Any interested parties are kindly invited to get in touch with Murat Eskiyerli, the lead RevEDA developer
Jan 11, 2024
[github] new RevEDA Release
Any interested parties are kindly invited to get in touch with Murat Eskiyerli, the lead RevEDA developer
[C4P] 82nd DRC
- An informative, timely short course in rapidly developing fields
- Oral and poster presentations on electronic/photonic device experiments
- and simulations
- Plenary and invited presentations given by worldwide leaders
- Evening rump sessions
- Strong student participation and Student Paper Awards
- Focus Sessions on Devices for Neuromorphic Computing
- More than 50 invited speakers covering a wide spectrum of devices
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- Feb. 16, 2024 Abstract Submission Deadline
- April 5, 2024 Acceptance Notification
- April 10, 2024 Registration Opens
- May 15, 2024 Early Bird Registration Deadline
Jan 8, 2024
[paper] OTA using the Open Sky130 PDK
doi: 10.5281/zenodo.10646550
Faculdade de Engenharia, Universidade Federal de Juiz de Fora, Brazil
Abstract: This paper describes the design, layout and simulation of a linear transconductance Operational Transconductance Amplifier (OTA) using the SkyWater 130nm open Process Design Kit (PDK). By using a known source degeneration technique, it is possible to either decrease and linearize the transconductance of the OTA for a wider range of input voltages, making it proper for use on Gm-C filters. Only open source tools, suited for the Sky130 PDK, were used in this design, showing the applicability to analog designs.
(b) Alternative source degeneration triode MOSFETs; and its GDSII layout, with identification of some relevant parts: (A) differential pair; (B) source-degeneration resistors; (C) biasing transistors.
Acknowledgment: This work is result from a scientific initiation project covered by the VI VIC 2022/2023 Program, by PROPP/UFJF.
[paper] Polylogarithms in MOSFET Modeling
Department of Electronics and Circuits, Universidad Simón Bolívar, Caracas, Venezuela
Abstract: We present a review of recent uses of the special mathematical function known as the polylogarithm for MOSFET modeling applications. We first summarize some basic properties of polylogarithms, with a particular focus on those with negative exponential argument. After examining cases of the use of first order polylogarithms pertinent to electron device modeling, we explain the reasons that motivate the use of polylogarithms of diverse orders for formulating mono- and poly-crystalline succinct compact MOSFET models. We then analyze a particular representative example: the modeling of polysilicon MOSFETs using the polylogarithm. Recalling that polylogarithms may be used to faithfully represent Fermi-Dirac Integrals in general, and considering that they are analytically differentiable and integrable, we describe a full Fermi–Dirac Statistics-based version of the usually approximate Boltzmann Statistics-based MOSFET Surface Potential Equation (SPE).
TABLE: Some Features of Polylogarithms with Negative Exponential Argument
[paper] Compact Model of Graphene FETs
1 Departament d’Enginyeria Electrònica, Escola d’Enginyeria, UAB, 08193 Bellaterra, Spain
2 Graphenea Semiconductor SLU, 20009 San Sebastián, Spain.
Abstract: The main target of this article is to propose for the first time a physics-based continuous and symmetric compact model that accurately captures I–V experimental dependencies induced by geometrical scaling effects for graphene field-effect transistor (GFET) technologies. Such a scalable model is an indispensable ingredient for the boost of large-scale GFET applications, as it has been already proved in solid industry-based CMOS technologies. Dependencies of the physical model parameters on channel dimensions are thoroughly investigated, and semi-empirical expressions are derived, which precisely characterize such behaviors for an industry-based GFET technology, as well as for others developed in the research laboratory. This work aims at the establishment of the first industry standard GFET compact model that can be integrated in circuit simulation tools and, hence, can contribute to the update of GFET technology from the research level to massive industry production.
Fig: Graphenea GFET schematic cross-section not drawn to scale. Graphene under metal contacts is not shown.The drain current has explicit derivation in respect to Qgr, where Qt and Qp(n) are the transport sheet and p(n)-type charges, respectively; Vc is the chemical potential, h is the reduced Planck constant, uf is the Fermi velocity, e is the electron charge, and k is a coefficient. Qt and, thus, ID can be calculated according to Vc polarity at source (Vcs) and drain (Vcd), respectively. Hence, at n-type region where Vcs, Vcd > 0 and Qp = 0
Acknowledgements: This work was supported in part by the European Union’s Horizon 2020 Research and Innovation Program GrapheneCore3 under Grant 881603; in part by the Ministerio de Ciencia, Innovación y Universidades under Grant RTI2018-097876-B-C21 (MCIU/AEI/ FEDER, UE), Grant FJC2020-046213-I, and Grant PID2021-127840NBI00 (MCIN/AEI/FEDER, UE); in part by the European Union Regional Development Fund within the Framework of the ERDF Operational Program of Catalonia 2014–2020 with the Support of the Department de Recerca i Universitat, with a grant of 50% of Total Cost Eligible; and in part by the GraphCAT Project under Grant 001-P-001702.



