Damage Accumulation in Silica Glass Nanofibers

Abstract

The origin of the brittle-to-ductile transition, experimentally observed in amorphous silica nanofibers as the sample size is reduced, is still debated. Here we investigate the issue by extensive molecular dynamics simulations at low and room temperatures for a broad range of sample sizes, with open and periodic boundary conditions. Our results show that small sample-size enhanced ductility is primarily due to diffuse damage accumulation, that for larger samples leads to brittle catastrophic failure. Surface effects such as boundary fluidization contribute to ductility at room temperature by promoting necking, but are not the main driver of the transition. Our results suggest that the experimentally observed size-induced ductility of silica nanofibers is a manifestation of finite-size criticality, as expected in general for quasi-brittle disordered networks.

Avalanches and Structural Change in Cyclically Sheared Silica Glass

“…Despite such consistent analysis within the framework of [51], the large value of τ c is surprising. Similar values have been discussed for silica nanofibres [56], amorphous silicon [58] and in preliminary results for a short ranged silica-like model [75]. Although the details in these systems differ, we speculate that the open framework structure common to these systems may provide an explanation.…”

“…Computational investigations of yielding in amorphous solids described above have largely been performed for solids with particles interacting with spherically symmetric, short ranged interactions. In particular, relatively few studies [37,[52][53][54][55][56] have addressed the archetypal glass, silica, which is characterised by an open, tetrahedral, local geometry, and whose interaction potential includes long range Coulomb interactions (or silicon [57][58][59][60], which shares several geometric and thermodynamic characteristics). In the liquid state, the tetrahedral network structure of silica entails a rich spectrum of novel behavior, including density maxima [61,62], a liquidliquid phase transition [63,64] and a strong-to-fragile transition [65][66][67][68].…”

Athermal Fracture of Elastic Networks: How Rigidity Challenges the Unavoidable Size-Induced Brittleness

“…∆σ max is the maximum stress drop and it is calculated following a procedure highlighted in Ref. [36]. It consists of (i) calculating the derivative of the stress-strain curve; (ii) identifying the strain interval for which the derivative is greater than a certain threshold (here we use zero, but we checked that our results are robust using different thresholds); (iii) for each strain interval, calculate the stress drop as the difference in the stress associated to the extremal values of the interval; (iv) the maximum stress drop is ∆σ max .…”

The role of temperature in the rigidity-controlled fracture of elastic networks

“…The peak stress s p is defined as the highest measured stress, and the peak strain e p is its corresponding strain value. The maximum stress drop Ds max is calculated according to a procedure 13,32 where we (i) calculate the derivative of the stress-strain curve, (ii) make a list of consecutive data points which have a negative derivative and note the initial and final strain of each interval, (iii) calculate the stress drops by subtracting the stress at the final strain from the stress at the initial strain, (iv) identify the largest stress interval, which corresponds to maximum stress drop Ds max . For the stress distribution analysis, we make instantaneous histograms of the bond lengths c i during the simulation at every percent strain.…”