A percolating path to green iron.

About 1.9 gigatons of steel is produced every year, emitting 8% (3.6 gigatons) of global CO in the process.

Next generation fatigue crack growth experiments of aerospace materials.

Today's societal challenges require rapid response and smart materials solutions in almost all technical areas. Driven by these needs, data-driven research has emerged as an enabler for faster innovation cycles. In fields such as chemistry, materials science and life sciences, automatic and even autonomous data generation and processing is already accelerating knowledge discovery.

Damage Mechanisms and Anisotropy of an AA7010-T7452 Open-Die Forged Alloy: Fatigue Crack Propagation.

The process-microstructure-property relationship of high-strength 7000 series aluminum alloys during fatigue crack propagation (FCP) is highly relevant for safety during the design and service of aircraft structural components. It is scientifically evident that many metallurgical factors affect FCP properties, but partly contradictory or inconclusive results show that the quantitative description of the relationships is still a major challenge among researchers and engineers. Most research focuses on sheet or plate products and investigations lack quantitative information on the process-property relationship between open-die forged thick products and FCP.

Explainable machine learning for precise fatigue crack tip detection.

Data-driven models based on deep learning have led to tremendous breakthroughs in classical computer vision tasks and have recently made their way into natural sciences. However, the absence of domain knowledge in their inherent design significantly hinders the understanding and acceptance of these models. Nevertheless, explainability is crucial to justify the use of deep learning tools in safety-relevant applications such as aircraft component design, service and inspection.

Interface-Mediated Twinning-Induced Plasticity in a Fine Hexagonal Microstructure Generated by Additive Manufacturing.

The grain size is a determinant microstructural feature to enable the activation of deformation twinning in hexagonal close-packed (hcp) metals. Although deformation twinning is one of the most effective mechanisms for improving the strength-ductility trade-off of structural alloys, its activation is reduced with decreasing grain size. This work reports the discovery of the activation of deformation twinning in a fine-grained hcp microstructure by introducing ductile body-centered cubic (bcc) nano-layer interfaces.

Pyrometric-Based Melt Pool Monitoring Study of CuCr1Zr Processed Using L-PBF.

The potential of in situ melt pool monitoring (MPM) for parameter development and furthering the process understanding in Laser Powder Bed Fusion (LPBF) of CuCr1Zr was investigated. Commercial MPM systems are currently being developed as a quality monitoring tool with the aim of detecting faulty parts already in the build process and, thus, reducing costs in LPBF. A detailed analysis of coupon specimens allowed two processing windows to be established for a suitably dense material at layer thicknesses of 30 µm and 50 µm, which were subsequently evaluated with two complex thermomechanical-fatigue (TMF) panels.

Pandora's Box-Influence of Contour Parameters on Roughness and Subsurface Residual Stresses in Laser Powder Bed Fusion of Ti-6Al-4V.

The contour scan strategies in laser powder bed fusion (LPBF) of Ti-6Al-4V were studied at the coupon level. These scan strategies determined the surface qualities and subsurface residual stresses. The correlations to these properties were identified for an optimization of the LPBF processing.

Semantic segmentation of synchrotron tomography of multiphase Al-Si alloys using a convolutional neural network with a pixel-wise weighted loss function.

Human-based segmentation of tomographic images can be a tedious time-consuming task. Deep learning algorithms and, particularly, convolutional neural networks have become state of the art techniques for pattern recognition in digital images that can replace human-based image segmentation. However, their use in materials science is beginning to be explored and their application needs to be adapted to the specific needs of this field.

Special Issue: Thermo-Mechanical Behaviour of Structural Lightweight Alloys.

The need to reduce the ecological footprint of (water, land, air) vehicles in this era of climate change requires pushing the limits in the development of lightweight structures and materials [...

Peritectic titanium alloys for 3D printing.

Metal-based additive manufacturing (AM) permits layer-by-layer fabrication of near net-shaped metallic components with complex geometries not achievable using the design constraints of traditional manufacturing. Production savings of titanium-based components by AM are estimated up to 50% owing to the current exorbitant loss of material during machining. Nowadays, most of the titanium alloys for AM are based on conventional compositions still tailored to conventional manufacturing not considering the directional thermal gradient that provokes epitaxial growth during AM.

Revealing the Effect of Local Connectivity of Rigid Phases during Deformation at High Temperature of Cast AlSi12Cu4Ni(2,3)Mg Alloys.

The 3D microstructure and its effect on damage formation and accumulation during tensile deformation at 300 °C for cast, near eutectic AlSi12Cu4Ni2Mg and AlSi12Cu4Ni3Mg alloys has been investigated using in-situ synchrotron micro-tomography, complemented by conventional 2D characterization methods. An increase of Ni from 2 to 3 wt.% leads to a higher , quantified by the Euler number , at constant of rigid 3D networks formed by primary and eutectic Si and intermetallics owing to the formation of the plate-like Al-Ni-Cu-rich δ-phase.

An Assessment of Subsurface Residual Stress Analysis in SLM Ti-6Al-4V.

Ti-6Al-4V bridges were additively fabricated by selective laser melting (SLM) under different scanning speed conditions, to compare the effect of process energy density on the residual stress state. Subsurface lattice strain characterization was conducted by means of synchrotron diffraction in energy dispersive mode. High tensile strain gradients were found at the frontal surface for samples in an as-built condition.

Inducing Stable α + β Microstructures during Selective Laser Melting of Ti-6Al-4V Using Intensified Intrinsic Heat Treatments.

Selective laser melting is a promising powder-bed-based additive manufacturing technique for titanium alloys: near net-shaped metallic components can be produced with high resource-efficiency and cost savings [...

Non-negative matrix factorization for the near real-time interpretation of absorption effects in elemental distribution images acquired by X-ray fluorescence imaging.

Elemental distribution images acquired by imaging X-ray fluorescence analysis can contain high degrees of redundancy and weakly discernible correlations. In this article near real-time non-negative matrix factorization (NMF) is described for the analysis of a number of data sets acquired from samples of a bi-modal α+β Ti-6Al-6V-2Sn alloy. NMF was used for the first time to reveal absorption artefacts in the elemental distribution images of the samples, where two phases of the alloy, namely α and β, were in superposition.

3D elemental sensitive imaging using transmission X-ray microscopy.

Determination of the heterogeneous distribution of metals in alloy/battery/catalyst and biological materials is critical to fully characterize and/or evaluate the functionality of the materials. Using synchrotron-based transmission x-ray microscopy (TXM), it is now feasible to perform nanoscale-resolution imaging over a wide X-ray energy range covering the absorption edges of many elements; combining elemental sensitive imaging with determination of sample morphology. We present an efficient and reliable methodology to perform 3D elemental sensitive imaging with excellent sample penetration (tens of microns) using hard X-ray TXM.

A comparative study of high resolution cone beam X-ray tomography and synchrotron tomography applied to Fe- and Al-alloys.

X-ray computed tomography (XCT) has become a very important method for non-destructive 3D-characterization and evaluation of materials. Due to measurement speed and quality, XCT systems with cone beam geometry and matrix detectors have gained general acceptance. Continuous improvements in the quality and performance of X-ray tubes and XCT devices have led to cone beam CT systems that can now achieve spatial resolutions down to 1 μm and even below.