The adhesive and frictional behavior of endgrafted poly [2-(dimethylamino)ethyl methacrylate] (PDMAE-MA) films (brushes) in contact with atomic force microscope tips from which PDMAEMA or poly(methacrylic acid) (PMAA) were grafted has been shown to be a strong function of pH in aqueous solution. The interaction between the brushcoated surfaces is determined by a combination of electrostatic and noncovalent interactions, modulated by the effect of the solvation state on the brush and the resulting area of contact between the probe and the surface. For cationic PDMAEMA− PDMAEMA contacts at low pH, the brushes are highly solvated; a combination of electrostatic repulsion and a high degree of solvation (leading to a significant osmotic pressure) leads to a small area of contact, weak adhesion, and energy dissipation through plowing. As the pH increases, the electrostatic repulsion and the osmotic pressure decrease, leading to an increase in the area of contact and a concomitant increase in the strength of adhesion through hydrophobic interactions; as a consequence, the friction−load relationship becomes nonlinear as shear processes contribute to friction and the mechanics are fitted by DMT theory and, at higher pH, by the JKR model. For PDMAEMA−PMAA, the electrostatic interaction is attractive at neutral pH, leading to a large adhesion force, a large area of contact, and a nonlinear friction−load relationship. However, as the pH becomes either very small or very large, a significant charge is acquired by one of the contacting surfaces, leading to a large amount of bound solvent and a significant osmotic pressure that resists deformation. As a consequence, the area of contact is small, adhesion forces are reduced, and the friction−load relationship is linear, with energy dissipation dominated by molecular plowing.
The frictional behaviour of end-grafted poly[2-(dimethyl amino)ethyl methacrylate] films (brushes) has been shown by friction force microscopy to be a strong function of pH in aqueous solution. Data were acquired using bare silicon nitride and gold-coated tips, and gold coated probes that were functionalized by the deposition of self-assembled monolayers. At the extremes of pH (pH = 1, 2, and 12), the friction-load relationship was found to be linear, in agreement with Amontons' law of macroscopic friction. However, at intermediate pH values, the data were fitted by single asperity contact mechanics models; both Johnson-Kendall-Roberts (JKR) and Derjaguin-Muller-Toporov models were observed, with JKR behaviour fitting the data better at relatively neutral pH.
The nanoscopic adhesive and frictional behaviour of end-grafted poly[2-(dimethyl amino)ethyl methacrylate] (PDMAEMA) films (brushes) in contact with gold-or PDMAEMA-coated atomic force microscope tips in potassium halide solutions with different concentrations up to 300 mM is a strong function of salt concentration. The conformation of the polymers in the brush layer is sensitive to salt concentration, which leads to large changes in adhesive forces and the contact mechanics at the tip-sample contact, with swollen brushes (which occur at low salt concentrations) yielding large areas of contact and friction-load plots that fit JKR behaviour, while collapsed brushes (which occur at high salt concentrations) yield sliding dominated by ploughing, with conformations in between fitting DMT mechanics. The relative effect of the different anions follows the Hofmeister series, with I − collapsing the brushes more than Br − and Cl − for the same salt concentration.
Addition of a strong base to Nafion® proton exchange membranes is a common practice in industry to increase their overall performance in fuel cells. Here, we investigate the evolution of the nano-rheological properties of Nafion thin films as a function of the casting pH, via characterization with static and dynamic, contact and intermittent-contact atomic force microscopy (AFM) techniques. The addition of KOH causes non-monotonic changes in the viscoelastic properties of the films, which behave as highly dissipative, softer materials near neutral pH values, and as harder, more elastic materials at extreme pH values. We quantify this behavior through calculation of the temporal evolution of the compliance and the glassy compliance under static AFM measurements. We complement these observations with dynamic AFM metrics, including dissipated power and virial (for intermittent-contact-mode measurements), and contact resonance frequency and quality factor (for dynamic contact-mode measurements). We explain the non-monotonic material property behavior in terms of the degree of ionic crosslinking and moisture content of the films, which vary with the addition of KOH. This work focuses on the special case study of the addition of strong bases, but the observed mechanical property changes are broadly related to water plasticizing effects and ionic crosslinking, which are also important in other types of films.
A persistent challenge in materials science is the characterization of a large ensemble of heterogeneous nanostructures in a set of images. This often leads to practices such as manual particle counting, and sampling bias of a favorable region of the “best” image. Herein, we present the open-source software, imaging criteria and workflow necessary to fully characterize an ensemble of SEM nanoparticle images. Such characterization is critical to nanoparticle biosensors, whose performance and characteristics are determined by the distribution of the underlying nanoparticle film. We utilize novel artificial SEM images to objectively compare commonly-found image processing methods through each stage of the workflow: acquistion, preprocessing, segmentation, labeling and object classification. Using the semi- supervised machine learning application, Ilastik, we demonstrate the decomposition of a nanoparticle image into particle subtypes relevant to our application: singles, dimers, flat aggregates and piles. We outline a workflow for characterizing and classifying nanoscale features on low-magnification images with thousands of nanoparticles. This work is accompanied by a repository of supplementary materials, including videos, a bank of real and artificial SEM images, and ten IPython Notebook tutorials to reproduce and extend the presented results.
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