Nanocrystals of Novel Lead-Free Perovskite Materials in a 3D Polymer Matrix: Synthesis and Evaluation of Their Applicability in Ionizing Radiation Detection – POLYNCS

Since the dawn of civilization, humans have needed to store and transmit information to pass accumulated knowledge to future generations. Methods of information storage have evolved significantly over the centuries. However, despite the sophistication of modern technologies, they struggle to keep pace with the explosive growth of data generation. The amount of data currently produced exceeds the capacity of conventional storage media, such as hard drives or flash memory—a trend that continues to accelerate. A major drawback of commonly used hard drives is their limited stability and high energy consumption.

Nature uses nucleic acids as its primary information carriers. It has been demonstrated that synthetic DNA can be used to encode binary code, enabling the storage of text or computer processor instructions through the representation of 0s and 1s by two selected nucleotides.

Sequence-defined polymers (SDPs) offer a stable, resource- and energy-efficient, and sustainable solution for data storage—a promising alternative to DNA. The properties of synthetic polymers can be precisely tailored to specific needs. By selecting structural building blocks from a wide library of synthetic monomers, polymer characteristics can be tuned to increase stability, extend lifespan, or simplify data reading. Moreover, the expanded alphabet of synthetic monomers enables higher information density.

In addition, the storage capacity of sequence-defined polymers can be further enhanced through spatial organization of digital polymers using non-covalent synthesis methods, such as Layer-by-Layer (LbL) deposition of polyelectrolytes. These approaches overcome the limitations of traditional polymer synthesis, allowing the sequential assembly of macromolecules on a small surface area and resulting in materials with exceptionally high data density.

Compared to conventional hard drives, the read/write speed of macromolecular data storage is significantly lower. Therefore, polymers will not replace electronic drives but may address the challenge of long-term data archiving, serving as durable molecular information carriers. A key requirement, however, is the efficiency and speed of data reading.

The project aims to develop sequence-defined polymers designed for reading encoded information based on their fluorescent properties. Fluorescent dye-containing monomers will be synthesized and used to encode information within macromolecular chains via iterative synthesis. A critical aspect of the work will be to select appropriate monomer structures that enable the formation of polymers exhibiting sequence-dependent fluorescence.

The resulting polymer characteristics will be used to train neural networks. By applying artificial intelligence tools, fluorescence can be evaluated as a method for reading information encoded in macromolecules. The project is based on the hypothesis that fluorescence spectroscopy offers a promising technique for polymer sequencing. The advantages of fluorescence as a sequencing method include speed, low cost, non-destructive measurement, no need for sample recovery, high sensitivity, and potential for miniaturization and high-throughput parallel analysis.

Despite the great potential of fluorescence for sequencing applications, the main scientific challenge of this project lies in designing polymers that generate sequence-dependent fluorescence signals. To achieve this, monomers will be designed to respond to the distance between fluorophore units (affecting energy transfer) and to environmental conditions.

The expected results will contribute to new fundamental knowledge on the relationship between monomer sequence and fluorescence properties in polymers. Research on discrete systems will allow for systematic comparison of different sequences and a deeper understanding of underlying phenomena. Furthermore, the use of AI tools will enable discoveries beyond the reach of traditional analytical methods. The acquired knowledge will advance the fields of polymer chemistry (through the synthesis of novel structures) and functional materials science (through the creation of new data storage materials), while also evaluating fluorescence spectroscopy as an emerging technique for polymer sequencing.