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Searching for chromate replacements using natural language processing and machine learning algorithms

Engineering and Technology

Searching for chromate replacements using natural language processing and machine learning algorithms

S. Zhao and N. Birbilis

This study, conducted by Shujing Zhao and Nick Birbilis, showcases how natural language processing and machine learning can uncover alternatives to chromate for corrosion protection. By analyzing an extensive database of scientific literature, the research reveals how automated interpretation can yield expert insights in materials science.

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