DistantNews
China's 'super catalyst' turns waste water into fertiliser building block, tripling output
🇨🇳 China /Environment & Climate

China's 'super catalyst' turns waste water into fertiliser building block, tripling output

From South China Morning Post · (2h ago) English Positive tone

Translated from English, summarized and contextualized by DistantNews.

TLDR

  • A Chinese research team developed a novel dual-atom catalyst (DAC) that converts nitrate pollution in wastewater into ammonia with nearly triple the efficiency of traditional methods.
  • The breakthrough, detailed in the Journal of the American Chemical Society, utilizes AI-driven deep learning to identify effective metal pairs for the catalyst, overcoming previous manufacturing challenges.
  • This innovation offers a low-energy waste-to-resource solution that could significantly bolster China's fertilizer supply chain.

South China Morning Post reports on a significant scientific advancement originating from China: a 'super catalyst' capable of transforming harmful nitrate pollution in wastewater into ammonia, a key component for fertilizer production. This breakthrough, achieved by researchers at the Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, not only triples the efficiency of conventional methods but also offers a low-energy, waste-to-resource pathway.

dual-atom catalysts, or DACs. Unlike their single-atom cousins, DACs feature two adjacent metal atoms able to work together drive complex, multi-step reactions, such as turning nitrate into ammonia or converting carbon dioxide.

Explaining the core technology behind the breakthrough.

The innovation hinges on dual-atom catalysts (DACs), which, unlike single-atom catalysts, can drive complex chemical reactions. A key challenge in DAC development has been the painstaking, trial-and-error process of identifying suitable metal pairs. However, the Chinese team leveraged deep learning and AI to train a model that efficiently pinpoints these pairs, significantly accelerating the development process and overcoming limitations in metal loading and fitting.

But making them has long been a painstaking trial-and-error affair, with little theoretical guidance, low metal loadings and the lack of an easy way to fit in different metal pairs.

Describing the previous challenges in developing dual-atom catalysts.

Published in the prestigious Journal of the American Chemical Society and featured on its cover, this research underscores China's growing prowess in scientific innovation. The potential impact on the nation's fertilizer supply chain is substantial, promising greater self-sufficiency and more sustainable agricultural practices. This development is a testament to the power of interdisciplinary research, combining materials science with artificial intelligence to address pressing environmental and industrial needs.

Han Lili and her colleagues at the Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, relied on deep learning to train an AI model to pinpoint metal pairs with high pairing rates – those that readily lock together.

Detailing the method used by the researchers to overcome previous challenges.
DistantNews Editorial

Originally published by South China Morning Post in English. Translated, summarized, and contextualized by our editorial team with added local perspective. Read our editorial standards.

More Stories

From Our Blog