Hyphenated Mass Spectrometry Methods for Enlarged Capacity Data Storage Systems based on Chemical Mixtures

Abstract

Encoding abstract information in chemical mixtures uses the selective presence or absence of specific analytes, creating a binary-based framework for data storage. Data storage capacity (C in bits) can be maximized by encoding with large analyte libraries (M) at distinguishable concentration levels (L), where C = M·log2L. However, roboust decoding of such complex libraries remains challenging for practical applications. This study introduces hyphenated Mass Spectrometry (MS) methods, Liquid Chromatography (LC) and Flow Injection Analysis (FIA) that meet the dual requirements of high analyte coverage and precise quantitation to maximize data storage capacity. Encoding and decoding use plant metabolite libraries to create specific mixtures. Using LC-MS, it is feasible to encode and decode up to 200 bits per mixture, with scalability reaching 10³-10⁴ bits at the cost of low decoding rates (ca. 0.5 bits / sec). FIA-MS offers a high-throughput alternative, handling 100 bits at faster rates (ca. 3 bits / sec). The data storage capacity can be three-fold expanded by incorporating up to eight quantitation levels, supporting binary, quaternary, or octal encoding schemes. To demonstrate the practical application of these methods, we encode and decode various digital file formats such as texts and multicolor images.