PhD position Modelling austenite decomposition: bainite, acicular ferrite, heat of transf. and effect of deformation – Technical University of Delft, Delft (the Netherlands)

////PhD position Modelling austenite decomposition: bainite, acicular ferrite, heat of transf. and effect of deformation – Technical University of Delft, Delft (the Netherlands)

Introduction

The understanding of bainite formation in steels is one of the most controversial topics in physical metallurgy . There are two schools of thought describing this phase transformation. The “diffusional” school accepts that the growth of bainitic subunits is controlled by the diffusion of carbon at the interface, while the “displacive” school considers that the diffusion of carbon into the austenite occurs after the diffusionless growth of the bainitic ferrite. Following both approaches to this problem, there exist several models that predict the formation and kinetics of bainite in steels. However, these models do not tackle the polycrystalline morphology of the phases in the microstructure and therefore do not provide in principle information on grain sizes or compositional gradients. The formation of acicular ferrite follows the same general mechanisms as bainite, although it nucleates at inclusions. The development of a model for bainite including microstructural aspects, such as gradients and morphologies, could be in principle extended to acicular ferrite considering the different nucleation sites. Phase transformations after the deformation of austenite are characterized by different transformation temperatures and kinetics, although experimental studies performed in this field led often to contradictory results. Due to these uncertainties, models with predictive abilities able to explain these effects are not yet available.

Organization

The Department of Materials Science and Engineering (MSE) of the Delft University of Technology, undertakes coherent and innovative research dedicated to developing, producing, characterising and manipulating materials, with a focus on metals. The aim is to develop fundamental understanding forming the basis for better performance, a longer life cycle with preservation of functionality, while at the same time optimising sustainable use of resources and minimising environmental footprint.

The microstructure section of the MSE department with five senior scientists and some 15 PhD students and post-docs, has a leading position worldwide in the field of microstructure control, based on both experimental characterisation and physical modelling. For more information: https://www.tudelft.nl/en/3me/departments/materials-science-and-engineering/research/microstructures/

Function

This PhD project forms part of the Digitally Enhanced New Steel Product Development (DENS) program, in which Tata Steel Europe, Materials innovation institute (M2i) and several academic partners collaborate to enable the development of new generations of advanced materials for e.g. the automotive industry.

Digitally Enhanced New Steel Product Development (DENS) program

Significant progress has been made in the past decades in the development of advanced models that describe the behavior of steel during processing and subsequent applications. However, the quantitative application of through process models in new steel product development still lacks predictivity. In modern steel grades, parameters of the steel production process have a significant influence on the final material properties. Furthermore, the trend towards complex multi-phase microstructures requires very sophisticated models to describe their mechanical properties in a predictive manner. The main scientific challenge addressed in this program is to integrate state-of-the-art models in a single through process model framework that can be applied in practice for new steel product development.

The understanding of bainite formation in steels is one of the most controversial topics in physical metallurgy. Existing predictive models on this phase transformation do not provide information on grain sizes or compositional gradients. Experimental studies on transformation temperatures and kinetics of austenite formation show contradicting results. Furthermore, the possibility to extend a model for bainite microstructure to acicular ferrite remains unexplored. To study the present uncertainties on phase transformations after austenite deformation, this project has three aims:

1. To create a physically-based and robust model for 3D description of the bainite and acicular ferrite formation in a polycrystalline material.

The developed model should not only provide kinetics information of the bainite formation but also compositional gradients and morphological information. This model will be validated by comparison with outcomes from selected materials. As a further step, the model will be extended to predict the kinetics of acicular ferrite formation.

2. To develop a model describing phase transformations from deformed austenite.

Research in literature on phase transformations from deformed austenite is often contradictory. Therefore, this task will start with an experimental investigation on these effects. With that information, a model will be proposed for the microstructural development of that austenite during further cooling. With respect to undeformed austenite, deformed austenite entails different critical temperatures and times. These phenomena occur typically in hot rolled of higher alloyed grades. The task will continue with the validation of the model and further implementation.

3. To model the effect of heat of bainite transformation locally and globally in the system.

Online control over the microstructure relies on control of the time-temperature path. The time-temperature is a result of the applied cooling and the heat of transformation. Therefore, an accurate description of the heat of transformation of bainite is essential for control of the microstructure. In this task, the heat of transformation of bainite will be systematically investigated and a model developed based on the results. This step will be followed by the validation of the model.

Requirements

We are searching for enthusiastic candidates holding a MSc degree in physics, chemistry, materials science or similar field. The candidate must have knowledge on physics of materials, solid state physics, solid-solid phase transformations and mechanical behaviour. Moreover, the candidate should have:

  • affinity for computational calculation as well as a solid background on mathematics and numerical methods.
  • an “academic attitude” with excellent analytical skills, taking initiative, inventiveness, curiosity and critical thinking about the research approach and results.
  • strong communication skills (high English proficiency), ability to integrate, and have good social behaviour.

Offer

The TU Delft offers a customisable compensation package, a discount for health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. An International Children’s Centre offers childcare and an international primary school. Dual Career Services offers support to accompanying partners. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.

The PhD. candidate will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment; an excellent team of supervisors, academic staff and a mentor; and a Doctoral Education Programme aimed at developing your transferable, discipline-related and research skills. Please visit www.phd.tudelft.nl for more information.

Information

Minds for Innovation is the recruitment partner for this project. For more information regarding recruitment please contact Jolanda de Roo. E: j.deroo@mindsforinnovation.nl, T: + 316 572 913 50

For more information on the project specifics, please contact Prof. Maria Santofimia Navarro. E: M.J.SantofimiaNavarro@tudelft.nl

Application

Application documents (in PDF format) must contain:

  • letter of motivation containing why you are interested in this specific project and why you would be a good candidate (refer to vacancy number 3ME17-75 in the subject)
  • detailed curriculum vitae and contact information of two potential referees
  • transcripts of BSc and MSc grades
  • transcript of English test

Apply before the deadline of July 31st 2018.

As one of the first selection steps, you will be invited to participate on our specialised online assessment. If you would like to know more about why we use this and how we have set it up, then check out our website.

2018-06-20T02:10:08+00:00 June 6th, 2018|