STM topography (a) and current (b) image of a sample of highly oriented pyrolitic graphite (HOPG).

<p>The tracking of the topography and current image is clear. The scanning parameters are the following: current setpoint 1.0 nA, bias voltage 80 mA, integral gain 1, tip velocity 0.18 μm/s. The image is consisted with the large literature of STM images of HOPG [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135594#pone.0135594.ref022" target="_blank">22</a>].</p

Image reproduced from reference [7] showing topography STM images of a sample of mixed ligand nanoparticles imaged at different scan angles and scan sizes.

<p>The cross section achieved by averaging the images at the white band shown on them is presented in (h). All images are show in their full scan range. A complete description of the images is found in reference [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135594#pone.0135594.ref007" target="_blank">7</a>]. Reproduced from reference [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135594#pone.0135594.ref007" target="_blank">7</a>]. Reproduced by permission of The Royal Society of Chemistry.</p

Topography STM images obtained by inducing feedback loop oscillation on a sample of nanoparticles.

<p>Scan angle is varied across the images that the features do not change direction. (f) 1D PSD plot of the images showing sharp peaks at the spatial frequency corresponding the spacing of the feedback loop oscillation (larger peak) and to its first harmonic.</p

(a to c) STM topography images used in reference [1] and downloaded from http://dx.doi.org/10.6084/m9.figshare.882904 on August 11, 2014. Insets of these images are used in reference [1] Fig 3 to argue that gains affect the spacing for feedback loop artifacts. The images shown are three representative ones over a set of 10. (d) PSD plot for all 10 images. Peaks for the feedback loop oscillation are clearly visible. Plots for images at 13% (red) and 14% (light blue) show two peaks. The image at 13% is the image shown in (b). Image in (a) is a representative image from the group below 13% and the one in (c) comes from the group above. In (e) we plot the trend for the spacing corresponding to the frequency at the peak in the PSD plot for these images, in red are all of the peaks for the curves below 13% and for the lower spacing peak for the two curves at 13 and 14%. In blue the peaks for the higher spacing for these two images, and for single peak in the images acquired at higher gains.

<p>(a to c) STM topography images used in reference [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135594#pone.0135594.ref001" target="_blank">1</a>] and downloaded from <a href="http://dx.doi.org/10.6084/m9.figshare.882904" target="_blank">http://dx.doi.org/10.6084/m9.figshare.882904</a> on August 11, 2014. Insets of these images are used in reference [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135594#pone.0135594.ref001" target="_blank">1</a>] <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135594#pone.0135594.g003" target="_blank">Fig 3</a> to argue that gains affect the spacing for feedback loop artifacts. The images shown are three representative ones over a set of 10. (d) PSD plot for all 10 images. Peaks for the feedback loop oscillation are clearly visible. Plots for images at 13% (red) and 14% (light blue) show two peaks. The image at 13% is the image shown in (b). Image in (a) is a representative image from the group below 13% and the one in (c) comes from the group above. In (e) we plot the trend for the spacing corresponding to the frequency at the peak in the PSD plot for these images, in red are all of the peaks for the curves below 13% and for the lower spacing peak for the two curves at 13 and 14%. In blue the peaks for the higher spacing for these two images, and for single peak in the images acquired at higher gains. In (d) the dotted lines demark a region in the PSD with many features corresponding to the sizes of the hemispheres present in the sample. As long as these features are present (gains below 13%) one can assume that the tip is tracking the sample. In this case the feedback loop oscillations all happen at the same spacing, above 14% tracking is lost (as evident when looking at the PSD) and the oscillations start becoming dependent on the gains. Evidently at 13 and 14% the imaging happens in a mode that is somewhat in between the two. The analysis of this data shows that what stated in reference [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135594#pone.0135594.ref001" target="_blank">1</a>] is incorrect.</p

STM topography (reproduced from reference [6]) images of the same nanoparticles imaged at higher and lower resolution the arrows indicated the persistence of the same three stripe-like domains as the scan size is varied.

<p>Importantly resolution decreases the dots present in (a) merge into continuous lines in (b). Reprinted with permission by the American Chemical Society.</p

(a and b) 1D PSD plots for STM topography images of nanoparticles imaged with feedback loop oscillations induced. Plots in (a) are for images at 1.03 μm/s and in (b) are at 1.55 μm/s. (c and d) representative images for the images analyzed in (b) taken with the integral gain of 1 and 1.8, respectively. (e) Plot for the trend for the spacing corresponding to the frequency at the main peak in the PSD plots shown in (a, black) and (b, red). In the case of (a) we see minimal dependence on gain; in (b) we observe a weak dependence after the gain of 1.5, where the PSD plot show a start of loss of tracking. In any case the change in spacing measured is only ~ 0.2 nm (20% of the smallest spacing measured at this speed). We should highlight that the vast majority of our images are at speeds below 1.0 μm/s and are obtained currently at gains below 0.5 while historically at gains below 1, hence is a regime where in our microscope there is no dependence of the measured spacing on gains.

<p>(a and b) 1D PSD plots for STM topography images of nanoparticles imaged with feedback loop oscillations induced. Plots in (a) are for images at 1.03 μm/s and in (b) are at 1.55 μm/s. (c and d) representative images for the images analyzed in (b) taken with the integral gain of 1 and 1.8, respectively. (e) Plot for the trend for the spacing corresponding to the frequency at the main peak in the PSD plots shown in (a, black) and (b, red). In the case of (a) we see minimal dependence on gain; in (b) we observe a weak dependence after the gain of 1.5, where the PSD plot show a start of loss of tracking. In any case the change in spacing measured is only ~ 0.2 nm (20% of the smallest spacing measured at this speed). We should highlight that the vast majority of our images are at speeds below 1.0 μm/s and are obtained currently at gains below 0.5 while historically at gains below 1, hence is a regime where in our microscope there is no dependence of the measured spacing on gains.</p

(a) STM image of a sample of nanoparticles imaged in phenyl octane. This image is taken from reference [5] (Moglianetti et al. Scanning Tunneling Microscopy and Small Angle Neutron Scattering Study of Mixed Monolayer Protected Gold Nanoparticles in Organic Solvents. Chem. Sci. 2014, 5, 1232–1240; http://dx.doi.org/10.1039/C3SC52595C) where a full description of the image and of the sample can be found. Reproduced by permission of the Royal Society of Chemistry. All rights reserved. (b) Same image as the one shown in (a) with curvature removed using the same procedure described in reference [1], this is done so to highlight the features on the nanoparticles it should be noted the alignment of these features across many particles.

<p>(a) STM image of a sample of nanoparticles imaged in phenyl octane. This image is taken from reference [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135594#pone.0135594.ref005" target="_blank">5</a>] (Moglianetti et al. Scanning Tunneling Microscopy and Small Angle Neutron Scattering Study of Mixed Monolayer Protected Gold Nanoparticles in Organic Solvents. Chem. Sci. 2014, 5, 1232–1240; <a href="http://dx.doi.org/10.1039/C3SC52595C" target="_blank">http://dx.doi.org/10.1039/C3SC52595C</a>) where a full description of the image and of the sample can be found. Reproduced by permission of the Royal Society of Chemistry. All rights reserved. (b) Same image as the one shown in (a) with curvature removed using the same procedure described in reference [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135594#pone.0135594.ref001" target="_blank">1</a>], this is done so to highlight the features on the nanoparticles it should be noted the alignment of these features across many particles.</p

Enhancing Radiotherapy by Lipid Nanocapsule-Mediated Delivery of Amphiphilic Gold Nanoparticles to Intracellular Membranes

Amphiphilic gold nanoparticles (amph-NPs), composed of gold cores surrounded by an amphiphilic mixed organic ligand shell, are capable of embedding within and traversing lipid membranes. Here we describe a strategy using crosslink-stabilized lipid nanocapsules (NCs) as carriers to transport such membrane-penetrating particles into tumor cells and promote their transfer to intracellular membranes for enhanced radiotherapy of cancer. We synthesized and characterized interbilayer-crosslinked multilamellar lipid vesicles (ICMVs) carrying amph-NPs embedded in the capsule walls, forming Au-NCs. Confocal and electron microscopies revealed that the intracellular distribution of amph-NPs within melanoma and breast tumor cells following uptake of free particles <i>vs</i> Au-NCs was quite distinct and that amph-NPs initially delivered into endosomes by Au-NCs transferred over a period of hours to intracellular membranes through tumor cells, with greater intracellular spread in melanoma cells than breast carcinoma cells. Clonogenic assays revealed that Au-NCs enhanced radiotherapeutic killing of melanoma cells. Thus, multilamellar lipid capsules may serve as an effective carrier to deliver amphiphilic gold nanoparticles to tumors, where the membrane-penetrating properties of these materials can significantly enhance the efficacy of frontline radiotherapy treatments

Colloidal Stability of Self-Assembled Monolayer-Coated Gold Nanoparticles: The Effects of Surface Compositional and Structural Heterogeneity

Surface heterogeneity plays an important role in controlling colloidal phenomena. This study investigated the self-aggregation and bacterial adsorption of self-assembled monolayer coated gold nanoparticles (AuNPs) with different surface compositional and structural heterogeneity. Evaluation was performed on AuNPs coated with (1) one ligand with charged terminals (MUS), (2) two homogeneously distributed ligands with respectively charged and nonpolar terminals (brOT) and (3) two ligands with respectively charged and nonpolar terminals with stripe-like distribution (OT). The brOT particles have less negative electrophoretic mobility (EPM) values, smaller critical coagulation concentration (CCC) and larger adsorption rate on <i>Escherichia coli</i> than that of AuNPs with homogeneously charged groups, in good agreement with DLVO predictions. Although the ligand composition on the surface of AuNPs is the same, OT particles have less negative EPM values and faster rate of bacterial adsorption, but much larger CCC compared to brOT. The deviation of OT particles from brOT and MUS in their self-aggregation behavior reflects the effects of surface heterogeneity on electrical double layer structures at the interface. Results from the present study demonstrated that, besides chemical composition, organization of ligands on particle surface is important in determining their colloidal stability

Nucleation and Island Growth of Alkanethiolate Ligand Domains on Gold Nanoparticles

The metal oxide cluster α-AlW₁₁O₃₉^9– (<b>1</b>), readily imaged by cryogenic transmission electron microscopy (cryo-TEM), is used as a diagnostic protecting anion to investigate the self-assembly of alkanethiolate monolayers on electrostatically stabilized gold nanoparticles in water. Monolayers of <b>1</b> on 13.8 ± 0.9 nm diameter gold nanoparticles are displaced from the gold surface by mercaptoundecacarboxylate, HS(CH₂)₁₀CO₂^– (<b>11-MU</b>). During this process, no aggregation is observed by UV–vis spectroscopy, and the intermediate ligand-shell organizations of <b>1</b> in cryo-TEM images indicate the presence of growing hydrophobic domains, or “islands”, of alkanethiolates. UV–vis spectroscopic “titrations”, based on changes in the surface plasmon resonance upon exchange of <b>1</b> by thiol, reveal that the 330 ± 30 molecules of <b>1</b> initially present on each gold nanoparticle are eventually replaced by 2800 ± 30 molecules of <b>11-MU</b>. UV–vis kinetic data for <b>11-MU</b>-monolayer formation reveal a slow phase, followed by rapid self-assembly. The Johnson, Mehl, Avrami, and Kolmogorov model gives an Avrami parameter of 2.9, indicating continuous nucleation and two-dimensional island growth. During nucleation, incoming <b>11-MU</b> ligands irreversibly displace <b>1</b> from the Au-NP surface <i>via</i> an associative mechanism, with <i>k</i>_nucleation = (6.1 ± 0.4) × 10² M^–1 s^–1, and 19 ± 8 nuclei, each comprised of <i>ca</i>. 8 alkanethiolates, appear on the gold-nanoparticle surface before rapid growth becomes kinetically dominant. Island growth is also first-order in [<b>11-MU</b>], and its larger rate constant, <i>k</i>_growth, (2.3 ± 0.2) × 10⁴ M^–1 s^–1, is consistent with destabilization of molecules of <b>1</b> at the boundaries between the hydrophobic (alkanethiolate) and the electrostatically stabilized (inorganic) domains