Initial Size Research Articles

Insights into metal wear and particle breakage using Bond's abrasiveness test

Nearly 80 years ago Fred Bond proposed his abrasiveness test, also known as Allis Chalmers abrasion test, together with empirical equations that have been used to predict the wear of mill and crusher liners, besides grinding media. Although those equations have been widely criticized over the years, in particular owing to the limited accuracy of the correlations originally proposed to predict wear, it remains the most widely used test to measure ore abrasiveness in the minerals industry. The work analyzes the test, through experiments conducted under conditions that differ from those originally proposed by Bond in order to gain insights on metal wear and particle breakage. The effects of particle size, ore competence, metal hardness and time of batch operation are analyzed. It is shown that initial particle size strongly affects the rate of wear, that the intensity of fragmentation varies with hardness of the paddle and that the size distribution from the ground material offers a valid proxy for ore competence that may be useful in geometallurgical studies.

Tumor shape as a prognostic factor for the growth of intracanalicular vestibular schwannoma: a long-term observational study.

To evaluate the predictive factors of tumor growth in patients with vestibular schwannoma (VS) managed with the wait-and-scan approach. The data of 31 patients diagnosed with intracanalicular VS and followed for > 5years were retrospectively analyzed. VS was diagnosed according to MRI findings and tumor growth was monitored. Tumor growth was defined as an increase of 2mm or more in the maximal tumor diameter. The association between the initial tumor size and shape and tumor growth was assessed. Tumor growth was observed in 16 of 31 patients (51.6%) over a mean follow-up duration of 7.3years. The initial tumor size was not statistically correlated with tumor growth. However, fusiform or cylindrical tumors exhibited higher growth rates than oval or round tumors. Additionally, a significant correlation was observed between cerebellopontine angle extension and tumor shape. In this study, 51.6% of the patients with intracanalicular VS who were managed with the wait-and-scan strategy over a follow-up period of > 5years showed tumor growth. Tumor shape, especially fusiform or cylindrical shape, was found to be a significant predictor of tumor growth.

Converting Commercial Zn Foils into Single (002)‐Textured Zn with Millimeter‐Sized Grains for Highly Reversible Aqueous Zinc Batteries

AbstractRechargeable aqueous zinc batteries are promising but hindered by unfavorable dendrite growth and side reactions on zinc anodes. In this study, we demonstrate a fast melting‐solidification approach for effectively converting commercial Zn foils into single (002)‐textured Zn featuring millimeter‐sized grains. The melting process eliminates initial texture, residual stress, and grain size variations in diverse commercial Zn foils, guaranteeing the uniformity of commercial Zn foils into single (002)‐textured Zn. The single (002)‐texture ensures large‐scale epitaxial and dense Zn deposition, while the reduction in grain boundaries significantly minimizes intergranular reactions. These features enable large grain single (002)‐textured Zn shows planar and dense Zn deposition under harsh conditions (100 mA cm−2, 100 mAh cm−2), impressive reversibility in Zn||Zn symmetric cell (3280 h under 1 mA cm−2, 830 h under 10 mAh cm−2), and long cycling stability over 180 h with a high depth of discharge value of 75 %. This study successfully addresses the issue of uncontrollable texture formation in Zn foils following routine annealing treatments with temperatures below the Zn melting point. The findings of this study establish a highly efficient strategy for fabricating highly reversible single (002)‐textured Zn anodes.

Converting Commercial Zn Foils into Single (002)-Textured Zn with Millimeter-Sized Grains for Highly Reversible Aqueous Zinc Batteries.

Rechargeable aqueous zinc batteries are promising but hindered by unfavorable dendrite growth and side reactions on zinc anodes. In this study, we demonstrate a fast melting-solidification approach for effectively converting commercial Zn foils into single (002)-textured Zn featuring millimeter-sized grains. The melting process eliminates initial texture, residual stress, and grain size variations in diverse commercial Zn foils, guaranteeing the uniformity of commercial Zn foils into single (002)-textured Zn. The single (002)-texture ensures large-scale epitaxial and dense Zn deposition, while the reduction in grain boundaries significantly minimizes intergranular reactions. These features enable large grain single (002)-textured Zn shows planar and dense Zn deposition under harsh conditions (100 mA cm-2, 100 mAh cm-2), impressive reversibility in Zn||Zn symmetric cell (3280 h under 1 mA cm-2, 830 h under 10 mAh cm-2), and long cycling stability over 180 h with a high depth of discharge value of 75 %. This study successfully addresses the issue of uncontrollable texture formation in Zn foils following routine annealing treatments with temperatures below the Zn melting point. The findings of this study establish a highly efficient strategy for fabricating highly reversible single (002)-textured Zn anodes.

Simulation of pulsatory liposome working using a linear approximation for transmembrane pore dynamics

This paper presents an analytical solution of the differential equations describing the pulsatory liposome dynamics. We consider a unilamellar liposome filled with an aqueous solution of osmotic solute inserted in a hypotonic aqueous medium. Due to the osmosis process the liposome has a cyclic evolution. The lipid vesicle swells to a critical size, at which point a transbilayer pore suddenly appears. Part of the internal solution leaks through this pore. The liposome relaxes and returns to the initial size. The swelling starts again and the liposome goes through a periodical process. The swelling of the liposome is described by a differential equation. The appearance of the pore changes the evolution of the liposome. The internal solution comes out through the pore and the liposome starts its deflation (relaxation). The evolution of the pore has two phases: first, the radius of the pore increases to its maximum value, then the radius decreases until it disappears, and the liposome reaches its initial size. During each cycle, the liposome will release a quantity (a pulse) of the solution from its interior. All the processes which contribute to the liposome relaxing and its coming back to the initial size are described by three differential equations. This system of differential equations can be integrated using numerical methods. The functions – which model our biological engine in three stages, are as follows: R(t) - the liposome radius, r(t) - the pore radius, C(t) - solute concentration, Q(t) - the osmotic solute amount inside the liposome. The graphs representing these functions contain important linear portions, which suggested a solution using analytical methods. Based on some analytical methods, we solve these equations, and their explicit solutions are validated by comparing with numerical results of previous studies.

Hierarchical porous poly (L-lactic acid) fibrous vascular graft with controllable architectures and stable structure

Electrospun fibre has shown great potential in tissue engineering and regenerative medicine due to its high specific surface area and extracellular matrix-mimicking structure. However, fabricating an electrospun fibrous scaffold with controllable complex 3D macroscopic configuration remains a challenge. In the present study, a novel method was designed to transform 2D electrospun poly (L-lactic acid) (PLLA) fibrous membrane to tubular PLLA fibrous scaffolds with 3D complex but tailored configuration. The electrospun PLLA fibrous membrane was rolled around a designed mould and then treated with acetone. Treated vascular grafts’ length, diameter, and shape can be tailored by the mould parameters. Moreover, treated vascular grafts achieve favourable mechanical properties (Young’s modulus = 155 MPa, tensile stress = 8.79 MPa and radial force = 2.2 N) and the mechanical properties could be engineered on demand. In addition, treated vascular grafts kept their initial structure and size during long-term in vitro experiments once they were formed. In addition, with the acetone-induced recrystallization of PLLA, pristine solid PLLA fibres were changed to hierarchical porous PLLA fibres with ultra-high specific surface area (28.9 m2/g) and wettability (water contact angle = 101.32°), which has positive effects on cell adhesion and proliferation ability. A7r5 in vitro experiment shows that the proliferation rate of treated vascular grafts increased 153% at day 4 and 170.6% at day 7 compared with pristine vascular grafts.

Probabilistic fatigue life prediction of corroded PC beams considering spatial variability of pitting corrosion

Pitting corrosion intensifies local stress in materials, accelerating the fatigue crack initiation and propagation at the pit root. The randomly distributed corrosion pits can result in fatigue fractures in rebars and wires at non-critical sections, which further increases the fatigue failure probability of structures. However, previous studies have scarcely taken this into account. Here, we propose a novel model for fatigue life prediction of corroded post-tensioned prestressed concrete (PC) beams, considering the spatial variability of pitting corrosion. First, a Weibull distribution model of the pitting factor is developed based on the 3D laser scanning method. Then, the 3D non-Gaussian random field of the pitting factor in PC beams is generated using the inverse Nataf transformation. Next, the 3D pit-induced stress concentration is modeled using pit shape ratios. Following that, the initiation and propagation of fatigue cracks in pitting corroded wires and rebars are considered by the equivalent initial flaw size methodology. Finally, the fatigue analyses of the pitting corroded wires and rebars in all beam elements are conducted step by step until the load-bearing capacity of PC beams becomes lower than the applied load. The proposed prediction model is validated using the experimental data. The results reveal that neglecting the spatial variability of pitting corrosion overestimates the fatigue life of corroded PC beams, especially under high corrosion degrees.

CFD simulation on droplet behaviour in post-dryout region

Abstract The investigation on heat transfer in post-dryout region is of great significance to determine the maximum wall temperature when dryout occurs. In this paper, the superheated vapor is considered as Eulerian continuous phase. With DPM (Discrete Particle Method) in the ASNSYS Fluent, droplets will be tracked with Lagrangian method. Heat, momentum and mass are exchanged between the two phases inside Eulerian control volumes. The stochastic tracking is included to investigate the effect of turbulence in the continuous phase on the droplet motion. The results show that the wall temperature profile differs a lot under different initial droplet sizes. By summary of the droplet evaporation rate, it’s found that less than 2 % evaporation happens directly on the wall surface, while evaporation mostly happens in the vapor layer near the wall.

Benchmarking Active Learning Protocols for Ligand-Binding Affinity Prediction.

Active learning (AL) has become a powerful tool in computational drug discovery, enabling the identification of top binders from vast molecular libraries. To design a robust AL protocol, it is important to understand the influence of AL parameters, as well as the features of the data sets on the outcomes. We use four affinity data sets for different targets (TYK2, USP7, D2R, Mpro) to systematically evaluate the performance of machine learning models [Gaussian process (GP) model and Chemprop model], sample selection protocols, and the batch size based on metrics describing the overall predictive power of the model (R2, Spearman rank, root-mean-square error) as well as the accurate identification of top 2%/5% binders (Recall, F1 score). Both models have a comparable Recall of top binders on large data sets, but the GP model surpasses the Chemprop model when training data are sparse. A larger initial batch size, especially on diverse data sets, increased the Recall of both models as well as overall correlation metrics. However, for subsequent cycles, smaller batch sizes of 20 or 30 compounds proved to be desirable. Furthermore, adding artificial Gaussian noise to the data up to a certain threshold still allowed the model to identify clusters with top-scoring compounds. However, excessive noise (<1σ) did impact the model's predictive and exploitative capabilities.

Adsorption characteristics of Ag+ on sphalerite surface: a combined experimental and first-principle study.

The rapid development of industrial society is also accompanied by the generation of a large amount of heavy metal wastewater, which has caused serious harm to the ecological environment and human society. Natural sphalerite has an important value in the environmental field due to its own semiconducting properties. In order to effectively remove Ag+ from wastewater containing silver, this study develops a natural mineral-based Ag+ adsorbent material (sphalerite) based on elemental affinity qualities and mineralization principles. The results of batch experiments showed that the initial Ag+ concentration of 50 mg/L reduced to 0.094 mg/L with a reaction duration of 15 min, a sphalerite dose of 5 g/L, an initial particle size of -400 mesh (38 μm), a reaction temperature of 25 °C, and a pH of 5. The highest adsorption capacity is 19.77 mg/g, and the adsorption behavior is consistent with the Freundlich isotherm model and pseudo-second-order adsorption kinetics. The results of solution chemical analysis indicate that the presence of Ag+ is primarily influenced by the presence of S2-. Further analysis using SEM-EDS, FTIR, and XPS techniques reveals thatAg+ is chemically adsorb onto the mineral surface, resulting in the formation of Ag2S. DFT calculations further confirm the overlap between the Ag 4d orbitals and the S 3p orbitals on the surface of sphalerite, further confirming its chemical adsorption. Mulliken populations suggest that charge transfer occurs between Ag+ and S atoms in the sphalerite surface. This research systematically reveals the Ag+ adsorption mechanism on sphalerite surfaceand expands research ideas for treating heavy metal wastewater.

Review of the research status on the transmission and diffusion characteristics of indoor viral aerosol particles.

This study reviews the generation and diffusion characteristics of indoor viral aerosol particles, numerical simulation methods for the diffusion process of viral aerosols, and related research on the impact mechanism of different ventilation methods on the diffusion process of viral aerosols. Research has shown that the selection of initial conditions such as exhalation mode, initial airflow velocity, particle size, turbulence model, and calculation method for the generation of aerosol particles by the human body is of great significance for the numerical simulation of the diffusion process of viral aerosol particles. At the same time, on the basis of selecting appropriate ventilation methods, the reasonable setting of ventilation parameters (temperature, speed, height, etc.) can effectively suppress the spread of viral aerosols. This study can provide a theoretical basis for the study of related respiratory diseases, as well as technical and theoretical support for the selection of indoor ventilation methods to reduce the risk of human exposure caused by viral aerosols in the construction field. It also provides guidance and reference for aerosol transport and environmental protection in indoor atmospheric environments.

Dissonance In the Public Eye: Understanding the Role of Initial Affection and Deviation Size on Negative Evaluations

This study examined the impact of a public figure's deviation from societal expectations on public perceptions and economic support intentions. We hypothesized that smaller deviations would induce higher negative evaluations, and that initial personal liking for the figure would interact with deviation size to affect these evaluations. Although we did not find substantial support for our primary hypothesis, we observed an interaction effect consistent with our secondary hypothesis. Specifically, among those who initially liked the figure, minor deviations incited marginally higher negative evaluations than significant deviations. The findings suggest that initial affection introduces an additional layer of complexity in public reactions to a figure's deviations, which aligns with the Cognitive Dissonance Theory. Interestingly, participants were more likely to endorse harm for smaller deviations, implying that society tends to reprimand public figures more severely for minor deviations. There were no significant effects observed for economic support intentions. The study's implications are discussed in the context of understanding public figures' influence and societal reactions. These findings highlight the intricate dynamics of public sentiment and emphasize the need for future research to continue exploring these multifaceted relationships.

On efficient modelling of radical production in cavitation assisted reactors

Process intensification by cavitation is gaining widespread attention due to the benefits that the intense bubble collapse conditions can provide, yet, several knowledge gaps exist in the modelling of such systems. This work studies the numerical prediction of single bubble dynamics and the various approaches that can be employed to estimate the changes in the chemical composition of cavitating bubbles. Specific emphasis is placed on the prediction of the radical production rates during bubble collapse and the computational performance, with the aim of coupling the single bubble dynamics to flow models for reactor hydrodynamics. The results reveal that the choice of chemical reaction approach has virtually no effect on the bubble dynamics, whereas the predicted radical production rates can differ substantially. It is found that evaluating the radical production only on temperature peaks, an approach commonly followed in literature, may result in the most erroneous estimations (on average 12.8 times larger than those of the full kinetic model), while a simplified kinetic model yields more accurate predictions (2.3 times larger) at the expense of increased computational times. Continuous evaluation of the bubble content by assuming equilibrium when the bubble temperature is above a certain threshold (≈1500K) is shown to be capable of predicting total radical production values close to those estimated by solving the kinetics of a detailed reaction model (19.8% difference), as well as requiring only 22.2% more computational costs compared to simulations without chemical reaction modelling. Such an equilibrium approach is therefore recommended for future studies aiming to couple flow simulations with single bubble dynamics to accurately predict radical production rates in cavitation devices, involving numerous bubbles following different flow trajectories. Furthermore, an algebraic expression that successfully approximates the full kinetic simulation results is proposed as a function of the initial nucleus size and the time integral of the liquid pressure when it is under vapor pressure. Such a model can be applied in modelling efforts that do not require local instantaneous radical concentrations, and paves the way for efficient closure modelling of radical production in CFD simulations of hydrodynamic reactors.

Impact of temporal beach grain size variability on aeolian sediment transport and topographic evolution in a microtidal environment

While the impact of the spatio/temporal variability of grain size on morphological beach state is reasonably well understood, relatively little is known on its impact at a scale of days/months on aeolian sediment transport. This study focuses on five short intensive wind events during which aeolian sediment transport measurements, beach surface sampling and elevation change surveys were carried out for 1 to 3 days, over a 16-month period on a microtidal beach dominated by offshore winds. Monthly observations show a high temporal variability in beach grain size in relation to the decoupling between hydrodynamic and aeolian processes, from medium sand after a marine storm and inundation of the beach, to very coarse sand after several weeks of storm-force winds. During each wind event, topographic change on the beach ranged from zero, to 0.55 m. The time scale of coarsening depended on the initial beach grain size and could be very fast when the beach was composed of medium sand (e.g. 388 μm sand changed to coarse sand of 547 μm in 40 h). In contrast, it took one month to transition from a coarse median beach grain size of 883 μm to a very coarse one of 1323 μm. This variability in grain size results in dramatically different rates of sediment flux. For example, during average wind speeds of 10 to 14 m/s the sediment flux when the beach was composed of medium sized sand ranged between 21 and 154 kg/m/h compared to 0.4 to 50 kg/m/h when the beach was composed of coarse and very coarse sized grains. Overall, this study highlights the importance of beach grain size variability on aeolian sediment transport and shows that for similar incident wind and climatic conditions aeolian sediment transport rates vary dramatically. The study demonstrates the importance of taking care when using a constant median grain size in the calculation of long-term aeolian sand transport on beaches with heterogeneous spatial and temporal beach grain size variability.

Thermo-hydro-mechanical (THM) analysis of rock-ice avalanches: Considering the effects of particle breakage in the sliding zone

The high-speed and long-distance sliding characteristics of large-scale rock-ice avalanches usually make them a catastrophic event, which seriously threatens the safety of human beings and infrastructure. Obviously, apart from the lubrication of ice and water, the fragmentation of particles in the slip zone is also an important contribution to the hypermobility of rock-ice avalanches. Up to now, existing researches have not taken into account the impact of particle breakage on rock-ice landslides. In this paper, a thermal-hydro-mechanical (THM) model for the high-speed rock-ice avalanches is developed, which mainly considers the particle breakage due to sliding shear deformation and the ice melting caused by frictional heat. The results of the model analysis applied to the Chamoli avalanche indicate that particle fragmentation has a significant effect on landslide sliding. When the particle breakage is considered, the simulated velocity and displacement of landslide are closer to the existing research results. Both thermal pressurization and particle crushing are two important mechanisms that lead to a high-speed sliding of rock-ice landslide, and these two mechanisms affect each other. It is demonstrated from a set of sensitivity analyses that the initial grain size distribution, fractal dimension and the thickness of the slide mass have clear impacts on the evolution of the granular crushing index, which thus affects the characteristics of the landslide eventually. In particular, the sensitivity analysis of the slide thickness once again demonstrates the importance of considering particle fragmentation in the analysis of landslide sliding.

Inter-Comparison of Lightning Measurements in Quasi-Linear Convective Systems

Data from four lightning networks collected during three quasi-linear convective systems (QLCS) are used to understand the differences in detection for optimizing their combined use. Additionally, using unique aspects from each network provides a more complete picture of lightning in a thunderstorm. The four lightning networks examined include a Lightning Mapping Array (LMA), the Earth Networks Total Lightning Network (ENTLN), the Geostationary Lightning Mapper (GLM), and the National Lightning Detection Network (NLDN). The data from each network are inter-matched and locations where each network uniquely detected a flash versus all are analyzed in reference to three QLCSs, including two QLCSs that occurred in the Southeast (22 March 2022 and 30 March 2022) during the Propagation, Evolution, and Rotation in Linear Systems (PERiLS) field campaign, and one case from Oklahoma (26 February 2023). Unique aspects of the lightning provided by each network are examined, including flash initiation altitude, size, type, and energy. Lightning flash trends and characteristics for each QLCS are similar between networks in general, but deviate in certain conditions and locations. Times of decreased matching between networks were associated with localized increases in lightning rates, smaller flash sizes, and lower-energy flashes. The differences in each network’s performance across the QLCSs demonstrates the importance of understanding the limitations in each and the advantage of using multiple networks.

Natural history and growth prediction model of pancreatic serous cystic neoplasms

ObjectiveSerous cystic neoplasms (SCN) are benign pancreatic cystic neoplasms that may require resection based on local complications and rate of growth. We aimed to develop a predictive model for the growth curve of SCNs to aid in the clinical decision making of determining need for surgical resection. MethodsUtilizing a prospectively maintained pancreatic cyst database from a single institution, patients with SCNs were identified. Diagnosis confirmation included imaging, cyst aspiration, pathology, or expert opinion. Cyst size diameter was measured by radiology or surgery. Patients with interval imaging ≥3 months from diagnosis were included. Flexible restricted cubic splines were utilized for modeling of non-linearities in time and previous measurements. Model fitting and analysis were performed using R (V3.50, Vienna, Austria) with the rms package. ResultsAmong 203 eligible patients from 1998 to 2021, the mean initial cyst size was 31 mm (range 5–160 mm), with a mean follow-up of 72 months (range 3–266 months). The model effectively captured the non-linear relationship between cyst size and time, with both time and previous cyst size (not initial cyst size) significantly predicting current cyst growth (p < 0.01). The root mean square error for overall prediction was 10.74. Validation through bootstrapping demonstrated consistent performance, particularly for shorter follow-up intervals. ConclusionSCNs typically have a similar growth rate regardless of initial size. An accurate predictive model can be used to identify rapidly growing outliers that may warrant surgical intervention, and this free model (https://riskcalc.org/SerousCystadenomaSize/) can be incorporated in the electronic medical record.

Evaluating Target Expansion for Eye Pointing Tasks

Abstract The idea of target expansion was proposed two decades ago for manual target acquisition, but it is not feasible to implement this idea in traditional user interfaces as the interactive system cannot know exactly which target is the desired one and should be expanded among several candidates. With the increasing maturity of eye tracking technology, gaze input has moved from an academically promising technique to an input method with built-in support in Windows 10; and target expansion has already become very feasible in the context of gaze input, as the user’s eye gaze is inherently an indicator of the desired target due to the natural eye-hand coordination in everyday tasks. However, a comprehensive evaluation is still lacking. In this study, two experiments were conducted, each with a different group of subjects, to investigate the effects of target expansion under different expansion feedback styles (visible vs. invisible), expansion factors, as well as different target appearances (i.e., circular vs. rectangular). The experimental results indicated that (1) the index of difficulty in eye pointing tasks (IDeye) does not depend on the initial size of the target, but on its final size, and that the corresponding human performance can be accurately predicted using the IDeye model instead of Fitts’ law; and that (2) the visible expansion style could disrupt the user’s fixations, making the measured human performance less efficient to some extent, but overall the theoretical predictions using the IDeye model were almost the same as the baselines. Following the experimental results, this study also provided some practical suggestions for UI design.

The mismatch between swimming speeds and flow regimes when optimising exercise regimes to improve Chinook salmon, Oncorhynchus tshawytscha, performance

Exercise regimes provide a promising opportunity to enhance production performance during hatchery rearing, but exercise-enhanced traits are presently poorly understood in Chinook salmon. In addition, spinal health can be a concern in some farms in New Zealand and unfavourable correlations between higher condition factor and spinal curvature have been detected. Exercise regimes, in other salmonids, have improved bone mineralisation and lowered condition factor. Therefore, we hypothesise that sustained swimming could be used as a tool to improve spinal health. Here we tested the influence of low (0.3 bl s−1) and moderate (0.8 bl s−1) flow regimes on post-smolt (initial size: wet weight = 82.9 ± 0.3 g, fork length = 174.6 ± 0.2 mm) Chinook salmon feed efficiency and growth performance, as well as spinal health. We first measured the actual swimming speeds of Chinook salmon under low and moderate flow regimes to determine differences in exercise levels. Swimming speeds were not different between the flow regimes and were much higher than the set flow, because the Chinook salmon were advancing around the tank, swimming faster than the set flow at their own chosen swimming speed. Moderate flow regimes improved feed efficiency but did not influence other feed and growth metrics or spinal curvature and vertebral anomalies prevalence or severity. Production performance significantly differed between individuals with normal spinal health and those that developed spinal anomalies (vertebral compression, −fusion, and/or -vertical shift) or spinal curvature (lordosis, kyphosis, and/or scoliosis). Chinook salmon that developed spinal anomalies were smaller, grew slower, and exhibited poorer feed efficiency, whereas individuals that developed spinal curvature were significantly heavier, longer, and had higher condition factor. The probability of individuals developing spinal curvature increased with higher condition factor. These results provide critical information for industry to consider in their selective breeding objectives to curb the prevalence and severity of spinal curvature incidences.

Size-dependent thermal oxidation kinetics in Sm2(Co, Fe, Cu, Zr)17 alloy powder

This study investigates the interrelationship between the oxide growth kinetics and the microstructural changes induced by dry, thermal oxidation in Sm2(Co, Fe, Cu, Zr)17 alloy powder (of varying particle sizes and compositions). Whereas, model-free iso-conversional methods are used to determine the kinetic-triplets during the non-isothermal oxidation stage, power-law dependent kinetic model is considered during the entire oxidation process to calculate the reaction order, rate constant and the apparent-activation energy. A distinctly different oxide growth kinetics, with strong dependency on the initial particle size(s) and the alloy composition-induced oxide microstructure is seen here.