7th Edition of
Chemistry World Conference
June 21-23, 2027 | Rome, Italy
AI & Machine Learning in Chemistry
Advancements in AI & machine learning in chemistry are revolutionizing research by enhancing reaction predictions, material design, and drug discovery. Machine learning models analyze vast chemical datasets, accelerating compound screening and reaction optimization. AI-driven simulations reduce trial-and-error in experiments, making chemical processes more efficient and sustainable. Neural networks and predictive algorithms improve molecular modeling, enabling precise identification of novel compounds. Automation in data analysis streamlines workflows in spectroscopy, chromatography, and synthesis. The integration of AI with experimental chemistry fosters innovation across multiple fields, from pharmaceuticals to green chemistry. As computational power grows, machine learning continues to reshape chemical research, driving faster discoveries and smarter, data-driven solutions.
Thomas Jay Webster
Brown University, United States
Yong Xiao Wang
Albany Medical College, United States
Hossam A Gabbar
Ontario Tech University, Canada
Victor John Law
University College Dublin, IrelandSubmit your abstract Today
Title : Fighting antibiotic resistance: Eliminating implant infections in humans without antibiotics
Thomas Jay Webster, Brown University, United States
Title : Direct solar leaf-dehydration: physiochemistry, and practice on the island of Crete
Victor John Law, University College Dublin, Ireland
Title : Tomographic image of molecules based on spin-spin interactions that are part of them resonating nuclei of atoms
Vladimir Voronov, Irkutsk National Research Technical University, Russian Federation
Title : PH-dependent recoil stabilization in Iodates following the (n,gamma) process
Shree Niwas Chaturvedi, Centre for Aptitude Analysis and Talent Search, Heritage School, Buxar, India
Title : Antibacterial activity of bioactive compounds extracted from the Egyptian untapped green algae Rhizoclonium hieroglyphicum
Ahmed Diab Mohamed Ahmed El Esawy, Drinking Water and Sanitation Company, Egypt
Title : Study of hydrogen transfer reactions within the framework of the non-equilibrium approach
I A Romanskii, N N Semenov Institute of Chemical Physics, Russian Federation