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Record W2517077054 · doi:10.1149/ma2016-02/53/3969

Bottom-Gate Self-Aligned Homojunction TFT with Double Oxide Semiconducting Layers

2016· article· en· W2517077054 on OpenAlexaff
Hye‐In Yeom, Chi‐Sun Hwang, Sang‐Hee Ko Park

Bibliographic record

VenueECS Meeting Abstracts · 2016
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsMaterials scienceThin-film transistorOptoelectronicsTransistorParasitic capacitanceEtching (microfabrication)Oxide thin-film transistorHomojunctionDopingDopantGate oxideSubstrate (aquarium)OxideElectrodeCapacitanceLayer (electronics)NanotechnologyElectrical engineeringVoltage

Abstract

fetched live from OpenAlex

After huge effort has been made over the last decade, oxide thin-film transistors (TFTs) have been successfully adopted in the backplane of high resolution AM-LCD and AM-OLED displays. However, as displays and electronic devices evolve to next generations, it is necessary to not only enhance field-effect mobility, but also reduce RC-delay for high driving speed [1, 2]. In this regard, self-aligned structure has been considered as one of promising candidates for satisfying these requirements [3] due to the minimum parasitic capacitances between electrodes. Nonetheless, there are several concerns especially in doping process at contact region because it is difficult to control dopant diffusion, resulting in unstable performance and another unexpected parasitic capacitance. Here, we propose improved structure adopting double oxide semiconducting layers, which can precisely define the channel dimension by gate electrode. Figure 1 demonstrates both structures of conventional self-aligned TFT and our improved self-aligned TFT. As shown in the figure, first channel layer of oxide material with high mobility and high carrier density plays as the real electron flow path and the contacts with source/drain (S/D) metal electrode without additional doping process. Consequently, the issues originated from doping process can be easily overcome. Meanwhile, second active layer with the relatively low carrier density is defined by the gate electrode and plays a role as a carrier controlling part for reliable switching performance. To fabricate our self-aligned TFTs, gate metal was firstly patterned on glass substrate by wet etching. After depositing SiO 2 by PECVD as a gate insulator, first semiconducting layer was grown by sputter or plasma-enhanced atomic layer deposition (PEALD). The second active layer was deposited and formed by back-side exposure using gate electrode as a masking layer. Then, SiO 2 by PECVD was deposited to passivate whole device. Finally, S/D metal layer was formed, followed by annealing process in vacuum condition. As a starting research, we had to carefully consider proper oxide semiconductors according to their characteristics and etch selectivity between first and second channel layers. Although adopting highly conducting oxides such as ITO and In 2 O 3 as a first channel layer would be better for lowering the contact resistance, it is hard to deplete the carriers. Hence, thinner film thickness (<10nm) or other deposition method such as PEALD should be considered to obtain semiconducting behavior. Accordingly, we have firstly investigated the switching behavior of In 2 O 3 /ZnO double layered TFT by means of PEALD with bottom-gate coplanar structure. The In 2 O 3 /ZnO TFT shows mobility of 32 cm 2 /Vs with good bias stability as shown in Figure 2. The improved self-aligned TFTs were successfully fabricated and well-performed using sputtered ITO/IGZO and PEALD In 2 O 3 /ZnO. We will report the device characteristics and further investigate and reveal the origin of stable electrical behavior by simulation. [Acknowledgement] This work was supported by Open Innovation Lab Project from National Nanofab Center (NNFC). [Reference] [1] K. Yokoyama, S. Hirakata, S. Yamazaki, M. Nakada, T. Sato, and N. Goto, “A 2.78-in 1058-ppi ultra-high-resolution OLED display using CAAC-OS FETs,” SID digest 2015, 46, 1039-1042. [2] J. U. Bae, D. H. Kim, K. Kim, K. Jung, W. Shin, I. Kang, and S. D. Yeo, “Development of oxide TFT’s structures,” SID digest 2013, 44, 89-92. [3] N. Morosawa, Y. Ohshima, M. Morooka, T. Arai, and T. Sasaoka, “Novel self-aligned top-gate oxide TFT for AMOLED displays,” Journal of the society for Information Display 2012, 20 (1), 47-52. Figure 1

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.196
Teacher spread0.185 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2016
Admission routes1
Has abstractyes

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