Guest writer Geoffrey Ozin, of the University of Toronto, addresses the difficult problem of reproducing synthesis results in nanochemistry.
The six concepts of nanochemistry that constitute the foundation of a chemical approach to nanomaterials are size and shape, surface and defects, self-assembly and utility in advanced materials and biomedical applications. In this bottom-up paradigm for making nanomaterials, synthetic methods for controlling the degree of perfection of nanomaterials have improved enormously compared to the early days of colloid chemistry that more recently underwent metamorphosis to nanochemistry but how well has the field progressed since then with respect to the reproducibility of a synthesis and why do we care?
The scientific method is founded upon the principle of reproducibility. It has been claimed that the reproducibility of research published in scientific journals is as low as 10-30%: a worrying assertion for the long-term credibility of scientific results. In the context of a nanochemistry approach to nanomaterials, a fair question to ask is what do we actually mean by reproducibility and how reproducible is your nanomaterial synthesis? The degree of agreement between replicate syntheses, by the same or different persons under identical experimental conditions, is a measure of the reproducibility of the synthetic method described in the open literature or patent sources. In academic and industrial research, synthetic protocols reported in a paper or patent should enable replication of the work as a platform for new discoveries, as validation of a claim and as an enabler for commercialization opportunities. So what is the best measure of reproducibility for the synthesis of a nanomaterial, a unique state of matter having properties intermediate between molecules and materials but without the benefits of their atomic perfection and purity? And how reproducible does a nanomaterials synthesis method have to be in order to be useful?
Size and Shape
The problem with nanomaterials is that the product of a synthesis is invariably a poly-dispersion, namely an ensemble of nanoparticles with a distribution of sizes and shapes rather than a collection of identical nanoparticles. Only recently have size separation and analytical techniques been applied to poly-dispersions of nanoparticles to narrow the size distribution in order to better define structure-property relations. So reproducibility in this context perhaps can be best measured and reported in terms of the ability to replicate the distribution of nanoparticle sizes and shapes in a given sample, defined by a poly-dispersity index, PDI = [σ/d)2 + 1] where d and σ are the mean size and the estimated standard deviation of the nanoparticle size distribution. The trouble here is the precision with which one can measure the size and shape of a statistically meaningful population of nanoparticles in distribution. Because many properties of nanoparticles are described by quantum mechanical scaling laws that result from spatial confinement effects of electrons and holes, ideally the size and shape of nanoparticles could be defined with atomic exactitude but in practice this is not possible. Even for the best mono-dispersions typically with PDI of 1.05 the standard deviation of the measurement of nanoparticle size and shape within a distribution in atom equivalents may be tens to hundreds to thousands. Variability of this order of magnitude from nanoparticle synthesis to synthesis can manifest, for example, as inconsistent chemical, electrochemical and photochemical behavior; discrepant optical, electrical, optoelectronic, thermoelectric and piezoelectric properties; and variable activity in biomedical diagnostics and therapeutics.
Surface, Defects, Self-Assembly
External surfaces of nanomaterials present even more serious challenges with respect to reproducibility. The surface is perhaps the most poorly defined, difficult to control and hard to understand property of nanomaterials. Here one has to be cognizant of the surface structure and composition, charge, different kinds of defects (e.g., point, line, plane and cluster) and bonded and adsorbed impurities as well as the number and distribution of organic and/or inorganic capping groups bonded to these surfaces. These features are exceptionally hard to quantify and are never exactly the same from nanoparticle to nanoparticle and between repeat syntheses. Further, because of the high surface to volume ratio inherent to nanoparticles, a large fraction of coordinately unsaturated atoms exist on the surface that can cause the composition to be inherently non-stoichiometric, a property that is exceedingly difficult to quantify analytically. The outcome of non-stoichiometry in nanoparticles can be manifest as doping, mixed valence and trap states. In addition, the forces that control the self-assembly of nanomaterials into functional architectures are varied and complex and the nature of the surface plays a dominant role in determining the structure and properties of the resulting nanoscale constructs. So the ability to control and quantify the reproducibility of nanoparticle surfaces and defects and their self-assembly is nearly impossible. This presents a serious challenge for many advanced materials and biomedical applications with their associated health and safety related issues that rely on command and control of the chemical and physical properties of nanoparticle surfaces.
For molecules and materials that can be purified as single product and single phase, their yield is a quantity that in principle can be precisely defined but what do we mean by yield of a nanomaterial that is presented as an ensemble of nanoparticles with variable sizes, shapes, surfaces and defects? Is measured mass yield of the entire distribution with its estimated standard deviation the meaningful measure of yield and does it adequately define the reproducibility of the synthetic method or does one need to examine each component nanoparticle in the histograms of size, shape and surface?
Because of these synthetic uncertainties, experiments conducted on nanomaterials emerging from different preparations are reporting results for an ensemble average, which for some applications might be quite acceptable but for others could prove to be problematical. Each situation has to be carefully scrutinized with respect to its tolerance to the variations in heterogeneity inherent in the reproducibility of all synthetic nanomaterials.
Towards Reproducibility Standards
The misery about reproducibility of nanomaterials presented in the literature is a worrisome situation for the academic and government research community, and industries that manufacture nanomaterials and develop products and processes thereof. The crux of the problem is a lack of standards and procedures for quantifying reproducibility of known and new nanomaterials. Surely it is the responsibility of the authors of papers and inventors on patents as well as peer reviewers, examiners and publishers of these papers and patents to diligently attend to this aspect of the research, which is blatantly missing from most reports of nanomaterials syntheses.
One could resolve this problem by requiring evidence of the degree of reproducibility to be a prerequisite for publication of papers containing a nanomaterials synthesis. It is true that many analytical methods for defining reproducibility approach their limit of resolution for nanoscale materials therefore it is even more important to provide a sufficiently large set of data to inform the reader about the accuracy and reproducibility of the results.
In this regard, transmission electron microscopy TEM should not be regarded as science but art. At least for the purpose of reporting on reproducibility of a nanomaterials synthesis it cannot serve as a defining experimental diagnostic of the entire product but more often than not a biased slice of reality. Angle dependant dynamic light scattering, DLS and small angle X-ray scattering, SAXS could instead become mandatory standard characterization methods because they give meaningful information on the nanoparticle size and shape distribution of an assembly. Whenever quantum size effects come into play, preparative ultra-centrifugation could be practiced whenever possible in order to obtain and report upon narrower size distributions and the power of analytical ultra-centrifugation could be exploited to define the number of molecules on the surface and atoms in the core of nanoparticles in a distribution.
Ultimately a higher standard is expected of researchers and a tougher stance by referees and publishers for evidence of reproducibility of a nanomaterials synthesis as these higher standards of practice would greatly benefit the nanochemistry community as well as facilitate the transformation of nanomaterials ideas in the laboratory to innovative products and processes in the market place.
I am well aware of the problem to introduce these standards into every day practice and the additional time and effort required to implement them but all one can do is appeal to the scientific conscience of nanochemistry researchers to investigate and report on the extent of reproducibility of their synthetic nanomaterials work.
Nano Food for Thought
On a final note in the context of nano reproducibility, how does the nano community judge scientific quality? Some might say that the work with amazing images and routine science is looked upon more favorably than the work with amazing science and routine images. High quality images cannot be a substitute for high quality science. It should be science first and photography second! The question is, how representative are these art nano images of your pet nanomaterial and the reproducibility of the synthesis. The dilemma the nano community faces is that the literature is replete with the litter of irreproducible nanomaterials syntheses, which undermines progress in the field, diminishes its credibility scientifically and jeopardizes its commercial potential.