Réaction oscillante de Belousov. 2. Etude d'un nouveau modèle cinétique

1977 ◽  
Vol 55 (17) ◽  
pp. 3147-3155 ◽  
Author(s):  
Guy Schmitz
Keyword(s):  
Kinetic Model ◽  
Kinetic Parameters ◽  
Analog Computer ◽  
Limiting Cycle ◽  
Oscillating Reaction

On the basis of our results dealing with the bromate-cerous reaction we propose and discuss a new kinetic model for the Belousov–Zhabotinskii oscillating reaction. The existence of a limiting cycle is shown with an analog computer for a set of semi-empirically chosen kinetic parameters.

Kinetic modelling of the photocatalytic inactivation of bacteria

2010 ◽  
Vol 61 (6) ◽  
pp. 1547-1553 ◽  
Author(s):  
Javier Marugán ◽  
Rafael van Grieken ◽  
Alberto E. Cassano ◽  
Orlando M. Alfano
Keyword(s):  
Kinetic Model ◽  
Kinetic Parameters ◽  
Catalyst Concentration ◽  
Kinetic Modelling ◽  
Kinetic Constant ◽  
Water Disinfection ◽  
Radiation Absorption ◽  
Simple Modification ◽  
Model Based ◽  
Photocatalytic Inactivation

This work analyzes the kinetic modelling of the photocatalytic inactivation of E. coli in water using different types of kinetic models; from an empirical equation to an intrinsic kinetic model including explicit radiation absorption effects. Simple empirical equations lead to lower fitting errors, but require a total of 12 parameters to reproduce the results of four inactivation curves when the catalyst concentration was increased. Moreover, these parameters have no physical meaning and cannot be extrapolated to different experimental conditions. The use of a pseudo-mechanistic model based on a simplified reaction mechanism reduces the number of required kinetic parameters to 6, being the kinetic constant the only parameter that depends on the catalyst concentration. Finally, a simple modification of a kinetic model based on the intrinsic mechanism of photocatalytic reactions including explicit radiation absorption effects achieved the fitting of all the experiments with only three parameters. The main advantage of this approach is that the kinetic parameters estimated for the model become independent of the irradiation form, as well as the reactor size and its geometrical configuration, providing the necessary information for scaling-up and design of commercial-scale photoreactors for water disinfection.

Kinetics and Modelling of Bulk and Solution Diallyl Terephthalate Polymerization

2006 ◽  
Vol 4 (1) ◽  
Author(s):  
Iztok Hace
Keyword(s):  
Kinetic Model ◽  
Kinetic Parameters ◽  
Rate Constants ◽  
Chain Transfer ◽  
Average Molecular Weight ◽  
Propagation Rate ◽  
Reaction Conditions ◽  
Diffusion Limitations ◽  
Kinetics Of ◽  
Dicyclohexyl Peroxydicarbonate

Free radical polymerization kinetics of diallyl terephthalate (DAT) in solution was investigated with two different peroxide initiators: dicyclohexyl peroxydicarbonate (CHPC) and benzoyl peroxide (BPO) in temperature range from 50°C to 110°C, where ortho-xylene was used as a solvent. Conversion points were measured using Fourier Transform Infrared (FTIR) measurements. Previously developed kinetic model for bulk DAT polymerization, was extended to solution DAT polymerization. The ratio of solvent chain - transfer rate constants to propagation rate constants of the polymerization system were found between 1.25 10-4 to 1.68 10-4 for various reaction conditions. They were obtained using the calculated initial polymerization rates and the number average molecular weight measurements made by GPC. The effect of different solvent fractions and initiator concentrations on the diffusion limitations were investigated. Only two kinetic parameters, kpd0 and ktd0 were obtained by fitting the kinetic model onto measured conversions for various reaction conditions at 0.2, 0.5 and 0.8 solvent fractions. Thus obtained kpd0 and ktd0 kinetic parameters were extrapolated to zero solvent fractions and from obtained values of kinetic parameters the conversion points for bulk DAT polymerization were calculated and compared to measured conversion points.

Predicting overall survival (OS) and overall response (OR) following durvalumab treatment in patients with multiple cancer types using a hybrid modeling strategy.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15161-e15161
Author(s):  
Ting Chen ◽  
Yanan Zheng ◽  
Lorin Roskos ◽  
Donald E Mager
Keyword(s):  
Kinetic Model ◽  
Kinetic Parameters ◽  
Rate Constant ◽  
Tumor Size ◽  
Hybrid Modeling ◽  
Tumor Growth Rate ◽  
Growth Rate Constant ◽  
Model Parameters ◽  
Cancer Types ◽  
Modeling Strategy

e15161 Background: This study aimed to predict OS/OR and identify key predictors in patients with diverse cancer types treated with durvalumab, a PD-L1 targeting monoclonal antibody, using a hybrid modeling strategy that combines population pharmacodynamic (PD) modeling and machine learning (ML) algorithms. Methods: Individual longitudinal tumor size measurements and OS/OR data were available for 855 patients who received durvalumab therapy (10 mg/kg Q2W or 20 mg/kg Q4W; NCT01693562). Nine cancer types included non-small cell lung cancer (NSCLC), bladder cancer (BC), microsatellite instability-high (MSI-H) cancer, hepatocellular carcinoma (HCC), squamous cell carcinoma of the head and neck (SCCHN), gastroesophageal cancer (GEC), ovarian cancer (OC), pancreatic adenocarcinoma (PDAC) and triple-negative breast cancer (TNBC). A tumor kinetic model was developed to characterize diverse temporal profiles using a population-based modeling approach. Individual estimated tumor kinetic model parameters and patient demographic/physiological factors were used as inputs for predicting OS/OR using several ML approaches. Results: The final tumor kinetic model with liver metastasis (LM), neutrophil/lymphocyte ratio (NLR), tumor size at baseline (TBSL) and cancer types as covariates characterized the temporal tumor size data well. HCC and MSI-H cancer have the slowest tumor growth rate constant (kg), while GEC, SCCHN and TNBC have the fastest kg. BC, NSCLC and OC have the highest tumor killing rate constant. The most important predictors of OS identified by ML approach were tumor kinetic parameters (kg, fraction of drug-sensitive cells, time-delay in immune response), along with baseline disease factors, including hemoglobin (HGBBL), albumin (ALB), and NLR. Decision tree-based algorithms showed the best performance in predicting OR with accuracy above 90%. In addition to tumor kinetic parameters, PD-L1 expression on tumor cells (TC) and ALB were the most important predictors of OR. Conclusions: A combined population PD/ML approach showed good predictions of OS/OR in patients with different cancer types treated with durvalumab. LM, NLR,TBSL and cancer types were found to be important factors for tumor kinetics. In addition to tumor kinetic parameters, HGBBL, ALB, and NLR were found to be important predictors of OS, and TC and ALB were found to be important predictors of OR. These findings could provide a guidance on patient selection in future clinical trials.

Second-Order Kinetic Model for the Sorption of Cu(II) Ions in Aqueous Solutions of Zeolite NaA

2012 ◽  
Vol 560-561 ◽  
pp. 1174-1177 ◽  
Author(s):  
Dimitar Petrov Georgiev ◽  
Bogdan Iliev Bogdanov ◽  
Yancho Hristov ◽  
Irena Markovska
Keyword(s):  
Kinetic Model ◽  
Aqueous Solutions ◽  
Kinetic Parameters ◽  
Linear Equations ◽  
Linear Method ◽  
Second Order ◽  
Order Kinetic ◽  
Zeolite Naa ◽  
Order Kinetic Model ◽  
Pseudo Second Order

In this study, the sorption of Cu(II) ions in aqueous solutions of Zeolite NaA by performing batch kinetic sorption experiments. The equilibrium kinetic data were analyzed using the pseudo-second-order kinetic model. A comparison was made of the linear least-squares method and nonlinear method of the widely used pseudo-second-order kinetic model for the sorption of Cu(II) ions of Zeolite . Four pseudo-second-order kinetic linear equations are discussed. Kinetic parameters obtained from the four kinetic linear equations using the linear method differed but they were the same when using the non-linear method. Kinetic parameters obtained from four kinetic linear equations using the linear method differed. Equation type 1 pseudo-second-order kinetic model very well represented the kinetic of the adsorption Cu(II) ions by Zeolite NaA. Equation type 4 exhibited the worst fit. Present investigation showed that the non-linear method may be a better way to determine the kinetic parameters.

scholarly journals Rapid multistep kinetic model generation from transient flow data

2017 ◽  
Vol 2 (2) ◽  
pp. 103-108 ◽  
Author(s):  
Christopher A. Hone ◽  
Nicholas Holmes ◽  
Geoffrey R. Akien ◽  
Richard A. Bourne ◽  
Frans L. Muller
Keyword(s):  
Kinetic Model ◽  
Kinetic Parameters ◽  
Transient Flow ◽  
Accurate Estimation ◽  
Model Generation ◽  
Flow Data

SNAr reaction profiles were generated using an automated reactor, collected in less than 3 hours, and allowed accurate estimation of kinetic parameters.

scholarly journals Kinetic study of propane aromatization over Zn/HZSM-5 zeolite under conditions of catalyst deactivation using genetic algorithm

2018 ◽  
Vol 83 (4) ◽  
pp. 473-488 ◽  
Author(s):  
Abbas Roshanaei ◽  
Mehdi Alavi
Keyword(s):  
Genetic Algorithm ◽  
Kinetic Model ◽  
Kinetic Parameters ◽  
Catalyst Deactivation ◽  
Flow Reactor ◽  
Plug Flow ◽  
Kinetic Studies ◽  
Space Velocity ◽  
Propane Aromatization ◽  
Aromatization Reaction

The kinetic studies of propane aromatization reaction over Zn/ /HZSM-5 catalyst at temperature of 500?560?C and space velocity of 500?2500 cm3 gcat -1 h-1, in a plug flow reactor, under catalyst deactivating conditions were performed. A lumped kinetic model consisting of six lumped components and six reaction steps was proposed to describe the aromatization of propane. The kinetic model involves 18 kinetic parameters and one catalyst deactivation constant. The reaction steps orders were obtained by the power law model. Frequency factors and the apparent activation energies of the reaction steps were calculated based on the Arrhenius equation. An exponential function depending on the time-on-stream was applied for the catalyst deactivation model and the kinetic parameters were calculated via a genetic algorithm. The kinetic results indicated that the lumped kinetic model can well estimate the product yields of propane aromatization.

scholarly journals A Useful Excel-Based Program for Kinetic Model Discrimination

2018 ◽  
Vol 2 (4) ◽  
pp. 57 ◽  
Author(s):  
Lidia Pino ◽  
Vincenzo Recupero ◽  
Agustín Hernández
Keyword(s):  
Regression Analysis ◽  
Kinetic Model ◽  
Linear Regression ◽  
Kinetic Parameters ◽  
Kinetic Models ◽  
Linear Regression Analysis ◽  
Dry Reforming ◽  
Model Discrimination ◽  
Enzyme Kinetic ◽  
User Friendly

In the present study, the ANEMONA.XLT tool, an Excel template that was designed for calculation of enzyme kinetic parameters, has been successful adapted to some proposed models for dry reforming reaction, such as Eley-Rideal or Langmuir-Hinshelwood kinetic models. Model discrimination by non-linear regression analysis has been applied to data from the literature; the predicted kinetic parameters that were obtained using ANEMONA.XLT were fully comparable with those already published. Thus, the template can be a helpful and user-friendly alternative tool for researchers who do not have advanced skills in computer programming.

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