Computational Characterization of the Structure, Energy, Strengths, and Fracture Resistances of Symmetric Tilt Grain Boundaries in Ice.

Using an interatomic potential that can capture the tetrahedral configuration of water molecules (HO) in ice without the need to explicitly track the motion of the O and H atoms, coarse-grained (CG) atomistic simulations are performed here to characterize the structures, energy, cohesive strengths, and fracture resistance of the grain boundaries (GBs) in polycrystalline ice resulting from water freezing. Taking the symmetric tilt grain boundaries (STGBs) with a tilting axis of ⟨0001⟩ as an example, several main findings from our simulations are (i) the GB energy, , exhibits a strong dependence on the GB misorientation angle, θ. The classical Read-Shockley model only predicts the - θ relation reasonably well when θ < 20° or θ > 45° but fails when 20° < θ < 45°; (ii) two "valleys" appear in the -θ landscape.

Quantitative matching of forensic evidence fragments using fracture surface topography and statistical learning.

The complex jagged trajectory of fractured surfaces of two pieces of forensic evidence is used to recognize a "match" by using comparative microscopy and tactile pattern analysis. The material intrinsic properties and microstructures, as well as the exposure history of external forces on a fragment of forensic evidence have the premise of uniqueness at a relevant microscopic length scale (about 2-3 grains for cleavage fracture), wherein the statistics of the fracture surface become non-self-affine. We utilize these unique features to quantitatively describe the microscopic aspects of fracture surfaces for forensic comparisons, employing spectral analysis of the topography mapped by three-dimensional microscopy.

Quantitative matching of forensic evidence fragments utilizing 3D microscopy analysis of fracture surface replicas.

Silicone casts are widely used by practitioners in the comparative analysis of forensic items. Fractured surfaces carry unique details that can provide accurate quantitative comparisons of forensic fragments. In this study, a statistical analysis comparison protocol was applied to a set of 3D topological images of fractured surface pairs and their replicas to provide confidence in the quantitative statistical comparison between fractured items and their silicone cast replicas.

Classification with the matrix-variate- distribution.

Matrix-variate distributions can intuitively model the dependence structure of matrix-valued observations that arise in applications with multivariate time series, spatio-temporal or repeated measures. This paper develops an Expectation-Maximization algorithm for discriminant analysis and classification with matrix-variate -distributions. The methodology shows promise on simulated datasets or when applied to the forensic matching of fractured surfaces or the classification of functional Magnetic Resonance, satellite or hand gestures images.

A highly stretchable double-network composite.

Inspired by the toughening mechanism of double-network (DN) hydrogels, a soft composite consisting of a fabric mesh and VHB tape layers was fabricated. The composite was as stiff as the fabric mesh, and as stretchable as the VHB tape. At certain compositions, the composite was significantly stronger and tougher than the base materials.

Magnetorheological brush - a soft structure with highly tuneable stiffness.

By combining the field-stiffening effect of magnetorheological (MR) elastomers and the Euler buckling mechanism, we developed a brush-like magneto-active structure with highly tuneable stiffness. When the applied mechanical load is within a certain range, the effective stiffness of the structure can be tuned by several orders of magnitude with the applied magnetic field. The performance of the structure and its dependence on various synthesis parameters, such as the curing field and filler concentration, were investigated experimentally.