Chemical Data Storage Encoding Digital Information
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Solution Overview
Problem
Current data storage technologies face limitations in achieving high information density and parallel speedy memory interrogation, particularly in molecular and chemical information systems.
Innovation Solution
The development of a method for computing with chemicals, where abstract digital data is encoded into liquid volumes of chemicals, translated into a chemical form, and read using spectrometry or spectroscopy, enabling the use of chemical perceptrons for data storage and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If DNA is used for long-term archival information storage, then information density is improved (achieving about 214 petabytes per gram), but memory interrogation speed deteriorates (requiring cumbersome stochastic methods like PCR or sequential methods like nanopores)
Solution Approach 1:
The patent replaces slow stochastic biochemical methods (PCR) and sequential physical methods (nanopores) with parallel optical detection methods (spectrometry and spectroscopy). This substitution enables simultaneous reading of multiple chemical signals, dramatically improving memory interrogation speed while maintaining the high information density of molecular storage systems.
Solution Approach 2:
The patent implements preliminary encoding of digital data into chemical forms (absorption spectra, fluorescence emissions, mass-to-charge ratios) that are inherently parallelizable. By pre-organizing data in chemical dimensions that can be simultaneously detected, the system enables fast parallel interrogation without requiring sequential processing of individual molecules.
2Productivity
If conventional semiconductor technologies are used, then memory interrogation speed is maintained, but information density deteriorates (lacking the extreme density achieved by molecular storage)
Solution Approach 1:
The patent transitions from two-dimensional planar storage in semiconductors to multi-dimensional chemical space utilization. By encoding information across multiple chemical dimensions (different molecules, concentrations, spectral properties, mass-to-charge ratios), the system achieves exponential increases in information density while maintaining parallel processing capabilities through chemical reactions and optical detection.
3Quantity of substance
If the metabolome is used for information storage, then information density and dynamic range are improved, but system complexity deteriorates (managing diverse chemical dimensions and properties)
Solution Approach 1:
The patent employs a universal chemical language based on standardized molecular encodings where different molecules serve multiple functions. The same chemical detection methods (spectrometry, spectroscopy, mass spectrometry) can read multiple types of encoded information simultaneously, reducing operational complexity despite the diversity of chemical dimensions available for storage.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for high-density data storage and efficient data interrogation, demonstrating the potential for gigabyte-scale data storage with high accuracy and low power consumption.
Implementation Method 1
reading the data set using spectrometry, spectroscopy, or both analytical methods
Implementation Method 2
reading the data set using spectrometry, spectroscopy, or both analytical methods
Implementation Method 3
reading the data set using spectrometry, spectroscopy, or both analytical methods
Data Source
AI summary
The invention provides methods for computing with chemicals by encoding digital data into a plurality of chemicals to obtain a dataset; translating the dataset into a chemical form; reading the data set; querying the dataset by performing an operation to obtain a perceptron; and analyzing the perceptron for identifying chemical structure and/or concentration of at least one of the chemicals, thereby developing a chemical computational language. The invention demonstrates a workflow for representing abstract data in synthetic metabolomes. Also presented are several demonstrations of kilobyte-scale image data sets stored in synthetic metabolomes, recovered at >99% accuracy.