Publications

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We apply density-functional theory calculations to predict dopant modulation of electrical conductivity (σo) for seven dopants (C, Si, Ge, H, F, N, and B) sampled at 18 quantum molecular dynamics configurations of five independent insertion sites into two (high/low) baseline references of σo in amorphous Ta2O5, where each reference contains a single, neutral O vacancy center (VO0). From this statistical population (n = 1260), we analyze defect levels, physical structure, and valence charge distributions to characterize nanoscale modification of the atomistic structure in local dopant neighborhoods. C is the most effective dopant at lowering Ta2Ox σo, while also exhibiting an amphoteric doping behavior by either donating or accepting charge depending on the host oxide matrix. Both B and F robustly increase Ta2Ox σo, although F does so through elimination of Ta high charge outliers, while B insertion conversely creates high charge O outliers through favorable BO3 group formation, especially in the low σo reference. While N applications to dope and passivate oxides are prevalent, we found that N exacerbates the stochasticity of σo we sought to mitigate; sensitivity to the N insertion site and some propensity to form N-O bond chemistries appear responsible. We use direct first-principles predictions of σo to explore feasible Ta2O5 dopants to engineer improved oxides with lower variance and greater repeatability to advance the manufacturability of resistive memory technologies.

First-principles calculations of electrical conductivity (σo) are revisited to determine the atomistic origin of its stochasticity in a distribution generated from sampling 14 ab-initio molecular dynamics configurations from 10 independently quenched models (n = 140) of substoichiometric amorphous Ta2O5, where each structure contains a neutral O monovacancy (VO0). Structural analysis revealed a distinct minimum Ta-Ta separation (dimer/trimer) corresponding to each VO0 location. Bader charge decomposition using a commonality analysis approach based on the σo distribution extremes revealed nanostructural signatures indicating that both the magnitude and distribution of cationic charge on the Ta subnetwork have a profound influence on σo. Furthermore, visualization of local defect structures and their electron densities reinforces these conclusions and suggests σo in the amorphous oxide is best suppressed by a highly charged, compact Ta cation shell that effectively screens and minimizes localized VO0 interaction with the a-Ta2O5 network; conversely, delocalization of VO0 corresponds to metallic character and high σo. The random network of a-Ta2O5 provides countless variations of an ionic configuration scaffold in which small perturbations affect the electronic charge distribution and result in a fixed-stoichiometry distribution of σo; consequently, precisely controlled and highly repeatable oxide fabrication processes are likely paramount for advancement of resistive memory technologies.