Robust procedure for creating and characterizing the atomic structure of scanning tunneling microscope tips

Scholarly Works

• Rahman Laskar, M. A.; Celano, U. Scanning probe microscopy in the age of machine learning. APL Machine Learning 2023, 1. doi:10.1063/5.0160568
• Bazrafshan, M. A.; Khoeini, F.; Szafran, B. Insights into electronic and transport properties of phosphorene nanorings in two perpendicular directions: Effects of circular and elliptical external potentials. Journal of Applied Physics 2023, 134. doi:10.1063/5.0165936
• Dednam, W.; Tewari, S.; Lombardi, E. B.; Palacios, J. J.; van Ruitenbeek, J. M.; Sabater, C. Dynamic bonding influenced by the proximity of adatoms to one atom high step edges. Physical Review B 2022, 106. doi:10.1103/physrevb.106.125418
• Nguyen, L. T. P.; Liu, B. H. Emerging machine learning strategies for diminishing measurement uncertainty in SPM nanometrology. Surface Topography: Metrology and Properties 2022, 10, 33002–033002. doi:10.1088/2051-672x/ac8a62
• Luo, K.; Dai, Y.-B.; Li, M.; Wang, X.-F.; Zhou, L. Full range modulation of giant magnetoresistance in graphene–like zigzag nanoribbons via dual edge disorders. Physica E: Low-dimensional Systems and Nanostructures 2021, 130, 114703. doi:10.1016/j.physe.2021.114703
• Capiod, P.; van der Sluijs, M.; de Boer, J.; Delerue, C.; Swart, I.; Vanmaekelbergh, D. Electronic properties of atomically coherent square PbSe nanocrystal superlattice resolved by Scanning Tunneling Spectroscopy. Nanotechnology 2021, 32, 325706. doi:10.1088/1361-6528/abfd57
• Leeuwenhoek, M.; Groenewoud, F.; van Oosten, K.; Benschop, T.; Allan, M. P.; Gröblacher, S. Fabrication of on-chip probes for double-tip scanning tunneling microscopy. Microsystems & nanoengineering 2020, 6, 99. doi:10.1038/s41378-020-00209-y
• Gordon, O. M.; Moriarty, P. Machine learning at the (sub)atomic scale: next generation scanning probe microscopy. Machine Learning: Science and Technology 2020, 1, 023001. doi:10.1088/2632-2153/ab7d2f
• Krull, A.; Hirsch, P.; Rother, C.; Schiffrin, A.; Krull, C. Artificial-intelligence-driven scanning probe microscopy. Communications Physics 2020, 3, 54. doi:10.1038/s42005-020-0317-3
• Gordon, O. M.; Junqueira, F. L. Q.; Moriarty, P. Embedding human heuristics in machine-learning-enabled probe microscopy. Machine Learning: Science and Technology 2020, 1, 015001. doi:10.1088/2632-2153/ab42ec
• Leeuwenhoek, M.; Norte, R. A.; Bastiaans, K. M.; Cho, D.; Battisti, I.; Blanter, Y.; Gröblacher, S.; Allan, M. P. Nanofabricated tips for device-based scanning tunneling microscopy. Nanotechnology 2019, 30, 335702. doi:10.1088/1361-6528/ab1c7f
• Tewari, S.; Bakermans, J.; Wagner, C.; Galli, F.; van Ruitenbeek, J. M. Intuitive human interface to a scanning tunnelling microscope: observation of parity oscillations for a single atomic chain. Beilstein journal of nanotechnology 2019, 10, 337–348. doi:10.3762/bjnano.10.33

Explore citations to this article at