Carbon nanotubes are nanoscale, cylindrical, hollow, and tube-shaped molecules that are made of carbon atoms, according to Britannica.
According to a recent study, Skoltech researchers directed an international team to look into the best AI algorithms that help delineate conditions for synthesis that favor carbon nanotube formation. These contain characteristics that are tailored-fit to applications such as tech regarding hydrogen power, lasers, delivery of drugs, monitoring sensors that are environmental in nature, and other applications.
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AI and Carbon Nanotube Synthesis
The findings of the study were published in the Carbon publication.
Phys notes that if one thinks of graphene as a layer of carbon that has a thickness of a singular atom and that has atoms that form a honeycomb-like arrangement, nanotubes with single walls can be expected when a graphene sheet is wrapped in a cylinder. This may be the case even if this is not how carbon nanotubes are formed.
According to lead study author Dmitry Krasnikov, the study brings fresh ideas on how carbon nanotube properties are fine tuned. He mentions that because of their remarkable characteristics, carbon nanotubes can be applied in various ways. Krasnikov also states that there is no singular nanotube that is capable of ruling all fields and applications.
In order to come up with carbon nanotubes with specific properties, scientists need to understand the exact characteristics that get affected by certain tweaks in parameters and how they are affected.
According to primary investigator Albert Nasibulin, several parameters are involved, including the geometry of reactors, the composition of the gas, time of residence, and other parameters. Their complicated interplay means that optimising carbon nanotubes' synthesis may be something that AI excels at. Nasibulin notes that their specific study reveals the AI algorithms best for optimising aerosol synthesis parameters.
Aerosol Synthesis and Carbon Nanotubes
One common way of forming carbon nanotubes is through aerosol synthesis. The process involves feeding a preceding catalyst and carbon-containing gas into a specific reactor. In this process, elevated temperature levels lead to their decomposition. Both end up with carbon and particles that crystalize and become nanotubes.
In the recent study, researchers considered three conditions for synthesis that are variable and four that lead to affecting nanotube properties. These were done as part of attempts to maximize parameters in various models.
The researchers note that this study was conducted on a small scale and was pushed through with a narrow dataset-does not just show how 250 points of data are enough to come up with precise predictions but also serves as an important move toward reaching a smart reactor in Skoltech. As the data set grows, the research team may see more accurate predictions and unhurried expansions in the span of synthesis parameters that can be tuned and carbon nanotube properties that can be managed.
Later on, the smart reactor can become a comprehensive solution for managing and placing parameters that are the right fit for manufacturing carbon nanotubes with single walls. Later on, this can be done with characteristics tailored for certain applications.
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