Artificial Intelligence (AI) and Machine Learning (ML) are transforming catalysis by providing innovative approaches to accelerate catalyst discovery, optimization, and understanding reaction mechanisms. AI and ML's ability to process vast data enables efficient analysis of complex catalytic systems, offering insights that would be difficult to obtain through traditional methods. One of the primary applications of Artificial Intelligence and Machine Learning in catalysis is the design of new catalysts with enhanced performance. By utilizing machine learning algorithms, researchers can predict catalyst properties based on molecular structure, identifying key features that improve efficiency. Additionally, AI and ML are revolutionizing the study of reaction mechanisms by modeling complex catalytic cycles and transition states, leading to more selective and efficient processes. As AI and ML technologies advance, they will continue to play a crucial role in developing more sustainable and cost-effective catalytic processes for industrial applications.
Title : A desirable framework for establishing a resource circulation society
Dai Yeun Jeong, Jeju National University, Korea, Republic of
Title : Design of efficient and stable structured catalysts for biofuels transformation into syngas by using advanced technologies of nanocomposite active components synthesis, supporting on heat conducting substrates and sintering
Vladislav Sadykov, Novosibirsk State University, Russian Federation
Title : Dipotassium cobalt pyrophosphate: From solid-state synthesis to the assessment of K2CoP2O7 for the oxidative degradation of methylene blue
Nora Elouhabi, Ibn Tofail University, Morocco
Title : Personalized and Precision Medicine (PPM) as a unique healthcare model through Bi-odesign-Inspired Bio- and chemical engineering applications to secure the human healthcare and biosafety: Engineering of biocatalysts - from evolution to creation
Sergey Suchkov, R&D Director of the National Center for Human Photosynthesis, Mexico
Title : Enhanced photocatalytic activities of NaLi1.07Co2.94(MoO4)5 nanoparticles under solar light
Rawia Nasri, University of Tunis El Manar, Tunisia
Title : Sulfur-doped geometry-tunable carbon nitride nanotubes with high crystallinity for visible light nitrogen fixation
Yuxiang Zhu, Yunnan University, China