Research team to develop superconducting materials by combining artificial intelligence, chemistry, and physics

The team members have worked extensively on researching the topic "Detection of Superconducting Materials at Room Temperature and Atmospheric Pressure Conditions Using Chemistry-Informed Neural Networks". To select a feasible and promising research topic, they combined artificial intelligence, physics, and chemistry.

Notably, the research team was honored with an award for presenting the best interdisciplinary project.

Aram Sargsyan, a researcher at YSU Photonics and Artificial Intelligence Laboratory, speaks about the objectives and significance of the project’s topic.

Currently, there are a variety of superconducting materials available worldwide, which, however, function either under extremely low temperature conditions or under very high pressure (when considering high temperatures). As a result, their widespread application remains costly and challenging, preventing us from fully harnessing their potential. This potential is significant, given that these materials are used in technologies such as quantum computers and magnetically levitated trains. Consequently, we aim to develop superconductors that operate under conditions close to normal atmospheric pressure and at as high temperatures as possible.

Another objective is to create new methodologies and algorithms that will enable us to design such stable materials. Here, we enhance conventional artificial intelligence by incorporating relevant principles from chemistry and physics. This allows us to develop artificial intelligence models that inherently understand the chemical and physical laws at play in these processes.

In the global scientific community, topics in these areas are of great interest and are still considered unsolved problems. Any progress made in addressing these challenges will bring us a step closer to an energy-efficient world and a new era in operating and computing systems.

Aram is an expert in artificial intelligence, also engaged in the design of optical computing systems and the optimization of optoelectronic issues. Within the framework of this project, he will attempt to "bridge" artificial intelligence and chemistry by designing chemistry-informed neural networks, conducting experiments, collecting and processing data, and creating algorithms. According to him, such initiatives contribute to the formation of a stronger and more collaborative scientific community.

Armen Hovhannisyan, a researcher at the Institute of Chemical Physics of the National Academy of Sciences of Armenia, a lecturer at the Chair of Management at the European University of Armenia (EUA), and a chemist-environmentalist, speaks about the challenges in planning the project, overcoming them, and the outcomes of the research work.

There were several challenges, but they were mainly related to the shortage of time and the lack of "manpower." Regarding time, we had only 3 days to conceptualize the project, develop it, and explore possible directions. Before that, the team consisted of five members, but three days before the project deadline, only Aram and I remained. I believe that overcoming these challenges is the result of our diligence and determination. We put in a great deal of effort for the success of this project. During the event, some of the jury members even joked that the topic deserved a Nobel Prize. 

From the perspective of technological innovation, the project offers the opportunity to create a chemistry-informed neural network, which will simplify data analysis in chemistry by eliminating errors associated with the human factor. Currently, such networks are rare in chemistry, and their level of application is very low or almost nonexistent.

The approach used in this project is entirely new and has great potential, considering the continuously developing digital technologies and the opportunities they provide. If successfully implemented, the results of the project will have revolutionary significance for the advancement of science.

The project’s expected outcome is the development of compounds/materials that exhibit superconductivity at room temperature and atmospheric pressure. These materials could serve as the foundation for technologies such as quantum computers for everyday use, flying vehicles, houses, and other innovations that we have only seen in movies. 

Armen will collect databases related to superconductors, develop and program chemistry-informed neural networks, synthesize chemical compounds, and extract characteristic properties using experimental methods, among other tasks.

At the conclusion of the work, the scientific team expects to achieve progress on two fronts: 

• Strengthening the connection between the fields of artificial intelligence and chemistry, and 
• Unveiling new horizons in the production of superconducting materials.

This scientific project, which combines artificial intelligence, physics, and chemistry, could be a significant step in the development of superconducting materials and open up new opportunities both in scientific and technological fields.