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.

可以利用化学混合物以高度紧凑的形式存储大量数据，并且由于使用了大规模的分子库，因此具有潜在的大规模可扩展性。由于具有许多可用物种而产生的并行性，基于化学的存储器还可以为物理计算提供更高的吞吐量。在这里，我们表示化学溶液中的非二进制矩阵，并使用化学反应并行执行多个矩阵乘法和加法。作为案例研究，我们演示了图像处理，其中在化学混合物中编码小灰度图像，并使用苯酚乙酰化反应进行基于核的卷积。在这些实验中，我们使用测得的反应产物（乙酸苯酯）浓度重建输出图像。此外，我们建立了实现化学图像处理和验证基于反应的乘法所需的化学标准。最重要的是，这项工作表明基本的算术运算可以通过化学反应可靠地进行。我们的方法可以作为开发更高级的化学计算体系结构的基础。