資源・素材2024(秋田)

講演情報(2024年8月7日付 確定版)

若手・一般ポスター発表

15:15-17:15 ポスター発表(鉱物処理/リサイクル) [9/11(水) PM ポスター発表会場]

2024年9月11日(水) 15:15 〜 17:15 ポスター会場 3(大学会館 1F クレール)

15:15 〜 17:15

[P047C] Optimization of mediators in laccase reactions for degradation of carbonaceous matter in double refractory gold ores

○Cindy -1[博士課程], Hirofumi Ichinose1, Keiko Sasaki2 (1. Kyushu University, 2. Waseda University)

キーワード:Double refractory gold ores, Carbonaceous matter, Enzymatic degradation, Laccase, Mediator

Despite their higher Au contents compared to other ores, double refractory gold ores (DRGOs) have not been economically developed due to the presence of sulfides locking Au grains and carbonaceous matter capable of adsorbing Au(CN)2- during cyanidation. Growing environmental concerns have driven the exploration of more sustainable methods for degrading carbonaceous matter in DRGOs. This study investigated the use of laccase enzyme, assisted by various electron mediators, to enhance the degradation of carbonaceous matter, thereby improving Au extraction efficiency. While the laccase-mediator system (LMS) is known to oxidize both phenolic and non-phenolic compounds, its effectiveness in treating the complex aromatic structures found in DRGOs remains underexplored. The research delved into the mechanisms of several mediators—1-hydroxybenzotriazole hydrate, 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid), 2,6-dimethoxyphenol, violuric acid monohydrate, and guaiacol—in LMSs to optimize the degradation process. Various characterization techniques, including Raman spectrometry, 3-dimensional fluorescence spectrometry, and thermogravimetry-differential thermal analysis, were utilized to assess the carbonaceous matter before and after treatments. Results indicated that optimizing mediators for LMS in solid-phase reactions significantly enhanced carbonaceous matter degradation, leading to higher Au extraction. This advancement not only promises more efficient Au recovery but also aligns with sustainable mining practices. Further research is warranted to refine these methods and assess their scalability.

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