Dergiler / Journal of Scientific Reports-B / 2026 / Issue: 016

Jeolojik Karakterizasyon ve Maden Arama Alanında Nanoteknolojiye Dayalı Sensörler: Yeni Nesil Yaklaşımlar

Nanotechnology-based sensors in geological characterization and mineral exploration: Next-generation approaches

Cumhur Eren Işık(Kütahya Dumlupınar Üniversitesi)0000-0002-1129-2497
İrem Türk(KÜTAHYA DUMLUPINAR ÜNİVERSİTESİ)0009-0004-2630-9855
Sayfa
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Yayın Tarihi
2026-08-31
DOI
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Yapay Zeka Hızlı Bakış & Çıkarımlar

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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Özetle, nanoteknoloji destekli sensörlerin, geleneksel analiz tekniklerini tamamlayan gelişmiş analiz araçları sağladığı ve disiplinlerarası teknolojilerdeki ilerlemelerle birleştirildiğinde, maden arama alanında daha verimli ve çevre dostu çözümler sunabileceği ortaya konmuştur.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Küresel ölçekte kritik minerallere olan talebin hızlı artışı, jeolojik karakterizasyon ve maden arama tekniklerinin hız, doğruluk ve sürdürülebilirlik açısından geliştirilmiş verimli analitik teknolojilerin önemini artırmıştır.
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Temel Bulgular & Veri:Geleneksel jeolojik, jeokimyasal ve jeofiziksel tekniklerin yüksek doğruluğuna rağmen, bu yöntemlerin etkinliği yavaş analiz süreleri, yüksek maliyetler ve laboratuvara bağımlı olmaları nedeniyle sınırlıdır.
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Sonuç & Katkı:Özetle, nanoteknoloji destekli sensörlerin, geleneksel analiz tekniklerini tamamlayan gelişmiş analiz araçları sağladığı ve disiplinlerarası teknolojilerdeki ilerlemelerle birleştirildiğinde, maden arama alanında daha verimli ve çevre dostu çözümler sunabileceği ortaya konmuştur.
🔬Tür:Laboratuvar & Saha Deneyi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Nanotechnology · nanosensors · geological characterization

Özet

Küresel ölçekte kritik minerallere olan talebin hızlı artışı, jeolojik karakterizasyon ve maden arama tekniklerinin hız, doğruluk ve sürdürülebilirlik açısından geliştirilmiş verimli analitik teknolojilerin önemini artırmıştır. Geleneksel jeolojik, jeokimyasal ve jeofiziksel tekniklerin yüksek doğruluğuna rağmen, bu yöntemlerin etkinliği yavaş analiz süreleri, yüksek maliyetler ve laboratuvara bağımlı olmaları nedeniyle sınırlıdır. Bu derlemede, jeolojik karakterizasyon ve maden arama alanlarında nanoteknolojiye dayalı sensörler konusunda güncel gelişmeler kapsamlı bir şekilde analiz edilmektedir. İlk olarak, nanoteknolojiye dayalı sensörlerin çalışma prensibi ve grafen, karbon nanotüpler, MXene, kuantum noktaları ve metal/metal oksit nanopartiküller gibi belirli nanomalzemelerin nanosensörlerin etkinliğini artırmadaki rolü ele alınmaktadır. Daha sonra, jeolojik karakterizasyon ve maden arama çalışmalarında elektrokimyasal, optik, yüzey destekli Raman saçılımı (SERS) ve alan etkili transistör (FET) tabanlı sensörlerin kullanımı ele alınmıştır. Ayrıca, yapay zeka, makine öğrenimi, Nesnelerin İnterneti (IoT), uzaktan algılama, hiperspektral görüntüleme ve coğrafi bilgi sistemleri (GIS) ile birlikte nanosensörlerin kullanımının rolü vurgulanmıştır. Ayrıca, seçicilik, matris paraziti, uzun vadeli kararlılık, standardizasyon ve ticari ölçeklendirme gibi sensörlerin pratik uygulamasına ilişkin mevcut sorunlar gözden geçirildi; hibrit nanokompozitler, mikroakışkan cihazlar, akıllı sensör sistemleri ve yapay zeka teknolojisiyle desteklenen karar verme sistemlerinin geliştirilmesine yönelik gelecekteki yönelimler belirlendi. Özetle, nanoteknoloji destekli sensörlerin, geleneksel analiz tekniklerini tamamlayan gelişmiş analiz araçları sağladığı ve disiplinlerarası teknolojilerdeki ilerlemelerle birleştirildiğinde, maden arama alanında daha verimli ve çevre dostu çözümler sunabileceği ortaya konmuştur.

Abstract

The fast growth of the demand of critical minerals on a global scale has increased the importance of development of efficient analytical technologies with enhanced speed, accuracy, and sustainability of the techniques for geological characterization and mineral exploration. Despite high accuracy of conventional geological, geochemical, and geophysical techniques, their effectiveness is limited by slow analysis, high expenses, and lab-dependent nature of the methods. In this review, current achievements in nanosensors, for geological characterization and mineral exploration are analyzed comprehensively. First, the principle of operation of nanosensors, and the role of specific nanomaterials, including graphene, carbon nanotubes, MXene, quantum dots, and metal/metal oxide nanoparticles, in enhancing the effectiveness of nanosensors are discussed. Later, the use of electrochemical, optical, surface enhanced Raman scattering (SERS) and field-effect transistor (FET)-based sensors in geological characterization and mineral exploration was discussed. In addition, the role of using nanosensors with artificial intelligence, machine learning, Internet of Things (IoT), remote sensing, hyperspectral imaging, and geographic information systems (GIS) was highlighted. Furthermore, current problems associated with practical implementation of sensors like selectivity, matrix interference, long-term stability, standardization, and commercial scale-up were reviewed; future directions for development of hybrid nanocomposites, microfluidic devices, intelligent sensor systems, and decision-making systems aided by artificial intelligence technology were defined. In summary, it was found out that nanotechnology-enabled sensors provide advanced analysis tools which complement conventional analysis techniques and which, combined with advances in interdisciplinary technologies, could provide more efficient and environmentally friendly solutions in mineral exploration.

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Bu Makaleye Atıf Yap

Işık, C. E., Türk, İ. (2026). Jeolojik Karakterizasyon ve Maden Arama Alanında Nanoteknolojiye Dayalı Sensörler: Yeni Nesil Yaklaşımlar. Journal of Scientific Reports-B, Issue: 016. https://ajindex.com/articles/1619074

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Kaynakça (204)

  1. A. Hool, C. Helbig, and G. Wierink, “Challenges and opportunities of the European Critical Raw Materials Act,” Miner. Econ. 2023 373, vol. 37, no. 3, pp. 661–668, Sep. 2023, doi: 10.1007/S13563-023-00394-Y.
  2. G. W. Lederer et al., “Annual review 2023: Critical minerals,” Min. Eng., vol. 76, no. 5, pp. 29–42, 2024.
  3. M. Reich and A. C. Simon, “Critical Minerals,” Annu. Rev. Earth Planet. Sci., vol. 53, no. 1, pp. 141–168, May 2025, doi: 10.1146/ANNUREV-EARTH-040523-023316/CITE/REFWORKS.
  4. F. Yang, R. Zuo, and O. P. Kreuzer, “Artificial intelligence for mineral exploration: A review and perspectives on future directions from data science,” Earth-Science Rev., vol. 258, p. 104941, Nov. 2024, doi: 10.1016/J.EARSCIREV.2024.104941.
  5. C. A. Moreira, L. P. Innocenti Helene, C. A. Moreira, and L. P. Innocenti Helene, “Identification for a Favorable Area of Groundwater Exploitation Based on Structural and Geoelectrical Data in Fractured Aquifer in Southern Brazil,” Geofísica Int., vol. 61, no. 4, pp. 287–300, 2022, doi: 10.22201/IGEOF.00L67L69P.2022.6L.4.2045.
  6. H. R. Rollinson, S. Killops, V. Killops, and P. Fletcher, Using Geochemical Data: Evaluation, Presentation, Interpretation. 2013.
  7. O. Mejías et al., “Fate, distribution, and transport dynamics of indium in a polymetallic mine waste environment: An integrated mineralogical characterisation and geochemical modelling study,” Sci. Total Environ., vol. 998, p. 180268, Oct. 2025, doi: 10.1016/J.SCITOTENV.2025.180268.
  8. B. Sen, A. Şavk, and F. Sen, “Highly efficient monodisperse Pt nanoparticles confined in the carbon black hybrid material for hydrogen liberation,” J. Colloid Interface Sci., vol. 520, pp. 112–118, Jun. 2018, doi: 10.1016/J.JCIS.2018.03.004.
  9. Y. Yildiz et al., “Highly Monodisperse Pt/Rh Nanoparticles Confined in the Graphene Oxide for Highly Efficient and Reusable Sorbents for Methylene Blue Removal from Aqueous Solutions,” ChemistrySelect, vol. 2, no. 2, pp. 697–701, Jan. 2017, doi: 10.1002/SLCT.201601608;REQUESTEDJOURNAL:JOURNAL:23656549;PAGEGROUP:STRING:PUBLICATION.
  10. B. Sen, S. Kuzu, E. Demir, S. Akocak, and F. Sen, “Polymer-graphene hybride decorated Pt nanoparticles as highly efficient and reusable catalyst for the dehydrogenation of dimethylamine–borane at room temperature,” Int. J. Hydrogen Energy, vol. 42, no. 36, pp. 23284–23291, Sep. 2017, doi: 10.1016/J.IJHYDENE.2017.05.112.
  11. E. Erken, Y. Yildiz, B. Kilbaş, and F. Şen, “Synthesis and Characterization of Nearly Monodisperse Pt Nanoparticles for C1 to C3 Alcohol Oxidation and Dehydrogenation of Dimethylamine-borane (DMAB),” J. Nanosci. Nanotechnol., vol. 16, no. 6, pp. 5944–5950, Jun. 2016, doi: 10.1166/JNN.2016.11683.
  12. F. Şen and G. Gökaǧaç, “Improving Catalytic Efficiency in the Methanol Oxidation Reaction by Inserting Ru in Face-Centered Cubic Pt Nanoparticles Prepared by a New Surfactant, tert-Octanethiol,” Energy and Fuels, vol. 22, no. 3, pp. 1858–1864, May 2008, doi: 10.1021/EF700575T.
  13. A. Hojjati-Najafabadi et al., “Bacillus thuringiensis Based Ruthenium/Nickel Co-Doped Zinc as a Green Nanocatalyst: Enhanced Photocatalytic Activity, Mechanism, and Efficient H2 Production from Sodium Borohydride Methanolysis,” Ind. Eng. Chem. Res., vol. 62, no. 11, pp. 4655–4664, Mar. 2023, doi: 10.1021/ACS.IECR.2C03833.
  14. E. Erken et al., “New Pt(0) Nanoparticles as Highly Active and Reusable Catalysts in the C1–C3 Alcohol Oxidation and the Room Temperature Dehydrocoupling of Dimethylamine-Borane (DMAB),” J. Clust. Sci. 2015 271, vol. 27, no. 1, pp. 9–23, Jun. 2015, doi: 10.1007/S10876-015-0892-8.
  15. B. Sen, S. Kuzu, E. Demir, E. Yıldırır, and F. Sen, “Highly efficient catalytic dehydrogenation of dimethyl ammonia borane via monodisperse palladium–nickel alloy nanoparticles assembled on PEDOT,” Int. J. Hydrogen Energy, vol. 42, no. 36, pp. 23307–23314, Sep. 2017, doi: 10.1016/J.IJHYDENE.2017.05.115.
  16. B. Şen, A. Aygün, T. O. Okyay, A. Şavk, R. Kartop, and F. Şen, “Monodisperse palladium nanoparticles assembled on graphene oxide with the high catalytic activity and reusability in the dehydrogenation of dimethylamine-borane,” Int. J. Hydrogen Energy, vol. 43, no. 44, pp. 20176–20182, Nov. 2018, doi: 10.1016/J.IJHYDENE.2018.03.175.
  17. S. Günbatar, A. Aygun, Y. Karataş, M. Gülcan, and F. Şen, “Carbon-nanotube-based rhodium nanoparticles as highly-active catalyst for hydrolytic dehydrogenation of dimethylamineborane at room temperature,” J. Colloid Interface Sci., vol. 530, pp. 321–327, Nov. 2018, doi: 10.1016/J.JCIS.2018.06.100.
  18. K. Nesrin et al., “Biogenic silver nanoparticles synthesized from Rhododendron ponticum and their antibacterial, antibiofilm and cytotoxic activities,” J. Pharm. Biomed. Anal., vol. 179, p. 112993, Feb. 2020, doi: 10.1016/J.JPBA.2019.112993.
  19. H. Goksu, Y. Yildiz, B. Çelik, M. Yazici, B. Kilbas, and F. Sen, “Eco-friendly hydrogenation of aromatic aldehyde compounds by tandem dehydrogenation of dimethylamine-borane in the presence of a reduced graphene oxide furnished platinum nanocatalyst,” Catal. Sci. Technol., vol. 6, no. 7, pp. 2318–2324, Apr. 2016, doi: 10.1039/C5CY01462J.
  20. B. Şahin, E. Demir, A. Aygün, H. Gündüz, and F. Şen, “Investigation of the effect of pomegranate extract and monodisperse silver nanoparticle combination on MCF-7 cell line,” J. Biotechnol., vol. 260, pp. 79–83, Oct. 2017, doi: 10.1016/J.JBIOTEC.2017.09.012.
  21. S. Ertan, F. Şen, S. Şen, and G. Gökağaç, “Platinum nanocatalysts prepared with different surfactants for C1-C3 alcohol oxidations and their surface morphologies by AFM,” J. Nanoparticle Res., vol. 14, no. 6, pp. 1–12, Jun. 2012, doi: 10.1007/S11051-012-0922-5/FIGURES/8.
  22. N. Korkmaz, Y. Ceylan, P. Taslimi, A. Karadağ, A. S. Bülbül, and F. Şen, “Biogenic nano silver: Synthesis, characterization, antibacterial, antibiofilms, and enzymatic activity,” Adv. Powder Technol., vol. 31, no. 7, pp. 2942–2950, Jul. 2020, doi: 10.1016/J.APT.2020.05.020.
  23. N. Lolak, E. Kuyuldar, H. Burhan, H. Goksu, S. Akocak, and F. Sen, “Composites of Palladium-Nickel Alloy Nanoparticles and Graphene Oxide for the Knoevenagel Condensation of Aldehydes with Malononitrile,” ACS Omega, vol. 4, no. 4, pp. 6848–6853, Apr. 2019, doi: 10.1021/ACSOMEGA.9B00485/SUPPL_FILE/AO9B00485_SI_001.PDF.
  24. B. Sen, B. Demirkan, A. Şavk, S. Karahan Gülbay, and F. Sen, “Trimetallic PdRuNi nanocomposites decorated on graphene oxide: A superior catalyst for the hydrogen evolution reaction,” Int. J. Hydrogen Energy, vol. 43, no. 38, pp. 17984–17992, Sep. 2018, doi: 10.1016/J.IJHYDENE.2018.07.122.
  25. H. Göksu, Y. Yıldız, B. Çelik, M. Yazıcı, B. Kılbaş, and F. Şen, “Highly Efficient and Monodisperse Graphene Oxide Furnished Ru/Pd Nanoparticles for the Dehalogenation of Aryl Halides via Ammonia Borane,” ChemistrySelect, vol. 1, no. 5, pp. 953–958, Apr. 2016, doi: 10.1002/SLCT.201600207.
  26. F. Şen, G. Gökağaç, and S. Şen, “High performance Pt nanoparticles prepared by new surfactants for C 1 to C3 alcohol oxidation reactions,” J. Nanoparticle Res., vol. 15, no. 10, pp. 1–9, Oct. 2013, doi: 10.1007/S11051-013-1979-5/FIGURES/6.
  27. Y. Yildiz, E. Erken, H. Pamuk, H. Sert, and F. Şen, “Monodisperse Pt Nanoparticles Assembled on Reduced Graphene Oxide: Highly Efficient and Reusable Catalyst for Methanol Oxidation and Dehydrocoupling of Dimethylamine-Borane (DMAB),” J. Nanosci. Nanotechnol., vol. 16, no. 6, pp. 5951–5958, Jun. 2016, doi: 10.1166/JNN.2016.11710.
  28. Y. Wu et al., “Hydrogen generation from methanolysis of sodium borohydride using waste coffee oil modified zinc oxide nanoparticles and their photocatalytic activities,” Int. J. Hydrogen Energy, vol. 48, no. 17, pp. 6613–6623, Feb. 2023, doi: 10.1016/J.IJHYDENE.2022.04.177.
  29. B. Şen, A. Aygün, A. Şavk, S. Akocak, and F. Şen, “Bimetallic palladium–iridium alloy nanoparticles as highly efficient and stable catalyst for the hydrogen evolution reaction,” Int. J. Hydrogen Energy, vol. 43, no. 44, pp. 20183–20191, Nov. 2018, doi: 10.1016/J.IJHYDENE.2018.07.081.
  30. B. Sen, S. Kuzu, E. Demir, T. Onal Okyay, and F. Sen, “Hydrogen liberation from the dehydrocoupling of dimethylamine–borane at room temperature by using novel and highly monodispersed RuPtNi nanocatalysts decorated with graphene oxide,” Int. J. Hydrogen Energy, vol. 42, no. 36, pp. 23299–23306, Sep. 2017, doi: 10.1016/J.IJHYDENE.2017.04.213.
  31. Z. Ozturk, F. Sen, S. Sen, and G. Gokagac, “The preparation and characterization of nano-sized Pt-Pd/C catalysts and comparison of their superior catalytic activities for methanol and ethanol oxidation,” J. Mater. Sci., vol. 47, no. 23, pp. 8134–8144, Jul. 2012, doi: 10.1007/S10853-012-6709-3/FIGURES/12.
  32. H. Göksu, B. Çelik, Y. Yıldız, F. Şen, and B. Kılbaş, “Superior Monodisperse CNT-Supported CoPd (CoPd@CNT) Nanoparticles for Selective Reduction of Nitro Compounds to Primary Amines with NaBH4 in Aqueous Medium,” ChemistrySelect, vol. 1, no. 10, pp. 2366–2372, Jul. 2016, doi: 10.1002/SLCT.201600509.
  33. F. Şen, S. Şen, and G. Gökaǧaç, “Efficiency enhancement of methanol/ethanol oxidation reactions on Pt nanoparticles prepared using a new surfactant, 1,1-dimethyl heptanethiol,” Phys. Chem. Chem. Phys., vol. 13, no. 4, pp. 1676–1684, Jan. 2011, doi: 10.1039/C0CP01212B.
  34. M. A. Darwish, W. Abd-Elaziem, A. E. De, and A. A. Zayed, “Advancements in nanomaterials for nanosensors: a comprehensive review,” 2024, doi: 10.1039/d4na00214h.
  35. M. Q. Khan, J. Khan, M. A. H. Alvi, H. Nawaz, M. Fahad, and M. Umar, “Nanomaterial-based sensors for microbe detection: a review,” Discov. Nano 2024 191, vol. 19, no. 1, pp. 120-, Jul. 2024, doi: 10.1186/S11671-024-04065-X.
  36. Y. Dong, C. Guo, J. Wang, C. Ye, and Q. Min, “Recent Advances in DNA Nanotechnology-Based Sensing Platforms for Rapid Virus Detection,” ChemBioChem, vol. 25, no. 17, p. e202400230, Sep. 2024, doi: 10.1002/CBIC.202400230.
  37. T. Cong Dinh et al., “Nanomaterial-enhanced electrochemical strategies for the detection of motor function–modulating substances,” Mater. Res. Express, vol. 13, no. 9, p. 092002, May 2026, doi: 10.1088/2053-1591/AE67E2.
  38. H. Shirmard, E. Farahbakhsh, R. D. Müller, and R. Chandra, “A review of machine learning in processing remote sensing data for mineral exploration,” Remote Sens. Environ., vol. 268, Jan. 2022, doi: 10.1016/j.rse.2021.112750.
  39. M. Holzinger, A. Le Goff, and S. Cosnier, “Nanomaterials for biosensing applications: A review,” Front. Chem., vol. 2, no. AUG, p. 108707, Aug. 2014, doi: 10.3389/FCHEM.2014.00063/FULL.
  40. D. Chimene, D. L. Alge, and A. K. Gaharwar, “Two-Dimensional Nanomaterials for Biomedical Applications: Emerging Trends and Future Prospects,” Adv. Mater., vol. 27, no. 45, pp. 7261–7284, Dec. 2015, doi: 10.1002/ADMA.201502422;REQUESTEDJOURNAL:JOURNAL:15214095;WGROUP:STRING:PUBLICATION.
  41. R. Abdel-Karim, “Nanotechnology-Enabled Biosensors: A Review of Fundamentals, Materials, Applications, Challenges, and Future Scope,” Biomed. Mater. Devices 2024 22, vol. 2, no. 2, pp. 759–777, Jan. 2024, doi: 10.1007/S44174-023-00147-Z.
  42. S. He et al., “A review on graphene-based sensors for tactile applications,” Sensors Actuators A Phys., vol. 372, pp. 1–49, Jul. 2024, doi: 10.1016/J.SNA.2024.115363.
  43. S. Sharma and T. Mondal, “Recent Advances in Graphene-Polymer Nanocomposite-Based Flexible Sensors and Triboelectric Nanogenerators,” Small, vol. 21, no. 27, p. 2501722, Jul. 2025, doi: 10.1002/SMLL.202501722;WGROUP:STRING:PUBLICATION.
  44. M. Mozafari and M. Soroush, “Surface functionalization of MXenes,” Mater. Adv., vol. 2, no. 22, pp. 7277–7307, Nov. 2021, doi: 10.1039/D1MA00625H.
  45. S. Jung, U. Zafar, L. S. K. Achary, and C. M. Koo, “Ligand chemistry for surface functionalization in MXenes: A review,” EcoMat, vol. 5, no. 10, p. e12395, Oct. 2023, doi: 10.1002/EOM2.12395;JOURNAL:JOURNAL:25673173;ISSUE:ISSUE:DOI.
  46. C. I. L. Justino, T. A. P. Rocha-Santos, S. Cardoso, A. C. Duarte, and S. Cardosa, “Strategies for enhancing the analytical performance of nanomaterial-based sensors,” TrAC Trends Anal. Chem., vol. 47, pp. 27–36, Jun. 2013, doi: 10.1016/J.TRAC.2013.02.004.
  47. J. Claudinon et al., “A Label-Free Optical Detection of Pathogens in Isopropanol as a First Step towards Real-Time Infection Prevention,” Biosens. 2021, Vol. 11, Page 2, vol. 11, no. 1, p. 2, Dec. 2020, doi: 10.3390/BIOS11010002.
  48. J. Cheong et al., “Engineered nanoparticles for clinical assays,” Nat. Rev. Bioeng. 2024 210, vol. 2, no. 10, pp. 887–905, Jul. 2024, doi: 10.1038/s44222-024-00208-y.
  49. X. D. Wang, O. S. Wolfbeis, and R. J. Meier, “Luminescent probes and sensors for temperature,” Chem. Soc. Rev., vol. 42, no. 19, pp. 7834–7869, Sep. 2013, doi: 10.1039/C3CS60102A.
  50. R. A. Viscarra Rossel, D. J. J. Walvoort, A. B. McBratney, L. J. Janik, and J. O. Skjemstad, “Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties,” Geoderma, vol. 131, no. 1–2, pp. 59–75, Mar. 2006, doi: 10.1016/J.GEODERMA.2005.03.007.
  51. K. A. Jannath, “Fundamentals of electrochemical sensors, nanomaterials, and progressive applications,” Discov. Electrochem. 2026 31, vol. 3, no. 1, pp. 41-, May 2026, doi: 10.1007/S44373-026-00131-4.
  52. P. Mehrotra, “Biosensors and their applications – A review,” J. Oral Biol. Craniofacial Res., vol. 6, no. 2, pp. 153–159, May 2016, doi: 10.1016/J.JOBCR.2015.12.002.
  53. T. Lim, H. Zhang, and S. Lee, “Gold and silver nanocomposite-based biostable and biocompatible electronic textile for wearable electromyographic biosensors,” APL Mater., vol. 9, no. 9, p. 91113, Sep. 2021, doi: 10.1063/5.0058617/122921.
  54. C. Dincer et al., “Disposable Sensors in Diagnostics, Food, and Environmental Monitoring,” Adv. Mater., vol. 31, no. 30, p. 1806739, Jul. 2019, doi: 10.1002/ADMA.201806739;REQUESTEDJOURNAL:JOURNAL:15214095;WGROUP:STRING:PUBLICATION.
  55. H. Zhang et al., “Recent advances in designable nanomaterial-based electrochemical sensors for environmental heavy-metal detection,” Nanoscale, vol. 17, no. 5, pp. 2386–2407, Jan. 2025, doi: 10.1039/D4NR04108A.
  56. C. I. L. Justino, A. R. Gomes, A. C. Freitas, A. C. Duarte, and T. A. P. Rocha-Santos, “Graphene based sensors and biosensors,” TrAC Trends Anal. Chem., vol. 91, pp. 53–66, Jun. 2017, doi: 10.1016/J.TRAC.2017.04.003.
  57. Harshita, H. F. Wu, and S. K. Kailasa, “Recent advances in nanomaterials-based optical sensors for detection of various biomarkers (inorganic species, organic and biomolecules),” Luminescence, vol. 38, no. 7, pp. 954–998, Jul. 2023, doi: 10.1002/BIO.4353.
  58. A. Lesiak, K. Drzozga, J. Cabaj, M. Bański, K. Malecha, and A. Podhorodecki, “Optical Sensors Based on II-VI Quantum Dots,” Nanomater. 2019, Vol. 9, Page 192, vol. 9, no. 2, p. 192, Feb. 2019, doi: 10.3390/NANO9020192.
  59. X. Wang et al., “Development of QDs-based nanosensors for heavy metal detection: A review on transducer principles and in-situ detection,” Talanta, vol. 239, p. 122903, Mar. 2022, doi: 10.1016/J.TALANTA.2021.122903.
  60. B. Sharma, R. R. Frontiera, A. I. Henry, E. Ringe, and R. P. Van Duyne, “SERS: Materials, applications, and the future,” Mater. Today, vol. 15, no. 1–2, pp. 16–25, Jan. 2012, doi: 10.1016/S1369-7021(12)70017-2.
  61. W. Hua et al., “Resistance of Superhydrophobic Surface-Functionalized TiO2 Nanotubes to Corrosion and Intense Cavitation,” Nanomater. 2018, Vol. 8, Page 783, vol. 8, no. 10, p. 783, Oct. 2018, doi: 10.3390/NANO8100783.
  62. S. Y. Ding et al., “Nanostructure-based plasmon-enhanced Raman spectroscopy for surface analysis of materials,” Nat. Rev. Mater. 2016 16, vol. 1, no. 6, pp. 16021-, Apr. 2016, doi: 10.1038/natrevmats.2016.21.
  63. P. Kumar et al., “Metal oxide nanomaterials based electrochemical and optical biosensors for biomedical applications: Recent advances and future prospectives,” Environ. Res., vol. 247, p. 118002, Apr. 2024, doi: 10.1016/J.ENVRES.2023.118002.
  64. M. Kaisti, “Detection principles of biological and chemical FET sensors,” Biosens. Bioelectron., vol. 98, pp. 437–448, Dec. 2017, doi: 10.1016/J.BIOS.2017.07.010.
  65. G. Seo et al., “Rapid Detection of COVID-19 Causative Virus (SARS-CoV-2) in Human Nasopharyngeal Swab Specimens Using Field-Effect Transistor-Based Biosensor,” ACS Nano, vol. 14, no. 4, pp. 5135–5142, Apr. 2020, doi: 10.1021/ACSNANO.0C02823.
  66. Y. Ohno, K. Maehashi, and K. Matsumoto, “Label-Free Biosensors Based on Aptamer-Modified Graphene Field-Effect Transistors,” J. Am. Chem. Soc., vol. 132, no. 51, pp. 18012–18013, Dec. 2010, doi: 10.1021/JA108127R.
  67. J. B. Kaushal, P. Raut, and S. Kumar, “Organic Electronics in Biosensing: A Promising Frontier for Medical and Environmental Applications,” Biosensors, vol. 13, no. 11, Oct. 2023, doi: 10.3390/bios13110976.
  68. S. K. Vashist and P. Vashist, “Recent Advances in Quartz Crystal Microbalance-Based Sensors,” J. Sensors, vol. 2011, no. 1, p. 571405, Jan. 2011, doi: 10.1155/2011/571405.
  69. L. Wang et al., “The research Progress of nanomaterial-enhanced quartz crystal microbalance sensing technology: A review,” Microchem. J., vol. 224, p. 117506, May 2026, doi: 10.1016/J.MICROC.2026.117506.
  70. T. A. Kuchmenko and L. B. Lvova, “A Perspective on Recent Advances in Piezoelectric Chemical Sensors for Environmental Monitoring and Foodstuffs Analysis,” Chemosens. 2019, Vol. 7, Page 39, vol. 7, no. 3, p. 39, Aug. 2019, doi: 10.3390/CHEMOSENSORS7030039.
  71. R. K. Yohan, M. Jagannathan, and G. Sivalingam, “The role of emerging photoactive nanostructures in electrochemical sensor construction: Synthesis, properties, challenges, and perspectives,” J. Ind. Eng. Chem., vol. 145, pp. 234–254, May 2025, doi: 10.1016/J.JIEC.2024.12.076.
  72. F. Beck, M. Loessl, and A. J. Baeumner, “Signaling strategies of silver nanoparticles in optical and electrochemical biosensors: considering their potential for the point-of-care,” Microchim. Acta 2023 1903, vol. 190, no. 3, pp. 91-, Feb. 2023, doi: 10.1007/S00604-023-05666-6.
  73. E. Voitechovič and R. Pauliukaite, “Electrochemical multisensor systems and arrays in the era of artificial intelligence,” Curr. Opin. Electrochem., vol. 42, p. 101411, Dec. 2023, doi: 10.1016/J.COELEC.2023.101411.
  74. A. Baruah et al., “Biomedical applications of graphene-based nanomaterials: recent progress, challenges, and prospects in highly sensitive biosensors,” Discov. Nano 2024 191, vol. 19, no. 1, pp. 103-, Jun. 2024, doi: 10.1186/S11671-024-04032-6.
  75. K. S. Novoselov, V. I. Fal’Ko, L. Colombo, P. R. Gellert, M. G. Schwab, and K. Kim, “A roadmap for graphene,” Nat. 2012 4907419, vol. 490, no. 7419, pp. 192–200, Oct. 2012, doi: 10.1038/nature11458.
  76. M. Pumera, “Graphene-based nanomaterials for energy storage,” Energy Environ. Sci., vol. 4, no. 3, pp. 668–674, Mar. 2011, doi: 10.1039/C0EE00295J.
  77. C. B. Jacobs, M. J. Peairs, and B. J. Venton, “Review: Carbon nanotube based electrochemical sensors for biomolecules,” Anal. Chim. Acta, vol. 662, no. 2, pp. 105–127, Mar. 2010, doi: 10.1016/J.ACA.2010.01.009.
  78. M. Trojanowicz, “Analytical applications of carbon nanotubes: a review,” TrAC Trends Anal. Chem., vol. 25, no. 5, pp. 480–489, May 2006, doi: 10.1016/J.TRAC.2005.11.008.
  79. S. Hasanova, A. Boyraz, M. Mammadzada, and E. Zor, “MXene-based sensors on pharmaceutical and environmental assays,” Essent. Chem, vol. 1, no. 1, pp. 1–25, Dec. 2024, doi: 10.1080/28378083.2024.2386526.
  80. B. Anasori, M. R. Lukatskaya, and Y. Gogotsi, “2D metal carbides and nitrides (MXenes) for energy storage,” Nat. Rev. Mater. 2017 22, vol. 2, no. 2, pp. 16098-, Jan. 2017, doi: 10.1038/natrevmats.2016.98.
  81. A. Ali et al., “Recent Advancements in MXene-Based Biosensors for Health and Environmental Applications—A Review,” Biosens. 2024, Vol. 14, Page 497, vol. 14, no. 10, p. 497, Oct. 2024, doi: 10.3390/BIOS14100497.
  82. M. S. Al Ja’farawy et al., “Graphene quantum dot nanocomposites: electroanalytical and optical sensor technology perspective,” J. Anal. Sci. Technol. 2023 141, vol. 14, no. 1, pp. 29-, Jul. 2023, doi: 10.1186/S40543-023-00393-2.
  83. Y. Cheng, B. Jiang, S. Chaemchuen, F. Verpoort, and Z. Kou, “Advances and challenges in designing MXene quantum dots for sensors,” Carbon Neutralization, vol. 2, no. 2, pp. 213–234, Mar. 2023, doi: 10.1002/CNL2.47.
  84. M. Li, T. Chen, J. J. Gooding, and J. Liu, “Review of Carbon and Graphene Quantum Dots for Sensing,” ACS Sensors, vol. 4, no. 7, pp. 1732–1748, Jul. 2019, doi: 10.1021/ACSSENSORS.9B00514.
  85. M. J. Molaei, “Principles, mechanisms, and application of carbon quantum dots in sensors: a review,” Anal. Methods, vol. 12, no. 10, pp. 1266–1287, Mar. 2020, doi: 10.1039/C9AY02696G.
  86. V. Naresh and N. Lee, “A Review on Biosensors and Recent Development of Nanostructured Materials-Enabled Biosensors,” Sensors (Basel)., vol. 21, no. 4, p. 1109, Feb. 2021, doi: 10.3390/S21041109.
  87. M. S. Chavali and M. P. Nikolova, “Metal oxide nanoparticles and their applications in nanotechnology,” SN Appl. Sci. 2019 16, vol. 1, no. 6, pp. 607-, May 2019, doi: 10.1007/S42452-019-0592-3.
  88. L. Y. Zhu, L. X. Ou, L. W. Mao, X. Y. Wu, Y. P. Liu, and H. L. Lu, “Advances in Noble Metal-Decorated Metal Oxide Nanomaterials for Chemiresistive Gas Sensors: Overview,” Nano-Micro Lett. 2023 151, vol. 15, no. 1, pp. 89-, Apr. 2023, doi: 10.1007/S40820-023-01047-Z.
  89. F. Wang, S. P. Yeap, C. Y. Cheok, C. K. Ang, and R. Saidur, “Progress and Insights on Graphene and MXene-based Emerging 2-Dimensional Conductive Nanomaterials for Fabrication of Flexible Gas Sensors,” ChemBioEng Rev., vol. 10, no. 6, pp. 907–923, Dec. 2023, doi: 10.1002/CBEN.202300010;REQUESTEDJOURNAL:JOURNAL:21969744;ISSUE:ISSUE:DOI.
  90. Y. Yao et al., “Progress towards efficient MXene sensors,” Commun. Mater. 2025 61, vol. 6, no. 1, pp. 210-, Sep. 2025, doi: 10.1038/s43246-025-00907-y.
  91. M. H. Fakhr, A. I. G. Zintzun, A. Michaelis, J. Opitz, and N. Beshchasna, “Application of MXene-based nanocomposites in electrochemical biosensors,” Appl. Surf. Sci. Adv., vol. 32, p. 100959, Mar. 2026, doi: 10.1016/J.APSADV.2026.100959.
  92. S. Askari et al., “Two-Dimensional Nanomaterial-Based Aptasensors: Graphene and MXenes as Emerging Biosensing Platforms,” ACS Appl. Nano Mater., vol. 8, no. 37, pp. 17819–17862, Sep. 2025, doi: 10.1021/ACSANM.5C03078.
  93. K. Mykhailivna Doroshenko and O. I. Shefchenko, “RETRACTED ARTICLE: Graphene-based MXene nanocomposites for highly sensitive and selective detection of diverse analytes,” Fullerenes, Nanotub. Carbon Nanostructures, vol. 34, no. 8, pp. i–xxx, 2026, doi: 10.1080/1536383X.2025.2553699.
  94. A. Thakur, V. C. Anadebe, A. Zarrouk, O. Dagdag, A. Kumar, and V. Khanna, “Nanobiosensors for Food Pathogen Detection: Trends and Limitations,” pp. 81–106, 2025, doi: 10.1007/978-981-95-0136-6_5.
  95. G. U. Sikakwe, “Mineral exploration employing drones, contemporary geological satellite remote sensing and geographical information system (GIS) procedures: A review,” Remote Sens. Appl. Soc. Environ., vol. 31, p. 100988, Aug. 2023, doi: 10.1016/J.RSASE.2023.100988.
  96. R. S. Harmon, “Laser-Induced Breakdown Spectroscopy in Mineral Exploration and Ore Processing,” Miner. 2024, Vol. 14, Page 731, vol. 14, no. 7, p. 731, Jul. 2024, doi: 10.3390/MIN14070731.
  97. V. Balaram and S. S. Sawant, “Indicator Minerals, Pathfinder Elements, and Portable Analytical Instruments in Mineral Exploration Studies,” Miner. 2022, Vol. 12, Page 394, vol. 12, no. 4, p. 394, Mar. 2022, doi: 10.3390/MIN12040394.
  98. B. Lemière and R. S. Harmon, “XRF and LIBS for Field Geology,” Portable Spectrosc. Spectrom., pp. 455–497, Apr. 2021, doi: 10.1002/9781119636489.CH42.
  99. S. O. Fakayode, C. Walgama, V. E. Fernand Narcisse, and C. Grant, “Electrochemical and Colorimetric Nanosensors for Detection of Heavy Metal Ions: A Review,” Sensors (Basel)., vol. 23, no. 22, Nov. 2023, doi: 10.3390/S23229080.
  100. Y. GadelHak, S. H. M. Hafez, H. F. M. Mohamed, E. E. Abdel-Hady, and R. Mahmoud, “Nanomaterials-modified disposable electrodes and portable electrochemical systems for heavy metals detection in wastewater streams: A review,” Microchem. J., vol. 193, p. 109043, Oct. 2023, doi: 10.1016/J.MICROC.2023.109043.
  101. K. H. Gebremedhin et al., “Nanomaterial-based optical colorimetric sensors for rapid monitoring of inorganic arsenic species: a review,” Discov. Nano 2024 191, vol. 19, no. 1, pp. 38-, Feb. 2024, doi: 10.1186/S11671-024-03981-2.
  102. S. Bilge, B. Dogan-Topal, M. M. Gürbüz, S. A. Ozkan, and A. Sınağ, “Recent trends in core/shell nanoparticles: their enzyme-based electrochemical biosensor applications,” Microchim. Acta 2024 1915, vol. 191, no. 5, pp. 240-, Apr. 2024, doi: 10.1007/S00604-024-06305-4.
  103. S. Santra, D. Datta, S. Biswas, and B. Das, “Role of Silica, Carbon, and ZnO Nanomaterials in the Fabrication of Electrochemical Sensors for the Detection of Water Contaminants and Food Dye,” Part. Part. Syst. Charact., vol. 41, no. 9, p. 2400020, Sep. 2024, doi: 10.1002/PPSC.202400020;SUBPAGE:STRING:FULL.
  104. Z. Otgonbayar and W. C. Oh, “Comprehensive and multi-functional MXene based sensors: An updated review,” FlatChem, vol. 40, p. 100524, Jul. 2023, doi: 10.1016/J.FLATC.2023.100524.
  105. Q. Wang et al., “MXene-based electrochemical (bio) sensors for sustainable applications: Roadmap for future advanced materials,” Nano Mater. Sci., vol. 5, no. 1, pp. 39–52, Mar. 2023, doi: 10.1016/J.NANOMS.2022.07.003.
  106. D. Çimen, N. Bereli, and A. Denizli, “Advanced Plasmonic Nanosensors for Monitoring of Environmental Pollutants,” Curr. Anal. Chem., vol. 19, no. 1, pp. 2–17, Jan. 2023, doi: 10.2174/1573411018666220618155324.
  107. Z. Wang, B. Yao, Y. Xiao, X. Tian, and Y. Wang, “Fluorescent Quantum Dots and Its Composites for Highly Sensitive Detection of Heavy Metal Ions and Pesticide Residues: A Review,” Chemosens. 2023, Vol. 11, Page 405, vol. 11, no. 7, p. 405, Jul. 2023, doi: 10.3390/CHEMOSENSORS11070405.
  108. N. Khansili, “Advances in material for colorimetric and fluorescent detection of arsenic,” Biosens. Bioelectron. X, vol. 15, p. 100410, Dec. 2023, doi: 10.1016/J.BIOSX.2023.100410.
  109. X. X. Han, R. S. Rodriguez, C. L. Haynes, Y. Ozaki, and B. Zhao, “Surface-enhanced Raman spectroscopy,” Nat. Rev. Methods Prim. 2022 11, vol. 1, no. 1, pp. 87-, Jan. 2022, doi: 10.1038/s43586-021-00083-6.
  110. W. Wang, P. Ma, and D. Song, “Applications of surface-enhanced Raman spectroscopy based on portable Raman spectrometers: A review of recent developments,” Luminescence, vol. 37, no. 11, pp. 1822–1835, Nov. 2022, doi: 10.1002/BIO.4383;PAGE:STRING:ARTICLE/CHAPTER.
  111. Y. J. Zhang et al., “Shell-isolated nanoparticle-enhanced Raman spectroscopy,” Nat. Rev. Methods Prim. 2023 31, vol. 3, no. 1, pp. 36-, May 2023, doi: 10.1038/s43586-023-00217-y.
  112. M. K. Filippidou and S. Chatzandroulis, “Microfluidic Devices for Heavy Metal Ions Detection: A Review,” Micromachines 2023, Vol. 14, Page 1520, vol. 14, no. 8, p. 1520, Jul. 2023, doi: 10.3390/MI14081520.
  113. S. S. Nadumane, R. Biswas, and N. Mazumder, “Integrated microfluidic platforms for heavy metal sensing: a comprehensive review,” Anal. Methods, vol. 16, no. 18, pp. 2810–2823, Apr. 2024, doi: 10.1039/D4AY00293H.
  114. F. Yao et al., “Review on the development of multi- and hyperspectral remote sensing technology for exploration of copper–gold deposits,” Ore Geol. Rev., vol. 162, p. 105732, Nov. 2023, doi: 10.1016/J.OREGEOREV.2023.105732.
  115. A. B. Pour et al., “Remote sensing for mineral exploration,” Geospatial Anal. Appl. to Miner. Explor. Remote Sensing, GIS, Geochemical, Geophys. Appl. to Miner. Resour., pp. 17–149, Jan. 2023, doi: 10.1016/B978-0-323-95608-6.00002-0.
  116. A. Barhoum, S. Hamimed, H. Slimi, A. Othmani, F. M. Abdel-Haleem, and M. Bechelany, “Modern designs of electrochemical sensor platforms for environmental analyses: Principles, nanofabrication opportunities, and challenges,” Trends Environ. Anal. Chem., vol. 38, p. e00199, Jun. 2023, doi: 10.1016/J.TEAC.2023.E00199.
  117. A. Sahragard, P. Varanusupakul, and M. Miró, “Nanomaterial decorated electrodes in flow-through electrochemical sensing of environmental pollutants: A critical review,” Trends Environ. Anal. Chem., vol. 39, p. e00208, Sep. 2023, doi: 10.1016/J.TEAC.2023.E00208.
  118. A. Dhaffouli, “Next-generation antifouling electrochemical sensors: From surface design to practical applications,” Microchem. J., vol. 220, p. 116637, Jan. 2026, doi: 10.1016/J.MICROC.2025.116637.
  119. C. W. Huang, C. Lin, M. K. Nguyen, A. Hussain, X. T. Bui, and H. H. Ngo, “A review of biosensor for environmental monitoring: principle, application, and corresponding achievement of sustainable development goals,” Bioengineered, vol. 14, no. 1, pp. 58–80, 2023, doi: 10.1080/21655979.2022.2095089.
  120. N. Kilinc-Ata, M. Alshami, and K. Munir, “How do strategic mineral resources affect clean energy transition? Cross-sectional autoregressive distributed lag (CS-ARDL) approach,” Miner. Econ. 2023 364, vol. 36, no. 4, pp. 643–654, Mar. 2023, doi: 10.1007/S13563-023-00373-3.
  121. P. Ghamisi et al., “Responsible Artificial Intelligence for Earth Observation: Achievable and realistic paths to serve the collective good,” IEEE Geosci. Remote Sens. Mag., vol. 13, no. 3, pp. 72–96, 2025, doi: 10.1109/MGRS.2025.3529726.
  122. M. S. Zhdanov et al., “Academic Editors: The Evolution of Machine Learning in Large-Scale Mineral Prospectivity Prediction: A Decade of Innovation (2016-2025),” 2016, doi: 10.3390/min15101042.
  123. J. N. Amoldago and E. D. Sunkari, “Application of Hydrogeochemistry in Mineral Exploration: A Systematic Review of Global Practices, Emerging Trends, and Future Directions,” Minerals, vol. 16, no. 5, p. 451, May 2026, doi: 10.3390/MIN16050451/S1.
  124. A. J. Goodman, B. F. Benner, and M. D. Montaño, “Out of the lab and into the environment: the evolution of single particle ICP-MS over the past decade,” Environ. Sci. Nano, vol. 12, no. 3, pp. 1789–1800, Mar. 2025, doi: 10.1039/D4EN00804A.
  125. J. A. Kidder, “TRACE AND ISOTOPIC GEOCHEMISTRY OF GROUNDWATERS IN MINERAL EXPLORATION”.
  126. M. Schindler, J. Xu, and M. F. Hochella, “Abiotic and biotic-controlled nanomaterial formation pathways within the Earth’s nanomaterial cycle,” Commun. Earth Environ. 2024 51, vol. 5, no. 1, pp. 646-, Nov. 2024, doi: 10.1038/s43247-024-01823-8.
  127. J. R. Lead and K. J. Wilkinson, “Aquatic Colloids and Nanoparticles: Current Knowledge and Future Trends,” Environ. Chem., vol. 3, no. 3, pp. 159–171, Jul. 2006, doi: 10.1071/EN06025.
  128. M. Alam, A. R. J. Downey, B. Cai, and M. Baalousha, “Elemental Composition of Magnetic Nanoparticles in Wildland–Urban Interface Fire Ashes Revealed by Single Particle-Inductively Coupled Plasma-Time-of-Flight-Mass Spectrometer,” Nanomaterials, vol. 15, no. 18, p. 1420, Sep. 2025, doi: 10.3390/NANO15181420/S1.
  129. J. E. Bourdeau, S. E. Zhang, G. T. Nwaila, and Y. Ghorbani, “Data generation for exploration geochemistry: Past, present and future,” Appl. Geochemistry, vol. 172, Oct. 2024, doi: 10.1016/J.APGEOCHEM.2024.106124.
  130. X. Huang et al., “Trends, risks and opportunities in environmental nanotechnology,” Nat. Rev. Earth Environ. 2024 58, vol. 5, no. 8, pp. 572–587, Jul. 2024, doi: 10.1038/s43017-024-00567-5.
  131. T. Li, X. Zhu, X. Hai, S. Bi, and X. Zhang, “Recent Progress in Sensor Arrays: From Construction Principles of Sensing Elements to Applications,” ACS Sensors, vol. 8, no. 3, pp. 994–1016, Mar. 2023, doi: 10.1021/ACSSENSORS.2C02596.
  132. H. Adam et al., “Integration of microfluidic channel on electrochemical-based nanobiosensors for monoplex and multiplex analyses: An overview,” J. Taiwan Inst. Chem. Eng., vol. 146, p. 104814, May 2023, doi: 10.1016/J.JTICE.2023.104814.
  133. P. Zhao and Y. Chen, “Digital Geosciences and Quantitative Mineral Exploration,” J. Earth Sci. 2021 322, vol. 32, no. 2, pp. 269–275, Apr. 2021, doi: 10.1007/S12583-021-1440-0.
  134. V. P. Aswathi, S. Meera, C. G. A. Maria, and M. Nidhin, “Green synthesis of nanoparticles from biodegradable waste extracts and their applications: a critical review,” Nanotechnol. Environ. Eng., vol. 8, no. 2, pp. 377–397, Jun. 2023, doi: 10.1007/s41204-022-00276-8.
  135. M. A. Hussain, S. Mishra, N. V. Bora, and L. V. Bora, “Green nanomaterials based nanosensors,” Compr. Anal. Chem., vol. 105, pp. 171–189, Jan. 2024, doi: 10.1016/BS.COAC.2023.07.001.
  136. A. García-Quintero and M. Palencia, “A critical analysis of environmental sustainability metrics applied to green synthesis of nanomaterials and the assessment of environmental risks associated with the nanotechnology,” Sci. Total Environ., vol. 793, p. 148524, Nov. 2021, doi: 10.1016/J.SCITOTENV.2021.148524.
  137. M. D. Arif, M. E. Hoque, M. Z. Rahman, and M. U. Shafoyat, “Emerging directions in green nanomaterials: Synthesis, physicochemical properties and applications,” Mater. Today Commun., vol. 40, p. 109335, Aug. 2024, doi: 10.1016/J.MTCOMM.2024.109335.
  138. V. Taranovic, S. J. Barnes, S. Beresford, M. Williams, C. MacRae, and L. E. Schoneveld, “Nova-Bollinger Ni-Cu Sulfide Ore Deposits, Fraser Zone, Western Australia: Petrogenesis of the Host Intrusions,” Econ. Geol., vol. 117, no. 2, pp. 455–484, Mar. 2022, doi: 10.5382/ECONGEO.4873.
  139. F. Zhang et al., “Distinct REY sources recorded in the Doushantuo phosphorite,” Ore Geol. Rev., vol. 157, p. 105470, Jun. 2023, doi: 10.1016/J.OREGEOREV.2023.105470.
  140. B. Lemière and Y. A. Uvarova, “New developments in field-portable geochemical techniques and on-site technologies and their place in mineral exploration,” Geochemistry Explor. Environ. Anal., vol. 20, no. 2, pp. 205–216, May 2020, doi: 10.1144/GEOCHEM2019-044;REQUESTEDJOURNAL:JOURNAL:GEEA;JOURNAL:JOURNAL:GEEA;ISSUE:ISSUE:DOI.
  141. T. Hu, Q. Lai, W. Fan, Y. Zhang, and Z. Liu, “Advances in Portable Heavy Metal Ion Sensors,” Sensors (Basel)., vol. 23, no. 8, Apr. 2023, doi: 10.3390/S23084125.
  142. C. Douvris, T. Vaughan, D. Bussan, G. Bartzas, and R. Thomas, “How ICP-OES changed the face of trace element analysis: Review of the global application landscape,” Sci. Total Environ., vol. 905, p. 167242, Dec. 2023, doi: 10.1016/J.SCITOTENV.2023.167242.
  143. L. Mathieu, “Quantifying Hydrothermal Alteration: A Review of Methods,” Geosci. 2018, Vol. 8, Page 245, vol. 8, no. 7, p. 245, Jul. 2018, doi: 10.3390/GEOSCIENCES8070245.
  144. W. M. Calvin and E. L. Pace, “Mapping alteration in geothermal drill core using a field portable spectroradiometer,” Geothermics, vol. 61, pp. 12–23, May 2016, doi: 10.1016/J.GEOTHERMICS.2016.01.005.
  145. M. L. Pereira, V. Zanon, I. Fernandes, L. Pappalardo, and F. Viveiros, “Hydrothermal alteration and physical and mechanical properties of rocks in a volcanic environment: A review,” Earth-Science Rev., vol. 252, May 2024, doi: 10.1016/j.earscirev.2024.104754.
  146. S. Hajaj, A. El Harti, A. B. Pour, A. Jellouli, Z. Adiri, and M. Hashim, “A review on hyperspectral imagery application for lithological mapping and mineral prospecting: Machine learning techniques and future prospects,” Remote Sens. Appl. Soc. Environ., vol. 35, p. 101218, Aug. 2024, doi: 10.1016/J.RSASE.2024.101218.
  147. H. Zhang, B. Li, M. Karimi, S. Saydam, and M. Hassan, “Recent Advancements in IoT Implementation for Environmental, Safety, and Production Monitoring in Underground Mines,” IEEE Internet Things J., vol. 10, no. 16, pp. 14507–14526, Aug. 2023, doi: 10.1109/JIOT.2023.3267828.
  148. C. Cacciuttolo, V. Guzmán, P. Catriñir, E. Atencio, S. Komarizadehasl, and J. A. Lozano-Galant, “Low-Cost Sensors Technologies for Monitoring Sustainability and Safety Issues in Mining Activities: Advances, Gaps, and Future Directions in the Digitalization for Smart Mining,” Sensors 2023, Vol. 23, Page 6846, vol. 23, no. 15, p. 6846, Aug. 2023, doi: 10.3390/S23156846.
  149. G. B. Davis, J. L. Rayner, and M. J. Donn, “Advancing ‘Autonomous’ sensing and prediction of the subsurface environment: a review and exploration of the challenges for soil and groundwater contamination,” Environ. Sci. Pollut. Res. 2023 308, vol. 30, no. 8, pp. 19520–19535, Jan. 2023, doi: 10.1007/S11356-022-25125-8.
  150. Y. Gu et al., “Chemical antifouling strategies in sensors for food analysis: A review,” Compr. Rev. Food Sci. Food Saf., vol. 22, no. 5, pp. 4074–4106, Sep. 2023, doi: 10.1111/1541-4337.13209;PAGE:STRING:ARTICLE/CHAPTER.
  151. N. Adil, R. Wang, and X. Wang, “Self-Calibrated Ion-Selective Electrodes,” Anal. Chem., vol. 95, no. 29, pp. 11149–11156, Jul. 2023, doi: 10.1021/ACS.ANALCHEM.3C02135.
  152. J. Wu, H. Liu, W. Chen, B. Ma, and H. Ju, “Device integration of electrochemical biosensors,” Nat. Rev. Bioeng. 2023 15, vol. 1, no. 5, pp. 346–360, Feb. 2023, doi: 10.1038/s44222-023-00032-w.
  153. H. Yang, X. Ji, S. Lee, and I. Moon, “Recent Advances and Future Perspectives of AI-Based Mineral Exploration: A Review of Machine Learning, Deep Learning, and Geologically Informed Approaches,” Miner. 2026, Vol. 16, Page 584, vol. 16, no. 6, p. 584, May 2026, doi: 10.3390/MIN16060584.
  154. D. Yang and C. Priest, “Industry relevant microfluidic platforms for mineral leaching experiments,” Front. Chem. Eng., vol. 6, p. 1445900, Sep. 2024, doi: 10.3389/FCENG.2024.1445900/TEXT.
  155. A. K. Goyal and A. Nigam, “Sensors for toxic metal ion detection in aquatic environment: current status and future perspectives,” Discov. Appl. Sci. 2025 712, vol. 7, no. 12, pp. 1405-, Nov. 2025, doi: 10.1007/S42452-025-07936-9.
  156. R. Bogue, “Nanomaterials for gas sensing: a review of recent research,” Sens. Rev., vol. 34, no. 1, pp. 1–8, Jan. 2014, doi: 10.1108/SR-03-2013-637.
  157. A. Wang and L. Fu, “Nano-Functional Materials for Sensor Applications,” Mol. 2024, Vol. 29, Page 5515, vol. 29, no. 23, p. 5515, Nov. 2024, doi: 10.3390/MOLECULES29235515.
  158. N. Singhal et al., “AI-Enabled Nano Biosensors for Estimating Heavy Metal Contamination in Crops,” Sens. Imaging 2025 261, vol. 26, no. 1, pp. 166-, Dec. 2025, doi: 10.1007/S11220-025-00679-2.
  159. R. He, L. Chen, P. Chu, P. Gao, and J. Wang, “Recent advances in nonenzymatic electrochemical biosensors for sports biomarkers: focusing on antibodies, aptamers and molecularly imprinted polymers,” Anal. Methods, vol. 16, no. 36, pp. 6079–6097, Sep. 2024, doi: 10.1039/D4AY01002G.
  160. W. Raza, K. Ahmad, and T. H. Oh, “Progress in Layered Double Hydroxide-Based Materials for Gas and Electrochemical Sensing Applications,” Chemosens. 2025, Vol. 13, Page 115, vol. 13, no. 3, p. 115, Mar. 2025, doi: 10.3390/CHEMOSENSORS13030115.
  161. H. Wang et al., “An integrated wearable microfluidic electrochemical/colorimetric intelligent sensing platform for comprehensive sweat analysis,” Biosens. Bioelectron., vol. 306, p. 118746, Aug. 2026, doi: 10.1016/J.BIOS.2026.118746.
  162. L. L. Lin et al., “Surface-Enhanced Raman Spectroscopy for Biomedical Applications: Recent Advances and Future Challenges,” ACS Appl. Mater. Interfaces, vol. 17, no. 11, pp. 16287–16379, Mar. 2025, doi: 10.1021/ACSAMI.4C17502.
  163. Y. Yue, C. Chen, Y. Liu, D. Kong, and D. Wei, “Multifunctional Integrated Biosensors Based on Two-Dimensional Field-Effect Transistors,” ACS Appl. Mater. Interfaces, vol. 16, no. 51, pp. 70160–70173, Dec. 2024, doi: 10.1021/ACSAMI.4C18412.
  164. D. Singh and R. Kamal, “Quantum dot-based sensors and nanotheranostics for early detection and targeted therapy for colorectal cancer.,” Nanomedicine J., vol. 13, no. 2, p. 256, Apr. 2026, doi: 10.22038/NMJ.2025.86235.2168.
  165. J. Zhang, M. H. Kim, S. Lee, and S. Park, “Integration of nanobiosensors into organ-on-chip systems for monitoring viral infections,” Nano Converg. 2024 111, vol. 11, no. 1, pp. 47-, Nov. 2024, doi: 10.1186/S40580-024-00455-0.
  166. L. Velasco, H. Zhou, D. Li, and C. Lee, “Technology Landscape Review of In-Sensor Photonic Intelligence: From Optical Sensors to Smart Devices,” AI Sensors 2025, Vol. 1, Page 5, vol. 1, no. 1, p. 5, Jul. 2025, doi: 10.3390/AISENS1010005.
  167. H. Wang et al., “Graphene oxide/multi-walled carbon nanotubes/gold nanoparticle hybridfunctionalized disposable screen-printed carbon electrode to determine Cd(II) and Pb(II) in soil,” Int. J. Agric. Biol. Eng., vol. 12, no. 3, pp. 194–200, 2019, doi: 10.25165/J.IJABE.20191203.4300.
  168. Q. Chen, Y. Yang, M. Ilnur, W. Liang, A. Shen, and J. Hu, “‘Mixing-and-measuring’ surface-enhanced Raman scattering (SERS) detection of Bacillus cereus for potentially aiding gold mine field exploration,” Talanta, vol. 204, pp. 44–49, Nov. 2019, doi: 10.1016/J.TALANTA.2019.05.068.
  169. N. Li, S. Han, S. Lin, X. Y. Sha, and W. Hasi, “Detection of Soluble Mercury in Cinnabar Using a CV-Ag NPs SERS Probe,” Anal. Sci., vol. 37, no. 10, pp. 1407–1412, 2021, doi: 10.2116/ANALSCI.21P047.
  170. N. Logan, J. Lou-Franco, C. Elliott, and C. Cao, “Catalytic gold nanostars for SERS-based detection of mercury ions (Hg2+) with inverse sensitivity,” Environ. Sci. Nano, vol. 8, no. 9, pp. 2718–2730, Sep. 2021, doi: 10.1039/D1EN00548K.
  171. G. Zhao, X. Wang, G. Liu, and N. Thi Dieu Thuy, “A disposable and flexible electrochemical sensor for the sensitive detection of heavy metals based on a one-step laser-induced surface modification: A new strategy for the batch fabrication of sensors,” Sensors Actuators B Chem., vol. 350, p. 130834, Jan. 2022, doi: 10.1016/J.SNB.2021.130834.
  172. H. Lv et al., “Portable anti-fouling electrochemical sensor for soil heavy metal ions detection based on the screen-printed carbon electrode modified with silica isoporous membrane,” J. Electroanal. Chem., vol. 930, p. 117141, Feb. 2023, doi: 10.1016/J.JELECHEM.2023.117141.
  173. M. Patel et al., “Ternary nanocomposite-based smart sensor: Reduced graphene oxide/polydopamine/alanine nanocomposite for simultaneous electrochemical detection of Cd2+, Pb2+, Fe2+, and Cu2+ ions,” Environ. Res., vol. 221, p. 115317, Mar. 2023, doi: 10.1016/J.ENVRES.2023.115317.
  174. M. G. Ellis, U. Pant, J. Lou-Franco, N. Logan, and C. Cao, “Directed Assemblyof Au Nanostar@Ag Satellite Nanostructuresfor SERS-Based Sensing of Hg2+ Ions,” ACS Appl. Nano Mater., vol. 6, no. 12, pp. 10431–10440, Jun. 2023, doi: 10.1021/ACSANM.3C01382.
  175. H. Xing, X. Zhang, S. Zhai, W. Mu, C. Li, and X. Han, “Screen-printed electrode containing bismuth/graphene oxide hybrid for simultaneous detection of cadmium and lead ions,” J. Electroanal. Chem., vol. 961, p. 118222, May 2024, doi: 10.1016/J.JELECHEM.2024.118222.
  176. G. Ananganó-Alvarado et al., “Beyond Traditional Methods: Machine Learning for Geochemical Baselines and Anomaly Detection,” Minerals, vol. 16, no. 7, p. 700, Jul. 2026, doi: 10.3390/min16070700.
  177. L. F. de Brito, C. Juliani, C. de C. Carneiro, and L. F. Dutra, “Mineral prospective mapping for Zn-Pb-Cu-(Ag-Au) through machine learning in the Camaquã Basin, Southern Brazil,” J. Appl. Geophys., vol. 250, p. 106252, Jul. 2026, doi: 10.1016/J.JAPPGEO.2026.106252.
  178. A. S. Akingboye, A. A. Bery, M. D. Dick, B. M. Ahmed, T. O. Ale, and A. O. Olusola, “State-of-the-Art Review of Artificial Intelligence in Environmental Geophysics and Geotechnical Engineering,” May 2026, doi: 10.20944/PREPRINTS202605.1511.V1.
  179. Z. Li et al., “An Adaptive Generalized Regression Neural Network Approach for Ore Grade Estimation Considering Spatial Anisotropy,” Nat. Resour. Res. 2025 345, vol. 34, no. 5, pp. 2423–2442, Jul. 2025, doi: 10.1007/S11053-025-10535-5.
  180. N. Hammouri et al., “Machine and deep learning in geological applications: a review of advances, challenges, and future research directions,” Mediterr. Geosci. Rev. 2026 81, vol. 8, no. 1, pp. 127–148, Feb. 2026, doi: 10.1007/S42990-026-00220-X.
  181. M. Pouresmaieli, M. Ataei, and A. Taran, “Future mining based on internet of things (IoT) and sustainability challenges,” Int. J. Sustain. Dev. World Ecol., vol. 30, no. 2, pp. 211–228, Feb. 2023, doi: 10.1080/13504509.2022.2137261.
  182. M. N. Rahman and K. Lo, “Integrating Deep Learning and IoT for Enhanced Monitoring and Sustainable Mining Practices,” pp. 61–83, 2025, doi: 10.1007/978-3-031-84583-3_5.
  183. Y. Y. Ghadi et al., “Machine Learning Solutions for the Security of Wireless Sensor Networks: A Review,” IEEE Access, vol. 12, pp. 12699–12719, 2024, doi: 10.1109/ACCESS.2024.3355312.
  184. M. Tshanga M, L. Ncube, and E. van Niekerk, “Remote sensing insights into subsurface-surface relationships: Land Cover Analysis and Copper Deposits Exploration,” Earth Sci. Informatics 2024 175, vol. 17, no. 5, pp. 3979–4000, Aug. 2024, doi: 10.1007/S12145-024-01423-2.
  185. D. Tuia et al., “Artificial Intelligence to Advance Earth Observation: A review of models, recent trends, and pathways forward,” IEEE Geosci. Remote Sens. Mag., vol. 13, no. 4, pp. 119–141, 2025, doi: 10.1109/MGRS.2024.3425961.
  186. F. Koerting et al., “VNIR-SWIR Imaging Spectroscopy for Mining: Insights for Hyperspectral Drone Applications,” Min. 2024, Vol. 4, Pages 1013-1057, vol. 4, no. 4, pp. 1013–1057, Nov. 2024, doi: 10.3390/MINING4040057.
  187. W. Tan, S. Wu, Y. Li, and Q. Guo, “Digital Twins’ Application for Geotechnical Engineering: A Review of Current Status and Future Directions in China,” Appl. Sci. 2025, Vol. 15, Page 8229, vol. 15, no. 15, p. 8229, Jul. 2025, doi: 10.3390/APP15158229.
  188. J. Yang, X. Cao, J. Yao, Z. Kang, J. Chang, and Y. Wang, “Geographical big data and data mining: A new opportunity for ‘water-energy-food’ nexus analysis,” J. Geogr. Sci. 2024 342, vol. 34, no. 2, pp. 203–228, Jan. 2024, doi: 10.1007/S11442-024-2202-6.
  189. Z. Wang, L. Bi, J. Li, Z. Wu, and Z. Zhao, “Development Status and Trend of Mine Intelligent Mining Technology,” Math. 2025, Vol. 13, Page 2217, vol. 13, no. 13, p. 2217, Jul. 2025, doi: 10.3390/MATH13132217.
  190. X. Wang et al., “Data-driven artificial intelligence in mineral processing: From sensor technology, intelligent algorithms to Genetic Mineral Processing Engineering,” Int. J. Miner. Metall. Mater., 2026, doi: 10.1007/S12613-026-3503-9.
  191. C. Cacciuttolo, E. Atencio, S. Komarizadehasl, and J. A. Lozano-Galant, “Internet of Things Long-Range-Wide-Area-Network-Based Wireless Sensors Network for Underground Mine Monitoring: Planning an Efficient, Safe, and Sustainable Labor Environment,” Sensors 2024, Vol. 24, Page 6971, vol. 24, no. 21, p. 6971, Oct. 2024, doi: 10.3390/S24216971.
  192. P. Pranjal and A. Soni, “Next-Generation Geographical Information SystemsIntegrating Artificial Intelligence, Geographic Information Systems, and Satellite Imagery for Mapping and Surveying,” Glob. Land-Ocean Geospatial Appl. Mapp. Surv. with Remote Sens. GIS, pp. 216–233, Jan. 2025, doi: 10.1201/9781003422877-10/NEXT-GENERATION-GEOGRAPHICAL-INFORMATION-SYSTEMS-PRANSHU-PRANJAL-ASHISH-SONI.
  193. G. A. Quezada, M. Rai, and M. Rai, “Nanotechnology and AI in Next-Generation Agriculture,” Cutting-Edge Agri-Technologies for Next-Generation Farming, pp. 3–14, Jan. 2026, doi: 10.1201/9781003659907-2/NANOTECHNOLOGY-AI-NEXT-GENERATION-AGRICULTURE-GRACIELA-AVILA-QUEZADA-MAHENDRA-RAI.
  194. A. Machín and F. Márquez, “Next-Generation Chemical Sensors: The Convergence of Nanomaterials, Advanced Characterization, and Real-World Applications,” Chemosens. 2025, Vol. 13, Page 345, vol. 13, no. 9, p. 345, Sep. 2025, doi: 10.3390/CHEMOSENSORS13090345.
  195. Y. Wang, X. Yang, and T. Yang, “Nanobiosensors for Leukemia Minimal Residual Disease Monitoring: A Review of Recent Advances and Translational Challenges,” ACS Sensors, Jul. 2026, doi: 10.1021/ACSSENSORS.6C01594.
  196. N. Thanjavur, L. Bugude, and Y. J. Kim, “Integration of Functional Materials in Photonic and Optoelectronic Technologies for Advanced Medical Diagnostics,” Biosens. 2025, Vol. 15, Page 38, vol. 15, no. 1, p. 38, Jan. 2025, doi: 10.3390/BIOS15010038.
  197. K. Vaid, I. Verma, V. Pullagantil, R. Zboril, and A. Bakandritsos, “Matrix tolerance, probe orientation, and antifouling interfaces in graphene biosensors,” Biosens. Bioelectron., vol. 312, p. 118986, Nov. 2026, doi: 10.1016/J.BIOS.2026.118986.
  198. A. Anney, S. Biswas, A. Anney, and S. Biswas, “Nanomaterials in Energy Storage and Sensing: A Comprehensive Review,” World J. Nano Sci. Eng., vol. 16, no. 1, pp. 1–21, Jan. 2026, doi: 10.4236/WJNSE.2026.161001.
  199. W. Zaman and A. Ayaz, “Real-Sample Validation of Microchemical Sensors: Matrix Effects, Chemometric Reliability, and Field-Ready Analytical Performance,” Crit. Rev. Anal. Chem., 2026, doi: 10.1080/10408347.2026.2695427.
  200. A. E. Ibrahim et al., “Understanding Analytical Methods Assessment Metrics: A Two Decades’ Simple and Comprehensive Review (2006─2025),” Anal. Chem., vol. 98, no. 12, pp. 8730–8756, Mar. 2026, doi: 10.1021/ACS.ANALCHEM.6C00002.
  201. M. Basholli-Salihu, T. Kryeziu, A. Loshaj-Shala, A. Zimmer, and S. S. Behzadi, “Sustainable Circular Manufacturing Using Smart Nanomaterials,” pp. 63–77, 2026, doi: 10.1007/978-3-032-12685-6_3.
  202. D. Panáček et al., “Nanomaterial-Based Inkjet Printing for Electrochemical Sensing,” Small, vol. 22, no. 10, p. e13028, Feb. 2026, doi: 10.1002/SMLL.202513028;CTYPE:STRING:JOURNAL.
  203. S. Kumari, N. Roy, and V. Kumar, “Introduction to AI and IoT in the Field of Earth Sciences,” pp. 1–9, 2025, doi: 10.1007/978-3-031-84583-3_1.
  204. T. N. Hale et al., “Critical minerals policies need clearer interface with scientifically credible targets,” Glob. Sustain., vol. 8, p. e25, Jul. 2025, doi: 10.1017/SUS.2025.10014.