Method Development

Scientists of the Max-Planck-Institut für Eisenforschung pioneer new machine learning model for corrosion-resistant alloy design. Their results are now published in the journal Science Advances more

A further step in unravelling materials’ properties down to the atomic scale more

Video: How to save time and effort in materials’ characterization? more

Statistical significance in materials science is a challenge that has been trying to overcome by miniaturization. However, this process is still limited to 4-5 tests per parameter variance, i.e. Size, orientation, grain size, composition, etc. as the process of fabricating pillars and testing has to be done one by one. With this project, we aim to fabricate arrays of well-defined and located particles that can be tested in an automated manner. With a statistically significant amount of samples tested per parameter variance, we expect to apply more complex statistical models and implement machine learning techniques to analyze this complex problem. more

In this project, links are being established between local chemical variation and the mechanical response of laser-processed metallic alloys and advanced materials.

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In collaboration with Dr. Edgar Rauch, SIMAP laboratory, Grenoble, and Dr. Wolfgang Ludwig, MATEIS, INSA Lyon, we are developing a correlative scanning precession electron diffraction and atom probe tomography method to access the three-dimensional (3D) crystallographic character and compositional information of nanomaterials with unprecedented spatial and chemical resolution. more

About 90% of all mechanical service failures are caused by fatigue. Avoiding fatigue failure requires addressing the wide knowledge gap regarding the micromechanical processes governing damage under cyclic loading, which may be fundamentally different from that under static loading. This is particularly true for deformation-induced martensitic transformation (DIMT), one of the most common strengthening mechanisms for alloys. Here, we identify two antagonistic mechanisms mediated by martensitic transformation during the fatigue process through in situ observations and demonstrate the dual role of DIMT in fatigue crack growth and its strong crack-size dependence. Our findings open up avenues for designing fatigue-resistant alloys through optimal use of DIMT. They also enable the development of physically based lifetime prediction models with higher fidelity.
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Within this project, we will use an infra-red laser beam source based selective powder melting to fabricate copper alloy (CuCrZr) architectures. The focus will be on identifying the process parameter-microstructure-mechanical property relationships in 3-dimensional CuCrZr alloy lattice architectures, under both quasi-static and dynamic loading conditions.
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In this project we developed a phase-field model capable of describing multi-component and multi-sublattice ordered phases, by directly incorporating the compound energy CALPHAD formalism based on chemical potentials. We investigated the complex compositional pathway for the formation of the η-phase in Al-Zn-Mg-Cu alloys during commercial multi-stage artificial ageing treatments.
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Here, we aim to develop machine-learning enhanced atom probe tomography approaches to reveal chemical short/long-range order (S/LRO) in a series of metallic materials. more

The structures of grain boundaries (GBs) have been investigated in great detail. However, much less is known about their chemical features, owing to the experimental difficulties to probe these features at the near-atomic scale inside bulk material specimens. Atom probe tomography (APT) is a tool capable of accomplishing this task, with an ability to quantify chemical characteristics at near-atomic scale. more

Water electrolysis has the potential to become the major technology for the production of the high amount of green hydrogen that is necessary for its widespread application in a decarbonized economy. The bottleneck of this electrochemical reaction is the anodic partial reaction, the oxygen evolution reaction (OER), which is sluggish and hence requires efficient catalysts. We use electrochemical in situ spectroscopy techniques to study this reaction in detail. more

Crystal plasticity modelling has gained considerable momentum in the past 20 years [1]. Developing this field from its original mean-field homogenization approach using viscoplastic constitutive hardening rules into an advanced multi-physics continuum field solution strategy requires a long-term initiative. The group “Theory and Simulation” of Franz Roters is working in this field since 2000. Code development during the last years was coordinated by the group “Integrated Computational Materials Engineering” headed by Martin Diehl.  more

The development of pyiron started in 2011 in the CM department to foster the implementation, rapid prototyping and application of the highly advanced fully ab initio simulation techniques developed by the department. The pyiron platform bundles the different steps occurring in a typical simulation life cycle in a single software platform and provides both developers and users an intuitive and easy to use interface that shields them from the underlying computationally efficient but highly complex data and job management concepts. more

The prediction of materials properties with ab initio based methods is a highly successful strategy in materials science. While the working horse density functional theory (DFT) was originally designed to describe the performance of materials in the ground state, the extension of these methods to finite temperatures has seen remarkable breakthroughs. This is needed, since many functional and structural mechanisms as well as the stability of relevant phases dramatically change with temperature.
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In 2020, an interdepartmental software task force (STF) was formed to serve as a forum for discussion on topics related to software development and digital workflows at the MPIE. A central goal was to facilitate interdepartmental collaboration by co-developing and integrating workflows, aligning internally developed software, and rolling out digital services. Trainings and workshops were organized in order to engage the entire MPIE community. Some highlights of the STF activities will be outlined in the following.
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Developing and providing accurate simulation techniques to explore and predict structural properties and chemical reactions at electrified surfaces and interfaces is critical to surmount materials-related challenges in the context of sustainability, energy conversion and storage. The groups of C. Freysoldt, M. Todorova and S. Wippermann develop various methods to incorporate finite electric fields in density-functional theory (DFT) and apply them to answer fundamental questions in corrosion, field evaporation, and the thermodynamics and transformation of electrochemical interfaces.
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The utilization of Kelvin Probe (KP) techniques for spatially resolved high sensitivity measurement of hydrogen has been a major break-through for our work on hydrogen in materials. A relatively straight forward approach was hydrogen mapping for supporting research on hydrogen embrittlement that was successfully applied on different materials, and this cooperation was continued, see e.g. [1, 2]. 
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Photovoltaic materials have seen rapid development in the past decades, propelling the global transition towards a sustainable and CO₂-free economy. Storing the day-time energy for night-time usage has become a major challenge to integrate sizeable solar farms into the electrical grid. Developing technologies to convert solar energy directly into hydrogen fuels would not only ease grid operation, but also power other energy demands, e.g. fuel cell vehicles.
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The field of micromechanics has seen a large progress in the past two decades, enabled by the development of instrumented nanoindentation. Consequently, diverse methodologies have been tested to extract fundamental properties of materials related to their plastic and elastic behaviour and fracture toughness. Established experimental protocols are carried out either at atmospheric conditions or at ultra-high vacuum inside an electron microscope. more