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2CV.3.19: Towards the correlation of mechanical properties and sawing parameters of silicon wafers
Bidiville, A., Wasmer, K., Michler, J., Ballif, C., Van der Meer, M., & Nasch, P. M. (2007). 2CV.3.19: Towards the correlation of mechanical properties and sawing parameters of silicon wafers. Presented at the Poster presented at the 22nd European Photovoltaic Solar Energy & Exhibition. Mailand, Italy.
2CV.3.20: effect of strength test methods on silicon wafer strength measurements
Wasmer, K., Bidiville, A., Michler, J., Ballif, C., Van der Meer, M., & Nasch, P. (2007). 2CV.3.20: effect of strength test methods on silicon wafer strength measurements. Presented at the 22nd European photovoltaic solar energy & exhibition. Mailand, Italy.
3D and 4D printing of complex structures of Fe-Mn-Si-based shape memory alloy using laser powder bed fusion
Kim, D., Ferretto, I., Leinenbach, C., & Lee, W. (2022). 3D and 4D printing of complex structures of Fe-Mn-Si-based shape memory alloy using laser powder bed fusion. Advanced Materials Interfaces, 9(13), 2200171 (11 pp.). https://doi.org/10.1002/admi.202200171
3D magnetic patterning in additive manufacturing via site-specific in-situ alloy modification
Arabi-Hashemi, A., Maeder, X., Figi, R., Schreiner, C., Griffiths, S., & Leinenbach, C. (2020). 3D magnetic patterning in additive manufacturing via site-specific in-situ alloy modification. Applied Materials Today, 18, 100512 (9 pp.). https://doi.org/10.1016/j.apmt.2019.100512
3D printing: fabrication of metal matrix composite by laser metal deposition and direct dry injection of nanopowders
Cui, D., Mohanta, A., Leparoux, M., Hoffmann, P., Favre, S., & Tortorici, P. (2020). 3D printing: fabrication of metal matrix composite by laser metal deposition and direct dry injection of nanopowders. Presented at the Medtronic science & technology online conference. Minneapolis, USA.
3D reconstruction of cracks propagation in mechanical workpieces analyzing non-stationary acoustic mixtures
Shevchik, S. A., Meylan, B., Violakis, G., & Wasmer, K. (2019). 3D reconstruction of cracks propagation in mechanical workpieces analyzing non-stationary acoustic mixtures. Mechanical Systems and Signal Processing, 119, 55-64. https://doi.org/10.1016/j.ymssp.2018.09.022
4D printing of recoverable buckling-induced architected iron-based shape memory alloys
Jafarabadi, A., Ferretto, I., Mohri, M., Leinenbach, C., & Ghafoori, E. (2023). 4D printing of recoverable buckling-induced architected iron-based shape memory alloys. Materials and Design, 233, 112216 (12 pp.). https://doi.org/10.1016/j.matdes.2023.112216
A close look at temperature profiles during laser powder bed fusion using operando X-ray diffraction and finite element simulations
Gh Ghanbari, P., Markovic, P., Van Petegem, S., Makowska, M. G., Wrobel, R., Mayer, T., … Hosseini, E. (2023). A close look at temperature profiles during laser powder bed fusion using operando X-ray diffraction and finite element simulations. Additive Manufacturing Letters, 6, 100150 (9 pp.). https://doi.org/10.1016/j.addlet.2023.100150
A cnn prediction method for belt grinding tool wear in a polishing process utilizing 3-axes force and vibration data
Caesarendra, W., Triwiyanto, T., Pandiyan, V., Glowacz, A., Permana, S. D. H., & Tjahjowidodo, T. (2021). A cnn prediction method for belt grinding tool wear in a polishing process utilizing 3-axes force and vibration data. Electronics, 10(12), 1429 (30 pp.). https://doi.org/10.3390/electronics10121429
A molecular dynamics study of Ag-Ni nanometric multilayers: thermal behavior and stability
Baras, F., Politano, O., Li, Y., & Turlo, V. (2023). A molecular dynamics study of Ag-Ni nanometric multilayers: thermal behavior and stability. Nanomaterials, 13(14), 2134 (24 pp.). https://doi.org/10.3390/nano13142134
A non-volatile optical memory in silicon photonics
Geler-Kremer, J., Eltes, F., Stark, P., Sharma, A., Caimi, D., Offrein, B. J., … Abel, S. (2021). A non-volatile optical memory in silicon photonics. In Proceedings optical fiber communication conference (OFC) 2021 (p. Th4I.2 (3 pp.). https://doi.org/10.1364/OFC.2021.Th4I.2
A parametric neutron Bragg edge imaging study of additively manufactured samples treated by laser shock peening
Busi, M., Kalentics, N., Morgano, M., Griffiths, S., Tremsin, A. S., Shinohara, T., … Strobl, M. (2021). A parametric neutron Bragg edge imaging study of additively manufactured samples treated by laser shock peening. Scientific Reports, 11(1), 14919 (9 pp.). https://doi.org/10.1038/s41598-021-94455-3
A simple method for measuring plasma power in rf-GDOES instruments
Nelis, T., Aeberhard, M., Rohr, L., Michler, J., Belenguer, P., Guillot, P., & Thérèse, L. (2007). A simple method for measuring plasma power in rf-GDOES instruments. Analytical and Bioanalytical Chemistry, 389(3), 763-767. https://doi.org/10.1007/s00216-007-1509-3
A simple scaling model for balling defect formation during laser powder bed fusion
Lindström, V., Lupo, G., Yang, J., Turlo, V., & Leinenbach, C. (2023). A simple scaling model for balling defect formation during laser powder bed fusion. Additive Manufacturing, 63, 103431 (12 pp.). https://doi.org/10.1016/j.addma.2023.103431
AM/LW process monitoring combining high-speed X-ray imaging, acoustic & optical sensors and artificial intelligence
Wasmer, K., Le, T. Q., Meylan, B., Vakili-Farahani, F., Leinenbach, C., Olbinado, M. P., … Shevchik, S. A. (2018). AM/LW process monitoring combining high-speed X-ray imaging, acoustic & optical sensors and artificial intelligence. Presented at the ESRF user meeting 2018. Grenoble, France.
Accessing the structure of γ-Al<sub>2</sub>O<sub>3</sub> nanoparticles (NPs) with the charge-optimized many-body interatomic potential
Greminger, J. A. S., Gramatte, S., Politano, O., Baras, F., & Turlo, V. (2021). Accessing the structure of γ-Al2O3 nanoparticles (NPs) with the charge-optimized many-body interatomic potential. Presented at the Swiss nano convention 2021. Basel.
Acoustic emission and machine learning based classification of wear generated using a pin-on-disc tribometer equipped with a digital holographic microscope
Deshpande, P., Pandiyan, V., Meylan, B., & Wasmer, K. (2021). Acoustic emission and machine learning based classification of wear generated using a pin-on-disc tribometer equipped with a digital holographic microscope. Wear, 476, 203622 (12 pp.). https://doi.org/10.1016/j.wear.2021.203622
Acoustic emission and machine learning for in situ monitoring of a gold-copper ore weakening by electric pulse
Meylan, B., Shevchik, S. A., Parvaz, D., Mosaddeghi, A., Simov, V., & Wasmer, K. (2021). Acoustic emission and machine learning for in situ monitoring of a gold-copper ore weakening by electric pulse. Journal of Cleaner Production, 280, 124348 (12 pp.). https://doi.org/10.1016/j.jclepro.2020.124348
Acoustic emission for <i>in situ</i> monitoring of solid materials pre-weakening by electric discharge: a machine learning approach
Shevchik, S. A., Meylan, B., Mosaddeghi, A., & Wasmer, K. (2018). Acoustic emission for in situ monitoring of solid materials pre-weakening by electric discharge: a machine learning approach. IEEE Access, 6, 40313-40324. https://doi.org/10.1109/ACCESS.2018.2853666
Acoustic emission for in situ quality monitoring in additive manufacturing using spectral convolutional neural networks
Shevchik, S. A., Kenel, C., Leinenbach, C., & Wasmer, K. (2018). Acoustic emission for in situ quality monitoring in additive manufacturing using spectral convolutional neural networks. Additive Manufacturing, 21, 598-604. https://doi.org/10.1016/j.addma.2017.11.012
 

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