دنیای نانو

دنیای نانو

ادغام هوش مصنوعی و نانوتکنولوژی: پیشرفت‌ها، کاربردها و ملاحظات اخلاقی

نوع مقاله : مروری

نویسنده
گروه آموزش شیمی، دانشگاه فرهنگیان، تهران، ایران
چکیده
پژوهش حاضر به بررسی زمینه‌های ادغام هوش مصنوعی و نانوتکنولوژی می‌پردازد و نحوه بهره‌گیری تکنیک‌های هوش مصنوعی از جمله یادگیری ماشین، یادگیری عمیق و شبکه‌های عصبی را به منظور ارتقای بهره‌وری، دقت و مقیاس‌پذیری کاربردهای فناوری نانو بررسی می‌کند. برخی از کاربردهای هوش مصنوعی در نانوتکنولوژی شامل تسریع در کشف و بهینه‌سازی طراحی نانومواد، بهینه‌سازی تحویل دارو، استفاده از نانوحسگرهای مجهز به هوش مصنوعی برای نظارت بیولوژیکی و محیط‌زیستی و پیش‌بینی خواص مواد بیان می‌شود. علاوه بر آن، چالش‌ها، فرصت‌ها و چشم‌اندازهای پیش روی ادغام هوش مصنوعی و فناوری نانو به منظور ایجاد پیشرفت‌های تحول‌آفرین در زمینه‌های گوناگون از مراقبت‌های بهداشتی و علم مواد گرفته تا پایداری محیط‌زیستی بررسی می‌شود. در پایان به مسائل اخلاقی همچون سوگیری الگوریتمی، حریم خصوصی داده‌ها و اثرات اجتماعی ادغام این فناوری‌ها پرداخته و بر ضرورت وضع مقررات شفاف، توسعه مسئولانه و اخلاقی برای اطمینان از ادغام نانوتکنولوژی مبتنی بر هوش مصنوعی تأکید می‌شود.
کلیدواژه‌ها
موضوعات

عنوان مقاله English

Integration of Artificial Intelligence and Nanotechnology: Advancements, Applications, and Ethical Considerations

نویسنده English

Seyed Mohsen Mousavi
Department of Chemistry Education, Farhangian University, Tehran, Iran
چکیده English

This study explores the integration of artificial intelligence and nanotechnology, examining how artificial intelligence techniques, including machine learning, deep learning, and neural networks, enhance the efficiency, precision, and scalability of nanotechnology applications. Main artificial intelligence This study examines the integration of artificial intelligence and nanotechnology, focusing on how AI techniques, including machine learning, deep learning, and neural networks, enhance the efficiency, precision, and scalability of nanotechnology applications. Key AI applications in nanotechnology include accelerating nanomaterial discovery and design optimization, improving drug delivery systems, and utilizing AI-driven nanosensors for biological and environmental monitoring. Furthermore, AI is applied to predict material properties, supporting innovations in energy. This study also assesses the challenges, opportunities, and potential of AI and nanotechnology integration for transformative progress in fields from healthcare and materials science to environmental sustainability. Ethical issues, including algorithmic bias, data privacy, and societal impact, are discussed, highlighting the necessity for transparent regulations and ethical frameworks to ensure the responsible application of AI-driven nanotechnology.

کلیدواژه‌ها English

Nanotechnology
Artificial Intelligence
AI-Nanotechnology Integration
Nanomaterials
Nanosensors
[1] Kumar A, Jayeoye TJ, Mohite P, Singh S, Rajput T, Munde S, Eze FN, Chidrawar VR, Puri A, Prajapati BG, Parihar A. Sustainable and consumer-centric nanotechnology-based materials: An update on the multifaceted applications, risks and tremendous opportunities. Nano-Structures & Nano-Objects. 2024;38:101148. https://doi.org/10.1016/j.nanoso.2024.101148
[2] Luther W. International strategy and foresight report on nanoscience and nanotechnology. Future Technologies Division of VDI Technologiezentrum GmbH, 2004.
[3] Naik GG, Minocha T, Yadav SK, Sahu AN. Fluorescent carbon dots for sensing therapeutic moieties. Nanomedicine. 2024;19(18):1687-1710.
[4] Khan MY, Elme NS, Tahrim HM, Raza K. A Review on Nanotechnology and Its Impact with Challenges on Electrical Engineering. Control Systems and Optimization Letters. 2024;2(1):82-9. https://doi.org/10.59247/csol.v2i1.78
[5] Naik GG, Minocha T, Verma A, Yadav SK, Saha S, Agrawal AK, Singh S, Sahu AN. Asparagus racemosus root-derived carbon nanodots as a nano-probe for biomedical applications. Journal of Materials Science. 2022;57(43):20380-401. https://doi.org/10.1007/s10853-022-07908-z
[6] Naik GG, Pratap R, Mohapatra D, Shreya S, Sharma DK, Parmar AS, Patra A, Sahu AN. From phytomedicine to photomedicine: quercetin-derived carbon nanodots—synthesis, characterization and healthcare applications. Journal of Materials Science. 2023;58(34):13744-61. https://doi.org/10.1007/s10853-023-08880-y
[7] Anusha JR, Citarasu T, Uma G, Vimal S, Kamaraj C, Kumar V, Muzammil K, Sankar MM. Recent advances in nanotechnology-based modifications of micro/nano PET plastics for green energy applications. Chemosphere. 2024;141417. https://doi.org/10.1016/j.chemosphere.2024.141417
[8] Karthikeyan B, Velvizhi G. A state-of-the-art on the application of nanotechnology for enhanced biohydrogen production. International Journal of Hydrogen Energy. 2024;52:536-54. https://doi.org/10.1016/j.ijhydene.2023.04.237
[9] Bayda S, Adeel M, Tuccinardi T, Cordani M, Rizzolio F. The history of nanoscience and nanotechnology: from chemical-physical applications to nanomedicine. Molecules. 2019;25(1):112. https://doi.org/10.3390/molecules25010112
[10] Liu L, Bi M, Wang Y, Liu J, Jiang X, Xu Z, Zhang X. Artificial intelligence-powered microfluidics for nanomedicine and materials synthesis. Nanoscale. 2021;13(39):19352-66. https://doi.org/10.1039/D1NR06195J
[11] McCarthy J, Minsky ML, Rochester N, Shannon CE. A proposal for the Dartmouth summer research project on artificial intelligence, August 31, 1955. AI Magazine. 2006;27(4):12-4. https://doi.org/10.1609/aimag.v27i4.1904
[12] Heydari S, Masoumi N, Esmaeeli E, Ayoubzadeh SM, Ghorbani-Bidkorpeh F, Ahmadi M. Artificial Intelligence in nanotechnology for treatment of diseases. Journal of Drug Targeting. 2024;1-20. https://doi.org/10.1080/1061186X.2024.2393417
[13] Liang CJ, Le TH, Ham Y, Mantha BR, Cheng MH, Lin JJ. Ethics of artificial intelligence and robotics in the architecture, engineering, and construction industry. Automation in Construction. 2024;162:105369. https://doi.org/10.1016/j.autcon.2024.105369
[14] Liu Y, Alzahrani IR, Jaleel RA, Al Sulaie S. An efficient smart data mining framework based cloud internet of things for developing artificial intelligence marketing information analysis. Information Processing & Management. 2023;60(1):103121. https://doi.org/10.1016/j.ipm.2022.103121
[15] Hangaragi S, Singh T, Neelima N. Face detection and Recognition using Face Mesh and deep neural network. Procedia Computer Science. 2023;218:741-9. https://doi.org/10.1016/j.procs.2023.01.054
[16] Waisberg E, Ong J, Masalkhi M, Zaman N, Sarker P, Lee AG, Tavakkoli A. Meta smart glasses—large language models and the future for assistive glasses for individuals with vision impairments. Eye. 2024;(6):1036-8. https://doi.org/10.1038/s41433-024-02986-y
[17] Saraf S, You HW, Umapathi M, Ravikumar KK, Mishra S. Strategies of artificial intelligence tools in the domain of nanomedicine. Journal of Drug Delivery Science and Technology. 2023;91:105157. https://doi.org/10.1016/j.jddst.2023.105157
[18] Sacha GM, Varona P. Artificial intelligence in nanotechnology. Nanotechnology. 2013;24(45):452002. https://doi.org/10.1088/0957-4484/24/45/452002
[19] Hassan SA, Almaliki MN, Hussein ZA, Albehadili HM, Banoon SR, Al-Aboodi A, Al-Saady M. Development of Nanotechnology by Artificial Intelligence: A Comprehensive Review. Journal of Nanostructures. 2023;13(4):915-32.
[20] Agrawal R, Tilak P, Devand A, Bhatnagar A, Gupta P. Artificial Intelligence in Nanotechnology. International Conference on Data Science and Big Data Analysis 2023 (pp. 239-248). Singapore: Springer Nature. https://doi.org/10.1007/978-981-99-9179-2_18
[21] Sarwar S, Raja DA, Hussain D. Chapter 1 Introduction to nanotechnology, in Handbook of Nanomaterials, 2024;1:1-26. https://doi.org/10.1007/978-3-662-54357-3_1
[22] Wang Y, Fu EY, Zhai X, Yang C, Pei F. Introduction of artificial Intelligence. Intelligent Building Fire Safety and Smart Firefighting. Cham: Springer Nature Switzerland, 2024: 65-97. https://doi.org/10.1007/978-3-031-48161-1_4
[23] Marquis YA, Oladoyinbo TO, Olabanji SO, Olaniyi OO, Ajayi SA. Artificial Intelligence: Transforming Nanotechnology and Materials Science. Asian Journal of Advanced Research and Reports. 2024;18(1):30-5. https://doi.org/10.9734/ajarr/2024/v18i1596
[24] Chugh V, Basu A, Kaushik A, Bhansali S, Basu AK. Employing nano-enabled artificial intelligence (AI)-based smart technologies for prediction, screening, and detection of infectious diseases. Nanoscale. 2024;16(11):5458-86. https://doi.org/10.1039/D3NR05648A
[25] Badini S, Regondi S, Pugliese R. Unleashing the power of artificial intelligence in materials design. Materials. 2023;16(17):5927. https://doi.org/10.3390/ma16175927
[26] Choudhary K, Wines D, Li K, Garrity KF, Gupta V, Romero AH, Kroger JT, Saritas K, Fuhr A, Ganesh P, Kent PR. JARVIS-Leaderboard: a large scale benchmark of materials design methods. npj Computational Materials. 2024;10(1):93. https://doi.org/10.1038/s41524-024-01259-w
[27] Nandipati M, Fatoki O, Desai S. Bridging Nanomanufacturing and Artificial Intelligence—A Comprehensive Review. Materials. 2024;17(7):1621. https://doi.org/10.3390/ma17071621
[28] Liu Z, Zhao Y, Yin Z. Low-power soft transistors triggering revolutionary electronics. The Innovation. 2024;5(3). https://doi.org/10.1016/j.xinn.2024.100616
[29] Papadimitriou I, Gialampoukidis I, Vroshidis S, Kompatsiaris I. AI methods in materials design, discovery and manufacturing: A review. Computational Materials Science. 2024;235:112793. https://doi.org/10.1016/j.commatsci.2024.112793
[30] Li C, Bao L, Ji Y, Tian Z, Cui M, Shi Y, Zhao Z, Wang X. Combining machine learning and metal-organic frameworks for advanced separation applications. Chemical Engineering Journal. 2024.
[31] Yan J, Zhang Z, Meng M, Li J, Sun L. Insights into deep learning framework for molecular property prediction based on different tokenization algorithms. Chemical Engineering Science. 2024;285:119471. https://doi.org/10.1016/j.ces.2023.119471
[32] Agu PC, Obulose CN. Piquing artificial intelligence towards drug discovery: Tools, techniques, and applications. Drug Development Research. 2024;85(2):e22159. https://doi.org/10.1002/ddr.22159
[33] Naik GG, Jagtap VA. Two Heads Are Better than One: Unravelling the Potential Impact of Artificial Intelligence in Nanotechnology. Nano TransMed. 2024:100041. https://doi.org/10.1016/j.ntm.2024.100041
[34] Wang Z, Zhu X. Enhancing Nanocrystal Synthesis: A Comparative Study of Online AI Optimization and Offline High-Throughput Experimentation in Chemical Material Discovery. ACS Applied Nano Materials. 2024;7(6):6499-505. https://doi.org/10.1021/acsanm.4c00255
[35] Vidya Wicaksana Putra R, Marchisio A, Zayer F, Dias J, Shafique M. Embodied Neuromorphic Artificial Intelligence for Robotics: Perspectives, Challenges, and Research Development Stack. arXiv e-prints. 2024:arXiv-2404.03325. https://doi.org/10.48550/arXiv.2404.03325
[36] Zhou JB, Tang D, He L, Lin S, Lei JH, Sun H, Xu X, Deng CX. Machine learning model for anti-cancer drug combinations: Analysis, prediction, and validation. Pharmacological Research. 2023;194:106830. https://doi.org/10.1016/j.phrs.2023.106830
[37] Kumar A, Panda D, Gangawane KM. Computational modeling on the design of the morphology of aerogels. Hybrid Aerogels: Energy and Environmental Applications. 2024:269.
[38] Vijaya R, Lincy BC, RamanG G, Kirubakaran N, Chacko L, Bhupathyraaj M, Kiruba M, Alharbi HF. Applications of Artificial Intelligence in Drug Delivery Systems. In: Artificial Intelligence in Pharmaceutical Sciences. 2023:42-53, CRC Press.
[39] Deori C, Hujuri L, Sarma G, Sonowal T. Artificial Intelligence (AI): Its Role in Drug Discovery and Novel Drug Delivery System. International Journal of Science and Research. 2024;13(2):1426-1430. https://doi.org/10.21275/SR24219203948
[40] Zhang P, Guo Z, Ullah S, Melagaki G, Afantitis A, Lynch I. Nanotechnology and artificial intelligence to enable sustainable and precision agriculture. Nature Plants. 2021;7(7):864-876. https://doi.org/10.1038/s41477-021-00946-6
[41] Skäur S, Kumar R, Singh K, Huang Y. Leveraging artificial intelligence for enhanced sustainable energy management. J. Sustain. Energy. 2024;3(1):1-20. https://doi.org/10.56578/jse030101
[42] Arellano Vidal CL, Govan JE. Machine learning techniques for improving nanosensors in agro-environmental applications. Agronomy. 2024;14(2):341. https://doi.org/10.3390/agronomy14020341
[43] Parihar A, Sharma P, Choudhary NK, Khan R, Mostafavi E. Internet-of-Things-integrated Molecularly Imprinted Polymer-based Electrochemical Nanosensors for Pesticide Detection in the environment and food products. Environmental Pollution. 2024:124029. https://doi.org/10.1016/j.envpol.2024.124029
[44] Thakur A, Devi P. A comprehensive review on water quality monitoring devices: materials advances, current status, and future perspective. Critical Reviews in Analytical Chemistry. 2024;54(2):193-218. https://doi.org/10.1080/10408347.2022.2070838
[45] Liu S, Tian G, Xu Y. A novel scene classification model combining ResNet based transfer learning and data augmentation with a filter. Neurocomputing. 2019;338:191-206. https://doi.org/10.1016/j.neucom.2019.01.090
[46] Adir O, Poley M, Chen G, Froim S, Krinsky N, Shklover J, Shainsky-Roitman J, Lammers T, Schroeder A. Integrating artificial intelligence and nanotechnology for precision cancer medicine. Advanced Materials. 2020;32(13):1901989.
[47] Sacha GM, Varona P. Artificial intelligence in nanotechnology. Nanotechnology. 2013;24(45):452002. https://doi.org/1088/0957-4484/24/45/452002
[48] Yang Y, Bevan MA, Li B. Efficient navigation of colloidal robots in an unknown environment via deep reinforcement learning. Advanced Intelligent Systems. 2020;2(1):1900106. https://doi.org/10.1002/aisy.201900106
[49] Holzinger A, Keiblinger K, Holub P, Zatloukal K, Müller H. AI for life: Trends in artificial intelligence for biotechnology. New Biotechnology. 2023;74:16-24. https://doi.org/10.1016/j.nbt.2023.02.001
دوره 20، شماره 76
پاییز 1403
صفحه 136-121

  • تاریخ دریافت 10 آبان 1403
  • تاریخ پذیرش 24 آذر 1403