You’ve got to love Aydogan Ozcan. The UCLA professor is coming out with new laboratory equipment that relies on accessible technology every few months now. He and his team have previously released a system for detecting Albumin and a smartphone device for finding allergens in food. And, last October, we covered a 3D-printed microscope adapter for your smartphone. Most recently, the professor and his team have published a paper detailing a mercury detector that, as you may have guessed, also relies on a smartphone with a bit of 3D printing to boot.
The ability to detect poisonous heavy metals has decreased in cost recently, but, as the report points out, low-cost methods for detecting something like mercury don’t utilize the technology that so many people carry around in their pockets. “Cellphone subscriptions worldwide have reached more than 7 billion by the end of 2013, and smart- phone penetration rate is globally increasing,” the paper explains and, with that in mind, the researchers endeavoured to create a device that uses the computing power and wireless capabilities of a smartphone for heavy metal detection:
To provide a field-portable, cost-effective, and wirelessly connected platform to sensitively quantify heavy metal ion concentration in water samples, here we report a battery-powered mobile sensing device that consists of a lightweight (∼37 g) opto-mechanical attachment to a smart-phone along with a custom- developed Android application for quantification, reporting, and sharing of detection results. This lab-on- a-phone device is based on dual-wavelength illumination using light-emitting diodes (LEDs) at 523 and 625 nm and can quantify mercury-induced subtle transmission changes of a colorimetric assay utilizing citrate-stabilized plasmonic Au NPs and aptamers (Apt) mixed within disposable test tubes. Due to the shift in the plasmonic resonance wavelength of dispersed and aggregated Au NPs in response to mercury(II) ions, we demonstrated sensitive detection of mercury contamination in water samples with a limit of detection (LOD) of ∼3.5 ppb, which has the same order of magnitude as the maximum contaminant level (MCL) of mercury(II) recommended for drinking water, i.e., 2 and 6 ppb, as established by the U.S. Environmental Protection Agency (EPA) and the World Health Organization (WHO), respectively.23,24 With this cellphone-based colorimetric detection platform, we also demonstrated geospatial mapping of mercury(II) contamination in California by testing water samples collected at more than 50 locations, from tap water sources as well as natural sources such as rivers, lakes, and beaches.
In other words, by combining red and green LEDs with a colorimetric assay, relying on previously developed low-cost mercury detection methods, the researchers were able to construct a device that attaches to a Samsung Galaxy II and reacts to mercury in a water sample. The entire housing of the device was designed in Autodesk Inventor and constructed on a Dimension Elite 3D printer from Stratasys.
Figure 1. from the report: “Design of the ratiometric optical reader on a smart-phone. (a) 3D schematic illustration of the internal structure of the opto-mechanical attachment. The inset image shows the same attachment with a slightly different observation angle. (b) Photograph of the actual optical reader installed on an Android-based smartphone. The screen of the smart-phone displays a typical image of the sample and control cuvettes when illuminated by red (625 nm) and green (523 nm) LEDs simultaneously.”
The technical details of the apparatus are a bit confusing, but the LEDs seem to capture the samples in the right light to read the level of mercury saturation. Red and green images of water samples, housed in small test tubes, are taken and sent to an Android app developed by the team. The app matches your image against a controlled sample image and “a previously stored calibration curve is used to convert the calculated signal ratio into the mercury concentration level of the sample (in ppb), and the results are then displayed on the screen of the phone.” This whole process takes about 7 seconds.
“Screen shots of our mercury detection application running on an Android phone. (a) Main menu; (b) calibration menu; (c) preview of a captured or selected colorimetric image before proceeding to analyze/quantify the sample; (d) display of the results; (e) spatiotemporal mapping of mercury contamination using a Google Maps-based interface; (f) tracking of mercury levels as a function of time per location.”
The sample can be locked into a GPS location so that the team was able to go throughout California and document water from more than 50 locations, hinting at the possibility of a global mercury (and other toxins) pollution database. As you can see from the chart below, the majority of tests that revealed unsafe concentrations of mercury, “above 6 ppb, i.e., the safety level recommended by WHO are mostly from ocean samples, with the worst being from the San Francisco Bay.” The report links this with the fact that the ocean is the last place that water travels to on its journey through land.
I hate to think about just how relevant this application is, considering the acts of industrial negligence that have occurred as of late (and since the Industrial Revolution). The Fukushima Nuclear Plant is still in the process of being cleaned up and stabilized. Freedom Industries’ chemical spill is a US example of how the lack of regulation and regulation enforcement has affected the drinking water of a large population. And, even more recently, the US’s largest energy plant, a Duke Energy plant in North Carolina, spilled 27 million gallons of water contaminated with toxic coal ash into the Dan River and threatened the region’s supply of drinking water. If such companies aren’t sufficiently regulated before it’s too late, we may end up relying on smartphone devices such as Ozcan’s to remain safe in a polluted world. We may end up with smartphones more and more similar to the Tricoders of Star Trek, but it may be at the price of a stable environment.
Source: ACS Nano
