Kinetic Modeling Approach Research Articles

Kinetic modeling of Maillard and caramelization reactions in sucrose-rich and low moisture foods applied for roasted nuts and seeds

A kinetic model was proposed by using a multiresponse kinetic modeling approach for Maillard and caramelization reactions in low moisture foods at neutral pH containing a moderate amount of amino acid and sucrose but a restricted amount reducing sugar. The change in the amount of sucrose, protein-bound lysine, free amino acids, and certain products of Maillard reaction was monitored during roasting of sunflower seed, pumpkin seed, flaxseed, peanut, and almond at 160 and 180 °C. A slightly different model was proposed for pumpkin seed due to its difference in compositional and physicochemical characteristics as expressed by principal component analysis. Accordingly, 3-deoxyglucosone formation via sugar degradation; 5-hydroxymethylfurfural formation from 3-deoxyglucosone and only in pumpkin seeds the conversion of N-ε-fructoselysine to glyoxal and Heyns product to 1-deoxyglucosone were found to be quantitatively important. N-ε-carboxymethyllysine and N-ε-carboxyethyllysine mainly originated through oxidation of N-ε-fructoselysine and the reaction of methylglyoxal with lysine residue, respectively.

Exploring Acrylamide and 5-Hydroxymethylfurfural Formation in Glucose-Asparagine-Linoleic Acid System With a Kinetic Model Approach.

In the “glucose-asparagine-linoleic acid” ternary system, a kinetic model approach was used to explore formation and elimination law of target hazards, including acrylamide (AA) and 5-hydroxymethylfurfural (5-HMF), and their related precursors and intermediate products. The results showed that the elimination of glucose and asparagine and the formation of fructose (generated from glucose isomerization), 3-deoxyglucosone (3-DG), methylglyoxal (MGO), and glyoxal (GO), AA and 5-HMF followed first-order reaction kinetics with high fit coefficients (R2 > 0.9). In addition, the kinetic reaction rate constants increased as the increasing temperature, and all models followed the Arrhenius law. Results of statistical correlations analysis suggested that at lower temperature, the generic amino acid route and the specific amino acid route may paly crucial roles for the formation of AA and 5-HMF, while at high temperature a linoleic acid pathway may be predominantly involved.

Biogas production from residual marine macroalgae biomass: Kinetic modelling approach

Modelling the conversion of residual biomass to renewable fuels is of high relevance to promote the development of effective technological solutions. The present study compares the performance of five different kinetic models (pseudo-first-order kinetics, logistics, modified Gompertz, double-Gompertz, and multi-Gompertz) to describe the cumulative methane production during a low-solids anaerobic digestion of marine macroalgae waste. Different substrate concentrations were evaluated (0.9, 1.7 and 2.5% TS) with the best methane yield (105.2 mL CH4.g VS−1) being obtained at the highest amount of biomass. All models fitted the experimental data with R2 > 0.988. The innovative multi-Gompertz model herein proposed led to the best performance indexes for all tested experimental conditions, allowing to predict methane yields more accurately when the digestion occurs in two or more steps, as it was the case with marine macroalgae waste.

Backslopping Time, Rinsing of the Grains During Backslopping, and Incubation Temperature Influence the Water Kefir Fermentation Process.

For eight backslopping steps, eight series of water kefir fermentation processes differing in backslopping time and rinsing of the grains during each backslopping step and eight series of fermentation processes differing in incubation temperature and backslopping time were followed. Short backslopping times resulted in high relative abundances of Liquorilactobacillus nagelii and Saccharomyces cerevisiae, intermediate backslopping times in high relative abundances of Leuconostoc pseudomesenteroides, and long backslopping times in high relative abundances of Oenococcus sicerae and Dekkera bruxellensis. When the grains were rinsed during each backslopping step, the relative abundances of Lentilactobacillus hilgardii and Leuc. pseudomesenteroides increased and those of D. bruxellensis and Liql. nagelii decreased. Furthermore, rinsing of the grains during each backslopping step resulted in a slightly higher water kefir grain growth and lower metabolite concentrations. The relative abundances of Liquorilactobacillus mali were highest at 17°C, those of Leuc. pseudomesenteroides at 21 and 25°C, and those of Liql. nagelii at 29°C. With a kinetic modeling approach, the impact of the temperature and rinsing of the grains during the backslopping step on the volumetric production rates of the metabolites was determined.

A new approach of kinetic modeling: Kinetically consistent energy profile and rate expression analysis

We report a scaling relation-based L-H kinetic model to assess reaction rate, where general principles for making a kinetically consistent free energy profile are suggested. Water-gas shift, Fischer-Tropsch synthesis, and steam methane reforming are employed as three model reactions to illustrate this approach. Herein, potential energies and free energies are calculated by improved scaling relations. The different methods to construct energy profiles are compared, and free energy diagrams rather than potential energy diagrams are more favorable to be employed in the field of reaction mechanism discriminations and kinetics investigations due to consisting of thermodynamic information. The sequence of various elementary steps is important to generate appropriate rate-determining step and rate expressions. It is suggested that the sequence of the elementary step follows a principle that the reaction step is set just before it is required, and desorption occurs just after the formation of the intermediates. Based on the procedure elucidated here, it is easy to get turnover frequency straightforwardly from the free energy diagram of reaction and the surface site coverages from the free energy diagram of intermediates. The scaling relation-based L-H kinetic model exhibits a similar accuracy for predicting the surface coverages and reaction rates with full microkinetic modeling toward all the three model reactions. It demonstrates that the approach proposed herein greatly simplifies the calculation but maintains high accuracy as compared to full microkinetic modeling. This approach can be widely applied for kinetic modeling to elucidate the reaction mechanism and kinetics for chemical processes of interest.

A New Kinetic Modeling Approach for Predicting the Lifetime of ATH-Filled Silane Cross-Linked Polyethylene in a Nuclear Environment.

This study focuses on the degradation of a silane cross-linked polyethylene (Si-XLPE) matrix filled with three different contents of aluminum tri-hydrate (ATH): 0, 25, and 50 phr. These three materials were subjected to radiochemical ageing at three different dose rates (8.5, 77.8, and 400 Gy·h−1) in air at low temperatures close to ambient (47, 47, and 21 °C, respectively). Changes due to radio-thermal ageing were investigated according to both a multi-scale and a multi-technique approach. In particular, the changes in the chemical composition, the macromolecular network structure, and the crystallinity of the Si-XLPE matrix were monitored by FTIR spectroscopy, swelling measurements in xylene, differential scanning calorimetry, and density measurements. A more pronounced degradation of the Si-XLPE matrix located in the immediate vicinity of the ATH fillers was clearly highlighted by the swelling measurements. A very fast radiolytic decomposition of the covalent bonds initially formed at the ATH/Si-XLPE interface was proposed to explain the higher concentration of chain scissions. If, as expected, the changes in the elastic properties of the three materials under study are mainly driven by the crystallinity of the Si-XLPE matrix, in contrast, the changes in their fracture properties are also significantly impacted by the degradation of the interfacial region. As an example, the lifetime was found to be approximately halved for the two composite materials compared to the unfilled Si-XLPE matrix under the harshest ageing conditions (i.e., under 400 Gy·h−1 at 21 °C). The radio-thermal oxidation kinetic model previously developed for the unfilled Si-XLPE matrix was extended to the two composite materials by taking into account both the diluting effect of the ATH fillers (i.e., the ATH content) and the interfacial degradation.

Removal of Lignin from Wastewater Using an Industrial Waste as Adsorbent: A Statistical and Kinetic Modeling Approach

Abstract Lignin and its derivatives are identified as the prime pollutants in the effluents of many industries such as rice mill, paper, and pulp, which subsequently create dark coloration and toxi...

A model-free sparse approximation approach to robust formal reaction kinetics

Accurate and transferable models of reaction kinetics are of key importance for chemical reactors on both laboratory and industrial scale. Usually, setting up such models requires a detailed mechanistic understanding of the reaction process and its interplay with the reactor setup. We present a data driven approach which analyzes the influence of process parameters on the reaction rate to identify locally approximated effective rate laws without prior knowledge and assumptions. The algorithm we propose determines relevant model terms from a polynomial ansatz employing well established statistical methods. For the optimization of the model parameters special emphasize is put on the robustness of the results by taking not only the quality of the fit but also the distribution of errors into account in a multi-objective optimization. We demonstrate the flexibility of this approach based on artificial kinetic data sets from microkinetic models. This way, we show that the kinetics of both the classical HBr reaction and a prototypical catalytic cycle are automatically reproduced. Further, combining our approach with experimental screening designs we illustrate how to efficiently explore kinetic regimes by using the example of the catalytic oxidation of CO. • Data driven approach for robust kinetic modeling. • Algorithm automatically determines functional form of model to avoid bias. • Effective kinetic models do not require mechanistic understanding. • Automatic discovery of kinetic regimes.

Three-stage modelling and parametric analysis of a downdraft biomass gasifier

Syngas production from biomass resources suggest considerable privileges to attain energy sustainability in future. Design and control strategies are essential to extend the technology of biomass gasifiers, which require reliable model developments. The overarching contribution of this study is to develop and evaluate a three-stage biomass gasifier model. The model consists of three successive sub-models for drying and pyrolysis, partial oxidation and char reduction reactors. The pyrolysis of raw material is simulated based on the ligno-cellulosic structure of the biomass by adopting comprehensive kinetic rate modelling approach. The partial oxidation sub-model is built by axis-symmetric 2D transport equations including detailed chemical scheme. Char reduction sub-model is extended based on axis-symmetric 2D DPM model accompanied by appropriate chemical kinetic scheme considering heterogeneous and homogeneous reactions. Accuracy of each sub-model is separately verified by comparison with available numerical and experimental data. Moreover, the correctness and predictability of the complete gasifier model is evaluated using two experimental reports. For both cases, investigations demonstrate high resolution agreement between the results of the developed model and available experimental measurements both thermally and chemically. Furthermore, a parametric analysis is conducted to investigate the gasifier performance against the variations of the main system operating parameters including the type of the feeding biomass and its moisture content, equivalence ratio and air initial temperature. Based on the results, higher volatiles mass fractions and lower char mass fraction have been produced from pyrolyzing of hardwood in comparison with beech wood. Also, Results reveal that with increase of the moisture content from 15% to 35%, syngas LHV and cold gas efficiency reduce by 1.9559 MJ . kg −1 and 25.78% respectively, while H 2 mole fraction at the gasifier outlet rises by 0.90%. On the contrary, growth of equivalence ratio from 2 to 10 leads to the drastic increase of syngas LHV by 5.6404 MJ . kg −1 , however, cold gas efficiency peaks to 82.75% at the equivalence ratio of 4. Besides, varying the inlet air temperature over a range of 500 K–1300 K causes 0.6938 MJ . kg −1 growth of syngas LHV as well as 9.43% rise of cold gas efficiency. • A conceptual three-stage model is developed to simulate the performance of a downdraft biomass gasifier. • The model includes three separate successive sub-models for pyrolysis, partial oxidation and char reduction. • Results of each sub-model and the whole three-stage model are experimentally validated. • Three-stage model is evaluated for two different lignocellulosic feedstocks. • The effects of the key operating parameters on the gasifier performance are analyzed.

Optimized Methodology for Reference Region and Image-Derived Input Function Kinetic Modeling in Preclinical PET.

PET imaging of small animals is often used for assessing biodistribution of a novel radioligand and pharmacology in small animal models of disease. PET acquisition and processing settings may affect reference region or image-derived input function (IDIF) kinetic modeling estimates. We examined four different factors in comparing quantitative results: 1) effect of reconstruction algorithm, 2) number of MAP iterations, 3) strength of the MAP prior, and 4) Attenuation and scatter. The effect of these parameters has not been explored for small-animal reference region and IDIF kinetic modeling approaches. Dynamic PET/CT scans were performed in 3 species with 3 different tracers: house sparrows with [11C]raclopride, rats with [18F]AS2471907 (11βHSD1) and mice with [11C]UCB-J (SV2A). FBP yielded lower kinetic modeling estimates compared to 3D-OSEM-MAP reconstructions, in sparrow and rat studies. Target resolutions (MAP prior strength) of 1.5 and 3.0mm demonstrated reduced VT in rats but only 3.0mm reduced BP ND in sparrows. Therefore, use of the highest target resolution (0.8mm) is warranted. We demonstrated using kinetic modeling that forgoing CT-based attenuation and scatter correction may be appropriate to improve animal throughput when using short-lived radioisotopes in sparrows and mice. This work provides recommendations and a framework for future optimization of kinetic modeling for preclinical PET methodology with novel radioligands.

Kinetic Monte Carlo simulations for heterogeneous catalysis: Fundamentals, current status, and challenges.

Kinetic Monte Carlo (KMC) simulations in combination with first-principles (1p)-based calculations are rapidly becoming the gold-standard computational framework for bridging the gap between the wide range of length scales and time scales over which heterogeneous catalysis unfolds. 1p-KMC simulations provide accurate insights into reactions over surfaces, a vital step toward the rational design of novel catalysts. In this Perspective, we briefly outline basic principles, computational challenges, successful applications, as well as future directions and opportunities of this promising and ever more popular kinetic modeling approach.

Kinetic modeling and non-invasive approach for translocator protein quantification with 11C-DPA-713

Introduction11C-DPA-713 is a positron emission tomography (PET) radiotracer developed for imaging the expression of the translocator protein (TSPO) in glial cells, which is considered to be a marker of the neuroinflammatory burden. This study investigated the pharmacokinetic profile of 11C-DPA-713 and evaluated kinetic modeling and non-invasive TSPO quantification using dynamic PET imaging data in the Alzheimer's disease (AD) and cognitive normal (CN) participants. MethodsEleven patients with AD and 6 CN participants were examined using dynamic 11C-DPA-713 PET imaging for 60 min with arterial blood sampling. Time-activity curves were calculated from the cerebellum and three composite regions of interest (ROIs), according to the anatomical definitions of Braak's stages 1 to 3, stage 4, stage 5, and stage 6 that correspond to the pathological stages of tangle deposition. The total distribution volume (VT) was evaluated using compartmental modeling and graphical analysis. Reference region–based methods were implemented using an optimal area that was assumed to be void of the radiotracer target as reference tissue. ResultsThe concentration of radioactivity in plasma demonstrated rapid clearance. 11C-DPA-713 peaked rapidly in the gray matter. Compartmental modeling resulted in a good fit, and the one-tissue model with estimated blood volume correction (1Tv) showed the best performance. The estimated VT obtained from the graphical plasma methods was highly correlated with that obtained from 1Tv. Reference region–based analysis was conducted using the Braak 6 area as the reference region, and the estimated non-displaceable binding potential was highly correlated with that obtained from 1Tv. Conclusion11C-DPA-713 possesses properties suitable for TSPO quantification with PET imaging. The Braak 6 area was shown to be a useful reference region in the patients with AD and the CN participants, and non-invasive reference tissue models using the Braak 6 area as a reference region can be employed for TSPO quantification with 11C-DPA-713-PET imaging as an alternative to the invasive compartmental model.

Simultaneous radiomethylation of [11C]harmine and [11C]DASB and kinetic modeling approach for serotonergic brain imaging in the same individual

Simultaneous characterization of pathologies by multi-tracer positron emission tomography (PET) is among the most promising applications in nuclear medicine. Aim of this work was the simultaneous production of two PET-tracers in one module and test the relevance for human application. [11C]harmine and [11C]DASB were concurrently synthesized in a ‘two-in-one-pot’ reaction in quality for application. Dual-tracer protocol was simulated using 16 single PET scans in different orders of tracer application separated by different time intervals. Volume of distribution was calculated for single- and dual-tracer measurements using Logan’s plot and arterial input function in 13 brain regions. The ‘two-in-one-pot’ reaction yielded equivalent amounts of both radiotracers with comparable molar activities. The simulations of the dual-tracer application were comparable to the single bolus injections in 13 brain regions, when [11C]harmine was applied first and [11C]DASB second, with an injection time interval of 45 min (rxy = 0.90). Our study shows the successful simultaneous dual-tracer production leading to decreased radiation burden and costs. The simulation of dual subject injection to quantify the monoamine oxidase-A and serotonin transporter distribution proved its high potential. Multi-tracer imaging may drive more sophisticated study designs and diminish the day-to-day differences in the same individual as well as increase PET scanner efficiency.

Stability Modelling of mRNA Vaccine Quality Based on Temperature Monitoring throughout the Distribution Chain.

The vaccine distribution chains in several low- and middle-income countries are not adequate to facilitate the rapid delivery of high volumes of thermosensitive COVID-19 mRNA vaccines at the required low and ultra-low temperatures. COVID-19 mRNA vaccines are currently distributed along with temperature monitoring devices to track and identify deviations from predefined conditions throughout the distribution chain. These temperature readings can feed into computational models to quantify mRNA vaccine critical quality attributes (CQAs) and the remaining vaccine shelf life more accurately. Here, a kinetic modelling approach is proposed to quantify the stability-related CQAs and the remaining shelf life of mRNA vaccines. The CQA and shelf-life values can be computed based on the conditions under which the vaccines have been distributed from the manufacturing facilities via the distribution network to the vaccination centres. This approach helps to quantify the degree to which temperature excursions impact vaccine quality and can also reduce vaccine wastage. In addition, vaccine stock management can be improved due to the information obtained on the remaining shelf life of mRNA vaccines. This model-based quantification of mRNA vaccine quality and remaining shelf life can improve the deployment of COVID-19 mRNA vaccines to low- and middle-income countries.

The impact of a trace amount of water in an electrolyte on the performance of Li‐ion batteries—An empirical kinetic model approach

A spiral wound-type lithium-ion battery (LIB) was assembled with an NCM532 cathode, a graphite anode and an electrolyte containing 1 M LiPF6 in EC/DEC (1:1 by wt). Different amounts of trace water, from 100 to 900 ppm, were intentionally added into the electrolyte. After stabilizing, the water and the hydrofluoric acid contents in the electrolyte were determined with Karl Fischer titration and coulometric titration, respectively. The performance of the LIBs made with the electrolytes of different amounts of trace water was investigated and the effects of the trace water in the electrolyte were revealed. An empirical model was used in this study to calculate the LIBs capacity attenuation constant. By varying the temperature, the activation energy of capacity decay can also be obtained based on the Arrhenius equation. The results indicated that added trace water up to 900 ppm may not significantly harm the cyclic stability of LIBs at least around room temperature. The capacity fade for the cells with the addition of 300 ppm water was slower than those without water addition. The activation energy of capacity decay was also found to be higher as the contents of added trace water are in the range of 100-400 ppm. This suggests a cost-reducing process of LIBs manufacture in the moisture control respect. Novelty statement Different amounts of trace water were intentionally added into the electrolyte and variation of water as well as formed HF contents were determined by Karl Fischer titration and coulometric titration, respectively. The kinetic information of water reacted with LiPF6 was then obtained. After introducing those electrolytes into the LIB cells, the performances of those LIBs were investigated and the capacity attenuation constants and capacity decay activation energies upon those LIBs were calculated through a newly suggested empirical kinetic model.

The transition from a nitrogen oxides-limited regime to a volatile organic compounds-limited regime in the petrochemical industrialized Lanzhou City, China

Heavy ozone (O3) pollution is often observed in the petrochemical industrial city of Lanzhou, located in the semi-arid and mountainous northwest China. The mountain-valley topography, special meteorological conditions, and high precursor emissions from the petrochemical industry across the city caused significantly increasing surface ozone concentrations in recent years. We investigated temporal distributions of O3 and its precursors and explored volatile organic compounds (VOCs) ‘composition and its contribution to O3 formation. The Ozone Isopleth Plotting Research (OZIPR) model was used to illustrate the ozone isoconcentration curves and assess the responses and sensitivity of O3 concentrations to its precursors. The results show that, in summer 2018, the VOCs/ nitrogen oxides (NOx) ratio defined in the ridgeline of the Empirical Kinetic Modeling Approach (EKMA) curve was about 13.8:1, indicating that ozone was formed in the NOx-limited regime, whereas in summer 2019, this ratio was 15:1, indicating that ozone was formed in the VOCs-limited regime, featuring a transition from a NOx-limited regime in summer 2018 to a VOCs-limited regime in summer 2019. We explored potential causes of this transition and attributed it to a large-scale instrument overhaul that resulted in significantly lower OH radical concentrations in summer 2019 and lower VOC emission after the overhaul. The modeling results using the Regional Atmospheric Chemical Mechanism version 2 (RACM2) photochemical box model show that the peak OH radical concentration in the summer of 2018 was much higher than that of 2019, reaching 12.38 × 106 molecules·cm−3. The result was confirmed by the Community Multiscale Air Quality (CMAQ) modeling system.

Investigation of thermal contaminants in coffee beans induced by roasting: A kinetic modeling approach

The roasting-induced formation of thermal contaminants in coffee beans, including 5-hydroxymethylfurfural (5-HMF), acrylamide (AA), furan (F), 2-methyl furan (2-MF), and 3-methyl furan (3-MF), was investigated using a kinetic modeling approach. Results showed that AA and 5-HMF formation and elimination occur simultaneously in coffee beans during roasting and that the related reactions follow first-order reaction kinetics. The concentrations of F, 2-MF, and 3-MF increased throughout the roasting experiment, and variations in the concentrations of these compounds during roasting could be best described by empirical, logistic model. The increase in weight loss and decrease in moisture content of the beans during roasting also displayed first-order reaction kinetics. High coefficients of determination (R2 > 0.981) were observed for all fitted models, and the reaction rate constants of all models followed the Arrhenius law.

A New Approach of Kinetic Modeling: Kinetically Consistent Energy Profile and Rate Expression Analysis

A New Approach of Kinetic Modeling: Kinetically Consistent Energy Profile and Rate Expression Analysis

Predicting equilibrium moisture content of mushrooms by NARX neural network and first order kinetic modelling approaches

Soft-cellular and porous agricultural products continuously exchange water vapor with their surrounding environment. The aim of this work was to model the water vapor sorption kinetics of mushrooms by strictly pragmatic and numerical approaches. A nonlinear autoregressive with exogenous inputs (NARX) neural network was used to simulate water vapor sorption kinetics over a wide range of relative humidity at temperatures of 20-40°C. The predictive power of the neural network was based on physical data, namely time-series of relative humidity at constant temperature. In addition, the time dependence of water vapor sorption was fitted by a first-order kinetic model, which was applicable for all relative humidity steps. Both models were fed with a total sample size of ca. 11000 data points generated by an automated gravimetric dynamic vapor sorption system. A neural network with a seven-node hidden layer was found to have the best performance. The results revealed the potential efficient use of artificial neural networks in simulating water vapor sorption kinetics of mushrooms and consequently predicting equilibrium moisture content with a high accuracy in the entire range of relative humidity and temperature covered by the experiments.

Mathematically modelling the inactivation kinetics of Geobacillus stearothermophilus spores: Effects of sterilization environments and temperature profiles

In this study, inactivation kinetics of Geobacillus stearothermophilus spores were evaluated in different sterilization environments. The kinetics were analysed and mathematically modelled based on experimental data collected. The inactivation kinetics were measured precisely in moist heat environments using different sterilization temperatures and holding times. All measured inactivation times were shorter than the inactivation time indicated by the Biological Indicator (BI) manufacturer. Increasing sterilization efficiency was found in the following environments: air, saturated steam, wet steam, liquid water, dialysis solutions. Applying first- and second-order reaction kinetics approaches, formulas were derived from measured data that enabled bacterial inactivation to be modelled. A mathematical first-order reaction kinetic modelling approach could be taken to effectively predict inactivation kinetics for G. stearothermophilus spores based on the experimentally measured data collected in wet steam and air environments. A second-order reaction kinetics approach could be taken, however, to model measured data more accurately in liquid water and dialysis-solution environments. The mathematical models presented here can be applied to describe inactivation kinetics for G. stearothermophilus spores in different sterilization test environments or for any given sterilization temperature profile. These findings can be used to improve the quality of sterilization processes.