Model-fitting Methods Research Articles

Effects of fitting methods, high b-values and image quality on diffusion and perfusion quantification and reproducibility in the calf

PurposesThe study aimed to optimize diffusion-weighted imaging (DWI) image acquisition and analysis protocols in calf muscles by investigating the effects of different model-fitting methods, image quality, and use of high b-value and constraints on parameters of interest (POIs). The optimized modeling methods were used to select the optimal combinations of b-values, which will allow shorter acquisition time while achieving the same reliability as that obtained using 16 b-values. MethodsTest-retest baseline and high-quality DWI images of ten healthy volunteers were acquired on a 3T MR scanner, using 16 b-values, including a high b-value of 1200 s/mm2, and structural T1-weighted images for calf muscle delineation. Three and six different fitting methods were used to derive ADC from monoexponential (ME) model and Dd, fp, and Dp from intravoxel incoherent motion (IVIM) model, with or without the high b-value. The optimized ME and IVIM models were then used to determine the optimal combinations of b-values, obtainable with the least number of b-values, using the selection criteria of coefficient of variance (CV) ≤10% for all POIs. ResultsThe find minimum multivariate algorithm was more flexible and yielded smaller fitting errors. The 2-steps fitting method, with fixed Dd, performed the best for IVIM model. The inclusion of high b-value reduced outliers, while constraints improved 2-steps fitting only. ConclusionsThe optimal numbers of b-values for ME and IVIM models were nine and six b-values respectively. Test-retest reliability analyses showed that only ADC and Dd were reliable for calf diffusion evaluation, with CVs of 7.22% and 4.09%.

Evaluation of oil palm waste mild pyrolysis kinetic parameters

With the goal of contrasting model-fitting and model-free methods for the kinetics of mild pyrolysis for empty fruit bunches (EFB), EFB were thermal decomposed and the profile was analysed using thermalgravimetric analysis (TGA). Coats-Redfern (CR) and Kissinger-Akahira-Sunose (KAS) methods were selected to represent model-fitting and model-free methods respectively. The activation energies (Ea) calculated for CR ranged between 22.45 and 26.31 kJ mol−1 (regression coefficient, R2 of 0.93 to 0.95) while the average Ea for KAS was 3.98 kJ mol−1. Compared with other typical model fuels, the mild pyrolysis of EFB from this work shows higher thermal instability, hence more reactive compared to previous works. Furthermore, the KAS method is more reliable in representing the mild pyrolysis process due to its higher overall regression coefficients showing that the assumptions of the KAS method are more accurate.

A spectroscopic modelling method for the detached eclipsing binaries to derive atmospheric parameters

Based on luminosity contributions, we develop aspectroscopic modelling method to derive atmospheric parameters of component stars in binary systems. The method is designed for those spectra of binaries that show double-lined features due to radial-velocity differences between the component stars. We first derive the orbital parameters and the stellar radii by solving the light and radial-velocity curves. The luminosity contributions in different phases can then be calculated. We construct a synthesised double-lined spectra model by superposing theoretical single-star spectra according to the luminosity contributions. Finally, we derive the atmospheric parameters of each component star using the model-fitting method. For multi-epoch double-lined spectra observed by the Large sky Area Multi-Object Spectroscopic Telescope (LAMOST) Medium Resolution Survey (R ~ 7500), our method gives robust results for detached eclipsing binary systems observed in different orbital phases. Furthermore, this method can also be applied to other spectroscopic data with different resolutions as long as the systems are detached eclipsing binaries with nearly spherical stars.

A combined kinetic analysis for thermal characteristics and reaction mechanism based on non-isothermal experiments: The case of poly(vinyl alcohol) pyrolysis

This work aims to implement one efficient combined kinetic approach for determining thermal kinetic triplets and elucidating reaction mechanism for poly(vinyl alcohol). Thermogravimetric pyrolysis profiles were acquired in inert nitrogen atmosphere with 5, 10, 15, and 20 K/min heating rates, and its thermal decomposition behavior was characterized in details. With respect to two main stages identified in whole pyrolysis process, their activation energies varying with conversion extents were computed by applying several model free methods, including FWO, KAS, FR, and advanced isoconversion approaches. Subsequently, the linear CR and non-linear masterplots model fitting methods were to severely figure out the appropriate reaction mechanism functions. Of particular interest is observed that F3/2 and F2 mechanism models were separately deemed to be appropriate for two stages, but they failed in giving good overlapping details with experimental data. Furthermore, a combined kinetic analysis was carefully conducted to obtain kinetics triplets, which includes model independent analysis and thoroughly considers kinetic compensation effect. Thereby, accurate reaction models were separately optimized and reconstructed for two distinct pyrolysis steps by the imported accommodation functions. This work finally provides a precise methodology to gain insight into thermal behavior and decomposition mechanism of poly(vinyl alcohol) , and improve the prediction accuracy of kinetics.

Effect of the milling conditions on the decomposition kinetics of gibbsite

Synthetic gibbsite (Al(OH)3) was mechanically activated by attrition milling for 24h, with various grinding ball-to-powder weight ratios (0, 5, 10, and 20), and characterized by thermal analysis (TG-DSC). Further, we determined the corresponding kinetic parameters using the model-free and model-fitting methods from the Thermogravimetric Analysis (TG) data set. We found that the activation energies provided by both models agree very well. At temperatures higher than 350°C, the milled samples (GB5, GB10, and GB20) lose mass very slowly, while the unmilled sample (GB0) decomposes faster. In addition, we demonstrated that the decomposition mechanism of each sample engages multi-step reactions, and the corresponding activation energies change with the increasing milling conditions.

Effect of different thermoplastics on the thermal degradation behavior, kinetics, and thermodynamics of discarded bakelite.

In this work, the kinetics, thermodynamics, and mechanism for co-pyrolysis of thermoplastic (PP, HDPE, PS, PMMA)blended bakelite (BL) (1:1 by weight) are explored utilizing different kinetics models like model-fitting and KAS model-free method. The thermal degradation experiments of each sample are conducted from ambient to 1000°C temperature at 5, 10, 20, 30, and 50°C/min heating rates in an inert environment. Thermoplastic blended bakelite is degraded in four steps, including two significant weight loss steps. A significant synergetic effect was observed by the addition of thermoplastics, which is reflected in the change in the thermal degradation temperature zone and the weight loss pattern. Among the four thermoplastics blended bakelites, the promotional synergetic effect is more pronounced for PP addition, causing an increase in the degradation of discarded bakelite by 20%, whereas the addition of PS, HDPE, and PMMA enhances the degradation of bakelite by 10%, 8%, and 3% respectively. Again, the activation energy of the thermal degradation of PP blended bakelite is found lowest followed by HDPE blended bakelite, PMMA blended bakelite, and PS blended bakelite. The mechanism of thermal degradation of bakelite changed from F5 to F3, F3, F1, and F2.5 by the addition of PP, HDPE, PS, and PMMA respectively. A significant change in the thermodynamics of the reaction is also found in the addition of thermoplastics. The kinetics, degradation mechanism, and thermodynamics for thermal degradation of the thermoplastic blended bakelite contribute to the optimization of pyrolysis reactor design to increase valuable pyrolytic products.

Thermal degradation model of used surgical masks based on machine learning methodology

BackgroundThe COVID-19 pandemic has leveraged facial masks to be one of the most effective measures to prevent the spread of the virus, which thereby has exponentially increased the usage of facial masks that lead to medical waste mismanagements which pose a serious threat to life. Thermal degradation or pyrolysis is an effective treatment method for the used facial mask wastes and this study aims to investigate the thermal degradation of the same. MethodsPredicted the TGA experimental curves of the mask components using a Machine Learning model known as Artificial Neural Network (ANN). Significant findingsThree different parts of the mask namely- ribbon, body, and corner were separated and used for the analysis. The thermal degradation behavior is studied using Thermogravimetric Analysis (TGA) and this is crucial for determining the reactivity of the individual mask components as they are subjected to a range of temperatures. Using the curves obtained from TGA, kinetic parameters such as Activation energy (E) and Pre-exponential factor (A) were estimated using the Coats-Redfern model-fitting method. Using the determined kinetic parameters, thermodynamic quantities such as a change in Enthalpy (ΔH), Entropy (ΔS), and Gibbs-Free energy (ΔG) were also calculated. Since TGA is a costly and time-consuming process, this study attempted to predict the TGA experimental curves of the mask components using a Machine Learning model known as Artificial Neural Network (ANN). The dataset obtained at a heating rate of 10°C/min was used to train the 3 different neural networks corresponding to the mask components and it showed an excellent agreement with experimental data (R2 > 0.99). Through this study, a complex chemical process such as thermal degradation was modelled using Machine Learning based on available experimental parameters without delving into the intricacies and complexities of the process.

Study on Thermal Degradation Processes of Polyethylene Terephthalate Microplastics Using the Kinetics and Artificial Neural Networks Models

Because of its slow rate of disintegration, plastic debris has steadily risen over time and contributed to a host of environmental issues. Recycling the world’s increasing debris has taken on critical importance. Pyrolysis is one of the most practical techniques for recycling plastic because of its intrinsic qualities and environmental friendliness. For scale-up and reactor design, an understanding of the degradation process is essential. Using one model-free kinetic approach (Friedman) and two model-fitting kinetic methods (Arrhenius and Coats-Redfern), the thermal degradation of Polyethylene Terephthalate (PET) microplastics at heating rates of 10, 20, and 30 °C/min was examined in this work. Additionally, a powerful artificial neural network (ANN) model was created to forecast the heat deterioration of PET MPs. At various heating rates, the TG and DTG thermograms from the PET MPs degradation revealed the same patterns and trends. This showed that the heating rates do not impact the decomposition processes. The Friedman model showed activation energy values ranging from 3.31 to 8.79 kJ/mol. The average activation energy value was 1278.88 kJ/mol from the Arrhenius model, while, from the Coats-Redfern model, the average was 1.05 × 104 kJ/mol. The thermodynamics of the degradation process of the PET MPs by thermal treatment were all non-spontaneous and endergonic, and energy was absorbed for the degradation. It was discovered that an ANN, with a two-layer hidden architecture, was the most effective network for predicting the output variable (mass loss%) with a regression coefficient value of (0.951–1.0).

BabyNet: Reconstructing 3D faces of babies from uncalibrated photographs

We present a 3D face reconstruction system that aims at recovering the 3D facial geometry of babies from uncalibrated photographs, BabyNet. Since the 3D facial geometry of babies differs substantially from that of adults, baby-specific facial reconstruction systems are needed. BabyNet consists of two stages: 1) a 3D graph convolutional autoencoder learns a latent space of the baby 3D facial shape; and 2) a 2D encoder that maps photographs to the 3D latent space based on representative features extracted using transfer learning. In this way, using the pre-trained 3D decoder, we can recover a 3D face from 2D images. We evaluate BabyNet and show that 1) methods based on adult datasets cannot model the 3D facial geometry of babies, which proves the need for a baby-specific method, and 2) BabyNet outperforms classical model-fitting methods even when a baby-specific 3D morphable model, such as BabyFM, is used.

The pyrolysis behavior of poly(styrene–methyl methacrylate) copolymer and expanded polystyrene (EPS) foams using model-free and model fitting methods

The pyrolysis behavior of poly(styrene–methyl methacrylate) copolymer and expanded polystyrene (EPS) foams using model-free and model fitting methods

Comparative bio-energy potential of De-oiled coconut pulp and Coconut shell: Insights from physicochemical characterization, pyrolysis kinetics and thermodynamic studies

It is critical to study the bioenergy potential of De-oiled coconut pulp (a new biomass material) in comparison with Coconut shell which are two major wastes from Coconut fruit often disposed of by Coconut oil processing mills, in tropical countries especially Nigeria. Their comparative potential as a bioenergy source was assessed via physicochemical and thermo-chemical characteristics. Both biomass wastes were heated from ambient temperature to 1123.15 K at 5, 10, 15, 20, and 30 K∙min−1. A global dynamic mechanism from the Coats-Redfern model–fitting method was applied to non-isothermal data, using isoconversional methods, to obtain the non-isothermal kinetic and thermodynamic parameters. The physicochemical analysis of the biomass wastes revealed that De-oiled coconut pulp has the potential to produce lighter volatile products but the Coconut shell will produce relatively heavier but cleaner products from a less problematic pyrolysis process. The average apparent activation energies (Ea) from Friedman, FWO, and KAS methods for De-oiled coconut pulp were 333.1 kJ∙mol−1, 316.08 kJ∙mol−1, and 342.01 kJ∙mol−1 while for Coconut shell were 185.29 kJ∙mol−1, 178.75 kJ∙mol−1, and 176.98 kJ∙mol−1 respectively. The dynamic mechanism function, f(α), for reaction order from the Coats-Redfern model–fitting method, were (1 - α)4.2 and (1 - α)6.35 for De-oiled coconut pulp and Coconut shell respectively. Experimental values of differential change in weight with respect to temperature were in good agreement with Friedman model predictions for the pyrolysis of De-oiled coconut pulp at 5 K∙min−1 and 30 K∙min−1 (R2 = 0.7025 and 0.7495, RMSE = 0.087 and 0.1313 respectively) and for the pyrolysis of Coconut shell at 10 K∙min−1 (R2 = 0.8743, RMSE = 0.0663). F-test confirmed the fitness of the model predictions with experimental data. KAS and FWO established ΔG as a thermodynamic property of a great potential utility. The thermodynamic properties revealed that the pyrolysis of both biomass wastes was endothermic. The physicochemical properties established that both biomass wastes are potential bioenergy sources. The level of mass conversion was dependent on the apparent activation energy Ea which confirms proof of multi-step decomposition kinetics, an assumption made for isoconversional model development. Biomass reactivity in pyrolysis is critical to the application of reaction order from Coats-Redfern isothermal kinetics to non-isothermal kinetics.

Kinetics Study of Polypropylene Pyrolysis by Non-Isothermal Thermogravimetric Analysis.

Polypropylene (PP) is considered as one of six polymers representative of plastic wastes. This paper attempts to obtain information on PP polymer pyrolysis kinetics with the help of thermogravimetric analysis (TGA). TGA is used to measure the weight of the sample with temperature increases at different heating rates-5, 10, 20, 30, and 40 K min-1-in inert nitrogen. The pyrolytic kinetics have been analyzed by four model-free methods-Friedman (FR), Flynn-Wall-Qzawa (FWO), Kissinger-Akahira-Sunose (KAS) and Starnik (STK)-and by two model-fitting methods-Coats-Redfern (CR) and Criado methods. The values of activation energies of PP polymer pyrolysis at different conversions are in good agreement with the average of (141, 112, 106, 108 kJ mol-1) for FR, FWO, KAS and STK, respectively. Criado methods have been implemented with the CR method to obtain the reaction mechanism model. As per Criado's method, the most controlling reaction mechanism has been identified as the geometrical contraction models-cylinder model.

Kinetic parameters underlying hematite-assisted decomposition of tribromophenol

Interaction of brominated flame retardants (BFRs) and transition metal oxides is a widely utilized approach in thermal recycling of bromine-contaminated plastics. An optimum design of the operation requires the development of accurate thermo-kinetic parameters that dictate the co-degradation of both entities. To attain this obviative, thermal degradation behavior pertinent to co-pyrolysis and co-combustion of hematite (Fe2O3): tribromophenol (TBP) mixtures was explored in a thermogravimetric analyzer (TGA) at various heating rates. Thermo-kinetic parameters for mixtures were acquired based on TGA runs while employing three major model-free or isoconversional methods (KAS, Starink, and FWO) and model-fitting methods (Coats-Redfern). Obtained profiles infer that the addition of hematite systematically reduces the governing activation energy (Ea) in both thermochemical processes in reference to neat TBP. The hematite-assisted debromination of TBP under oxidative conditions entails lower activation energy when compared with degradation under pyrolytic conditions. Molecular modeling mapped out initial mechanisms that operate in the interaction with a prime focus on reactions that lead to ring opening of the aromatic rings. Overall, the results obtained from the thermal chemical conversions find direct application in reactor modeling and heat transfer design in domains related to the recycling of electronic and electrical waste (e-wastes).

Non-isothermal thermo-kinetics and empirical modeling: Comparative pyrolysis of cow and Buffalo manure

Dumping dairy manure in surroundings of confined animal feeding operations (CAFO) is an extensively implemented malpractice. This exercise poses serious environmental complications along with global warming, water, and air pollution. This study aims to explore and compare the pyrolytic conversion of the dairy manure of two common milch animals (Cow and Buffalo) of CAFO through detailed kinetic and thermodynamic analysis. Physicochemical characterization indicated an analogy in samples with close values of volatile contents (63 % ± 0.22), elemental carbon contents (37 % ± 0.24) and heating values (16 MJ/Kg ± 0.0.95). Subsequently, under non-isothermal and inert thermogravimetric analysis (TGA), the thermal degradations kinetics were studied through Isoconversional methods and Model fitting methods. TGA recorded major conversion (≈ 50 %) during active pyrolysis zone in temperature range of 240 to 360⁰C for both sample with similar patterns. The average activation energy (Ea) determined by the Isoconversional methods were 143.84 and 137.74 kJ mol−1, with corresponding frequency factor (A) values of 4.19 × 1026 and 2.47 × 1023 min−1 for cow manure (CM) and buffalo manure (BM), respectively. The kinetic compensation effect described strong linear relationship between the Ln(A) and Ea with comparable isokinetic temperatures. Master plot indicated that decomposition was driven by order-based reaction (Fn) with transition to Diffusion (Dn) models. The empirical modeling by Sestak and Berggren’s model showed an excellent correlation with the experimental data. Finally, thermodynamic analysis indicated a non-spontaneous and endothermic trend in entire conversion. Overall, the study suggested comparable thermo-kinetics of CM and BM pyrolysis.

Pyrolysis Kinetic Study of Polylactic Acid

Polylactic acid (PLA) is a biodegradable polymer and is mainly used in the textile and food packaging fields. The aim of this work is to build knowledge on the kinetics of the pyrolysis of PLA with the help of thermogravimetric analysis (TGA) using four model-free methods, namely Friedman, Flynn-Wall-Qzawa (FWO), Kissinger-Akahira-Sunose (KAS), and Starink. Additionally, two model-fitting methods (the Coats-Redfern and Criado methods) were applied. TGA data at 5, 10, 20, and 30 K/min heating rates were collected. The obtained activation energies of the pyrolysis of PLA at different conversions by the model-free models were in good agreement and the average values were 97, 109, 104, and 104 kJ/mol for Friedman, FWO, KAS, and Starink, respectively. The Criado model was used together with the Coats-Redfern model to identify the most appropriate reaction mechanism. As per this work, the best controlling reaction mechanism of the PLA pyrolysis can be expressed by the geometrical contraction model (R2).

Thermal degradation characteristics, kinetic and thermodynamic analyses of date palm surface fibers at different heating rates

The potential of the least-exploited date pam waste was presented as feedstock for bio-oil production. The surface fibers of the date palm are widely available as waste material in the Gulf region, the Middle East, and Africa. Chemical composition analysis and physiochemical characterization showed that surface fibers are valuable feedstock for energy production. Surface fibers were analyzed thermogravimetrically at different heating rates (10, 20, and 30 °C /min) in an inert atmosphere. Decomposition was carried out in three stages: dehydration, devolatilization, and solid combustion. Kinetic analysis was performed on the devolatilization region using the Coats–Redfern model–fitting method using twenty–one reaction mechanisms from four different solid-state reaction mechanisms. Two diffusion models: one–way transport (g(x) = α2) and Valensi equation (g(x) = α+(1-α) × ln(1-α)) showed the highest regression coefficient (R2) with the experimental data. The activation energy (Ea) and the pre-exponential factor (A) was estimated to be 91.40 kJ/mol and 1.59 × 103 –29.39 × 103 min−1, respectively. The kinetic parameters were found to be dependent on the heating rate. The surface fibers' thermodynamic parameters ΔH, ΔG, and ΔS were 80–97, 151–164, and −0.17- −0.18 kJ/mol, respectively. This indicates that the pyrolysis of surface fibers is endothermal and not spontaneous. Since there is not much experimental work on the pyrolysis of surface fibers available in the literature, the reported results are crucial for designing the pyrolysis process.

Kinetic analysis of complex chemical reactions by coupling model-free and model-fitting analysis

Three different complex multi-step reaction mechanisms of parallel-competing, consecutive and parallel-independent reactions were simulated for two different sets of kinetic parameters. The two sets were chosen in such a way to represent two very different situations. An advanced non-linear isoconversional method (NLN) and a multiple heating rates model-fitting method using nonlinear optimization (NLO) were applied to the data. The errors in kinetic parameters were evaluated for each set of data and for each method. It is shown that analysis of the thermoanalytical curves and of the Eα-dependencies can be used in complementary with the model-fitting approach for the elucidation of the reaction mechanisms and estimation of the kinetic parameters of each step. In most cases, NLO improved the accuracy of the kinetic parameters obtained from NLN method, but only if the mechanism was known. However, selecting the right mechanism is an essential problem of NLO. The study showed that it was possible to accurately fit the mechanism of two consecutive steps with a model of two independent steps that resulted in evaluating invalid kinetic parameters. This example also highlights an important limitation of the so-called deconvolution kinetic analysis which consists in fitting of various multi-step reaction mechanisms with a model of independent steps.

Thermo-kinetic analysis and microstructural characterization of fractured-carbonate rock exposed to high temperature

A significant amount of the world oil reserves is held in naturally fractured carbonate reservoirs which can undergo temperature-induced changes in structural and physicochemical properties while applying thermal stimulation methods. This study reports thermo-kinetic and microstructural analyses of a fractured-carbonate rock from a Mexican reservoir exposed to high temperatures using thermogravimetry and X-ray micro-computed tomography. Activation energies and reaction mechanism kinetics involved in the thermal degradation of the rock sample were determined through iso-conversional and model-fitting methods. X-ray diffraction revealed the expected mineralogy of the rock sample: dolomite (96.5%) and quartz (3.5%). Results indicated that rock thermal-decomposition follows a first-order reaction kinetics with an average activation energy of 195.910 kJ/mol. Noteworthy microstructural changes were detected on the analyzed fractured-carbonate rock exposed to heat-treatment which resulted in percent increases of 7.47, 4.37 and 25.39% in total, effective and isolated porosity, respectively. Results presented in this work can be relevant for the exploitation through thermal stimulation methods of naturally fractured carbonate reservoirs.

Optimized TGA-based experimental method for studying intrinsic kinetics of coal char oxidation under moderate or intense low-oxygen dilution oxy-fuel conditions

Accurate assessment of coal char oxidation kinetics is essential for the design of efficient combustion systems; nonetheless currently, there is little research on this aspect under moderate or intense low-oxygen dilution (MILD) oxy-fuel (MO) conditions. In this study, experimental and modeling studies were conducted for analyzing the intrinsic kinetic properties of coal char oxidation under MILD air-combustion (MA) and MO conditions based on thermogravimetric analysis (TGA). The experimental conditions were improved to minimize various diffusion resistances in the crucible during the TGA experiments. Under the optimal conditions of TGA experiments, the reactivity differences of coal char under the MA and MO atmospheres were small. Both nonlinear model-fitting and linear model-free analysis methods were used to analyze kinetic parameters of coal char oxidation. The results showed that the random pore model correlated the best with the experimental results. The activation energies of coal char under the optimal conditions in MA and MO atmospheres (i.e., 104.4 kJ/mol and 98.2 kJ/mol, respectively) were much higher than those obtained by the conventional method. The reaction orders of coal char oxidation in MA and MO atmospheres were close to 1.0, and the specific values were affected by the diffusion effect and background atmosphere.

Isothermal Kinetic Study and Shelf-Life Prediction of Triple Base Propellant Using Vacuum Stability Test in Combination with HPLC and GPC

ABSTRACT In this study, isothermal decomposition kinetic of a triple-base propellant (TBP) has been investigated by vacuum stability test (VST). The volumes of the evolved gas have been recorded step by step to monitor gas evolution in VST at 80°C, 90°C, 100°C, 110°C, 120°C, and 150°C. This semi-continuous data-recording mode makes it possible to use the Berthelot equation for shelf-life prediction of TBP. Activation energy has been calculated in both model-free and model-fitting methods, and F0/R1 is determined as the best model for thermal decomposition of TBP at VST. High-performance liquid chromatography has been used to determine stabilizer (methyl centralite) content of the TBP at various extents of reactions (α). The critical amount of stabilizer was specified at 2% α. Arrhenius average temperatures have been calculated at various climate categories and used as actual storage temperatures. Molecular weight (Mw) reductions of nitrocellulose were determined by gel permeation chromatography during aging. According to the results, the shelf-life of TBP has been estimated using the Berthelot equation at 2% α in various climate categories. Shelf-life of studied TBP differs from 14 to about 36 (years) in extremely hot dry (A1) to intermediate (A3) climate categories.