10th Edition of World Nanotechnology Conference
March 10-12, 2025
AI and Machine Learning in Nanotechnology
AI and Machine Learning in Nanotechnology are accelerating the development of new materials and applications by enabling better simulations, predictions, and optimization processes. AI-driven algorithms are used to analyze vast amounts of data, helping researchers identify the most promising nanomaterials for specific applications, whether in medicine, energy storage, or electronics. Machine learning techniques also enable the design of nanomaterials with customized properties, enhancing their performance and efficiency. Additionally, AI is improving the manufacturing processes for nanomaterials, making them more scalable and cost-effective. The integration of AI and machine learning with nanotechnology is unlocking new possibilities for creating smarter, more efficient solutions across various industries.
Harry E Ruda
University of Toronto, Canada
Paulo Cesar De Morais
Catholic University of Brasilia, Brazil
Thomas J Webster
Hebei University of Technology, China
Frank Hagelberg
East Tennessee State University, United States
Ribal Georges Sabat
Royal Military College of Canada, Canada
Thomas J Webster
Hebei University of Technology, China
Antonio Pantano
University of Palermo, ItalySubmit your abstract Today
Title : Recent advances in nanomedicine: Sensors, implants, artificial intelligence, saving the environment, human studies, and more
Thomas J Webster, Hebei University of Technology, China
Title : Harnessing the unique transport properties of InAs nanowires for single molecule level sensing
Harry E Ruda, University of Toronto, Canada
Title : Photonic metasurfaces in azobenzene materials
Ribal Georges Sabat, Royal Military College of Canada, Canada
Title : Using CuO polycrystalline nanofilms as sensor for small organic molecules
Paulo Cesar De Morais, Catholic University of Brasilia, Brazil
Title : Microplastics and nanoplastics in Antartica. Consideration their impact on ecosystems and human and fauna health
Maria Cecilia Colautti, Defense University of Republic of Argentina, Argentina
Title : Surface-enhanced stimulated Raman spectroscopy with squeezed photonic states
Frank Hagelberg, East Tennessee State University, United States