Soft solids are sticky. They attract each other and spontaneously form a large area of contact. Their force of attraction is higher when separating than when forming contact, a phenomenon known as adhesion hysteresis. The common explanation for this hysteresis is viscoelastic energy dissipation or contact aging. Here, we use experiments and simulations to show that it emerges even for perfectly elastic solids. Pinning by surface roughness triggers the stick-slip motion of the contact line, dissipating energy. We derive a simple and general parameter-free equation that quantitatively describes contact formation in the presence of roughness. Our results highlight the crucial role of surface roughness and present a fundamental shift in our understanding of soft adhesion.
While metal nanoparticles are widely used, their small size makes them mechanically unstable. Extensive prior research has demonstrated that nanoparticles with sizes in the range of 10-50 nm fail by the surface nucleation of dislocations, which is a thermally activated process. Two different contributions have been suggested to cause the weakening of smaller particles: first, geometric effects such as increased surface curvature reduce the barrier for dislocation nucleation; second, surface diffusion happens faster on smaller particles, thus accelerating the formation of surface kinks which nucleate dislocations. These two factors are difficult to disentangle. Here we use in situ compression testing inside a transmission electron microscope to measure the strength and deformation behavior of platinum particles in three groups: 12 nm bare particles, 16 nm bare particles, and 12 nm silica-coated particles. Thermodynamics calculations show that, if surface diffusion were the dominant factor, the last two groups would show equal strengthening. Our experimental results refute this, instead demonstrating a 100% increase in mean yield strength with increased particle size and no statistically significant increase in strength due to the addition of a coating. A separate analysis of stable plastic flow corroborates the findings, showing an order-of-magnitude increase in the rate of dislocation nucleation with a change in particle size and no change with coating. Taken together, these results demonstrate that surface diffusion plays a far smaller role in the failure of nanoparticles by dislocations as compared to geometric factors that reduce the energy barrier for dislocation nucleation.
The mechanical behavior of nanostructures is known to transition from a Hall-Petch-like "smaller-is-stronger" trend, explained by dislocation starvation, to an inverse Hall-Petch "smaller-is-weaker" trend, typically attributed to the effect of surface diffusion. Yet recent work on platinum nanowires demonstrated the persistence of the smaller-is-stronger behavior down to few-nanometer diameters. Here, we used in situ nanomechanical testing inside of a transmission electron microscope (TEM) to study the strength and deformation mechanisms of platinum nanoparticles, revealing the prominent and size-dependent role of surfaces. For larger particles with diameters from 41 nm down to approximately 9 nm, deformation was predominantly displacive yet still showed the smaller-is-weaker trend, suggesting a key role of surface curvature on dislocation nucleation. For particles below 9 nm, the weakening saturated to a constant value and particles deformed homogeneously, with shape recovery after load removal. Our high-resolution TEM videos revealed the role of surface atom migration in shape change during and after loading. During compression, the deformation was accommodated by atomic motion from lower-energy facets to higher-energy facets, which may indicate that it was governed by a confined-geometry equilibration; when the compression was removed, atom migration was reversed, and the original stress-free equilibrium shape was recovered.
The elastic behavior of nanoparticles depends strongly on particle shape, size, and crystallographic orientation. Many prior investigations have characterized the elastic modulus of nanoscale particles using experiments or simulations; however their reported values vary widely depending on the methods for measurement and calculation. To understand these discrepancies, we used classical molecular dynamics simulation to model the compression of platinum nanoparticles with two different polyhedral shapes and a range of sizes from 4 to 20 nm, loaded in two different crystal orientations. Multiple standard methods were used to calculate the elastic modulus from stress-vs-strain data for each nanoparticle. The magnitudes and particle-size dependence of the resulting moduli varied with calculation method and, even for larger nanoparticles where bulk-like behavior may be expected, the effective elastic modulus depended strongly on shape and orientation. Analysis of per-atom stress distributions indicated that the shape- and orientation-dependence arise due to stress triaxiality and inhomogeneity across the particle. When the effective elastic modulus was recalculated using a representative volume element in the center of a large nanoparticle, the elastic modulus had the expected value for each orientation and was shape independent. It is only for single-digit nanoparticles that meaningful differences emerged, where even the very center of the particle had a lower modulus due to the effect of the surface. These findings provide better understanding of the elastic properties of nanoparticles and disentangle geometric contributions (such as stress triaxiality and spatial inhomogeneity) from true changes in elastic properties of the nanoscale material.
While it is well established that nanoparticle shape can depend on equilibrium thermodynamics or growth kinetics, recent computational work has suggested the importance of thermal energy in controlling the distribution of shapes in populations of nanoparticles. Here, we used transmission electron microscopy to characterize the shapes of bare platinum nanoparticles and observed a strong dependence of shape distribution on particle size. Specifically, the smallest nanoparticles (<2.5 nm) had a truncated octahedral shape, bound by ã111ã and ã100ã facets, as predicted by lowest-energy thermodynamics. However, as particle size increased, the higher-energy ã110ã facets became increasingly common, leading to a large population of non-equilibrium truncated cuboctahedra. The observed trends were explained by combining atomistic simulations (both molecular dynamics and an empirical square-root bond-cutting model) with Boltzmann statistics. Overall, this study demonstrates experimentally how thermal energy leads to shape variation in populations of metal nanoparticles, and reveals the dependence of shape distributions on particle size. The prevalence of non-equilibrium facets has implications for metal nanoparticles applications from catalysis to solar energy.
Friction is one of the leading causes of energy loss in moving parts, and understanding how roughness affects friction is of utmost importance. From creating surfaces with high friction to prevent slip and movement, to creating surfaces with low friction to minimize energy loss, roughness plays a key role. By measuring shear stresses of crosslinked elastomers on three rough surfaces of similar surface chemistry across nearly six decades of sliding velocity, we demonstrate the dominant role of adhesive frictional dissipation. Furthermore, while it was previously known that roughness-induced oscillations affected the viscoelastic dissipation, we show that these oscillations also control the molecular detachment process and the resulting adhesive dissipation. This contrasts with typical models of friction, where only the amount of contact area and the strength of interfacial bonding govern the adhesive dissipation. Finally, we show that all the data can be collapsed onto a universal curve when the shear stress is scaled by the square root of elastic modulus and the velocity is scaled by a critical velocity at which the system exhibits macroscopic buckling instabilities. Taken together, these results suggest a design principle broadly applicable to frictional systems ranging from tires to soft robotics.
The adhesion between nanoscale components has been shown to increase with applied load, contradicting well-established mechanics models. Here, we use in situ transmission electron microscopy and atomistic simulations to reveal the underlying mechanism for this increase as a change in the mode of separation. Analyzing 135 nanoscale adhesion tests on technologically relevant materials of anatase TiO2, silicon, and diamond, we demonstrate a transition from fracture-controlled to strength-controlled separation. When fracture models are incorrectly applied, they yield a 7-fold increase in apparent work of adhesion; however, we show that the true work of adhesion is unchanged with loading. Instead, the nanoscale adhesion is governed by the product of adhesive strength and contact area; the pressure dependence of adhesion arises because contact area increases with applied load. By revealing the mechanism of separation for loaded nanoscale contacts, these findings provide guidance for tailoring adhesion in applications from nanoprobe-based manufacturing to nanoparticle catalysts.
Adhesives , Physical Phenomena
While roughening the surface of neural implants has been shown to significantly improve their performance, the mechanism for this improvement is not understood, preventing systematic optimization of surfaces. Specifically, prior work has shown that the cellular response to a surface can be significantly enhanced by coating the implant surface with inorganic nanoparticles and neuroadhesion protein L1, and this improvement occurs even when the surface chemistry is identical between the nanoparticle-coated and uncoated electrodes, suggesting the critical importance of surface topography. Here, we use transmission electron microscopy to characterize the topography of bare and nanoparticle-coated implants across 7 orders of magnitude in size, from the device scale to the atomic scale. The results reveal multiscale roughness, which cannot be adequately described using conventional roughness parameters. Indeed, the topography is nearly identical between the two samples at the smallest scales and also at the largest scales but vastly different in the intermediate scales, especially in the range of 5-100 nm. Using a multiscale topography analysis, we show that the coating causes a 76% increase in the available surface area for contact and an order-of-magnitude increase in local surface curvature at characteristic sizes corresponding to specific biological structures. These are correlated with a 75% increase in bound proteins on the surface and a 134% increase in neurite outgrowth. The present investigation presents a framework for analyzing the scale-dependent topography of medical device-relevant surfaces, and suggests the most critical size scales that determine the biological response to implanted materials.
Nanoparticles , Titanium , Coated Materials, Biocompatible/chemistry , Nanoparticles/chemistry , Surface Properties , Titanium/chemistry
Abstract: Materials science is about understanding the relationship between a material's structure and its properties-in the sphere of mechanical behavior, this includes elastic modulus, yield strength, and other bulk properties. We show in this issue that, analogously, a material's surface structure governs its surface properties-such as adhesion, friction, and surface stiffness. For bulk materials, microstructure is a critical component of structure; for surfaces, the structure is governed largely by surface topography. The articles in this issue cover the latest understanding of these structure-property connections for surfaces. This includes both the theoretical basis for how properties depend on topography, as well as the latest understanding of how surface topography emerges, how to measure and understand topography-dependent properties, and how to engineer surfaces to improve performance. The present article frames the importance of surface topography and its effect on properties; it also outlines some of the critical knowledge gaps that impede progress toward optimally performing surfaces.
Understanding the size- and shape-dependent properties of platinum nanoparticles is critical for enabling the design of nanoparticle-based applications with optimal and potentially tunable functionality. Toward this goal, we evaluated nine different empirical potentials with the purpose of accurately modeling faceted platinum nanoparticles using molecular dynamics simulation. First, the potentials were evaluated by computing bulk and surface properties-surface energy, lattice constant, stiffness constants, and the equation of state-and comparing these to prior experimental measurements and quantum mechanics calculations. Then, the potentials were assessed in terms of the stability of cubic and icosahedral nanoparticles with faces in the {100} and {111} planes, respectively. Although none of the force fields predicts all the evaluated properties with perfect accuracy, one potential-the embedded atom method formalism with a specific parameter set-was identified as best able to model platinum in both bulk and nanoparticle forms.
A mechanistic understanding of adhesion in soft materials is critical in the fields of transportation (tires, gaskets, and seals), biomaterials, microcontact printing, and soft robotics. Measurements have long demonstrated that the apparent work of adhesion coming into contact is consistently lower than the intrinsic work of adhesion for the materials, and that there is adhesion hysteresis during separation, commonly explained by viscoelastic dissipation. Still lacking is a quantitative experimentally validated link between adhesion and measured topography. Here, we used in situ measurements of contact size to investigate the adhesion behavior of soft elastic polydimethylsiloxane hemispheres (modulus ranging from 0.7 to 10 MPa) on 4 different polycrystalline diamond substrates with topography characterized across 8 orders of magnitude, including down to the angstrom scale. The results show that the reduction in apparent work of adhesion is equal to the energy required to achieve conformal contact. Further, the energy loss during contact and removal is equal to the product of the intrinsic work of adhesion and the true contact area. These findings provide a simple mechanism to quantitatively link the widely observed adhesion hysteresis to roughness rather than viscoelastic dissipation.
Nanoindentation and sliding experiments using single-crystal silicon atomic force microscope probes in contact with diamond substrates in vacuum were carried out in situ with a transmission electron microscope (TEM). After sliding, the experimentally measured works of adhesion were significantly larger than values estimated for pure van der Waals (vdW) interactions. Furthermore, the works of adhesion increased with both the normal stress and speed during the sliding, indicating that applied stress played a central role in the reactivity of the interface. Complementary molecular dynamics (MD) simulations were used to lend insight into the atomic-level processes that occur during these experiments. Simulations using crystalline silicon tips with varying degrees of roughness and diamond substrates with different amounts of hydrogen termination demonstrated two relevant phenomena. First, covalent bonds formed across the interface, where the number of bonds formed was affected by the hydrogen termination of the substrate, the tip roughness, the applied stress, and the stochastic nature of bond formation. Second, for initially rough tips, the sliding motion and the associated application of shear stress produced an increase in irreversible atomic-scale plasticity that tended to smoothen the tips' surfaces, which resulted in a concomitant increase in adhesion. In contrast, for initially smooth tips, sliding roughened some of these tips. In the limit of low applied stress, the experimentally determined works of adhesion match the intrinsic (van der Waals) work of adhesion for an atomically smooth silicon-diamond interface obtained from MD simulations. The results provide mechanistic interpretations of sliding-induced changes and interfacial adhesion and may help inform applications involving adhesive interfaces that are subject to applied shear forces and displacements.
Conductive modes of atomic force microscopy are widely used to characterize the electronic properties of materials, and in such measurements, contact size is typically determined from current flow. Conversely, in nanodevice applications, the current flow is predicted from the estimated contact size. In both cases, it is very common to relate the contact size and current flow using well-established ballistic electron transport theory. Here we performed 19 electromechanical tests of platinum nanocontacts with in situ transmission electron microscopy to measure contact size and conductance. We also used molecular dynamics simulations of matched nanocontacts to investigate the nature of contact on the atomic scale. Together, these tests show that the ballistic transport equations under-predict the contact size by more than an order of magnitude. The measurements suggest that the low conductance of the contact cannot be explained by the scattering of electrons at defects nor by patchy contact due to surface roughness; instead, the lower-than-expected contact conductance is attributed to approximately a monolayer of insulating surface species on the platinum. Surprisingly, the low conductance persists throughout loading and even after significant sliding of the contact in vacuum. We apply tunneling theory and extract best-fit barrier parameters that describe the properties of this surface layer. The implications of this investigation are that electron transport in device-relevant platinum nanocontacts can be significantly limited by the presence and persistence of surface species, resulting in current flow that is better described by tunneling theory than ballistic electron transport, even for cleaned pure-platinum surfaces and even after loading and sliding in vacuum.
Metal nanocontacts play a critical role in atomic force microscopy, functional nanostructures, metallic nanoparticles, and nanoscale electromechanical devices. In all cases, knowledge of the area of contact, and its variation with load, is critical for the quantitative prediction of behavior. Often, the contact area is predicted using continuum mechanics models which relate contact size to geometry, material properties, and load. Here we show for platinum nanoprobes that the contact size deviates significantly from these continuum predictions, even at low applied loads and in the absence of irreversible shape change. We use in situ transmission electron microscopy (TEM) with matched molecular dynamics (MD) simulations to investigate the load-dependent size of the contact. Direct measurements of contact radius from MD and TEM exceed the predictions of continuum mechanics by 24%-164%, depending on the model applied. The physical mechanism for this deviation is found to be dislocation activity in the near-surface material, which is fully reversed upon unloading. These findings demonstrate that contact mechanics models are insufficient for predicting contact area in real-world platinum nanostructures, even at ultra-low applied loads.
Nanoscale contact area in conductive atomic force microscopy can be determined by analyzing current flow using electron transport theories. However, it is recognized that native oxides on the conductive tip will reduce current flow, thus degrading the accuracy of the measured contact area. To quantify the adverse effect of an oxide on contact area measurements, we use molecular dynamics simulations of an oxide-coated platinum tip and a crystalline platinum substrate, where both the contact size and conductance can be inferred from the positions of atoms in the interface. We develop a method to approximate conductance based on the distance between atoms in platinum channels across the contact. Then, the contact area calculated from conductance using ballistic transport and tunneling theories is compared to that obtained using the known positions of atoms in the contact. The difference is small for very thin (<0.1 nm) or very thick (>1.0 nm) oxides, where ballistic transport and tunneling theories work well; however, the difference is significant for oxides between these limits, which is expected to be the case for platinum in many practical applications.
Sliding wear is particularly problematic for micro- and nano-scale devices and applications, and is often studied at the small scale to develop practical and fundamental insights. While many methods exist to measure and quantify the wear of a sliding atomic force microscope (AFM) probe, many of these rely on specialized equipment and/or assumptions from continuum mechanics. Here we present a methodology that enables simple, purely AFM-based measurement of wear, in cases where the AFM probe wears to a flat plateau. The rate of volume removal is recast into a form that depends primarily on the time-varying contact area. This contact area is determined using images of sharp spikes, which are analyzed with a simple thresholding technique, rather than requiring sophisticated computer algorithms or continuum mechanics assumptions. This approach enables the rapid determination of volume lost, rate of material removal, normal stress, and interfacial shear stress at various points throughout the wear experiment. The method is demonstrated using silicon probes sliding on an aluminum oxide substrate. As a validation for the present method, direct imaging in the transmission electron microscope is used to verify the method's parameters and results. Overall, it is envisioned that this purely AFM-based methodology will enable higher-throughput wear experiments and direct hypothesis-based investigation into the science of wear and its dependence on different variables.
Surface roughness affects the functional properties of surfaces, including adhesion, friction, hydrophobicity, biological response, and electrical and thermal transport properties. However, experimental investigations to quantify these links are often inconclusive because surfaces are fractal-like, and the values of measured roughness parameters depend on measurement size. Here, we demonstrate the characterization of topography of an ultrananocrystalline diamond (UNCD) surface at the angstrom scale using transmission electron microscopy (TEM), as well as its combination with conventional techniques to achieve a comprehensive surface description spanning 8 orders of magnitude in size. We performed more than 100 individual measurements of the nanodiamond film using both TEM and conventional techniques (stylus profilometry and atomic force microscopy). While individual measurements of root-mean-square (RMS) height, RMS slope, and RMS curvature vary by orders of magnitude, we combine the various techniques using the power spectral density and use this to compute scale-independent parameters. This analysis reveals that "smooth" UNCD surfaces have an RMS slope greater than 1, even larger than the slope of the Austrian Alps when measured on the scale of a human step. This approach of comprehensive multiscale roughness characterization, measured with angstrom-scale detail, will enable the systematic evaluation and optimization of other technologically relevant surfaces, as well as systematic testing of the many analytical and numerical models for the behavior of rough surfaces.
High-resolution lithography often involves thin resist layers which pose a challenge for pattern characterization. Direct evidence that the pattern was well-defined and can be used for device fabrication is provided if a successful pattern transfer is demonstrated. In the case of thermal scanning probe lithography (t-SPL), highest resolutions are achieved for shallow patterns. In this work, we study the transfer reliability and the achievable resolution as a function of applied temperature and force. Pattern transfer was reliable if a pattern depth of more than 3 nm was reached and the walls between the patterned lines were slightly elevated. Using this geometry as a benchmark, we studied the formation of 10-20 nm half-pitch dense lines as a function of the applied force and temperature. We found that the best pattern geometry is obtained at a heater temperature of â¼600 °C, which is below or close to the transition from mechanical indentation to thermal evaporation. At this temperature, there still is considerable plastic deformation of the resist, which leads to a reduction of the pattern depth at tight pitch and therefore limits the achievable resolution. By optimizing patterning conditions, we achieved 11 nm half-pitch dense lines in the HM8006 transfer layer and 14 nm half-pitch dense lines and L-lines in silicon. For the 14 nm half-pitch lines in silicon, we measured a line edge roughness of 2.6 nm (3σ) and a feature size of the patterned walls of 7 nm.
Nanoscale wear is a critical issue that limits the performance of tip-based nanomanufacturing and nanometrology processes based on atomic force microscopy (AFM). Yet, a full scientific understanding of nanoscale wear processes remains in its infancy. It is therefore important to quantitatively understand the wear behavior of AFM tips. Tip wear is complex to understand due to adhesive forces and contact stresses that change substantially as the contact geometry evolves due to wear. Here, we present systematic characterization of the wear of commercial Si AFM tips coated with thin diamond-like carbon (DLC) coatings. Wear of DLC was measured as a function of external loading and sliding distance. Transmission electron microscopy imaging, AFM-based adhesion measurements, and tip geometry estimation via inverse imaging were used to assess nanoscale wear and the contact conditions over the course of the wear tests. Gradual wear of DLC with sliding was observed in the experiments, and the tips evolved from initial paraboloidal shapes to flattened geometries. The wear rate is observed to increase with the average contact stress, but does not follow the classical wear law of Archard. A wear model based on the transition state theory, which gives an Arrhenius relationship between wear rate and normal stress, fits the experimental data well for low mean contact stresses (<0.3 GPa), yet it fails to describe the wear at higher stresses. The wear behavior over the full range of stresses is well described by a recently proposed multibond wear model that exhibits a change from Archard-like behavior at high stresses to a transition state theory description at lower stresses.
Single-asperity wear experiments and simulations have identified different regimes of wear including Eyring- and Archard-like behaviors. A multibond dynamics model has been developed based on the friction model of Filippov et al. [Phys. Rev. Lett. 92, 135503 (2004)]. This new model captures both qualitatively distinct regimes of single-asperity wear under a unified theoretical framework. In this model, the interfacial bond formation, wearless rupture, and transfer of atoms are governed by three competing thermally activated processes. The Eyring regime holds under the conditions of low load and low adhesive forces; few bonds form between the asperity and the surface, and wear is a rare and rate-dependent event. As the normal stress increases, the Eyring behavior of wear rate breaks down. A nearly rate-independent regime arises under high load or high adhesive forces, in which wear becomes very nearly, but not precisely, proportional to sliding distance. In this restricted regime, the dependence of wear rate per unit contact area is nearly independent of the normal stress at the point of contact. In true contact between rough elastic surfaces, where contact area is expected to grow linearly with normal load, this would lead to behavior very similar to that described by the Archard equation. Detailed comparisons to experimental and molecular dynamics simulation investigations illustrate both Eyring and Archard regimes, and an intermediate crossover regime between the two.
