Scientific publications

Time-dependent indentation plasticity experiments have been conducted with single-dislocation resolution on KBr(100) surfaces using atomic force microscopy (AFM) in ultrahigh vacuum. Discontinuous displacements of the the tip (pop-ins) with a typical distance on the order of 1 Å or less indicate the nucleation and glide of single dislocations within the sample. Pop-in events were observed to occur repeatedly for as long as 4 min while holding the indentation at constant load. These observations indicate that nucleation of dislocations below the indenting AFM tip is stress assisted and thermally activated. The rate of pop-in events decays with time in a power-law dependence with an exponent of −0.8. The characteristic decay of indentation creep in AFM indentation is much slower than in instrumented nanoindentation for comparable experimental conditions. Closed-loop load controlled and open-loop indentations result in the same pop-in displacement and rate, proving that in AFM-based indentation the influence of instrumental inertia is small compared to most instrumented nanoindentation experiments. A comparison between indentation with sharp silicon tips and with blunter diamond tips demonstrates the importance of the tip radius even at the nanometer length scale; sharper tips activate additional glide systems.

Noncontact atomic force microscopy provides access to several complementary signals, such as topography, damping, and contact potential. The traditional presentation of such data sets in adjacent figures or in colour-coded pseudo-three-dimensional plots gives only a qualitative impression. We introduce two-dimensional histograms for the representation of multichannel NC-AFM data sets in a quantitative fashion. Presentation and analysis are exemplified for topography and contact-potential data for graphene grown epitaxially on 6H-SiC(0001), as recorded by Kelvin probe force microscopy in ultrahigh vacuum. Sample preparations by thermal decomposition in ultrahigh vacuum and in an argon atmosphere are compared and the respective growth mechanisms discussed.

Having reached the quantum and thermodynamic limits of detection, atomic force microscopy (AFM) experiments are routinely being performed at the fundamental limit of signal to noise. A critical understanding of the statistical properties of noise leads to more accurate interpretation of data, optimization of experimental protocols, advancements in instrumentation, and new measurement techniques. Furthermore, accurate simulation of cantilever dynamics requires knowledge of stochastic behavior of the system, as stochastic noise may exceed the deterministic signals of interest, and even dominate the outcome of an experiment. In this article, the power spectral density (PSD), used to quantify stationary stochastic processes, is introduced in the context of a thorough noise analysis of the light source used to detect cantilever deflections. The statistical properties of PSDs are then outlined for various stationary, nonstationary, and deterministic noise sources in the context of AFM experiments. Following these developments, a method for integrating PSDs to provide an accurate standard deviation of linear measurements is described. Lastly, a method for simulating stochastic Gaussian noise from any arbitrary power spectral density is presented. The result demonstrates that mechanical vibrations of the AFM can cause a logarithmic velocity dependence of friction and induce multiple slip events in the atomic stick-slip process, as well as predicts an artifactual temperature dependence of friction measured by AFM.

Friction and wear of single layers of graphene have been studied at the micrometer scale. Epitaxial graphene grown by thermal decomposition on SiC-6H(0001) is found to have an initial friction coefficient of 0.02, significantly lower than graphite under the same experimental conditions. During reciprocal sliding the graphene layer is damaged. The evolving friction coefficient of 0.08 for the carbon-rich interface layer terminating the SiC layer is still lower than that of graphite and five times lower than that of the hydrogen-etched SiC substrate. Micrometer-sized patches within the sliding track retain the low friction coefficient of graphene even after hundred sliding cycles.

In this article, we present an analytical model that describes the plowing coefficient of friction for sliding, elastic-plastic contacts between a conical tip with a spherical extremity and a flat substrate. The model includes the effects of adhesion and bridges the gap between models which are based solely on dislocation activity and those based solely on interfacial effects scaling with the contact area. The Derjaguin-Muller-Toporov approximation for adhesive contact stress is used in our description of the contacts. Our model shows excellent agreement with large-scale molecular dynamics simulations and atomic force microscopy experiments of nanoscratching on copper single crystals. One important result of our study is that the model predicts coefficients of friction that are an order of magnitude higher than typically reported for nanoscale elastic contacts. Furthermore, the coefficients of friction described by the model are very close to values typical of macroscale sliding contacts.

The lubricating properties of an ionic liquid on gold surfaces can be controlled through application of an electric potential to the sliding contact. A nanotribology approach has been used to study the frictional behaviour of 1-butyl-1-methylpyrrolidinium tris(pentafluoroethyl) trifluorophosphate ([Py1,4]FAP) confined between silica colloid probes or sharp silica tips and a Au(111) substrate using atomic force microscopy. Friction forces vary with potential because the composition of a confined ion layer between the two surfaces changes from cation-enriched (at negative potentials) to anion enriched (at positive potentials). This offers a new approach to tuning frictional forces reversibly at the molecular level without changing the substrates, employing a self-replenishing boundary lubricant of low vapor pressure.

This letter reports on the tunable wetting behavior of poly(dimethylsiloxane) (PDMS) via the combination of nanostructuring and plasma treatment. The PDMS is first micro/nanostructured by an integrated casting process. Subsequently, an inductively coupled plasma is used to modify the siloxanes' surface chemistry. Sulfur hexafluoride, fluoroform, as well as octafluorocyclobutane plasma were applied to treat PDMS samples successively. By optimizing the treatment parameters, tunable wettability of the siloxane was observed, i.e., superhydrophilicity and superhydrophobicity. The stability of its wetting behavior has been demonstrated after 24 h. This stable and tunable wettability extends the applications of PDMS in microfluidic systems.

It has been shown recently that chirp-evoked auditory brainstem responses (ABRs) show better performance than click stimulations, especially at low intensity levels. In this paper we present the development, test, and evaluation of a series of notched-noise embedded frequency specific chirps. ABRs were collected in healthy young control subjects using the developed stimuli. Results of the analysis of the corresponding ABRs using a time-scale phase synchronization stability (PSS) measure are also reported. The resultant wave V amplitude and latency measures showed a similar behavior as for values reported in literature. The PSS of frequency specific chirp-evoked ABRs reflected the presence of the wave V for all stimulation intensities. The scales that resulted in higher PSS are in line with previous findings, where ABRs evoked by broadband chirps were analyzed, and which stated that low frequency channels are better for the recognition and analysis of chirp-evoked ABRs. We conclude that the development and test of the series of notched-noise embedded frequency specific chirps allowed the assessment of frequency specific ABRs, showing an identifiable wave V for different intensity levels. Future work may include the development of a faster automatic recognition scheme for these frequency specific ABRs.

Objective: The objective of our research is to structure a foundation for an electrophysiological loudness scaling measurement, in particular to estimate an uncomfortable loudness (UCL) level by using the hybrid wavelet-kernel novelty detection (HWND). Methods and materials: Late auditory evoked potentials (LAEPs) were obtained from 20 normal hearing adults. These LAEPs were stimulated by 4 intensity levels (60 decibel (dB) sound pressure level (SPL), 70. dB SPL, 80. dB SPL, and 90. dB SPL). We have extracted the habituation correlates in LAEPs by using HWND. For this, we employed a lattice structure-based wavelet frame decompositions for feature extraction combined with a kernel-based novelty detector. Results: The group results showed that the habituation correlates degrees, i.e., relative changes within the sweep sequences, were significantly different among 60. dB SPL, 70. dB SPL, 80. dB SPL, and 90. dB SPL stimulation level, independently from the intensity related amplitude information in the averaged LAEPs. At these particular intensities, 60% of the subjects show the correlation between the novelty measures and the stimulation levels resembles a loudness scaling function, in reverse. In this paper, we have found a correlation in between the novelty measures and loudness perception as well. We have found that high ranges of loudness levels such as loud, upper level and too loud show generally 4.88% of novelty measures and comfortable ranges of loudness levels, i.e., soft, comfortable but soft, comfortable loud and comfortable but loud are generally have 12.29% of novelty measures.Additionally, we demonstrated that our sweep-to-sweep basis of post processing scheme is reliable for habituation extraction and offers an advantage of reducing experimental time as the proposed scheme need less than 20% of single sweeps in comparison to the amount that are commonly used in arithmetical average for a meaningful result. Conclusions: We assessed the feasibility of habituation correlates for an objective loudness scaling. With respect to this first feasibility study, the presented results are promising when using the described signal processing and machine learning methodology. For the group results, the novelty measures approach is able to discriminate 60. dB, 70. dB, 80. dB and 90. dB stimulated sweeps. In addition, a correlation between the novelty measures and the subjective loudness scaling is observed. However, more loudness perception and frequency specific experiments need to be conducted to determine the UCL novelty measures threshold as well as clinically oriented studies are necessary to evaluate whether this approach might be used in the objective hearing instrument fitting procedures.

Mechanical forces play a vital role in the activities of cells and their interaction with biological and nonbiological material. Various experiments have successfully measured forces exerted by the cells when in contact with a substrate, but the intracellular contractile machinery leading to these actions is not entirely understood. Tan, (2003, Cells Lying on a Bed of Microneedles: An Approach to Isolate Mechanical Force, Proc. Natl. Acad. Sci. USA, 100(4), pp. 1484-1489) use a bed of PDMS posts as the substrate for cells and measure the localized mechanical forces exerted by the cell cytoskeleton on the posts. In live cell experiments for this setup, post deflections are measured, and from these results the forces applied by the cell are calculated. From such results, it is desirable to quantify the contractile tensions generated in the force-bearing elements corresponding to the stress fibers within the cell cytoskeleton that generate the loads applied to the posts. The purpose of the present article is to consider the cytoskeleton as a discrete network of force-bearing elements, and present a structural mechanics based methodology to estimate the configuration of the network, and the contractile tension in the corresponding stress fibers. The network of stress fibers is modeled as a structure of truss elements connected among the posts adhered to a single cell. In-plane force equilibrium among the network of stress fibers and the system of posts is utilized to calculate the tension forces in the network elements. A Moore-Penrose pseudo-inverse is used to solve the linear equations obtained from the mechanical equilibrium of the cell-posts system, thereby obtaining a least squares fit of the stress fiber tensions to the post deflections. The predicted network of force-bearing elements provides an approximated distribution of the prominent stress fibers connected among deflected posts, and the tensions in each fibril.