Global Kinetic Parameters Research Articles

Application of singular value decomposition analysis: Insights into the complex mechanisms of amyloidogenesis

Amyloidogenesis, with its multifaceted nature spanning from peptide self-assembly to membrane-mediated structural transitions, presents a significant challenge for the interdisciplinary scientific community. Here, we emphasize on how Singular Value Decomposition (SVD) can be employed to reveal hidden patterns and dominant modes of interaction that govern the complex process of amyloidogenesis. We first utilize SVD analysis on Circular Dichroism (CD) spectral datasets to identify the intermediate structural species emerging during peptide-membrane interactions and to determine binding constants more precisely than conventional methods. We investigate the monomer loss kinetics associated with peptide self-assembly using Nuclear Magnetic Resonance (NMR) dataset and determine the global kinetic parameters through SVD. Furthermore, we explore the seeded growth of amyloid fibrils by analyzing a time-dependent NMR dataset, shedding light on the kinetic intricacies of this process. Our analysis uncovers two distinct states in the aggregation of Aβ40 and pinpoints key residues responsible for this seeded growth. To strengthen our findings and enhance their robustness, we validate those using simulated data, thereby highlighting the physical interpretations derived from SVD. Overall, SVD analysis offers a model-free, global kinetic perspective, enabling the selection of optimal kinetic models. This study not only contributes valuable insights into the dynamics but also highlights the versatility of SVD in unravelling complex processes of amyloidogenesis.

Development of a novel subgrid combustion model for buoyant turbulent diffusion flames

A novel approach is presented to incorporate finite rate reactions in modeling of turbulent diffusion flame, with the existence of unresolved flamelets inside the CFD grid cells taken into account. This approach, called SCM (subgrid combustion model), is applied in large eddy simulations of the UMD line burner flames. With the global kinetic parameters fitted for the measurement data and detailed simulations of autoignition in stoichiometric methane-air mixture, as well as for the extinction strain rate in the opposed non-premixed jets, the SCM model is shown to replicate the mean temperature profiles in unsuppressed flame with mean total heat release of 50 kW. For flame suppression via dilution of the oxidizer flow by nitrogen, the lift-off and extinction of non-anchored flame are predicted in agreement with the experimental data. The SCM is designed as a tool to allow for the finite rate kinetics effects in large eddy simulations of buoyant turbulent diffusion flames, with the focus on weakly turbulent regions, in which applicability of conventional combustion models is limited.

Compartment model-based nonlinear unmixing for kinetic analysis of dynamic PET images.

When no arterial input function is available, quantification of dynamic PET images requires a previous step devoted to the extraction of a reference time-activity curve (TAC). Factor analysis is often applied for this purpose. This paper introduces a novel approach that conducts a new kind of nonlinear factor analysis relying on a compartment model, and computes the kinetic parameters of specific binding tissues jointly. To this end, it capitalizes on data-driven parametric imaging methods to provide a physical description of the underlying PET data, directly relating the specific binding with the kinetics of the non-specific binding in the corresponding tissues. This characterization is introduced into the factor analysis formulation to yield a novel nonlinear unmixing model designed for PET image analysis. This model also explicitly introduces global kinetic parameters that allow for a direct estimation of a binding potential that represents the ratio at equilibrium of specifically bound radioligand to the concentration of nondisplaceable radioligand in each non-specific binding tissue. The performance of the method is evaluated on synthetic and real data to demonstrate its potential interest.

Assessing the thermal and fungal behavior of eco-friendly epoxy thermosets derived from vegetable oils for wood protective coatings

The paper deals with the study of the obtaining, characterization and thermal and fungal behavior of a green thermoset based on epoxidized soybean oil (ESO), castor oil maleic anhydride adduct (COMA) and methyl nadic anhydride (MNA). By varying the MNA/COMA crosslinking agent ratio, resins with different degree of stiffness can be obtained suitable for green thermosets coatings. Differential scanning calorimetry (DSC) and a simultaneous TG/FT-IR/MS coupling were used to establish the crosslinking behavior, evolved gases analysis and thermal decomposition mechanisms associated with their corresponding kinetic parameters. The non–isothermal global kinetic parameters values (activation energy and pre–exponential factor) were calculated with the aid of the Friedman and Flynn–Wall–Ozawa isoconversional methods. The curves shape of the variation of activation energy versus conversion degree and first derivative (DTG) curves shapes suggest that the thermal degradation processes occurred in multi-step kinetics. Using a multivariate linear regression method the most probable thermal decomposition and crosslinking kinetic models were established. A good concordance between experimental and simulated data was obtained, confirming the correct description of the thermal mechanisms. The main identified gaseous fragments were water, carbon dioxide, saturated and unsaturated hydrocarbons and carboxylic derivatives. The decay resistance against two wood decaying strains, P. chrysogenum and A. brasiliensis was also evaluated.

Theoretical and Mechanistic Validation of Global Kinetic Parameters of the Inactivation of GABA Aminotransferase by OV329 and CPP-115

((S)-3-Amino-(difluoromethylenyl)cyclopent-1-ene-1-carboxylic acid (OV329) is a recently discovered inactivator of γ-aminobutyric acid aminotransferase (GABA-AT), which has 10 times better inactivation efficiency than its predecessor, CPP-115, despite the only structural difference being an endocyclic double bond in OV329. Both compounds are mechanism-based enzyme inactivators (MBEIs), which inactivate GABA-AT by a similar mechanism. Here, a combination of a variety of computational chemistry tools and experimental methods, including quantum mechanical (QM) calculations, molecular dynamic simulations, progress curve analysis, and deuterium kinetic isotope effect (KIE) experiments, are utilized to comprehensively study the mechanism of inactivation of GABA-AT by CPP-115 and OV329 and account for their experimentally obtained global kinetic parameters kinact and KI. Our first key finding is that the rate-limiting step of the inactivation mechanism is the deprotonation step, and according to QM calculations and the KIE experiments, kinact accurately represents the enhancement of the rate-limiting step for the given mechanism. Second, the present study shows that the widely used simple QM models do not accurately represent the geometric criteria that are present in the enzyme for the deprotonation step. In contrast, QM cluster models successfully represent both the ground state destabilization and the transition state stabilization, as revealed by natural bond orbital analysis. Furthermore, the globally derived KI values for both of the inactivators represent the inhibitor constants for the initial binding complexes (Kd) and indicate the inactivator competition with the substrate according to progress curve analysis and the observed binding isotope effect. The configurational entropy loss accounts for the difference in KI values between the inactivators. The approach we describe in this work can be employed to determine the validity of globally derived parameters in the process of MBEI optimization for given inactivation mechanisms.

Thermal and electrical behavior of hybrid thermosets based on epoxy and maleimide resins cured with p‐aminobenzoic acid

AbstractTwo thermoset systems based on maleimides and diglycidyl ether of bisphenol A (DGEBA) cured with p‐aminobenzoic acid were characterized in terms of thermal and electrical behavior. Thermal characterization has been undertaken by means of thermogravimetric analysis in nitrogen atmosphere up to 600°C using simultaneous thermogravimetric/Fourier transform infrared/mass spectrometry (TG/FT‐IR/MS) analysis. In the first stage of thermal degradation, the global kinetic parameters [activation energy (Ea) and preexponential factor (log A1 (s−1))] were calculated using the isoconversional method of Friedman. The energies variation as well as the shape of the differential thermal analysis curves suggests that the thermal decomposition process occurred in multiple stages. The evolved gases analysis was conducted by simultaneous TG/FT‐IR/MS coupled techniques. Dielectric relaxation spectroscopy characterization was also made.

Predicting the biomass conversion performance in a fluidized bed reactor using isoconversional model‐free method

The first objective of this study to analyze the detailed pyrolysis kinetics of four Canadian feedstocks through two techniques: thermogravimetric analysis (TGA) using the isoconversional model‐free method; and fast pyrolysis in a fluidized bed reactor using the simple Arrhenius model. The four biomass feedstocks were pyrolyzed in a fluidized bed reactor at 400–520 °C. The experiments were conducted for three size fractions. The thermogravimetric analysis was performed at four heating rates (2, 5, 10, and 15 °C/min) in an inert atmosphere. TGA experiments showed that the decomposition rate of agricultural residues was significantly lower than woody biomass due to high volatiles and low ash content in the latter. The range of average activation energy from fluidized bed experiments was 150–168 kJ/mol and 160–180 kJ/mol from TGA experiments. The difference is attributed to different methodology in the experiments and the determination of kinetic parameters. The second objective was to apply the global kinetic parameters from the TGA to predict the decomposition of biomass to biochar and to compare it with the experimental biochar left in the fluidized bed reactor at different temperatures. This study also confirmed that at high temperatures for all the feedstocks, average kinetics parameters obtained from the TGA could produce fluidized bed biomass conversion results with an average variation of 4 %.

Rare-event sampling of epigenetic landscapes and phenotype transitions.

Stochastic simulation has been a powerful tool for studying the dynamics of gene regulatory networks, particularly in terms of understanding how cell-phenotype stability and fate-transitions are impacted by noisy gene expression. However, gene networks often have dynamics characterized by multiple attractors. Stochastic simulation is often inefficient for such systems, because most of the simulation time is spent waiting for rare, barrier-crossing events to occur. We present a rare-event simulation-based method for computing epigenetic landscapes and phenotype-transitions in metastable gene networks. Our computational pipeline was inspired by studies of metastability and barrier-crossing in protein folding, and provides an automated means of computing and visualizing essential stationary and dynamic information that is generally inaccessible to conventional simulation. Applied to a network model of pluripotency in Embryonic Stem Cells, our simulations revealed rare phenotypes and approximately Markovian transitions among phenotype-states, occurring with a broad range of timescales. The relative probabilities of phenotypes and the transition paths linking pluripotency and differentiation are sensitive to global kinetic parameters governing transcription factor-DNA binding kinetics. Our approach significantly expands the capability of stochastic simulation to investigate gene regulatory network dynamics, which may help guide rational cell reprogramming strategies. Our approach is also generalizable to other types of molecular networks and stochastic dynamics frameworks.

Operando Spectroscopy of Alkyl Carbonate-Based Electrolyte Decomposition in LiCoO2 Batteries

Electrolytes composed of alkyl carbonate solvents with lithium hexafluorophosphate (LiPF6) salt have enjoyed near universal adoption in lithium ion batteries. Despite the wide adoption of these electrolytes, significant safety issues can occur under mechanical, electrochemical, or thermal abuse. Safety concerns will only increase with an expanded number of battery applications (including emerging markets for used batteries), higher energy density, and a need for extreme fast charging in electric vehicle applications. The stability of ethylene carbonate (EC) against oxidation at the cathode while forming a stable solid electrolyte interface (SEI) upon reduction at the anode has made this solvent a key ingredient in almost all lithium ion batteries. Linear carbonates (e.g. diethyl carbonate (DEC) or dimethyl carbonate (DMC)) are mixed with EC to reduce viscosity and increase ion mobility, while maintaining a wide electrochemical stability window. While stable against reduction at the anode, the higher volatility and lower boiling points of linear alkyl carbonates increase risk of vapor buildup within the battery. At elevated temperature, these carbonate-based electrolytes become unstable as SEI decomposition, solvent-salt reactions, anode reduction, cathode oxidation, and thermal decomposition lead to thermal runaway, battery venting, fire, or explosion. In an effort to improve safety and explore alternative electrolytes, numerous studies have sought to identify the underlying mechanisms of electrolyte decomposition. Differential scanning calorimetry and accelerated rate calorimetry experiments are commonly used to identify onset temperatures of key reactions, global kinetic parameters, and heat release rates. Ex-situ electrolyte and gas analyses are also used to identify decomposition mechanisms and reaction products. However, much remains unknown about the detailed decomposition chemistry in lithium ion batteries. Furthermore, decomposition chemistry is highly dependent on the composition of the electrolyte and electrode, making it difficult to predict thermal stability in new or modified battery chemistries. Here we present operando Fourier transform infrared (FTIR) spectroscopy measurements of electrolyte decomposition in lithium ion batteries. Using attenuated total reflection (ATR) spectroscopy, we simultaneously monitored electrolyte composition and electrochemical performance of heated LiCoO2 coin cells with EC/DEC/LiPF6 electrolyte and Celgard separators. Using the ATR method, an infrared evanescent wave propagates several microns into the electrolyte-saturated pores of the anode and cathode layers, respectively. The resulting absorption spectra are analyzed to identify electrolyte species and their molecular bonds. The coin cell geometry allows for careful control and monitoring of electrolyte temperature and composition at charge/discharge rates > 1C. Electrolyte decomposition was monitored during battery cycling as a function of electrolyte composition, battery temperature, C-rate, and state of charge. The role of LiPF6 in solvent decomposition reactions was also explored. These measurements captured the dynamics of SEI formation on the graphite anode, including identification of key molecular bonds involved in EC decomposition during formative cycles from density functional theory modeling. At temperatures above 70°C, SEI decomposition was observed, followed by an increase in EC decomposition. Overcharging resulted in irreversible damage of the LiCoO2 cathode without any observable change in electrolyte composition. Spectral analysis further revealed distinct reaction mechanisms for temperature-induced EC decomposition and EC decomposition associated with SEI formation.

Influence of different tanning agents on bovine leather thermal degradation

The objective of the paper consists in studying the thermal behavior of chrome-free tanned bovine leather (wet-white), using a new product based on titanium and aluminum salts, compared with the same leather tanned by chromium salts (wet-blue). The aim is to find a possibility for replacing the wet-blue leather, containing Cr (III) salts, with the environmentally friendly wet-white leather. The thermal behavior was studied by dynamic thermogravimetry in nitrogen atmosphere, up to 700 °C. Global kinetic thermal decomposition parameters values were obtained with the isoconversional integral method of Flynn–Wall–Ozawa. The kinetic model best describing the thermal degradation process and the kinetic parameters for each individual stage were determined from non-isothermal data by means of a multivariate nonlinear regression method. The evolved gases analysis was conducted on a coupling to a quadrupole mass spectrometer and a Fourier transform infrared spectrophotometer equipped with external modulus for gas analysis. FTIR, microscopic, and elementary composition studies of residues were conducted. There was found that the differences in non-isothermal decomposition kinetics, evolved gases, and residue analyses were dependent on the nature of the two used tanning agents. It was observed that the wet-white leather exhibited lower thermal stability and temperatures of evolved gases. The metal concentrations in the residues and their porous and fibrillar morphologies recommend them as possible candidates for obtaining cost-friendly adsorbents.

Determination of global kinetic parameters by optimization procedure using burning velocity measurements

The optimization procedure was developed to derive the global kinetic parameters using experimental dependence of burning velocity on the equivalence ratio. The simple model of laminar premixed flame propagation with assumed constant parameters was used to demonstrate the features of the suggested procedure. The suggested method allows finding optimal parameters for the defined functional dependence of the reaction rate on the temperature and reactant concentrations. The dependence of combustion adiabatic temperature on equivalence ratio is assumed to be known from the flame equilibrium calculations. The global kinetic parameters of combustion reaction were determined for methane, ethylene and propane mixtures with air on the basis of experimental data on burning velocity as function of the equivalence ratio. The calculated overall kinetic parameters are compared with parameters obtained by other methods within similar global model.

Methane thermal decomposition in regenerative heat exchanger reactor: Experimental and modeling study

In this work, thermal decomposition of methane (TDM) was experimentally studied at nominal gas temperatures of 1070 K–1450 K in a non-catalytic laboratory test reactor. The purpose was to use a simple kinetic mechanism to describe the TDM reaction, which could be applied in industrial reactor design. The experimental data was utilized to optimize global kinetic parameters describing the TDM reaction in the test reactor. For comparison, a 37-step reaction mechanism for TDM was adopted from the literature. When analyzing experimental datasets from the literature, the optimized global kinetics provided better agreement with the experimental data than the 37-step mechanism when the reactor temperature profiles were defined in detail. Since the 37-step mechanism was not able to predict the solid carbon formation well enough, the mechanism was slightly adjusted according to a reaction flow and sensitivity analysis. Additionally, it was suggested that the 37-step mechanism can be improved by optimizing the reaction mechanism by using a detailed experimental data of hydrocarbon formation in TDM achieved in an environment where the temperature profiles are fully defined.

Rational Optimization of Mechanism-Based Inhibitors through Determination of the Microscopic Rate Constants of Inactivation.

Mechanism-based inhibitors (MBIs) are widely employed in chemistry, biology, and medicine because of their exquisite specificity and sustained duration of inhibition. Optimization of MBIs is complicated because of time-dependent inhibition resulting from multistep inactivation mechanisms. The global kinetic parameters kinact and KI have been used to characterize MBIs, but they provide far less information than is commonly assumed, as shown by derivation and simulation of these parameters. We illustrate an alternative and more rigorous approach for MBI characterization through determination of the individual microscopic rate constants. Kinetic analysis revealed the rate-limiting step of inactivation of the PLP-dependent enzyme BioA by dihydro-(1,4)-pyridone 1. This knowledge was subsequently applied to rationally design a second-generation inhibitor scaffold with a nearly optimal maximum inactivation rate (0.48 min-1).

Estimating the Pyrolysis Kinetic Parameters of Coal, Biomass, and Their Blends: A Comparative Study

The pyrolysis kinetic parameters of two coal ranks (DECS-25 lignite and DECS-38 sub-bituminous), two biomass materials (corn stover and switchgrass), and their respective blends were investigated at various heating rates ranging between 5 and 40 °C/min using thermogravimetric analysis. Complex models for devolatilization of the feedstocks were solved for obtaining and predicting the global kinetic parameters. Distributed activation energy model (method 1) and matrix inversion algorithm (method 2) were utilized and compared for this purpose. The results indicate that the matrix inversion algorithm predicts the kinetic parameters such that the weight loss characteristics can be best represented for both single fuels as well as that of blended materials. The algorithm can also be used for determining the number of reactions occurring in the devolatilization temperature interval. The number of reactions occurring during the devolatilization of blended materials falls between those that occur during the devola...

Curing kinetics, thermal and morphological characterization of the biobased thermosets from epoxy resin/epoxidized hemp oil

The paper presents the synthesis and thermal behavior of an epoxy matrix from diglycidyl ether of bisphenol A (DGEBA) and epoxidized hemp oil crosslinked with two hydroxy carboxylic acids (HAc). Epoxidized hemp oil (EHO) was obtained via epoxidation in situ with peroxyacetic acid. The chemical structures of hemp oil (HO), EHO and epoxy matrix were confirmed using FT-IR and 1H NMR spectroscopy. The kinetics of the curing reactions were studied by differential scanning calorimetry (DSC) using multivariate non-linear regression method from the “Thermokinetics-3” software (Netzsch). Also, the thermal decomposition behavior of network has been studied in nitrogen atmosphere up to 600°C using simultaneous TG/FT-IR/MS technique. Using the above software, the global kinetic parameters of thermal decomposition were determined and was found that the thermal decomposition process occurs in three steps. A good correlation was observed between experimental and simulated data. The chemical composition of gases that arise in the process of thermal decomposition was assessed using FT-IR and MS techniques.

A study on coating properties of an epoxy system hardened with maleinized castor oil

The paper describes coating properties (pencil hardness, adhesion, flexibility, solvent resistance) of a flexible biobased polyepoxide network from diglycidyl ether of bisphenol A crosslinked with castor oil maleate. Curing kinetics, electrical and photochemical behaviour were described. The structure was confirmed by Fourier transform infrared spectroscopy (FTIR). Global kinetic curing parameters values were determined via differential scanning calorimetry (DSC), by applying the Ozawa, Kissinger and non-linear regression methods. Kinetic parameters of each individual stage, obtained through multivariate non–linear regression method, indicated a three stage curing mechanism. A good correlation was found between experimental data and that simulated by the applied software. The material was further characterized by DSC and dielectric measurements. Crosslinking density and Shore hardness were determined from swelling and mechanical tests. 2-(4,6-diphenyl-1,3,5-triazin-2-yl)-5-[(hexyl)oxy]-phenol photostabilizer was added and photochemical behaviour was assessed at two different wavelengths.

A combined genetic algorithm and least squares fitting procedure for the estimation of the kinetic parameters of the pyrolysis of agricultural residues

The main objective of this study is to implement a two-step fitting procedure to estimate the kinetic parameters of two distinct pyrolysis models to study the pyrolysis of pine bark, wheat straw and rice husk. Thermogravimetric curves were obtained for the three biomass fuels for heating rates of 5, 10 and 15K/min in an inert atmosphere of Argon to investigate the impact of the type of biomass in the pyrolysis behavior under different heating conditions. Distinctive thermogravimetric and differential thermogravimetric curves were obtained owing to the different composition of the biomass fuels. For the conditions examined, the impact of the heating rate on the profile curves was marginal. In order to better understand the impact of the biomass composition in the pyrolysis, their main components were estimated. Additionally, a two-step algorithm was used to calibrate the global kinetic parameters of a single reaction model and of a three parallel reaction model, based on the fitting of predicted curves to the experimental ones. The first step was a genetic algorithm procedure. An evaluation function that minimizes the deviation between the experimental and predicted pyrolysis yields, while preserving the characteristics of the mass decomposition during pyrolysis, is presented in this work. The second step was a least squares minimization that was used for further refining the solution obtained in the first step. The method showed excellent repeatability. For each biomass fuel, all heating rates were globally fitted, with errors of the order of ∼5% for the single reaction model and of less than 1.6% for the three parallel reaction model. The activation energies obtained by fitting each model to the experimental data are generally within the values reported in the literature. Finally, a sensitivity analysis showed that the variation of the composition of each biomass used in this study does not affect significantly the predictions of the three parallel model.

TGA/DTA–FTIR–MS coupling as analytical tool for confirming inclusion complexes occurrence in supramolecular host–guest architectures

The paper deals with the insights on the thermal decomposition of a viologen included in a [2]rotaxane structure alongside β-cyclodextrin. Thermal stability studies were conducted by dynamic thermogravimetry in inert atmosphere. Complexation phenomena occurence led to an increase in inclusion complex thermal stability. Simultaneous TGA–DTA analysis indicated lower intensity of the complexed guest molecule melting profile. Kinetics of the thermal decomposition process was conducted by applying the isoconversional methods of Friedman and Flynn–Wall–Ozawa. Global kinetic parameters values exhibited an increase with the conversion degree, indicating a complex thermal degradation process. The form of the kinetic model which best described the thermal decomposition process and the kinetic parameters values corresponding to each degradation stage were determined with a multivariate non-linear regression method. A two dimensional diffusion (D2) kinetic model best fitted the thermogravimetric data. A correlation between kinetic data and structural changes during thermal decomposition was established. The evolved gas analysis was conducted on a coupling of simultaneous thermal analysis device to a quadrupole mass spectrometer and a Fourier transform infrared spectrophotometer. The complex gaseous mixture evolved during thermal decomposition of the structure was comprised of: water, carbon monoxide, carbon dioxide, hydrogen cyanide, methanol and ethanol, acetic acid, hydrogen bromide and amine and furan derivatives.

ChemInform Abstract: Critical Review of the Global Chemical Kinetics of Cellulose Thermal Decomposition

AbstractReview: 86 refs.

New energy value chain through pyrolysis of hospital plastic waste

In this paper, the evolution in thermochemical behaviours of hospital plastic wastes and changes in chemical composition and characteristics of pyrolysis liquid products have been investigated by using different fixed bed reactor scales. The main objective is to identify the critical technical parameters enabling thermochemical process adaptation in function of raw materials chemical structure, with the aim of maximising the yield of condensable fraction and optimising its energetic properties related to internal combustion engines.It is a step-by-step procedure using three reactor capacity levels, which allows various aspects approach of thermochemical process development from the evaluation of global reaction kinetic parameters to the measurement of physicochemical properties of the final pyrolysis products. In order to reduce the gas and solid fractions with corresponding increasing of condensable products, the transposition of thermal and kinetic information provided by thermogravimetric analysis (TGA) to larger reactors is used to control of process parameters. In this experimental work the mass of samples increases from 0.05 g in the thermogravimetric analyser to 600 g in the bench scale reactor.Gas-chromatography techniques have been used to identify the chemical composition of gases (GC/TCD) and liquids (GC/FID-MS).It was established that changing the reactor scale does not result in significant differences in pyrolysis product distribution, neither in gas composition. On the other hand, the aspect and the quality of condensable fraction display a high variability. Also, the energy contained in the final valuable pyrolysis product was compared with the energy demand during the thermochemical transformation in order to evaluate the energy efficiency of the process.