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dc.contributor.authorde Almeida, João Paulo
dc.contributor.authorRodrigo Silva, Jackson
dc.contributor.authorSabino-Júnior, José Roberto
dc.contributor.authorCarvalho, Vinicius A.
dc.contributor.authorToito Suarez, Willian
dc.contributor.authorErenas Rodríguez, Miguel María 
dc.contributor.authorCapitán Vallvey, Luis Fermín 
dc.contributor.authorOliveira, Severino Carlos
dc.contributor.authordos Santos, Vagner Bezerra
dc.date.accessioned2025-10-01T09:56:09Z
dc.date.available2025-10-01T09:56:09Z
dc.date.issued2025-09-19
dc.identifier.citationde Almeida, J. P., Silva, J. R., Sabino-Júnior, J. R., Carvalho, V. A., Suarez, W. T., Erenas, M. M., Capitán-Vallvey, L. F., Oliveira, S. C., & dos Santos, V. B. (2025). Nitrogen-doped carbon quantum dot nanoparticle fluorescent probes for quantification of Ni(II) in environmental water samples collected using an unmanned aerial vehicle. ACS Applied Nano Materials, acsanm.5c03254. https://doi.org/10.1021/acsanm.5c03254es_ES
dc.identifier.urihttps://hdl.handle.net/10481/106741
dc.description.abstractIn this work, an innovative and low-cost method was developed to quantify Ni(II) ions in environmental water samples based on fluorescence digital images from quantum dots using a smartphone as a detector. The method is based on the fluorescence quenching of nitrogen-doped carbon dots (N,C-QDs) when nickel reacts with dimethylglyoxime. The fluorescence emission from nanoparticles is captured by a smartphone coupled to a portable UV-LED chamber. An analytical curve was developed to detect Ni(II), and a concentration range from 10.9 to 275.0 μg L–1 with detection and quantification limits of 2.7 and 8.3 μg L–1, respectively. Thus, the method attempted the recommended values of Ni(II) according to agencies such USEPA (100 μg L–1), WHO (70 μg L–1), EFSA (20 μg L–1), and CONAMA (25 μg L–1) for fresh waters. Moreover, to evaluate the accuracy and precision of the proposed method, a reference method based on inductively coupled plasma-optical emission spectrometry was used for comparison purposes. The results obtained by both methods showed no differences at a 95% confidence level (n = 3) when employing the F-test and T-test statistical methods. Furthermore, the fluorescence digital image-based (FDIB) method was highly selective for Ni(II) ions with an interference response lower than 5.0%, and it presented a good recovery from 93.6 to 109.0%. Moreover, aiming to develop a high-level automation method for environmental monitoring, an adapted unmanned aerial vehicle (UAV) controlled by a smartphone via Wi-Fi, equipped with a micropump and a miniaturized solenoid valve powered by a solar energy system, was developed. This innovation reduced collection time, allowed access to hard-to-reach locations, and reduced sampling costs by using renewable energy, thus being environmentally friendly. This new analytical method using N,C-QDs-FDIB-UAV proposed for monitoring Ni(II) in environmental water samples offers numerous advantages, such as high sensitivity, selectivity supplied by nanoparticle probe together the portability, low cost, autonomous, and an eco-friendly methodology obtained from the UAV system.es_ES
dc.description.sponsorshipFundação de Amparo à Ciência e Tecnologia de Pernambuco (FACEPE) (APQ-0942-1.06/22, APQ-0413-1.06/21, APQ-1050-1.06/24)es_ES
dc.description.sponsorshipConselho Nacional de Ciência e Tecnologia (CNPQ) (421147/2018-0, 441109/2023-3, 308422/2023-6, 308848/2025-0)es_ES
dc.language.isoenges_ES
dc.publisherAmerican Chemical Societyes_ES
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs 3.0 Licensees_ES
dc.rightsAtribución 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectnanoparticleses_ES
dc.subjectdigital imagees_ES
dc.subjectnickel es_ES
dc.titleNitrogen-Doped Carbon Quantum Dot Nanoparticle Fluorescent Probes for Quantification of Ni(II) in Environmental Water Samples Collected using an Unmanned Aerial Vehiclees_ES
dc.typejournal articlees_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doi10.1021/acsanm.5c03254
dc.type.hasVersionVoRes_ES


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