Si/SiO2 interface states and neutral oxide traps induced by surface microroughness

Kimura, Mikihiro; Mitsuhashi, J.; Koyama, Hiroshi

doi:10.1063/1.358909

Cited by 23 publications

(6 citation statements)

References 22 publications

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“…In some cases the glass surface morphology and overall roughness has become the threshold for the continued development of novel electronics and portable devices [3,4]. The surface morphology, chemical composition and homogeneity of glass manufacturing products can influence a wide variety of performance related properties including the mechanical strength and chemical durability [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Quantitative morphological and compositional evaluation of laboratory prepared aluminoborosilicate glass surfaces

Gong¹,

Wren²,

Mellott³

2015

Applied Surface Science

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a b s t r a c tSurface finishing techniques including polishing, etching and heat treatment can modify the topography and the surface chemical composition of glasses. It is widely acknowledged that atomic force microscopy (AFM) can be used to quantify the morphology of surfaces, providing various parameters including average, peak-to-valley, and apparent root-mean-square roughness. Furthermore advanced power spectral density (PSD) analysis of AFM-derived surface profiles offers quantification of the spatial homogeneity of roughness values along different wavelengths, resulting in parameters including equivalent RMS, Hurst exponent, and fractal dimension. Outermost surface (∼8 nm) chemical composition can be quantitatively measured by X-ray photoelectron spectroscopy. In this paper, we first developed a series of surface finishing methods for an aluminoborosilicate glass system by polishing, etching or heat treatment. The chemical composition and environment of prepared glass surfaces were quantified by XPS and topographical analysis was carried out by fractal and k-correlation model fitting of PSD profiles derived via AFM. The chemical environment of elements, as determined via XPS, present on the prepared surfaces are similar to those within the pristine bulk glass. The compositional evolution of polished and melt surfaces are discussed in context of corrosion phenomena associated with the grinding, polishing, and etching of surfaces and the thermal heat treatment utilized for processing, respectively. Good correlation between surface finishing methods, chemical composition and topographical parameters were observed. More importantly, extensive discussions on topographical parameters including equivalent RMS, Hurst exponent, and fractal dimension are presented as a function of processing method.

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Section: Introductionmentioning

confidence: 99%

Quantitative morphological and compositional evaluation of laboratory prepared aluminoborosilicate glass surfaces

Gong¹,

Wren²,

Mellott³

2015

Applied Surface Science

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“…reported that nanoscale roughness (<1 nm) can alter the gate oxide reliability of SiO 2 thin films deposited on Si substrates, and further affect the morphological features of deposited SiO 2 films at both the nanoscale and microscale (>1 μm). Several other authors , also reported that the breakdown strength ( Q BD ) of multilayer film-based devices is associated with the interface roughness between successive layers. Also, the surface roughness of materials has been reported to significantly change the hydrophobicity, tribological properties, electrical properties (e.g., formation of electrical double layer), , and other physio-chemical properties of materials. − However, those reported phenomena were based on roughness values specified using average roughness (Ra) or root-mean-square (RMS) roughness, which do not provide any information with respect to the spatial distribution of roughness or the scale dependency of roughness.…”

Section: Introductionmentioning

confidence: 94%

Surface Roughness Measurements Using Power Spectrum Density Analysis with Enhanced Spatial Correlation Length

et al. 2016

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Roughness of a surface as characterized by an atomic force microscope (AFM) is typically expressed using conventional statistical measurements including root-mean-square, peak-to-valley ratio, and average roughness. However, in these measurements only the vertical distribution of roughness (z-axis) is considered. Additionally, roughness of a surface as determined by AFM is a function of the scanning scale, sampling interval and/ or scanning methods; therefore, the consideration and quantification of the lateral distribution (x and y) is necessary. Power spectral density (PSD) analysis provides both lateral and vertical signals captured from AFM images. By applying one of the commonly adopted models to the PSD data, the fractal model and k-correlation model, the equivalent root mean squared roughness, correlation length, fractal dimension and Hurst exponent are quantified. These parameters describe the spatial distribution of roughness and spatial length scale of the roughness values. Longer correlation length is preferred for the comprehensive measurement of roughness of surface at a given spatial wavelength. However, a method to enhance correlation length has yet to be discussed. In this paper, we discuss the state-of-the-art issues associated with roughness evaluation from AFM analysis and propose that the spatial correlation length can be enhanced through the combination PSD profiles over a wide range of spatial frequencies.

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“…1 and has been shown in Figure 30. The trap generation is initially nearly linearly proportional to time, but the time dependence becomes t m where m is less than 0.2 at breakdown [503,523,621,691]. Notice that the trap density in the oxide, immediately prior to oxide breakdown, drops as the gate stress voltage increases.…”

Section: Si -O -Simentioning

confidence: 99%

“…There appears to be no major thickness dependence to trap generation [340,343,355,511,553,573,581]. Similarly, there appears to be no major effect of changing the gate voltage polarity on trap generation, other than, injecting electrons from the smoother oxide-substrate interface (positive gate voltage) results in more uniform trap generation, longer time-to-breakdown, and more traps in the oxide at breakdown, a seemingly contradictory concept [46,47,256,504,523,625,680].…”

Section: Oxide Trap Generationmentioning

confidence: 99%

Oxide Wearout, Breakdown, and Reliability

Dumin

2001

Int. J. Hi. Spe. Ele. Syst.

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The subject of oxide wearout, breakdown, and reliability will be reviewed, largely, from an historical perspective. Five topics will be discussed: oxide breakdown, oxide leakage currents, trap generation, statistics, and reliability. An early model of oxide breakdown, developed by Klein and Solomon, will be described and will be shown to be generally applicable to oxides manufactured today, and to other solid insulators, as well. Both hard and soft breakdowns were included in this model and will be discussed here. The importance of stressinduced-leakage-currents (SILCs) and direct tunneling currents will be discussed in the context of device applications, thinner oxides, and oxide reliability. The diminishing importance of breakdown in ultra thin oxides in ultra small devices will be contrasted with the increasing importance of oxide leakage currents. Trap generation is important in the triggering of breakdown and in the formation of SILCs. Trap generation will be discussed in some detail. Various statistical formulations of oxide breakdown, and how these distributions are related to trap generation, will be discussed. All of these effects will be related to oxide reliability and oxide integrity. An extensive bibliography has been included to help the reader obtain more detailed information concerning the concepts being discussed. Int. J. Hi. Spe. Ele. Syst. 2001.11:617-718. Downloaded from www.worldscientific.com by UNIVERSITY OF VIRGINIA on 04/10/15. For personal use only. Int. J. Hi. Spe. Ele. Syst. 2001.11:617-718. Downloaded from www.worldscientific.com by UNIVERSITY OF VIRGINIA on 04/10/15. For personal use only. Oxide Wearout, Breakdown, and Reliability 619found in an early review paper [20]. This wearout/breakdown model will be referred to as the "Klein/Solomon" model below when comparisons with modern works are needed.The Klein/Solomon model has been refined and confirmed continuously from the 1970s through the present time [10,20,. The extent of the damage is determined both by the 1/2 CV 2 energy stored in the capacitor and by the rate at which this energy discharges through the local hot spot [10,20,75,82,83,88,92,93,96,[100][101][102]. The local hot spot is often accompanied by light emission, in many cases incandescence [8-10, 103-115]. Several techniques have been developed for using the damage introduced during the breakdown to study the breakdown process [80,[116][117][118][119][120][121][122][123][124]. During the breakdown event, the stored energy in the capacitor, 1/2 CV 2 , partially discharges through the breakdown region in a time limited by the impedance of the total measurement system [8][9][10][82][83][84][85].The local breakdowns are intimately coupled to the trap generation and various trap generation models will be discussed in a separate section.During the breakdowns described by Klein/Solomon, one of two scenarios is possible during and following a breakdown discharge. Which scenario takes place depends on the oxide thickness, the oxide area, the magnitude of the stored energy, the ...

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Si/SiO2 interface states and neutral oxide traps induced by surface microroughness

Cited by 23 publications

References 22 publications

Quantitative morphological and compositional evaluation of laboratory prepared aluminoborosilicate glass surfaces

Quantitative morphological and compositional evaluation of laboratory prepared aluminoborosilicate glass surfaces

Surface Roughness Measurements Using Power Spectrum Density Analysis with Enhanced Spatial Correlation Length

Oxide Wearout, Breakdown, and Reliability

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