Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (16/16 displayed)

  • 2024Highly complex materials processes as understood by phase-field simulationscitations
  • 2024Automated Workflow for Phase‐Field Simulations: Unveiling the Impact of Heat‐Treatment Parameters on Bainitic Microstructure in Steel1citations
  • 2024Multi-phase-field approach to fracture demonstrating the role of solid-solid interface energy on crack propagationcitations
  • 2023Coherency loss marking the onset of degradation in high temperature creep of superalloys15citations
  • 2023Solidification of the Ni-based superalloy CMSX-4 simulated with full complexity in 3-dimensions7citations
  • 2023Phase-Field Study of the History-Effect of Remelted Microstructures on Nucleation During Additive Manufacturing of Ni-Based Superalloys14citations
  • 2022Efficient reconstruction of prior austenite grains in steel from etched light optical micrographs using deep learning and annotations from correlative microscopy11citations
  • 2022Efficient reconstruction of prior austenite grains in steel from etched light optical micrographs using deep learning and annotations from correlative microscopycitations
  • 2022Schmid rotations during high temperature creep in Ni-based superalloys related to coherency loss1citations
  • 202045-degree rafting in Ni-based superalloys 44citations
  • 2016Atomistically informed extended Gibbs energy description for phase-field simulation of tempering of martensitic steelcitations
  • 2016Microstructure design of tempered martensite by atomistically informed full-field simulationcitations
  • 2015Primary combination of phase-field and discrete dislocation dynamics methods for investigating athermal plastic deformation in various realistic Ni-base single crystal superalloy microstructures14citations
  • 2015Primary combination of phase-field and discrete dislocation dynamics methods for investigating athermal plastic deformation in various realistic Ni-base single crystal superalloy microstructures14citations
  • 2012Martensitic phase transformations in Ni–Ti-based shape memory alloys : the Landau theorycitations
  • 2008Theory of size mismatched alloy systems : many-body Kanzaki forcescitations

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Chart of shared publication
Salama, Hesham
2 / 2 shared
Uddagiri, Murali
3 / 5 shared
Ali, Muhammad Adil
5 / 9 shared
Steinbach, Ingo
12 / 48 shared
Nerella, Dhanunjaya Kumar
1 / 1 shared
Krupp, Ulrich
1 / 28 shared
Gulbay, Oguz
1 / 2 shared
Ackermann, Marc
3 / 5 shared
Jafarzadeh, Hossein
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Stricker, Markus
2 / 10 shared
Tegeler, Marvin
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Wahlmann, Benjamin
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Koerner, Carolin
1 / 1 shared
Bachmann, Björn-Ivo
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Staudt, Thorsten
2 / 8 shared
Durmaz, Ali Riza
2 / 12 shared
Birtz, Dominik
1 / 1 shared
Mücklich, Frank
2 / 79 shared
Müller, Martin
2 / 38 shared
Britz, Dominik
1 / 15 shared
Amin, Waseem
1 / 5 shared
Čak, Miroslav
1 / 1 shared
Drautz, Ralf
2 / 25 shared
Hammerschmidt, Thomas
1 / 11 shared
Borukhovich, Efim
1 / 2 shared
Du, Guanxing
1 / 1 shared
Hartmaier, Alexander
3 / 54 shared
Boeff, Martin
1 / 5 shared
Stratmann, Matthias
1 / 3 shared
Ma, Anxin
2 / 12 shared
Fivel, Marc
1 / 14 shared
Gao, Siwen
2 / 6 shared
Kumar Rajendran, Mohan
1 / 1 shared
Fivel, Marc C.
1 / 29 shared
Rajendran, Mohan Kumar
1 / 1 shared
Finel, Alphonse
1 / 16 shared
Salman, Umut
1 / 1 shared
Díaz-Ortiz, Alejandro
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Udyansky, A.
1 / 5 shared
Bugarev, V. N.
1 / 1 shared
Reichert, H.
1 / 3 shared
Dosch, Helmut
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Co-Authors (by relevance)

  • Salama, Hesham
  • Uddagiri, Murali
  • Ali, Muhammad Adil
  • Steinbach, Ingo
  • Nerella, Dhanunjaya Kumar
  • Krupp, Ulrich
  • Gulbay, Oguz
  • Ackermann, Marc
  • Jafarzadeh, Hossein
  • Stricker, Markus
  • Tegeler, Marvin
  • Wahlmann, Benjamin
  • Koerner, Carolin
  • Bachmann, Björn-Ivo
  • Staudt, Thorsten
  • Durmaz, Ali Riza
  • Birtz, Dominik
  • Mücklich, Frank
  • Müller, Martin
  • Britz, Dominik
  • Amin, Waseem
  • Čak, Miroslav
  • Drautz, Ralf
  • Hammerschmidt, Thomas
  • Borukhovich, Efim
  • Du, Guanxing
  • Hartmaier, Alexander
  • Boeff, Martin
  • Stratmann, Matthias
  • Ma, Anxin
  • Fivel, Marc
  • Gao, Siwen
  • Kumar Rajendran, Mohan
  • Fivel, Marc C.
  • Rajendran, Mohan Kumar
  • Finel, Alphonse
  • Salman, Umut
  • Díaz-Ortiz, Alejandro
  • Udyansky, A.
  • Bugarev, V. N.
  • Reichert, H.
  • Dosch, Helmut
OrganizationsLocationPeople

article

Automated Workflow for Phase‐Field Simulations: Unveiling the Impact of Heat‐Treatment Parameters on Bainitic Microstructure in Steel

  • Salama, Hesham
  • Shchyglo, Oleg
  • Nerella, Dhanunjaya Kumar
  • Krupp, Ulrich
  • Gulbay, Oguz
  • Ali, Muhammad Adil
  • Steinbach, Ingo
  • Ackermann, Marc
Abstract

<jats:p>Bainitic steels are extensively utilized across various sectors, such as the automotive and railway industries, owing to their impressive mechanical properties, including strength, hardness, and fatigue resistance. However, the pursuit of achieving the desired optimal mechanical properties presents considerable challenges due to the intricate bainitic microstructures consisting of multiple phases. To tackle these challenges, an automated workflow is used for extracting 2D and 3D microstructural features. The proposed method allows for a detailed examination of the correlations between microstructure characteristics and the processing parameters, specifically the holding temperature during transformation. In these findings, it is revealed that as the holding temperature decreases, there is a notable reduction in microstructural element size and carbon partitioning. Some of the observations are microstructural features such as area, perimeter, and thickness of the bainitic ferrite grains under two different holding temperatures. Phase‐field simulations results show that the microstructures at lower holding temperatures have finer grains. The distributions of grain areas and perimeters are uniform, with smaller grains dominating at low and high isothermal holding temperatures. While the grain thickness measurements from simulations and experiments at high temperature are qualitatively aligned, data from low temperatures show discrepancies.</jats:p>

Topics
  • impedance spectroscopy
  • Carbon
  • grain
  • phase
  • experiment
  • simulation
  • strength
  • steel
  • fatigue
  • hardness
  • aligned