Simplifying Electron Diffraction Pattern Identification of Mixed-Material Nanoparticles

Introduction Metallic and non-metallic nanoparticles (NPs), ranging in size from 1–200 nm, have unique functional properties that differ from their bulk materials and their component atoms or molecules [1]. These unique properties have driven the demand for nano-sized materials and new methods to synthesize NPs, which are used in drug delivery systems [2], bio-imaging agents [3], catalysts [4], photonics, and optical devices [5]. Inorganic NPs can be synthesized with a variety of methods that impart size, shape, and other structural properties. Cobalt-based NPs, for instance, display unique size and shape-dependent magnetic properties [6], while the band gap, UV blocking properties and stability of zinc oxide (ZnO) NPs enable new applications in products ranging from cosmetics [7] to solar cell power [8]. Approaches to NP synthesis include solvothermal, biological, and other templates [9], as well as ligands to seed NP growth and molding strategies [10]. Our approach for synthesizing metal NPs involves using toroidal topologies of plasmid DNA as sacrificial molds and varying conditions to fabricate size-tunable gold, nickel, and cobalt NPs [9]. Plasmid DNA provides a relatively inexpensive monodispersed template that can be engineered to form in a range of sizes and exploits the well-established high affinity for metal cations. This strategy is generally a greener approach to NP synthesis because the solvent is water and the template is biodegradable. We have characterized these NPs by atomic force microscopy (AMF) and transmission electron microscopy (TEM). For example, a pcDNA3.1 (+) plasmid can be used as a sacrificial mold to yield disc-shaped gold and nickel NPs in the range of 28 ± 3 nm × 8 ± 1 nm and 52 ± 5 nm × 13 ± 1 nm, respectively. Columnar-shaped ZnO NPs were synthesized using a pH gradient and imaged to reveal a bimodal distribution in the range of 70 ± 10 nm × 50 ± 10 nm and 135 ± 15 nm × 80 ± 10 nm. In order to confirm the nature of these NPs, which were composed of both metals and non-metallic materials, we compared their electron microdiffraction (mD) patterns to known standards [11–12]. There are two methods for obtaining electron diffraction (ED) patterns [13]. The selected area diffraction (SAD) method uses an aperture to select the area producing the ED pattern, while mD and convergent beam electron diffraction (CBED) techniques use the beam to select the area producing the pattern. The minimum area that can be selected on a 100 kV TEM by the SAD method is 1 m [12]. Because mD uses the beam to select the area, the minimum size in the TEM mode is limited by the electron source. The sharp diffracted beams of mD, as opposed to the discs of CBED, are produced by using a small (20–30 m) second condenser aperture [14]. Because the size of the NPs under examination was less than 200 nm, mD was the method of choice. Microdiffraction (mD) is a reliable method of verifying the identity of individual NPs when there is not enough sample for powder X-ray diffraction (XRD) analysis. In the use of plasmid molds, the resulting materials could be the starting metal ion salts, the metal oxides, the target metal NPs, or combinations of these (for example, nickel metal, NiO, Ni2O3, NiX2). Similar analytical criteria are needed for the formation of inorganic materials such as ZnO and TiO2. Morphology alone cannot differentiate these NPs because the metals in the NPs sometimes exist in more than one oxidation state. In other cases, similar morphologies proved to be two different materials. Identification of the NPs necessitated the indexing of individual diffraction patterns, a very time consuming and tedious procedure. To simplify the identification of materials, when one has an idea what the material might be (that is, NiO or Ni2O3) and standards with which to compare them, we present two easily applied and straightforward methods for comparing electron diffraction (ED) patterns. Identifying total unknowns will still require indexing individual diffraction patterns. The example shown in Figure 1 illustrates that this technique can be applied to inclusions in tissue samples as well as to particulate materials.