ArticleACS nano2014
Detection and spatial mapping of mercury contamination in water samples using a smart-phone.
Article in ACS nano, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
69 citing papers in PubMed, 398 citations in OpenAlex.
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- Restricted Intramolecular Rotation: A Dual Fluorescence Response to HgJournal of fluorescence · 2025Article
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- Discoloration of stretched colored elastomeric modules : An in vivo study.Journal of orofacial orthopedics = Fortschritte der Kieferorthopadie : Organ/official journal Deutsche Gesellschaft fur Kieferorthopadie · 2024Article
- Multi-scale fractal Fourier Ptychographic microscopy to assess the dose-dependent impact of copper pollution on living diatoms.Scientific reports · 2024Article
- Quantitative, high-sensitivity measurement of liquid analytes using a smartphone compass.Nature communications · 2024Article
- A digital image colorimetry system based on smart devices for immediate and simultaneous determination of enzyme-linked immunosorbent assays.Scientific reports · 2024Article
- Advancing biological investigations using portable sensors for detection of sensitive samples.Heliyon · 2023Review
- Portable sensing devices for smart healthcare and prevention of lead poisoning.Journal of the Chinese Medical Association : JCMA · 2023Review
- A smartphone-based fluorospectrophotometer and ratiometric fluorescence nanoprobe for on-site quantitation of pesticide residue.iScience · 2023Article
- Smartphone-Based Quantitative Analysis of Protein Array Signals for Biomarker Detection in Lupus.Chemosensors (Basel, Switzerland) · 2022Article
- High Quality TaSNanomaterials (Basel, Switzerland) · 2022Article
- Portable smartphone-based colorimetric system for simultaneous on-site microfluidic paper-based determination and mapping of phosphate, nitrite and silicate in coastal waters.Environmental monitoring and assessment · 2022Article
- A large dataset of white blood cells containing cell locations and types, along with segmented nuclei and cytoplasm.Scientific reports · 2022Observational
- Comparative Study on the Efficiency of Mercury Removal From Wastewater Using Bacterial Cellulose Membranes and Their Oxidized Analogue.Frontiers in bioengineering and biotechnology · 2022Article
- Development and optimization of heavy metal lead biosensors in biomedical and environmental applications.Journal of the Chinese Medical Association : JCMA · 2021Review
- Sensitive quantitative detection of SARS-CoV-2 in clinical samples using digital warm-start CRISPR assay.Biosensors & bioelectronics · 2021Article
- Band-pass filter-assisted ratiometric fluorescent nanoprobe composed of N-(2-aminoethyl-1,8-naphthalimide)-functionalized gold nanoclusters for the determination of alkaline phosphatase using digital image analysis.Mikrochimica acta · 2021Article
- Smartphone-enabled field monitoring tool for rapid hexavalent chromium detection in water.Analytical and bioanalytical chemistry · 2021Article
- Aptamer-Functionalized Hybrid Nanostructures for Sensing, Drug Delivery, Catalysis and Mechanical Applications.International journal of molecular sciences · 2021Review
9 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 2 institutions in 1 country.
Funding
Abstract
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.