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- ItemAn AI-based open recommender system for personalized labor market driven education(Amsterdam [u.a.] : Elsevier Science, 2022) Tavakoli, Mohammadreza; Faraji, Abdolali; Vrolijk, Jarno; Molavi, Mohammadreza; Mol, Stefan T.; Kismihók, GáborAttaining those skills that match labor market demand is getting increasingly complicated, not in the last place in engineering education, as prerequisite knowledge, skills, and abilities are evolving dynamically through an uncontrollable and seemingly unpredictable process. Anticipating and addressing such dynamism is a fundamental challenge to twenty-first century education. The burgeoning availability of data, not only on the demand side but also on the supply side (in the form of open educational resources) coupled with smart technologies, may provide a fertile ground for addressing this challenge. In this paper, we propose a novel, Artificial Intelligence (AI) driven approach to the development of an open, personalized, and labor market oriented learning recommender system, called eDoer. We discuss the complete system development cycle starting with a systematic user requirements gathering, and followed by system design, implementation, and validation. Our recommender prototype (1) derives the skill requirements for particular occupations through an analysis of online job vacancy announcements
- ItemFrom microfluidics to hierarchical hydrogel materials(Amsterdam [u.a.] : Elsevier Science, 2023) Weigel, Niclas; Li, Yue; Fery, Andreas; Thiele, JulianOver the past two decades, microfluidics has made significant contributions to material and life sciences, particularly via the design of nano-, micro- and mesoscale materials such as nanoparticles, micelles, vesicles, emulsion droplets, and microgels. Unmatched in control over a multitude of material parameters, microfluidics has also shed light on fundamental aspects of material design such as the early stages of nucleation and growth processes as well as structure evolution. Exemplarily, polymer hydrogel particles can be formed via microfluidics with exact control over size, shape, functionalization, compartmentalization, and mechanics that is hardly found in any other processing method. Interestingly, the utilization of microfluidics for material design largely focuses on the fabrication of single entities that act as reaction volume for organic and cell-free biosynthesis, cell mimics, or local environment for cell culturing. In recent years, however, hydrogel design has shifted towards structures that integrate a large variety of functions, e.g., to address the demands for sensing tasks in a complex environment or more closely mimicking architecture and organization of tissue by multiparametric cultures. Hence, this review provides an overview of recent literature that explores microfluidics for fabricating hydrogel materials that go well beyond common length scales as well as the structural and functional complexity of microgels necessary to produce hierarchical hydrogel structures. We focus on examples that utilize microfluidics to design microgel-based assemblies, on microfluidically made polymer microgels for 3D bioprinting, on hydrogels fabricated by microfluidics in a continuous fashion, like fibers, and on hydrogel structures that are shaped by microchannels.
- ItemMicrobiome-based biotechnology for reducing food loss post harvest(Amsterdam [u.a.] : Elsevier Science, 2022) Wassermann, Birgit; Abdelfattah, Ahmed; Cernava, Tomislav; Wicaksono, Wisnu; Berg, GabrieleMicrobiomes have an immense potential to enhance plant resilience to various biotic and abiotic stresses. However, intrinsic microbial communities respond to changes in their host's physiology and environment during plant's life cycle. The potential of the inherent plant microbiome has been neglected for a long time, especially for the postharvest period. Currently, close to 50% of all produced fruits and vegetables are lost either during production or storage. Biological control of spoilage and storage diseases is still lacking sufficiency. Today, novel multiomics technologies allow us to study the microbiome and its responses on a community level, which will help to advance current classic approaches and develop more effective and robust microbiome-based solutions for fruit and vegetable storability, quality, and safety.
- ItemA novel approach to fabricate load-bearing Ti6Al4V-Barium titanate piezoelectric bone scaffolds by coupling electron beam melting and field-assisted sintering(Amsterdam [u.a.] : Elsevier Science, 2022) Riaz, Abdullah; Polley, Christian; Lund, Henrik; Springer, Armin; Seitz, HermannA critical-size bone defect in load-bearing areas is a challenging clinical problem in orthopaedic surgery. Titanium alloy (Ti6Al4V) scaffolds have advantages because of their biomechanical stability but lack electrical activity, which hinders their further use. This work is focused on the fabrication of Ti6Al4V-Barium Titanate (BaTiO3) bulk composite scaffolds to combine the biomechanical stability of Ti6Al4V with electrical activity through BaTiO3. For the first time, a hollow cylindrical Ti6Al4V is additively manufactured by electron beam melting and combined with piezoelectric BaTiO3 powder for joint processing in field-assisted sintering. Scanning electron microscope images on the interface of the Ti6Al4V-BaTiO3 composite scaffold showed that after sintering, the Ti6Al4V lattice structure bounded with BaTiO3 matrix without its major deformation. The Ti6Al4V-BaTiO3 scaffold had average piezoelectric constants of (0.63 ± 0.12) pC/N directly after sintering due to partial dipole alignment of the BaTiO3 tetragonal phase, which increased to (4.92 ± 0.75) pC/N after a successful corona poling. Moreover, the nanoindentation values of Ti6Al4V exhibited an average hardness and Young's modulus of (5.9 ± 0.9) GPa and (130 ± 14) GPa, and BaTiO3 showed (4.0 ± 0.6) GPa and (106 ± 10) GPa, respectively. It reveals that the Ti6Al4V is the harder and stiffer part in the Ti6Al4V-BaTiO3 composite scaffold. Such a scaffold has the potential to treat critical-size bone defects in load-bearing areas and guide tissue regeneration by physical stimulation.
- ItemExperimental and numerical characterization of imperfect additively manufactured lattices based on triply periodic minimal surfaces(Amsterdam [u.a.] : Elsevier Science, 2023) Günther, Fabian; Pilz, Stefan; Hirsch, Franz; Wagner, Markus; Kästner, Markus; Gebert, Annett; Zimmermann, MartinaLattices based on triply periodic minimal surfaces (TPMS) are attracting increasing interest in seminal industries such as bone tissue engineering due to their excellent structure-property relationships. However, the potential can only be exploited if their structural integrity is ensured. This requires a fundamental understanding of the impact of imperfections that arise during additive manufacturing. Therefore, in the present study, the structure-property relationships of eight TPMS lattices, including their imperfections, are investigated experimentally and numerically. In particular, the focus is on biomimetic network TPMS lattices of the type Schoen I-WP and Gyroid, which are fabricated by laser powder bed fusion from the biocompatible alloy Ti-42Nb. The experimental studies include computed tomography measurements and compression tests. The results highlight the importance of process-related imperfections on the mechanical performance of TPMS lattices. In the numerical work, firstly the as-built morphology is artificially reconstructed before finite element analyses are performed. Here, the reconstruction procedure previously developed by the same authors is used and validated on a larger experimental matrix before more advanced calculations are conducted. Specifically, the reconstruction reduces the numerical overestimation of stiffness from up to 341% to a maximum of 26% and that of yield strength from 66% to 12%. Given a high simulation accuracy and flexibility, the presented procedure can become a key factor in the future design process of TPMS lattices.
- ItemMachine learning for additive manufacturing: Predicting materials characteristics and their uncertainty(Amsterdam [u.a.] : Elsevier Science, 2023) Chernyavsky, Dmitry; Kononenko, Denys Y.; Han, Jun Hee; Kim, Hwi Jun; van den Brink, Jeroen; Kosiba, KonradAdditive manufacturing (AM) is known for versatile fabrication of complex parts, while also allowing the synthesis of materials with desired microstructures and resulting properties. These benefits come at a cost: process control to manufacture parts within given specifications is very challenging due to the relevance of a large number of processing parameters. Efficient predictive machine learning (ML) models trained on small datasets, can minimize this cost. They also allow to assess the quality of the dataset inclusive of uncertainty. This is important in order for additively manufactured parts to meet property specifications not only on average, but also within a given variance or uncertainty. Here, we demonstrate this strategy by developing a heteroscedastic Gaussian process (HGP) model, from a dataset based on laser powder bed fusion of a glass-forming alloy at varying processing parameters. Using amorphicity as the microstructural descriptor, we train the model on our Zr52.5Cu17.9Ni14.6Al10Ti5 (at.%) alloy dataset. The HGP model not only accurately predicts the mean value of amorphicity, but also provides the respective uncertainty. The quantification of the aleatoric and epistemic uncertainty contributions allows to assess intrinsic inaccuracies of the dataset, as well as identify underlying physical phenomena. This HGP model approach enables to systematically improve ML-driven AM processes.
- ItemControlling the Young’s modulus of a ß-type Ti-Nb alloy via strong texturing by LPBF(Amsterdam [u.a.] : Elsevier Science, 2022) Pilz, Stefan; Gustmann, Tobias; Günther, Fabian; Zimmermann, Martina; Kühn, Uta; Gebert, AnnettThe ß-type Ti-42Nb alloy was processed by laser powder bed fusion (LPBF) with an infrared top hat laser configuration aiming to control the Young’s modulus by creating an adapted crystallographic texture. Utilizing a top hat laser, a microstructure with a strong 〈0 0 1〉 texture parallel to the building direction and highly elongated grains was generated. This microstructure results in a strong anisotropy of the Young’s modulus that was modeled based on the single crystal elastic tensor and the experimental texture data. Tensile tests along selected loading directions were conducted to study the mechanical anisotropy and showed a good correlation with the modeled data. A Young’s modulus as low as 44 GPa was measured parallel to the building direction, which corresponds to a significant reduction of over 30% compared to the Young’s modulus of the Gaussian reference samples (67–69 GPa). At the same time a high 0.2% yield strength of 674 MPa was retained. The results reveal the high potential of LPBF processing utilizing a top hat laser configuration to fabricate patient-specific implants with an adapted low Young’s modulus along the main loading direction and a tailored mechanical biofunctionality.
- ItemConstrained incipient phase transformation in Ni-Mn-Ga films: A small-scale design challenge(Amsterdam [u.a.] : Elsevier Science, 2023) Fareed, Adnan; Rosalie, Julian M.; Kumar, Sourabh; Kar, Satyakam; Hickel, Tilmann; Fähler, Sebastian; Maaß, RobertNi-Mn-Ga shape-memory alloys are promising candidates for large strain actuation and magnetocaloric cooling devices. In view of potential small-scale applications, we probe here nanomechanically the stress-induced austenite–martensite transition in single crystalline austenitic thin films as a function of temperature. In 0.5 µm thin films, a marked incipient phase transformation to martensite is observed during nanoindentation, leaving behind pockets of residual martensite after unloading. These nanomechanical instabilities occur irrespective of deformation rate and temperature, are Weibull distributed, and reveal large spatial variations in transformation stress. In contrast, at a larger film thickness of 2 μm fully reversible transformations occur, and mechanical loading remains entirely smooth. Ab-initio simulations demonstrate how an in-plane constraint can considerably increase the martensitic transformation stress, explaining the thickness-dependent nanomechanical behavior. These findings for a shape-memory Heusler alloy give insights into how reduced dimensions and constraints can lead to unexpectedly large transformation stresses that need to be considered in small-scale actuation design.
- ItemDesigning the microstructural constituents of an additively manufactured near β Ti alloy for an enhanced mechanical and corrosion response(Amsterdam [u.a.] : Elsevier Science, 2022) Hariharan, Avinash; Goldberg, Phil; Gustmann, Tobias; Maawad, Emad; Pilz, Stefan; Schell, Frederic; Kunze, Tim; Zwahr, Christoph; Gebert, AnnettAdditive manufacturing of near β-type Ti-13Nb-13Zr alloys using the laser powder bed fusion process (LPBF) opens up new avenues to tailor the microstructure and subsequent macro-scale properties that aids in developing new generation patient-specific, load-bearing orthopedic implants. In this work, we investigate a wide range of LPBF parameter space to optimize the volumetric energy density, surface characteristics and melt track widths to achieve a stable process and part density of greater than 99 %. Further, optimized sample states were achieved via thermal post-processing using standard capability aging, super-transus (900 °C) and sub-transus (660 °C) heat treatment strategies with varying quenching mediums (air, water and ice). The applied heat treatment strategies induce various fractions of α, martensite (α', α'') in combination with the β phase and strongly correlated with the observed enhanced mechanical properties and a relatively low elastic modulus. In summary, our work highlights a practical strategy for optimizing the mechanical and corrosion properties of a LPBF produced near β-type Ti-13Nb-13Zr alloy via careful evaluation of processing and post-processing steps and the interrelation to the corresponding microstructures. Corrosion studies revealed excellent corrosion resistances of the heat-treated LPBF samples comparable to wrought Ti-13Nb-13Zr alloys.
- ItemAdditively manufactured AlSi10Mg lattices – Potential and limits of modelling as-designed structures(Amsterdam [u.a.] : Elsevier Science, 2022) Gebhardt, Ulrike; Gustmann, Tobias; Giebeler, Lars; Hirsch, Franz; Hufenbach, Julia Kristin; Kästner, MarkusAdditive manufacturing overcomes the restrictions of classical manufacturing methods and enables the production of near-net-shaped, complex geometries. In that context, lattice structures are of high interest due to their superior weight reduction potential. AlSi10Mg is a well-known alloy for additive manufacturing and well suited for such applications due to its high strength to material density ratio. It has been selected in this study for producing bulk material and complex geometries of a strut-based lattice type (rhombic dodecahedron). A detailed characterisation of as-built and heat-treated specimens has been conducted including microstructural analyses, identification of imperfections and rigorous mechanical testing under different load conditions. An isotropic elastic–plastic material model is deduced on the basis of tension test results of bulk material test specimens. Performed experiments under compression, shear, torsion and tension load are compared to their virtual equivalents. With the help of numerical modelling, the overall structural behaviour was simulated using the detailed lattice geometry and was successfully predicted by the presented numerical models. The discussion of the limits of this approach aims to evaluate the potential of the numerical assessment in the modelling of the properties for novel lightweight structures.