How safe are nanoparticles? Amanda Barnard, at the Commonwealth Scientific and Industrial Research Organisation, Clayton, Australia, reveals how computation can help to identify and prevent nanohazards

For the move from nanoscience to nanotechnology to be sustainable, it is important that issues surrounding the risks be addressed before commercialisation, both in terms of exposure and potential nanohazards. Since we (as a society) are diligently producing more and more biodegradable and recyclable products, it is inevitable that any nanoparticles in them will be introduced into the natural world. Since we currently have no efficient way of extracting nanoparticles once released, we must assume that the duration of exposure is indefinite.

Predicting the properties of nanoparticles could help to identify and prevent nanohazards to health and the environment

The hazards associated with nanomaterials are another story. We already have the expertise required to assess and mitigate potential nanohazards. If done correctly, the overall risk can be significantly reduced - or even prevented entirely. But how do we move from hazard to prevention, and where do we start?

To date, most toxicity studies of nano-sized particles are based on established research on airborne ultra-fine particles, known to occur either naturally or unintentionally through human activities or industrial processes. The main difference between this field and the emerging field of nanotoxicology is that nanomaterials are being specifically engineered to exhibit characteristics that are unlike any we have encountered before. It is these engineered characteristics that provide the superior performance we desire for a variety of high tech applications.

Currently attention is focused on interactions between nanomaterials and living organisms. There have been numerous reports, surveys, inquiries and articles from academic, government and private bodies. Common concerns raised in these documents are the potential hazards associated with dispersed or isolated nanomaterials, as opposed to those already integrated into products and devices. This is because many isolated nanomaterials are smaller than the biological systems with which they interact, and can potentially damage tissue at the cellular level or even damage DNA.

This is an area of increasing activity, and researchers with diverse scientific backgrounds are focusing their efforts on characterising nanoparticles and their interactions. However, it is not intuitively clear where individual efforts (and resources) should be focused or how we can collaborate to achieve optimal results. It is helpful to have an overarching scheme to highlight how to combine these isolated investigations in a logical and systematic way.

Firstly, to find a link between nanohazards and their prevention (that does not require something dangerous to have already happened), we need to develop new predictive capabilities based on fundamental physical properties. We already have some clues of where to look, such as the strong link between nanohazards and the reactivity of nanoparticle surfaces. We also know that the reactivity of nanoparticles can exhibit a high degree of selectivity that depends sensitively on the material (both composition and solid phase), the size (surface-to-volume ratio), and on the shape (nanomorphology).

Therefore, combining reactivity measurements and nanomorphology modelling can open up routes to prevention. These routes take account of the natural distribution of possible values resulting from the dispersivity of sizes, shapes and surface chemistries exhibited by real samples, while still providing insight into the underlying mechanisms involved. The key here is to adopt strategy that builds on the strengths of each approach.

Once we have obtained sufficient data and developed a robust understanding of the potential hazards associated with nanomaterials, linking our predictions with actual prevention mechanisms will still present a challenge. Making this final connection is more than just a multidisciplinary problem. It is a multi-field problem and will be as much an exercise in knowledge sharing as it will be in scientific discovery.

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