Publication

Abstract : The convergence of Artificial Intelligence (AI) and nanotechnology has revolutionized how nanoscale systems are studied, developed, and applied. This review explores the transformative potential of AI in nanotechnology, highlighting its applications, benefits, and challenges. AI's ability to analyze complex data, predict nanoscale phenomena, and optimize processes has enabled significant advancements in nanomaterials discovery, nanomanufacturing, nanomedicine, and nanosensors. For example, AI has accelerated the discovery of nanomaterials for energy storage, optimized nanoparticle designs for personalized drug delivery, and enhanced the sensitivity of nanosensors for environmental monitoring.<br><br>Despite its benefits, the integration of AI in nanotechnology faces challenges, including data scarcity, high computational demands, and the complexity of nanoscale interactions. Ethical and regulatory issues, such as data privacy and algorithmic bias, also need to be addressed. However, emerging trends in quantum computing, interdisciplinary collaborations, and the development of explainable AI frameworks promise to overcome these hurdles, paving the way for transformative innovations.<br><br>This review concludes by emphasizing the need for responsible innovation and global cooperation to harness AI's full potential in nanotechnology. By addressing current challenges and exploring future opportunities, AI-driven nanotechnology can play a critical role in solving global challenges, including climate change, energy sustainability, and advanced healthcare solutions.