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Abstract：
Nowadays, it is fascinating to engineer waste biomass into functional valuable nanomaterials. We investigate the production of hetero-atom doped carbon quantum dots (N-S@MCDs) to address the adaptability constraint in green precursors concerning the contents of the green precursors i.e., Tagetes erecta (marigold extract). The successful formation of N-S@MCDs as described has been validated by distinct analytical characterizations. As synthesized N-S@MCDs successfully incorporated on corn-starch powder, providing a nano-carbogenic fingerprint powder composition (N-S@MCDs/corn-starch phosphors). N-S@MCDs imparts astounding color-tunability which enables highly fluorescent fingerprint pattern developed on different non-porous surfaces along with immediate visual enhancement under UV-light, revealing a bright sharp fingerprint, along with long-time preservation of developed fingerprints. The creation and comparison of latent fingerprints (LFPs) are two key research in the recognition and detection of LFPs, respectively. In this work, developed fingerprints are regulated with an artificial intelligence program. The optimum sample has a very high degree of similarity with the standard control, as shown by the program\'s good matching score (86.94%) for the optimal sample. Hence, our results far outperform the benchmark attained using the conventional method, making the N-S@MCDs/corn-starch phosphors and the digital processing program suitable for use in real-world scenarios.
摘要：
如今,将废弃生物质转化为有价值的功能性纳米材料是令人着迷的。我们研究了杂原子掺杂的碳量子点（N-S@MCD）的生产，以解决绿色前体中有关绿色前体含量的适应性约束，即万寿菊（万寿菊提取物）。所述N-S@MCD的成功形成已通过不同的分析表征得到验证。合成的N-S@MCDs成功掺入玉米淀粉粉，提供纳米碳指纹粉末组合物(N-S@MCD/玉米淀粉磷光体)。N-S@MCD赋予了惊人的色彩可调性，可以在不同的无孔表面上形成高度荧光的指纹图案，并在紫外线下立即增强视觉，露出一个明亮清晰的指纹，以及长时间保存的指纹。潜在指纹(LFP)的创建和比较是LFP识别和检测的两项关键研究,分别。在这项工作中,开发的指纹是由人工智能程序控制的。最佳样品与标准对照具有非常高的相似性，如程序所示，最佳样本的良好匹配分数（86.94％）。因此，我们的结果远远超过了使用常规方法获得的基准，使N-S@MCD/玉米淀粉荧光粉和数字处理程序适用于现实世界的场景。
