Efficient optomechanical mode-shape mapping of micromechanical devices
D. Hoch, K.-J. Haas, L. Moller, T. Sommer, P. Soubelet, J. Finley, M. Poot
Micromachines 12, 880 (2021).
Visualizing eigenmodes is crucial in understanding the behavior of state-of-the-art micromechanical devices. We demonstrate a method to optically map multiple modes of mechanical structures simultaneously. The fast and robust method, based on a modified phase-lock loop, is demonstrated on a silicon nitride membrane and shown to outperform three alternative approaches. Line traces and two-dimensional maps of different modes are acquired. The high quality data enables us to determine the weights of individual contributions in superpositions of degenerate modes.
3D Deep Learning Enables Accurate Layer Mapping of 2D Materials
X.C. Dong, H.W. Li, Z.T. Jiang, T. Grunleitner, I. Gueler, J. Dong, K. Wang, M.H. Koehler, M. Jakobi, B.H. Menze, A.K. Yetisen, I.D. Sharp, A.V. Stier, J.J. Finley, A.W. Koch
ACS Nano 15 (2), 3139-3151 (2021).
Layered, two-dimensional (2D) materials are promising for next-generation photonics devices. Typically, the thickness of mechanically cleaved flakes and chemical vapor deposited thin films is distributed randomly over a large area, where accurate identification of atomic layer numbers is time-consuming. Hyperspectral imaging microscopy yields spectral information that can be used to distinguish the spectral differences of varying thickness specimens. However, its spatial resolution is relatively low due to the spectral imaging nature. In this work, we present a 3D deep learning solution called DALM (deep-learning-enabled atomic layer mapping) to merge hyperspectral reflection images (high spectral resolution) and RGB images (high spatial resolution) for the identification and segmentation of MoS2 flakes with mono-, bi-, tri-, and multilayer thicknesses. DALM is trained on a small set of labeled images, automatically predicts layer distributions and segments individual layers with high accuracy, and shows robustness to illumination and contrast variations. Further, we show its advantageous performance over the state-of-the-art model that is solely based on RGB microscope images. This AI-supported technique with high speed, spatial resolution, and accuracy allows for reliable computer-aided identification of atomically thin materials.
Site-selectively generated photon emitters in monolayer MoS2 via local helium ion irradiation
J. Klein, M. Lorke, M. Florian, F. Sigger, J. Wierzbowski, J. Cerne, K. Müller, T. Taniguchi, K. Watanabe, U. Wurstbauer, M. Kaniber, M. Knap, R. Schmidt, J. Finley, A. Holleitner.
Nature Communications 10, Article number: 2755 (2019).
Quantum light sources in solid-state systems are of major interest as a basic ingredient for integrated quantum photonic technologies. The ability to tailor quantum emitters via site-selective defect engineering is essential for realizing scalable architectures. However, a major difficulty is that defects need to be controllably positioned within the material. Here, we overcome this challenge by controllably irradiating monolayer MoS2 using a sub-nm focused helium ion beam to deterministically create defects. Subsequent encapsulation of the ion exposed MoS2 flake with high-quality hBN reveals spectrally narrow emission lines that produce photons in the visible spectral range. Based on ab-initio calculations we interpret these emission lines as stemming from the recombination of highly localized electron–hole complexes at defect states generated by the local helium ion exposure. Our approach to deterministically write optically active defect states in a single transition metal dichalcogenide layer provides a platform for realizing exotic many-body systems, including coupled single-photon sources and interacting exciton lattices that may allow the exploration of Hubbard physics.
Breakdown of corner states and carrier localization by monolayer fluctuations in a radial nanowire quantum wells
M. M. Sonner, A. Sitek, L. Janker, D. Rudolph, D. Ruhstorfer, M. Döblinger, A. Manolescu, G. Abstreiter, J. J. Finley, A. Wixforth, G. Koblmueller, H. J. Krenner
Nano Lett. 19 (5), 3336-3343 (2019).
We report a comprehensive study of the impact of the structural properties in radial GaAs-Al0.3Ga0.7As nanowire-quantum well heterostructures on the optical recombination dynamics and electrical transport properties, emphasizing particularly the role of the commonly observed variations of the quantum well thickness at different facets. Typical thickness fluctuations of the radial quantum well observed by transmission electron microscopy lead to pronounced localization. Our optical data exhibit clear spectral shifts and a multipeak structure of the emission for such asymmetric ring structures resulting from spatially separated, yet interconnected quantum well systems. Charge carrier dynamics induced by a surface acoustic wave are resolved and prove efficient carrier exchange on native, subnanosecond time scales within the heterostructure. Experimental findings are corroborated by theoretical modeling, which unambiguously show that electrons and holes localize on facets where the quantum well is the thickest and that even minute deviations of the perfect hexagonal shape strongly perturb the commonly assumed 6-fold symmetric ground state.