The integration of comprehensive digital twins in laboratory environments heralds a paradigm shift, enabling a level of automation and data management previously unattainable. This integration promises to enhance the efficiency and scope of self-driving laboratories and pave the way for creating a general “artificial intelligence (AI) scientist” with universal capabilities.
Mxene-Based Hybrid Nano-Architectures for Environmental Remediation and Sensor Applications: From Design to Applications, Micro and Nano Technologies series, 2024, Pages 113-127