The visual story of data storage: From storage properties to user interfaces

Hyphenated mass spectrometry methods for enlarged capacity data storage systems based on chemical mixtures

Encoding abstract information in chemical mixtures uses the selective presence or absence of specific analytes, creating a binary-based framework for data storage. Data storage capacity (C in bits) can be maximized by encoding with large analyte libraries (M) at distinguishable concentration levels (L), where C = M·log2L. However, roboust decoding of such complex libraries remains challenging for practical applications. This study introduces hyphenated mass spectrometry (MS) methods, liquid chromatography (LC) and flow injection analysis (FIA) that meet the dual requirements of high analyte coverage and precise quantitation to maximize data storage capacity. Encoding and decoding use plant metabolite libraries to create specific mixtures. Using LC-MS, it is feasible to encode and decode up to 200 bits per mixture, with scalability reaching 103-104 bits at the cost of low decoding rates (ca. 0.5 bits per sec). FIA-MS offers a high-throughput alternative, handling 100 bits at faster rates (ca. 3 bits per sec). The data storage capacity can be three-fold expanded by incorporating up to eight quantitation levels, supporting binary, quaternary, or octal encoding schemes. To demonstrate the practical application of these methods, we encode and decode various digital file formats such as texts and multicolor images.

Super-multiplexed imaging and coding in the range of radio frequency

The era of the Internet has led to an information explosion, creating significant challenges for current techniques in information storage and access. High-performance strategies that expand existing methods offer a promising solution. Imaging-based approaches are vital for information perception but remain underexplored for information processing due to limited multiplexity. Here, we introduce 19F magnetic resonance imaging-Empowered information Assess and Storage Technique (FEAST), enabled by 22 fluorinated quaternary ammonium derivatives with distinct 19F chemical shifts. We developed three coding platforms for FEAST: fluorinated choline analog solutions, fluorinated deep eutectic solvents, and fluorinated ionogels. These platforms allow 2-spatial-dimensional applications, such as 16-bit encoding, "dual-color" watermarking, multiplexed Colorcodes, and encrypted QR codes, as well as 3-spatial-dimensional applications like "cubic" information storage, implanted anti-counterfeit labels, and FEAST-guided encryption. This work highlights FEAST's potential for advanced information storage and access, which is inspiring for further developments with versatile and robust coding platforms.

Data Storage Using DNA

The exponential growth of global data has outpaced the storage capacities of current technologies, necessitating innovative storage strategies. DNA, as a natural medium for preserving genetic information, has emerged as a highly promising candidate for next-generation storage medium. Storing data in DNA offers several advantages, including ultrahigh physical density and exceptional durability. Facilitated by significant advancements in various technologies, such as DNA synthesis, DNA sequencing, and DNA nanotechnology, remarkable progress has been made in the field of DNA data storage over the past decade. However, several challenges still need to be addressed to realize practical applications of DNA data storage. In this review, the processes and strategies of in vitro DNA data storage are first introduced, highlighting recent advancements. Next, a brief overview of in vivo DNA data storage is provided, with a focus on the various writing strategies developed to date. At last, the challenges encountered in each step of DNA data storage are summarized and promising techniques are discussed that hold great promise in overcoming these obstacles.

Content-based filter queries on DNA data storage systems

Recent developments in DNA data storage systems have revealed the great potential to store large amounts of data at a very high density with extremely long persistence and low cost. However, despite recent contributions to robust data encoding, current DNA storage systems offer limited support for random access on DNA storage devices due to restrictive biochemical constraints. Moreover, state-of-the-art approaches do not support content-based filter queries on DNA storage. This paper introduces the first encoding for DNA that enables content-based searches on structured data like relational database tables. We provide the details of the methods for coding and decoding millions of directly accessible data objects on DNA. We evaluate the derived codes on real data sets and verify their robustness.

DNA-Aeon provides flexible arithmetic coding for constraint adherence and error correction in DNA storage

The extensive information capacity of DNA, coupled with decreasing costs for DNA synthesis and sequencing, makes DNA an attractive alternative to traditional data storage. The processes of writing, storing, and reading DNA exhibit specific error profiles and constraints DNA sequences have to adhere to. We present DNA-Aeon, a concatenated coding scheme for DNA data storage. It supports the generation of variable-sized encoded sequences with a user-defined Guanine-Cytosine (GC) content, homopolymer length limitation, and the avoidance of undesired motifs. It further enables users to provide custom codebooks adhering to further constraints. DNA-Aeon can correct substitution errors, insertions, deletions, and the loss of whole DNA strands. Comparisons with other codes show better error-correction capabilities of DNA-Aeon at similar redundancy levels with decreased DNA synthesis costs. In-vitro tests indicate high reliability of DNA-Aeon even in the case of skewed sequencing read distributions and high read-dropout.

Nanopore Detection Assisted DNA Information Processing

The deoxyribonucleotide (DNA) molecule is a stable carrier for large amounts of genetic information and provides an ideal storage medium for next-generation information processing technologies. Technologies that process DNA information, representing a cross-disciplinary integration of biology and computer techniques, have become attractive substitutes for technologies that process electronic information alone. The detailed applications of DNA technologies can be divided into three components: storage, computing, and self-assembly. The quality of DNA information processing relies on the accuracy of DNA reading. Nanopore detection allows researchers to accurately sequence nucleotides and is thus widely used to read DNA. In this paper, we introduce the principles and development history of nanopore detection and conduct a systematic review of recent developments and specific applications in DNA information processing involving nanopore detection and nanopore-based storage. We also discuss the potential of artificial intelligence in nanopore detection and DNA information processing. This work not only provides new avenues for future nanopore detection development, but also offers a foundation for the construction of more advanced DNA information processing technologies.

Design considerations for advancing data storage with synthetic DNA for long-term archiving

Deoxyribonucleic acid (DNA) is increasingly emerging as a serious medium for long-term archival data storage because of its remarkable high-capacity, high-storage-density characteristics and its lasting ability to store data for thousands of years. Various encoding algorithms are generally required to store digital information in DNA and to maintain data integrity. Indeed, since DNA is the information carrier, its performance under different processing and storage conditions significantly impacts the capabilities of the data storage system. Therefore, the design of a DNA storage system must meet specific design considerations to be less error-prone, robust and reliable. In this work, we summarize the general processes and technologies employed when using synthetic DNA as a storage medium. We also share the design considerations for sustainable engineering to include viability. We expect this work to provide insight into how sustainable design can be used to develop an efficient and robust synthetic DNA-based storage system for long-term archiving.