Modeling and optimization of ITO/Al/ITO multilayer films characteristics using neural network and genetic algorithm

Cho, Edward Namkyu; Moon, Pyung; Kim, Chang-Eun; Yun, Ilgu

doi:10.1016/j.eswa.2012.02.019

Cited by 23 publications

(14 citation statements)

References 15 publications

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“…The post annealed IAAI indicates transmittance of ̴ 86.1 % in the visible range. The increase in transmittance is attributed to the improvement of the metals interlayer crystallinity (after annealed) which resulted in minimum light scattering from the metals thin films [28][29][30]. Besides, the post-annealing treatment has successfully able to reduce the defects responsible for light scattering and hence the enhancement in structural ordering and consequently the transmittance [4,35].…”

Section: Resultsmentioning

confidence: 99%

“…Further treatments beyond 500°C resulted in the degradation of films structure due to the appearance of metallic nanoparticle on the multilayer surface [4,28]. Furthermore, post-annealing at 200 °C was found to be remarkable for 5.07 nm intermediate Al films with an estimation of 12.28 × 10 -4 Ω -1 figure of merit (FOM) as obtained by Cho et al, [29]. Rapid thermal annealing conducted on ITO/Ag/ITO films by Joeng et al, [28] indicates a good improvement in transmittance for film annealed at 300°C and lowest sheet resistance and resistivity was obtained by film annealed at 500°C but with reduced optical transmittance.…”

Section: Introductionmentioning

confidence: 84%

“…Sheet resistance and resistivity of IAAI film are shown to be lower compared to annealed ITO film and further decreases upon annealing at 400 transmittance of the film, the conduction of heat treatment at high temperature narrows the transparencyconductivity trade-off by reducing the film structural defects. Similarly, considering the multilayer structure of IAAI film, it is sheet resistance can be expressed as[29];…”

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confidence: 99%

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Structural optical and electrical properties of transparent conductive ITO/Al-Ag/ITO multilayer contact

Isiyaku¹,

Ali²,

Nayan³

2019

Preprint

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Developing a new design and structure of transparent conductive oxides (TCO) materials to improve performance in optoelectronic devices are important and quite challenging. Microstructural, optical and electrical properties of sandwiched Al-Ag metals interlayer between top and bottom ITO layers (ITO/Al-Ag/ITO) have been investigated. The multilayer ITO/Al-Ag/ITO (IAAI) films were prepared using RF and DC magnetron sputtering method. Post annealing treatment at 400oC was conducted on IAAI and ITO (for reference) films in air. X-ray diffraction measurements show that the insertion of Al-Ag intermediate bilayer led to the crystallization of Ag interlayer even at as-deposited stage. Peaks intensities at ITO (222), Ag (111) and Al (200) crystal plane were observed after annealing treatment, indicating an enhancement in crystallinity of the IAAI film. The post-annealed IAAI film reveals a continuous and smooth surface roughness with improved growth in grain size as examined by atomic force microscopy (AFM) and field emission scanning electron microscopic (FESEM) respectively. Comparing the optoelectronic properties of IAAI film with single ITO film, the annealed IAAI film exhibited a remarkable improvement in optical transmittance (86.1%) with a very low sheet resistance of 2.93 Ω/sq as measured by UV-Vis spectrophotometer and four-point probe method. The carrier concentration increased more than double when Al-Ag layer was inserted between the ITO layers as determined by Hall Effect measurements. The under layer Al film helps to halts the Ag film agglomeration and oxidation which subsequently enhances the stability of IAAI multilayer film. The performance of IAAI contact has been found to be high at 76.4 × 10-3 Ω compares to single ITO (69.4 × 10-3) contact as calculated by the figure of merit (FOM).

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 84%

mentioning

confidence: 99%

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Structural optical and electrical properties of transparent conductive ITO/Al-Ag/ITO multilayer contact

Isiyaku¹,

Ali²,

Nayan³

2019

Preprint

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“…Due to these excellent properties, ITO films have been widely researched for use in a variety of optoelectronic devices: liquid crystal displays (LCD), energyefficient windows, solar cells, organic light emitting and strain sensors devices [4][5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Microstructure and opto-electric properties of Cu/ITO thin films

Wang

Shi

et al. 2012

Journal of Alloys and Compounds

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“…Yang et al used a generalized regression neural network (GRNN) to predict the friction coefficient of Cr 1− Al C film [7]. Cho et al optimized the characteristics of ITO/Al/ITO multilayer films by advantages of neural network and genetic algorithm [8]. Bahramian made use of an artificial neural network to predict the growth rate of TiO 2 nanostructured film [9].…”

Section: Introductionmentioning

confidence: 99%

An Ensemble Learning for Predicting Breakdown Field Strength of Polyimide Nanocomposite Films

Guo

Yin

Zhao

et al. 2015

Journal of Nanomaterials

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Using the method of Stochastic Gradient Boosting, ten SMO-SVR are constructed into a strong prediction model (SGBS model) that is efficient in predicting the breakdown field strength. Adopting the method of in situ polymerization, thirty-two samples of nanocomposite films with different percentage compositions, components, and thicknesses are prepared. Then, the breakdown field strength is tested by using voltage test equipment. From the test results, the correlation coefficient (CC), the mean absolute error (MAE), the root mean squared error (RMSE), the relative absolute error (RAE), and the root relative squared error (RRSE) are 0.9664, 14.2598, 19.684, 22.26%, and 25.01% with SGBS model. The result indicates that the predicted values fit well with the measured ones. Comparisons between models such as linear regression, BP, GRNN, SVR, and SMO-SVR have also been made under the same conditions. They show that CC of the SGBS model is higher than those of other models. Nevertheless, the MAE, RMSE, RAE, and RRSE of the SGBS model are lower than those of other models. This demonstrates that the SGBS model is better than other models in predicting the breakdown field strength of polyimide nanocomposite films.

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Modeling and optimization of ITO/Al/ITO multilayer films characteristics using neural network and genetic algorithm

Cited by 23 publications

References 15 publications

Structural optical and electrical properties of transparent conductive ITO/Al-Ag/ITO multilayer contact

Structural optical and electrical properties of transparent conductive ITO/Al-Ag/ITO multilayer contact

Microstructure and opto-electric properties of Cu/ITO thin films

An Ensemble Learning for Predicting Breakdown Field Strength of Polyimide Nanocomposite Films

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