Atomic precision materials engineering (ATMEN)

2017–2022

Despite more than fifty years of scientific progress since Richard Feynman's 1959 vision for nanotechnology, there is only one way to manipulate individual atoms in materials: scanning tunneling microscopy. Since the late 1980s, its atomically sharp tip has been used to move atoms over clean metal surfaces held at cryogenic temperatures. Scanning transmission electron microscopy, on the other hand, has been able to resolve atoms only more recently by focusing the electron beam with sub-atomic precision. This is especially useful in the two-dimensional form of hexagonally bonded carbon called graphene, which has superb electronic and mechanical properties. Several ways to further engineer those have been proposed, including by doping the structure with substitutional heteroatoms such as boron, nitrogen, phosphorus and silicon. My recent discovery that the scattering of the energetic imaging electrons can cause a silicon impurity to move through the graphene lattice has revealed a potential for atomically precise manipulation using the Ångström-sized electron probe. To develop this into a practical technique, improvements in the description of beam-induced displacements, advances in heteroatom implantation, and a concerted effort towards the automation of manipulations are required. My project tackles these in a multidisciplinary effort combining innovative computational techniques with pioneering experiments in an instrument where a low-energy ion implantation chamber is directly connected to an advanced electron microscope. To demonstrate the power of the method, I will prototype an atomic memory with an unprecedented memory density, and create heteroatom quantum corrals optimized for their plasmonic properties. The capability for atom-scale engineering of covalent materials opens a new vista for nanotechnology, pushing back the boundaries of the possible and allowing a plethora of materials science questions to be studied at the ultimate level of control.

Please see also our public outreach website.

Funder: European Research Council

Project identifier: 756277

Principal investigator: T. Susi

Project publications

2024

Propst, D., Joudi, W., Längle, M., Madsen, J., Kofler, C., Mayer, B. M., Lamprecht, D., Mangler, C., Filipovic, L., Susi, T., & Kotakoski, J. (2024). Automated image acquisition and analysis of graphene and hexagonal boron nitride from pristine to highly defective and amorphous structures. Scientific Reports, 14(1), Article 26939. https://doi.org/10.1038/s41598-024-77740-9

Trentino, A., Zagler, G., Längle, M., Madsen, J., Susi, T., Mangler, C., Åhlgren, E. H., Mustonen, K., & Kotakoski, J. (2024). Single atoms and metal nanoclusters anchored to graphene vacancies. Micron, 184, Article 103667. https://doi.org/10.1016/j.micron.2024.103667

Mortensen, J. J., Larsen, A. H., Kuisma, M., Ivanov, A. V., Taghizadeh, A., Peterson, A., Haldar, A., Dohn, A. O., Schäfer, C., Jónsson, E. Ö., Hermes, E. D., Nilsson, F. A., Kastlunger, G., Levi, G., Jónsson, H., Häkkinen, H., Fojt, J., Kangsabanik, J., Sødequist, J., ... Thygesen, K. S. (2024). GPAW: An open Python package for electronic structure calculations. Journal of Chemical Physics, 160(9), Article 092503. https://doi.org/10.1063/5.0182685

2023

Bui, T. A., Leuthner, G. T., Madsen, J., Monazam, M. R. A., Chirita, A. I., Postl, A., Mangler, C., Kotakoski, J., & Susi, T. (2023). Creation of Single Vacancies in hBN with Electron Irradiation. Small, 19(39), Article 2301926 . https://doi.org/10.48550/arXiv.2303.00497, https://doi.org/10.1002/smll.202301926

Postl, A., Kozyrau, E., Madsen, J., & Susi, T. (2023). Challenges for Scaling Up Electron-Beam Manipulation of Graphene Impurities. Microscopy and Microanalysis, 29(Suppl. 1), 1370-1371. https://doi.org/10.1093/micmic/ozad067.704

Hudak, B. M., Markevich, A., Susi, T., Lupini, A. R., & Stroud, R. M. (2023). Direct Positioning of Point Defects in 3D Materials Using STEM. Microscopy and Microanalysis, 29(Suppl. 1), 1365. https://doi.org/10.1093/micmic/ozad067.701

Schloz, M., Müller, J., Pekin, T. C., Van den Broek, W., Madsen, J., Susi, T., & Koch, C. T. (2023). Deep reinforcement learning for data-driven adaptive scanning in ptychography. Scientific Reports, 13(1), Article 8732. https://doi.org/10.48550/arXiv.2203.15413, https://doi.org/10.1038/s41598-023-35740-1

Speckmann, C., Lang, J., Madsen, J., Ahmadpour Monazam, M. R., Zagler, G., Leuthner, G. T., McEvoy, N., Mangler, C., Susi, T., & Kotakoski, J. (2023). Combined electronic excitation and knock-on damage in monolayer MoS₂. Physical Review B, 107(9), Article 094112. https://doi.org/10.1103/PhysRevB.107.094112

Li, Z., Rose, H., Madsen, J., Biskupek, J., Susi, T., & Kaiser, U. (2023). Computationally Efficient Handling of Partially Coherent Electron Sources in (S)TEM Image Simulations via Matrix Diagonalization. Microscopy and Microanalysis, 29(1), 364–373. https://doi.org/10.1017/S1431927622012387

Elibol, K., Susi, T., Mangler, C., Eder, D., Meyer, J. C., Kotakoski, J., Hobbs, R. G., van Aken, P. A., & Bayer, B. C. (2023). Linear indium atom chains at graphene edges. npj 2D Materials and Applications, 7(1), Article 2. https://doi.org/10.1038/s41699-023-00364-6

2022

Susi, T. (2022). Identifying and manipulating single atoms with scanning transmission electron microscopy. Chemical Communications, 58(88), 12274-12285. https://doi.org/10.1039/D2CC04807H

Kalinin, S., Ziatdinov, M., Spurgeon, S. R., Ophus, C., Stach, E. A., Susi, T., Agar, J., & Randall, J. (2022). Deep learning for electron and scanning probe microscopy: From materials design to atomic fabrication. MRS Bulletin, 47(9), 931-939. https://doi.org/10.1557/s43577-022-00413-3

Postl, A., Hilgert, P. P. P., Markevich, A., Madsen, J., Mustonen, K., Kotakoski, J., & Susi, T. (2022). Indirect measurement of the carbon adatom migration barrier on graphene. Carbon, 196, 596-601. https://doi.org/10.1016/j.carbon.2022.05.039

Niggas, A., Schwestka, J., Balzer, K., Weichselbaum, D., Schlünzen, N., Heller, R., Creutzburg, S., Inani, H., Tripathi, M., Speckmann, C., McEvoy, N., Susi, T., Kotakoski, J., Gan, Z., George, A., Turchanin, A., Bonitz, M., Aumayr, F., & Wilhelm, R. A. (2022). Ion-Induced Surface Charge Dynamics in Freestanding Monolayers of Graphene and MoS₂ Probed by the Emission of Electrons. Physical Review Letters, 129(8), Article 086802. https://doi.org/10.1103/PhysRevLett.129.086802

Golze, D., Hirvensalo, M., Hernandez-Leon, P., Aarva, A., Etula, J., Susi, T., Rinke, P., Laurila, T., & Caro, M. A. (2022). Accurate Computational Prediction of Core-Electron Binding Energies in Carbon-Based Materials: A Machine-Learning Model Combining Density-Functional Theory and GW. Chemistry of Materials, 34(14), 6240-6254. https://doi.org/10.1021/acs.chemmater.1c04279

Zagler, G., Stecher, M., Trentino, A., Kraft, F., Su, C., Postl, A., Längle, M., Pesenhofer, C., Mangler, C., Ahlgren, E. H., Markevich, A., Zettl, A., Kotakoski, J., Susi, T., & Mustonen, K. (2022). Beam-driven dynamics of aluminium dopants in graphene. 2D Materials, 9(3), Article 035009. https://doi.org/10.1088/2053-1583/ac6c30

Chirita, A., Markevich, A., Tripathi, M., Pike, N. A., Verstraete, M. J., Kotakoski, J., & Susi, T. (2022). Three-dimensional ab initio description of vibration-assisted electron knock-on displacements in graphene. Physical Review B, 105(23), Article 235419. https://doi.org/10.1103/PhysRevB.105.235419

Trentino, A., Mizohata, K., Zagler, G., Längle, M., Mustonen, K., Susi, T., Kotakoski, J., & Åhlgren, E. H. (2022). Two-step implantation of gold into graphene. 2D Materials, 9(2), Article 025011. https://doi.org/10.1088/2053-1583/ac4e9c

Mustonen, K., Hofer, C., Kotrusz, P., Markevich, A., Hulman, M., Mangler, C., Susi, T., Pennycook, T. J., Hricovini, K., Richter, C., Meyer, J. C., Kotakoski, J., & Skakalova, V. (2022). Toward Exotic Layered Materials: 2D Cuprous Iodide. Advanced Materials, 34(9), Article 2106922. https://doi.org/10.1002/adma.202106922

Langer, R., Mustonen, K., Markevich, A., Otyepka, M., Susi, T., & Blonski, P. (2022). Graphene Lattices with Embedded Transition-Metal Atoms and Tunable Magnetic Anisotropy Energy: Implications for Spintronic Devices. ACS Applied Nano Materials, 5(1), 1562–1573. https://doi.org/10.1021/acsanm.1c04309