Non-metallic dopant modulation of conductivity in substoichiometric tantalumpentoxide: A first-principles study

We apply density-functional theory calculations to predict dopant modulation ofelectrical conductivity (σo) for seven dopants (C, Si,Ge, H, F, N, andB) sampled at 18 quantum molecular dynamics configurations of five independent insertionsites into two (high/low) baseline references of σo in amorphou...

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Veröffentlicht in:Journal of applied physics 2017-06, Vol.121 (21)
Hauptverfasser: Bondi, Robert J, Fox, Brian P, Marinella, Matthew J
Format: Artikel
Sprache:eng
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Zusammenfassung:We apply density-functional theory calculations to predict dopant modulation ofelectrical conductivity (σo) for seven dopants (C, Si,Ge, H, F, N, andB) sampled at 18 quantum molecular dynamics configurations of five independent insertionsites 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 analyzedefect levels, physical structure, and valence charge distributions to characterizenanoscale modification of the atomistic structure in local dopant neighborhoods. Cis the most effective dopant at lowering Ta2Ox σo, while alsoexhibiting an amphoteric doping behavior by either donating or accepting charge depending on thehost oxide matrix. Both B and F robustly increase Ta2Oxσo, although F does so through elimination of Ta high charge outliers, whileB insertion conversely creates high charge O outliers through favorable BO3group formation,especially in the low σo reference. While N applications to dope and passivateoxides are prevalent, we found that N exacerbates the stochasticity of σo wesought to mitigate; sensitivity to the N insertion site and some propensity to form N-Obond chemistriesappear responsible. We use direct first-principles predictions of σo to explorefeasible Ta2O5dopants toengineer improved oxides with lower variance and greater repeatability to advance themanufacturability of resistive memory technologies.
ISSN:0021-8979
1089-7550