In recent years, the field of molecular data storage has emerged from a niche to a vibrant research topic. Herein, we describe a simultaneous and automated read-out of data stored in mixtures of sequence-defined oligomers. Therefore, twelve different sequence-defined tetramers and three hexamers with different mass markers and side chains are successfully synthesised via iterative Passerini three-component reactions and subsequent deprotection steps. By programming a straightforward python script for ESI-MS/MS analysis, it is possible to automatically sequence and thus read-out the information stored in these oligomers within one second. Most importantly, we demonstrate that the use of mass-markers as starting compounds eases MS/MS data interpretation and furthermore allows the unambiguous reading of sequences of mixtures of sequence-defined oligomers. Thus, high data storage capacity considering the field of synthetic macromolecules (up to 64.5 bit in our examples) can be obtained without the need of synthesizing long sequences, but by mixing and simultaneously analysing shorter sequence-defined oligomers.

近年来，分子数据存储领域已经从一个小众领域发展成为一个充满活力的研究主题。在此，我们描述了存储在序列定义的寡聚物混合物中的数据的同步和自动读出。因此，通过迭代的帕塞里尼三组分反应和随后的去保护步骤，成功合成了十二个不同的序列定义的四聚体和三个具有不同质量标记和侧链的六聚体。通过编写用于 ESI-MS/MS 分析的简单 Python 脚本，可以在一秒钟内自动测序并读出这些低聚物中存储的信息。最重要的是，我们证明使用质量标记作为起始化合物可以简化 MS/MS 数据解释，此外还可以明确读取序列定义的寡聚物混合物的序列。因此，考虑到合成大分子领域（在我们的示例中高达 64.5 位），无需合成长序列，而是通过混合并同时分析较短的序列定义的低聚物，即可获得高数据存储容量。