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arXiv · 2404.09694

MAM-STM: A software for autonomous control of single moieties towards specific surface positions

Bernhard Ramsauer·Johannes J. Cartus·Oliver T. Hofmann
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Abstract

In this publication we introduce MAM-STM, a software to autonomously manipulate arbitrary moieties towards specific positions on a metal surface utilizing the tip of a scanning tunneling microscope (STM). Finding the optimal manipulation parameters for a specific moiety is challenging and time consuming, even for human experts. MAM-STM combines autonomous data acquisition with a sophisticated Q-learning implementation to determine the optimal bias voltage, the z-approach distance, and the tip position relative to the moiety. This then allows to arrange single molecules and atoms at will. In this work, we provide a tutorial based on a simulated response to offer a comprehensive explanation on how to use and customize MAM-STM. Additionally, we assess the performance of the machine learning algorithm by benchmarking it within a simulated stochastic environment.

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Bernhard Ramsauer, Johannes J. Cartus, Oliver T. Hofmann. 2024-04-15. MAM-STM: A software for autonomous control of single moieties towards specific surface positions. https://arxiv.org/abs/2404.09694

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