Researchers at the National University of Singapore (NUS) have developed an innovative method for creating carbon-based quantum materials atom by atom. This method combines the use of scanning probe microscopy with advanced deep neural networks. The achievement underlines the capabilities of artificial intelligence (AI) in manipulating materials at the sub-angstrom level, offering significant advantages for basic science and potential future uses.
Open-shell magnetic nanographenes represent a technologically appealing class of new carbon-based quantum materials, which host robust π-spin centers and non-trivial collective quantum magnetism. These properties are crucial for developing high-speed electronic devices at the molecular level and creating quantum bits, the building blocks of quantum computers.
Despite significant advancements in the synthesis of these materials through on-surface synthesis, a type of solid-phase chemical reaction, achieving precise fabrication and tailoring of the properties of these quantum materials at the atomic level has remained a challenge.
The research team, led by Associate Professor Lu Jiong from the NUS Department of Chemistry and the Institute for Functional Intelligent Materials together with Associate Professor Zhang Chun from the NUS Department of Physics, have introduced the concept of the chemist-intuited atomic robotic probe (CARP) by integrating probe chemistry knowledge and artificial intelligence to fabricate and characterize open-shell magnetic nanographenes at the single-molecule level. This allows for precise engineering of their π-electron topology and spin configurations in an automated manner, mirroring the capabilities of human chemists.
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