The application of Artificial Intelligence (AI) and Machine Learning (ML) to catalysis is revolutionizing the way researchers approach catalyst discovery, optimization, and reaction mechanism understanding. By using AI algorithms, researchers can now analyze and predict the complex relationships between catalyst composition, structure, and reaction outcomes, which were previously difficult to map manually. One of the primary advantages of Artificial Intelligence and Machine Learning in catalysis is their ability to process large datasets generated from high-throughput screening and experimental results. These algorithms can identify subtle correlations between catalyst properties and reaction performance, leading to the discovery of more efficient and selective catalysts. For example, ML models can be trained to recognize the structural features of catalysts that contribute to their reactivity, allowing for the design of new catalysts with optimized properties for specific reactions. In addition to designing catalysts, AI and ML are also being applied to reaction mechanism analysis, where they can model the sequence of steps involved in catalytic processes, identifying intermediates, transition states, and energy profiles.
Stanislaw Dzwigaj
Sorbonne University, France
Dai Yeun Jeong
Asia Climate Change Education Center, Korea, Republic of
Enrico Paris
CREA-IT & DIAEE, Italy
Hanna Kierzkowska Pawlak
Lodz University of Technology, Poland
Ling Yin
Cornell University, United States
Tsitsishvili Vladimer
Petre Melikishvili Institute of Physical and Organic Chemistry at the Tbilisi State University, Georgia
Rafia Ahmad
King Abdullah University of Science and Technology, Saudi Arabia
Eun Han Lee
Korea Institute of Energy Research, Korea, Republic of
Neul Ha
Sungkyunkwan University, Korea, Republic of
Shailza Sharma
RMIT University, AustraliaSubmit your abstract Today
Title : Application of vanadium, tantalum and chromium single-site zeolite catalysts in catalysis
Stanislaw Dzwigaj, Sorbonne University, France
Title : Morphological studies of quaternary alloys
Yarub Al Douri, European Academy of Sciences, Belgium
Title : The Concept and Implications of Low Carbon Green Growth
Dai Yeun Jeong, Asia Climate Change Education Center, Korea, Republic of
Title : Advances in heterogeneous catalysis for green conversion of propene to aldehydes and alcohols
Ram Sambhar Shukla, CSIR-Central Salt and Marine Chemicals Research Institute (CSMCRI), India
Title : Advanced nanostructures for carbon neutrality and sustainable H₂ energy
Tokeer Ahmad, Jamia Millia Islamia, India
Title : Influence of various catalysts on H₂ enhancement and CO2 capture during syngas upgrading
Enrico Paris, CREA-IT & DIAEE, Italy
Title :
Ramesh C Gupta, Nagaland University, India
Title : Nanomaterials to fight cancer, cysts, infection, and numerous other health ailments: Human data
Thomas J Webster, Brown University, United States
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Ling Yin, Cornell University, United States
Title : Dimethyl ether synthesis from syngas over Cu-Zn/Al2O3 catalysts prepared using the Sol-Gel method
Uday Som, Shizuoka University, Japan