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S1 Graphical abstract -

التفاصيل البيبلوغرافية
العنوان: S1 Graphical abstract -
المؤلفون: Nisha Yadav, Deeksha Mudgal, Amarnath Mishra, Sacheendra Shukla, Tabarak Malik, Vivek Mishra
سنة النشر: 2024
مصطلحات موضوعية: Biotechnology, Ecology, Inorganic Chemistry, Science Policy, Biological Sciences not elsewhere classified, Chemical Sciences not elsewhere classified, Information Systems not elsewhere classified, two key research, tagetes erecta <, results far outperform, marigold extract ), machine learning algorithms, immediate visual enhancement, good matching score, functional valuable nanomaterials, engineer waste biomass, distinct analytical characterizations, bright sharp fingerprint, benchmark attained using, artificial intelligence program, porous surfaces along, mcds successfully incorporated, green precursors concerning, div >< p, starch phosphors ), green precursors, starch phosphors, program ’, starch powder, time preservation
الوصف: 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.
نوع الوثيقة: article in journal/newspaper
اللغة: unknown
Relation: https://figshare.com/articles/journal_contribution/S1_Graphical_abstract_-/24944168
DOI: 10.1371/journal.pone.0296270.s013
الاتاحة: https://doi.org/10.1371/journal.pone.0296270.s013
https://figshare.com/articles/journal_contribution/S1_Graphical_abstract_-/24944168
Rights: CC BY 4.0
رقم الانضمام: edsbas.7824A028
قاعدة البيانات: BASE
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