Evaluation of the concentration of point defects in GaN

Reshchikov, M. A.; Usikov, A.; Helava, H.; Makarov, Yu.N.; Prozheeva, Vera; Makkonen, Ilja; Tuomisto, Filip; Leach, J. H.; Udwary, K.

doi:10.1038/s41598-017-08570-1

Cited by 63 publications

(74 citation statements)

References 46 publications

(77 reference statements)

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“…In addition, after 2-4 years following the initial analysis of these samples, the PL intensity and spectrum for sample H3 have changed, which explains the remaining difference by up to a factor of 3 between the concentrations for sample H3 reported in ref. 12 and in the current work.…”

Section: Resultssupporting

confidence: 54%

“…Note that the values for samples H3 and H202 in Table 2 differ from those reported for the same samples in ref. 12 . The main reason is that in the current work PL spectra measured as a function of wavelength λ were multiplied by λ 3 to represent PL spectra in units proportional to the number of emitted photons as a function of photon energy (see Methods).…”

Section: Resultsmentioning

confidence: 99%

“…4 , the concentration of defects responsible for the RL1 band was underestimated by a factor of 2 and that for the UVL band was overestimated by a factor of 3 in ref. 12 . In addition, after 2-4 years following the initial analysis of these samples, the PL intensity and spectrum for sample H3 have changed, which explains the remaining difference by up to a factor of 3 between the concentrations for sample H3 reported in ref.…”

Section: Resultsmentioning

confidence: 99%

“… , E 0 is the ZPL energy, and Ω is energy of the dominant phonon mode in the excited state. The concentration of defects, N, responsible for the UVL, YL1 and RL1 bands can be determined at 100 K from the dependence of the absolute internal quantum efficiency (IQE) of PL, η, on the excitation intensity, P exc , or the excitation photon flux, P 0 , as explained elsewhere 12,24,25 . The η P ( ) 0 dependence can be fitted with the following expression Fig.…”

Section: Rl1 Band Yl1 Band (C N ) Uvl Band (Mgmentioning

confidence: 99%

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Determination of the concentration of impurities in GaN from photoluminescence and secondary-ion mass spectrometry

Reshchikov

Vorobiov

Andrieiev

et al. 2020

Sci Rep

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photoluminescence (pL) was used to estimate the concentration of carbon in Gan grown by hydride vapor phase epitaxy (HVPE). The PL data were compared with profiles of the impurities obtained from secondary ion mass spectrometry (SiMS) measurements. comparison of pL and SiMS data has revealed that apparently high concentrations of C and O at depths up to 1 µm in SIMS profiles do not represent depth distributions of these species in the Gan matrix but are rather caused by post-growth surface contamination and knocking-in impurity species from the surface. in particular, pL analysis supplemented by reactive ion etching up to the depth of 400 nm indicates that the concentration of carbon in nitrogen sites is below 2-5 × 10 15 cm −3 at any depth of Gan samples grown by HVpe. We demonstrate that pL is a very sensitive and reliable tool to determine the concentrations of impurities in the Gan matrix.GaN is a key material in modern solid-state lighting technology. The investigation and identification of point defects in GaN is very important, with immediate technology relevance to longer lifetime of light-emitting devices. Photoluminescence (PL) is a powerful tool for investigation of point defects in GaN 1 . Only few point defects in unintentionally doped GaN are well understood and reliably identified. One of them is the C N defect with the −/0 and 0/ + thermodynamic transition levels at 0.916 eV and ~0.3 eV, respectively, above the valence band 2-5 . This defect is responsible for the yellow luminescence (YL1) band with a maximum at 2.2 eV and zero phonon line (ZPL) at 2.59 eV in n-type GaN. Transitions via the 0/ + level of this defect can be observed as the blue luminescence (BL C ) band with a maximum at 3.3 eV at high excitation intensity 4 . The YL1 band is commonly observed in n-type GaN layers grown by metalorganic chemical vapor deposition (MOCVD), where the concentration of unintentionally introduced carbon is usually in the range of 10 16 -10 18 cm −3 , depending on growth conditions 6,7 . Undoped or Si-doped GaN samples grown by hydride vapor phase epitaxy (HVPE) contain much less carbon (10 15 -10 16 cm −3 ) 8-11 , yet still the YL1 band may be strong in these samples due to high hole-capture cross-section for the C N defects 12 .We have recently demonstrated 12 that PL can be used for determination of concentrations of defects responsible for PL bands. However, the concentrations of impurities found from PL were inconsistent with the concentrations found from secondary-ion mass spectrometry (SIMS) analysis in that study. Comparison of these two techniques is complicated by the following ambiguity. SIMS measurements provide depth profiles of impurity concentrations regardless of positions of impurity species (lattice sites or precipitations), whereas PL signal, excited with above-bandgap light, is collected from impurity atoms at lattice sites in the near-surface region (roughly, top 0.4 µm layer in GaN). The problem is that close to the surface, where PL is collected, very high concentrations of carbon an...

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Section: Resultssupporting

confidence: 54%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Rl1 Band Yl1 Band (C N ) Uvl Band (Mgmentioning

confidence: 99%

See 2 more Smart Citations

Determination of the concentration of impurities in GaN from photoluminescence and secondary-ion mass spectrometry

Reshchikov

Vorobiov

Andrieiev

et al. 2020

Sci Rep

Self Cite

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“…[1][2][3] Translating this wealth of information to a microscopic identification of a given defect requires comparison with theoretical or computational models, and first-principles calculations based on density functional theory (DFT) have proven very helpful. [4][5][6][7][8] One of the key quantities measured in DLTS is the activation energy for carrier emission from a defect, ∆E a . Defect identification is often based on comparing ∆E a with values of the defect ionization energy ∆E i determined from zero-temperature first-principles calculations.…”

mentioning

confidence: 99%

Defect identification based on first-principles calculations for deep level transient spectroscopy

Wickramaratne

Dreyer

Monserrat

et al. 2018

Applied Physics Letters

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Deep level transient spectroscopy (DLTS) is used extensively to study defects in semiconductors. We demonstrate that great care should be exercised in interpreting activation energies extracted from DLTS as ionization energies. We show how first-principles calculations of thermodynamic transition levels, temperature effects of ionization energies, and nonradiative capture coefficients can be used to accurately determine actual activation energies that can be directly compared with DLTS. Our analysis is illustrated with hybrid functional calculations for two important defects in GaN that have similar thermodynamic transition levels, and shows that the activation energy extracted from DLTS includes a capture barrier that is temperature dependent, unique to each defect, and in some cases large in comparison to the ionization energy. By calculating quantities that can be directly compared with experiment, first-principles calculations thus offer powerful leverage in identifying the microscopic origin of defects detected in DLTS.PACS numbers: 72.20.Jv, 84.37.+q Point defects and impurities are present in all semiconductors. They can act as recombination centers that lower the efficiency of optoelectronic devices, or as carrier traps in electronic devices such as transistors. Microscopic identification of the detrimental defects is crucial in order to mitigate their impact. Deep level transient spectroscopy (DLTS) is a powerful technique for determining the properties of defects; from an analysis of electrical measurements on a pn junction or Schottky diode, properties such as the position of the defect level within the band gap, electrical nature (donor or acceptor), density, and carrier capture cross section of specific defects can be obtained. [1][2][3] Translating this wealth of information to a microscopic identification of a given defect requires comparison with theoretical or computational models, and first-principles calculations based on density functional theory (DFT) have proven very helpful. [4][5][6][7][8] One of the key quantities measured in DLTS is the activation energy for carrier emission from a defect, ∆E a . Defect identification is often based on comparing ∆E a with values of the defect ionization energy ∆E i determined from zero-temperature first-principles calculations. However, the underlying theory of DLTS 2,3 makes clear that ∆E a and ∆E i are distinct, and the use of ∆E i can affect the correct identification of a defect.In the present study we describe a first-principles approach to explicitly determine the activation energies measured in DLTS. Recent advances have enabled the quantitative prediction of defect levels in the band gap 9 and the ability to accurately describe nonradiative carrier capture. 10 We will show that ∆E a can significantly differ from ∆E i for some defects, demonstrating the need to explicitly calculate the activation energy in order to correctly identify defects detected by DLTS. Our analysis is general, but will be illustrated with examples of deep defects in GaN...

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Reducing Atomic Defects in 2D Transition Metal Dichalcogenides

Zhang,

Wang,

Nong

et al. 2024

Adv Funct Materials

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Preparing high‐quality 2D semiconductors represented by transition metal dichalcogenides (TMDCs) is of great importance for the next‐generation devices. However, currently available 2D TMDCs contain many atomic defects, which greatly affect their electronic and optical properties. This review starts with the formation of atomic defects and their effects on the properties of 2D TMDCs. Then, techniques for characterizing atomic defects are systematically summarized, including atomic‐resolution imaging and spectroscopy measurements. Further, recent progress on defect suppression during growth and defect repair after growth is reviewed. Finally, challenges and opportunities in this important field are discussed.

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Evaluation of the concentration of point defects in GaN

Cited by 63 publications

References 46 publications

Determination of the concentration of impurities in GaN from photoluminescence and secondary-ion mass spectrometry

Determination of the concentration of impurities in GaN from photoluminescence and secondary-ion mass spectrometry

Defect identification based on first-principles calculations for deep level transient spectroscopy

Reducing Atomic Defects in 2D Transition Metal Dichalcogenides

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