Virtual Simulation and Training (United States)

Minho Choi et al. (article no. 1700275) have investigated a computational high-throughput screening method to search a suitable doping element for novel phase-change materials. 29 dopants (Ag, Bi, Co, Cr, Er, Fe, Ga, Gd, Ir, Po, Rh, Ge, Ta, Nb, Sc, Zr, Mo, Si, La, Lu, Tl, V, Pr, Tb, Y, Yb, Cu, Ti, and Zn) have been screened by calculating the doping formation energy and lattice distortion angle with density functional theory when these dopants substitute each host atom – In, Sb, and Te sites in the ternary alloy In3SbTe2 (IST) in this work. Comparing with the 216 supercell model, the authors have confirmed that the 64 model is a fast and effective method to predict a suitable dopant through ab initio molecular dynamics (AIMD) simulations of lattice distortion. Theoretically, Y is predicted as an ideal dopant because of its negative doping formation energy and the largest lattice distortion. Experimentally, the Y-doped IST shows excellent thermodynamic stability and a fast switching at lower power consumption.

Respirators are currently approved by testing them on a number of subjects without specifying facial sizes. Anthropometrically designed test panels were developed that represent the majority of the working population in terms of relevant facial measurements.