Dynamic bonding of metallic nanocontacts: Insights from experiments and atomistic simulations

The conductance across an atomically narrow metallic contact can be measured by using scanning tunneling microscopy. In certain situations, a jump in the conductance is observed right at the point of contact between the tip and the surface, which is known as “jump to contact” (JC). Such behavior provides a way to explore, at a fundamental level, how bonding between metallic atoms occurs dynamically. This phenomenon depends not only on the type of metal but also on the geometry of the two electrodes. For example, while some authors always find JC when approaching two atomically sharp tips of Cu, others find that a smooth transition occurs when approaching a Cu tip to an adatom on a flat surface of Cu. In an attempt to show that all these results are consistent, we make use of atomistic simulations; in particular, classical molecular dynamics together with density functional theory transport calculations to explore a number of possible scenarios. Simulations are performed for two different materials: Cu and Au in a [100] crystal orientation and at a temperature of 4.2 K. These simulations allow us to study the contribution of short- and long-range interactions to the process of bonding between metallic atoms, as well as to compare directly with experimental measurements of conductance, giving a plausible explanation for the different experimental observations. Moreover, we show a correlation between the cohesive energy of the metal, its Young's modulus, and the frequency of occurrence of a jump to contact.

Modeling contact formation between atomic-sized gold tips via molecular dynamics

The formation and rupture of atomic-sized contacts is modelled by means of molecular dynamics simulations. Such nano-contacts are realized in scanning tunnelling microscope and mechanically controlled break junction experiments. These instruments routinely measure the conductance across the nano-sized electrodes as they are brought into contact and separated, permitting conductance traces to be recorded that are plots of conductance versus the distance between the electrodes. One interesting feature of the conductance traces is that for some metals and geometric configurations a jump in the value of the conductance is observed right before contact between the electrodes, a phenomenon known as jump-to-contact. This paper considers, from a computational point of view, the dynamics of contact between two gold nano-electrodes. Repeated indentation of the two surfaces on each other is performed in two crystallographic orientations of face-centred cubic gold, namely (001) and (111). Ultimately, the intention is to identify the structures at the atomic level at the moment of first contact between the surfaces, since the value of the conductance is related to the minimum cross-section in the contact region. Conductance values obtained in this way are determined using first principles electronic transport calculations, with atomic configurations taken from the molecular dynamics simulations serving as input structures.

Quantum interference in atomic-sized point contacts

The conductance of atomic-sized metallic point contacts is shown to be strongly voltage dependent due to quantum interference with impurities even in samples with low impurity concentrations. Transmission through these small contacts depends not only on the local atomic structure at the contact but also on the distribution of impurities or defects within a coherence length of the contact. In contrast with other mesoscopic systems we show that transport through atomic contacts is coherent even at room temperature. The use of a scanning tunneling microscope (STM) makes it possible to fabricate one atom contacts of gold whose transmission can be controlled by manipulation of the contact allowing inelastic spectroscopy in such small contacts.

A new approach for semi-automatic rock mass joints recognition from 3D point clouds

Rock mass characterization requires a deep geometric understanding of the discontinuity sets affecting rock exposures. Recent advances in Light Detection and Ranging (LiDAR) instrumentation currently allow quick and accurate 3D data acquisition, yielding on the development of new methodologies for the automatic characterization of rock mass discontinuities. This paper presents a methodology for the identification and analysis of flat surfaces outcropping in a rocky slope using the 3D data obtained with LiDAR. This method identifies and defines the algebraic equations of the different planes of the rock slope surface by applying an analysis based on a neighbouring points coplanarity test, finding principal orientations by Kernel Density Estimation and identifying clusters by the Density-Based Scan Algorithm with Noise. Different sources of information —synthetic and 3D scanned data— were employed, performing a complete sensitivity analysis of the parameters in order to identify the optimal value of the variables of the proposed method. In addition, raw source files and obtained results are freely provided in order to allow to a more straightforward method comparison aiming to a more reproducible research.

Discontinuity spacing analysis in rock masses using 3D point clouds

The complete characterization of rock masses implies the acquisition of information of both, the materials which compose the rock mass and the discontinuities which divide the outcrop. Recent advances in the use of remote sensing techniques – such as Light Detection and Ranging (LiDAR) – allow the accurate and dense acquisition of 3D information that can be used for the characterization of discontinuities. This work presents a novel methodology which allows the calculation of the normal spacing of persistent and non-persistent discontinuity sets using 3D point cloud datasets considering the three dimensional relationships between clusters. This approach requires that the 3D dataset has been previously classified. This implies that discontinuity sets are previously extracted, every single point is labeled with its corresponding discontinuity set and every exposed planar surface is analytically calculated. Then, for each discontinuity set the method calculates the normal spacing between an exposed plane and its nearest one considering 3D space relationship. This link between planes is obtained calculating for every point its nearest point member of the same discontinuity set, which provides its nearest plane. This allows calculating the normal spacing for every plane. Finally, the normal spacing is calculated as the mean value of all the normal spacings for each discontinuity set. The methodology is validated through three cases of study using synthetic data and 3D laser scanning datasets. The first case illustrates the fundamentals and the performance of the proposed methodology. The second and the third cases of study correspond to two rock slopes for which datasets were acquired using a 3D laser scanner. The second case study has shown that results obtained from the traditional and the proposed approaches are reasonably similar. Nevertheless, a discrepancy between both approaches has been found when the exposed planes members of a discontinuity set were hard to identify and when the planes pairing was difficult to establish during the fieldwork campaign. The third case study also has evidenced that when the number of identified exposed planes is high, the calculated normal spacing using the proposed approach is minor than those using the traditional approach.