Self-affinity study of nanostructured porous silicon–crystalline silicon interfaces

Escorcia‐García, J.; Cruz-Silva, Rodolfo; Agarwal, Vivechana

doi:10.1016/j.apsusc.2009.08.035

Cited by 4 publications

(2 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is a not a complete set of estimators for the self-similarity or LRD parameter (other estimators that are well established in the statistics community include the fractional exponential (FEXP) model [30]). Here, we want to focus on some of the most popular estimators in the physics and geosciences communities (R/S [31][32][33][34][35], DFA [7,[35][36][37], GPH [3,38,39], VB [40] and WL [21,41]).…”

Section: Introductionmentioning

confidence: 99%

Robustness of estimators of long-range dependence and self-similarity under non-Gaussianity

Franzke

Graves

Watkins

et al. 2012

Phil. Trans. R. Soc. A.

View full text Add to dashboard Cite

Long-range dependence and non-Gaussianity are ubiquitous in many natural systems like ecosystems, biological systems and climate. However, it is not always appreciated that both phenomena may occur together in natural systems and that self-similarity in a system can be a superposition of both phenomena. These features, which are common in complex systems, impact the attribution of trends and the occurrence and clustering of extremes. The risk assessment of systems with these properties will lead to different outcomes (e.g. return periods) than the more common assumption of independence of extremes.Two paradigmatic models are discussed which can simultaneously account for long-range dependence and non-Gaussianity: Autoregressive Fractional Integrated Moving Average (ARFIMA) and Linear Fractional Stable Motion (LFSM). Statistical properties of estimators for long-range dependence and self-similarity are critically assessed. It is found that the most popular estimators can be biased in the presence of important features of many natural systems like trends and multiplicative noise. Also the long-range dependence and non-Gaussianity of two typical natural time series are discussed.

show abstract

Section: Introductionmentioning

confidence: 99%

Robustness of estimators of long-range dependence and self-similarity under non-Gaussianity

Franzke

Graves

Watkins

et al. 2012

Phil. Trans. R. Soc. A.

View full text Add to dashboard Cite

show abstract

“…Transmission line model though easy to handle lacks the relevant physical justification in addition to this semi-infinite diffusion (Warburg) have no exact corresponding circuit element and specialized elements have to be added. Fractal model of porous structure of DSSCs are proposed [27][28][29][30] in order to comprehend the disorder morphology of such electrodes. In these works a simplified fractal model has been used which fails to identify realistic fractal DSSC with crossover time and length scales.…”

mentioning

confidence: 99%

Theory for IMPS on Rough and Finite Fractal Dye Sensitized Solar Cell

Kant

Chowdhury

Srivastav

2018

J. Electrochem. Soc.

View full text Add to dashboard Cite

A generalized theoretical model of intensity modulated photocurrent spectroscopy (IMPS) for the random morphology in a dye sensitized solar cell (DSSC) under uniform illumination is developed. The generalized IMPS expression for the disordered semiconducting/conducting glass interface of a DSSC is obtained in term of power spectral density of roughness. Influence of surface roughness on the dynamic response of DSSC originate due to the coupling of characteristic phenomenological and morphological length scales. A detailed analysis of IMPS response is performed over finite self- affine fractals to highlight roughness induced anomalies and cause of photocurrent enhancement. The IMPS of a rough DSSC exhibit three characteristic frequency regimes: lifetime of charge carrier dependent low frequency regime, surface irregularity dependent intermediate power-law regime and diffusion controlled high frequency regime. Finally, our theory facilitates the understanding of dynamics and kinetics of charge carriers under the influence of ubiquitous surface disorder.

show abstract

Porous silicon pillar and bilayer structure as a nucleation center for the formation of aligned vanadium pentoxide nanorods

Balderas‐Valadez

Antúnez

Olive-Méndez

et al. 2017

Ceramics International

View full text Add to dashboard Cite

Self-affinity study of nanostructured porous silicon–crystalline silicon interfaces

Cited by 4 publications

References 32 publications

Robustness of estimators of long-range dependence and self-similarity under non-Gaussianity

Robustness of estimators of long-range dependence and self-similarity under non-Gaussianity

Theory for IMPS on Rough and Finite Fractal Dye Sensitized Solar Cell

Porous silicon pillar and bilayer structure as a nucleation center for the formation of aligned vanadium pentoxide nanorods

Contact Info

Product

Resources

About