Research Area Leader - In-Situ Alloying
Adress: Freisinger Landstraße 52.
85748, Garching bei München
Germany.
E-Mail: rafael.paiotti(at)tum.de
Tel.: +49 (0) 89 289 - 55332
Fax: +49 (0) 89 289 - 55342
Room: B1.2.10
Research Focus:
- Directed energy deposition additive manufacturing
- Functionally graded metallic materials
- Metal matrix composites and shape memory alloys
Publications
R. P. M. P. M. Guimarães et al., ‘Ageing response of Ni-rich NiTi shape memory alloy additively manufactured by electron beam freeform fabrication’, J. Mater. Res. Technol., vol. 35, no. November 2024, pp. 2656–2675, Mar. 2025.
R. Guimarães et al., ‘The electron beam freeform fabrication of NiTi shape memory alloys. Part II: Influence of the heat treatment on the superelastic behaviour’, Proc. Inst. Mech. Eng. Part J. Mater. Des. Appl., vol. 238, no. 1, pp. 100–111, Jan. 2024.
R. Guimarães et al., ‘The electron beam freeform fabrication of NiTi shape memory alloys. Part I: Microstructure and physical–chemical behavior’, Proc. Inst. Mech. Eng. Part J. Mater. Des. Appl., vol. 235, no. 4, pp. 709–716, Apr. 2021.
R. P. M. Guimarães et al., ‘Powder bed fusion processes: main classes of alloys, current status, and technological trends’, in Advances in Metal Additive Manufacturing, Elsevier, 2023, pp. 1–104.
R. P. M. Guimarães, F. Pixner, N. Enzinger, C. A. Feliciano Belei, P. dos S. Effertz, and S. T. Amancio-Filho, ‘Directed energy deposition processes and process design by artificial intelligence’, in Advances in Metal Additive Manufacturing, Elsevier, 2023, pp. 105–146.
R. P. Marcondes Guimarães, J. Soyama, T. Ebel, M. C. Fredel, and F. Pyczak, ‘Influence of α-Phase Field Heat Treatment on the Tensile and Primary Creep Resistance of a Powder Metallurgical Processed Ti-45Al-5Nb-0.2B-0.2C Titanium Aluminide Alloy’, Mater. Sci. Forum, vol. 899, pp. 418–423, Jul. 2017.
R. Paiotti Marcondes Guimarães et al., ‘In Situ Analysis of the Phase Transformation Kinetics in the β-Water-Quenched Ti-5Al-5Mo-5V-3Cr-1Zr Alloy during Ageing after Fast Heating’, Quantum Beam Sci., vol. 4, no. 1, p. 12, Feb. 2020.
P. S. Effertz, W. S. de Carvalho, R. P. M. Guimarães, G. Saria, and S. T. Amancio-Filho, ‘Optimization of Refill Friction Stir Spot Welded AA2024-T3 Using Machine Learning’, Front. Mater., vol. 9, no. April, pp. 1–9, Apr. 2022.