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.
Title : Circumventing challenges in developing CVD graphene on steels for extraordinary and durable corrosion resistance
Raman Singh, Monash University, Australia
Title : Evaluating cytotoxicity of metal-doped tin oxide nanoparticles
Paulo Cesar De Morais, Catholic University of Brasilia, Brazil
Title : Nanotechnology and polymers for sea and ocean sterilization using artificial intelligence with artificial intelligence-engineered nano-polymer membranes
Fadi Ibrahim Ahmed, Al-shujaa bin Al-aslam School, Kuwait
Title : Dual memory characteristics and crystallographic transformations in shape memory alloys
Osman Adiguzel, Firat University, Turkey
Title : Flexible fabric-based nanostructured color-generating film systems
Xinhua Ni, Guangzhou City University of Technology, China
Title : A broadband, angle-insensitive aluminium-based near infra-red absorber for protecting warfighters and sensitive optics technologies
Chayanika Baishya, Indian Institute of Technology Guwahati, India