TY - JOUR A1 - Tavasolyzadeh, Zeynab A1 - Tang, Peng A1 - Hahn, Marc Benjamin A1 - Hweidi, Gada A1 - Nordholt, Niclas A1 - Haag, Rainer A1 - Sturm, Heinz A1 - Topolniak, Ievgeniia T1 - 2D and 3D Micropatterning of Mussel‐Inspired Functional Materials by Direct Laser Writing JF - Small : nano micro N2 - AbstractThis work addresses the critical need for multifunctional materials and substrate‐independent high‐precision surface modification techniques that are essential for advancing microdevices and sensing elements. To overcome existing limitations, the versatility of mussel‐inspired materials (MIMs) is combined with state‐of‐the‐art multiphoton direct laser writing (DLW) microfabrication. In this way, 2D and 3D MIM microstructures of complex designs are demonstrated with sub‐micron to micron resolution and extensive post‐functionalization capabilities. This study includes polydopamine (PDA), mussel‐inspired linear, and dendritic polyglycerols (MI‐lPG and MI‐dPG), allowing their direct microstructure on the substrate of choice with the option to tailor the patterned topography and morphology in a controllable manner. The functionality potential of MIMs is demonstrated by successfully immobilizing and detecting single‐stranded DNA on MIM micropattern and nanoarray surfaces. In addition, easy modification of MIM microstructure with silver nanoparticles without the need of any reducing agent is shown. The methodology developed here enables the integration of MIMs in advanced applications where precise surface functionalization is essential. KW - Direct laser writing KW - Mussel-inspired materials KW - Polyglycerol KW - Polydopamine KW - Micropatterning PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-588778 DO - https://doi.org/10.1002/smll.202309394 SN - 1613-6829 SP - 1 EP - 12 PB - Wiley-VCH CY - Weinheim AN - OPUS4-58877 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Kindrachuk, Vitaliy A1 - Darvishi Kamachali, Reza T1 - Mean-field modeling and phase-field simulation of grain growth under directional driving forces JF - Materialia N2 - Directional grain growth is a common phenomenon in the synthetic and natural evolution of various polycrystals. It occurs in the presence of an external driving force, such as a temperature gradient, along which grains show a preferred, yet competitive, growth. Novel additive manufacturing processes, with intense, localized energy deposition, are prominent examples of when directional grain growth can occur, beneath the melting pool. In this work, we derive a phenomenological mean-field model and perform 3D phase-field simulations to investigate the directional grain growth and its underlying physical mechanisms. The effect of the intensity of driving force is simulated and systematically analyzed at the evolving growth front as well as various cross-sections perpendicular to the direction of the driving force. We found that although the directional growth significantly deviates from normal grain growth, it is still governed by a power law relation α tⁿ with an exponent n ~ 0.6–0.7. The exponent n exhibits a nontrivial dependence on the magnitude of the directional driving force, such that the lowest growth exponent is observed for intermediate driving forces. We elaborate that this can originate from the fact that the forces at grain boundary junctions evolve out of balance under the influence of the directional driving force. With increasing the driving forces, the growth exponent asymptotically approaches a value of n ≈ 0.63, imposed by the largest possible grain aspect ratio for given grain boundary energies. The current combined mean-field and phase-field framework pave the way for future exploration in broader contexts such as the evolution of complex additively manufactured microstructures. KW - Additive manufacturing KW - Phase-field simulation KW - Grain growth KW - Mean-field modelling KW - Directional grain growth PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-593210 DO - https://doi.org/10.1016/j.mtla.2023.101989 SN - 2589-1529 VL - 33 SP - 1 EP - 10 PB - Elsevier AN - OPUS4-59321 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Ginés-Palomares, Juan Carlos A1 - Fateri, Miranda A1 - Kalhöfer, Eckhard A1 - Schubert, Tim A1 - Meyer, Lena A1 - Kolsch, Nico A1 - Brandic Lipinska, Monica A1 - Davenport, Robert A1 - Imhof, Barbara A1 - Waclavicek, René A1 - Sperl, Matthias A1 - Makaya, Advenit A1 - Günster, Jens T1 - Laser melting manufacturing of large elements of lunar regolith simulant for paving on the Moon JF - nature scientific reports N2 - The next steps for the expansion of the human presence in the solar system will be taken on the Moon. However, due to the low lunar gravity, the suspended dust generated when lunar rovers move across the lunar soil is a significant risk for lunar missions as it can affect the systems of the exploration vehicles. One solution to mitigate this problem is the construction of roads and landing pads on the Moon. In addition, to increase the sustainability of future lunar missions, in-situ resource utilization (ISRU) techniques must be developed. In this paper, the use of concentrated light for paving on the Moon by melting the lunar regolith is investigated. As a substitute of the concentrated sunlight, a high-power CO2 laser is used in the experiments. With this set-up, a maximum laser spot diameter of 100 mm can be achieved, which translates in high thicknesses of the consolidated layers. Furthermore, the lunar regolith simulant EAC-1A is used as a substitute of the actual lunar soil. At the end of the study, large samples (approximately 250 × 250 mm) with interlocking capabilities were fabricated by melting the lunar simulant with the laser directly on the powder bed. Large areas of lunar soil can be covered with these samples and serve as roads and landing pads, decreasing the propagation of lunar dust. These manufactured samples were analysed regarding their ineralogical composition, internal structure and mechanical properties. KW - Regolith KW - ISRU KW - Moon KW - Laser KW - Additive manufacturing PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-585985 DO - https://doi.org/10.1038/s41598-023-42008-1 SN - 2045-2322 VL - 13 SP - 1 EP - 10 PB - Springer AN - OPUS4-58598 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Wandtke, Karsten A1 - Schröpfer, Dirk A1 - Scharf-Wildenhain, R. A1 - Hälsig, A. A1 - Kannengießer, Thomas A1 - Kromm, Arne A1 - Hensel, J. T1 - Influence of the WAAM process and design aspects on residual stresses in high-strength structural steels JF - Welding in the World N2 - Wire arc additive manufacturing (WAAM) enables the efficient production of weight-optimized modern engineering structures. Further increases in efficiency can be achieved by using high-strength structural steels. Commercial welding consumables for WAAM are already available on the market. Lack of knowledge and guidelines regarding welding residual stress and component safety during production and operation leads to severely limited use for industry applications. The sensitive microstructure of high-strength steels carries a high risk of cold cracking; therefore, residual stresses play a crucial role. For this reason, the influences of the material, the WAAM process, and the design on the formation of residual stresses and the risk of cold cracking are being investigated. The material used has a yield strength of over 800 MPa. This strength is adjusted via solid solution strengthening and a martensitic phase transformation. The volume expansion associated with martensite formation has a significant influence on the residual stresses. The focus of the present investigation is on the additive welding parameters and component design on their influence on hardness and residual stresses, which are analyzed by means of X-ray diffraction (XRD). Reference specimens (hollow cuboids) are welded fully automated with a systematic variation of heat control and design. Welding parameters and AM geometry are correlated with the resulting microstructure, hardness, and residual stress state. Increased heat input leads to lower tensile residual stresses which causes unfavorable microstructure and mechanical properties. The component design affects heat dissipation conditions and the intensity of restraint during welding and has a significant influence on the residual stress. KW - DED-arc KW - Additive manufacturing KW - High-strength steel filler metal KW - Residual stress PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-572698 DO - https://doi.org/10.1007/s40194-023-01503-9 SN - 1878-6669 VL - 67 IS - 4 SP - 987 EP - 996 PB - Springer CY - Berlin AN - OPUS4-57269 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Oster, Simon A1 - Scheuschner, Nils A1 - Chand, Keerthana A1 - Altenburg, Simon A1 - Gerlach, G. T1 - Potentials and challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring in laser powder bed fusion JF - Technisches Messen N2 - Laser powder bed fusion is one of the most promising additive manufacturing techniques for printing complex-shaped metal components. However, the formation of subsurface porosity poses a significant risk to the service lifetime of the printed parts. In-situ monitoring offers the possibility to detect porosity already during manufacturing. Thereby, process feedback control or a manual process interruption to cut financial losses is enabled. Short-wave infrared thermography can monitor the thermal history of manufactured parts which is closely connected to the probability of porosity formation. Artificial intelligence methods are increasingly used for porosity prediction from the obtained large amounts of complex monitoring data. In this study, we aim to identify the potential and the challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring. Therefore, the porosity prediction task is studied in detail using an exemplary dataset from the manufacturing of two Haynes282 cuboid components. Our trained 1D convolutional neural network model shows high performance (R² score of 0.90) for the prediction of local porosity in discrete sub-volumes with dimensions of (700 x 700 x 40) μm³. It could be demonstrated that the regressor correctly predicts layer-wise porosity changes but presumably has limited capability to predict differences in local porosity. Furthermore, there is a need to study the significance of the used thermogram feature inputs to streamline the model and to adjust the monitoring hardware. Moreover, we identified multiple sources of data uncertainty resulting from the in-situ monitoring setup, the registration with the ground truth X-ray-computed tomography data and the used pre-processing workflow that might influence the model’s performance detrimentally. T2 - XXXVII. Messtechnisches Symposium 2023 CY - Freiburg, Germany DA - 27.09.2023 KW - Porosity prediction KW - Defect detection KW - Laser powder bed fusion (PBF-LB/M, L-PBF) KW - Selective laser melting KW - Thermography KW - Machine learning PY - 2023 DO - https://doi.org/10.1515/teme-2023-0062 SN - 0171-8096 SN - 2196-7113 VL - 90 SP - 85 EP - 96 PB - De Gruyter CY - Berlin AN - OPUS4-58366 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Tang, Chi-Long A1 - Seeger, Stefan A1 - Röllig, Mathias T1 - Improving the comparability of FFF-3D printing emission data by adjustment of the set extruder temperature JF - Atmospheric Environment: X N2 - Fused filament fabrication (FFF) is a material extrusion-based technique often used in desktop 3D printers. Polymeric filaments are melted and are extruded through a heated nozzle to form a 3D object in layers. The extruder temperature is therefore a key parameter for a successful print job but also one of the main emission driving factors as harmful pollutants (e.g., ultrafine particles) are formed by thermal polymer degradation. The awareness of potential health risks has increased the number of emission studies in the past years. However, studies usually refer their calculated emission data to the printer set extruder temperature for comparison purposes. In this study, we used a thermocouple and an infrared camera to measure the actual extruder temperature and found significant temperature deviations to the displayed set temperature among printer models. Our result shows that printing the same filament feedstocks with three different printer models and with identical printer set temperature resulted in a variation in particle emission of around two orders of magnitude. A temperature adjustment has reduced the variation to approx. one order of magnitude. Thus, it is necessary to refer the measured emission data to the actual extruder temperature as it poses a more accurate comparison parameter for evaluation of the indoor air quality in user scenarios or for health risk assessments. KW - Ultrafine particles KW - Infrared thermography KW - Thermocouple KW - Indoor air quality KW - FFF-3D printer PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-572842 DO - https://doi.org/10.1016/j.aeaoa.2023.100217 VL - 18 SP - 100217 PB - Elsevier Ltd. CY - Amsterdam, Niederlande AN - OPUS4-57284 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -