Wide Range Of Heating Rates Research Articles

Composite liquids under high-power heating: superheat of water in micro-explosion of water-in-fuel droplets

Abstract The article analyses the degree of water superheating with respect to the liquid-vapour equilibrium line in experiments on the micro-explosion of a composite droplet comprised of two immiscible liquids. The analyses were carried out for water-in-fuel drops under conditions of high-power heating. This degree is compared with the mechanical effect of droplet decay, involving the formation of daughter droplets. Our attention was drawn to the smallness of the degree of superheating preceding the decay. A model of the boiling up of such a droplet is constructed taking into account the sources of premature boiling up of water inherent in micro-explosive experiments. The dependencies of the boiling up temperature of water on the heating rate obtained in the model turned out to be in accordance with the experimental data across a wide range of heating rates. A hypothesis about the local superheating of the transition layer, which is not detected in the experiment, is formulated. Thus, a step has been taken to clarify the essence of the mismatch of the degree of superheating of water recorded by macroscopic equipment along with a completely satisfactory generation of daughter droplets serving as the basis for advanced fuel technology.

Problems with the determination of activation energy as function of the reacted fraction from thermoanalytical experiments

The so-called compensation effect is well known between the activation energy, E, and the pre-exponential factor, A. The present work shows by examples that much higher compensation effects may arise when E and A vary with the reacted fraction. For this purpose, a set of five simulated experiments were constructed by first-order kinetics with E = 200 kJ mol−1 at a wide range of heating rates. These data were evaluated by the method of least squares assuming E and A as functions of the reacted fraction. Such E functions were found which highly differed from a constant E while described well the evaluated data. They included a linearly increasing E and several parabolic E functions. The observed effects may contribute to the contradictory kinetic parameters that were reported in the literature of the isoconversional (“model-free”) studies. It was found that the compensation effects between E and A functions can be 8–11 times higher than between E and A values.

A review on biomass thermal-oxidative decomposition data and machine learning prediction of thermal analysis

Thermochemical conversion is the most economical approach to recovering energy and alternative fuels from biomass feedstock. This work first reviews the literature data on thermal-oxidative decomposition for common biomass types and forms a database of 18 parameters, including element, proximate, and thermogravimetric analysis (TGA). Then, an Artificial Neural Network (ANN) model is developed for the prediction of TGA data. Pearson correlation coefficient analysis reveals that the influence of environment heating rate on biomass thermal decomposition is larger than that of fuel properties. By inputting biomass elemental/proximate analysis and heating rate, the ANN model successfully predicts 8 key TGA parameters, namely, pyrolysis-onset temperature, peak pyrolysis temperature, oxidation-dominant temperature, peak oxidation temperature, oxidation-end temperature, peak pyrolysis rate, oxidation-dominant rate, and peak oxidation rate, with R2 values greater than 0.98. A better performance can be achieved when all ten input features are considered. Final, an open-access online software, Intelligent Fuel Thermal Analysis (IFTA), is developed to predict thermal-oxidative decomposition across a wide range of heating rates and biomass types. This work provides a better understanding of biomass thermal-oxidative decomposition dynamics and a shortcut to obtain key parameters of biomass degradation without TGA tests.

Assessing pyrolysis performance and product evolution of various medical wastes based on model-free and TG-FTIR-MS methods

The COVID-19 pandemic has caused a substantial rise in the amount of medical waste, posing additional hurdles in waste management. Disposing of this waste properly is essential to curb transmission of the diseases. The pyrolysis reaction kinetics, synergistic interactions, and pyrolysis gas release behavior of typical constituents of medical waste (MW): syringe (SY), medical gloves (MG), cotton swab sticks (CS), and their blends were examined by utilizing advanced analytical techniques including TG, TG-FTIR, TG-MS, and kinetic models (Friedman, KAS). The experiments were conducted using a wide range of heating rates, namely 10, 20, 30, and 40 °C⋅min−1. The pyrolysis reactions were mainly endothermic, with main stages ranging from 352.0–480.0 °C, from 381.0–511.0 °C, from 200.0–404.5 °C, 336.6–509.9 °C, 375.4–477.6 °C, 384.0–500.9 °C, for SY, MG, CS, SY5MG5, SY7CS3, and MG7CS3, respectively. According to the KAS method, the average activation energies for the mono-pyrolysis of SY, MG, and CS were determined as 240.8, 226.1, and 147.5 kJ⋅mol−1 respectively. Interestingly, during the pyrolysis of blends such as SY5MG5, SY7CS3, and MG7CS3, the activation energies decreased to 177.2, 159.9, and 149.1 kJ⋅mol−1 respectively. Notably, the experimental activation energy values (Eexp) obtained during the co-pyrolysis were significantly lower than the calculated values (Ecal), revealing an apparent synergistic effect during the pyrolysis of various MW blends. The pyrolysis process of MW blends resulted in the release of significant volatile components, including CH4, CO, C3H6, CO2, C2H5OH, C4H8, C5H8, C6H6, C6H14, C7H8, and C8H10. The specific composition of these volatile components varied depending on the types of waste present in the blends.

Crystallization kinetics in a lithium disilicate glass revisited: Model-free and model-fitting approaches

The present work estimated the crystallization activation energy, Eα, the pre-exponential term, A, and the reaction model, g(α), of a lithium disilicate glass using model-free and model-fitting approaches. Samples with distinct granulometry (PD1: < 105 μm; and PD5: 600–850 μm) were heated at several rates (0.5 to 30 K/min). Our results show that Eα, A, and g(α) are susceptible to particle size. PD1 crystallizes in a single step, and the surface mainly governs it all β values. On the other hand, the overall crystallization of PD5 is more complex and can be described by different Avrami reaction models, with n = 1, 1.5, 2, and 3. In addition, we found that the crystallized fraction at the crystallization peak (αTp) varies significantly with the particle size and heating rate, which confirms that all the methods that assume that the αTp is constant are inadequate to describe the crystallization of glasses over a wide range of heating rates.

Predicting tobacco pyrolysis based on chemical constituents and heating conditions using machine learning approaches

Tobacco is a special type of biomass that consists of complex chemical constituents. Currently, only global kinetic models have been developed for tobacco pyrolysis, but accurate kinetics considering the effects of the complex chemical constituents and heating conditions have not been well established. To this end, a general tobacco pyrolysis model was developed based on the complex chemical constituents and heating conditions using machine learning approaches. Specifically, chemical analysis and thermogravimetric analysis (TGA) of 49 tobacco samples under a wide range of heating rates were first conducted by experiments and then used to construct a database for the model development. Subsequently, the constructed database was divided into seen and unseen data-sets for the model development and evaluation. General pyrolysis models for single/multiple heating rates were developed from the seen data-set using an advanced machine learning approach, the Extremely Randomized Trees (Extra-Trees, ET). The performances of models were further evaluated on the unseen data-set through comparisons with the experimental data. The results showed that after feature selection based on Pearson correlation coefficient and hyper-parameters optimization, the trained models could accurately reproduce the tobacco pyrolysis behavior on the unseen data with R2>0.967 based on a single heating rate and with R2>0.974 based on all heating rates. In addition, the predicted derivative thermogravimetry (DTG) profiles were integrated to obtain the TGA profiles, and the results agreed very well with the experimental data (R2>0.99).

Comparison of Artificial Neural Networks and kinetic inverse modeling to predict biomass pyrolysis behavior

The prediction of biomass pyrolysis behavior has received immense research attention, which has challenged scientists as well as industrialists. Currently, the main predictive tool is inverse modeling which is based on a specific kinetic scheme. However, real biomass pyrolysis entails a complex reaction mechanism, the appropriate kinetic scheme is being explored. Because pyrolysis prediction is closely related to the accuracy of the proposed kinetic scheme, whether the prediction can be achieved without prior knowledge of the kinetic scheme is intriguing. Therefore, Artificial neural networks (e.g., back propagation neural network and Elman neural network) are applied for prediction based on unknown kinetic schemes. Specifically, Elman neural network, which is an uncommon biomass pyrolysis prediction method, has been applied. Moreover, the neural network structure that was subjected to different data sets was optimized to establish the optimal neuron number in the hidden layer, transfer function, and training function, which were based on thermogravimetric data over a wide heating rate range. Eventually, the predicted results agreed well with the experimental data. Moreover, compared with kinetic inverse modeling coupled with a common heuristic algorithm known as particle swarm optimization, our current ANNs results, which were based on the unknown kinetic scheme exhibited superior prediction ability, especially in the shoulder and peak regions of mass loss rate curves.

Toba-CPD: An Extended Chemical Percolation Devolatilization Model for Tobacco Pyrolysis.

Tobacco features chemical compositions different from that of raw lignocellulosic biomass. Currently, the performance of network models, like Bio-Chemical Percolation Devolatilization (Bio-CPD), on tobacco pyrolysis is unclear, and only global kinetics have been proposed for tobacco devolatilization, which does not have the versatility for a wide range of heating conditions and tobacco types. To address this issue, the present work first assessed the performance of the Bio-CPD model on tobacco pyrolysis through an a priori study, which showed large deviations. Afterward, an extended Chemical Percolation Devolatilization model for tobacco pyrolysis (Toba-CPD) was developed by modifying the kinetic parameters using a grid-search optimization strategy. The process of grid-search optimization strategy is based on the kinetic parameters of the Bio-CPD model and modified with experimental results of 11 tobacco types under a wide range of heating rates. Finally, the performance of Toba-CPD was measured with experimental results which were not used during parameters optimization. Results demonstrated that the Toba-CPD models could well reproduce the pyrolysis of various tobacco types under a wide range of heating rates (R2 > 0.957).

A semi-global reaction mechanism for the thermal decomposition of low-density polyethylene blended with ammonium polyphosphate and pentaerythritol

A semi-global reaction mechanism has been developed to capture the decomposition of a polymer, i.e. low-density polyethylene (LDPE) that contains a condensed-phase-active intumescent flame retardant, i.e. ammonium polyphosphate (APP) mixed with pentaerythritol (PER) with ratio 3:1 (wt/wt). The methodology combines thermogravimetric analysis (TGA) in anaerobic environment over a wide range of heating rates and inverse modeling of these experiments based on the Shuffled Complex Evolution (SCE) optimization algorithm. The decomposition of neat LDPE can be described by a single first-order reaction. In contrast, the decomposition of the APP/PER additive is characterized by strong interactions between the reactants and a 5-step reaction mechanism was designed driven by the mechanisms of the intumescence process. The direct coupling of the 1-step reaction mechanism for LDPE and the 5-step reaction mechanism for APP/PER was found to provide decent predictions for the decomposition of the 90%LDPE/10% APP/PER blend. The slight interactions between the LDPE matrix and the APP/PER additive were taken into account by updating the kinetic parameters of two reactions, leading to a final robust and accurate 6-step reaction model.

PYROLYSIS KINETICS OF KEYBOARD PLASTIC WASTE USING THERMOGRAVIMETRIC ANALYSER TO ASSESS ITS ENERGY POTENTIAL

In this paper, the kinetic parameters of discarded computer keyboard plastic waste are estimated using thermogravimetric analysis (TGA) with four different non-isothermal kinetic models at a wide range of heating rates 5, 10, 15, 20, 40, 60 and 100 °C/min. The gross calorific value of waste computer keyboard plastic is 38.96 MJ/Kg. FT-IR analysis confirms the presence of alcohol, phenol, ether, ester, carboxylic acid, aromatic, and alkene compounds in keyboard plastic waste. The average values of activation energy are calculated as 158.1668, 198.883, 193.612, and 197.765 kJmol−1 from Kissinger, Friedman, FWO, and Coats-Redfern methods, respectively. The kinetic data obtained in this work would be useful for accurate prediction of reaction behaviour and in the design of efficient commercial process for the conversion of such plastic wastes to energy.

Pyrolysis characteristics and kinetic study of coal in a novel concentrating photothermal thermogravimetric analyzer: Effect of heating rate

Coal pyrolysis is the initial reaction of vast utilization technologies, and the quantitative description of pyrolysis characteristics and accurate kinetic parameters under the wide range of heating rates are of significant challenges. The effect of heating rate from 5 ℃/min to 1000 ℃/min on coal pyrolysis in a novel concentrating photothermal thermogravimetric analyzer was systematically investigated. A new temperature control scheme especially for the ultra-fast heating process was proposed, guaranteeing the absolute temperature control error was less than 4 ℃ throughout the whole heating process. As the heating rate increased from 5 ℃/min to 1000 ℃/min, the absolute value of maximum mass loss rate increased linearly from 4.18 wt%/min to 66.06 wt%/min, and the specific reaction rate for coal conversion at 20% and 50% also increased linearly by 15.4 times and 16.4 times, respectively. The mean activation energies exhibited the exponential decrease tendency from 235.41 kJ/mol to 28.37 kJ/mol. The transformation rates for functional groups of chars were accelerated with the heating rate, and the char with same conversion rate would be more condensed. The activation energy of coal during pyrolysis under heating rate of 1000 ℃/min was binomially correlated with the ratio of small aromatic rings to large ones in char.

Feasibility study on co-processing of automobile shredder residue in coal-fired power plants via pyrolysis

Facing the challenges of organic industrial solid waste (OISW) disposal, co-processing of OISW by power plants has become a developing trend. In order to avoid feeding problems of OISW and enhance the combustion adaptability of the furnace, pyrolysis coupled with incineration technology is proposed as a potential method. Among various OISW, automobile shredder residue (ASR) is regarded as a promising fuel due to its high heating value. In view of engineering application, the researches focused on the products’ properties and economic evaluation under a wide range of heating rates which are insufficient. In this study, regarding the rapid pyrolysis by conducting the high-temperature flue gas as heating source in power plants, the pyrolysis behavior of ASR was correspondingly studied under a wide range of heating rates. The formation of volatiles and property’s improvement were further investigated for generating high-valued oil. Results showed that the high heating rate is not only beneficial to the homogenization of pyrolytic products but also the aromatization in oil and radical generation in gases. Importantly, it also contributed to the cleavage of the single bond connected to the benzene ring and carbon-oxygen single bond for esters. By conducting the enhanced cracking of volatiles, the wax-like fraction was significantly reduced. In addition, the deoxygenation in oil (oxygen content decreased by 20 wt%) and high heating value of gases (increased by 73%) were improved. Our findings demonstrated the feasibility and economic efficiency for the co-processing of ASR in coal-fired power plants via pyrolysis and thus provide guidance for future commercial application.

Transformation behavior and fate of chlorine in polychloroprene (PCP) during its pyrolysis

Polychloroprene (PCP) rubber is mostly mixed in industrial solid waste (ISW) as the main source of chlorine element. Whereas, the products formation and chlorine behavior during the pyrolysis are insufficiently illustrated for this typical chlorinated polymer, which is not conducive to the chlorine regulation of ISW pyrolytic products. In order to investigate the chlorine transformation behavior, the PCP pyrolysis under the influence of a wide range of heating rates (3–600 °C/min) was conducted to explore the chlorine distribution properties as well as its migration mechanism in the present study. Importantly, 30–65 wt% chlorine was found to be migrated to gas and tar, respectively. Compared with PVC, the differences of chlorine distribution between PCP and PVC may be attributed to the easier cyclization with a longer molecular chain. Also, the release temperature of HCl acted as main component determines its availability for the subsequent formation of chlorinated hydrocarbons. In details, the conversion pathway from chlorinated limonene to Cl-aromatic hydrocarbons was confirmed and the reaction was found to be enhanced at higher temperature and heating rate. By analyzing the content of tar components (especially at low heating rate), it was found that the major formation pathway of aromatic hydrocarbons was supposed to be the direct Diels-Alder reaction of monomer rather than the dechlorination of intermediate chlorinated limonene. Our findings discussed the effect mechanism of heating rate and temperature on chlorine behavior during PCP pyrolysis, providing guidance for the chlorine regulation of ISW pyrolytic products.

Experimental and Kinetic Studies on Tobacco Pyrolysis under a Wide Range of Heating Rates.

In the present work, experimental and kinetic studies are conducted to explore and model tobacco pyrolysis characteristics under a wide range of heating conditions. First, thermal decomposition processes of a tobacco sample were investigated using thermogravimetric analysis/difference thermogravimetry (TGA/DTG) experiments under a wide range of heating rates (10–500 K/min), and the TGA/DTG profiles were compared to highlight the effect of heating rate on the pyrolysis characteristics. The results showed that the tobacco sample was sufficiently devolatilized at 1173.15 K (900 °C) and the final volatiles yields were not sensitive to the heating rate. Moreover, it was illustrated that the DTG curve presents a polymerization trend with the increase in heating rate. Then, kinetic parameters, including total component mass fraction, preexponential factor, and activation energy, were derived by deconvolution from TG/DTG profiles for each component with a one-step kinetic framework, and the correlations between kinetic parameters and heating rates were further explored and modeled. The results illustrated that four subpeaks can be found in the deconvolution, indicating the four components (volatile components, hemicellulose, cellulose, and lignin). In addition, the activation energy of each component was found to be insensitive with heating rate (with standard deviation less than 20%). Therefore, an average activation energy was used for each component to avoid the compensation effect and a power correlation between the heating rate and the preexponential factor could be found. A posteriori analysis also confirmed the validity of this correlation.

Identifying Synergistic Effects between Biomass Components during Pyrolysis and Pointers Concerning Experiment Design

A review of existing data has shown that “char yield deficits” develop during the pyrolysis of lignocellulosic biomass, relative to char yields expected from pyrolyzing chemically isolated lignins and the proportion of lignin in the particular biomass. This paper describes two sets of pyrolysis experiments. The work done in a thermogravimetric (TG) balance was initiated to probe whether diminishing heating rates might reduce, or even wipe out, the “char yield deficits” identified in previous work, where a wide range of heating rates had been used. Experiments were performed at 2 °C min–¹, a lower heating rate than that has hitherto been used to investigate char deficits. The effect was confirmed at this slow heating rate, using samples of birchwood and almond shells. A parallel set of differential scanning calorimetry (DSC) experiments provided evidence that mechanisms by which biomass samples pyrolyze are distinct from those of biomass components pyrolyzing in isolation. Moreover, the observed effects could not be replicated by simply mixing the three biomass components in appropriate proportions. The “lignin char deficit” is consistent with chemical interactions between intermeshed biomass components during pyrolysis altering reaction pathways and product distributions relative to the pyrolysis of biomass components pyrolyzed in isolation. The present work also shows that sample mass loss in TG balances is affected by altering sample loading, leading to potential errors. The design of pyrolysis experiments is discussed and approaches are suggested to prevent masking of key pyrolysis phenomena, viz. synergistic effects between biomass components or onset-of-pyrolysis temperatures, through the appropriate selection of experimental parameters.

Performance of fire protective coatings on structural steel member exposed to high temperature

The purpose of this study is to investigate the performance of fire protective materials in protecting steel section. A new indexing system is introduced, named as fire endurance index (FEI), which can be used to evaluate the performance of fire protective materials.,In this study, experiments were carried out using W4 × 13 steel section. Eight samples were prepared; one was a bare steel section without any coating material, and seven were prepared using four types of materials such as vermiculite-gypsum plaster, gypsum plaster, concrete cover and glass wool-concrete cover for fireproofing of the sections. An enclosed electric coiled furnace was used for heating the samples for a certain period. The duration of protection was determined, and the FEI of the materials was calculated. The higher the index value is, the better the performance.,The results demonstrate that the glass-wool-concrete cover offered the best performance at high temperature among the four types of materials. In the experiment with glass-wool-concrete cover, the furnace temperature reached 750°C, whereas the steel temperature reached only 100°C. The FEI of the coatings were calculated. Among the eight samples, glass wool-concrete cover also achieved the highest index value.,The experimental work was performed using a limited number of specimens. Furthermore, the robustness of the indexing system needs to be evaluated with other materials and a wide range of heating rate and temperature. This study sets the foundation for future work.,The findings of this research may contribute to a better understanding of the performance of the materials used as fire protective coatings. This might be helpful for the researchers and practitioners in their design and implementation of legislation of fire safety codes.,Understanding the performance of the fire protective coatings will help in evaluating the fire resistance capabilities of the materials to use for the structural steel members, which may protect collapses and disasters of buildings.,This paper deals with the performance of four types of materials, that can be used as fire protective coatings for structural steel members. Furthermore, the FEI explicitly indicated their performance with numerical values. In this study, the heating of the specimens was performed using a non-standard fire curve based on the concept that naturally occurring incidents of fire do not follow the standard fire curves.

Design, fabrication and validation of an improved coil for induction dilatometry

Dilatometry is a versatile tool to investigate thermal expansion or phase transformations in various materials based on the length changes upon heating and cooling. Since most modern thermal processes tend to take place at high heating and cooling rates it can be demonstrated that a large longitudinal temperature gradient within dilatometric samples impedes the accurate investigation of physical mechanisms. In this study we investigate how an instrumental advancement of the induction heating system can be implemented in a dilatometric setup in order to mitigate the temperature gradient and its effect on the measured length change for a wide range of heating rates. For this purpose a numerical method for heating design optimization using a FEM simulation of the dilatometric experiment is developed and validated. The presented heating component design method in combination with additive manufacturing capabilities allows for a more accurate and flexible method of detecting dilatation in a dilatometric setup. Extreme temperature differences of 140∘C for a maximum heating rate of 800∘C/s could be reduced by 15-45% within the sample using new optimized instrumentation. This leads to a more profound and exact interpretation of dilatometric data for high heating rates and complex time temperature profiles.

Non-isothermal nanocrystallization of Fe83.3Si4B8P4Cu0.7 (NANOMET®) alloy: modeling and the heating rate effect on magnetic properties

The kinetics of the nanocrystallization of a Fe83.3Si4B8P4Cu0.7 amorphous alloy by using differential scanning calorimetry has been investigated by non-isothermal annealing in a wide heating rate range from 10 °C min−1 to 200 °C min−1. The amorphous alloy was prepared by melt-spinning and showed a two-stage crystallization. In the first crystallization stage, α-Fe nanocrystals are formed. This phase is responsible for the good soft magnetic properties. The activation energy during the crystallization of the α-Fe nanocrystalline phase was determined from an isoconversional approach, and was found to be distinctively varying during the crystallization. An attempt was made to model the crystallization in an interval where the activation energy is relatively constant. The Malek criterion indicated that the Kolmogorov–Johnson–Mehl–Avrami model is not appropriate, whereas the Sestak–Berggren model meets the criterion. The acquired model shows good agreement with the experimental results. The magnetic properties of annealed ribbons at different heating rates show an initially steep decrease of the coercivity (Hc) from 82 A m−1 at a heating rate of 10 °C min−1 to 20 A m−1 above 100 °C min−1, whereas saturation magnetization (Ms) is practically invariant at ca 175 Am2 kg−1. This dependence is explained as due to diminishing grain size with higher heating rates, which is further supported by x-ray diffraction measurements.

Energy Utilization of Algae Biomass Waste Enteromorpha Resulting in Green Tide in China: Pyrolysis Kinetic Parameters Estimation Based on Shuffled Complex Evolution

Enteromorpha is a species of algae biomass that is spread widely and has resulted in green tides in China in recent years. It was urgent to explore an appropriate method for taking advantage of the ocean waste as an energy supply in the current sustainable development. Pyrolysis, as the first step of thermochemical conversion in energy utilization, was given attention in order to study its behavior based on thermogravimetric experiments over a wide heating-rate range from 5 to 60 K/min. The whole pyrolysis process was divided into three stages: water evaporation, the main components decomposition, and carbonate decomposition. To estimate the detailed kinetic parameters (activation energy, the pre-exponential factor, and reaction order etc.), the Kissinger method was used to establish the original kinetic parameters at different stages and provide the parameter search range for the next heuristic algorithm, and then the Shuffled Complex Evolution optimization algorithm was coupled and first applied to the algae biomass pyrolysis. Eventually, the predicted results of mass loss rate based on the optimized kinetic parameters agreed well with the thermogravimetric experimental data, with the R2 value being up to 0.92 for all the heating rates.

Separating β relaxation from α relaxation in fragile metallic glasses based on ultrafast flash differential scanning calorimetry

Despite numerous studies on the glass transition and the related relaxation dynamics, the physical mechanism of activation of multiscale relaxation events under various external stimuli in amorphous materials is still unclear. In this study, by combining traditional differential scanning calorimetry (DSC) and Flash DSC with heating rates spanning over five orders of magnitude, the thermodynamic responses have been systematically studied for several fragile and strong metallic glasses (MGs). A common endothermic event, before the glass transition, is detected when the heating rate increases above a critical value for fragile MGs. This endothermic event is verified to represent the activation of secondary $\ensuremath{\beta}$ relaxation (Johari-Goldstein relaxation), which is commonly found in amorphous materials. For fragile MGs, with an increase in fragility, the critical heating rate to separate $\ensuremath{\beta}$ relaxation from $\ensuremath{\alpha}$ relaxation decreases. In contrast, the $\ensuremath{\beta}$ relaxation does not appear within the current experimental heating rate limit for strong glass systems. Finally, based on the potential energy landscape model and the flow unit model of the heterogeneous structure for MGs, a pathway is proposed for the fragile and strong MGs to understand the physical mechanism for the separation of $\ensuremath{\beta}$ relaxation from $\ensuremath{\alpha}$ relaxation via ultrafast heating. This study clearly demonstrates that the Flash DSC with a wide heating rate range is an effective tool to study the relaxation dynamics in amorphous materials.