6.4 Materialinformatik
Filtern
Erscheinungsjahr
- 2023 (15)
Dokumenttyp
- Vortrag (15)
Sprache
- Englisch (15)
Referierte Publikation
- nein (15)
Schlagworte
- Ab initio simulations (6)
- Workflows (6)
- Defects (5)
- Phase diagrams (5)
- Digital Infrastructure (3)
- Hydrogen embrittlement (2)
- Integrated Development Environment (2)
- Platform MaterialDigital (2)
- Thermodynamics (2)
- Ab initio thermodynamics (1)
Organisationseinheit der BAM
Eingeladener Vortrag
- nein (15) (entfernen)
Suitable material solutions are of key importance in designing and producing components for engineering systems – either for functional or structural applications. Materials data are generated, transferred, and introduced at each step along the complete life cycle of a component. A reliable materials data space is therefore crucial in the digital transformation of an industrial branch.
Therefore, the “Innovation Platform MaterialDigital (PMD) funded by the German Federal Ministry of Education and Research (BMBF), aims to develop a sustainable infrastructure for the standardized digital representation of materials science and materials engineering. With its partners (KIT, Fraunhofer IWM, FIZ, Leibnitz IWT, BAM, MPIE), the PMD is committed to build up a materials science data space. To achieve this the PMD provides a prototypical infrastructure for the digitalization of materials implemented by decentralized data servers, standardized data schemas and digital workflows. Following the FAIR principles, it will promote the semantic interoperability across the frontiers of materials classes.
Standards, methods, and tools developed within the platform are deployed and consolidated within the context of currently near 20 BMBF-funded academic and industrial research consortia and made available to the material science community in general. In this context scientific workflows represent a major focus area, represented within the platform by the workflow frameworks pyiron and SimStack. In consequence, the platform is building up a digital library in form of a workflow store along with common standards for the definition and representation of digital workflows.
In this presentation we will describe the status of our Platform MaterialDigital with a focus on the workflow activities. The current status and the vision for dissemination of the solutions developed in the PMD within the community are provided.
Suitable material solutions are of key importance in designing and producing components for engineering systems – either for functional or structural applications. Materials data are generated, transferred, and introduced at each step along the complete life cycle of a component. A reliable materials data space is therefore crucial in the digital transformation, both in academia and industry.
Therefore, the consortium NFDI MatWerk aims to develop a sustainable infrastructure for the standardized digital representation of materials science and engineering (MatWerk). The goal is to seamlessly integrate decentralized data and metadata, experimental and computational workflows, and a materials ontology to maximize interoperability and reproducibility of materials data processing. To this end, data use profiles of participant projects from different sub-disciplines are analyzed to identify the most relevant scientific scenarios within MatWerk.
Similarly, the Plattform MaterialDigital (PMD) is committed to provide a prototypical infrastructure for the digitalization of materials in an industrial context implemented by decentralized data servers, semantic data schemas and digital workflows. The standards, methods, and tools developed within the PMD are deployed and consolidated within the context of currently more than 20 BMBF-funded academic and industrial research consortia. Scientific workflow environments represent a major focus area, including efforts to improve the definition and representation of digital workflows, as well as their distribution in form of a workflow store.
In this presentation we will describe the overarching visions behind these initiatives, their status, and progress of dissemination with a focus on the workflow activities. Following the philosophy of both consortia, specific examples will be used to demonstrate innovative and pragmatic solutions.
Suitable material solutions are of key importance in designing and producing components for engineering systems – either for functional or structural applications. Materials data are generated, transferred, and introduced at each step along the complete life cycle of a component. A reliable materials data space is therefore crucial in the digital transformation and an important prerequisite for machine learning in materials science.
Therefore, the consortium NFDI MatWerk aims to develop a sustainable infrastructure for the standardized digital representation of materials science and engineering (MatWerk). The goal is to seamlessly integrate decentralized data and metadata, experimental and computational workflows, and a materials ontology to maximize interoperability and reproducibility of materials data processing. To this end, data use profiles of participant projects from different sub-disciplines are analyzed to identify the most relevant scientific scenarios within MatWerk.
Similarly, the Plattform MaterialDigital (PMD) is committed to provide a prototypical infrastructure for the digitalization of materials in an industrial context implemented by decentralized data servers, semantic data schemas and digital workflows. The standards, methods, and tools developed within the PMD are deployed and consolidated within the context of currently more than 20 BMBF-funded academic and industrial research consortia. Scientific workflow environments represent a major focus area, including efforts to improve the definition and representation of digital workflows, as well as their distribution in form of a workflow store.
In this presentation we will describe the overarching visions behind these initiatives, their status, and progress of dissemination with a focus on the workflow activities and the connection to machine learning applications. Following the philosophy of both consortia, specific examples will be used to demonstrate innovative and pragmatic solutions.
Material science problems have intrinsically multiscale and multiphysics characters, and require us to employ a combination of methods on different time and length scales to resolve critical features. Normally creating workflows that connect data in multiple scales and various methods is a cumbersome task. Pyiron, an integrated development environment (IDE) for material science, contains modules for the atomistic as well as continuum scale that make a seamless connection possible. To this end, it provides a high-level coherent language in a unified workflow platform to study materials, for example, with density functional theory (DFT) simulations in the same framework as with the finite element method (FEM). In this work, in addition to the introduction of different features in pyiron and its continuum module, a couple of exemplary workflows are demonstrated, bridging the scales in pyiron. One such workflow is analyzing the elastoplastic response of metallic alloys, where the elastic properties of the system are dependent on the atomistic composition and structure of the alloy. We use pyiron atomistics to model the dependence of elastic moduli on the atomistic composition of Al-Mg alloys. Benefiting from the integration of DAMASK in the continuum module of pyiron, the model can be used as an input to simulate the elastoplastic response of the alloy under various loadings. In addition, finite element simulations using the FEniCS package are currently integrated into the continuum module and will be demonstrated in the presentation.
Extensive experimental observations indicate the presence of nano-voids and the increase of free volume along the grain boundaries in hydrogen contaminated metals. This rate-dependent phenomenon motivates theoretical investigations of the underlying mechanisms. Here, a hydrogen enhanced cross-slip (HECS) mechanism in the close vicinity of the grain boundaries is demonstrated by direct molecular dynamics simulations. To this end, the interaction of the screw dislocations with a variety of symmetric tilt grain boundaries in H-charged and H-free bicrystalline nickel specimens is examined. The presence of segregated hydrogen atoms at the grain boundaries induces a stress field in their vicinity, and thus the barrier for cross-slip of screw dislocations considerably decreases. The enhanced crossslip of dislocations facilitates the formation of jogs. These jogs can form vacancies during the glide process. This mechanism shows nano-scale evidence of enhanced vacancy formation and subsequent increase in the free volume along the grain boundaries in the presence of H. This increase of the free-volume along the grain boundary dmaages the material and induce further embrittlement in addition to the direct effect of hydrogen in decreasing the fracture energy.
Understanding segregation to grain boundaries, and eventually their defect phase diagrams, is critical to enable rational grain boundary engineering for alloys design. Here, we discuss the progress and challenges one may face when generating such a database of defect-solute interactions, in the context of studying of grain boundary segregation of solutes and impurities in Fe GBs. To compute the large number of relevant defect-solute interactions we have performed high-throughput ab initio calculations using efficient and highly automated workflows using pyiron. We study has been performed across a representative set of coincident-site-lattice (CSL) type tilt GBs. Based on the large ab-initio datasets, we extract and analyse the chemical and structural trends observed in the solute segregation behaviour across the periodic table. The features which are most important in evaluating site segregation are presented and discussed.
Since the function of materials is controlled by properties and processes on the atomic scale, ab initio based high-throughput methods are valuable strategies in materials design. For computational efficiency, they are however often restriction to T=0K calculations, while many technologically relevant materials properties and thermodynamic stabilities change when going from low to high temperatures. On the other hand, the constantly increasing performance of digital tools for simulation and data-driven science enables more targeted material development including these kinds of finite-temperature effects. A flexible infrastructure, including data management and workflow solutions is required to make this symbiosis user-friendly efficient. Within this presentation, examples from ab initio thermodynamics for the design of phase stabilities in hard-magnetic alloys and defect-phases in advanced high-strength steels will be demonstrated. We will discuss physical concepts with a focus at the impact of magnetic excitations. At the same time, the examples will be used to derive requirements and present solutions for a digital infrastructure. An outlook will be given to current strategies with the NDFI initiative NFDI-MatWerk.
Since the function of materials is controlled by properties and processes on the atomic scale, ab initio based high-throughput methods are valuable strategies in materials design. For computational efficiency, they are however often restriction to T=0K calculations, while many technologically relevant materials properties and thermodynamic stabilities change when going from low to high temperatures. On the other hand, the constantly increasing performance of digital tools for simulation and data-driven science enables more targeted material development including these kinds of finite-temperature effects. A flexible infrastructure, including data management and workflow solutions is required to make this symbiosis user-friendly efficient. Within this presentation, examples from ab initio thermodynamics for the design of phase stabilities in hard-magnetic alloys and defect-phases in advanced high-strength steels will be demonstrated. We will discuss physical concepts with a focus at the impact of magnetic excitations. At the same time, the examples will be used to derive requirements and present solutions for a digital infrastructure. An outlook will be given to current strategies with the NDFI initiative NFDI-MatWerk.
In our current view, reference datasets in the MSE domain represent specific material properties, e.g., structural, mechanical, … characteristics. A reference dataset must fulfill high-quality standards, not only in precision of measurement but also in a comprehensive documentation of material, processing, and testing history (metadata). This Infrastructure Use Case (IUC) aims to develop a framework for generating reference material datasets using creep data of a single crystal Ni-based superalloy as a best practice example. In a community-driven process, we aim to encourage the discussion and establish a framework for the creation and distribution of reference material datasets. In this poster presentation, we highlight our current vision and activities and intend to stimulate the discussion about the topic reference datasets and future collaborations and work.
Defect-hydrogen interaction in Al alloys: Challenges and benefits revealed by ab initio calculations
(2023)
Climate change motivates the search for light-weight materials for transportation and energy storage solutions. As one of the challenges, the deleterious effect of hydrogen on the mechanical properties of metallic alloys is known to reduce the applicability of metallic alloys, motivating the characterization and simulation of hydrogen-defect interactions in these materials. In this work, the interaction of hydrogen with planar defects in aluminium has been investigated by means of ab initio simulations.
On the one hand, two distinct types of GBs have been considered – the Σ11(113) [011] with a close-packed interface structure and the Σ5(210) [001] with a more open interface structure – in order to reveal the mechanisms governing the H segregation energetics. The investigations are afterwards extended to the impact of solutes in the Al alloy. Two scenarios are compared: Their segregation to the grain boundaries and their binding in precipitates. We therewith gained insights into the role of the solute size on the structural and chemical embrittlement in absence and presence of hydrogen. A thermodynamic assessment of the impact of solutes onto H chemisorption in the interfacial vicinity is provided by performing a high-throughput analysis for potential alloying candidates. The identified trends of the solute-H interactions are used to examine the relative importance of changes in hydrogen enhanced decohesion as a thermodynamic effect.
On the other hand, the interaction of hydrogen with defects can be beneficial for the formation of metal hydrides. To enhance the formation and stability of such often highly volatile hydrides we have consider a novel concept: tailoring and employing the negative pressure of microstructural and structural defects to enhance H solubility and thus hydride formation. Using systematic ab initio and atomistic simulations, we demonstrate that an enhancement in the formation of hydrides at the negatively pressurized crack tip region is feasible by increasing the mechanical tensile load on the specimen. The theoretical predictions have been used to reassess and interpret atom probe tomography experiments for a high-strength 7XXX-aluminium alloy that show a substantial enhancement of hydrogen concentration at structural defects near a stress-corrosion crack tip. Based on these insights we derive strategies for enhancing the capability of metals as H-storage materials.