Kinetic parameters for thermal decomposition of hydrazine

The propulsion of most of the operating satellites comprises monopropellant (hydrazine - N2H4) or bipropellant (monometilydrazine - MMH and nitrogen tetroxide) chemical systems. When some sample of the propellant tested fails, the entire sample lot shall be rejected, and this action has turned into a health problem due to the high toxicity of N2H 4. Thus, it is interesting to know hydrazine thermal behavior in several storage conditions. The kinetic parameters for thermal decomposition of hydrazine in oxygen and nitrogen atmospheres were determined by Capela-Ribeiro nonlinear isoconversional method. From TG data at heating rates of 5, 10, and 20 C min-1, kinetic parameters could be determined in nitrogen (E = 47.3 ± 3.1 kJ mol-1, lnA = 14.2 ± 0.9 and T b = 69 C) and oxygen (E = 64.9 ± 8.6 kJ mol-1, lnA = 20.7 ± 3.1 and T b = 75 C) atmospheres. It was not possible to identify a specific kinetic model for hydrazine thermal decomposition due to high heterogeneity in reaction; however, experimental f(α)g(α) master-plot curves were closed to F 1/3 model. © 2013 Akadémiai Kiadó, Budapest, Hungary.

Electrochemical kinetic study of surface layer growth on natural pyrite in acid medium

This paper presents electrochemical experiments on natural pyrite that combine potentiostatic and voltammetric techniques. X-ray microanalysis is used as an auxiliary technique. The layer growth on pyrite surface is conducted in a wide range of pH and potential range: 3.4 <= pH <= 5.9 with E = 0.80 V (versus SHE), and 0.80 V <= E <= 1.00 V with pH 4.5 (versus SHE) in acetic acid-acetate buffer. This work is unique for two reasons: (1) phenomenological model about layer growth is applied and mathematical-physic consistence is verified and (2) Meyer's hypotheses of chemical mechanism are used to explain kinetic parameters of the phenomenological model. (c) 2005 Elsevier B.V. All rights reserved.

The kinetic of mullite crystallization: Effect of water content

The kinetic of mullite crystallization from sol–gel method, with different water content, was investigated under non-isothermal conditions using DTA. The sols were obtained from Al(NO3)3.9H2O (ANN) and Si(OC2H5)4 (TEOS) mixtures by varying the water–alcohol content of the system. The crystalline phase changes were verified by X-ray diffraction (XRD). For a sample prepared using ethanol-based alkoxide solution (M0), only Al-poor mullite (p-mullite) crystallizes at 1000 °C; for the one synthesized with low water concentration (M6) Al-rich mullite (r-mullite) and spinel crystallize together; and for a sample prepared using a water-based alkoxide solution only spinel is formed. Thus, the variation of water contents during the synthesis caused great variations in the course of mullitization process. The average value of the apparent activation energy determined for p-mullite, r-mullite and spinel phase crystallization were found to be E = (899 ± 61) kJ mol−1, E = (1015 ± 272) kJ mol−1 and E = (980 ± 196) kJ mol−1, respectively. These results showed that sample M(0) was a monophasic gel, where aluminum and silicon atoms are mixed at a molecular level while sample M(100) was a diphasic gel, where silicon and aluminum atoms are distributed in a nanometric level. The fast reaction between TEOS and water molecules is responsible for this great difference in the sample's homogeneity. The kinetic model of the crystallization process was determined using Malek's procedure. It was established that the crystallization of p-mullite, r-mullite and spinel phase can be described by Šesták–Berggren autocatalytic model.

Application of succinylated sugarcane bagasse as adsorbent to remove methylene blue and gentian violet from aqueous solutions - Kinetic and equilibrium studies

In a previous work, succinylated sugarcane bagasse (SCB 2) was prepared from sugarcane bagasse (B) using succinic anhydride as modifying agent. In this work the adsorption of cationic dyes onto SCB 2 from aqueous solutions was investigated. Methylene blue, MB, and gentian violet, GV, were selected as adsorbates. The capacity of SCB 2 to adsorb MB and GV from aqueous single dye solutions was evaluated at different contact times, pH, and initial adsorbent concentration. According to the obtained results, the adsorption processes could be described by the pseudo-second-order kinetic model. Adsorption isotherms were well fitted by Langmuir model. Maximum adsorption capacities for MB and GV onto SCB 2 were found to be 478.5 and 1273.2 mg/g, respectively. (C) 2011 Elsevier Ltd. All rights reserved.

Determination of the intrinsic kinetic parameters of sulfide-oxidizing autotrophic denitrification in differential reactors containing immobilized biomass

Nitrogen removal coupled with sulfide oxidation has potential for the treatment of effluents from anaerobic reactors because they contain sulfide, which can be used as an endogenous electron donor for denitrification. This work evaluated the intrinsic kinetics of sulfide-oxidizing autotrophic denitrification via nitrate and nitrite in systems containing attached cells. Differential reactors were fed with nitrified synthetic domestic sewage and different sulfide concentrations. The intrinsic kinetic parameters of nitrogen removal were determined when the mass transfer resistance was negligible. This bioprocess could be described by a half-order kinetic model for biofilms. The half-order kinetic coefficients ranged from 0.425 to 0.658 mg N-1/2 L-1/2 h(-1) for denitrification via nitrite and from 0.190 to 0.609 mg N-1/2 L-1/2 h(-1) for denitrification via nitrate. In this latter, the lower value was due to the use of electrons donated from intermediary sulfur compounds whose formation and subsequent consumption were detected. (C) 2011 Elsevier Ltd. All rights reserved.

Lesion detection and classification in breast cancer: evaluation of approaches based on morphological features, tracer kinetic modelling and semi-quantitative parameters in MR functional imaging (DCE-MRI)

The diagnosis, grading and classification of tumours has benefited considerably from the development of DCE-MRI which is now essential to the adequate clinical management of many tumour types due to its capability in detecting active angiogenesis. Several strategies have been proposed for DCE-MRI evaluation. Visual inspection of contrast agent concentration curves vs time is a very simple yet operator dependent procedure, therefore more objective approaches have been developed in order to facilitate comparison between studies. In so called model free approaches, descriptive or heuristic information extracted from time series raw data have been used for tissue classification. The main issue concerning these schemes is that they have not a direct interpretation in terms of physiological properties of the tissues. On the other hand, model based investigations typically involve compartmental tracer kinetic modelling and pixel-by-pixel estimation of kinetic parameters via non-linear regression applied on region of interests opportunely selected by the physician. This approach has the advantage to provide parameters directly related to the pathophysiological properties of the tissue such as vessel permeability, local regional blood flow, extraction fraction, concentration gradient between plasma and extravascular-extracellular space. Anyway, nonlinear modelling is computational demanding and the accuracy of the estimates can be affected by the signal-to-noise ratio and by the initial solutions. The principal aim of this thesis is investigate the use of semi-quantitative and quantitative parameters for segmentation and classification of breast lesion. The objectives can be subdivided as follow: describe the principal techniques to evaluate time intensity curve in DCE-MRI with focus on kinetic model proposed in literature; to evaluate the influence in parametrization choice for a classic bi-compartmental kinetic models; to evaluate the performance of a method for simultaneous tracer kinetic modelling and pixel classification; to evaluate performance of machine learning techniques training for segmentation and classification of breast lesion.

Implementation of a phenomenological evaporation model into a porous network simulation for water management in low temperature fuel cells

A phenomenological transition film evaporation model was introduced to a pore network model with the consideration of pore radius, contact angle, non-isothermal interface temperature, microscale fluid flows and heat and mass transfers. This was achieved by modeling the transition film region of the menisci in each pore throughout the porous transport layer of a half-cell polymer electrolyte membrane (PEM) fuel cell. The model presented in this research is compared with the standard diffusive fuel cell modeling approach to evaporation and shown to surpass the conventional modeling approach in terms of predicting the evaporation rates in porous media. The current diffusive evaporation models used in many fuel cell transport models assumes a constant evaporation rate across the entire liquid-air interface. The transition film model was implemented into the pore network model to address this issue and create a pore size dependency on the evaporation rates. This is accomplished by evaluating the transition film evaporation rates determined by the kinetic model for every pore containing liquid water in the porous transport layer (PTL). The comparison of a transition film and diffusive evaporation model shows an increase in predicted evaporation rates for smaller pore sizes with the transition film model. This is an important parameter when considering the micro-scaled pore sizes seen in the PTL and becomes even more substantial when considering transport in fuel cells containing an MPL, or a large variance in pore size. Experimentation was performed to validate the transition film model by monitoring evaporation rates from a non-zero contact angle water droplet on a heated substrate. The substrate was a glass plate with a hydrophobic coating to reduce wettability. The tests were performed at a constant substrate temperature and relative humidity. The transition film model was able to accurately predict the drop volume as time elapsed. By implementing the transition film model to a pore network model the evaporation rates present in the PTL can be more accurately modeled. This improves the ability of a pore network model to predict the distribution of liquid water and ultimately the level of flooding exhibited in a PTL for various operating conditions.

Kinetic modeling of sodium in the lunar exosphere

Our knowledge about the lunar environment is based on a large volume of ground-based, remote, and in situ observations. These observations have been conducted at different times and sampled different pieces of such a complex system as the surface-bound exosphere of the Moon. Numerical modeling is the tool that can link results of these separate observations into a single picture. Being validated against previous measurements, models can be used for predictions and interpretation of future observations results. In this paper we present a kinetic model of the sodium exosphere of the Moon as well as results of its validation against a set of ground-based and remote observations. The unique characteristic of the model is that it takes the orbital motion of the Moon and the Earth into consideration and simulates both the exosphere as well as the sodium tail self-consistently. The extended computational domain covers the part of the Earth’s orbit at new Moon, which allows us to study the effect of Earth’s gravity on the lunar sodium tail. The model is fitted to a set of ground-based and remote observations by tuning sodium source rate as well as values of sticking, and accommodation coefficients. The best agreement of the model results with the observations is reached when all sodium atoms returning from the exosphere stick to the surface and the net sodium escape rate is about 5.3 × 1022 s−1.

A model for amplification of hair-bundle motion by cyclical binding of Ca2+ to mechanoelectrical-transduction channels

Amplification of auditory stimuli by hair cells augments the sensitivity of the vertebrate inner ear. Cell-body contractions of outer hair cells are thought to mediate amplification in the mammalian cochlea. In vertebrates that lack these cells, and perhaps in mammals as well, active movements of hair bundles may underlie amplification. We have evaluated a mathematical model in which amplification stems from the activity of mechanoelectrical-transduction channels. The intracellular binding of Ca2+ to channels is posited to promote their closure, which increases the tension in gating springs and exerts a negative force on the hair bundle. By enhancing bundle motion, this force partially compensates for viscous damping by cochlear fluids. Linear stability analysis of a six-state kinetic model reveals Hopf bifurcations for parameter values in the physiological range. These bifurcations signal conditions under which the system’s behavior changes from a damped oscillatory response to spontaneous limit-cycle oscillation. By varying the number of stereocilia in a bundle and the rate constant for Ca2+ binding, we calculate bifurcation frequencies spanning the observed range of auditory sensitivity for a representative receptor organ, the chicken’s cochlea. Simulations using prebifurcation parameter values demonstrate frequency-selective amplification with a striking compressive nonlinearity. Because transduction channels occur universally in hair cells, this active-channel model describes a mechanism of auditory amplification potentially applicable across species and hair-cell types.

A constant radius of curvature model for the organization of DNA in toroidal condensates.

Toroidal DNA condensates have received considerable attention for their possible relationship to the packaging of DNA in viruses and in general as a model of ordered DNA condensation. A spool-like model has primarily been supported for DNA organization within toroids. However, our observations suggest that the actual organization may be considerably different. We present an alternate model in which DNA for a given toroid is organized within a series of equally sized contiguous loops that precess about the toroid axis. A related model for the toroid formation process is also presented. This kinetic model predicts a distribution of toroid sizes for DNA condensed from solution that is in good agreement with experimental data.

Kinetics of the combustion of olive oil. A semi-global model

Support for this work was provided by PROMETEO/2009/043/FEDER of Generalitat Valenciana (Spain) and CTQ2008-05520 (Spanish MCI/research).

Kinetic study and thermal decomposition behavior of viscoelastic memory foam

A systematic investigation of the thermal decomposition of viscoelastic memory foam (VMF) was performed using thermogravimetric analysis (TGA) to obtain the kinetic parameters, and thermogravimetric analysis coupled to Fourier Transformed Infrared Spectrometry (TGA-FTIR) and thermogravimetric analysis coupled to Mass Spectrometry (TGA-MS) to obtain detailed information of evolved products on pyrolysis and oxidative degradations. Two consecutive nth-order reactions were employed to correlate the experimental data from dynamic and isothermal runs performed at three different heating rates (5, 10 and 20 K/min) under an inert atmosphere. On the other hand, for the kinetic study of the oxidative decomposition, the data from combustion (synthetic air) and poor oxygen combustion (N2:O2 = 9:1) runs, at three heating rates and under dynamic and isothermal conditions, were correlated simultaneously. A kinetic model consisting of three consecutive reactions presented a really good correlation in all runs. TGA-FTIR analysis showed that the main gases released during the pyrolysis of VMF were determined as ether and aliphatic hydrocarbons, whereas in combustion apart from the previous gases, aldehydes, amines and CO2 have also been detected as the main gases. These results were confirmed by the TGA-MS.

Adsorption of food dyes onto chitosan: Optimization process and kinetic

Adsorption of food dyes acid blue 9 and food yellow 3 onto chitosan was optimized. Chitosan was obtained from shrimp wastes and characterized.Afull factorial design was used to analyze the effects of pH, stirring rate and contact time in adsorption capacity. In the optimal conditions, adsorption kinetics was studied and the experimental data were fitted with three kinetic models. The produced chitosan showed good characteristics for dye adsorption. The optimal conditions were: pH 3, 150rpm and 60 min for acid blue 9 and pH 3, 50rpm and 60 min for food yellow 3. In these conditions, the adsorption capacities values were 210mgg−1 and 295mgg−1 for acid blue 9 and food yellow 3, respectively. The Elovich kinetic model was the best fit for experimental data and it showed the chemical nature of dyes adsorption onto chitosan.

Three-dimensional kinetic simulations of active suspensions: effect of chemotaxis and steric interaction

In this work, the effects of chemotaxis and steric interactions in active suspensions are analyzed by extending the kinetic model proposed by Saintillan and Shelley [1, 2]. In this model, a conservation equation for the active particle configuration is coupled to the Stokes equation for the flow arising from the force dipole exerted by the particles on the fluid. The fluid flow equations are solved spectrally and the conservation equation is solved by second-order finite differencing in space and second-order Adams-Bashforth time marching. First, the dynamics in suspensions of oxytactic run-and-tumble bacteria confined in thin liquid films surrounded by air is investigated. These bacteria modify their tumbling behavior by making temporal comparisons of the oxygen concentration, and, on average, swim towards high concentrations of oxygen. The kinetic model proposed by Saintillan and Shelley [1, 2] is modified to include run-and-tumble effects and oxygentaxis. The spatio-temporal dynamics of the oxygen and bacterial concentration are analyzed. For small film thicknesses, there is a weak migration of bacteria to the boundaries, and the oxygen concentration is high inside the film as a result of diffusion; both bacterial and oxygen concentrations quickly reach steady states. Above a critical film thickness (approximately 200 micron), a transition to chaotic dynamics is observed and is characterized by turbulent-like 3D motion, the formation of bacterial plumes, enhanced oxygen mixing and transport into the film, and hydrodynamic velocities of magnitudes up to 7 times the single bacterial swimming speed. The simulations demonstrate that the combined effects of hydrodynamic interactions and oxygentaxis create collective three-dimensional instabilities which enhances oxygen availability for the bacteria. Our simulation results are consistent with the experimental findings of Sokolov et al. [3], who also observed a similar transition with increasing film thickness. Next, the dynamics in concentrated suspensions of active self-propelled particles in a 3D periodic domain are analyzed. We modify the kinetic model of Saintillan and Shelley [1, 2] by including an additional nematic alignment torque proportional to the local concentration in the equation for the rotational velocity of the particles, causing them to align locally with their neighbors (Doi and Edwards [4]). Large-scale three- dimensional simulations show that, in the presence of such a torque both pusher and puller suspensions are unstable to random fluctuations and are characterized by highly nematic structures. Detailed measures are defined to quantify the degree and direction of alignment, and the effects of steric interactions on pattern formation will be presented. Our analysis shows that steric interactions have a destabilizing effect in active suspensions.

Kinetic modelling of in vitro data of PI3K, mTOR1, PTEN enzymes and on-target inhibitors Rapamycin, BEZ235, and LY294002

The phosphatidylinositide 3-kinases (PI3K) and mammalian target of rapamycin-1 (mTOR1) are two key targets for anti-cancer therapy. Predicting the response of the PI3K/AKT/mTOR1 signalling pathway to targeted therapy is made difficult because of network complexities. Systems biology models can help explore those complexities but the value of such models is dependent on accurate parameterisation. Motivated by a need to increase accuracy in kinetic parameter estimation, and therefore the predictive power of the model, we present a framework to integrate kinetic data from enzyme assays into a unified enzyme kinetic model. We present exemplar kinetic models of PI3K and mTOR1, calibrated on in vitro enzyme data and founded on Michaelis-Menten (MM) approximation. We describe the effects of an allosteric mTOR1 inhibitor (Rapamycin) and ATP-competitive inhibitors (BEZ2235 and LY294002) that show dual inhibition of mTOR1 and PI3K. We also model the kinetics of phosphatase and tensin homolog (PTEN), which modulates sensitivity of the PI3K/AKT/mTOR1 pathway to these drugs. Model validation with independent data sets allows investigation of enzyme function and drug dose dependencies in a wide range of experimental conditions. Modelling of the mTOR1 kinetics showed that Rapamycin has an IC50 independent of ATP concentration and that it is a selective inhibitor of mTOR1 substrates S6K1 and 4EBP1: it retains 40% of mTOR1 activity relative to 4EBP1 phosphorylation and inhibits completely S6K1 activity. For the dual ATP-competitive inhibitors of mTOR1 and PI3K, LY294002 and BEZ235, we derived the dependence of the IC50 on ATP concentration that allows prediction of the IC50 at different ATP concentrations in enzyme and cellular assays. Comparison of the drug effectiveness in enzyme and cellular assays showed that some features of these drugs arise from signalling modulation beyond the on-target action and MM approximation and require a systems-level consideration of the whole PI3K/PTEN/AKT/mTOR1 network in order to understand mechanisms of drug sensitivity and resistance in different cancer cell lines. We suggest that using these models in systems biology investigation of the PI3K/AKT/mTOR1 signalling in cancer cells can bridge the gap between direct drug target action and the therapeutic response to these drugs and their combinations.