AI and Robotic Technology in Materials and Chemistry Research

provides a necessary and timely introduction for the materials and chemistry scientist with traditional synthesis skills, about why and how to accept digitalization.

Autorentext
Prof. Xi Zhu obtained his bachelor's degree in physics from the University of Science and Technology of China (USTC) in 2006, and his Ph.D. at Nanyang Technological University (NTU), Singapore, in 2011. He joined The Chinese University of Hong Kong, Shenzhen in 2017, and holds the position of deputy director at Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS). His research interests focus on the application of condensed matter physics theory in interdisciplinary research. His current research focuses on the AI application in materials science and pharmacy, he leads the development of the on-demand and in-cloud materials synthesis platform scheme "MAOSIC" based on intelligent robots and cloud computing; and developed the blockchain technology endorsed automatic experimental platform (BiaeP) for unforgettable experimental data. Promoting the new advance of materials science in the AI era..

Inhalt

1. SURVEY OF CHALLENGES IN CHEMISTRY AND MATERIALS SCIENCE RESEARCH Introduction Energy Form Data 2. ROBOTS TECHNOLOGY DEVELOPMENT IN MORDEN SCIENTIFIC RESEARCH Introduction Early Development of Laboratory Automation (Before 2000) Preliminary Integration and Development of Laboratory Automation (2000-2019) Latest Developments and Current Trends (2020-2023) Outlook on Future Development Conclusion 3. AI ALGORITHM FOR CHEMICAL AND BIO MATERIALS DESIGN Introduction Molecular Representation and Encoding The Formulation of Accessible and Searchable Data AI for Molecular Structure-Property Relationship AI for Chemical and Bio Material Design 4. AUTONOMOUS LABORATORY EMPOWERED BY AI AND ROBOTICS Evolution of Laboratory Core Technologies in Autonomous Laboratories Example Autonomous Laboratory Solution Advanced Autonomous Laboratory Solutions Future Prospects and Trends 5. LARGE LANGUAGE MODELS FOR THE AUTONOMOUS MATERIALS RESEARCH Review of Large Language Models Development and Applications Fundamentals of LLM for Material Research: Database and Knowledge Base Construction Evaluation: Spider Matrix Ideation: AI Supervisor and ScholarNet Results and Discussion Conclusion 6. TOWARDS A BLOCKCHAIN-POWERED ANTI-COUNTERFEITING EXPERIMENTAL DATA SYSTEM IN AN AUTONOMOUS LABORATORY Blockchain Technology Laboratory Chemical Management and Safety The Problem of Data Integrity and Counterfeiting in Scientific Research Blockchain in the Autonomous Laboratory Symbolic Representation of Experiments Challenges and Limitations Conclusion 7. THE FUTURE INTEGRATED COMPUTATIONAL AND EXPERIMENTAL RESEARCH IN METAVERSE Introduction of Metaverse Research Paradigm in Metaverse H2O Phase Research in Metaverse Aqueous System Research in Metaverse Challenges & Future Directions