Efficient computation of adiabatic populations in multi-mode Jahn-Teller systems through the use of effective vibrational modes

A highly efficient scheme for computing adiabatic electronic populations in multi-mode Jahn-Teller systems is presented. It relies on the transformation to an effective-mode vibrational basis in which the relevant quantities depend on the coordinates of a single mode only. In this way, the generally tedious numerical evaluation of high-dimensional integrals is avoided and replaced by one-dimensional integrations. The effective-mode scheme is applied to a variety of two-mode and three-mode Jahn-Teller systems and gives a typical speedup of about two to three orders of magnitude as compared to the direct evaluation of the adiabatic populations. The gain grows rapidly with the numbers of modes.     

The Isolation and Determination of Sulforaphane from Broccoli Tissues by Reverse Phase‐High Performance Liquid Chromatography

Sulforaphane is a cognate isothiocyanate of glucoraphanin, released by degradation of glucosinolate through myrosinase enzyme, when Brassica tissues are crushed or chewed. C₈ analytical column and mixture of water/acetonitrile 65/35 (ν/ν) as mobile phase were used to separate sulforaphane in broccoli tissues (e.g., 7‐day‐seedling, seed, floret and leave). Confirmation of sulforaphane in crude extract of broccoli tissues was monitored using gas chromatography‐mass spectroscopy (GC‐MS). The highest amount of sulforaphane (1216 μg/g dry weight) found in 7‐day‐seedling. This method is suitable for routine screening of plant materials and proposes a low cost and robust technique for the analysis of sulforaphane.     

Recognition of \text {PSL}(2,p) by order and some information on its character degrees where p is a prime

Let \(G\) be a finite group and \(\text {cd}(G)\) be the set of irreducible character degrees of \(G\) . In this paper we prove that if \(p\) is a prime number, then the simple group \(\text {PSL}(2,p)\) is uniquely determined by its order and some information about its character degrees. In fact we prove that if \(G\) is a finite group such that (i) \(|G|=|\text {PSL}(2,p)|\) , (ii) \(p\in \text {cd}(G)\) , (iii) \(\text {cd}(G)\) has an even integer, and (iv) there does not exist any element \(a\in \text {cd}(G)\) such that \(2p\mid a\) , then \(G\cong \text {PSL}(2,p)\) . As a consequence of our result we get that \(\text {PSL}(2,p)\) is uniquely determined by its order and the largest and the second largest character degrees.     

Promoting lithium-ion battery performance by application of crystalline cathodes LixMn1−zFezPO4

Journal of Solid State Electrochemistry - LiMnPO4 (LMP) is known as a typical cathode for application in lithium-ion-batteries (LIB), since this cathode produces higher voltage. However, the...     

Comparing various machine learning approaches in modeling the dynamic viscosity of CuO/water nanofluid

Nanofluids are broadly employed in heat transfer mediums to enhance their efficiency and heat transfer capacity. Thermophysical properties of nanofluids play a crucial role in their thermal behavior. Among various properties, the dynamic viscosity is one of the most crucial ones due to its impact on fluid motion and friction. Applying appropriate models can facilitate the design of nanofluidics thermal devices. In the present study, various machine learning methods including MPR, MARS, ANN-MLP, GMDH, and M5-tree are used for modeling the dynamic viscosity of CuO/water nanofluid based on the temperature, concentration, and size of nanostructures. The input data are extracted from various experimental studies to propose a comprehensive model, applicable in wide ranges of input variables. Moreover, the relative importance of each variable is evaluated to figure out the priority of the variables and their influences on the dynamic viscosity. Finally, the accuracy of the models is compared by employing the statistical criteria such as R-squared value. The models’ outputs disclosed that employing ANN-MLP approach leads to the most precise model. R-square value and average absolute percent relative error (AAPR) value of the model by using ANN-MLP model are 0.9997 and 1.312%, respectively. According to these values, ANN-MLP is a reliable approach for predicting the dynamic viscosity of the studied nanofluid. Additionally, based on the relative importance of the input variables, it is concluded that concentration has the highest relative importance; while the influence of size is the lowest one.

     

Rapid, one-pot synthesis of highly-soluble carbon nanotubes functionalized by L-arginine

Functionalization of carbon nanotubes (CNTs) is a necessary step to exploit their valuable properties. Due to having several steps and especially acid treatment, most of current methods of functionalization result in irrecoverable defects on CNTs structure. Here, multiwalled carbon nanotubes (MWCNTs) were functionalized with L-arginine in a simple, one-pot and rapid microwave-assisted technique without any acid treatment step. The CNT functionalities were analyzed with infrared spectroscopy, thermogravimetric analysis, Raman spectroscopy, scanning electron microscopy, and transmission electron microscopy. The results confirmed the covalent functionalization of L-arginine with very low defects on CNTs. Also it is found that increase of input powers of microwave in the range 500–900 W, monotonically increase the degree of functionalization. The maximum dispersibility of MWCNT was found ～1.03 mg/mL corresponding to 900 W irradiation. Accounting considerable low treatment time, the method may be applied for large-scale solubilization of MWCNTs in an industrial scale.     

Homogeneous liquid‐phase microextraction followed by filtration‐based phase separation coupled to high‐performance liquid chromatography

A simple homogenous liquid‐phase microextraction methodology applying octanoic acid as the extraction phase was introduced for determination of chlorobenzenes. In this approach, phase separation phenomenon occurred by changing pH of the solution. The extraction phase was isolated based on filtration of emulsion instead of centrifugation and it was introduced to the high‐performance liquid chromatography instrument as an on‐line procedure. This method was used for extraction and determination of five chlorobenzenes in different samples. Experimental design and response surface methodology were used for the optimization of various parameters influencing the extraction efficiency of the method. Under optimal conditions, chlorobenzenes were effectively extracted, and preconcentration factors of 255–294 were obtained. The calibration curves were investigated in the concentration range of 1–200 μg/L and good linearity was achieved with coefficient of determinations better than 0.997. Limits of detection of 0.1 and 0.3 μg/L and suitable precision with relative standard deviations better than 5.1% (n = 5) were attained. Finally, the proposed method was applied to determine the concentration of chlorobenzenes in different samples and acceptable recoveries were gained.     

Lead(II)-selective electrode based on phenyl disulfide.

A PVC membrane electrode for lead ions based on phenyl disulfide as the membrane carrier was developed. The electrode exhibits a good Nernstian slope of 29.3 +/- 0.7 mV/decade and a linear range of 2.0 x 10(-6)-1.0 x 10(-2) M for Pb(NO3)2. The limit of detection is 1.2 x 10(-6) M. It has a response time of 45 s and can be used for at least fifty days without any divergence in potential. The proposed membrane sensor revealed high selectivity for Pb2+ over a wide variety of other metal ions and could be used in the pH range of 3.5-6.3. The electrode was used as an indicator electrode in potentiometric titration of lead ions.     

The 13C chemical shifts of 2′-hydroxy-substituted N-benzylidene-anilines and some N,N-(o-hydroxy-benzylidene)diamines

¹³C chemical shifts of fourteen substituted 2′-hydroxy-N-benzylidene-anilines and three N,N-(o-hydroxy-benzylidene)-diamines are reported.     

Improving the performance of a photonic crystal ring-resonator-based channel drop filter using particle swarm optimization method

The optical channel drop filters (CDFs) based on photonic crystals (PCs) are believed to be the essential components for compact photonic integrated circuits and WDM systems. One of the promising designs for a PC-CDF is based on the photonic crystal ring resonators (PCRRs). In this study, different parameters of a PCRR based CDF is optimized by using the particle swarm optimization (PSO) method in conjunction with the numerical method of two-dimensional (2D) finite-difference time-domain (FDTD) in a square lattice dielectric-rod 2D-PC. Hence a PC-CDF with ideal drop efficiency, large free spectral range (FSR) and acceptable quality factor will be proposed.