The unique properties of engineered nanoparticles (ENPs) have created intense interest in their environmental behavior. Due to the increased use of nanotechnology in consumer products, industrial applications and health care technology, nanoparticles are more likely to enter the environment. For this reason, it’s not only important to know the type, size and distribution of nanoparticles in soils, potable waters and wastewaters, but it’s also crucial to understand their impact on the growing mechanism of crops used for human consumption. Therefore, in order to ensure the future development of nanotechnology products, there’s clearly a need to evaluate the risks posed by these ENPs which will require proper tools to fully understand their toxological impact on human health.
Current approaches to assess exposure levels include predictions based on computer modeling, together with direct measurement techniques. Predictions through modeling are based on knowledge of how they are emitted into the environment and by their behavior in the samples being studied. While the lifecycles of ENPs are now starting to be understood, there’s very little known about their environmental behavior. For example, when Cd-based quantum dots are released into the environment, Cd is still in the solid phase. However, when they eventually dissolve, they become extremely toxic due to the inherent toxicity of Cd2+.
Prediction through lifecycle assessment modeling requires validation through measurement at environmentally significant concentrations. For ENPs that are being released into the environment, extremely sensitive methods are required to ensure that direct observations are representative in time and space. ENPs differ from most conventional ‘‘dissolved’’ chemicals in terms of their heterogeneous distributions in size, shape, surface charge, composition, degree of dispersion and more. For this reason, it’s not only important to determine their concentrations, but also these other important metrics.
The measurement and characterization of nanoparticles is therefore critical to all aspects of nanotechnology. In the field of environmental health, it has become clear that complete characterization of nanomaterials is important for interpreting the results of toxicological and human health studies. Metal-containing ENPs are a particularly significant class, as their use in consumer products and industrial applications makes them the fastest growing category of nanoparticles.
Many analytical techniques are available for nanometrology, only some of which can be successfully applied to environmental health studies. Methods for assessing particle size distributions include electron microscopy, chromatography, laser light scattering, ultrafiltration and field flow fractionation. However, the lack of specificity of these techniques is problematic for complex environmental matrices that may contain natural nanoparticles having polydisperse size distributions and heterogeneous compositions. For this reason, sensitive detection techniques are needed if specific information about the elemental composition and concentration of the nanoparticles is required. Unfortunately, difficulties can also arise with some detection techniques due to a lack of sensitivity for characterizing and quantifying particles at environmentally relevant concentrations.
Role of ICP-MS
One technique that is proving invaluable for detecting and sizing metallic nanoparticles is ICP mass spectrometry (ICP-MS). Its combination of elemental specificity, sizing resolution and unmatched sensitivity makes it extremely applicable for the characterization of ENPs containing elements such as Ag, Au and Ti which have been integrated into larger products such as consumer goods, foods, pharmaceuticals and personal care products.
Much of the early work has focused on the use of ICP-MS with particle separation techniques, such as field flow fractionation and chromatography. However, more recently, an exciting new approach called single-particle (SP) ICP-MS is showing a great deal of promise in several applications areas, including the determination of concentrations of silver NPs in complex wastewater samples. This technique is also ideally suited to differentiate between the analyte in solution and existing as a nanoparticle. This ability allows SP-ICP-MS to provide information on the size and size distribution of nanoparticles, as well as the dissolved concentration of the analyte.
SP-ICP-MS involves introducing NP-containing samples at environmentally significant concentrations into the ICP-MS and collecting time-resolved data. Because of the very low elemental concentrations and the transient nature of ionized nanoparticles, high sensitivity and very short measurement times are necessary in order to ensure the detection of individual particles as ion pulses. The number of observed pulses is related to the NP concentration by the nebulization efficiency and the total number of NPs in the sample, while the size of the NP is related to the pulse intensity.
Optimized measurement protocol
For this approach to work effectively, the speed of data acquisition and the response time of the detector must be fast enough to capture the time resolved NP pulses, which last less than 1 msec. If the electronics are not fast enough, two or three pulses can easily pass through and be erroneously detected as a single pulse. This is demonstrated in Figure 1, which shows the detection of two single particles over a fixed measurement (dwell) time. The graph shows two nanoparticles detected in a single dwell time window (top), resulting in an instrumental response (bottom), which is twice as large as one particle being detected. It can be clearly seen that by selecting a shorter dwell time, the possibility of detecting two pulses in the measurement window is significantly reduced.
The real-world analysis of a sample containing nanoparticles in suspension is more complex than the example shown in Figure 1. This is emphasized in Figure 2, which shows the signal from analysis of a sample containing 60-nm silver nanoparticles; each peak essentially results from a single nanoparticle being ionized in the plasma.
If one of these time-resolved peaks is examined closely as shown in Figure 3, it can be seen that the silver NP pulse has been generated in less than 1 msec. Ideally, for this application, the ICP-MS should be capable of using dwell times shorter than the particle transient time, thus avoiding false signals generated from clusters of particles. In practice, this means using a dwell time of a 10 to 100 µsec so the pulse can be fully characterized.
From a practical perspective, using very short integration times to fully characterize a NP pulse isn’t a trivial task because signal convolution is a complex process that requires a high level of data processing. In Figure 4a, data was collected with a dwell time of 100 µsec, which means that six points were used to define the peak. In Figure 4b, the dwell time was reduced to 50 µsec which results in 12 points being used to define the peak. This example clearly shows that shorter dwell times yields a more accurate mapping of the nanoparticle pulse, which is important for understanding the nanoparticle’s shape.
Another aspect of SP-ICP-MS analysis to consider is the settling time of the instrument’s electronics between measurements. For the analysis of dissolved elements, the settling time is important as the instrument moves between different masses. However, for the analysis of nanoparticles, only a single analyte mass is usually measured. As a result, there is no need for the instrument electronics to settle between measurements. The use of a settling time is actually detrimental to SP-ICP-MS analysis because it allows particles to be missed as they are ionized while the instrument is not measuring. Thus, the elimination of instrument settling time is important for nanoparticle analysis.
The excellent elemental sensitivity and specificity of ICP-MS makes it the ideal detection technique for the characterization of metal-based engineered nanomaterials. Coupled with particle separation techniques like field flow fractionation, ICP-MS is a very sensitive detector. In addition, using ICP-MS in the Single Particle analysis mode allows more information to be obtained in a much shorter time, such as understanding how much of the nanoparticle has dissolved in the sample and how much is still in the suspended particulate form. However it should be emphasized that measuring single particles with ICP-MS is quite different to measuring dissolved species. For this reason, it is very important that the speed of data acquisition and the measurement protocol be optimized to detect and process rapid transient events.