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Bunker et al: Integrating Nanotechnology into the Life Sciences: Lessons Learned 1583

Review Article

Integrating Nanotechnology into the Life Sciences: Lessons Learned

K.L. Bunker*, Julianne Wolfe and Linxian Wu RJ Lee Group, Inc., Monroeville, PA, USA.

Received January 20, 2012; accepted March 22, 2012 ABSTRACT

As nanomaterials are more frequently incorporated into the life science industry, the need to thoroughly understand their functionality becomes paramount. This review article will provide insight and lessons learned from numerous nanomaterial characterization projects where sample properties were evaluated to better understand various attributes that contribute to functionality. The lessons address a broad spectrum of topics ranging from sample preparation to the rapidly evolving regulatory landscape. Many of the hurdles encountered in maturing a product involving nanotechnology stem from navigating this regulatory landscape. There is a lack of standardization within the nanotechnology community including government agencies, industry, and academia. As a

result, there are a number of important issues to address, most notably the issue of nanotechnology safety. There are other areas that also emerge as significant challenges in nanotechnology integration: appropriate quality control measures, sample preparation and analysis selection and using nanomaterial characterization in improving products and processes throughout the product lifecycle. Specific examples are used to illustrate these challenges and provide insight to their corresponding solutions. Through these shared experiences, a broader picture emerges of what is entailed in resolving the analytical challenges of nanotechnology and life science integration, the likes of which can be translated to numerous other situations both current and prospective.

KEYWORDS: Nanotechnology; nanomedicine; nanopharmaceuticals; nanomaterials; nanocharacterization; life sciences; electron microscopy; nanoparticles; standards; quality by design.

Introduction Nanotechnology, the technology that involves

imaging, measuring, modeling and manipulating materials at dimensions between approximately 1 and 100 nanometers (nm) (NNI, 2006), is profoundly impacting human life. According to a nanotechnology market research report (Cientifica, 2007), the general nanotechnology global market in 2012 will be $263 billion, and will reach $1.5 trillion by 2015. In a more recent report, the market potential is estimated as $1.1 trillion by 2010-2015, and will reach $3.0 trillion by 2020 (Roco, 2005; 2011). Even more significant, this rapid growth will dominantly come from the pharmaceutical and healthcare sectors (life science), increasing from 15% in 2010 to 50% by 2015 (Roco, 2011). This estimated growth in the pharmaceutical and healthcare sectors appears to be supported by a published global survey (Wagner et al., 2006). Accordingly, by year 2006, there were already 38 commercial medical products on the

market, generating revenues of $6.8 billion. The world rate of increase in nanotechnology enabled products is projected to increase 25% annually (Roco, 2011). Those medical products ranged from drug delivery, in vivo imaging, and in vitro diagnostics, to therapeutics (Wagner et al., 2006). One of the most significant breakthroughs in recent years is the theranostic application of plasmonic nanoprobes for diagnosing and treating prostate cancer (Lukianova-Hleb et al., 2011). The potential application of the plasmonic nanoprobes in humans could possibly revolutionize the field of cancer therapy by incorporating diagnosis, treatment, and outcome reporting in one regimen. The early successes of such applications will undoubtedly generate both significant clinical and commercial interests (Jain, 2005; Marchant, 2009; Hu et al., 2011). In 2006, approximately 150 small to medium size companies engaged in nanomedicine research and development (Wagner et al., 2006); the number has more than doubled to over 350 in

International Journal of Pharmaceutical Sciences and Nanotechnology

Volume 5 • Issue 1 • April – June 2012MS ID: IJPSN-01-20-12-BUNKER

ABBREVIATIONS: CNT: carbon nanotube; EDS: energy dispersive X-ray spectroscopy; EPA: Environmental Protection Agency; FDA: Food and Drug Administration; FESEM: field emission scanning electron microscopy; FIFRA: Federal Insecticide, Fungicide and Rodenticide Act; ISO: International Organization for Standards; MSDS: materials safety and data sheet; NIST: National Institute of Standards and Technology; NIOSH: National Institute for Occupational Safety and Health; NSF: National Science Foundation; NNI: National Nanotechnology Initiative; PMN: premanufacture notice; POCT: point-of-care testing; QbD: quality by design; REL: recommended exposure limit; SEM: scanning electron microscopy; SRM: standard reference material; STEM: scanning transmission electron microscopy; TEM: transmission electron microscopy.

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2012 (Nanobio and Nanomedicine Companies listed on Nanowerk, January 2012). Conceivably, such a number will continue to climb due to the significant potential and attractiveness of the life science market.

While considerable investment and R&D activities are being observed in the application of nanotechnology in the life sciences, concerns regarding fundamental characteristics, behaviors, and potential associated toxicities continue to surface (Pautler and Brenner, 2010; Marchant, 2009; Sargent et al., 2009; Sanhai et al., 2008; Schneider, 2010a). One example is the therapeutic potential of nanoparticles to cross over the blood brain barrier, enabling diagnosis and treatment of various central nervous system diseases (Karanth and Murthy, 2008). While the prospect is clinically promising, the uncertainties of the fate of the nanoparticles dispersed in the human body demands clear understanding of the physicochemical properties, destination effects, and safeties of the nanomaterials (Hansen, 2007; Poland et al., 2008; Sanhai et al., 2008; Pautler and Brenner, 2010; Stone et al., 2010). In searching for the optimal mechanisms for nanomaterials characterization and standardization, a recent report highlighted analysis and comparison of some commercially available nanomaterials with their materials safety data sheets (MSDS) (Park and Grassian, 2010). The authors concluded that independent characterization of nanomaterials is a necessity because marked differences occurred between the MSDS and their analyses (Park and Grassian, 2010). These finding further echo the need to establish reference materials and consensus testing protocols for nanomaterials (Sanhai et al., 2008; Park and Grassian, 2010; Stone et al., 2010).

Nanotechnology for Today Nanomaterials have been used for hundreds of years

as evidenced by the presence of gold nanoparticles in medieval stained glass windows (Jembrih-Simburger et al., 2002; Schalm et al., 2009). Just over the past decade however, interest in the use of nanomaterials has grown enormously due to their wide range of applications (Schneider, 2010b). As of March 2011, the Project for Emerging Nanotechnologies has identified over 1,300 manufacturer-identified, nanotechnology-enabled products that have entered the commercial marketplace around the world (Suppan, 2011).

As discussed in the introduction, these materials have traditionally been defined as having at least one dimension between 1 and 100 nm (NNI, 2006). Because of the aforementioned behavioral and toxicity concerns, this traditional thought is now being challenged, a challenge that stems mainly from advancements in analytical characterization and manufacturing (Maynard, 2011; Bawa, 2011).

Advances in electron microscopy, atomic force microscopy, scanning tunneling microscopy, and other analytical techniques have given us the ability to see (or visualize) nanomaterials and further study the

attributes that generate their specific, desired qualities (Maynard, 2006a; Fender, 2008). This ability brings with it the responsibility to understand and scientifically support the functional properties leading to performance. Advances in manufacturing have provided the capability to engineer materials for specific needs (Fender, 2008), and thus the diversity and quantity of materials being studied has greatly increased. Without understanding the function and environmental impact of these materials, we may unknowingly subject populations to potentially harmful substances (Maynard, 2006b; Ramachandran et al., 2011; Schneider, 2010c; Casuccio et al., 2009a; 2009b; 2010; Methner et al., 2010a; 2010b; Schulte et al., 2008). Finally, the link between information availability and public opinion cannot be overlooked. For example, a lack of safety information about nuclear power and genetically modified foods made them easy targets for public resistance (Satterfield et al., 2009; Schneider, 2010d). By understanding the implications and functions of nanomaterials, the scientific community can more confidently make public education a priority.

A complete understanding of nanomaterials is a distant goal. However, through the work that has been done, we have already learned numerous and valuable lessons. First and foremost, navigating the regulatory landscape and confronting environmental health and safety issues are paramount in the application of nanotechnology in life sciences. In our efforts to assist manufacturers as they integrate nanomaterials into next-generation products, we have identified a number of broad categories where potential difficulties exist. Awareness of these challenges will aid in a more safe and rapid integration of nanomaterials in life science industries. These include:

• Standardization: the impact of lacking standard reference materials and protocols

• Safety and Regulations: discrepancies with respect to the safety of nanomaterials and the lack of regulations

• Quality Control: manufacturing challenges and the accuracy of manufacturer supplied information

• Sample Preparation: complexities of optimizing sample preparation for accurate materials characterization

• Improving Product and Process: evaluating materials at different stages of the product lifecycle

Navigating the Regulatory Landscape Perhaps some of the biggest lessons to be learned are

those that pertain not to a specific product type, but to the entire scientific community. Regulatory issues are rooted in the lack of standard reference materials, standard protocols, and collaboration efforts. Risks associated with use, such as toxicity and environmental impact, also create conflict within the industry.


Due to advanced manufacturing and safety concerns, many agencies are looking to refine the traditional definition of nanotechnology (Maynard, 2006b; 2011; Bawa, 2011). As applied to the life sciences, we can observe how the Food and Drug Administration (FDA) defines nanoscale in new guidance released in June 2011 (FDA, 2011). The purpose of this guidance is to assist manufacturers in determining if their product incorporates nanotechnology. The FDA’s definition begins with a traditional size designation of materials in the range of 1-100 nm. However, additional points made in the guidance reflect the inadequacies of basing the decision on size alone and address using material attributes for classification. The need for this additional guidance stems from controversy amongst industry, academia, and government in recognizing exactly what constitutes a nanomaterial (Maynard, 2011; Bawa, 2011). Consequently, similar products can be regarded as nanomaterials by some and not by others.

There is also argument that nanoscale materials are not novel since their macro counterparts are well established and characterized (Bawa, 2011; US EPA, 2008a). Therefore, new characterization and/or regulation are not warranted. The tendency for nanomaterials to aggregate or agglomerate may also cause confusion for manufacturers as to what is really considered nanoscale (ICCR, 2004; Hartung, 2010). The tendency for nanomaterials to aggregate or agglomerate pushes some nanomaterials beyond the traditional size definition even though their functionality may still be linked to the primary particle size of the material. These questions and discrepancies in the way traditional definitions are applied further demonstrate how the definition of a nanomaterial is a very gray area. Some, including the US Executive Office of the President, are now postulating that a definition should not even exist and that determination of a novel material be based on a set of attributes or qualities (Maynard, 2011; Holdren et al., 2011).

Standardization The need for standard reference materials (SRMs)

and standard protocols for the characterization of nanomaterials is significant (Sanhai et al., 2008; Park and Grassian, 2010; Stone et al., 2010), particularly in industries which depend on validated systems. By establishing standard protocols and implementing validation, the scientific community can make more appropriate data comparisons which will foster science-based regulation.

However, this task will not be easily implemented due to the wide variety of nanomaterials being produced. For SRMs, universal standards appropriate to qualify every type of nanomaterial will be difficult to create because material attributes are so diverse. Furthermore, multiple techniques are often used for adequate characterization. A standard, suitable for evaluation on a number of different instrumentation platforms, or a suite of standards that could be used as a grouping, would be required to qualify assorted attributes. The

application, scope, and cost of these standards must be taken into consideration so that they are realistically attainable for firms to use, which may pose significant challenges given a particular standard.

Organizations such as the International Organization for Standards (ISO) and ASTM International are now actively working towards standardization (Maynard, 2006b). In the bio-medical research community, the first nano-reference material was issued in 2008 as a combined effort between National Institute for Standards and Technology (NIST) and the National Cancer Institute (NIST, 2008). These gold nanoparticle reference materials are designed for laboratories studying the biological effects of nanoparticles. The three standards are nominally 10 nm, 30 nm, and 60 nm in diameter. In December 2011, NIST issued the first standard reference material for single-walled carbon nanotubes (CNTs). The material provides laboratories with a homogeneous sample of CNTs for use in chemical and toxicity analyses (ACS, 2012). Current efforts seek to develop nanoscale titanium dioxide and silver SRMs to assess the potential health risks and biological interactions associated with engineered nanomaterials (Cook and Kaiser, 2011). The creation of these SRMs will be a positive step forward for standardization.

Often, agencies disperse conflicting information among the scientific community, resulting in further complication of the standardization effort. At the highest level, we see a lack of agreement in the definition of a nanomaterial across the industry as previously mentioned (Roco, 2007). Evidence of conflict also exists within individual organizations. The FDA, for example, demonstrates contradictory thinking about the safety of nanomaterials depending not on the material itself, but where it is used. Pharmaceuticals that incorporate nanomaterials receive more scrutiny than dietary supplements or food products (Schneider 2010a; 2010c; 2010e) even though they may contain the same nanomaterial. The similarities between these products (i.e. they are taken internally and for the prevention or treatment of a condition) warrant they be regarded with the same caution.

Safety Considerations Human exposure to nanoparticles is an evolving area

of understanding. The latest Nanotechnology Task Force Report published by the FDA in 2007, establishes that “current science” does not support products incorporating nanoscale materials to be of greater safety concern than those without (FDA, 2007). However, a report in 2009 by the National Institute for Occupational Safety and Health (NIOSH) indicates that there is experimentally proven risk from exposure to nanomaterials and that research is needed to further understand their hazard potential (NIOSH, 2009). Here we have two well-known entities that seem to contradict each other. The FDA supports its position by stating that products will be safe even without new guidance or more strict nanomaterial regulation as they must receive


premarket approval (FDA 2007; Bawa, 2011). With this system, however, there still lies an opportunity for data from macro counterparts or similar nanomaterials to support approval. While there is a lack of regulations related to the safety of nanomaterials, there are guidance documents available from a variety of organizations and agencies (NIOSH, 2009, 2011; Technische Universitat Dresden, 2011; NRC, 2011; Anna, 2011).

Regulations As mentioned, the FDA issued a guidance document

in June 2011. In June 2011, the US Environmental Protection Agency (EPA) also issued draft guidelines for nanomaterials under the Federal Insecticide, Fungicide and Rodenticide Act (FIFRA). FIFRA’s guidelines are related to determining when a nanomaterial should be considered new, even if the macro counterparts are approved (US EPA, 2011a). In May of 2011, NIOSH finalized a Current Intelligence Bulletin on recommended exposure limits (REL) for titanium dioxide (TiO2). NIOSH recommends airborne exposure limits of 2.4 mg/m3 for fine TiO2 (100 nm-3 microns) and 0.3 mg/m3 for ultrafine TiO2 (< 100 nm) (NIOSH, 2011). This is the first time that different RELs have been recommended for the same substance based on size fractions. Through promulgation of these guidelines, the EPA and NIOSH have recognized that nanomaterials do in fact differ from their macro counterparts.

The EPA appears to be leading the way in terms of designating nanomaterial regulation. Previously in 2008, the EPA announced that CNTs are considered novel and are subject to premanufacture notice (PMN) requirements for new chemicals (EPA, 2008b). The Final Rules regarding CNTs were published in May 2011 (EPA, 2011b). This may become important to the life science industry as there is significant research being performed with CNTs for biomedical applications such as drug delivery (Liu et al., 2008; Bianco et al., 2005). The PMN process requires a full characterization of the product using a multidisciplinary approach as discussed earlier where no historical data is relied upon. This requirement ensures that there is accurate data to reflect the nature of the product under scrutiny. The requirement also provides confirmatory analyses through a multidisciplinary approach so that manufacture supplied information is more accurate. In addition to product attribute characterization, some companies are being asked to perform environmental release testing such as a dustiness test. This test provides information about the propensity of the material to produce airborne dust. Interestingly enough, the dustiness test has been used in the pharmaceutical industry for years to evaluate the potential of high potency drugs to become airborne causing a hazardous situation (Boundy et al., 2006).

In the life sciences, the need to develop a risk-based approach for product quality has become increasingly prevalent with the advent of Quality by Design (QbD) (ICH, 2009). Adverse effects to the patient have received

the most attention because they are believed to be the highest risk. However, immediate and substantial risk lies with current manufacturing staff and next generation scientists (Peters et al., 2008; Schulte et al., 2008; Casuccio et al. 2009a; 2009b; 2010; Methner et al., 2010a; 2010b; Ramachandran et al., 2011). These individuals work around nanomaterials every day long before any product is supplied to patients. Industry must be responsible for the safety of the workers and it must be held accountable if the safety data is found to be inadequate or scientifically unsound.

Quality Control One of the greatest issues concerning nanotechnology

revolves around the quality control of nanomaterials and the products in which they are utilized. Because of the multitude of applications in drug delivery systems, diagnostics, or as raw materials (Patel et al., 2008), nanoparticles are of great utility and exemplify well the need for adequate quality control. Unique approaches for enhancing product quality driven by the individual need of the manufacturer are illustrated using gold, silver, and titanium dioxide nanoparticle examples.

End User Information This example encompasses a manufacturer that

wanted to confirm the output of its process design to supply accurate information to end users. Two types of gold nanoparticle products were evaluated: rods and spheres. For each, the manufacturer was interested in knowing the approximate size and morphology to ensure the process was producing the intended result. Figure 1 shows a secondary electron scanning electron microscopy (SEM) image of the rods while Figures 2 and 3 show secondary electron images of the spheres. From these images, the anticipated morphology and size of each particle type are confirmed. It is noted that one particle in Figure 1 does appear to be spherical rather than rod shaped, i.e., mixed morphologies. It is also noted that there is a size distribution of the gold nanoparticles in Figure 3. To evaluate the significance of these observations, quality control experiments can be designed and the data analyzed in conjunction with performance data. Sample preparation and characterization protocols can be established to evaluate a statistically relevant population of particles and designate whether the product meets or falls out of specification. A particle based SEM analysis coupled with energy dispersive X-ray spectroscopy (EDS) characterization can yield information regarding various parameters such as size, shape, agglomeration/ aggregation tendencies, and elemental composition as added value over traditional techniques (such as dynamic light scattering) that usually only provide a size distribution of particles. By integrating these other parameters (e.g. shape, agglomeration/aggregation tendencies and elemental composition), a more comprehensive characterization of the material occurs that can be passed on to end users.


Fig. 1. A secondary electron image of gold nanorods that are approximately 20 nm in width and 50 nm in length.

Fig. 2. A secondary electron image of gold nanoparticles that are approximately 50 nm in diameter.

Fig. 3. A bright-field STEM image of gold nanoparticles with an average diameter of approximately 3.0 nm.

Manufacturer Supplied Information Manufacturer evaluation of a proposed raw material is

the scope of this example. A spherical nanosilver product in

a certain size range was identified by the manufacturer. This manufacturer felt further investigation of the material was warranted due to some discrepancies between the product specification sheet (which indicated a size range of 20-40 nm) and the MSDS (which indicated a size range of 20-100 nm). Figure 4 shows a secondary electron image of the nanosilver product in which mixed morphologies can be observed. Furthermore, by comparison to the size bar on the image, it is noted that some of these particles exceed the size specifications in both the specification sheet and the MSDS of the material. This analysis is in contrast to the data depicted on the specification sheet which displayed particles that were all nearly spherical and in the indicated size range of 20-40 nm. This is a very important lesson when dealing with purchased nanomaterials in that the information supplied by the manufacturer may not be accurate. Nanomaterials must continually be checked against their specification (Park and Grassian, 2010; Ramachandran et al., 2011; Hansen et al., 2007). This discrepancy is directly tied to the need for more independent characterization of commercial nanomaterials mentioned earlier (Park and Grassian, 2010).

Fig. 4. A secondary electron image of silver nanoparticles showing a variety of morphologies, including round and angular particles measuring between 10-150 nm. The sample also contains cylindrical particles measuring approximately 50 nm in width and up to >500 nm in length.

Manufacturing Difficulties The consistent manufacture of nanomaterials can be

a daunting task. In this example, two samples of nanoscale titanium dioxide, 5 nm and 7 nm, were analyzed to confirm the particle size. A secondary electron image of the 5 nm sample deposited onto a lacey carbon substrate supported by a TEM grid is shown in Figure 5. What is immediately noticeable is that the material is deposited across an area of approximately 20 microns. At this magnification, individual particles in the 5 nm range will not be visible. Upon closer examination (Figure 6A), it is apparent that the titanium dioxide particles are assembling themselves into larger clumps. As mentioned previously, nanomaterials have a tendency to aggregate (held together by stronger, more irreversible forces) or


agglomerate (held together by weaker forces and more easily reversible) (ASTM, 2006). Whether a mass is an agglomerate or aggregate may affect how the material functions in a finished product (Peters and Grassian, 2010). For example, surface area attributes have been found to impact the functionality of nanomaterials (Peters and Grassian, 2010). In a similar sized mass, aggregates will exhibit less surface area than agglomerates because agglomerates tend to exhibit surface area similar to the sum of the separated particles, in general (ICCR, 2004). The tendency of a material to aggregate or agglomerate should be well understood so it can be accounted for in the manufacturing process and utilized where appropriate.

Fig. 5. A secondary electron image of agglomerations of 5 nm titanium dioxide particles deposited onto a holey carbon substrate supported by a TEM.

Figure 6B depicts an aggregate or agglomerate of the 7 nm titanium dioxide particles. It is noted that the mass in Figure 6B (7 nm nanoparticles) is considerably larger than those found in Figure 6A (5 nm nanoparticles). Moving from 5-7 nm is a 40% increase in particle size. Is this the cause for the difference in aggregation or agglomeration tendency? Or, is this tendency due to some other factor such as a change in surface functionality. Are there other attributes affected by a significant change in particle size that we are yet unaware of? And furthermore, what constitutes a significant change: is 20% or 5% considered to be

significant? The degree of change for a specific property is another area that is not well understood as it pertains to nanomaterials and may be an area prone to causing confusion and ambiguity.

The Same or Different? We now return to a gold nanoparticle example. This

example demonstrates how establishing specifications for a product, weighing manufacturing outcomes vs. intended design, and understanding manufacturer supplied information go into understanding the ramifications of using a given material. One of the most important things to understanding a material’s toxicity or environmental impact lies in accurately representing it by the underlying data. Figures 7A and 7B depict similar gold nanoparticle examples. These materials were both housed in the same matrix solution and have a mean particle size of roughly 50 nm. It would not be out of the realm of possibility that a toxicity study performed on one of these might be utilized as material data for the other because of the similarities in morphology and elemental composition. However, the broader size distribution of the sample in Figure 7A is very apparent as well as its faceted nature over the particles observed in Figure 7B. Since there is little historical data on nanomaterials, it is extremely difficult to say whether these materials will truly act in a similar manner (Park and Grassian, 2010; FDA, 2007). Currently the only way to be sure is to conduct further characterization. Another issue stemming from this lack of historical data is how these materials act within the body (Sanhai et al., 2008; Canavan, 2011). Are the same properties that make them appealing therapeutic candidates (such as transcending specific barriers in the body) making them unsafe for use? We also must ensure we are taking into account all exposure populations through each step of the life cycle of a nanomaterial. This includes production and manufacturing of the nanomaterial, handling and processing when the nanomaterials are integrated into a consumer product, consumer use and exposure, and finally end of life of the nanomaterial product (Peters and Grassian, 2010; Schmid, 2007).

Fig. 6. A high magnification secondary electron image of agglomerations of (a) 5 nm and (b) 7 nm titanium dioxide particles.


Fig. 7. Secondary electron images showing a) and b) two types of gold nanoparticles, both with an average diameter of approximately 50 nm.

Lessons Learned Overall, the lesson to be learned from these

nanoparticle examples is that because of the uncertainty and difficulty in manufacturing, quality control is vital in nanomaterial investigation and maturation.

Not Your Same Old Preparation and Analysis

Sample preparation and the selection of an appropriate analysis technique are important to material characterization. We have found that with respect to nanomaterials, this importance is greatly enhanced. To demonstrate the heightened significance of sample preparation we present an example of a manufacturer of quantum dots. In this case, the quantum dot characterization was desired to confirm their size.

The Quantum Dot Advantage Quantum dots are nanoparticles of a semiconductor

material that are typically in the size range of 1-10 nm. They can be covalently linked with biorecognition molecules such as antibodies, peptides, and nucleic acids and used as fluorescent probes or labels for diagnostic imaging (Smith et al., 2004; 2006; Gao et al., 2004). Organic fluorophores have historically been used as biological labels for fluorescence imaging and detection. However, quantum dots have unique optical and electrical properties that make them favorable over historic organic dyes. Quantum dots absorb and emit light very efficiently, have narrow and sharply defined emission peaks, and are significantly brighter than organic dyes. These properties allow for highly sensitive detection as well tracking multiple targets simultaneously (Smith et al., 2004; 2006; Gao et al., 2004).

Quantum dots are synthesized to have specific optoelectronic properties such as the bandgap and emission wavelength. They can be “size-tunable” or “composition-tunable” in order to produce the desired wavelength of emission (Smith et al., 2004). By adjusting the size and composition, quantum dots can be prepared to emit fluorescent light from the ultraviolet, through the visible, and into the infrared spectra (400-4000 nm) (Smith et al., 2006).

The emission wavelength of the quantum dots in this study was controlled by adjusting their composition, but not the size. The goal was to produce uniformly sized quantum dots with a wide variety of emission wavelengths and at high yield. A report from the National Science Foundation emphasized that one of the critical challenges for manufacturers is the need to control the nanoscale process without compromising the inherent properties (NSF, 2008). The report stated that “nanoscale metrology and characterization is critical for successful R&D and scale up of nanomanufactured products” (NSF, 2008). Techniques such as dynamic light scattering had been used to obtain size information on the quantum dots and indicated the quantum dots were approximately 5 nm in diameter.

In this case, the manufacturer wanted to visualize the product. The manufacturer had worked with multiple analytical laboratories for a time period of two years in unsuccessful attempts to analyze the quantum dots using electron microscopy. After discussions regarding the manufacturing process and previous characterization efforts, it was determined that failed characterization efforts were due primarily to inadequate sample preparation. Without a good sample preparation, analysis will not be fruitful.

Optimized Sample Preparation Just as nanomaterials do not act in the same way as

their macro sized counterparts (Maynard, 2006a; The Royal Society and the Royal Academy of Engineering, 2004; Schneider, 2010c; 2010e), they also require different sample preparation techniques so they are accurately represented during analysis. Failure to select an appropriate sample preparation method can lead to misrepresentation and can often cause design or process changes that are unnecessary. It is clear that sample preparation is one of the most critical aspects of nanomaterial characterization.

Sample preparation methods depend on what type of characterization is being performed and what type of instrumentation is being used. In this case study, the quantum dots were being prepared for analysis by electron microscopy which warrants several things to consider: sample media, preparation media, the sample


treatment and the sample state. The sample media could be powder, a liquid suspension, a solid or a bulk piece of material all of which are treated slightly different. Various preparation media are also available such as TEM grids utilized for high resolution electron microscopy analysis. If a TEM grid is going to be used, there are subsequently several types of substrates to consider such as a carbon film, lacey, and holey substrates. Depending on the desired information, there may be additional sample treatments that are required prior to analysis. These may include coating the sample with a thin layer of a conductive material, staining, dialysis, ultramicrotomy, electropolishing, ion milling, or freeze fracture (Sridhara Rao et al., 2010). The state of the sample during analysis should also be considered. It may be suitable to analyze the sample under ambient conditions, but there are instances where a cryogenic environment or the use of high-temperature or liquid analysis in-situ techniques may be more suitable (Allard et al., 2010; Dukes et al., 2010; Lin et al., 2007).

By assessing these sample preparation considerations and looking at them collectively, it enables a method selection that offers the highest probability for an appropriate evaluation of the sample. In this example, the solvent that the quantum dots were dispersed in was not suitable for direct deposit onto a carbon film substrate. The original solvent was diluted with a different solvent which made the quantum dots much easier to disperse onto the substrate. While the dilution of the original solvent seems trivial, it proved to be the critical factor in preparing the quantum dots for evaluation by electron microscopy.

Visualization Once sample preparation was optimized, the

appropriate analysis platform was considered. Two platforms were available each having similar capabilities but different accelerating voltages. Initial data was acquired on both a 30 kV and 200 kV instrument. It was thought that due to the higher resolution capability, the higher accelerating voltage instrumentation would be optimal. However, better results were achieved on the 30 kV instrument due to enhanced image contrast

stemming from a larger interaction volume within the sample (Goldstein et al., 2003). The higher contrast allowed the quantum dots to be visualized much easier.

Figure 8A shows numerous quantum dots that are well dispersed with no overlapping. Comparing their size to the scale marker on the image they appear to be on the order of 5 nm. This confirmed what the manufacturer had determined with alternative methods. However, for quality control purposes more statistical evaluations of the data are required. Processing software is utilized in a semi-automated manner to efficiently size a statistically relevant population. The corresponding plot in Figure 8B shows a Gaussian distribution which is centered at a diameter of approximately 4.7 nm. This evaluation included approximately 2000 data points and enabled the manufacturer to statistically prove the material was being manufactured to the size specification.

While the goal of the characterization was to determine size, the manufacturer was readily able to visualize the morphology (shape) of the quantum dots. Quantum dots used for biological applications are typically described as somewhat spherical nanoparticles (Smith et al., 2004). The images of the quantum dots show that these particles, however, are not spherical but are very irregular and in some cases angular. This type of morphological information was not discernable with the techniques initially used to size the particles.

After experiencing success with imaging, the manufacturer wanted to proceed with EDS analysis to characterize the elemental composition of the quantum dots in order to have a more holistic understanding of the product. This would confirm that the synthesis process was controlled and the particles were of the expected composition. A cadmium selenide sulfide (CdSeS) core capped with a thin layer of zinc cadmium sulfide (ZnCdS) was the anticipated architecture of the material. The outer layer is a higher bandgap material that removes surface defects and prevents nonradiative recombination, resulting in an improvement in fluorescence quantum yield (Smith et al., 2004).

Fig. 8. (a) A bright-field STEM image of quantum dots and a (b) corresponding size distribution plot which is centered at approximately 4.7 nm.


Figure 9A shows individual quantum dots with varying gray levels indicating quickly there may be variability in the synthesis. This difference can be due to thickness or density differences within the particles. The EDS analysis did show that the elemental ratios of cadmium, selenium, zinc and sulfur vary between the quantum dots. The quantum dot with a darker gray level, highlighted with a circle in Figure 9A, contains cadmium, selenium, zinc and sulfur, indicative of the core and the outer coating material, as shown in the EDS spectrum in Figure 9B. The quantum dot with the lighter gray level, highlighted with a square in Figure 9A, contains cadmium, zinc, and sulfur, but not selenium indicating a potential remnant of the outer shell without the core material (Figure 9C). The systematic evaluation confirmed there was variability in the elemental composition and thus the synthesis process of the quantum dots.

Fig. 9. (a) A bright-field STEM image of quantum dots showing varying gray levels. A corresponding EDS spectrum from a quantum dot with (b) a darker gray level (circle) and c) a lighter gray level (square).

Lessons Learned In this case study, we discussed the importance of

working closely with the manufacturer and choosing the appropriate analytical technique and instrumentation. Producing accurate and reliable data is critical to the characterization of nanoscale products for quality control and process control. However, the most important lesson was the selection of the sample preparation. The quantum dot manufacturer spent two years trying to obtain images that would confirm or dispute the size that was obtained by alternative techniques. Once a suitable sample preparation was obtained, size, morphology, and elemental composition of the quantum dots was readily obtainable.

Improving product and process Materials characterization has direct implications

throughout the lifecycle of a product. Analysis of raw materials, intermediate and/or final products, and disposition effects can potentially impact process development. In this example, different manufacturing strategies of a point-of-care diagnostic were evaluated in order to better understand performance. The performance was directly related to deposition of CNT films within a biosensor.

Combining Technologies for Novel Applications Point-of-care testing (POCT), also known as near-

patient testing, is testing that is performed at the time of the consultation and outside of a central laboratory (Khunti, 2010; Hicks, 1996). POCT provides instant availability of results which allows for immediate and informed decisions to be made about patient care. Some advantages of POCT are earlier diagnosis and more efficient disease management with the potential for improved outcomes, improved patient satisfaction, and cost-effectiveness (Khunti, 2010; Veetil and Ye, 2007). In order to perform this type of in the field testing, portable and rapid diagnostics are needed. While conventional biosensing techniques are specific and sensitive, they are highly complex and are difficult to miniaturize (Balasubramanian and Burghard, 2006; Deng et al., 2007). The development of miniaturized devices which employ novel biosensing technology have the potential to dramatically affect public health (Pautler and Brenner, 2010; Sanhai et al., 2008; Bohunicky and Mousa, 2011; Kauffman et al., 2009; Tang et al., 2006).

In general, a biosensor converts a chemical interaction of a specific analyte into a measureable signal, whose magnitude is proportional to the concentration of the analyte (Figure 10). Enzymes or antibodies act as a sensing element and are responsible for the selective detection of the analyte of interest. A signal transducer recognizes the physiochemical change in the sensing element, and produces an output signal (electrical, optical, thermal, piezoelectric or magnetic). The output signal can then be used to determine the analyte concentration (Balasubramanian and Burghard, 2006; Dai et al., 2002; Kumar et al., 2011; Thevenot et al., 1999).


Fig. 10. A schematic of a biosensor showing the different components including the bioreceptor, transducer, and receptor.

CNTs are of great interest for a variety of applications due to several unique properties including electrical, mechanical, thermal, and high surface-to-volume ratios (Dai et al., 2002; Belin and Epron, 2005; Balasubramanian and Burghard, 2006; Kumar et al., 2011) and more specifically are used in the area of nanomedicine for biosensing, imaging, and therapeutics (Kostarelos et al., 2009; Bohunicky and Mousa, 2011; Kong et al., 2000; Kauffman et al., 2009). They have diameters on the order of nanometers and can reach several millimeters in length, making them suitable for use in miniaturized devices (Patel at al., 2008; Kostarelos et al., 2009). CNTs have been used to develop highly specific biosensors for streptavidin (SA) protein detection, glucose detection, and DNA sensing (Wang, 2005; Tang et al., 2006; Deng et al., 2007). The ability to chemically functionalize CNTs so that almost any chemical species can be attached to them is an advantage for biosensor applications (Balasubramanian and Burghard, 2006).

In this case study, CNTs act as the transducer in the biosensor and carry the electrical signal that is proportional to the concentration of the analyte. The bioreceptors that recognize the analyte are attached to the functionalized CNTs. The performance of the CNT-based biosensor depends on two things: the distribution of the CNT film and the attached biological receptors.

Raw Material Evaluation In order to evaluate the nature of the CNT film that

is deposited on a biosensor, it is important to first have an understanding of the raw material. It is essential to confirm that specifications and requirements are met before it is used in a process or product (Park and Grassian, 2010). The CNT raw material for this case study was not previously analyzed but believed to be bundles of CNTs distributed in a matrix. The CNT material was deposited onto a lacey carbon substrate supported by a TEM grid and analyzed using scanning transmission electron microscopy (STEM). The secondary electron image of the starting material shows a matrix of CNTs as anticipated (Figure 11A). The material was further analyzed in order to examine the internal structure of this matrix. In Figure 11B, the individual CNT bundles were differentiated and the size and interconnectivity of the bundles was able to be observed. The analysis confirmed bundles of CNTs formed a web-like matrix and the bundles were distributed in various directions forming multiple interconnections.

Process Outcome Evaluation As mentioned above, the performance of the

biosensor is based on the dispersion of the CNT film on the electrode. The dispersion and network density of CNTs affects the electrical properties of the film as well as the immobilization of the bioreceptor which affects selectivity and sensitivity (Balasubramanian and Burghard, 2006; Dai et al., 2002). Figure 12 shows secondary electron images of a CNT film from three different processes. The yellow overlay in Figure 12 highlights the dispersion of the CNT films. Again, the goal of the analysis was to determine the state and uniformity of the CNTs. Figure 12A shows a uniform, but relatively sparse dispersion of the CNTs from process one. The CNTs appear to be singular and not show the dense webbing observed in the raw material. Figure 12B shows a uniform dispersion as well, but much more dense webbing from process two. This density is similar to what was observed in the raw material. Finally, Figure 12C shows an agglomeration of CNTs from process three. The dispersion on this sample was not very uniform and resulted in numerous agglomerations of CNTs throughout the sample.

Fig. 11. (a) A low magnification secondary electron image of the starting CNT material and a (b) bright-field STEM image showing the individual bundles of CNTs (highlighted with the white lines).


Fig. 12. Secondary electron images of deposited CNTs showing (a) a uniform, but sparse distribution, (b) a dense and uniform distribution, and c) agglomerations of CNTs.

This data helped to identify which process produced uniform dispersions of CNTs and which resulted in undesirable agglomerations. In addition, this data could be related to modeling that was being performed in order to predict performance. The modeling was based on different thicknesses and densities of the CNT films in

order to understand the three dimensional structure of the layer. These characteristics can directly affect the conductivity, capacitance and other properties of the biosensor (Deng et al., 2007) and would remain speculative without visualization.

In addition to dispersion of CNTs, the location, density and clustering of the bioreceptors (sensing elements) also affect the performance of the biosensor (Veetil and Ye, 2007; Balasubramanian and Burghard, 2006). In order to aid in the visualization, the bioreceptors were tagged with 20 nm gold nanoparticles. If the gold nanoparticles could be visualized, information about the location and density of the bioreceptors could be obtained.

The gold nanoparticles were visible by backscattered electron imaging, which shows atomic number contrast in the image. Higher atomic number components appear brighter in these images (Goldstein et al., 2003). Figure 13A shows a backscattered electron image where the gold nanoparticles appear bright and spherical and are very easily recognized. The higher magnification image in Figure 13B also shows some clustering of the gold nanoparticles.

Lessons Learned Conclusive data from the different processes helped

the company with the continuous improvement of their product as they adjusted their process. We learned that electron microscopy techniques can be valuable in providing information on process performance as well as product development.

Summary The scientific community must collaborate to create a

uniform set of standards that demonstrate a consistent and credible stance on the use of nanotechnology. Policy makers and industry professionals agree that universal standards are needed, but not many have found ways to work together and at a similar pace for standardization (FDA, 2007; NIOSH, 2009; Morrissey, 2006; Schneider, 2010a). Industry, government agencies, and educational institutions can use their varying opinions to stimulate discussion rather than stir conflict. Research should be done in the spirit of advancing and promoting safe nanotechnology as a whole; that is, no single discipline should be responsible for lending funds or technical expertise. If nanotechnology is indeed the next industrial revolution, then it must be a joint effort. Until this occurs, manufactures must keep a close eye on developing regulations. In the life sciences, the FDA will likely govern current guidance and regulation issuance. Not only will manufactures in the life science industries keep abreast of what position the FDA takes, but they should also follow other regulatory agencies such as the EPA. Since the different agencies do collaborate on some levels, following all of them instead of a single governing entity will provide a comprehensive picture and potentially foreshadow regulations that have industry-wide implications.


Fig. 13. A backscattered electron image showing the (a) distribution of the gold nanoparticles on the CNT film and (b) a higher magnification image showing the clustering tendencies of the gold nanoparticles.

The industry is still in need of a clear leader to organize this collaboration. The formation of the National Nanotechnology Initiative in 2000 attempts to address nanotechnology collaboration and is responsible for keeping the delicate balance between innovation and safety (NNI, 2011; Roco, 2007; 2011). However, the NNI still appears to be a victim of traditional collaborative methods and bureaucracy. Because many parties review their initiatives, and because there is an imbalance between government, industry, and academia, the NNI and other agencies’ ability to change technology is often delayed. If regulatory agencies are to keep up, new ways of collaborating must be considered to speed these reaction times. Furthermore, funding plays a crucial role in nanoscale research and development. A lack of funding impacts safety research and programs, as well as ethics research and education (Lane and Kalil, 2005; Bawa and Johnson, 2008). Undoubtedly a clear and universal voice is required with respect to safety issues. However, with only approximately 7% of the nanotechnology budget this year allotted to the study of safety, fulfillment of this mission will continue to be difficult if underfunded (Schneier, 2010a). This means that for the immediate future, burden remains on the manufacturer to establish safety without any standard guidance. Investigating all industry guidance and requirements collectively can provide insight on establishing safety and functionality in the absence of standards. For example, the PMN process described earlier may provide insight about the types of attributes that require characterization for other types of materials slated for life science applications. The manufacturer must decipher a proper course of characterization from this collective body of knowledge until such a time that standard protocols and regulations do exist.

Someone must take the first step in this regulatory arena. An example of this is the new definition adopted by the European Commission in October 2011: Recommendation on the Definition of Nanomaterial. The definition includes unbound, aggregates, and agglomerations of nanomaterials, but is based on size alone and does not address novel properties of nanomaterials (European Union, 2011). The European Commission states that the definition will be used primarily in legislation to identify nanomaterials under

specific circumstances, including risk assessment and ingredient labeling. Some argue that this definition is inadequate and has the potential to cause public confusion. However, it is in the very least an established starting point to allow evaluation of something that is actually put into use. Flaws in this definition are sure to be encountered during the time it is applied but these discrepancies can be a learning experience for all in the field to produce more appropriate, science-based regulation. What this means for manufacturers is a clear path to move forward in the unification of the industry and also pertaining to their specific products.

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Address correspondence to: Dr. Kristin L. Bunker, Ph.D., Senior Scientist RJ Lee Group, Inc., 350 Hochberg Road Monroeville, PA, 15146, USA. Tel: 724-325-1776; Email: [email protected]

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