Jiajun Wang

Bio: Jiajun Wang is an academic researcher from Philips. The author has contributed to research in topics: Continuous cooling transformation & Ferrite (iron). The author has an hindex of 8, co-authored 10 publications receiving 416 citations.

Stabilization mechanisms of retained austenite in transformation-induced plasticity steel

Abstract: Three stabilization mechanisms—the shortage of nuclei, the partitioning of alloying elements, and the fine grain size—of the remaining metastable austenite in transformation-induced plasticity (TRIP) steels have been studied by choosing a model alloy Fe-0.2C-1.5Mn-1.5Si. An examination of the nucleus density required for an athermal nucleation mechanism indicates that such a mechanism needs a nucleus density as large as 2.5 · 1017 m−3 when the dispersed austenite grain size is down to 1 µm. Whether the random nucleation on various heterogeneities is likely to dominate the reaction kinetics depends on the heterogeneous embryo density. Chemical stabilization due to the enrichment of carbon in the retained austenite is the most important operational mechanism for the austenite retention. Based on the analysis of 57 engineering steels and some systematic experimental results, an exponential equation describing the influence of carbon concentration on the martensite start (Ms) temperature has been determined to be Ms (K)=273+545.8 · e−1.362wc(mass pct). A function describing the Ms temperature and the energy change of the system has been found, which has been used to study the influence of the grain size on the Ms temperature. The decrease in the grain size of the dispersed residual austenite gives rise to a significant decrease in the Ms temperature when the grain size is as small as 0.1 µm. It is concluded that the influence of the grain size of the retained austenite can become an important factor in decreasing the Ms temperature with respect to the TRIP steels.

Determination of Martensite Start Temperature in Engineering Steels Part I. Empirical Relations Describing the Effect of Steel Chemistry

Abstract: The dependency of the martensite start (ms) temperature upon composition of engineering steels has been examined by analyzing the results predicted by an artificial neural network (ANN) model and thermodynamic data. Two new formulas, the simple linear and binary interaction ones, have been statistically derived and applied to predict the is temperature in an Fe-C-Si-Mn-Cr-Mo system. It is shown that the separation of the influence of interactions from that of individual alloying elements is successful since most of the statistical results are reasonable and thus have been physically interpreted. The thermodynamic calculations show that the alloying elements have similar influence upon the is and A 3 temperatures. The apparent effect of carbon depends largely on C-X interactions. C-Mn and C-Mo interactions weaken the effect of carbon while that of C-Si interaction intensifies the role of C. This is supported by phenomenological results and has been physically interpreted. The interactions between substitutional alloying elements have also significant influence upon the is temperature. The Si-Mn interaction strongly increases the Ms while Si-Mo interaction significantly decreases the is. So far, there is no proper physical explanation for this though supportive evidence has been obtained from phenomenological results. in and Mo have the weakest apparent interaction, that is, their influence can be simply added up. Moreover, a semi-physical model has been built to predict the is temperature from a critical temperature, which can be calculated thermodynamically. It shows that the semi-physical method gives a satisfactory prediction of is with a standard error of 15.3°C. Evaluation of nine common empirical methods indicates that the Kung and Rayment (KR) formula gives the best predicting results amongst them.

On the influence of alloying elements on the bainite reaction in low alloy steels during continuous cooling

Abstract: The CCT diagrams of a class of Fe-(0.1–0.6)C-(0.4–2.0)Si-(0.4–2.0)Mn-(0.5–2.0)Cr-(0.0–0.8)Mo steels are predicted by an artificial neural network (ANN) model. The model indicates that an increase in carbon concentration (C wt%) gives rise to a decrease in bainite start (BS) temperatures. The rate of decrease depends also on cooling rate. Additions of Si, Mn, Cr and Mo all decrease the bainite start temperature. The dependencies for different alloying elements vary: 32, 100–120, 100–130, and 70–150°C per wt% of Si, Mn, Cr, and Mo, respectively. Mn shifts the whole bainite transformation region to the far right-hand side of the CCT diagram, while C, Cr, and Mo have considerable, and Si has minor effects on the incubation period of bainite. Mn and Cr significantly decrease the MS temperature, while Si only has a minor influence. When Mo 0.5 wt%, it increases MS temperature. Quasi-isochronal and quasi-isothermal methods have been used to analyze the influence of the proportion of Mo and C upon the BS and incubation period. Attempts, for qualitative explanations using the shear and diffusion mechanism, as well as a certain amount of thermodynamic analysis, have been made to interpret the influence of alloying elements on the nucleation of the bainite reaction. The results support that bainite reaction takes place utilizing a diffusion-controlled mechanism.

Effects of Carbon Concentration and Cooling Rate on Continuous Cooling Transformations Predicted by Artificial Neural Network

Abstract: Employing 151 continuous cooling transformation (CCT) diagrams, an artificial neural network (ANN) has been modeled and trained. The CCT diagrams of a class of Fe-xC-0.4Si-0.8Mn-1.0Cr-0.003P-0.002S (x within 0.1 through 0.6) steels are predicted by the model developed. It indicates that an increase in carbon concentration (C%) gives rise to a decrease in ferrite start (Fs), bainite start (BS), and martensite start (MS) temperatures, but the carbon concentration has weak effect on the pearlite end (Pe) temperature. The rate of decrease, ∂Fs/∂C, further depends on the carbon concentration. The carbon dependence predicted by the ANN is consistent with what is predicted by thermodynamic models. The Fs temperature is also affected by the cooling rate (υ), especially for high carbon steels and υ>0.1°C/s. C prolongs the incubation period of ferrite formation, but accelerates the overall growth kinetics of the pearlite reaction. The Fs and Pe temperatures at low cooling rates predicted by the ANN model are in agreement with those predicted by thermodynamic models. The deviations of Pe and Fs from their thermodynamic equilibrium counterparts are nearly independent of the carbon concentration. The minimum undercooling for both ferrite and pearlite reactions is around 50°C. It increases up to 100°C at higher cooling rates. Pre-bainite decomposition of austenite retards bainite formation. Employing the Ms temperature, the critical driving force for heterogeneous athermal nucleation is also estimated and related to the Ms temperature. Ms temperatures predicted by this model prove to be consistent with those predicted by several empirical linear models. It can be concluded that the current ANN model is reliable and effective.

Structure–properties relationship in TRIP steels containing carbide-free bainite

Abstract: The purpose of the present contribution is to review the current knowledge about the relationship between the micro-structure of cold rolled intercritically annealed low alloy TRIP-aided sheet steels and their mechanical properties from a materials engineering point of view. The focus is on their production in existing industrial lines and on their application in the manufacture of passenger cars with a body-in-white which offers an improved passive safety. The review aims to make clear that although low alloy TRIP-aided sheet steel is by now starting to be an established structural material in BIW manufacturing, there is still room for the further optimization of the composition and the processing. In addition, there are still a number of problems related to their physical metallurgy that require a better fundamental understanding.

Segregation mediated heterogeneous structure in a metastable β titanium alloy with a superior combination of strength and ductility

Abstract: In β titanium alloys, the β stabilizers segregate easily and considerable effort has been devoted to alleviate/eliminate the segregation. In this work, instead of addressing the segregation problems, the segregation was utilized to develop a novel microstructure consisting of a nanometre-grained duplex (α+β) structure and micrometre scale β phase with superior mechanical properties. An as-cast Ti-9Mo-6W alloy exhibited segregation of Mo and W at the tens of micrometre scale. This was subjected to cold rolling and flash annealing at 820 oC for 2 and 5 mins. The solidification segregation of Mo and W leads to a locally different microstructure after cold rolling (i.e., nanostructured β phase in the regions rich in Mo and W and plate-like martensite and β phase in regions relatively poor in Mo and W), which play a decisive role in the formation of the heterogeneous microstructure. Tensile tests showed that this alloy exhibited a superior combination of high yield strength (692 MPa), high tensile strength (1115 MPa), high work hardening rate and large uniform elongation (33.5%). More importantly, the new technique proposed in this work could be potentially applicable to other alloy systems with segregation problems.