Yonsei Institute for Advanced Study

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Research Areas

Functional Nanorobots

Scheme and 3D electron tomography of adaptable nanomachines having energy harvest, engine, clutch, and propeller functions in nanoscale

Magnetically actuated functional nanorobots (<500 nm) are engineered for precise motion and environmental interaction in microscale and biological settings. A programmable three-axis electromagnetic platform generates dynamic three-dimensional magnetic field vectors, including rotating magnetic fields (RMFs), which couple with tailored magnetic material properties to regulate individual nanorobot behavior. Energy transduction, torque generation, and propulsion are integrated within a compact architecture, where motion emerges from the balance of magnetic torque, low-Reynolds-number hydrodynamics, interfacial interactions, and stochastic fluctuations. Real-time modulation of field direction, magnitude, and temporal waveforms enables controlled orientation and propulsion of single nanorobots. This physically mediated material–field coupling framework establishes the hardware foundation of nano-physical AI systems.

Nano-Physical AI Systems

Conceptual schematic of a nano-physical AI system integrating multimodal sensing, autonomous decision-making, propulsion, and bio-interfacing functions at the nanoscale.

Nano-physical AI systems operate through a closed-loop architecture integrating sensing, decision, action, and interfacing. At the sensing stage, nanorobots transduce biological and chemical interactions—such as antigen–antibody binding, enzyme reactions, fluorescence modulation, or FRET—into measurable optical or physicochemical signals that are acquired via microscopy and converted into quantitative environmental data. These data are computationally analyzed in the decision stage to evaluate system states and determine appropriate control inputs. Action is executed through a programmable three-axis electromagnetic platform generating dynamic three-dimensional magnetic field vectors, including rotating magnetic fields (RMFs), whose real-time modulation regulates propulsion and orientation of individual nanorobots. Interfacing refers to the controlled physical and biochemical engagement of nanorobots with biological targets across relevant length scales, enabling interaction with viral-scale objects, bacteria-scale entities, or cell membrane surfaces within complex microenvironments. Environmental changes induced through action and interfacing generate updated signals that re-enter the sensing process, completing a continuously regulated nano-physical AI cycle.

Nanorobots Navigation

Nanorobot navigation under programmable magnetic fields with corresponding motion trajectories.

 Nanorobotic navigation is achieved using a programmable three-axis electromagnetic platform capable of generating dynamic three-dimensional magnetic field vectors, including rotating magnetic fields (RMFs), to regulate orientation and propulsion within a planar workspace. Real-time modulation of field direction, magnitude, and temporal waveforms enables stable trajectory tracking and directional switching of individual nanorobots under low-Reynolds-number conditions. As a proof of deterministic spatial control, particles were guided to trace the letters “YIBS” on a two-dimensional surface, demonstrating reproducible path execution under programmable electromagnetic actuation. Building upon this foundation, navigation is extended toward geometrically constrained environments and dynamically varying targets, where trajectory adjustments are continuously informed by microscopic observation and computational state evaluation. This integration of sensing, decision, and field-mediated actuation enables adaptive navigation, allowing motion strategies to be reconfigured in real time according to changing spatial conditions and target states within the microenvironment.

Soft-NanoBio-Robotics

Scheme and Tracking Image of adaptable nanomachines having energy harvest, engine, clutch, and propeller functions in nanoscale

The development of sophisticated machines at the nanoscale (< 500 nm) marks a critical advancement in modern science, including nanoscience, material sciences, and life sciences, offering new possibilities for the precise control and maneuvering of nanomaterials. To operate effectively in complex and dynamic biological systems, nanomachines must be endowed with autonomous, environmentally adaptive functionalities. These adaptive nanorobots are designed using functionally optimized and stimuli-responsive nanomaterials that can sense and respond to diverse physicochemical cues such as pH, temperature, or enzymatic environments.

Our research focuses on understanding of chemical processes below the nanoscale and nano-circumstances interfaces, essential to develop such adaptable nanomachines. Through this foundational understanding, we design and control nanorobots with optimized functional materials. With this foundation, nanorobots designed to diagnose and address challenges within biological environments could be further enhanced through the integration of AI, positioning them as transformative tools for future medicine.