Stochastic linear multistep methods for the simulation of chemical kinetics

In this paper, we introduce the Stochastic Adams-Bashforth (SAB) and Stochastic Adams-Moulton (SAM) methods as an extension of the tau-leaping framework to past information. Using the theta-trapezoidal tau-leap method of weak order two as a starting procedure, we show that the k-step SAB method with k >= 3 is order three in the mean and correlation, while a predictor-corrector implementation of the SAM method is weak order three in the mean but only order one in the correlation. These convergence results have been derived analytically for linear problems and successfully tested numerically for both linear and non-linear systems. A series of additional examples have been implemented in order to demonstrate the efficacy of this approach.

Double diffusive Marangoni convection flow of electrically conducting fluid in a square cavity with chemical reaction

Double diffusive Marangoni convection flow of viscous incompressible electrically conducting fluid in a square cavity is studied in this paper by taking into consideration of the effect of applied magnetic field in arbitrary direction and the chemical reaction. The governing equations are solved numerically by using alternate direct implicit (ADI) method together with the successive over relaxation (SOR) technique. The flow pattern with the effect of governing parameters, namely the buoyancy ratio W, diffusocapillary ratio w, and the Hartmann number Ha, is investigated. It is revealed from the numerical simulations that the average Nusselt number decreases; whereas the average Sherwood number increases as the orientation of magnetic field is shifted from horizontal to vertical. Moreover, the effect of buoyancy due to species concentration on the flow is stronger than the one due to thermal buoyancy. The increase in diffusocapillary parameter, w caus

Efficient simulation of stochastic chemical kinetics with the Stochastic Bulirsch-Stoer extrapolation method

Background Biochemical systems with relatively low numbers of components must be simulated stochastically in order to capture their inherent noise. Although there has recently been considerable work on discrete stochastic solvers, there is still a need for numerical methods that are both fast and accurate. The Bulirsch-Stoer method is an established method for solving ordinary differential equations that possesses both of these qualities. Results In this paper, we present the Stochastic Bulirsch-Stoer method, a new numerical method for simulating discrete chemical reaction systems, inspired by its deterministic counterpart. It is able to achieve an excellent efficiency due to the fact that it is based on an approach with high deterministic order, allowing for larger stepsizes and leading to fast simulations. We compare it to the Euler τ-leap, as well as two more recent τ-leap methods, on a number of example problems, and find that as well as being very accurate, our method is the most robust, in terms of efficiency, of all the methods considered in this paper. The problems it is most suited for are those with increased populations that would be too slow to simulate using Gillespie’s stochastic simulation algorithm. For such problems, it is likely to achieve higher weak order in the moments. Conclusions The Stochastic Bulirsch-Stoer method is a novel stochastic solver that can be used for fast and accurate simulations. Crucially, compared to other similar methods, it better retains its high accuracy when the timesteps are increased. Thus the Stochastic Bulirsch-Stoer method is both computationally efficient and robust. These are key properties for any stochastic numerical method, as they must typically run many thousands of simulations.

A novel near-infrared spectroscopy and chemometrics method for rapid analysis of several chemical components and antioxidant activity of mint (mentha haplocalyx briq.) samples

A novel near-infrared spectroscopy (NIRS) method has been researched and developed for the simultaneous analyses of the chemical components and associated properties of mint (Mentha haplocalyx Briq.) tea samples. The common analytes were: total polysaccharide content, total flavonoid content, total phenolic content, and total antioxidant activity. To resolve the NIRS data matrix for such analyses, least squares support vector machines was found to be the best chemometrics method for prediction, although it was closely followed by the radial basis function/partial least squares model. Interestingly, the commonly used partial least squares was unsatisfactory in this case. Additionally, principal component analysis and hierarchical cluster analysis were able to distinguish the mint samples according to their four geographical provinces of origin, and this was further facilitated with the use of the chemometrics classification methods-K-nearest neighbors, linear discriminant analysis, and partial least squares discriminant analysis. In general, given the potential savings with sampling and analysis time as well as with the costs of special analytical reagents required for the standard individual methods, NIRS offered a very attractive alternative for the simultaneous analysis of mint samples.

Particle emissions from biodiesels with different physical properties and chemical composition

Biodiesels produced from different feedstocks usually have wide variations in their fatty acid methyl ester (FAME) so that their physical properties and chemical composition are also different. The aim of this study is to investigate the effect of the physical properties and chemical composition of biodiesels on engine exhaust particle emissions. Alongside with neat diesel, four biodiesels with variations in carbon chain length and degree of unsaturation have been used at three blending ratios (B100, B50, B20) in a common rail engine. It is found that particle emission increased with the increase of carbon chain length. However, for similar carbon chain length, particle emissions from biodiesel having relatively high average unsaturation are found to be slightly less than that of low average unsaturation. Particle size is also found to be dependent on fuel type. The fuel or fuel mix responsible for higher particle mass (PM) and particle number (PN) emissions is also found responsible for larger particle median size. Particle emissions reduced consistently with fuel oxygen content regardless of the proportion of biodiesel in the blends, whereas it increased with fuel viscosity and surface tension only for higher diesel–biodiesel blend percentages (B100, B50). However, since fuel oxygen content increases with the decreasing carbon chain length, it is not clear which of these factors drives the lower particle emission. Overall, it is evident from the results presented here that chemical composition of biodiesel is more important than its physical properties in controlling exhaust particle emissions.

Systematic and Day-to-Day Effects of Chemical-Derived Population Estimates on Wastewater-Based Drug Epidemiology

Population size is crucial when estimating population-normalized drug consumption (PNDC) from wastewater-based drug epidemiology (WBDE). Three conceptually different population estimates can be used: de jure (common census, residence), de facto (all persons within a sewer catchment), and chemical loads (contributors to the sampled wastewater). De facto and chemical loads will be the same where all households contribute to a central sewer system without wastewater loss. This study explored the feasibility of determining a de facto population and its effect on estimating PNDC in an urban community over an extended period. Drugs and other chemicals were analyzed in 311 daily composite wastewater samples. The daily estimated de facto population (using chemical loads) was on average 32% higher than the de jure population. Consequently, using the latter would systemically overestimate PNDC by 22%. However, the relative day-to-day pattern of drug consumption was similar regardless of the type of normalization as daily illicit drug loads appeared to vary substantially more than the population. Using chemical loads population, we objectively quantified the total methodological uncertainty of PNDC and reduced it by a factor of 2. Our study illustrated the potential benefits of using chemical loads population for obtaining more robust PNDC data in WBDE.

Nitrogen-doped graphene films from chemical vapor deposition of pyridine: Influence of process parameters on the electrical and optical properties

Graphene films were produced by chemical vapor deposition (CVD) of pyridine on copper substrates. Pyridine-CVD is expected to lead to doped graphene by the insertion of nitrogen atoms in the growing sp2 carbon lattice, possibly improving the properties of graphene as a transparent conductive film. We here report on the influence that the CVD parameters (i.e., temperature and gas flow) have on the morphology, transmittance, and electrical conductivity of the graphene films grown with pyridine. A temperature range between 930 and 1070 °C was explored and the results were compared to those of pristine graphene grown by ethanol-CVD under the same process conditions. The films were characterized by atomic force microscopy, Raman and X-ray photoemission spectroscopy. The optical transmittance and electrical conductivity of the films were measured to evaluate their performance as transparent conductive electrodes. Graphene films grown by pyridine reached an electrical conductivity of 14.3 × 105 S/m. Such a high conductivity seems to be associated with the electronic doping induced by substitutional nitrogen atoms. In particular, at 930 °C the nitrogen/carbon ratio of pyridine-grown graphene reaches 3%, and its electrical conductivity is 40% higher than that of pristine graphene grown from ethanol-CVD.

Growth and electron effective mass measurements of strained Si and Si0.94Ge0.06 on relaxed Si0.62Ge0.38 buffers grown by rapid thermal chemical vapor deposition

Abstract: We report the growth and the electron cyclotron resonance measurements of n-type Si/Si0.62Ge0.38 and Si0.94Ge0.06/Si0.62Ge0.38 modulation-doped heterostructures grown by rapid thermal chemical vapor deposition. The strained Si and Si0.94Ge0.06 channels were grown on relaxed Si0.62Ge0.38 buffer layers, which consist of 0.6 mu m uniform Si0.62Ge0.38 layers and 0.5 mu m compositionally graded relaxed SiGe layers from 0 to 38% Ge. The buffer layers were annealed at 800 degrees C for 1 h to obtain complete relaxation. A 75 Angstrom Si(SiGe) channel with a 100 Angstrom spacer and a 300 Angstrom 2 X 10(19) cm(-3) n-type supply layer was grown on the top of the buffer layers. The cross-sectional transmission electron microscope reveals that the dense dislocation network is confined to the buffer layer, and relatively few dislocations terminate on the surface. The plan-view image indicates the threading dislocation density is about 4 X 10(6) cm(-2). The far-infrared measurements of electron cyclotron resonance were performed at 4 K with the magnetic field of 4-8 T. The effective masses determined from the slope of the center frequency of the absorption peak versus applied magnetic field plot are 0.203m(0) and 0.193m(0) for the two dimensional electron gases in the Si and Si0.94Ge0.06 channels, respectively. The Si effective mass is very close to that of a two dimensional electron gas in an Si MOSFET (0.198m(0)). The electron effective mass of Si0.94Ge0.06 is reported for the first time and is about 5% lower than that of pure Si.

Surface chemical studies of Thiobacillus ferrooxidans with reference to copper tolerance

A strain of Thiobacillus ferrooxidans was adapted to grow at higher concentrations of copper by single step culturing in the presence of 20 g/L (0.314 mol/L) cupric ions added to 9K medium. Exposure to copper results in change in the surface chemistry of the microorganism. The isoelectric point of the adapted strain (pI=4.7) was observed to be at a higher pH than that of the wild unadapted strain(pI=2.0). Compared to the wild strain, the copper adapted strain was found to be more hydrophobic and showed enhanced attachment efficiency to the pyrite mineral. The copper adsorption ability of the adapted strain was also found to be higher than that of the wild strain. Fourier transform infrared spectroscopy of adapted cells suggested that a proteinaceous new cell surface component is synthesized by the adapted strain. Treatment of adapted cells with proteinase-K, resulted in complete loss of tolerance to copper, reduction in copper adsorption and hydrophobicity of the adapted cells. These observations strongly suggest a role played by cell surface modifications of Thiobacillus ferrooxidans in imparting the copper tolerance to the cells and bioleaching of sulphide minerals.

Surface chemical studies on mica and galena using dextrin

The interactions of dextrin with biotite mica and galena have been investigated through adsorption, flotation, and electrokinetic measurements. The adsorption densities of dextrin onto mica continuously increase with increase of pH, while those onto galena show a maximum at pH 11.5. It is observed that the adsorption density of dextrin onto galena is quite high compared to that on mica. Both the adsorption isotherms exhibit Langmuirian behavior. Electrokinetic measurements portray conformational rearrangements of macromolecules with the loading, resulting in a shift of the shear plane, further away from the interface. Dissolution experiments indicate release of the lattice metal ions from mica and galena. Coprecipitation tests confirm polymer-metal ion interaction in the bulk solution. Dextrin does not exhibit any depressant action toward mica, whereas, with galena, the flotation recovery is decreased with an increase in pH beyond 9, in the presence of dextrin, complementing the adsorption results. Differential flotation results on a synthetic mixture of mica and galena show that mica can be selectively separated from galena using dextrin as a depressant for galena above pH 10. Possible mechanisms of interaction between dextrin and mica/galena are discussed.

The role of lysine-41 in RNase A catalysis - A quantum chemical study on the active site ligand complex

Several mechanisms have been proposed to explain the action of enzymes at the atomic level. Among them, the recent proposals involving short hydrogen bonds as a step in catalysis by Gerlt and Gassman [1] and proton transfer through low barrier hydrogen bonds (LBHBs) [2, 3] have attracted attention. There are several limitations to experimentally testing such hypotheses, Recent developments in computational methods facilitate the study of active site-ligand complexes to high levels of accuracy, Our previous studies, which involved the docking of the dinucleotide substrate UpA to the active site of RNase A [4, 5], enabled us to obtain a realistic model of the ligand-bound active site of RNase A. From these studies, based on empirical potential functions, we were able to obtain the molecular dynamics averaged coordinates of RNase A, bound to the ligand UpA. A quantum mechanical study is required to investigate the catalytic process which involves the cleavage and formation of covalent bonds. In the present study, we have investigated the strengths of some of the hydrogen bonds between the active site residues of RNase A and UpA at the ab initio quantum chemical level using the molecular dynamics averaged coordinates as the starting point. The 49 atom system and other model systems were optimized at the 3-21G level and the energies of the optimized systems were obtained at the 6-31G* level. The results clearly indicate the strengthening of hydrogen bonds between neutral residues due to the presence of charged species at appropriate positions. Such a strengthening manifests itself in the form of short hydrogen bonds and a low barrier for proton transfer. In the present study, the proton transfer between the 2'-OH of ribose (from the substrate) and the imidazole group from the H12 of RNase A is influenced by K41, which plays a crucial role in strengthening the neutral hydrogen bond, reducing the barrier for proton transfer.

The influence of the gas environment on morphology and chemical composition of surfaces micro-machined with a femtosecond laser

We investigated the influence of different gas environments on the fabrication of surfaces, homogeneously covered with equally sized and spaced micro-structures. Two types of structures have been successfully micro-machined with a femtosecond laser on titanium surfaces in various atmospheres. The surface chemistry of samples machined in oxygen and helium shows TiO2, while machining in nitrogen leads to an additional share of TiN. The actual surface structure was found to vary significantly as a function of the gas environment. We found that the ablated particles and their surface triggered two consecutive events: The optical properties of the gas environment became non-isotropic which then led to the pulse intensity being redistributed throughout the cross section of the laser beam. Additionally, the effective intensity was further reduced for TiN surfaces due to TiN's high reflectivity. Thus, the settings for the applied raster-scanning machining method had to be adjusted for each gas environment to produce comparable structures. In contrast to previous studies, where only noble gases were found suitable to produce homogeneous patches, we obtained them in an oxygen environment.

Homogeneous precipitation from solution by urea hydrolysis: a novel chemical route to the a-hydroxides of nickel and cobalt

Homogeneous precipitation from solution by hydrolysis of urea at elevated temperatures (T=120 degrees C) yields novel ammonia-intercalated alpha-type hydroxide phases of the formula M(OH)(x)(NH3)(0.4)(H2O)(y)(NO3)(2-x) where x=2, y=0.68 for M=Ni and x=1.85, y=0 for M=Co. These triple-layered hexagonal phases (a=3.08+/-0.01 Angstrom, c=21.7+/-0.05 Angstrom) are more crystalline than similar phases obtained by chemical precipitation or electrosynthesis. This method can be adapted as a convenient chemical route to the bulk synthesis of alpha-hydroxides.

Chemical Modification Studies of Gelonin - Involvement of Arginine Residues in Biological-Activity

Gelonin inhibits protein synthesis by inactivating the eukaryotic 60 S ribosomal subunit by an unknown mechanism. The protein was purified in high yield by a new method using Cibacron blue F3GA-Sepharose. Chemical modification studies reveal that arginine residues are essential for biological activity.

Composition of chemical attractants affects trap catches of the Australian sheep blowfly, lucilia cuprina, and other blowflies

Numbers of Lucilia cuprina (Australian sheep blowfly), Chrysomya spp., and Calliphora spp. blowflies caught on sticky traps baited with various synthetic attractants or a standard liver/sodium sulfide attractant in western Queensland were recorded. Numbers of each genus collected were influenced by the composition of the chemical attractants. Attractant mixtures based on 2-mercaptoethanol, indole, butanoic/pentanoic acid, and a sodium sulfide solution gave 5- to 20-fold higher L. cuprina catches than the liver standard. These blends attracted similar numbers of Chrysomya spp. (0.85–2.7× ) and fewer Calliphora spp. (0.02–0.2× ) compared to the liver standard. These synthetic attractants were more effective and selective for L. cuprina than the standard liver/sodium sulfide attractant, and they can be packaged in controlled-release dispensers to generate constant, prolonged release of the attractant.