Greenhouse Gas 'Methane' Replaced with Industrial Rice 'Ethylene'

Domestic Researchers Greatly Improve Yield Using Artificial Intelligence, Increasing Commercialization Potential

An illustration of the Artificial Bee Colony algorithm used to find conditions that increase the yield of the desired product (C2 compound) and minimize the formation of byproducts (charcoal, coke). Photo by Korea Research Institute of Chemical Technology

[Asia Economy Reporter Kim Bong-su] A pathway is expected to open for converting the greenhouse gas methane into useful chemical raw materials such as ethylene. A domestic research team has succeeded in raising the yield (ethylene output relative to methane input) to about 20%, close to the commercialization level (over 25%), through virtual experiments using artificial intelligence.

According to the Korea Research Institute of Chemical Technology on the 22nd, Dr. Hyun-Joo Jang and Dr. Hyun-Woo Kim from the Chemical Platform Research Division, along with Dr. Yong-Tae Kim from the Chemical Process Research Division, recently conducted experiments under challenging conditions such as temperatures exceeding 1000 degrees Celsius, gas velocity, and pressure directly in the laboratory to achieve these results. Utilizing machine learning and artificial bee colony algorithms of artificial intelligence, they performed virtual experiments to directly convert methane, a greenhouse gas, into useful chemical raw materials (such as ethylene), achieving a yield of about 20%, more than 10% higher than before. Ethylene, known as the "rice" of petrochemicals, is widely used as a raw material in everyday products including general plastics, vinyl, synthetic rubber, various construction materials, adhesives, and paints.

Methane is a substance derived from petrochemical processes and shale gas. Of the global annual methane production of 900 million tons, 92.2% is used for heating or power generation, while only 7.8% is used as a chemical raw material. Therefore, researchers have been seeking ways to convert methane into chemical raw materials. However, catalytic processes that directly convert methane into chemical raw materials without oxygen input are technically challenging and have not been commercialized due to the large amount of byproduct (charcoal) produced. In particular, when charcoal accumulates in the process pipeline, environmental and safety concerns arise, making it crucial to increase yield while minimizing byproducts.

In 2019, Dr. Yong-Tae Kim’s team at the same institute recorded a yield of 5.9% with almost no byproducts. Building on this, the research team achieved a 13% yield, twice that of 2019, through this AI research collaboration. This research achievement was even selected as the back cover paper of the international journal Reaction Chemistry & Engineering. After submitting the paper, the team continued AI-based research and has currently raised the direct conversion yield of methane to ethylene to 20%.

The basic yield for commercialization of methane-to-ethylene conversion is generally predicted by academia to be over 25%, with byproduct selectivity (the ratio of byproducts generated relative to converted methane) below 20%. The research team notably identified experimental conditions through AI that yield high output with minimal byproducts, and verified these conditions through direct experiments within an acceptable margin of error.

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