Quantum Revolution: Integrating Nanotechnology, Artificial Intelligence and Sustainable Innovations for the Future

  • Authors

    • Alka Pant School of Computing, Graphic Era Hill University, Dehradun, Uttarakhand, India
    • Ashutosh Kothiyal School of Computing, Graphic Era Hill University, Dehradun, Uttarakhand, India
    • Vandana Rawat Department of Computer Science & Engineering, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India
    https://doi.org/10.14419/xk2n4x45

    Received date: March 18, 2025

    Accepted date: June 2, 2025

    Published date: June 29, 2025

  • Quantum computing, Nanotechnology, Artificial intelligence, Machine learning, Sustainable Li-S batteries
  • Abstract

    “Every End Marks a New Beginning,” Cycle Continues—Life Changes! The world takes a step forward towards the future. The future is where revolutionary technology takes place and exploits quantum mechanics principles like superposition, entanglement, and interference. By existing in multiple states simultaneously, qubits perform fast and optimize operations growth. This paper explores the use case of quantum computing’s potential and integration with cutting-edge fields such as nanotechnology, AI, advanced DNA data storage, and sustainable Li-S energy storage devices. Achieving quantum computer integration with nanotechnology, advancing hardware for future challenges, and space exploration’ missions by precisely engineering qubit materials, superconducting circuits, and quantum dots. Graphene, carbon nanotubes, and fabrication techniques for driving scalable quantum device production. Quantum machine learning (QML) algorithms to solve complex optimizations and predictive tasks. Researching optimal solutions in data and battery storage systems and finding the best algorithm in quantum networking and communication for long-range connectivity with a fast and secure network. Investigating challenges such as error corrections, cost, accessibility, and adaptability. Combining all modern innovations with one technology offers the best result that can change the theoretical fiction world into the real world, not today, but in a few decades.

  • References

    1. Bawa, N. S. (2024). Exploring Quantum Computing: Principles and applications. Journal of Quantum Science and Technology, 1(3), 57–69. https://doi.org/10.36676/jqst.v1.i3.27
    2. Feynman, R. P. (1982). Simulating physics with computers. International Journal of Theoretical Physics, 21(6–7), 467–488. https://doi.org/10.1007/bf02650179
    3. Arute, F., Arya, K., Babbush, R., Bacon, D., Bardin, J. C Foxen, B. Martinis, J. M. (2019). Quantum supremacy using a programmable supercon-ducting processor. Nature, 574(777 9), 505–510. https://doi.org/10.1038/s41586-019-1666-5
    4. Srivastava, D., Menon, M., & Cho, N. K. (2001b). Computational nanotechnology with carbon nanotubes and fullerenes. Computing in Science & Engineering, 3(4), 42–55. https://doi.org/10.1109/5992.931903
    5. Baydin, A., Tay, F., Fan, J., Manjappa, M., Gao, W., &Kono, J. (2022). Carbon Nanotube devices for quantum technology. Materials, 15(4), 1535. DOI: https://doi.org/10.3390/ma15041535
    6. Yao, S., Yu, H., Bi, M., Zhang, C., Zhang, T., Zhang, X., Liu, H., Shen, X., & Xiang, J. (2022). Effect of binders on the microstructural and elec-trochemical performance of high‐sulphur‐loading electrodes in lithium‐sulphur batteries. International Journal of Energy Research, 46(14), 19585–19598. https://doi.org/10.1002/er.8532
    7. Doricchi, A., Platnich, C. M., Gimpel, A., Horn, F., Earle, M., Lanzavecchia, G., Cortajarena, A. L., Liz-Marzán, L. M., Liu, N., Heckel, R., Grass, R. N., Krahne, R., Keyser, U. F., &Garoli, D. (2022). Emerging Approaches to DNA data Storage: Challenges and Prospects. ACS Nano, 16(11), 17552–17571. https://doi.org/10.1021/acsnano.2c06748
    8. Soukarie, D., Nocete, L., Bittner, A. M., & Santiago, I. (2023). DNA data storage in electrospun and melt-electrowritten composite nucleic acid-polymer fibers. Materials Today Bio, 24, 100900. https://doi.org/10.1016/j.mtbio.2023.100900
    9. Zakeri, B., & Lu, T. K. (2015). DNA nanotechnology: new adventures for an old warhorse. Current Opinion in Chemical Biology, 28, 9–14. https://doi.org/10.1016/j.cbpa.2015.05.020
    10. Acharya, R., Aleiner, I., Allen, R., Andersen, T. I., Ansmann, M., Arute, F., Arya, K., Asfaw, A., Atalaya, J., Babbush, R., Bacon, D., Bardin, J. C., Basso, J., Bengtsson, A., Boixo, S., Bortoli, G., Bourassa, A., Bovaird, J., Brill, L., Zhu, N. (2023). Suppressing quantum errors by scaling a surface code logical qubit. Nature, 614(7949), 676–681. https://doi.org/10.1038/s41586-022-05434-1
    11. Pattanayak, S. (2021). Quantum Machine Learning with Python. In Apress eBooks. https://doi.org/10.1007/978-1-4842-6522-2
    12. Vazquez, A. C., Tornow, C., Ristè, D., Woerner, S., Takita, M., & Egger, D. J. (2024). Combining quantum processors with real-time classical communication. Nature, 636(8041), 75–79. https://doi.org/10.1038/s41586-024-08178-2
    13. Mohamed, W. a. A., El-Gawad, H. A., Mekkey, S., Galal, H., Handal, H., Mousa, H., &Labib, A. (2021). Quantum dots synthetization and future prospect applications. Nanotechnology Reviews, 10(1), 1926–1940. https://doi.org/10.1515/ntrev-2021-0118
    14. Pan, Y. (2024). Nanotechnology in Lithium-Sulfur Batteries: Addressing the challenges in battery cycle life and safety. Highlights in Science Engi-neering and Technology, 116, 190–196. https://doi.org/10.54097/zd5w0246
    15. Wild, M., O’Neill, L., Zhang, T., Purkayastha, R., Minton, G., Marinescu, M., & Offer, G. J. (2015). Lithium sulfur batteries, a mechanistic review. Energy & Environmental Science, 8(12), 3477–3494. https://doi.org/10.1039/c5ee01388g
    16. Einstein, A. (1920). Relativity: The Special and General Theory (R. W. Lawson, Trans.). Methuen & Co Ltd. (Original work published 1916). https://www.marxists.org/reference/archive/einstein/relativity/index.htm
    17. Liu, M., Li, Z., Cai, K., Allcock, J., Zhang, S., & Lui, J. C. S. (2024). Quantum BGP with Online Path Selection via Network Benchmarking. In Proceedings of IEEE INFOCOM 2024 – IEEE Conference on Computer Communications (Vancouver, BC, Canada, May 20–23, 2024). https://doi.org/10.1109/INFOCOM52122.2024.10621359
    18. Jiang, J.-L., Luo, M.-X., & Ma, S.-Y. (2024). Quantum Network Capacity of Entangled Quantum Internet. IEEE Journal on Selected Areas in Communications, 42(7), 1900–1918. https://doi.org/10.1109/JSAC.2024.3380091
    19. Ding, Y., Llewellyn, D., Faruque, I. I., Bacco, D., Rottwitt, K., Thompson, M. G., Wang, J., &Oxenlowe, L. K. (2020). Quantum Entanglement and Teleportation Based on Silicon Photonics. Quantum Entanglement and Teleportation Based on Silicon Photonics, 1-4. https://doi.org/10.1109/icton51198.2020.9203437
    20. Kim, K., Lim, K., Choi, B., Lee, W., Ko, Y., Choe, J. Kim, M., You, J., & Youn, C. J. (2023). Controllable Passive Multi-polarization-states Gener-ator based on Silicon Photonics for Quantum Communication. Optical Fiber Communication Conference (OFC) 2022, W2A.36. https://doi.org/10.1364/ofc.2023.w2a.36
    21. Balaji, P. G., Chamikar, P., Chowdary, O., &Belwal, M. (2024). Optimizing Compiler for Quantum computing using QiSkIt Terra. 2022 13th Inter-national Conference on Computing Communication and Networking Technologies (ICCCNT), 1–7. https://doi.org/10.1109/icccnt61001.2024.10726185
    22. Nivelkar, M., &Bhirud, S. G. (2021). Optimized Machine Learning: training and classification performance using Quantum computing. 2021 IEEE 6th International Conference on Computing, Communication and Automation (ICCCA), 8–13. https://doi.org/10.1109/iccca52192.2021.96664299
    23. Abdelgaber, N., &Nikolopoulos, C. (2020). Overview of Quantum Computing and its Applications in Artificial Intelligence. Overview of Quantum Computing and Its Applications in Artificial Intelligence. https://doi.org/10.1109/aike48582.2020.00038
    24. Choi, J., Oh, S., & Kim, J. (2020). The useful quantum computing techniques for artificial intelligence engineers. 2022 International Conference on Information Networking (ICOIN), 1–3. https://doi.org/10.1109/icoin48656.2020.9016555
    25. Peng, L.-M., Zhang, Z., & Wang, S. (2014). Carbon nanotube electronics: Recent advances. https://doi.org/10.1016/j.mattod.2014.07.008
    26. Graham, A. P., Duesberg, G. S., Hoenlein, W., Kreupl, F., Liebau, M., Martin, R., Rajasekharan, B., Pamler, W., Seidel, R., Steinhoegl, W., & Un-ger, E. (2005). How do carbon nanotubes fit into the semiconductor roadmap? Applied Physics A, 80, 1141–1151. https://doi.org/10.1007/s00339-004-3151-7
    27. Mani, V., Chen, S.-M., & Lou, B.-S. (2013). Three-dimensional graphene oxide-carbon nanotubes and graphene-carbon nanotubes hybrids. Interna-tional Journal of Electrochemical Science, 8, 11641–11660. https://doi.org/10.1016/S1452-3981(23)13212-3
    28. Jhanwar, A., & Nene, M. J. (2021). Enhanced Machine Learning using Quantum Computing. 2021 Second International Conference on Electronics and Sustainable Communication Systems (ICESC), 1407–1413. https://doi.org/10.1109/icesc51422.2021.9532638
    29. Stamper-Kurn, D., Isaacs, J., Roy Moulik, S., Mouradian, S., Marwaha, K., Challenge Institute for Quantum Computation, University of California, Berkeley, University of California, Berkeley, University of California, Berkeley, & University of Chicago. (n.d.). Topical: Quantum technologies in space. https://smd-cms.nasa.gov/wpcontent/uploads/2023/05/194_d48f1fb875c016f97021c15addadb1ab_Stamper_KurnDanM.pdff
    30. Quantum nanoscience. (2021). Nature Nanotechnology, 16(12), 1293. https://doi.org/10.1038/s41565-021-01058-0
    31. Pant, A., Sharma, S., & Pant, K. (2023). Evaluation of Machine learning Algorithms for Air Quality Index (AQI) prediction. Journal of Reliability and Statistical Studies, 16(2), 229–242. https://doi.org/10.13052/jrss0974-8024.1621
    32. Younus, M., & Nurmandi, A. (2023). Concept of Time Travel and the Different Theories for Making It Possible and the Implications of Time Trav-elling. Journal of World Science, 2(4). https://doi.org/10.58344/jws.v2i4.268
    33. Mbagwu, J. P. C., Abubakar, Z. L., & Ozuomba, J. O. (2020). A Review Article on Einstein Special Theory of Relativity. International Journal of Theoretical and Mathematical Physics, 10(3), 65–71. https://doi.org/10.5923/j.ijtmp.20201003.03
  • Downloads

  • How to Cite

    Pant, A., Kothiyal, A. ., & Rawat , V. . (2025). Quantum Revolution: Integrating Nanotechnology, Artificial Intelligence and Sustainable Innovations for the Future. International Journal of Basic and Applied Sciences, 14(2), 452-461. https://doi.org/10.14419/xk2n4x45