Technical Report 339, c4e-Preprint Series, Cambridge

Authors: Simon D. Rihm, Aleksandar Kondinski, and Markus Kraft*

Reference: Technical Report 339, c4e-Preprint Series, Cambridge, 2025

Associated Themes:
 

• AI and automation for accelerated materials discovery
• Semantic ontologies bridge computational and experimental domains
• The World Avatar enables dynamic, interoperable research workflows
• Demonstration of automated material discovery in reticular chemistry
• Demonstration of cross domain laboratory automation

This paper investigates how digital chemistry technologies such as machine learning, knowledge engineering, and laboratory automation are revolutionizing materials discovery for pressing global challenges in energy and healthcare. We introduce a comprehensive technology framework that integrates advanced databases, artificial intelligence models, semantic ontologies, and robotic systems to address fundamental challenges in chemical research. The World Avatar platform serves as a central case study, demonstrating its unique ability to connect computational design with experimental execution through dynamic and interoperable workflows. Practical applications in reticular chemistry and automated laboratory systems showcase the platform's capacity to enable autonomous discovery processes. Together, these technological advances are driving chemical research toward more scalable, reproducible, and intelligent materials development approaches.

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