Quantum Nanorobotics: A Proposal for Quantum-Enhanced Actuation and Sensing at the Molecular Scale
Indonesia Indonesia 
Pakistan 
Article Sidebar
-
Molecular Scale, Quantum Nanorobotics, Quantum Sensing
Abstract
Quantum nanorobotics has emerged as a promising interdisciplinary field aimed at enabling precise manipulation and sensing at the molecular scale, where classical mechanical approaches face fundamental limitations. The purpose of this study is to propose a unified framework for quantum-enhanced actuation and sensing that leverages quantum mechanical effects as functional resources in nanorobotic systems. The research adopts a conceptual–theoretical design supported by computational modeling and simulation grounded in quantum mechanics and quantum control theory. Simulation-based analyses demonstrate that quantum-enhanced sensing achieves significantly higher sensitivity, lower noise variance, and reduced energy consumption compared to classical nanoscale sensors, while quantum-based actuation exhibits improved precision, faster response times, and enhanced stability under environmental noise. The integrated sensing–actuation architecture reveals synergistic performance gains that surpass isolated enhancements, enabling reliable molecular-scale navigation and task execution. The study concludes that quantum coherence and tunneling can be systematically engineered to overcome classical constraints in nanorobotics, establishing quantum-enhanced control as a viable design paradigm. The novelty of this research lies in its integrative conceptual framework that unifies quantum sensing and actuation within a single nanorobotic architecture, providing a foundational model for future experimental development and interdisciplinary applications.
Full text article
References
Ansari, S. M. (2025). Cobalt ferrite nanoparticles: The physics, synthesis, properties, and applications. Applied Physics Reviews, 12(2). https://doi.org/10.1063/5.0244555
Deng, G. (2020). Natural-Killer-Cell-Inspired Nanorobots with Aggregation-Induced Emission Characteristics for Near-Infrared-II Fluorescence-Guided Glioma Theranostics. ACS Nano, 14(9), 11452–11462. https://doi.org/10.1021/acsnano.0c03824
Dhar, A. (2024). Nanotechnology-based theranostic and prophylactic approaches against SARS-CoV-2. Immunologic Research, 72(1), 14–33. https://doi.org/10.1007/s12026-023-09416-x
Dong, L. (2008). Engineering multiwalled carbon nanotubes inside a transmission electron microscope using nanorobotic manipulation. IEEE Transactions on Nanotechnology, 7(4), 508–517. https://doi.org/10.1109/TNANO.2008.926443
Dong, L. (2009). Metal-filled carbon nanotubes for nanofluidic systems: Modes of melting and evaporation. 2009 IEEE Rsj International Conference on Intelligent Robots and Systems Iros 2009, Query date: 2025-12-15 20:36:28, 1407–1412. https://doi.org/10.1109/IROS.2009.5354123
Dong, L. X. (2009). Nanotube boiler: Attogram copper evaporation driven by electric current, Joule heating, charge, and ionization. IEEE Transactions on Nanotechnology, 8(5), 565–568. https://doi.org/10.1109/TNANO.2009.2026172
Fang, G. J. (2013). Athermal photofluidization of glasses. Nature Communications, 4(Query date: 2025-12-15 20:36:28). https://doi.org/10.1038/ncomms2483
Frutiger, D. R. (2006). Optical tracking of multi-walled carbon nanotubes by attaching functionalized quantum dots. Proceedings of 1st IEEE International Conference on Nano Micro Engineered and Molecular Systems 1st IEEE NEMS, Query date: 2025-12-15 20:36:28, 1179–1184. https://doi.org/10.1109/NEMS.2006.334675
Hamdi, M. (2008). DNA nanorobotics. Microelectronics Journal, 39(8), 1051–1059. https://doi.org/10.1016/j.mejo.2007.10.021
Hamdi, M. (2009). Multiscale design and modeling of protein-based nanomechanisms for nanorobotics. International Journal of Robotics Research, 28(4), 436–449. https://doi.org/10.1177/0278364908099888
Hwang, G. (2008). 3-D InGaAs/GaAs helical nanobelts for optoelectronic devices. International Journal of Optomechatronics, 2(2), 88–103. https://doi.org/10.1080/15599610802081795
Jain, K. K. (2008). Recent advances in nanooncology. Technology in Cancer Research and Treatment, 7(1), 1–13. https://doi.org/10.1177/153303460800700101
Jiang, J. (2024). Advances and Prospects in Integrated Nano-oncology. Nano Biomedicine and Engineering, 16(2), 152–187. https://doi.org/10.26599/NBE.2024.9290060
Kaur, G. (2024). A Path of Novelty from Nanoparticles to Nanobots: Theragnostic Approach for Targeting Cancer Therapy. Critical Reviews in Therapeutic Drug Carrier Systems, 41(4), 1–38. https://doi.org/10.1615/CritRevTherDrugCarrierSyst.2023046674
Kaur, H. (2009). In-Vitro Transportation of Drug Molecule by Actin Myosin Motor System. Ifmbe Proceedings, 23(Query date: 2025-12-15 20:36:28), 902–905. https://doi.org/10.1007/978-3-540-92841-6_223
Majumdar, A. (2021). Quantum-Classical Simulation of Molecular Motors Driven only by Light. Journal of Physical Chemistry Letters, 12(23), 5512–5518. https://doi.org/10.1021/acs.jpclett.1c00951
Mannix, A. J. (2022). Robotic four-dimensional pixel assembly of van der Waals solids. Nature Nanotechnology, 17(4), 361–366. https://doi.org/10.1038/s41565-021-01061-5
Novakovi?, B. (2011). Dynamic model of nanorobot motion in multipotential field. Strojarstvo, 53(2), 103–111.
Qu, Z. (2023). Atomic-level Tracking and Analyzing of Quantum-dot Motion Steered by an Electrostatic Field Positioned by a Nanorobotic Manipulation Tip. Proceedings IEEE International Conference on Robotics and Automation, 2023(Query date: 2025-12-15 20:36:28), 5439–5444. https://doi.org/10.1109/ICRA48891.2023.10161087
Saper, G. (2021). Robotic end-to-end fusion of microtubules powered by kinesin. Science Robotics, 6(60). https://doi.org/10.1126/scirobotics.abj7200
Selvarajan, S. (2014). Noninvasive nanodiagnostics for cancer. Cancer Biomarkers Minimal and Noninvasive Early Diagnosis and Prognosis, Query date: 2025-12-15 20:36:28, 85–94. https://doi.org/10.1201/b16389
Yang, L. (2020). Automated Control of Magnetic Spore-Based Microrobot Using Fluorescence Imaging for Targeted Delivery with Cellular Resolution. IEEE Transactions on Automation Science and Engineering, 17(1), 490–501. https://doi.org/10.1109/TASE.2019.2937232
