Raabe, D.; Roters, F.: Using texture components in crystal plasticity finite element simulations. International Journal of Plasticity 20, pp. 339 - 361 (2004)
Roters, F.: Simulation der Umfornmung von metallischen Werkstoffen nach der Texturkomponenten-Kristallplastitizitäts-FEM. Simulation, pp. 50 - 53 (2003)
Roters, F.: A new concept for the calculation of the mobile dislocation density in constitutive models of strain hardening. Physica Status Solidi (b), pp. 68 - 74 (2003)
Raabe, D.; Zhao, Z.; Park, S. J.; Roters, F.: Theory of orientation gradients in plastically strained crystals. Acta Materialia 50 (2), pp. 421 - 440 (2002)
Karhausen, K. F.; Roters, F.: Development and application of constitutive equations for the multiple-stand hot rolling of Al-alloys. Journal of Materials Processing Technology 123, pp. 155 - 166 (2002)
Raabe, D.; Roters, F.; Zhao, Z.: Texture component crystal plasticity finite element method for physically-based metal forming simulations including texture update. Proc. 8th Int. Conf. on Aluminium Alloys, pp. 31 - 36 (2002)
Roters, F.; Zhao, Z.: Application of the texture component crystal plasticity finite element method for deep drawing simulations - A comparison with Hill’s yield criterion. Advanced Engineering Materials 4, pp. 221 - 223 (2002)
Roters, F.; Raabe, D.; Gottstein, G.: Work hardening in heterogeneous alloys - A microstructural approach based on three internal state variables. Acta Materialia 48 (17), pp. 4181 - 4189 (2000)
Roters, F.; Eisenlohr, P.; Bieler, T. R.; Raabe, D.: Crystal Plasticity Finite Element Methods in Materials Science and Engineering. Wiley-VCH, Weinheim (2010), 197 pp.
Shanthraj, P.; Diehl, M.; Eisenlohr, P.; Roters, F.; Raabe, D.: Spectral Solvers for Crystal Plasticity and Multi-physics Simulations. In: Handbook of Mechanics of Materials, pp. 1347 - 1372 (Eds. Hsueh, C.-H.; Schmauder, S.; Chen, C.-S.; Chawla, K. K.; Chawla, N. et al.). Springer, Singapore (2019)
Scientists of the Max-Planck-Institut für Eisenforschung pioneer new machine learning model for corrosion-resistant alloy design. Their results are now published in the journal Science Advances
Data-rich experiments such as scanning transmission electron microscopy (STEM) provide large amounts of multi-dimensional raw data that encodes, via correlations or hierarchical patterns, much of the underlying materials physics. With modern instrumentation, data generation tends to be faster than human analysis, and the full information content is…