed twisted nanostructures; however, anti-parallel β-sheets were observed in PTP while parallel β-sheets were obtained for TPT, although in both cases oligothiophenes adopted an H-like stacking mode. Obvious solvent-induced supramolecular chirality inversion from the oligothiophene segment was observed for PTP while such phenomenon was not clear for TPT. PTP and TPT gels also showed different stabilities towards temperature increase, as evidenced by variable-temperature circular dichroism study. From the data, it is suggested that the rational design of the location and ratio of peptide plays a key role in constructing materials with determined properties based on peptide–thiophene conjugates.     

Boron-iron nanochains for selective electrocatalytic reduction of nitrate

The electrocatalysis of nitrate reduction reaction(NRR) has been considered to be a promising nitrate removal technology.Developing a highly effective iron-based electrocatalyst is an essential challenge for NRR.Herein,boron-iron nanochains(B-Fe NCs) as efficient NRR catalysts were prepared via a facile lowcost and scalable method.The Fe/B ratio of the B-Fe NCs-x can be elaborately adjusted to optimize the NRR catalytic performance.Due to the electron transfer from boron to metal,the metal-metal bonds are weakened and the electron density near the metal atom centers are rearranged,which are favor of the conversion from NO_3~-into N_2.Moreover,the well-crosslinked chain-like architectures benefit the mass/electron transport to boost the exposure of abundant catalytic active sites.Laboratory experiments demonstrated that the optimized B-Fe NCs catalyst exhibits superior intrinsic electrocatalytic NRR activity of high nitrate conversion(～80%),ultrahigh nitrogen selectivity(～99%) and excellent long-term reactivity in the mixed electrolyte system(0.02 mol/L NaCl and 0.02 mol/L Na_2 SO_4 mixed electrolyte),and the electrocatalytic activity of the material shows poor performance at low chloride ion concentration(Nitrate conversion of ～61 % and nitrogen selectivity of ～57% in 0.005 mol/L NaCl and 0.035 mol/L Na_2 SO_4 mixed electrolyte).This study provides a broad application prospect for further exploring the highefficiency and low-cost iron-based functional nanostructures for electrocatalytic nitrate reduction.