Kinetics of solid state phase transformations: Measurement and modelling of some basic issues

Raju, S.; Mohandas, E.

doi:10.1007/s12039-010-0010-2

Cited by 11 publications

(16 citation statements)

References 23 publications

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“…Thus, the first detectable phase formation occurs not at the thermodynamic equilibrium temperature T o , but at a slightly higher temperature, that is decided by τ and β . In the real case, T ( β ) could be nonlinear, as τ ( T ) is itself is a function of T and β . However for the present study, the linear approximation is found to be applicable, as it is supported by the experimental data (see Figure ).…”

Section: Discussionsupporting

confidence: 53%

“…In the real case, T(b) could be nonlinear, as t(T) is itself is a function of T and b. [102] However for the present study, the linear approximation is found to be applicable, as it is supported by the experimental data (see Figure 5). The incubation time is a measure of the compromise between thermodynamic driving force and kinetic mobility factor.…”

Section: Heating Rate Sensitivity Of Recrystallization Temperaturesupporting

confidence: 51%

“…

T (β) = T_{normalo} + τ β

where, T ( β )/ K is the thermal arrest temperature measured for the chosen heating rate β /Ks −1 , and T o is the hypothetical value for the zero heating rate. For typical diffusional transformations, it is well‐known τ is related to the incubation time . The physical basis of Equation stems from the fact that for any diffusion mediated phase change, a threshold minimum time τ ( T ) needs to be spent at each temperature T ≥ T o , in order that the formation of new phase takes place by overcoming the free energy barrier.…”

Section: Discussionmentioning

confidence: 99%

“…For typical diffusional transformations, it is well-known t is related to the incubation time. [101,102] The physical basis of Equation 5…”

Section: Heating Rate Sensitivity Of Recrystallization Temperaturementioning

confidence: 99%

See 3 more Smart Citations

A Calorimetric Study of Recovery and Recrystallization in Fe–14.4 Cr–15.4 Ni–2.4 Mo–2.36 Mn–0.25 Ti–0.04 C–0.05 P (mass %) Austenitic Stainless Steel

Tripathy

Raju

Kumar

et al. 2013

steel research int.

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The stored energy release and the kinetics of recovery and recrystallization processes in 70 and 85% coldworked nuclear grade austenitic stainless steel have been investigated by dynamic calorimetry, the results of which are supplemented by optical microscopy and microhardness measurements. Distinct thermal arrests arising from recovery and recrystallization events that occur upon slow heating are around 815 and 1070 K, respectively. The peak recovery and recrystallization temperatures are found to be sensitive to prior coldwork and heating rate. Faster rates of heating pushed the recovery stage to higher temperatures overlapping with the domain of recrystallization, which resulted in a decreased dissipation of stored energy due to recovery. As a result, faster heating rates, served to accelerate the kinetics of recrystallization owing to higher driving force. It is also found that the dissolution of fine TiC particles lead to secondary recrystallization at higher temperatures. Modeling of lattice softening kinetics yielded values of effective activation energies for recovery and recrystallization processes in the range, 198 and 336 kJ mol−1, respectively.

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Section: Discussionsupporting

confidence: 53%

Section: Heating Rate Sensitivity Of Recrystallization Temperaturesupporting

confidence: 51%

“…

T (β) = T_{normalo} + τ β

Section: Discussionmentioning

confidence: 99%

“…For typical diffusional transformations, it is well-known t is related to the incubation time. [101,102] The physical basis of Equation 5…”

Section: Heating Rate Sensitivity Of Recrystallization Temperaturementioning

confidence: 99%

See 2 more Smart Citations

A Calorimetric Study of Recovery and Recrystallization in Fe–14.4 Cr–15.4 Ni–2.4 Mo–2.36 Mn–0.25 Ti–0.04 C–0.05 P (mass %) Austenitic Stainless Steel

Tripathy

Raju

Kumar

et al. 2013

steel research int.

View full text Add to dashboard Cite

show abstract

“…As a result, new strongly magnetic minerals are created during heatingcooling experiments and mono-phase reactions and transitions are modified (Hanesch et al, 2006). Kinetics of these nonisothermal solid phase transformations strongly depend on the heating and cooling rates applied (Raju and Mohandas, 2010).…”

Section: Discussion Thermomagnetic Analysis Of Magnetic Susceptibilitmentioning

confidence: 99%

Thermomagnetic Behavior of Magnetic Susceptibility—Heating Rate and Sample Size Effects

Jordanova

2016

Front. Earth Sci.

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Thermomagnetic analysis of magnetic susceptibility k(T) was carried out for a number of natural powder materials from soils, baked clay and anthropogenic dust samples using fast (11 • C/min) and slow (6.5 • C/min) heating rates available in the furnace of Kappabridge KLY2 (Agico). Based on the additional data for mineralogy, grain size and magnetic properties of the studied samples, behavior of k(T) cycles and the observed differences in the curves for fast and slow heating rate are interpreted in terms of mineralogical transformations and Curie temperatures. The effect of different sample size is also explored, using large volume and small volume of powder material. It is found that soil samples show enhanced information on mineralogical transformations and appearance of new strongly magnetic phases when using fast heating rate and large sample size. This approach moves the transformation at higher temperature, but enhances the amplitude of the signal of newly created phase. Large sample size gives prevalence of the local micro-environment, created by evolving gases, released during transformations. The example from archeological brick reveals the effect of different sample sizes on the observed Curie temperatures on heating and cooling curves, when the magnetic carrier is substituted magnetite (Mn0.2Fe2.70O4). Large sample size leads to bigger differences in Tcs on heating and cooling, while small sample size results in similar Tcs for both heating rates.

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A logistic kinetic model for isothermal and nonisothermal cure reactions of thermosetting polymers

López-Beceiro

Fontenot

Gracia-Fernández³

et al. 2014

J of Applied Polymer Sci

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A model describing the low-temperature crystallization kinetics observed for thermoplastic polymers from the melt by differential scanning calorimetry (DSC) was shown to accurately predict the cooling curves as a function of time and temperature. The model was successful for treating data for several cooling rates as well as for isothermal DSC data. In this article, we extended the model to cure reactions of thermosetting polymers. The parameters representing lower and upper exotherm reference temperatures in crystallization events have a different meaning for curing events. Thus, the model was modified to account for this change of context. The new model was tested for exothermic reactions of a HysolV R FP4527 epoxy adhesive system using data from DSC ramp heating experiments at several heating rates and also from isothermal experiments. Good fits were obtained for all the varied experimental conditions. The model made use of three fitting parameters with physical significance: a lower critical temperature (T c ) an activation energy (E b ), and a reaction order (s 1 1). Additionally, to complete the kinetic fitting, the dependence of the time to reach the reaction peak maximum for isothermal cure was considered. That dependence was found to follow a more simple model which is formally equivalent to that observed in isothermal crystallization, and which makes use of two parameters related to the limits of the temperature range in which the polymerization may occur.

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Kinetics of solid state phase transformations: Measurement and modelling of some basic issues

Cited by 11 publications

References 23 publications

A Calorimetric Study of Recovery and Recrystallization in Fe–14.4 Cr–15.4 Ni–2.4 Mo–2.36 Mn–0.25 Ti–0.04 C–0.05 P (mass %) Austenitic Stainless Steel

A Calorimetric Study of Recovery and Recrystallization in Fe–14.4 Cr–15.4 Ni–2.4 Mo–2.36 Mn–0.25 Ti–0.04 C–0.05 P (mass %) Austenitic Stainless Steel

Thermomagnetic Behavior of Magnetic Susceptibility—Heating Rate and Sample Size Effects

A logistic kinetic model for isothermal and nonisothermal cure reactions of thermosetting polymers

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