T.Y. Hsu

Size effect on the Fe nanocrystalline phase transformation

Abstract A thermodynamics for the phase transformation from γ(fcc) to α(bcc) in nanocrystalline (NC) Fe is considered. Gibbs free energies of the interfaces in NC γ- and α-Fe particles were calculated, respectively, by means of a quasiharmonic Debye approximation, yielding a larger increase in the total Gibbs free energy of α-Fe than that of γ-Fe. This is attributed to the difference in their interfacial energies. As a result, the fcc NC Fe can be thermodynamically stable at room temperature when the grain size is sufficiently small. Taking into account the thermodynamic equilibrium condition, the critical grain size for the γ-Fe phase to exist in stable form at 300 K was quantitatively calculated for different excess volumes Δ V , a parameter describing the state of interface based on a dilated crystal model. The assumptions made in the present model and the factors influencing the critical grain size are discussed.

Prediction of the flow stress of high-speed steel during hot deformation using a BP artificial neural network

Abstract The hot deformation behavior of T1 (W18Cr4V) high-speed steel was investigated by means of continuous compression tests performed on a Gleeble 1500 Thermomechanical simulator over a wide range of temperatures (950–1150°C) with strain rates of 0.001–10xa0s−1 and true strains of 0–0.7. The flow stress under the above-mentioned hot deformation conditions is predicted using a BP artificial neural network. The architecture of the network includes three input parameters: strain rate e , temperature T and true strain e; and just one output parameter: the flow stress σ. Two hidden layers are adopted, the first hidden layer including nine neurons and the second 10 neurons. It has been verified that a BP artificial neural network with 3–9–10–1 architecture can predict the flow stress of high-speed steel during hot deformation very well. Compared with the prediction method of flow stress using the Zener–Holloman parameter and hyperbolic sine stress function, the prediction method using the BP artificial neural network has higher efficiency and accuracy.

Novel ultrahigh-strength nanolath martensitic steel by quenching–partitioning–tempering process

A modified heat treatment process designated quenching–partitioning–tempering (Q–P–T) process is developed based on the quenching and partitioning process proposed by J.G. Speer et al. [ Acta Mater. 51, 2611 (2003)] and D.K. Matlock et al. [ Mater. Sci. Forum 426–432 , 1089 (2003)]. A Fe–0.485C–1.195Mn–1.185Si–0.98Ni–0.21Nb steel after Q–P–T process satisfies the designed requirement of tensile strength over 2000 MPa and elongation over 10%. The microstructure characterization indicates that this ultrahigh-strength steel consists of nanomicrostructures including lath martensite, filmlike retained austenite, and dispersive Nb-containing carbides. The effect of tempering time on the mechanical properties is analyzed based on microstructures.

Investigation on hot deformation behavior of AISI T1 high-speed steel

Abstract The hot deformation behavior of AISI T1 (18W–4Cr–1V) high-speed steel has been investigated in the temperature range 950–1150°C at strain rates of 0.001–10 s−1 and true strains of 0–0.6. The results show that the activation energy for deformation, Q, decreases with the increase of strain below 1000°C, and it changes slightly with the strain above 1000°C. Metallography shows that there are fine carbide particles precipitated in the grains, and that these lead to dispersion hardening and an increase in the value of Q. There are fewer of these particles above 1000°C than below it. The Zener–Hollomon parameter and the hyperbolic sine function are used to predict the flow stress as influenced by temperature and strain rate for different strain levels.

The effect of martensite ordering on shape memory effect in a Copper-Zinc-Aluminium alloy

Abstract The correlation between the shape memory effect (SME) and the degree of ordering in martensite formed through various heat-treatment processes, e.g. ice water quenching, step-quenching and aging etc., has been studied in a Cu-25.83wt. %Zn-3.96wt. %Al alloy, by estimating the spacing difference (Δd) of some pairs of diffracting planes with indices satisfying the relation (( h 1 2 − h 2 2 )/3 = ( k 2 2 − K 1 2 )/ n , which may reflect the degree of ordering in martensite. It is shown that SME dependes monotonically on Δd. The extent of ordering of the DO 3 parent phase, and in turn that of the martensite, increases with the holding duration in the course of step-quenching, which may be the main factor for enhancing the shape recovery rate η. The stabilization of martensite may be associated with the clustering of vacancies resulting in the local distortion of lattice plane and the formation of sessile dislocation, thus lowering the degree of ordering.

Influence of grain size and ordering degree of the parent phase on Ms in a cuznal alloy containing boron

Abstract In this paper, the influence of the average grain size and ordering degree of the parent phase on the starting temperature of thermoelastic martensitic transformation in a Cu-25.62 Zn-3.97 Al0.0018 B (wt%) shape memory alloy is studied. Based on the thermodynamics of phase transformation, a linear relationship between the starting temperature of martensitic transformation and the reciprocal of the square root of grain size is obtained, i.e. M s temperature decreases with increasing grain size, concurrent exactly with the result of electric resistance measurement. Application of Landaus theory gives a quantitative relationship between M s temperature and the ordering parameter of the parent phase, which is well confirmed by the results of X-ray diffraction and electric resistance measurement. Besides, the activation energy of the ordering process in the parent phase of the alloy employed is calculated to be 46 kJ/mol.

Influence of austenite grain size on γ-ε martensitic transformation temperature in Fe-Mn-Si-Cr alloys

Two alloys of Fe-26.4wt%Mn-6.2wt%Si-5.2wt%Cr (Alloy 1) and Fe-30wt%Mn-6.0wt%Si-5.3wt%Cr (Alloy 2) were prepared by vacuum induction melting. The starting temperature of fcc to hcp phase transformation, Ms, and the mean austenite grain size, D, increase with increasing the austenitizing temperature for both Fe-Mn-Si-Cr alloys. The Ms temperature maintains an exponential relationship with the reciprocal of the grain size as Ms = A exp ({minus}B/D), which may be related to the probability of finding the nucleation sites formed by the overlapping of stacking faults for coarser grains.

Effect of the Neel temperature, TN, on martensitic transformation in Fe–Mn–Si-based shape memory alloys

Abstract Internal friction and elastic modulus of Fe–30.30 Mn–6.10 Si, Fe–29.05 Mn–6.27 Si–0.024 RE (rare earth elements) and Fe–26.40 Mn–6.02 Si–5.20 Cr shape memory alloys were measured as a function of temperature from 150 to 600 K using an electrostatic audio-frequency internal friction instrument. The Neel temperature, TN, and Ms temperature of these alloys were determined. By calculating the area covering the internal friction peak of the e→γ reversion transformation, effects of the Neel temperature, TN, on the γ→e martensitic transformation were investigated. The results show that alloy compositions evidently affect the TN temperature, and RE and Cr reduce the TN temperature. With the decrease of the TN temperature and the increase of Ms–TN, the repressive effect of the TN temperature on the γ→e martensitic transformation decreases, and the amount of the martensitic e phase and the area of the internal friction peak of the e→γ transformation increase.

Analysis of the stress-strain curves of a Fe-Mn-Si shape memory alloy

Abstract The stress-induced martensitic transformation of an Fe-30(wt.%)Mn-6(wt.%)Si shape memory alloy has been studied through the tensile deformation and the recovery processes. The results show that the deformation process of Fe-Mn-Si shape memory alloys can be divided into three stages with different mechanisms. The first stage is the elastic stage, the second one is related to the γ → ϵ phase transformation, and the third one can be described as plastic deformation. An appropriate thermomechanical training procedure can markedly increase the recovery rate to close to 100%.

Diffusion of carbon during the formation of low-carbon martensite

The time required for carbon diffusion from martensite to enrich surrounding austenite from 0.27 to 1.04% C during the formation of low-carbon matensite is 10~(-7)s in order of magnitude as calculated. It does prove that the diffusion of carbon atoms can keep pace with the formation of lath martensite. From thermodynamical calculation, it is reasonable to recognize that the precipitation of carbon from martensite results the enrichment of austenite. TEM observation revealed that the quenched structure in a 0.12C-low Ni-Cr steel mainly contains lath martensite and interlath retained austenite, and also twin martensite. The existence of the latter further confirms the occurrence of carbon diffusion to enrich austenite during the martensite formation, and twin martensite forms at the parent phase where carbon enrichment is not very high. The interface of austenite and martensite is somewhat straight. The typical upper bainite (B_Ⅱ), B_Ⅲ type bainite and carbide-free bainite (B_1) can aU appear in the ame steel and there exists superledges at the interface of austenite and bainitie ferrite which is quite different to that of austenite and martensite. In addition, from the kinetics point of view. the growth rate of low-carbon martensite is 3 to 4 order of magnitude greater than that of upper bainite. It is more likely to conclude that the mechanism of the formation of lath martensite is not identical with that of bainite.