Implementing parallel arithmetic via acetylation and its application to chemical image processing
Implementing parallel arithmetic via acetylation and its application to chemical image processing
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DOI：
10.1098/rspa.2020.0899
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发表时间：
2021-04-01
影响因子：
3.5
通讯作者：
Kim, Eunsuk
中科院分区：
文献类型：
--
作者：
Dombroski, Amanda;Oakley, Kady;Kim, Eunsuk
化学混合物可以被用来以高度紧凑的形式存储大量数据，并且由于使用大规模分子库而具有大规模可扩展性的潜力。由于具有许多可用物种的并行性，基于化学的存储器还可以为具有增加的吞吐量的计算提供物理衬底。在这里，我们在化学溶液中表示非二元矩阵，并使用化学反应并行执行多个矩阵乘法和加法。作为一个案例研究，我们展示了图像处理，其中小灰度图像编码的化学混合物和基于内核的卷积进行使用苯酚乙酰化反应。在这些实验中，我们使用测量的反应产物（苯乙酸酯）的浓度来重建输出图像。此外，我们建立了实现化学图像处理所需的化学标准，并验证了基于反应的乘法。最重要的是，这项工作表明，基本的算术运算可以可靠地进行化学反应。我们的方法可以作为开发更先进的化学计算架构的基础。
Chemical mixtures can be leveraged to store large amounts of data in a highly compact form and have the potential for massive scalability owing to the use of large-scale molecular libraries. With the parallelism that comes from having many species available, chemical-based memory can also provide the physical substrate for computation with increased throughput. Here, we represent non-binary matrices in chemical solutions and perform multiple matrix multiplications and additions, in parallel, using chemical reactions. As a case study, we demonstrate image processing, in which small greyscale images are encoded in chemical mixtures and kernel-based convolutions are performed using phenol acetylation reactions. In these experiments, we use the measured concentrations of reaction products (phenyl acetates) to reconstruct the output image. In addition, we establish the chemical criteria required to realize chemical image processing and validate reaction-based multiplication. Most importantly, this work shows that fundamental arithmetic operations can be reliably carried out with chemical reactions. Our approach could serve as a basis for developing more advanced chemical computing architectures.