Predicting Low Energy Dopant Implant Profiles in Semiconductors using Molecular Dynamics

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The authors present a highly efficient molecular dynamics scheme for calculating dopant density profiles in group-IV alloy, and III-V zinc blende structure materials. Their scheme incorporates several necessary methods for reducing computational overhead, plus a rare event algorithm to give statistical accuracy over several orders of magnitude change in the dopant concentration. The code uses a molecular dynamics (MD) model to describe ion-target interactions. Atomic interactions are described by a combination of 'many-body' and pair specific screened Coulomb potentials. Accumulative damage is accounted for using a Kinchin-Pease type model, inelastic energy loss is represented by a Firsov expression, and electronic ... continued below

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Beardmore, K.M. & Gronbech-Jensen, N. May 2, 1999.

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The authors present a highly efficient molecular dynamics scheme for calculating dopant density profiles in group-IV alloy, and III-V zinc blende structure materials. Their scheme incorporates several necessary methods for reducing computational overhead, plus a rare event algorithm to give statistical accuracy over several orders of magnitude change in the dopant concentration. The code uses a molecular dynamics (MD) model to describe ion-target interactions. Atomic interactions are described by a combination of 'many-body' and pair specific screened Coulomb potentials. Accumulative damage is accounted for using a Kinchin-Pease type model, inelastic energy loss is represented by a Firsov expression, and electronic stopping is described by a modified Brandt-Kitagawa model which contains a single adjustable ion-target dependent parameter. Thus, the program is easily extensible beyond a given validation range, and is therefore truly predictive over a wide range of implant energies and angles. The scheme is especially suited for calculating profiles due to low energy and to situations where a predictive capability is required with the minimum of experimental validation. They give examples of using the code to calculate concentration profiles and 2D 'point response' profiles of dopants in crystalline silicon and gallium-arsenide. Here they can predict the experimental profile over five orders of magnitude for <100> and <110> channeling and for non-channeling implants at energies up to hundreds of keV.

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Medium: P; Size: vp.

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OSTI as DE00758946

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  • 195th Semi-Annual Meeting of the Electrochemical Society, Seattle, WA (US), 05/02/1999--05/06/1999

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  • Report No.: LA-UR-99-1035
  • Grant Number: W-7405-ENG-36
  • Office of Scientific & Technical Information Report Number: 758946
  • Archival Resource Key: ark:/67531/metadc708514

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  • May 2, 1999

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  • Sept. 12, 2015, 6:31 a.m.

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  • May 6, 2016, 1:51 p.m.

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Beardmore, K.M. & Gronbech-Jensen, N. Predicting Low Energy Dopant Implant Profiles in Semiconductors using Molecular Dynamics, article, May 2, 1999; New Mexico. (digital.library.unt.edu/ark:/67531/metadc708514/: accessed August 18, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.