Atomic layer deposition of nanocrystallite arrays of copper(I) chloride for optoelectronic structures

  • Philipp S. Maydannik
  • Gomathi Natarajan
  • David C. Cameron


Zinc blende structure γ-copper(I) chloride is a wide bandgap semiconductor with high exciton and biexciton binding energies. γ-CuCl has applications in UV-wavelength optoelectronic structures which can exploit these characteristics, such as 4-wave mixing and optical bistability. For these purposes, a controllable method of achieving thin films and nanocrystallite arrays is necessary. Atomic layer deposition (ALD) of nanocrystallites and thin films of γ-CuCl under restricted conditions has previously been demonstrated. This paper greatly extends the previous work and unequivocally confirms that ALD growth takes place over a range of deposition parameters, as characterised by growth saturation with increasing precursor dose, deposition rate independent of temperature and linear growth rate once a complete film has been formed. Arrays of nanocrystallites of different sizes can be controllably deposited by varying the number of ALD cycles within the initial nucleation region. In this region two distinct growth regimes have been observed depending on the length of the post-chloride precursor purge pulse. Long purge time results in retarded nucleation whereas short pulse time shows enhanced nucleation compared to a strictly linear process. The zinc blende γ-CuCl phase was confirmed with both X-ray analysis and also the signature excitonic Z1,2 and Z3 peaks in optical absorption, with no evidence of other impurities. This demonstrates that ALD is a suitable technique for the controllable deposition of thin films and arrays of nanocrystallites of CuCl which may facilitate the use of CuCl in thin film or nanocluster form for further exploration in optoelectronic and photonic applications.


CuCl Atomic Layer Deposition Optical Bistability Exciton Absorption Crystallite Diameter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was supported by the European Social Fund under South Savo Regional Council Grant No. ISLH-2007-0391 and Mikkeli City Council Grant No. 00143104.


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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Lappeenranta University of TechnologyMikkeliFinland
  2. 2.EL Technology ConsultingEspooFinland
  3. 3.Surface and Nano-Science DivisionIndira Gandhi Centre for Atomic ResearchChennaiIndia
  4. 4.R&D Centre for Low-Cost Plasma and Nanotechnology Surface ModificationMasaryk UniversityBrnoCzech Republic

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