Title: Kinetic Simulations of Cu Doping in Chlorinated CdSeTe PV Absorbers

Journal Article · · Physica Status Solidi. A, Applications and Materials Science
ORCiD logo [1];  [2]
  1. First Solar, Inc., Perrysburg, OH (United States); Arizona State University
  2. First Solar, Inc., Perrysburg, OH (United States)

This paper reports on 1D kinetic modeling of p-type doping formation in Cu-doped chlorinated CdSeTe photovoltaic (PV) absorbers with graded Se profiles. Following the recent progress in kinetic simulations of the defect chemistry in stoichiometric CdTe films, this work extends simulation capabilities to a domain of semiconductor alloy films with graded stoichiometries. The defect formation energies and ionization levels, as well as the diffusion and reaction barriers used in the reaction-diffusion equations are calculated from the first principles. A new formalism is employed to account for the uncertainty of the defect formation energies in semiconductor alloys caused by unknown local surrounding. Finally, the developed methodology is used to model a practical fabrication process of p-type doping formation in graded CdSeTe absorbers and to study the effect of alloy stoichiometry on the doping activation.

Research Organization:
Arizona State Univ., Tempe, AZ (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Solar Energy Technologies Office (EE-4S)
Grant/Contract Number:
EE0006344; EE0007536
OSTI ID:
1592014
Journal Information:
Physica Status Solidi. A, Applications and Materials Science, Journal Name: Physica Status Solidi. A, Applications and Materials Science Journal Issue: 15 Vol. 216; ISSN 1862-6300
Publisher:
WileyCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (3)

Radiative Efficiency and Charge‐Carrier Lifetimes and Diffusion Length in Polycrystalline CdSeTe Heterostructures journal December 2019
Radiative Efficiency and Charge‐Carrier Lifetimes and Diffusion Length in Polycrystalline CdSeTe Heterostructures journal January 2020
Machine-learned impurity level prediction for semiconductors: the example of Cd-based chalcogenides journal April 2020