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Autor(en) / Beteiligte
Titel
Modeling and Understanding the Compact Performance of h‐BN Dual‐Gated ReS2 Transistor
Ist Teil von
  • Advanced functional materials, 2021-06, Vol.31 (23), p.n/a
Ort / Verlag
Hoboken: Wiley Subscription Services, Inc
Erscheinungsjahr
2021
Quelle
Wiley Online Library
Beschreibungen/Notizen
  • In this study, high‐performance few‐layered ReS2 field‐effect transistors (FETs), fabricated with hexagonal boron nitride (h‐BN) as top/bottom dual gate dielectrics, are presented. The performance of h‐BN dual gated ReS2 FET having a trade‐off of performance parameters is optimized using a compact model from analytical choice maps, which consists of three regions with different electrical characteristics. The bottom h‐BN dielectric has almost no defects and provides a physical distance between the traps in the SiO2 and the carriers in the ReS2 channel. Using a compact analyzing model and structural advantages, an excellent and optimized performance is introduced consisting of h‐BN dual‐gated ReS2 with a high mobility of 46.1 cm2 V−1 s−1, a high current on/off ratio of ≈106, a subthreshold swing of 2.7 V dec−1, and a low effective interface trap density (Nt,eff) of 7.85 × 1010 cm−2 eV−1 at a small operating voltage (<3 V). These phenomena are demonstrated through not only a fundamental current–voltage analysis, but also technology computer aided design simulations, time‐dependent current, and low‐frequency noise analysis. In addition, a simple method is introduced to extract the interlayer resistance of ReS2 channel through Y‐function method as a function of constant top gate bias. Implementing compact modeling through analytical choice maps and extracting approximate their interlayer resistances in h‐BN dual‐gated ReS2. Optimization and interpretation of performances in ReS2 field‐effect transistors are conducted in parallel with secondary gm peaks, threshold voltages, subthreshold swing, mobility through DC analysis, time‐dependent current, low‐frequency noise, and technology computer aided design simulation analysis.
Sprache
Englisch
Identifikatoren
ISSN: 1616-301X
eISSN: 1616-3028
DOI: 10.1002/adfm.202100625
Titel-ID: cdi_proquest_journals_2536727001

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