4.8 Article

Dysprosium-doped cadmium oxide as a gateway material for mid-infrared plasmonics

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NATURE MATERIALS
卷 14, 期 4, 页码 414-420

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NATURE PORTFOLIO
DOI: 10.1038/NMAT4203

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资金

  1. NSF grant [CHE-1112017, DMR-1151568]
  2. US Department of Energy's National Nuclear Security Administration [DE-AC04-94AL85000]
  3. Air Force Office of Scientific Research under AFOSR [FA9550-14-1-0067, 5010-UV-AFOSR-0067]
  4. ONR Young Investigator Program [N00014-13-4-0528]
  5. Duke Center for Materials Genomics
  6. ONR [MURI N00014-13-1-0635]
  7. Division Of Chemistry [1112017] Funding Source: National Science Foundation

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The interest in plasmonic technologies surrounds many emergent optoelectronic applications, such as plasmon lasers, transistors, sensors and information storage. Although plasmonic materials for ultraviolet-visible and near-infrared wavelengths have been found, the mid-infrared range remains a challenge to address: few known systems can achieve subwavelength optical confinement with low loss in this range. With a combination of experiments and ab initio modelling, here we demonstrate an extreme peak of electron mobility in Dy-doped CdO that is achieved through accurate 'defect equilibrium engineering'. In so doing, we create a tunable plasmon host that satisfies the criteria for mid-infrared spectrum plasmonics, and overcomes the losses seen in conventional plasmonic materials. In particular, extrinsic doping pins the CdO Fermi level above the conduction band minimum and it increases the formation energy of native oxygen vacancies, thus reducing their populations by several orders of magnitude. The substitutional lattice strain induced by Dy doping is sufficiently small, allowing mobility values around 500 cm(2) V-1 s(-1) for carrier densities above 10(20) cm(3). Our work shows that CdO: Dy is a model system for intrinsic and extrinsic manipulation of defects affecting electrical, optical and thermal properties, that oxide conductors are ideal candidates for plasmonic devices and that the defect engineering approach for property optimization is generally applicable to other conducting metal oxides.

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