The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Detection and Spatial Mapping of Mercury Contamination in Water Samples Using a Smart-Phone
Open accessAbstract
Detection of environmental contamination such as trace-level toxic heavy metal ions mostly relies on bulky and costly analytical instruments. However, a considerable global need exists for portable, rapid, specific, sensitive, and cost-effective detection techniques that can be used in resource-limited and field settings. Here we introduce a smart-phone-based hand-held platform that allows the quantification of mercury(II) ions in water samples with parts per billion (ppb) level of sensitivity. For this task, we created an integrated opto-mechanical attachment to the built-in camera module of a smart-phone to digitally quantify mercury concentration using a plasmonic gold nanoparticle (Au NP) and aptamer based colorimetric transmission assay that is implemented in disposable test tubes. With this smart-phone attachment that weighs <40 g, we quantified mercury(II) ion concentration in water samples by using a two-color ratiometric method employing light-emitting diodes (LEDs) at 523 and 625 nm, where a custom-developed smart application was utilized to process each acquired transmission image on the same phone to achieve a limit of detection of ∼ 3.5 ppb. Using this smart-phone-based detection platform, we generated a mercury contamination map by measuring water samples at over 50 locations in California (USA), taken from city tap water sources, rivers, lakes, and beaches. With its cost-effective design, field-portability, and wireless data connectivity, this sensitive and specific heavy metal detection platform running on cellphones could be rather useful for distributed sensing, tracking, and sharing of water contamination information as a function of both space and time.
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Citations
Cites
Minamata Disease: Methylmercury Poisoning in Japan Caused by Environmental Pollution
Harada, M. (1995) · Critical Reviews in Toxicology · doi:10.3109/10408449509089885 · Cited by 2,069
Ecological effects, transport, and fate of mercury: a general review
Boening, D. W. (2000) · Chemosphere · doi:10.1016/s0045-6535(99)00283-0 · Cited by 1,841
Lee, J., Han, M. S., & Mirkin, C. A. (2007) · Angewandte Chemie International Edition · doi:10.1002/anie.200700269 · Cited by 1,308
MercuryII-Mediated Formation of Thymine−HgII−Thymine Base Pairs in DNA Duplexes
Miyake, Y., Togashi, H., Tashiro, M., Yamaguchi, H., Oda, S., Kudo, M., Tanaka, Y., Kondo, Y., Sawa, R., Fujimoto, T., et al. (2006) · Journal of the American Chemical Society · doi:10.1021/ja056354d · Cited by 1,079
Gold Nanoparticle-Based Sensing of “Spectroscopically Silent” Heavy Metal Ions
Kim, Y., Johnson, R. C., & Hupp, J. T. (2001) · Nano Letters · doi:10.1021/nl0100116 · Cited by 907
Effects of mercury on wildlife: A comprehensive review
Wolfe, M. F., Schwarzbach, S., & Sulaiman, R. A. (1998) · Environmental Toxicology and Chemistry · doi:10.1002/etc.5620170203 · Cited by 887
Clarkson, T. W. (1997) · Critical Reviews in Clinical Laboratory Sciences · doi:10.3109/10408369708998098 · Cited by 886
Point-of-care colorimetric detection with a smartphone
Shen, L., Hagen, J. A., & Papautsky, I. (2012) · Lab on a Chip · doi:10.1039/c2lc40741h · Cited by 609
15N−15N J-Coupling Across HgII: Direct Observation of HgII-Mediated T−T Base Pairs in a DNA Duplex
Tanaka, Y., Oda, S., Yamaguchi, H., Kondo, Y., Kojima, C., & Ono, A. (2007) · Journal of the American Chemical Society · doi:10.1021/ja065552h · Cited by 541
Lensfree microscopy on a cellphone
Tseng, D., Mudanyali, O., Oztoprak, C., Isikman, S. O., Sencan, I., Yaglidere, O., & Ozcan, A. (2010) · Lab on a Chip · doi:10.1039/c003477k · Cited by 480
Self-citationFluorescent Imaging of Single Nanoparticles and Viruses on a Smart Phone
Wei, Q., Qi, H., Luo, W., Tseng, D., Ki, S. J., Wan, Z., Göröcs, Z., Bentolila, L. A., Wu, T.-T., Sun, R., et al. (2013) · ACS Nano · doi:10.1021/nn4037706 · Cited by 452
Self-citationSelective Detection of Mercury (II) Ion Using Nonlinear Optical Properties of Gold Nanoparticles
Darbha, G. K., Singh, A. K., Rai, U. S., Yu, E., Yu, H., & Chandra Ray, P. (2008) · Journal of the American Chemical Society · doi:10.1021/ja801412b · Cited by 434
Liu, D., Wang, Z., & Jiang, X. (2011) · Nanoscale · doi:10.1039/c0nr00887g · Cited by 427
Integrated rapid-diagnostic-test reader platform on a cellphone
Mudanyali, O., Dimitrov, S., Sikora, U., Padmanabhan, S., Navruz, I., & Ozcan, A. (2012) · Lab on a Chip · doi:10.1039/c2lc40235a · Cited by 426
Optofluidic Fluorescent Imaging Cytometry on a Cell Phone
Zhu, H., Mavandadi, S., Coskun, A. F., Yaglidere, O., & Ozcan, A. (2011) · Analytical Chemistry · doi:10.1021/ac201587a · Cited by 390
Self-citationGold nanoparticle probes for the detection of mercury, lead and copper ions
Lin, Y.-W., Huang, C.-C., & Chang, H.-T. (2011) · The Analyst · doi:10.1039/c0an00652a · Cited by 379
Methylmercury production below the mixed layer in the North Pacific Ocean
Blum, J. D., Popp, B. N., Drazen, J. C., Anela Choy, C., & Johnson, M. W. (2013) · Nature Geoscience · doi:10.1038/ngeo1918 · Cited by 375
McDowell, M. A., Dillon, C. F., Osterloh, J., Bolger, P. M., Pellizzari, E., Fernando, R., de Oca, R. M., Schober, S. E., Sinks, T., Jones, R. L., et al. (2004) · Environmental Health Perspectives · doi:10.1289/ehp.7046 · Cited by 364
Smartphone based health accessory for colorimetric detection of biomarkers in sweat and saliva
Oncescu, V., O'Dell, D., & Erickson, D. (2013) · Lab on a Chip · doi:10.1039/c3lc50431j · Cited by 362
Mercury levels in high-end consumers of fish.
Hightower, J. M., & Moore, D. (2003) · Environmental Health Perspectives · doi:10.1289/ehp.5837 · Cited by 339
Cost-effective and compact wide-field fluorescent imaging on a cell-phone
Zhu, H., Yaglidere, O., Su, T.-W., Tseng, D., & Ozcan, A. (2011) · Lab Chip · doi:10.1039/c0lc00358a · Cited by 330
Self-citationLabel-free biodetection using a smartphone
Gallegos, D., Long, K. D., Yu, H., Clark, P. P., Lin, Y., George, S., Nath, P., & Cunningham, B. T. (2013) · Lab on a Chip · doi:10.1039/c3lc40991k · Cited by 312
Cellphone-based devices for bioanalytical sciences
Vashist, S. K., Mudanyali, O., Schneider, E. M., Zengerle, R., & Ozcan, A. (2014) · Analytical and Bioanalytical Chemistry · doi:10.1007/s00216-013-7473-1 · Cited by 305
Self-citationColorimetric Detection of Mercury Ions Based on Plasmonic Nanoparticles
Du, J., Jiang, L., Shao, Q., Liu, X., Marks, R. S., Ma, J., & Chen, X. (2013) · Small · doi:10.1002/smll.201200811 · Cited by 289
A personalized food allergen testing platform on a cellphone
Coskun, A. F., Wong, J., Khodadadi, D., Nagi, R., Tey, A., & Ozcan, A. (2013) · Lab Chip · doi:10.1039/c2lc41152k · Cited by 280
Self-citationQuantum dot enabled detection of Escherichia coli using a cell-phone
Zhu, H., Sikora, U., & Ozcan, A. (2012) · The Analyst · doi:10.1039/c2an35071h · Cited by 277
Self-citationCost-effective and rapid blood analysis on a cell-phone
Zhu, H., Sencan, I., Wong, J., Dimitrov, S., Tseng, D., Nagashima, K., & Ozcan, A. (2013) · Lab on a Chip · doi:10.1039/c3lc41408f · Cited by 274
Self-citationRapid electrochemical detection on a mobile phone
Lillehoj, P. B., Huang, M.-C., Truong, N., & Ho, C.-M. (2013) · Lab on a Chip · doi:10.1039/c3lc50306b · Cited by 259
Cho, E. S., Kim, J., Tejerina, B., Hermans, T. M., Jiang, H., Nakanishi, H., Yu, M., Patashinski, A. Z., Glotzer, S. C., Stellacci, F., et al. (2012) · Nature Materials · doi:10.1038/nmat3406 · Cited by 214
Chip-Based Scanometric Detection of Mercuric Ion Using DNA-Functionalized Gold Nanoparticles
Lee, J.-S., & Mirkin, C. A. (2008) · Analytical Chemistry · doi:10.1021/ac801046a · Cited by 210
Albumin testing in urine using a smart-phone
Coskun, A. F., Nagi, R., Sadeghi, K., Phillips, S., & Ozcan, A. (2013) · Lab on a Chip · doi:10.1039/c3lc50785h · Cited by 208
Self-citationMinamata Disease: Methylmercury Poisoning In Minamata And Niigata, Japan
Tsubaki, T., & Irukayama, K. (1977) · Medical Entomology and Zoology · Cited by 145
Smart-phone based computational microscopy using multi-frame contact imaging on a fiber-optic array
Navruz, İ., Coskun, A. F., Wong, J., Mohammad, S., Tseng, D. K., Nagi, R., Phillips, S. W., & Özcan, A. (2013) · Lab on a Chip · doi:10.1039/c3lc50589h · Cited by 112
Self-citationStacchiotti, A., Morandini, F., Bettoni, F., Schena, I., Lavazza, A., Grigolato, P. G., Apostoli, P., Rezzani, R., & Aleo, M. F. (2009) · Toxicology · doi:10.1016/j.tox.2009.08.014 · Cited by 108
Highly Robust, Recyclable Displacement Assay for Mercuric Ions in Aqueous Solutions and Living Cells
Liu, D., Wang, S., Swierczewska, M., Huang, X., Bhirde, A. A., Sun, J., Wang, Z., Yang, M., Jiang, X., & Chen, X. S. (2012) · ACS Nano · doi:10.1021/nn3046192 · Cited by 62
Computational imaging, sensing and diagnostics for global health applications
Coskun, A. F., & Özcan, A. (2013) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2013.08.008 · Cited by 43
Biological Monitoring for Mercury within a Community with Soil and Fish Contamination
Harnly, M., Seidel, S. L., Rojas, P., Fornes, R., Flessel, P., Smith, D., Kreutzer, R., & Goldman, L. R. (1997) · Environmental Health Perspectives · doi:10.1289/ehp.97105424 · Cited by 33
A novel camera phone-based platform for quantitative fluorescence sensing
O'Driscoll, S., MacCraith, B. D., & Burke, C. S. (2013) · Analytical Methods · doi:10.1039/c3ay40116b · Cited by 16
Cited by
Smartphone-based biosensors: A critical review and perspectives
Roda, A., Michelini, E., Zangheri, M., Di Fusco, M., Calabria, D., & Simoni, P. (2016) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2015.10.019 · Cited by 520
Point-of-Care Diagnostics: Recent Developments in a Connected Age
Nayak, S., Blumenfeld, N. R., Laksanasopin, T., & Sia, S. K. (2017) · Analytical Chemistry · doi:10.1021/acs.analchem.6b04630 · Cited by 508
Metadata
- Authors
- Wei, Q., Nagi, R., Sadeghi, K., Feng, S., Yan, E., Ki, S. J., Caire, R., Tseng, D., & Ozcan, A.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2014-01-28
- Volume
- 8
- Issue
- 2
- Pages
- 1121-1129
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W2016736813
- Cited by
- 400
- References
- 38
- FWCI
- 28.47
- Type
- journal article
- Language
- en
- Open access
- hybrid
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