Recent studies have demonstrated that amorphous materials, from granular packings to atomic glasses, share multiple striking similarities, including a universal onset strain level for yield. This is despite vast differences in length scales and in the constituent particles' interactions. However, the nature of localized particle rearrangements is not well understood, and how local interactions affect overall performance remains unknown. Here, we introduce a multiscale adhesive discrete element method to simulate recent novel experiments of disordered nanoparticle packings indented and imaged with single nanoparticle resolution. The simulations exhibit multiple behaviors matching the experiments. By directly monitoring spatial rearrangements and interparticle bonding/debonding under the packing's surface, we uncover the mechanisms of the yielding and hardening phenomena observed in experiments. Interparticle friction and adhesion synergistically toughen the packings and retard plastic deformation. Moreover, plasticity can result from bond switching without particle rearrangements. These results furnish insights for understanding yielding in amorphous materials generally.

Nanoindentation experiments on disordered nanoparticle packings performed both in an atomic force microscope and in situ in a transmission electron microscope are used to investigate the mechanics of plastic deformation. Under an applied load, these highly porous films exhibit load drops, the magnitudes of which are consistent with an exponential population distribution. These load drops are attributed to local rearrangements of a small number of particles, which bear similarities to shear transformation zones and to the T1 process, both of which have been previously predicted for disordered packings. An increase in the relative humidity results in an increase in the number of observed load drops, indicating that the strength of the particle interactions has a significant effect on the modes of plastic deformation. These results suggest how disordered nanoparticle packings may be expected to behave in devices operating under varying environments.

When deformed beyond their elastic limits, crystalline solids flow plastically via particle rearrangements localized around structural defects. Disordered solids also flow, but without obvious structural defects. We link structure to plasticity in disordered solids via a microscopic structural quantity, "softness," designed by machine learning to be maximally predictive of rearrangements. Experimental results and computations enabled us to measure the spatial correlations and strain response of softness, as well as two measures of plasticity: the size of rearrangements and the yield strain. All four quantities maintained remarkable commonality in their values for disordered packings of objects ranging from atoms to grains, spanning seven orders of magnitude in diameter and 13 orders of magnitude in elastic modulus. These commonalities link the spatial correlations and strain response of softness to rearrangement size and yield strain, respectively.

Atomic force microscopy-based nanoindentation is used to image and probe the local mechanical properties of thin disordered nanoparticle packings. The probed region is limited to the size of a few particles, and an individual particle can be loaded and displaced to a fraction of a single particle radius. The results demonstrate heterogeneous mechanical response that is location-dependent. The weak locations may be analogous to the "soft spots" previously predicted in glasses and other disordered packings.

To describe adhesion between bodies of known arbitrary shape and known elastic properties, contact mechanics models require knowledge or assumptions of a minimum of two parameters, the strength of the adhesive interaction (characterized by the intrinsic work of adhesion W adh,int ) and the length scale of the interaction (described by the range of adhesion z 0 ). One parameter can easily be measured if the other is estimated or assumed, but experimental techniques for determining both simultaneously are lacking. Here, we demonstrate a novel technique—called the Snap-in/pull-off Numerical Adhesion Parameter method—for experimentally determining both parameters simultaneously using adhesion measurements performed with an atomic force microscope probe whose geometry has been characterized. The method applies to materials that approach the rigid limit (high elastic moduli). The technique is explained and validated analytically for simple shapes (flat punch, paraboloid, and right cone), and trends in results are compared against prior literature. This approach allows calculation of the adhesion parameters to enable prediction of adhesion behavior, including for advanced technology applications.

The adhesive interactions between nanoscale silicon atomic force microscope (AFM) probes and a diamond substrate are characterized using in situ adhesion tests inside of a transmission electron microscope (TEM). In particular, measurements are presented both for the strength of the adhesion acting between the two materials (characterized by the intrinsic work of adhesion Wadh,int) and for the length scale of the interaction (described by the range of adhesion z0). These values are calculated using a novel analysis technique that requires measurement of the AFM probe geometry, the adhesive force, and the position where the snap‐in instability occurs. Values of Wadh = 0.66 J m−2 and z0 = 0.25 nm are extracted using this technique. This value of work of adhesion is 70% higher than the work of adhesion calculated if one uses a conventional paraboloidal asperity model. Comparing to literature, the work of adhesion obtained using the new method is significantly higher than most experimental and simulation values for similar material pairs. The discrepancy is attributed to nanoscale roughness, which was not accounted for previously. Furthermore, the value of the range of adhesion is comparable to previously reported values, but is significantly larger than the commonly assumed value of the interatomic spacing.

Cerebrospinal fluid (CSF) is produced at a constant rate in the choroid plexuses of the lateral and third ventricles, and it predominately drains through the Sylvius aqueduct to the fourth ventricle. If the Sylvius aqueduct becomes obstructed, such as caused by a growing tumor adjacent to it, CSF accumulates in the ventricles and the ventricles expand significantly, leading to a medical condition known as noncommunicating, hydrocephalus.

A biphasic model for noncommunicating hydrocephalus in patient-specific geometry is proposed. The model can take into account the nonlinear behavior of brain tissue under large deformation, the nonlinear variation of hydraulic conductivity with deformation, and contact with a rigid, impermeable skull using a recently developed algorithm. The model was capable of achieving over a 700 percent ventricular enlargement, which is much greater than in previous studies, primarily due to the use of an anatomically realistic skull recreated from magnetic resonance imaging rather than an artificial skull created by offsetting the outer surface of the cerebrum. The choice of softening or stiffening behavior of brain tissue, both having been demonstrated in previous experimental studies, was found to have a significant effect on the volume and shape of the deformed ventricle, and the consideration of the variation of the hydraulic conductivity with deformation had a modest effect on the deformed ventricle. The model predicts that noncommunicating hydrocephalus occurs for ventricular fluid pressure on the order of 1300 Pa.

The effect of atomic-scale roughness on adhesion between carbon-based materials is examined by both simulations and experimental techniques. Nanoscale asperities composed of either diamond-like carbon or ultrananocrystalline diamond are brought into contact and then separated from diamond surfaces using both molecular dynamics simulations and in situ transmission electron microscope (TEM)-based nanoindentation. Both techniques allow for characterization of the roughness of the sharp nanoasperities immediately before and after contact down to the subnanometer scale. The root mean square roughness for the simulated tips spanned 0.03 nm (atomic corrugation) to 0.12 nm; for the experimental tips, the range was 0.18–1.58 nm. Over the tested range of roughness, the measured work of adhesion was found to decrease by more than an order of magnitude as the roughness increased. The dependence of adhesion upon roughness was accurately described using a simple analytical model. This combination of simulation and experimental methodologies allows for an exploration of an unprecedented range of tip sizes and length scales for roughness, while also verifying consistency of the results between the techniques. Collectively, these results demonstrate the high sensitivity of adhesion to interfacial roughness down to the atomic limit. Furthermore, they indicate that care must be taken when attempting to extract work of adhesion values from experimental measurements of adhesion forces.

In a healthy brain, a continuous flow of cerebrospinal fluid (CSF) is produced in the choroid plexus, located in the lateral ventricles. Most of the CSF drains via the Sylvius aqueduct into the subarachnoid space around the brain, but a small amount flows directly through the cerebrum into the subarachnoid space inside the skull. Non-communicating hydrocephalus occurs when an obstruction blocks the Sylvius aqueduct. Because the cerebrum has only limited capacity for CSF to flow through it, CSF accumulates in the ventricles, yielding a significant increase in ventricular volume and deformation of the cerebrum, which may lead to tissue damage.