Multicomponent molecular memory.

Area of Science:

• Chemistry
• Data Storage
• Bioinformatics

Background:

• Multicomponent reactions (MCRs) are widely used in the pharmaceutical industry for synthesizing large molecular libraries due to their scalability.
• The potential of MCRs for applications beyond drug discovery, such as data storage, remains largely unexplored.

Purpose of the Study:

• To demonstrate the feasibility of using multicomponent reactions for large-scale molecular data storage.
• To encode and retrieve art historical image data using the Ugi reaction and mass spectrometry.

Main Methods:

• Employed the four-component Ugi reaction for combinatorial synthesis of molecular libraries.
• Encoded over 1.8 million bits of art historical image data, including a Picasso drawing.
• Utilized robotic synthesis for data writing and mass spectrometry for data reading, combined with sparse mixture mapping and supervised learning.

Main Results:

• Successfully encoded and retrieved digital data from synthesized Ugi product libraries.
• Achieved low bit error rates as low as 0.11% for single reads without library purification.
• Demonstrated the scalability of MCRs for non-biological data storage.

Conclusions:

• Multicomponent reactions, specifically the Ugi reaction, offer a viable platform for large-scale molecular data storage.
• This approach provides an information-centric perspective on high-throughput synthesis and screening of small-molecule libraries.
• The method shows promise for efficient and scalable data archiving using chemical synthesis.