Erik K. Richman and James E. Hutchison* Department of Chemistry and Materials Science Institute, University of Oregon, Eugene, Oregon 97403
evelopment in nanomaterials has moved beyond the discovery phase targeting wholly new compositions. Reports of more complex, composite systems are beginning to appear in the literature where the recombination of earlier materials into higher complexity structures introduces new questions of functionality.1–4 In growing numbers, producers are selling basic nanomaterials,5–8 and applications are being developed for the earliest discovered materials. The production and commercialization of fully integrated systems are only a matter of time. In exploiting bulk materials for commercial applications, such as electronics, large organizations (e.g., chip manufacturers) will use a clean room and vacuum environments, in addition to highly refined reagents, checking every step in the process with highly automated tools. As complex as electronic devices are, they are made of relatively simple materials, even at the nanoscale. In contrast, nanomaterials are frequently derived from benchtop production methods, with very little of the same thorough controls. To exploit nanomaterials, the tools must mature at the research laboratory level to enable more systematic characterization and quality control for production. New Uses, New Risks, New Unknowns. Mature materials development is generally predicated upon decreasing the metrology required. Figure 1 explores the relationship between developmental stages and characterization. The dotted curve describes the desirable trend wherein characterization breadth is reduced to the minimum set of properties at the point of use. A researcher will subject the material to all manner of tests such that the end consumer can use it with the expectation of advertised function. After the properties are researched, the synthesis routine for a particular nanomaterial is assumed to be unvarying and companies mass produce them, checking
D
www.acsnano.org
ABSTRACT The future of nanotechnology rests upon approaches to making new, useful nanomaterials and testing them in complex systems. Currently, the advance from discovery to application is constrained in nanomaterials relative to a mature market, as seen in molecular and bulk matter. To reap the benefits of nanotechnology, improvements in characterization are needed to increase throughput as creativity outpaces our ability to confirm results. The considerations of research, commerce, and regulation are part of a larger feedback loop that illustrates a mutual need for rapid, easy, and standardized characterization of a large property matrix. Now, we have an opportunity and a need to strike a new balance that drives higher quality research, simplifies commercial exploitation, and allows reasoned regulatory approaches.
only for quality control, which for simple chemicals might just be mass. With a constant, predictable supply, a known material can be exploited for applications. Alternately, effects can also be assessed for more complex systems, such as biological or environmental. In reality, there is a bottleneck in this process, represented by the dashed curve in Figure 1. For nanomaterials, so many properties are unknown or ill-defined that every step needs to be confirmed with control experiments to enable reproducible or predictable outcomes. Currently, reproducible results require slow, specialized monitoring of nanomaterials. Available products are frequently little more than laboratory curiosities with limited labels and unknown quality control and process efficiency.5–9 Applications and systems research developed from these massproduced materials will suffer unless discovery-level characterization is continued. The new properties raise concern for the altered effects and unpredictable toxicity causing regulators to revisit standards for exposure, emissions, and waste management.10–13 The characterization bottleneck is a natural opportunity to accelerate nanotechnology, but it requires understanding the problems’ facets in each sector of nanotechnology: research, commerce, and regulation. Researchers seek a deep understanding of nanomaterials that requires reproducible, well-defined properties and synthesis
NANO FOCUS
The Nanomaterial Characterization Bottleneck
*Address correspondence to
[email protected]. Published online September 22, 2009. 10.1021/nn901112p CCC: $40.75 © 2009 American Chemical Society
VOL. 3 ▪ NO. 9 ▪ 2441–2446 ▪ 2009
2441
NANO FOCUS
Figure 1. Characterization level ␣ as a function of known properties. Heavy characterization is necessary to establish existence, synthesis, and properties. Production characterization is mostly concerned with batch-to-batch variation and maintaining advertised functions or properties. Ideally, characterization of developed materials for application is limited to quality control of the applied device. In a mature field (dotted line), this function drops off rapidly between stages of development. Generally, nanotechnology (dashed line) is not achieving the drop-off necessary for profitable deployment. The value of addressing this bottleneck is the impact that faster, facile, and standardized characterization can make in developing nanotechnology.
only achievable by complete characterization. The same questions are faced repeatedly. Why did today’s batch fail? Are products strongly dependent on daily variables? How do physical properties relate to measured structure? Are the measurements coupled to uncontrolled variables? Is the benchtop a reproducible environment?
The characterization bottleneck is a natural opportunity to accelerate nanotechnology, but it requires understanding the problems’ facets in each sector of nanotechnology: research, commerce, and regulation. Manufacturers generally demand less breadth of analysis but higher throughput. Successful commercial entities seeking to shape a market want return customers. This means answering the questions of material reproducibility. What can be delivered? Can the customer trust the label? Can the next bottle be guaranteed the same as the 2442
last? How can questions of structure and purity be answered rapidly and inexpensively? Regulators face the fact that the altered properties of nanomaterials make using the antiquated rules for bulk materials imprecise and inaccurate. What materials can be released once they are made small? Where are these materials transported? How are the nanomaterials transformed upon release/exposure? How do nanomaterials interact with biological and environmental systems? What kind of MSDS can be delivered? Can exposure be reduced? All of these sectors would be enhanced by investment in fast techniques, recognized standards, and determination of a minimum characterization set. The speed of an experiment frequently determines its use and level of training difficulty. The tools that a company uses in microelectronics production are practically turn-key; the operator has little need for the theory behind the measurement to obtain consistent and useful results that guide manufacture. In contrast, nanomaterial characterization is still more akin to a research project. Establishing standards is the only way to make comparisons across systems. At present, there is no established “platinum⫺iridium bar” for standardizing nanoscale materials metrology, nor even a consistently preferred measurement. For example, if a particle size is reported with dynamic light scattering (DLS), it includes the
VOL. 3 ▪ NO. 9 ▪ RICHMAN AND HUTCHISON
ligand shell, while transmission electron microscopy (TEM) ignores it. Which is right? Which is relevant? Are both needed? Are both stable over time? Certainly minimum sets of characterization and standardized methods are necessary for efficient characterization. Value. One of the reasons to focus on nanometrology now is to preserve market value and expedite commercialization. Well-defined and wellcharacterized materials are the best way to build reproducibility and quality control into commercial systems. This leads to predictable behavior that can be regulated, ensuring safety, shaping the market to enhance acceptance of the capabilities of nanomaterials. In addition, there are clear consequences of failing to direct the market and building public perception and trust. To enter the market and to spread their benefits, the introduction of nanomaterials should heed similar situations from the past, including those surrounding Teflon14,15 and mercury preservatives.16 In each case, fear, uncertainty, and doubt have clouded the benefits due to debatable or unknown risks. The “nano” concept is powerful and has driven many papers, proposals, and early products. A potential effect of branding so many new materials under the heading of “nano” is that demonstrated or speculated side effects of some can tar the rest with the same brush, irrespective of similarity. Genetically modified foods serve as an example of the public delivering a broad negative reaction, independent of individual product merit.17 These situations can hopefully be avoided, as they will slow the adoption and benefits realized from nanomaterials due to socially amplified risk assessments.18,19 Navigating around these sorts of difficulties requires pure, well-defined and wellcharacterized nanomaterials, deliverable to users, as well as nanoenvironmental health and safety (nanoEHS) assessments that allow deterministic structural activity relationships (SARs). Purity. Generally, the method for producing nanomaterials in a lab flows from one of two starting points.20 From bulk matter, various etching tools can www.acsnano.org
branding so many new materials under the heading of “nano” is that demonstrated or speculated side effects of some can tar the rest with the same brush, irrespective of similarity. reduce or break up a solid until it starts to exhibit altered properties that do not scale. Alternately, starting from gases or solutes, atoms and molecules are assembled into structures of increasing complexity. Either way, some deliverable product (solution, suspension, film, or powder) results. Measurements then consist of techniques that often omit critical data (e.g., electron microscopy, X-ray diffraction). The difficulties are in the differences between the actual complexity and the ideal model system depicted in Figure 2. The discovery literature seeks to describe the ideal particle teased out of the swarm of heterogeneity in the real mixture. This tunnelvision approach produces an idealized picture at the cost of confusing results further down the developmental chain. The problem is fundamental, as the omitted data are not negligible fringe effects. At the nanoscale, everything is part of the fringe. Whether a nanomaterial is developed from the bottom up or pared away from the bulk down, the yields are never 100% single phase. This means that the remnant reactants, catalyst materials, and side products are present and significant,21,22 even though the focus of a discovery is usually only on the target structure. However, subsequent property measurements that are critical to manufacture, application, and regulation (i.e., mass, surface area, conductivity, optical absorbance, toxicity, reactivity, catalytic activity, symmetry) www.acsnano.org
For nanomaterials, it is a wholly different problem. Materials with a feature size of ⬍100 nm can be suspensions, powders, thin films, and single crystals, all with varied structures and compositions. An idealized particle (Figure 2) will possess a core and include N layers of shells and terminate in either a bare surface or ligand coating.1–4,20 The core can exhibit any of a number of shapes and symmetries: spheres, cubes, rods, triangles, planes, or combinations as with tetrapods or porous films. The shell may include subtle changes in atomic lattice or could be an altogether different compound. Finally, the ligand coating in a general system can range over many practical thicknesses from one or two bonds to thousands (in the case of a polymer). To make matters worse, most nanomaterials samples contain impuri-
ties that compromise detailed analysis and characterization. With regard to what we need to know, many nanomaterials properties scale with surface area or particle number. Unfortunately, the effective particle number of nanomaterials does not directly scale with its bulk or molecular dosimetrics: mass, volume, molality, molarity. For a given mass, the effective particle number is determined by many other factors (i.e., size, geometry, aggregation, solubility). A property that is particularly sensitive to the complexity is toxic response: a function of reactivity, bioavailability, and fate. Reactivity can be a function of surface area but also composition, interfacial coatings, band gaps, and so on. In a given system, bioavailability and fate may couple with size, number, aspect ratio, aggregation, coatings, and decomposition rate.23,25 The complexity grows as all of these properties are frequently shown to be tunable independent of one another in the normal course of discovery research.20 Characterization Methods for Common Materials. Let us consider primarily systems that are dispersible, as these present the greatest processability, depth of experience, and significant environmental exposure. Carbon nanotubes (CNTs) and gold nanoparticles have unique features illustrating the deviation from the bulk and the need for wider basic characterization in their study, manufacture, and application. They are major systems that have been heavily characterized and demonstrate, individually, aspects that need docu-
NANO FOCUS
A potential effect of
assume purity without demonstrating it. This disconnect arises because of the time costs associated with sensitive survey characterization and requires attention as conflicting results accumulate in the literature.23–25 Well-Characterized Materials. Naturally, it is convenient to call for greater characterization standards, but the problem is at least as complex as the materials. In bulk and molecular chemistry, most materials can be described with mass and elemental composition as they relate to structure to give all manner of properties. Structure, as a function of elemental composition and phase, combines well with mass for population-level behavior. With just a few measured variables, whether a material is “normal” becomes reasonably predictable.
Figure 2. Ideal nanoparticles are highly complex systems composed of core, shells, dynamic shells, ligands, ligand functional groups, surface charge, surface adsorbates, and structural geometry (i.e., aspect ratio for rod types). Real materials include far more species: side products, decomposition products, extra ligands, reactants, catalysts, and salts. Most are not tracked in the literature. VOL. 3 ▪ NO. 9 ▪ 2441–2446 ▪ 2009
2443
NANO FOCUS 2444
mentation for the development of future materials. Globally, electron microscopy is a standard for examining these materials. The high-resolution capability provides excellent insight, but TEM is limited when it comes to low-Z matter, especially for small-molecule adsorbates such as ligands or other uncrystallized surface matter. Additional characterization methods need to be applied, though the best ones can confirm properties like size while supplying additional insight like optical absorbance. Carbon nanotubes have captured massive attention due to their combination of electronic and mechanical properties.27–29 Applications range from reinforced composite materials to circuitry and sensors. Most production methods consist of heating a carbon source in the presence of a catalyst or host structure like the HiPco process.30 The product soot contains a great deal of extra material. There are various modes of cleaning arising in the literature to remove the catalysts and to destroy the side products,31,33 but these practices are neither efficient nor widespread.9,21,24 Because of the nanotube aspect ratio, the challenge to processing for study or application consists of preventing aggregation due to van der Waals forces and suspending them separately. From a nanoEHS perspective, the damage the tubes can do has been correlated largely with aggregation and catalyst content, though there are also concerns about the Trojan horse effect with physisorbed contaminants.26,32 So, how can one tell which tubes one has, before inserting them into a system? Labels reporting carbon purity are hardly illuminating. Basic determination of a CNT batch requires measurements of size, shape, distribution, conductivity, and contaminants. Raman infrared (IR) spectroscopy34 has been effectively used to determine CNT diameters but indicate little as to contaminants or aggregation. Similarly, examination by TEM is useful in determining size, aggregation, and catalyst remnants, but no adsorbates. As bundling affects the optical and surface properties, this is critical to standardize.22 Finding the adsorbed contaminants requires additional mea-
surements, including Fourier transform infrared (FT-IR), nuclear magnetic resonance (NMR), matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS), time-of-flight secondary ionization mass spectrometry (TOFSIMS), and X-ray photoelectron spectroscopy (XPS). Chemical catalogs, both large and small,5–7 give only limited characterization; some have TEM and energy-dispersive X-ray spectroscopy (EDX) data, some have only TEM data, others include Raman or IR spectra, and still others have only MSDS with “Not Determined” listed for many properties. Verifying claims of purity is thus up to the customers, many of whom are ill equipped to do so. As with carbon nanotubes, gold nanoparticles have found utility for their tunable optical properties, range of sizes, and rich ligand chemistry in applications including catalysts, electronics, photonics, and sensors.35–37 Therapeutically, the size, shape, ligand, and optical properties have been exploited for light-to-heat conversion in targeted tumor applications.38 This use is dependent upon the particles being welldefined and characterized with controlled history and purity. For a sophisticated system, dispersity or variance from an ideal specification can mean more than just application failure. Variation in the size, shape, and shell composition may alter optical properties, bioactivity, and the ability to pass through membranes. The wrong ligands or charge can result in interactions with charged membranes39 or protein coronas.40 Extra reactants or decomposition products can cloud interpretation of results and have their own side effects. Product literature typically delivers only the solubility, size range, and concentration, inductively coupled plasma mass spectrometry (ICP-MS) for gold, and nominal ligand.5 More thorough characterization requires the use of multiple complementary analytical techniques (Table 1). Verifying and expanding this information can require extensive capabilities and multiple separate measurements. Many techniques in Table 1 have some overlap, but most leave out critical information. Typically, only a fraction
VOL. 3 ▪ NO. 9 ▪ RICHMAN AND HUTCHISON
of these techniques is accessible or usable. While multiple techniques are required for characterization, complete execution slows or limits progress. For gold nanoparticles, a reduced set has been found to be reliable when combined with purification: 1H NMR to identify ligands and gross impurities;41 UV⫺vis spectroscopy can be used to verify the optical properties and estimate sizes from the plasmon spectral shifts; TEM/EDX can be used to determine geometry, core size, and elemental composition. While size and shape can be determined in a number of ways, methods often have different sensitivities to nanostructure features. To confuse the matter, some techniques include the organic ligand radius, others only measure the high-Z or crystalline core. Many of these methods are applied in ultrahigh vacuum, using electron beams leading to slow sampling rates. Of the solution-state experiments, sensitivity to low-count, large-radius species tends to disrupt the measurement if care is not taken to ensure purity. To deal with complex interferences generated by sample preparation, multiple simultaneous measurements are needed. As a step in the right direction, researchers and equipment manufacturers are integrating multiple complementary probes in single instrumental platforms. Typical pairs include electron and optical detectors for structure and chemical composition, ion and electron beams for sample preparation and observation, scanning probe and optical detectors for topography and chemical properties. The microscale legacy punctuates these early pairsOmany electron imaging instruments include EDX for in situ, simultaneous elemental analysis. While helpful, the sampling depth is more than an order of magnitude greater than the nanoscale regime, exaggerating substrate interferences. This slows analysis as cross-checking remains necessary. More detail is needed on the scale of the interfaces driving the effects in nanomaterials. These details are available in other measurements such as XPS and NMR that are nearly blind to nanoscale structure. XPS delivers excellent elwww.acsnano.org
experiment vs information
size
TEM SEM AFM UVⴚvisⴚIR
bulk to ⬍1 nm bulk to ⬃2 nm bulk to ⬃2 nm varies, nanoscale via material dependent absorption; sensitive to aggregation ⫺ indirect determination by density distribution ⫺ surface area 10⫺3000 nm sensitive to aggregation bulk to 1 nm 1⫺100 nm
H NMR XPS TGA BET DLS XRD SAXS
organic/inorganic hybrid structures
organic impurities
via EDX/EELS via EDX ⫺ limited to IR fingerprint matching
poor contrast poor contrast intermediate contrast functional groups
no no yes ⫺
UHV UHV interface solution
fingerprint matching elemental and chemical state via mass spectroscopy ⫺ ⫺ lattice parameter ⫺
functional groups quantitative core⫺shell mass ratio
yes yes ⫺ yes ⫺ ⫺ ⫺
solution UHV solid solid solution solid solid or solution
chemical ID
crystal only intermediate contrast
sample state
a
Hybrid structures are those with a significant organic and inorganic structure that need differentiation. Organic impurities are low Z small molecules that need detection or purification. Sample state is the necessary condition for measurement. No experiment captures the entire description of the particle, and many aspects require more than one experiment. The highlighted techniques are an example of a minimum characterization set for ligand-coated gold nanoparticles.
emental and chemical state information. It can be used to extract nanostructure from peak shape, though it gives an incomplete, statistics-driven picture.42 NMR delivers detailed bonding information via finger printing, The width of the peaks can detect ligand attachment to particles via a loss of signal and peak broadening due to diminished degrees of freedom. Nothing though is determined for the rest of the structure, and even the chemical information relies on foreknowledge. Directly coupling either of these measurements to a nanoscale probe gives a far more sophisticated materials measurement. Certainly, one way to address the throughput problem is development of more multiaspect instruments that can deal simultaneously with a single sample using as many probes as possible with as few assumptions as possible. OUTLOOK: BEYOND THE TOOLS The complexity of nanomaterial systems is the driving force for commercial, research, and regulatory interest. That interest can only be served with changes in the approaches to characterization. Assembling sufficient capabilities is a daunting task. Opportunities exist in facilitating the operation of so many tools. Addressing the throughput problem will mean speeding up critical characterization tools and engineering their usability for a wider audience. www.acsnano.org
Beyond just the tools, there are the usages: bridges between disciplines need to be strengthened. Physical chemistry property analyses require biological techniques in sample preparation, such as diafiltration for purity and cryogenic sample preparation for inorganic systems to preserve solution-state distributions. Analytical chemistry needs to be applied in preparation for toxicology assays: verification of purity, structure, and composition before testing. Potentially, this crossover would be more easily managed in user facilities that promote collaboration and communication, especially with commercial users. While intellectual property should be protected, basic interests can be shared as expertise becomes best practice. Higher complexity is coming faster than regulatory bodies can keep up. For the moment, the public belief is that “nano is good”. Maintaining the public trust benefits both research and business. However, without strong, clear evidence, the public will make up their own mind based upon social rather than physical data. We need methods of characterization that are fast, facile, and formal to preserve the public trust and to maximize the future utility of nanomaterials. Acknowledgment. The authors would like to thank Air Force Research Laboratory (under agreement number FA8650-05-1-5041) for support of this work. This Nano Focus article
NANO FOCUS
TABLE 1. Nanoparticle Characterization Experiment vs Sensitivitya
For the moment, the public belief is that “nano is good”. is based in part on a lecture by J.E.H. that was given as part of The Kavli Foundation ACS Presidential Plenary Symposium on “Challenges in Nanoscience” at the 237th ACS National Meeting held in Salt Lake City, UT, March 22⫺26, 2009.
REFERENCES AND NOTES 1. Nath, N.; Chilkoti, A. A Colorimetric Gold Nanoparticle Sensor to Interrogate Biomolecular Interactions in Real Time on a Surface. Anal. Chem. 2002, 74, 504– 509. 2. Qi, P.; Vermesh, O.; Grecu, M.; Javey, A.; Wang, Q.; Dai, H.; Peng, S.; Cho, K. J. Toward Large Arrays of Multiplex Functionalized Carbon Nanotube Sensors for Highly Sensitive and Selective Molecular Detection. Nano Lett. 2003, 3, 347–35. 3. Ferrari, M. Cancer Nanotechnology: Opportunities and Challenges. Nat. Rev. Cancer 2005, 5, 161–171. 4. Snyder, M. A.; Tsapatsis, M. Hierarchical Nanomanufacturing: From Shaped Nanoparticles to High-Performance Separation Membranes. Angew. Chem., Int. Ed. 2007, 46, 7560–7573. 5. NanomaterialsOPolyhedral Silsesquioxanes and Polymers, Single and Multi-Walled Nanotubes; http://www.sigmaaldrich.com/ materials-science/nanomaterials.html (accessed June 2009). 6. Cheaptubes.com, the Source for Carbon Nanotubes Home Page; http://www.cheaptubesinc.com (accessed June 2009).
VOL. 3 ▪ NO. 9 ▪ 2441–2446 ▪ 2009
2445
NANO FOCUS 2446
7. American Elements; http://www. americanelements.com (accessed June 2009). 8. Meliorum Technologies, Inc., Silicon Nanomaterial; http://www. meliorum.com/silicon.htm (accessed June 2009). 9. Guo, L.; Morris, D. G.; Liu, X.; Vaslet, C.; Hurt, R. H.; Kane, A. B. Iron Bioavailability and Redox Activity in Diverse Carbon Nanotube Samples. Chem. Mater. 2007, 19, 3472–3478. 10. Nanotechnology Environmental and Health Implications Working Group. Strategy for Nanotechnology-Related Environmental, Health, and Safety Research, February 2008. National Nanotechnology Initiative Web Site; http://www.nano.gov/NNI_EHS_ Research_Strategy.pdf (accessed June 2009). 11. EPA Office of Research and Development. Draft Nanomaterial Research Strategy (NRS), January 24, 2008. U.S. Environmental Protection Agency Web Site; http://epa.gov/ncer/ nano/publications/nano_strategy_ 012408.pdf (accessed June 2009). 12. Meng, H.; Xia, T.; George, S.; Nel, A. E. A Predictive Toxicological Paradigm for the Safety Assessment of Nanomaterials. ACS Nano 2009, 3, 1620–1627. 13. Hutchison, J. E. Greener Nanoscience: A Proactive Approach to Advancing Applications and Reducing Implications of Nanotechnology. ACS Nano 2008, 2, 395–402. 14. Dupont on Teflon; Teflon and Toxicity; http://www2.dupont.com/Teflon/en_US/ products/safety/index.html (accessed June 2009). 15. Self Help Alternative Medicine Advice on Teflon; http://www. tuberose.com/Teflon.html (accessed June 2009). 16. Gross, L. A Broken Trust: Lessons from the Vaccine⫺Autism Wars. PLoS Biol. 2009, 7, 1–7. 17. Sjoberg, L. Genetically Modified Food in the Eyes of the Public and Experts. Risk Manage. 2008, 10, 168–193. 18. Siegrist, M.; Keller, C.; Kastenholz, H.; Frey, S.; Wiek, A. Laypeople’s and Expert’s Perception of Nanotechnology Hazards. Risk Anal. 2007, 27, 59–69. 19. Frewer, L. J.; Miles, S.; Marsh, R. The Media and Genetically Modified Foods: In Support of Social Amplification of Risk. Risk Anal. 2002, 22, 701–711. 20. Cao, G. Nanostructures and Nanomaterials: Synthesis, Properties, and Applications; World Scientific: Singapore, 2004. 21. Hurt, R.; Monthioux, M.; Kane, A. Toxicology of Carbon Nanomaterials: Status, Trends, and Perspectives on the Special Issue. Carbon 2006, 44, 1028–1033. 22. O’Connell, M. J.; Bachilo, S. M.; Huffman, C. B.; Moore, V. C.; Strano, M. S.; Haroz, E. H.; Rialon, K. L.; Boul, P. J.; Noon, W. H.; Kittrell, C. Band Gap Fluorescence from Individual Single Walled Carbon Nanotubes. Science 2002, 297, 593–596.
23. Nel, A.; Madler, L.; Velegol, D.; Xia, T.; Hoek, E. M. V.; Somasundaran, P.; Klaessig, F.; Castranova, V.; Thompson, M. Understanding Biophysicochemical Interactions at the Nano-Bio Interface. Nat. Mater. 2009, 8, 543–557. 24. Nakamura, E.; Isobe, H. Functionalized Fullerenes in Water. The First 10 Years of Their Chemistry, Biology, and Nanoscience. Acc. Chem. Res. 2003, 36, 807–815. 25. Bosi, S.; Feruglio, L.; Da Ros, T.; Spalluto, G.; Gregoretti, B.; Terdoslavich, M.; Decorti, G.; Passamonti, S.; Moro, S.; Prato, M. Hemolytic Effects of WaterSoluble Fullerene Derivatives. J. Med. Chem. 2004, 47, 6711–6715. 26. Helland, A.; Wick, P.; Koehler, A.; Schmid, K.; Som, C. Reviewing the Environmental and Human Health Knowledge Base of Carbon Nanotubes. Environ. Health Perspect. 2007, 115, 1125–1131. 27. Thorstenson, E. T.; Ren, Z.; Chou, T.-W. Advances in the Science and Technology of Carbon Nanotubes and Their Composites: A Review. Compos. Sci. Technol. 2001, 61, 1899–1912. 28. Hurt, R. H.; Monthioux, M.; Kane, A. Toxicology of Carbon Nanomaterials: Status, Trends, and Perspectives on the Issue. Carbon 2006, 44, 1028–1033. 29. Wang, J. Carbon-Nanotube Based Electrochemical Biosensors: A Review. Electroanalysis 2005, 17, 7–14. 30. Bronikowski, M. J.; Willis, P. A.; Colbert, D. T.; Smith, K. A.; Smalley, R. E. GasPhase Production of Carbon SingleWalled Nanotubes from Carbon Monoxide via the HiPco Process: A Parametric Study. J. Vac. Sci. Technol., A 2001, 19, 1800–1805. 31. Hou, P.-X.; Liu, C.; Cheng, H.-M. Purification of Carbon Nanotubes. Carbon 2008, 46, 2003–2025. 32. Elgrabli, D.; Abella-Gallart, S.; Robidel, F.; Rogerieux, F.; Boczkowski, J.; Lacroix, G. Induction of Apoptosis and Absence of Inflammation in Rat Lung after Intratracheal Instillation of Multiwalled Carbon Nanotubes. Toxicology 2008, 253, 131–136. 33. Porro, S.; Musso, S.; Vinante, M.; Vanzetti, L.; Anderle, M.; Trotta, F.; Tagliaferro, A. Purification of Carbon Nanotubes Grown by Thermal CVD. Phys. E 2007, 37, 58–61. 34. Dresselhaus, M. S.; Dresselhaus, G.; Jorio, A. Raman Spectroscopy of Carbon Nanotubes in 1997 and 2007. J. Phys. Chem. C 2007, 111, 17887–17893. 35. Mohr, C.; Hofmeister, H.; Radnik, J.; Claus, P. Identification of Active Sites in GoldCatalyzed Hydrogenation of Acrolein. J. Am. Chem. Soc. 2003, 125, 1905–1911. 36. Maier, S. A.; Brongersma, M. L.; Kik, P. G.; Meltzer, S.; Requicha, A. A. G.; Koel, B. E.; Atwater, H. A. PlasmonicsOA Route to Nanoscale Optical Devices. Adv. Mater. 2001, 13, 1501–1505. 37. Willner, I.; Willner, B. Functional Nanoparticle Architectures for Sensoric, Optoelectronic, and Bioelectronic Applications. Pure. Appl. Chem. 2002, 74, 1773–1783.
VOL. 3 ▪ NO. 9 ▪ RICHMAN AND HUTCHISON
38. Huang, X. H.; Jain, P. K.; El-Sayed, I. H.; ElSayed, M. A. Plasmonic Photothermal Therapy (PPTT) Using Gold Nanoparticles. Lasers Med. Sci. 2008, 23, 217–228. 39. Goodman, C. M.; McCusker, C. D.; Yilmaz, T.; Rotello, V. M. Toxicity of Gold Nanoparticles Functionalized with Cationic and Anionic Side Chains. Bioconjugate Chem. 2004, 15, 897–900. 40. Eck, D.; Helm, C. A. Plasmon Resonance Measurements of the Adsorption Kinetics of a Biopolymer onto Gold Nanocolloids. Langmuir 2001, 17, 957– 960. 41. Sweeney, S. F.; Woehrle, G. H.; Hutchison, J. E. Rapid Purification and Size Separation of Gold Nanoparticles via Diafiltration. J. Am. Chem. Soc. 2006, 128, 3190–3197. 42. Tougaard, S. Accuracy of the NonDestructive Surface Nanostructure Quantification Technique Based on Analysis of the XPS or AES Peak Shape. Surf. Interface Anal. 1998, 26, 249–269.
www.acsnano.org
