Controlling of Hysteresis by Varying ZnO-Nanoparticles Amount in P3HT:ZnO Hybrid Thin-Film Transistor: Modeling

Ba, M.; Mansouri, S.; Jouili, A.; Yousfi, Y.; Chouiref, L.; Jdir, Maher; Erouel, Mohsen; Yakuphanoğlu, F.; Mir, L. El

doi:10.1007/s11664-022-10066-2

Cited by 8 publications

(5 citation statements)

References 49 publications

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“…We attribute this to the capability of designing ultra‐low threshold voltage OFET, as previously reported in References 16–18. In addition, the previous investigation recorded a very acceptable and controllable on/off current ratio and subthreshold swing (SS) 19–22 . In such a context, selecting the primary active OSC material, the device dimension, and the doping level is the critical design parameters for the OFETs 23 .…”

Section: Introductionsupporting

confidence: 54%

“…In addition, the previous investigation recorded a very acceptable and controllable on/off current ratio and subthreshold swing (SS). [19][20][21][22] In such a context, selecting the primary active OSC material, the device dimension, and the doping level is the critical design parameters for the OFETs. 23 Moreover, the OFET architecture, based on the gate and the contact arrangement, can influence the overall device I-V transfer characteristics.…”

Section: Introductionmentioning

confidence: 99%

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OFET Informatics: Observing the impact of organic transistor's design parameters on the device output performance using a machine learning algorithm

Mosalam

Hussien

Abdellatif

2023

Int J Numerical Modelling

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Organic field effect transistors (OFETs), used in the fabrication of nano‐sensors, are one of the most promising devices in organic electronics because of their lightweight, flexible, and low fabrication cost. However, the numerical modeling of such OFETs is still in an early stage due to the minimal analytical as well as numerical models presented in the literature. This research aims to demonstrate an experimentally verified machine‐learning model by investigating an OFET with polyaniline as a p‐type organic semiconductor. OFET's threshold voltage, on/off current ratio, subthreshold swing, and device mobilities are studied as the primary output chiasmatic parameters. The random‐forest machine learning model has shown the criticality of the doping effect on turning the OFET to depletion mode, with positive threshold voltage, under doping higher than cm−3. Additionally, the study highlights the effectiveness of the gate oxide thickness in controlling the OFET threshold voltage. A 50 nm oxide thickness showed sufficiency to have a non‐depleted OFET operation.

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Section: Introductionsupporting

confidence: 54%

Section: Introductionmentioning

confidence: 99%

OFET Informatics: Observing the impact of organic transistor's design parameters on the device output performance using a machine learning algorithm

Mosalam

Hussien

Abdellatif

2023

Int J Numerical Modelling

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“…An important device in this technology is the organic thin-film transistor (OTFT) which inherits the advantages of its intrinsic material, such as mechanical flexibility and low-cost solution processability [1][2][3][4][5][6][7]. Different OTFTs are fabricated accordingly in order to adapt to current requirements in non-volatile memory applications [8]. In particular, these transistors are present in several types of non-volatile memories, such as the organic phase-change memory transistors (OPCMTs) [9], transistor-based organic flash memories [5,10], organic resistive random-access memories (RRAMs) [11][12][13], organic ferroelectric field-effect-transistors [14][15][16][17], and magnetoresistive random-access memory (MRAM) [18].…”

Section: Introductionmentioning

confidence: 99%

Compact Modeling of Hysteresis in Organic Thin-Film Transistors

Romero,

Jiménez-Tejada,

Picos

et al. 2024

Preprint

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In this work, we propose a model that describes the temporal evolution of the threshold voltage and trapped charge density in Thin-Film Transistors (TFTs) under dynamic conditions, paving the way for the characterization and modeling of memory transistors. The model is expressed as a first-order differential equation for the trapped charge density, which is controlled by a time constant and an independent term proportional to the drain current. The time-dependent threshold voltage is introduced in a previously developed compact model for TFTs with special consideration to the contact effects. The combination of both models and the use of an evolutionary parameter extraction procedure allow for reproducing the experimental dynamic behavior of TFTs. The results of the model and the evolutionary procedure have been validated with published experimental data of pentacene-based transistors. The procedure is able to simultaneously reproduce three kinds of experiments with different initialization routines and constraints in each of them: output and transfer characteristics with hysteresis and current transients characteristics. ✩ The authors acknowledge support from the project PID2022-139586NB-44 funded by MCIN/AEI/10.13039/501100011033 and FEDER, EU. Funding for open access charge: Universidad de Granada / CBUA.

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“…Moreover, it exhibits a substantial exciton binding energy, measuring 60 meV at ambient temperature [1][2][3]. These distinctive attributes render ZnO suitable for a wide array of technological applications, encompassing gas detection sensors [4], photodetection devices [5], dyebased solar cells [6], transparent electrical conductors [7], devices that exploit piezoelectric effects [8], highcapacity electronic systems [9], thin-film transistor technology [10], light-emitting applications [11], and various solar cell configurations [12].…”

Section: Introductionmentioning

confidence: 99%

“…Similarly, the sol-gel process has demonstrated its efficacy in producing ZnO NRs, yielding products of high purity, uniformity, and crystalline quality [25]. Vapor deposition techniques, including chemical vapor deposition (CVD) [10] and physical vapor deposition (PVD) [26,27], have also been employed to synthesize ZnO NRs with controlled and superior characteristics. These methods, however, are often constrained by the necessity for hazardous and costly chemicals, elevated temperatures, and intricate equipment, restricting their broader application.…”

Section: Introductionmentioning

confidence: 99%

A novel approach to the green synthesis of zinc oxide nanorods using Thymus kotschyanus plant extract: effect of ammonium hydroxide and precursor concentration

Aspoukeh,

Barzinjy,

Hamad

2023

Nano Ex.

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This research introduces a pioneering green method for synthesizing zinc oxide nanorods (ZnO NRs) on a glass substrate using Thymus kotschyanus plant extract. The study delves into the intricate effects of ammonium hydroxide and precursor concentrations on the morphology, size, alignment, and crystalline structure of ZnO NRs. Through systematic experimentation, it was found that specific concentrations of these substances play vital roles in the formation and properties of the nanorods. Notably, a low concentration of the precursor coupled with a high concentration of ammonium hydroxide led to well-aligned hexagonal ZnO NRs with a remarkable aspect ratio. Variations in these concentrations were also found to influence the length, diameter, and alignment of the nanorods. The findings were corroborated using a diverse array of analytical techniques, including transmission and scanning electron microscopy, X-ray diffraction, UV-Vis spectroscopy, and energy-dispersive X-ray analysis. The UV-Vis spectra provided further insights into the optical properties and band gap energy of the ZnO NPs, while EDX analysis confirmed the elemental composition. This work represents a significant advancement in eco-friendly nanomaterial synthesis, providing detailed insights into the controlled fabrication of aligned ZnO NRs. Its innovative approach and extensive investigation into influencing factors make it a valuable contribution to the field of nanoscience.

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Controlling of Hysteresis by Varying ZnO-Nanoparticles Amount in P3HT:ZnO Hybrid Thin-Film Transistor: Modeling

Cited by 8 publications

References 49 publications

OFET Informatics: Observing the impact of organic transistor's design parameters on the device output performance using a machine learning algorithm

OFET Informatics: Observing the impact of organic transistor's design parameters on the device output performance using a machine learning algorithm

Compact Modeling of Hysteresis in Organic Thin-Film Transistors

A novel approach to the green synthesis of zinc oxide nanorods using Thymus kotschyanus plant extract: effect of ammonium hydroxide and precursor concentration

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