A new method to calculate kinetic parameters independent of the kinetic model: Insights on CO 2 and steam gasification

2015 ◽  
Vol 95 ◽  
pp. 346-357 ◽  
Author(s):  
Arturo Gomez ◽  
Nader Mahinpey
Keyword(s):  
Kinetic Model ◽  
Kinetic Parameters ◽  
Steam Gasification ◽  
New Method

New method of evaluation of the kinetic parameters of bi-exponential enzyme-catalyzed reactions

1998 ◽  
Vol 30 (6) ◽  
pp. 735-743 ◽  
Author(s):  
Carmelo Garrido-del Solo ◽  
Francisco Garcı́a-Cánovas ◽  
José Tudela ◽  
Bent H. Havsteen ◽  
Ramón Varón-Castellanos
Keyword(s):  
Kinetic Parameters ◽  
New Method ◽  
Catalyzed Reactions ◽  
Enzyme Catalyzed Reactions ◽  
Method Of Evaluation

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.

A new method to determine the microbial kinetic parameters in biological air filters

2008 ◽  
Vol 63 (16) ◽  
pp. 4126-4134 ◽  
Author(s):  
Marie-Caroline Delhoménie ◽  
Josiane Nikiema ◽  
Louise Bibeau ◽  
Michèle Heitz
Keyword(s):  
Kinetic Parameters ◽  
New Method ◽  
Air Filters

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.

The Catalytic Mechanism of Tyrosine Phenol-Lyase from Erwinia herbicola: The Effect of Substrate Structure on pH-Dependence of Kinetic Parameters in the Reactions with Ring-Substituted Tyrosines

1996 ◽  
Vol 51 (5-6) ◽  
pp. 363-370 ◽  
Author(s):  
N. G. Faleev ◽  
S.N. Spirina ◽  
V. S. Ivoilov ◽  
T. V. Demidkina ◽  
R. S. Phillips
Keyword(s):  
Kinetic Parameters ◽  
Aromatic Ring ◽  
Catalytic Mechanism ◽  
Ph Dependence ◽  
Phenolic Hydroxyl ◽  
New Method ◽  
Erwinia Herbicola ◽  
Substrate Structure ◽  
Tyrosine Phenol Lyase ◽  
Additional Base

Abstract Apparently homogeneous tyrosine phenol-lyase (TPL) from Erwinia herbicola has been prepared by a new method. The pH-dependencies of the main kinetic parameters for the reactions of Erwinia TPL with tyrosine, 2-fluorotyrosine, 3-fluorotyrosine, 2-chlorotyrosine, and 3.4-dihydroxyphenylalanine (DOPA ) have been studied. The pattern of pH-dependence of Vmax depends on the nature of the substituent in the aromatic ring. For the substrates bearing small substituents (H, 2-F, 3-F) Kmax values were found to be pH-independent. For 2-chlorotyrosine and DOPA Vmax decreased at lower pH, the effect being described by equation with one pKa. Generally two bases are reflected in the pH dependence of Vmax/Km. The first base, probably is responsible for the abstraction of a-proton, while the second one, interacts with the phenolic hydroxyl at the stage of binding. The reaction of TPL with DOPA differs from the reactions with other tyrosines by the requirement of an additional base which is reflected in the pH-profiles of both and Vmax/Km. For the reaction of TPL from Citrobacter intermedins with DOPA only Vmax/Km values could be determined. The activity of Citrobacter enzyme towards DOPA is considerably less than that of E. herbicola enzyme, and its maximal value is attained at higher pH.

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.

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