@misc{ImranSzyndlerAfzaletal., author = {Imran, Muhammad and Szyndler, Joanna and Afzal, Muhammad Junaid and Bambach, Markus}, title = {Dynamic recrystallization-dependent damage modeling during hot forming}, series = {International Journal of Damage Mechanics}, volume = {29}, journal = {International Journal of Damage Mechanics}, number = {2}, issn = {1530-7921}, doi = {10.1177/1056789519848477}, pages = {335 -- 363}, language = {en} } @misc{BambachSizovaSzyndleretal., author = {Bambach, Markus and Sizova, Irina and Szyndler, Joanna and Bennett, Jennifer and Hyatt, Greg and Cao, Jian and Papke, Thomas and Merklein, Marion}, title = {On the hot deformation behavior of Ti-6Al-4V made by additive manufacturing}, series = {Journal of Materials Processing Technology}, volume = {288}, journal = {Journal of Materials Processing Technology}, issn = {0924-0136}, doi = {10.1016/j.jmatprotec.2020.116840}, language = {en} } @misc{SzyndlerHaertelBambach, author = {Szyndler, Joanna and H{\"a}rtel, Sebastian and Bambach, Markus}, title = {Machine learning of the dynamics of strain hardening based on contact transformations}, series = {Journal of Intelligent Manufacturing}, volume = {2025}, journal = {Journal of Intelligent Manufacturing}, publisher = {Springer}, doi = {10.1007/s10845-025-02577-6}, pages = {22}, abstract = {Dislocation density-based models offer a physically grounded approach to modeling strain hardening in metal forming. Since these models are typically defined by Ordinary Differential Equations (ODEs), their accuracy is constrained by both, the model formulation and the parameter identification process. Machine Learning (ML) provides an alternative by allowing models to be constructed directly from experimental data, bypassing the accuracy limitations of explicitly defined models. However, applying ML to ODEs introduces the need for novel training techniques. This work presents a new approach for developing neural ODE models for flow curve description, utilizing a contact transformation to simplify the problem of learning an ODE into a learning a multivariate function.}, language = {en} } @misc{EmdadiYangSzyndleretal., author = {Emdadi, Aliakbar and Yang, Yitong and Szyndler, Joanna and Jensch, Felix and Ertugrul, G{\"o}khan and Tovar, Michael and H{\"a}rtel, Sebastian and Weiß, Sabine}, title = {Highly printable Fe₃Al intermetallic alloy}, series = {Metals : open access journal}, volume = {16}, journal = {Metals : open access journal}, number = {5}, publisher = {MDPI}, address = {Basel}, doi = {10.3390/met16010005}, pages = {1 -- 15}, abstract = {Intermetallic Fe₃Al-based alloys reinforced with Laves-phase precipitates are emerging as potential replacements for conventional high-alloy steels and possibly polycrystalline Ni-based superalloys in structural applications up to 700 °C. Their impressive mechanical properties, however, are offset by limited fabricability and poor machinability due to their severe brittleness. High tool wear during finish-machining, which is still required for components such as turbine blades, remains a key barrier to their broader adoption. In contrast to conventional manufacturing routes, additive manufacturing offers a viable solution by enabling near-net-shape manufacturing of difficult-to-machine iron aluminides. In the present study, laser powder bed fusion was used to produce an Fe-25Al-1.5Ta intermetallic containing strengthening Laves-phase precipitates, and the porosity, microstructure and phase composition were characterized as a function of the process parameters. The results showed that preheating the build plate to 650 °C effectively suppressed delamination and macrocrack formation, even though noticeable cracking still occurred at the high scan speed of 1000 mm/s. X-ray tomography revealed that samples fabricated with a lower scan speed (500 mm/s) and a higher layer thickness (0.1 mm) contained larger, irregularly shaped pores, whereas specimens printed at the same volumetric energy density (40 J/mm3) but with different parameter sets exhibited smaller fractions of predominantly spherical pores. All samples contained mostly elongated grains that were either oriented close to <001> relative to the build direction or largely texture-free. X-ray diffraction confirmed the presence of Fe₃Al and C14-type (Fe, Al)₂Ta Laves phase in all samples. Hardness values fell within a narrow range (378-398 HV10), with only a slight reduction in the specimen exhibiting higher porosity.}, language = {en} }