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.

We demonstrate a digital sensing platform, termed Albumin Tester, running on a smart-phone that images and automatically analyses fluorescent assays confined within disposable test tubes for sensitive and specific detection of albumin in urine. This light-weight and compact Albumin Tester attachment, weighing approximately 148 grams, is mechanically installed on the existing camera unit of a smart-phone, where test and control tubes are inserted from the side and are excited by a battery powered laser diode. This excitation beam, after probing the sample of interest located within the test tube, interacts with the control tube, and the resulting fluorescent emission is collected perpendicular to the direction of the excitation, where the cellphone camera captures the images of the fluorescent tubes through the use of an external plastic lens that is inserted between the sample and the camera lens. The acquired fluorescent images of the sample and control tubes are digitally processed within one second through an Android application running on the same cellphone for quantification of albumin concentration in urine specimen of interest. Using a simple sample preparation approach which takes ~ 5 minutes per test (including the incubation time), we experimentally confirmed the detection limit of our sensing platform as 5–10 μg/mL (which is more than 3 times lower than clinically accepted normal range) in buffer as well as urine samples. This automated albumin testing tool running on a smart-phone could be useful for early diagnosis of kidney disease or for monitoring of chronic patients, especially those suffering from diabetes, hypertension, and/or cardiovascular diseases.