Phase principle: the effect of melting ice will help create new materials with shape memory

Russian scientists have developed an original approach that allows us to study in detail what happens to matter at the moment of its transition from one state to another — for example, when ice melts, turning into water, or when water evaporates. For the first time, the specialists managed not only to record the fact of the transition itself, but also to analyze the internal state of the system at a critical point. The proposed approach is important not only for fundamental research, but also for the design of materials with unique properties, such as shape memory alloys, polymers for robotics, microelectronics and space technologies, experts say.

What is a phase transition?

Scientists from the L.D. Landau Institute of Theoretical Physics of the Russian Academy of Sciences (Chernogolovka) and graduate students from the National Research University Higher School of Economics (Moscow) have developed an original approach that allows us to study in detail what happens to matter at the moment of its transition from one state to another, using the example of melting ice.

For the first stage of the study, the authors used the cHARISMa supercomputer from the National Research University of Higher School of Economics. With this device, scientists mathematically "froze" the system at the point of phase transition, when ice and water exist simultaneously. Moreover, they did this not once, but thousands, creating many different "copies" of the system, each of which froze in a unique state of this transformation. This approach allowed us to obtain a large amount of data on behavior at a critical point.

Until now, scientists did not have the tools to study in detail the probabilities of finding a system in each of these phases at a critical temperature. The study of the state at the temperature of a phase transition of the first kind is important not only for a fundamental understanding of the nature of transitions, but also for the design of materials with controlled properties, such as shape memory alloys or polymers, the scientists said.

In the next step, the researchers applied a deep machine learning method to recognize one of three phases: water, ice, and a mixture of them. This is a key innovation — instead of the traditional division into two phases, the algorithm has learned to identify three states, allowing it to detail the critical point and see what is happening inside. Thus, scientists were able to estimate the probability of finding a substance in one state or another, which had previously failed due to the lack of a suitable technique for this.

— The combination of supercomputer technologies for obtaining a large set of data and machine learning methods for their analysis allowed us to take a fresh look at the first-kind phase transition. In fact, we have managed to look inside the critical point. In the future, we plan to study in detail the geometric phase transitions in the mixed state. There is a hypothesis that the probability of formation in a mixed state of a cluster reaching macroscopic size is finite. Apparently, our method will make it possible to give this a clearer formulation with an estimate of this probability," Lev Shchur, project leader, Doctor of Physico—Mathematical Sciences, head of the Laboratory of Computational Physics at the Higher School of Economics and chief researcher at the Landau Institute for Theoretical Physics of the Russian Academy of Sciences, told Izvestia.

Classification using machine learning will make it possible to study a whole class of complex systems in physics, chemistry and materials science that were previously difficult or impossible to analyze in such detail, the scientists said.

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What new materials can be obtained?

The research opens up opportunities for designing new materials with controllable properties, such as shape memory alloys, polymers, and functional coatings that can change their structure and characteristics under the influence of temperature, pressure, or an electric field, Alexey Salimon, head of the NUST MISIS Department of Physical Chemistry, told Izvestia.

— Such materials are in demand in microelectronics, aerospace, medicine and robotics. Understanding what happens in a substance at the moment of a phase transition helps to consciously refine the parameters of computational models and thereby predict how to change the composition or structure of a substance in order to obtain the desired properties. The greatest progress in this area is expected with a combination of supercomputer calculations, machine learning and experiments," the expert said.

Phase transition materials (MFPs) are capable of storing energy from 100 to 300 kJ/kg and releasing it over a narrow temperature range, explained Evgeny Alexandrov, Director of the NTI Center for Digital Materials Science: New Materials and Substances at Bauman Moscow State Technical University.

— Used as water heaters, portable heat accumulators for air conditioning and smoothing temperature fluctuations indoors. The global market for phase-change materials is projected to reach $6.3 billion by 2030, growing by about 19.8% annually. So far, only imported raw materials are available in Russia," the scientist noted.

The conducted research opens up new approaches for creating materials in non-trivial phases. In particular, this way it is possible to purposefully control the optical and electronic properties of a material without changing its basic chemical composition, but by controlling its crystallographic or surface phase, said Alexey Bolshakov, director of the Center for Photonics and Two-Dimensional Materials at MIPT. In this case, phase control can be achieved by using extreme synthesis modes that bring the system out of thermodynamic equilibrium.

The results of the study, supported by a grant from the Russian Science Foundation (RSF), are published in the journal Physical Review E.