Quantification of superoxide anions (O₂^•−) is significant in the monitoring of many serious diseases and the design of enzyme-mimic catalysts plays the main role in the development of non-enzymatic O₂^•− sensors. Herein, we proposed a facile self-assembly process to synthesize manganese phosphate modified carbon networks using three kinds of widely-used carbon materials (MWCNTs, NGS and GO) as pillar connectors. Characterizations demonstrate that manganese phosphate is widely dispersed inside and on the surface of carbon networks without visible morphology. Meanwhile, all three kinds of synthesized catalysts were successfully immobilized on the screen-printed carbon electrodes to evaluate the electrochemical performance of fabricated sensors. The results indicate that sensors based on Mn_x(PO₄)_y modified MWCNTs exhibit high sensitivity with an extremely low detection limit of 0.127 μM (S/N = 3) and a wide liner range of 0–1.817 mM (R² = 0.998). We further employed the recommended sensors in the real-time monitoring of HepG2 cells released O₂^•− under the stimulating of Zymosan (20 mg/mL). Noticeably, the proposed sensors exhibit not only sensitive response but also stable current steps upon different addition of Zymosan. The calculated concentrations of cell-released O₂^•− vary from 6.772 to 24.652 pM cell⁻¹ for the Zymosan amount used in this work. The established novel sensors display low background current and signal noises, thus holding unique advantages in the trace analysis of O₂^•− in biological samples and in vivo environment.

超氧阴离子（O ₂ ^•-）的定量在许多严重疾病的监测中具有重要意义，酶模拟催化剂的设计在非酶O ₂ ^•-的发展中起主要作用传感器。本文中，我们提出了一种简便的自组装方法，该方法使用三种广泛使用的碳材料（MWCNT，NGS和GO）作为支柱连接器来合成磷酸锰改性的碳网络。表征表明磷酸锰广泛分散在碳网络的内部和表面，没有可见的形态。同时，将三种合成的催化剂成功地固定在丝网印刷的碳电极上，以评估所制备传感器的电化学性能。结果表明，基于Mn _x（PO ₄）_y修饰的MWCNT的传感器表现出高灵敏度，极低的检测限0.127μM（S / N = 3）和宽的衬管范围0–1.817 mM（R ²= 0.998）。我们还采用了推荐的传感器，在对酵母聚糖（20 mg / mL）的刺激下，实时监测释放的O ₂ ^•-的HepG2细胞。值得注意的是，提出的传感器不仅表现出灵敏的响应，而且在添加酵母聚糖的情况下也表现出稳定的电流阶跃。对于这项工作中使用的酵母聚糖，计算出的细胞释放O ₂ ^•的浓度范围从6.772到24.652 pM细胞^-1。已建立的新型传感器显示低背景电流和信号噪声，因此在生物样品和体内环境中O ₂ ^•的痕量分析中拥有独特的优势。