Development of ductile iron alloy for ADI production using heated air in austempering

Abstract

Ductile iron is typically used in as-cast conditions. However, a typical heat treatment applied to ductile iron is austempering, which allows for increased tensile strength with good levels of elongation and toughness. The traditional means of austempering involves molten salt baths, but these baths have environmental and operational restrictions. Laboratory-level studies have found the feasibility of using heated air for cooling and holding during austempering. Due to the lower cooling severity of heated air, it is necessary to increase the austemperability of ductile iron. Elements that contribute to austemperability are manganese, copper, molybdenum, and nickel. This study used numerical, thermodynamics, and kinetics simulation to develop a suitable ductile iron alloy for obtaining ADI in a standard ASTM test specimen using heated air for cooling. According to the numerical simulation results, the average cooling rate between 900°C and 500°C in the critical region for air velocities of 5 m/s and 10 m/s at a temperature of 280°C ranged from 75°C/min to 82°C/min. Through thermodynamic and kinetic simulation, nickel has the most significant capacity to alter the austemperability of ductile iron. Based on these results, six ductile iron alloys with nickel contents ranging from 0.2 to 2% were developed. The experimental cooling rate is approximately 70°C/min, with the 3.41C, 2.72Si, 1.01Cu, 0.31Mn, 0.18Mo, and 1.13Ni alloy suitable for obtaining ADI.

Keywords:
ADI; austempering; austempered ductile iron; spheroidal graphite cast iron

1. Introduction

The microstructure and mechanical properties of ductile iron are altered following an austempering heat treatment cycle, resulting in the material known as Austempered Ductile Iron (ADI). ADI saw its initial widespread commercial applications in the United States, Europe, and China during the 1970s, particularly in the manufacturing of a diverse range of components utilized in truck suspensions, as well as in automotive gears and compressor crankshafts (Keough & Hayrynen, 2000). ADI is a versatile material due to its combination of mechanical properties and the production advantages offered by casting. Consequently, it finds applications in agricultural and mining equipment, machinery, and tool sectors, as well as in the automotive, road, and railway industries. The limitation of ADI lies in its application to components exposed to elevated temperatures (Gundlach et al., 1992; Kovacs, 2013).

The heat treatment cycle for obtaining ADI can be divided into three stages. The first stage is heating and holding at the austenitization temperature, with the primary objective of saturating the austenitic matrix with carbon in solid solution. The second stage is cooling to the austempering plateau. The cooling rate must be sufficiently high to prevent reconstructive transformations (formation of ferrite or pearlite). The austempering stage, during which the transformation of austenite into ausferrite occurs. Changes in austenitization temperature, as well as in the austempering temperature and time, lead to significant alterations in the mechanical properties of ADI (Putatunda, 2001; Zhang et al., 2014; Alves et al., 2018).

The widely employed medium in austempering treatments is molten salt baths, typically composed of a mixture of potassium nitrate, sodium nitrate, and sodium nitrite (Keough, 2013). Molten salt baths require careful operational considerations and face environmental constraints primarily due to contamination with additives that prevent decarburization. Furnaces using molten salt baths experience thermal losses, necessitating a significant energy input. Another inconvenience that diminishes the competitiveness of ADI is that components treated in salt baths must undergo a washing process before painting.

Despite the higher cost, low melting-point metals and alloys can be employed as an austempering medium. Studies have yielded favorable results on a laboratory scale using zinc-based alloys (Souza et al., 2018; Pereira et al., 2019). Researchers have also explored using inert gas jets or cold air flow on a laboratory scale to facilitate cooling from the austenitization temperature to the austempering temperature (Meier et al., 2013; Olawale et al., 2017). Utilizing heated air as a medium for cooling and maintaining the austempering temperature was a successful experimental study proposal (Pereira et al., 2020). This technique eliminates the need for the use of salt bath furnaces.

Compared to salt baths or metallic baths, the milder cooling severity of air necessitates additions of alloying elements that enhance hardenability or austemperability. In cast irons with free graphite, elements, such as Ni, Cu, Mn, and Mo are employed in conjunction with Si, enabling improved austemperability without causing defects (Akinribide et al., 2022; Keleş, Cengız, and Yildirim, 2023). In this study, an alloy is developed to obtain ADI in a standard ASTM CPy 13 mm specimen, with cooling facilitated through a heated airflow at a temperature of 280°C and a velocity of 10 m/s.

2. Materials and methods

In this section, the devices, equipment, materials, and procedures adopted in conducting this study will be presented. Figure 1 shows the flowchart of the experimental procedure.

Figure 1
Flow chart of the experimental method.

2.1 Effect of Ni, Cu, Mn, and Mo on austemperability

The effect on the Time-Temperature-Transformation (TTT) diagram of Ni, Cu, Mn, and Mo in a predefined, alloy-rich initial composition was measured using the MUCG83 software (Mathew Peet & H.K.D.H. Bhadeshia, no date). The choice of elements to be analyzed in this study was delimited based on what is recommended in ASTM 897. The reactions and transformations of interest during the cooling and austempering stages occur in the metallic matrix of ductile iron. After an adequate austenitization time, the metallic matrix reaches equilibrium with the graphite nodules, signifying that the matrix is saturated with carbon in a solid solution.

The matrix composition was considered 0.8% C, 2.5% Si, 1% Ni, 1% Cu, 0.3% Mn, 0.2% Mo, and 0.1% Cr. The carbon content in the matrix was estimated using the commonly used expression Cγ° = (Tγ/420) - 0.17 (%Si) -0.9, which was constructed in the past based on the Fe-Si-C diagram. For the elements Ni, Cu, Mn, and Mo, seven simulations were conducted with individual variations in the content of each analyzed element, comprising five points distributed within the range recommended by ASTM 897 and two points above the maximum content recommended by the standard, as shown in Table 1. The construction of the TTT diagrams followed the guidelines provided by the software developer.

Table 1
Alloying element contents used for TT T diagram simulations.

Element	P1	P2	P3	P4	P5	P6	P7
Ni (%)	0.00	0.50	1.00	1.50	2.00	2.50	3.00
Cu (%)	0.00	0.20	0.40	0.60	0.80	1.00	1.20
Mn (%)	0.00	0.09	0.18	0.26	0.35	0.44	0.52
Mo (%)	0.00	0.07	0.15	0.22	0.30	0.37	0.45

2.2 Ductile iron alloys

The charge calculation for alloy preparation was based on the chemical analysis provided by suppliers and laboratory analysis conducted through optical emission spectroscopy. Table 2 presents the quantities of each component used to prepare the six ductile iron alloys.

Table 2
Charge used for the elaboration of the alloys.

Charge	Alloy I	Alloy II	Alloy III	Alloy IV	Alloy V	Alloy VI
SiC (g)	6	6	6	6	6	6
Steel 1013 (g)	4000	4000	4000	4000	4000	4000
Cast Iron (g)	3600	3600	3600	3600	3600	3600
Pig Iron (g)	1000	1000	1000	1000	1000	1000
Graphite (g)	162	164	167	168	170	170
Fe-Si (g)	70	70	72	72	74	75
Fe-Mn (g)	4	4	5	5	5	5
Fe-Mo (g)	20	20	20	20	20	20
Ni (g)	0	16	54	91	128	170
Cu (g)	44	44	44	44	44	45

The production of ductile iron was conducted in a laboratory environment. Melting was performed using an Inductotherm medium-frequency induction furnace with 9.5 kg of cast iron capacity. The metal temperature was raised to 1510 (±10) °C and then poured into a sandwich-type treatment ladle containing nodularizing and inoculating alloys. A composition of 100g Fe46S-i8Mg and 80g Fe-75Si-0.5Al was employed. Upon reaching the temperature of 1350°C, a sand-cast sample was extracted using an ITALSAMP F sampler from Italterm for chemical analysis using a Bruker Q2 ION optical emission spectrometer. The metal was subsequently poured into ASTM standard molds for 13 mm CPy specimens made from silica sand bound with 4% sodium silicate.

2.3 Simulation of the cooling severity for CPy

The simulation of cooling severity was performed using the Flow module of the SolidWorks software under transient (dynamic) conditions. The simulation considered heat conduction in the solid (test specimen) and the effects of radiated heat without accounting for the roughness of the CPy or the existence of internal defects. The model boundaries were defined by a duct measuring 200 mm on each side and 1000 mm in length, with 2 mm steel walls considered ideal walls and at the same temperature as the airflow. The fluid used in the simulations was dry air under a pressure of 101325 Pa, with a temperature of 280°C, and velocities of 5 and 10 m/s under both laminar and turbulent flow conditions, with 2% turbulence level and entry into the duct in a developed form.

The simulations assessed the effect of the CPy orientation in the duct, with the longer side facing the air shockwave, as shown in Figure 2a, and the opposite, by rotating the CPy by 180°, as depicted in Figure 2b. The objective was to determine which configuration resulted in a higher cooling rate at the point of lower severity. Among the numerous results produced by the numerical simulation, attention was solely focused on the maximum temperature in the solid. This value represents the most critical region or the point with the lowest cooling rate.

Figure 2
View inside the duct showing airflow and interaction with the CPy. a) Simulated position +Z and b) Simulated position -Z. c) Cutaway view of the CPy in the cooling duct, allowing observation of temperature gradients in the solid.

2.4 Heat treatment and microstructural characterization

A detailed description of the apparatus is beyond the scope of this study and is still under refinement; however, a schematic diagram is presented in Figure 3. A square-profile duct was used, measuring 200 mm on each side and 1000 mm in length. A fan with twelve straight blades, each measuring 40 mm in height and 210 mm in length, was employed to generate the airflow. These blades were distributed on a base with a diameter of 540 mm. The fan was powered by a 3 HP three-phase electric motor operating at 3460 rpm. Airspeed in the fan outlet duct was measured using a Classic Pitot tube, and the average airspeed in the square duct was calculated based on the fan flow rate. Air circulates within the apparatus, heated to the specified temperature by resistances with a total power of 7500 W. Temperature control was automated (PID), regulating the activation of resistances or allowing the entry of ambient temperature air.

Figure 3
Schematic representation of the cooling and austempering device.

The CPy specimens were instrumented with type K thermocouples connected to a data acquisition system with a sampling rate of 2 Hz. The thermocouples were positioned in the central and thickest region of the CPy, approximately 30 mm from the surface. According to simulation data, this is the hot region of the CPy where cooling occurs more slowly. The treatment cycle commenced with the CP being austenitized in a muffle furnace at 900°C for 120 minutes. After austenitization, the instrumented CPy was swiftly transferred to the cooling duct with airflow at a temperature of 280°C (minimum measured at 275°C and maximum at 310°C). Upon reaching a temperature of 300°C, the CPy was removed from the cooling duct and placed in a muffle furnace at 340°C, thereby undergoing a two-step austempering treatment.

For the microstructure analysis, samples were extracted from the functional region of the CPy specimens, both in the as-cast condition and after heat treatment. In the treated CPy, the analyzed sample was taken from the upper central region of the useful area, which is the region with the lowest cooling rate in this part. The samples were ground and polished on a felt disc with 1.0 μm alumina and 0.25 μm diamond paste. Microstructures of the samples were revealed through etching with 2% Nital. Image capture was performed using an Olympus BX60M metallographic microscope with an IDS camera and Buehler OmniMet software.

In the as-cast samples, nodule counting and nodularity calculation were carried out through a semi-automated routine in the image analysis software. Ten images were analyzed for each sample, magnified at 100X, and unetched. The routine considers a nodule as non-spherical when its sphericity is below 0.65, which is the default value in the image analysis software and has not been altered. The routine identifies, but ignores particles with an average diameter below 10 μm.

A mechanical characterization was performed through hardness measurements. Samples cut from the functional region of the CPy had their hardness measured using the Brinell method with a Mitutoyo hardness tester. A hardened steel ball with a diameter of 2.5 mm and an applied load of 187 Kgf were used, following ASTME10-17 guidelines. For each evaluated condition, eight measurements were taken, and the results are presented as the mean and respective standard deviation.

3. Results

3.1 Effect of Ni, Cu, Mn, and Mo on austemperability

Shifting the curves of diffusional transformations (formation of ferrite and pearlite) to the right means, increases the austemperability of ductile iron. From the simulated TTT diagrams, the leftmost point corresponding to the onset of pearlite formation was identified. The effect of each element on the TTT diagram and indirectly on austemperability can then be estimated through a mathematical expression.

Figure 4 shows that the simulated TTT diagrams in the MUCG83 software can be observed. As expected, all elements shifted the pearlite formation curves to the right. When examining the TTT curves for the variation in nickel content, it is noted that the curves are significantly shifted downward in addition to rightward shifting. This occurs because nickel is a potent stabilizer of austenite.

Figure 4
Simulated TTT diagrams in MUCG83 with curves for the formation of ferrite and pearlite (between 500 and 700°C), curves for the formation of ausferrite (between 200 and 400°C), and the temperature of martensitic transformation (between 100 and 200°C).

Among the analyzed elements, nickel has the greatest ability to shift the curves of reconstructive transformations to the right, resulting in increased austemperability in ductile iron. The longer time for the onset of pearlite transformation allows for the use of higher Ni contents in nodular iron. This effect can be observed prominently in Figure 4 Figure 5. When the maximum Ni content proposed in the study is added, the start of pearlite formation changes from 80 to approximately 5800 seconds.

Figure 5
Influence of the content of Ni, Cu, Mn, and Mo on the time at which reconstructive transformations begin.

The results from simulated Time-Temperature-Transformation (TTT) diagrams were used to create equations that show how the amount of Ni, Cu, Mn, and Mo affects the onset of pearlite formation.

For nickel, R² of 0.99:

(1) $t\left(s\right)=73.4\times {\text{e}}^{\frac{\%Ni}{0.69}}$

For copper, R² of 0.98:

(2) $t\left(s\right)=123.9+191\times \%Cu$

For manganese, R² of 0.99:

(3) $t\left(s\right)=123.6\times {\text{e}}^{\frac{\%Mn}{0.32}}$

For molybdenum, R² of 0.99:

(4) $t\left(s\right)=268.7+242\times \%Mo$

3.2 Ductile iron alloys

The chemical composition of the sand-cast samples is presented in Table 3, with the results representing the average of four analyses. Only the elements most relevant to the study objective are shown. The residual Mg contents are above the targeted levels, a result of higher-than-expected efficiency in the nodularization treatment. Working with a high Mg content leads to wastage, as it does not translate into improved nodularization or nodule count. On the contrary, it can lead to the formation of deleterious phases in ductile iron. Adequate values are between 0.03 and 0.05%. The carbon equivalent is close to 4.2%, which is suitable for ductile iron production (Walton, 1958).

Table 3
Chemical composition of the six different produced alloys. Percentage by mass.

Alloy	C [%]	Si [%]	Mn [%]	Cr [%]	Mo [%]	Ni [%]	Cu [%]	Mg [%]	Fe [%]
I	3.293	2.729	0.284	0.106	0.206	0.224	1.021	0.084	bal.
II	3.460	2.721	0.284	0.099	0.202	0.378	1.029	0.133	bal.
III	3.264	2.649	0.283	0.102	0.198	0.754	1.027	0.071	bal.
IV	3.407	2.725	0.310	0.099	0.185	1.128	1.013	0.112	bal.
V	3.371	2.781	0.347	0.105	0.185	1.428	1.041	0.090	bal.
VI	3.174	2.619	0.274	0.098	0.197	1.962	1.011	0.077	bal.

Results of the nodule counts, nodularity, hardness, and microstructure in the CPy of the different alloys are presented in Table 4. It is observed that the addition of nickel resulted in a trend of increased hardness in the as-cast nodular iron. In alloy VI, martensite formation in the mold occurred, which is irrelevant for ADI production because the material will be austenitized during the austempering cycle. For casting, the formation of martensite could become a problem in the stages of channel removal, especially during deburring.

Table 4
Nodularity, number of nodules, Brinell hardness, and predominant microstructure. The standard deviation is shown in parentheses.

Alloy	Nodule count	Nodularity (%)	Hardness (HB)	Microstructure
I	187.1 (22.6)	84.7 (3.9)	291 (9.4)	Pearlite
II	195.9 (30.1)	92.6 (3.7)	299 (8.2)	Pearlite
III	193.0 (22.6)	88.8 (2.7)	306 (7.4)	Pearlite
IV	211.9 (30.1)	88.2 (4.3)	302 (4.7)	Pearlite
V	231.0 (36.6)	83.4 (5.2)	322 (8.3)	Pearlite
VI	223.0 (36.2)	92.2 (2.8)	356 (3.6)	Martensite

Nickel showed no effect on nodularity. Regarding the nodule count per area, there was a tendency for an increase in the average count, similar to the findings of Ramírez (2019), who observed a significant increase in thin and thick-walled geometries.

3.3 Simulation of CPy Cooling Severity

The cooling curves in the maximum temperature region of the CPy, obtained through numerical simulation, are presented in Figure 6. For all air velocities, the direction labeled +Z exhibited higher cooling effectiveness in the region of the highest temperature of the specimen, reaching the designated temperature of 550°C in less time. As the airspeed decreases, the difference decreases between the +Z and -Z directions, allowing the highest temperature region to reach the same 550°C.

Figure 6
Results of numerical simulations with cooling curves in the region of the highest temperature of the CPy at different air speeds and directions.

The observed behavior in the cooling curves of the hot region of the CPy is also confirmed when analyzing the average heat flux (W/m²) on the specimen's surface over a 300-second interval. At a speed of 5 m/s, the flux in the +Z direction is 393 W/m², while in the -Z direction, it is 350 W/m². This pattern persists at a speed of 10 m/s, with 547 and 491 W/m² values, respectively.

3.4 Heat treatment and microstructural characterization

From the temperature data recorded during the treatment, the most important values are those obtained during the cooling stage, with the most relevant range being between 900ºC and 500ºC. The critical temperature for forming perlite is between 700ºC and 500ºC (Saal et al., 2016). Below this temperature, reconstructive transformations no longer occur in considerable time due to the presence of alloying elements, particularly silicon and carbon, in solid solutions. Figure 7 presents the cooling curves of the CPys for alloys VI, V, IV, and III. Alloys II and I were not treated because the cooling curve of alloy III showed the formation of perlite, an exothermic reaction, indicating that the alloy does not have adequate austemperability for the cooling conditions.

Figure 7
Experimental cooling curves of alloys VI, V, IV, and III.

The microstructure analysis confirms the observations made in the cooling curves, indicating the formation of ausferrite in alloys VI and V and a large amount of perlite in alloy III. On the other hand, by observing Figure 8, no difference was found in the microstructure of alloys VI and V compared to alloy IV. This suggests that the small formation of ferrite and perlite may have occurred only in the thicker region of the CPy and not in its functional region.

Figure 8
Microstructure of alloys VI, V, IV, and III after the thermal treatment cycle. Alloys VI, V, and IV exhibit only ausferrite. In alloy III, ausferrite and the formation of fine perlite (darker region) can be observed.

Despite the difference in microstructure, there was no significant change in Brinell hardness (HB) among the analyzed alloys after the austempering treatment, with values of 324 (1.4), 323 (1.5), 325 (2.7), and 330 (6.1) respectively for alloys VI, V, IV, and III, with the standard deviation in parentheses.

4. Discussion

In the simulated diagram with the lowest alloy addition (Ni = 0%), the ferrite/perlite formation onset occurs approximately 11 seconds at an isothermal temperature of 650°C. According to an experimental diagram published by Olejarczyk-Wozeńska et al. (2012), in ductile iron containing 3.6% C, 2.72% Si, and 0.27% Mn, without additions of Cu, Ni, and Mo, it takes 10 seconds for approximately 5% transformation of austenite into perlite. This transformation occurs at a temperature of 650°C. Furthermore, according to the author's results, less than 2 minutes are needed for a complete transformation at the same temperature. In a CCT diagram, with ductile iron containing 3.2–3.8% C, 2.5–3.0% Si, and 2.5–3.0% Mn without additions of Cu, Ni, and Mo, and austenitized at 900°C for only 5 minutes, with cooling rates on the order of 1.39°C/s, perlite formation occurs. A 4-minute incubation period is required (Zhou et al., 2001).

It can be observed in the diagrams in Figure 3 that the onset of ausferrite formation, in the range between 300 and 400°C, occurs between 10 and 100 seconds, depending on the amount of Ni, Cu, Mn, and Mo. In ductile iron with a composition of 3.2% C, 2.4% Si, 0.62% Cu, 0.59% Ni, 0.21% Mn, and 0.13% Mo, austenitized at 950°C for 45 minutes, the kinetics of ausferrite formation in the range of 250 to 500°C was determined using dilatometry tests (Kutsov et al., 1999). In the austempering range of 340 to 380°C, the incubation time for the onset of ausferrite formation is approximately 2 minutes, concluding in about 50 minutes.

Manganese firmly shifts the onset curve of perlite formation to the right, as observed in Figures 3 4 and Equation 3. It is also a cost-effective element compared to others and is often present in scrap steels used by foundries. On the other hand, this element is a strong carbide former and alters the processing window of the austempering treatment (Thomson, 2000). Like Mo, Mn also segregates to the liquid during solidification. The maximum recommended amount of Mn is 0.35%, but it can increase to 0.65% in specific cases. Manganese reduces the processing window (Owhadi et al., 1997). Combined with segregation to the liquid, it causes the processing window in the intercellular regions, where it segregates, to differ from other regions, resulting in the decomposition of high-carbon austenite into ferrite and carbides.

Within the scope of this study, it was observed that nickel is the element with the greatest capacity to alter the austemperability of ductile iron, although this is largely due to the higher levels that can be added without causing defects, mainly related to the formation of carbides as occurs with Mn and Mo. However, nickel has a negative effect during austempering. Nickel reduces the transformation kinetics in the austempering step, likely because the element is a potent austenite stabilizer, while in ductile iron without nickel additions, transformations during austempering occur in 3200 seconds; with the addition of 1% nickel, this time increases to 5200 seconds (Górny, Tyrała, and Sikora, 2018).

Figure 6 shows that in the +Z direction at 5 m/s, the cooling curve is very similar to the -Z direction at 10 m/s. In other words, to achieve the same cooling rate in the less favorable direction, it is necessary to increase the airspeed by 100%. In a study involving the numerical simulation of cooling in the heat treatment of quenching (Bineli, 2009), it was possible to optimize cooling rates and temperature homogeneity in the solid through stirrers that altered the fluid flow and its interaction with the workpiece. The author also concluded that using Computational Fluid Dynamics (CFD) software can improve the treated material and reduce distortions in the workpiece during heat treatment. It is appropriate to estimate that when cooling complex parts with air or gases, the CFD software simulation step will be a fundamental part of the heat treatment design. Also, in Figure 6, it is observed that the difference between the simulated cooling curves in the range above 700°C is very similar. This is because, at high temperatures, thermal losses are dominated by radiation. According to Kreith et al. (2015), the amount of energy leaving a body via radiation depends on its temperature, which is elevated to the fourth power.

Under the treatment conditions, the average cooling rate between 900°C and 500°C was approximately 70°C per minute, slightly differing from what was found in numerical simulations, which showed rates of 75 and 82 ºC/min, respectively, for speeds of 5 and 10 m/s. This difference is due to some factors that were simplified during the simulation. The surface roughness of the test specimens was not considered, and the increase in the temperature of the duct walls was not taken into account. Additionally, precise control of the air temperature inside the duct was not achieved, with the temperature ranging between 275°C and 310°C instead of staying at a constant 280°C, as in the simulation. Other authors have also observed minor differences between simulated and experimental results, but the use of CFD simulations applied to heat treatments has been quite common (Banka et al., 2007; Yang, de Jong, & Reuter, 2007; Bineli, 2009; Ko et al., 2013; Bohlooli Arkhazloo et al., 2021; Ghyadh et al., 2021).

On the one hand, operational risks associated with furnaces with molten salt baths and environmental risks are eliminated; on the other hand, the production cost of nodular iron increases due to the need to add elements to improve austemperability. An inconvenience of using atmospheric air was forming an oxide layer on the surface of the CPy, approximately 82 to 93 µm thick. This oxidation issue can be easily overcome by using an inert gas in the device, a solution already adopted in laboratory setups (Meier et al., 2013; Saal et al., 2016).

5. Conclusions

The simulations allowed for a reduction in the number of alloys produced and defined the most favorable position to increase the cooling rate. Among the elements Cu, Mo, Mn, and Ni, nickel has the most significant capacity to increase the austemperability of ductile iron. While the element did not influence the degree of nodularization, its increase from 0.2% to 2% resulted in a 19% increase in nodule count.

Austempering using heated air for cooling has proven viable in a standard 13mm test specimen (CPy). Starting with a base alloy containing an average of 3.4% C, 2.7% Si, 1.0% Cu, 0.3% Mn, 0.2% Mo, 0.1% Cr, and a nickel content of 1.13%, it is suitable for obtaining ADI with an ausferrite microstructure free of perlite.

Acknowledgments

This study was financed by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES, Brasil), the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq, Brasil).

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Publication Dates

• Publication in this collection
  24 Feb 2025
• Date of issue
  Jan-Mar 2025

History

• Received
  08 Jan 2023
• Accepted
  04 Mar 2024