No Arabic abstract
Ever since its publication, the Griffith theory is the most widely used criterion for estimating the ideal strength and fracture strength of materials depending on whether the materials contain cracks or not. A Griffith strength limit of ~E/9 is the upper bound for ideal strengths of materials. With the improved quality of fabricated samples and the power of computational modeling, people have recently reported the possibility of exceeding the ideal strength predicted by the Griffith theory. In this study, a new strength criterion was established based on the stable analysis of thermodynamical systems; then first-principles density functional theory (DFT) is used to study the ideal strength of four materials (diamond, c-BN, Cu, and CeO2) under uniaxial tensile loading along the [100], [110], and [111] low-index crystallographic directions. By comparing the ideal strengths between DFT results and the Griffith theory, it is found that the Griffith theory fails in all the four materials. Further analysis of the fracture mechanism demonstrates that the failure of the Griffith theory is because the ideal strength point does not correspond to creating of new surfaces, which is against the Griffith assumption that the crack intrinsically exists all the time; the failure point corresponds to the crack at the start of propagation.
We study the mechanical properties of two-dimensional (2D) boron, borophenes, by first-principles calculations. The recently synthesized borophene with 1/6 concentration of hollow hexagons (HH) is shown to have in-plane modulus C up to 210 N/m and bending stiffness as low as D = 0.39 eV. Thus, its Foppl-von Karman number per unit area, defined as C/D, reaches 568 nm-2, over twofold higher than graphenes value, establishing the borophene as one of the most flexible materials. Yet, the borophene has a specific modulus of 346 m2/s2 and ideal strengths of 16 N/m, rivaling those (453 m2/s2 and 34 N/m) of graphene. In particular, its structural fluxionality enabled by delocalized multi-center chemical bonding favors structural phase transitions under tension, which result in exceptionally small breaking strains yet highly ductile breaking behavior. These mechanical properties can be further tailored by varying the HH concentration, and the boron sheet without HHs can even be stiffer than graphene against tension. The record high flexibility combined with excellent elasticity in boron sheets can be utilized for designing composites and flexible systems.
Based on the first-principles calculations, we perform an initiatory statistical assessment on the reliability level of theoretical positron lifetime of bulk material. We found the original generalized gradient approximation (GGA) form of the enhancement factor and correlation potentials overestimates the effect of the gradient factor. Furthermore, an excellent agreement between model and data with the difference being the noise level of the data is found in this work. In addition, we suggest a new GGA form of the correlation scheme which gives the best performance. This work demonstrates that a brand-new reliability level is achieved for the theoretical prediction on positron lifetime of bulk material and the accuracy of the best theoretical scheme can be independent on the type of materials.
We note that the social inequality, represented by the Lorenz function obtained plotting the fraction of wealth possessed by the faction of people (starting from the poorest in an economy), or the plot or function representing the citation numbers against the respective number of papers by a scientist (starting from the highest cited paper in scientometrics), captured by the corresponding inequality indices (namely the Kolkata $k$ and the Hirsch $h$ indices respectively), are given by the fixed points of these nonlinear functions. It has been shown that under extreme competitions (in the markets or in the universities), the $k$ index approaches to an universal limiting value, as the dynamics of competition progresses. We introduce and study these indices for the inequalities of (pre-failure) avalanches (obtainable from ultrasonic emissions), given by their nonlinear size distributions in the Fiber Bundle Models (FBM) of non-brittle materials. We will show how a prior knowledge of this terminal and (almost) universal value of the $k$ index (for a range of values of the Weibull modulus characterizing the disorder, and also for uniformly dispersed disorder, in the FBM) for avalanche distributions (as the failure dynamics progresses) can help predicting the point (stress) or time (for uniform increasing rate of stress) for complete failure of the bundle. This observation has also been complemented by noting a similar (but not identical) behavior of the Hirsch index ($h$), redefined for such avalanche statistics.
We present a general prediction scheme of failure times based on updating continuously with time the probability for failure of the global system, conditioned on the information revealed on the pre-existing idiosyncratic realization of the system by the damage that has occurred until the present time. Its implementation on a simple prototype system of interacting elements with unknown random lifetimes undergoing irreversible damage until a global rupture occurs shows that the most probable predicted failure time (mode) may evolve non-monotonically with time as information is incorporated in the prediction scheme. In addition, both the mode, its standard deviation and, in fact, the full distribution of predicted failure times exhibit sensitive dependence on the realization of the system, similarly to ``chaos in spinglasses, providing a multi-dimensional dynamical explanation for the broad distribution of failure times observed in many empirical situations.
Recent studies showed that hardness, a complex property, can be calculated using very simple approaches or even analytical formulae. These form the basis for evaluating controversial experimental results (as we illustrate for TiO2-cotunnite) and enable a systematic search for novel hard materials, for instance, using global optimization algorithms (as we show on the example of SiO2 polymorphs).