| Citation: | HE Tao, KANG Dong, GAN Liming, FENG Boxin, WANG Xiao, WANG Xi, WANG Peng. Preparation of Spent Mushroom Substrate Biochar and Its Application for Gold Determination in Rock and Mineral Samples by Flame Atomic Absorption SpectrometryJ. Rock and Mineral Analysis, 2026, 45(2): 434-445. DOI: 10.15898/j.ykcs.202503180049 |
Gold, as an important element in critical minerals, requires high-accuracy and high-precision analytical methods, crucial for revealing the genesis of geological minerals and for mineral resource exploration. Although activated carbon adsorption-flame atomic absorption spectrometry (FAAS) has been widely used for the determination of gold in rock and mineral samples, the quality of activated carbon significantly impacts the analytical results for gold. Conventional activated carbon is characterized by high ash content and low adsorption rate (only 90%–92%), which limits its application efficiency. Based on the high efficiency and environmental friendliness of spent mushroom substrate (SMS) biochar, an analytical method for gold determination using SMS biochar adsorption coupled with FAAS has been established. Single-factor experiments confirmed that carbonization temperature, ultrasonic time, modifier concentration, and adsorption time significantly affect the adsorption efficiency of SMS biochar for gold. By optimizing the preparation conditions via response surface methodology (RSM), the optimal preparation conditions were determined as follows: carbonization temperature of 505℃, ultrasonic time of 54 min, modifier concentration of 9%, and adsorption time of 170 min. Under these conditions, the gold adsorption rate reached over 98%. Using SMS biochar prepared under the optimized conditions as the adsorbent, spiked recovery tests were carried out on 4 gold ore certified reference materials (CRMs) with different gold contents and 4 real samples by FAAS. For the gold CRMs, the relative error (RE) between the determined values and the certified values ranged from 0.05% to 1.59%, and the relative standard deviation (RSD,