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Planning an academic career is a bit like enjoying a box of chocolate – you never know what you are going to get next. In this talk, I will begin with sharing how luck, difficult decisions, fate, and family constraints affected my career path across continents, universities, the private sector, and to becoming a director at a national laboratory. This journey was certainly not planned and highlights how opportunities and compromises together allow you to make much more out of your engineering degree than you ever have dreamed of.
After this unusual journey as a materials scientist, I am transitioning to the technical part of my talk, where we will discuss transport in metallic glasses. This out-of-equilibrium material has a long suite of remarkable mechanical and physical properties but suffers from property deterioration via physical aging. As a function of time, relaxation may indeed constitute significant threads to safe applications, such as a complete loss of toughness.
In the search for a physical understanding of aging, we exploit here the ability to track atomic-scale dynamics with coherent x-ray scattering. Conducted across temperatures and under the application of stress, the results reveal unexpected transport. In concert with microsecond molecular dynamic simulations, we identify possible mechanisms of atomic-scale dynamics that underly physical aging of metallic glasses. We find that classical Kohlrausch-Williams-Watts behavior is only suited for the short relaxation-time regime, whereas anomalous diffusion emerges at practically relevant times. We discuss these results in terms of the structural relaxation modes and propose a picture of a true microstructure in metallic glasses.
Plastic deformation in crystals is mediated by the motion of line defects known as dislocations. For decades, dislocation activity has been treated as a homogeneous, smooth continuous process that relies on well-average quantities. However, it is now recognized that plasticity can be determined by long-range correlated and intermittent collective dislocation activity, known as avalanches. These abrupt plastic fluctuations often exhibit pure power-law scaling or truncated power-law scaling, which indicates at least some degree of scale-free dislocation behavior. Intriguingly, such statistical signatures can persist across scales exceeding those of the material’s microstructure, raising the question of what relationship there may be between structure and long-range correlated dislocation activity that underlie power-law scaling.
In this talk, we address this question by highlighting examples in which a transition from scale-free to scale-dependent plastic deformation is observed either due to changing external testing conditions (stress-state or temperature) or by tuning the microstructure. In particular, we will focus on the details of the temperature-driven change, that demonstrates how scale-free intermittent flow in body-centered cubic Nb is progressively quenched out with decreasing temperature. The plastic response of Nb is shown to be bimodal across the studied temperature regime, with conventional thermally-activated smooth plastic flow coexisting with sporadic bursts controlled by athermal screw dislocation activity, thereby violating the classical notion of temperature-dependent screw dislocation motion at low temperatures. An abrupt increase of the athermal avalanche component is identified at the critical temperature of the material. We combine the experimental observations with 3D dislocation dynamics simulations, identify a possible origin to athermal screw activity, and discuss the co-existence scale-free and scale-dependent plasticity.
Bonds and local atomic environments are crucial descriptors of material properties. They have been used to create design rules and heuristics and as features in machine learning of materials properties. Implementations and algorithms (e.g., ChemEnv and LobsterEnv) for identifying local atomic environments based on geometrical characteristics and quantum-chemical bonding analysis are nowadays available. Fully automatic workflows and analysis tools have been developed to use quantum-chemical bonding analysis on a large scale. The lecture will demonstrate how our tools, that assess local atomic environments and perform automatic bonding analysis, help to develop new machine learning models and a new intuitive understanding of materials. Furthermore, the general trend toward automation in computational materials science and some of our recent contributions will be discussed.
One contribution of materials science to energy efficiency is the continuous development of novel high-performance structural materials that push the strength-ductility envelope. A prominent example are modern advanced high-strength steels (AHSSs), which have enabled considerable weight reductions in the automotive sector, thereby enabling greenhouse emission reductions. To protect such advanced alloys from property degradation via corrosion, zinc (Zn) coatings are often applied through galvanization. Whilst protective, a Zn-coating comes with problems – the AHSS substrate becomes susceptible for liquid-metal embrittlement (LME) than can be the origin of significant mechanical property degradation when liquified Zn infiltrates into the steel substrate. Being for from understood, we focus here on non-cracked environments to capture the early stages of LME. This approach revealed the nucleation and growth of nano-scale intermetallic phases inside uncracked GBs (Materials Today Advances 13, 100196, 2022), highlighting the complex multi-phase microstructure developing before cracking occurs. To shed further light on the early stages of LME in AHSSs, we also consider the microstructural evolution of interrupted welds. We discuss our findings in the context of the time-resolved substructure evolution right beneath the interface between the AHSS and the Zn-based coating and track how Zn progressively infiltrates the substrate along phase and grain boundaries. The experimental results are further corroborated with thermodynamic simulations.
The investigation of the long-term performance of sealing systems employed in containers for radioactive waste and spent nuclear fuel is one research focus area for division 3.4 “Safety of Storage Containers” at the Bundesanstalt für Materialforschung und -prüfung. Metallic seals are in use in interim storage casks for used fuel and high active waste. Their change in performance over time is of high importance for maintaining safe enclosure. Therefore, investigations on these systems were started at BAM to get a general understanding of the relevant processes. Our investigations comprise investigations on different parameters which influence the seal performance and the main part is focussed on the time and temperature dependent behaviour.
In this contribution an update on the performed tests and their respective results will be given in respect to the overview presented in 2020.
The understanding of the long-term behaviour of the sealing systems and the performance evaluation during interim storage and subsequent transportation are our goals.
The amount of absorbed energy in the keyhole as well as its distribution is essential to model the laser beam welding process. The recoil pressure is a key determining factor for the macroscopic flow of the molten metal in the weld pool during high-power laser beam welding. Consequently, a realistic implementation of the laser radiation on the weld metal is crucial to obtain accurate simulation results.
The following developments on the laser-material interaction are discussed for the numerical simulation of the laser beam welding process. The first implemented improvements relate to locating the exact reflection points in the ray tracing method in the determination algorithm for the intersection of the reflected rays and the keyhole surface. A second correction refers to the numerical treatment of the Gaussian distribution of the laser beam, whose beam width is defined by a decay of the laser intensity by a factor of 1/e2 thus ignoring around 14 % of the total laser beam energy. In a third step, the laser radiation distribution in vertical direction was approximated according to the beam caustics. Finally, a virtual mesh refinement was adopted in the ray tracing routine. The obtained numerical results were validated with experimental measurements.
The DACHS (Database for Automation, Characterization and Holistic Synthesis) project aims to create completely traceable experimental data, covering syntheses, measurements, analyses, and interpretations. DACHS_MOFs focuses on the synthesis and characterisation of metal-organic frameworks, across multiple, automation-assisted experimental series (AutoMOFs), with the overall goal of producing reproducible MOF samples through tracking of the synthesis parameters.
DACHS_MOFs is simultaneously used to test the DACHS principles.
This upload contain synthesis data from AutoMOFs_3 in HDF5 format (.h5). Each .h5 file contains detailed information on the chemical, experimenal, and synthesis parameters used during the synthesis of a single AutoMOF sample.
Since we are facing more extreme weathers, the occurrence
of wildfire has also increased accordingly. The EU project
TREEADS aims to adopt a holistic forest fire management
and an adaptive, collaborative governance approach based
on the deployment of a new systemic and technological
framework covering all three interconnected fire
management stages: prevention & preparedness, detection &
response, and restoration & adaptation.
As part of the task in the so-called German pilot, numerical
simulations are performed to investigate the influencing
factors for vegetation fires with fire dynamics simulator
(FDS). The characteristics of vegetation are strongly related
to the local weather and ecosystem. The investigation of the
fire behavior of vegetation must be based on the local
vegetation in Germany. Thus, the flame propagation of typical
vegetation in Germany (pine needles, oak leaves, European
beech leaves etc.) was investigated in small scale and medium
scale experiments. These results are used as validation case
studies for the further simulations.
Defects are still common in metal components built with Additive Manufacturing (AM). Process monitoring methods for laser powder bed fusion (PBF-LB/M) are used in industry, but relationships between monitoring data and defect formation are not fully understood yet. Additionally, defects and deformations may develop with a time delay to the laser energy input. Thus, currently, the component quality is only determinable after the finished process.
Here, active laser thermography, a nondestructive testing method, is adapted to PBF-LB/M, using the defocused process laser as heat source. The testing can be performed layer by layer throughout the manufacturing process. We study our proposed testing method along experiments carried out on a custom research PBF-LB/M machine using infrared (IR) cameras.
Our work enables a shift from post-process testing of components towards in-situ testing during the AM process. The actual component quality is evaluated in the process chamber and defects can be detected between layers.