Multicomponent molecular memory
Multicomponent molecular memory
复制标题
DOI：
10.1038/s41467-020-14455-1
复制
发表时间：
2020-02-04
影响因子：
16.6
通讯作者：
Rosenstein, Jacob K.
中科院分区：
文献类型：
--
作者：
Arcadia, Christopher E.;Kennedy, Eamonn;Rosenstein, Jacob K.
多组分反应使得能够从相对较少的输入合成大分子文库。这种可扩展性导致制药行业广泛采用这些反应。在这里，我们采用四组分Ugi反应来证明多组分反应可以为大规模分子数据存储提供基础。使用这种组合化学，我们编码了超过180万位的艺术历史图像，包括毕加索的立体派绘画。使用Ugi产品的自动合成库写入数字数据，并使用质谱法读取文件。我们将联合收割机稀疏混合映射与监督学习相结合，以实现单个读取的低至0.11%的误码率，而无需文库纯化。除了改进非生物分子数据存储的规模外，这些演示还提供了以信息为中心的高通量合成和筛选小分子文库的观点。小的非聚合物分子具有巨大的结构多样性，可用于表示信息。在这里，作者在Ugi产品的合成库中编码数据。
Multicomponent reactions enable the synthesis of large molecular libraries from relatively few inputs. This scalability has led to the broad adoption of these reactions by the pharmaceutical industry. Here, we employ the four-component Ugi reaction to demonstrate that multicomponent reactions can provide a basis for large-scale molecular data storage. Using this combinatorial chemistry we encode more than 1.8 million bits of art historical images, including a Cubist drawing by Picasso. Digital data is written using robotically synthesized libraries of Ugi products, and the files are read back using mass spectrometry. We combine sparse mixture mapping with supervised learning to achieve bit error rates as low as 0.11% for single reads, without library purification. In addition to improved scaling of non-biological molecular data storage, these demonstrations offer an information-centric perspective on the high-throughput synthesis and screening of small-molecule libraries. Small non-polymeric molecules have tremendous structural diversity that can be used to represent information. Here the authors encode data in synthesized libraries of Ugi products.