Open Access

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.

Metallic glasses (MGs) are disordered solids that exhibit a range of outstanding mechanical, thermomechanical, and functional properties. Whilst being a promising class of structural materials, well-defined and exploitable structure-property relationships are still lacking. This offsets them strongly from the crystalline counterparts, for which length-scale based property determination has been key for decades. In recent years, both atomistic simulations and experiments have nurtured the view of heterogeneities that manifest themselves either as a structural partitioning into well-relaxed percolated network components and more frustrated domains in atomistic simulations, or as spatially-resolved property fluctuations revealed with atomic force microscopy. These signatures depend sensitively on the processing history and likely reflect emerging medium-range order fluctuations at the scale of 1-10 nanometers. Here we demonstrate and discuss the emergence of spatially resolved property fluctuations at length scales that are one to two orders of magnitude larger. Such long-range decorrelation length scales are hard to reconcile in a monolithic glass but may offer the perspective of experimentally easy-to-access length-scale based structure-property relationships. Whilst long-range property fluctuations can be seen in both the plastic and elastic response, we focus here on high-throughput elastic nanoindentation mapping across the surface of a Zr-based model glass. After a deconvolution of surface topography and curvature effects, the spatially-resolved elastic response reveals an elastic microstructure with a correlation length of ca. 150-170 nm. Analytical scanning-transmission electron microscopy (STEM) is used to link the elastic property fluctuations to the chemistry and structure of the MG. In concert, nano-elastic mapping and STEM suggests that structural variations in the glass are responsible for the unexpectedly large length scales. We discuss these findings in terms of the materials processing history and the perspective of exploiting nanoindentation-based spatial mapping to uncover structural length scales in atomically disordered solids.

Liquid-metal embrittlement (LME) of galvanized (Zn-coated) advanced high-strength steels is a long-known problem in materials science. Here we reveal the initial microstructural processes underneath the Zn-coating that lead to LME-microcrack initiation in the steel substrate. We track the microstructural evolution during the first tens of milliseconds and find pronounced signatures of Fe-Zn intermetallic precipitation in both ferrite grain boundaries and at internal ferrite-oxide phase boundaries. In concert with novel CALPHAD-integrated density-based thermodynamic modelling, we demonstrate that Zn-rich intermetallic phase-nucleation can occur at markedly low processing temperatures due to a segregation transition. We show that a small Znenrichment caused by Zn bulk-diffusion during the initial temperature rise in a joining process is sufficient to induce the segregation transition and subsequent nucleation of Fe-Zn intermetallic grain-boundary phases, which the experiments link to crack initiation sites. These findings direct focus onto LME-controlling microstructural and thermodynamic phenomena at temperatures below the ductility trough and the austenite formation temperature.

We present an easy-to-apply method to predict structural trends in the internal nucleation tendency of oxide glasses. The approach is based on calculated crystal fracture surface energies derived from easily accessible diatomic bond energy and crystal lattice data. The applicability of the method is demonstrated on literature nucleation data for isochemically crystallizing oxide glasses.

Comprehensive materials characterization requires precise structural knowledge beyond traditional methods. The robot-assisted automated serial-sectioning and imaging (RASI) platform, developed at BAM, provides automated 3D metallographic reconstructions, enabling detailed microstructural analysis of technical materials. This article showcases RASI’s capabilities through several case studies, including characterization of lamellar graphite in gray cast iron, porosity in sintered steel, melt pool morphology in additively manufactured 316L stainless steel, defects in metal-ceramic packages, and oxidation behavior in an Fe-12Cr-2Co alloy. By automating sample handling, mechanical serial-sectioning, etching, and optical imaging, RASI captures complex 3D microstructures with high precision and at high speed. This approach reveals microstructural features missed by 2D analysis, even using stereological assumptions. Specifically, statistically rare and large microstructural features, such as secondary phases or interconnected pores, become apparent, which 2D methods cannot reveal. The generated volumetric data can furthermore serve as quantitative reference datasets (i.e., the ‘ground truth’) essential for validating other 3D characterization techniques and computational models, helping to bridge the gap between predictive simulations and real-world material behavior. RASI’s modular design makes it a flexible tool that provides realistic 3D insights into materials, which can be used for advanced materials research, process optimization, and quality control.