25 research outputs found
Nonvolatile CMOS memristor, reconfigurable array and its application in power load forecasting
© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This is the accepted manuscript version of a conference paper which has been published in final form at https://doi.org/10.1109/TII.2023.3341256The high cost, low yield, and low stability of nano-materials significantly hinder the application and development of memristors. To promote the application of memristors, researchers proposed a variety of memristor emulators to simulate memristor functions and apply them in various fields. However these emulators lack nonvolatile characteristics, limiting their scope of application. This paper proposes an innovative nonvolatile memristor circuit based on complementary metal-oxide-semiconductor (CMOS) technology, expanding the horizons of memristor emulators. The proposed memristor is fabricated in a reconfigurable array architecture using the standard CMOS process, allowing the connection between memristors to be altered by configuring the on-off state of switches. Compared to nano-material memristors, the CMOS nonvolatile memristor circuit proposed in this paper offers advantages of low manufacturing cost and easy mass production, which can promote the application of memristors. The application of the reconfigurable array is further studied by constructing an Echo State Network (ESN) for short-term load forecasting in the power system.Peer reviewe
Quantum Device: Empirical Modelling Of The Resonant Tunneling Diode
The transistor was widely employed in integrated circuit design. Nevertheless, the continued scaling the transistor size will affect the device performances. RTD is an efficient high-speed device and has high-frequency operation up to Terahertz (THz) compared to the transistor. It has the potential to replace the transistor in the ultra-high frequency device applications in the future. Furthermore, RTD is a low power consumption device that works at low power compared to the transistor. Low power consumption needs to consider in integrated circuit design to have highest dynamic performance. This study will be modelled two different material system of RTD, which is GaAs/AlAs and In0.8Ga0.2As/AlAs. The physic-based equation will be
simulated in MATLAB and the circuit model will be built up in LT Spice IV.Empirical fitting will be done in MATLAB to match the model to the experimental data. Meanwhile, in LT Spice IV, two methods were employed to simulate the circuit model, which are Table simulation and Polynomial simulation. The empirical fitting had been successfully matched the model to the experimental of GaAs/AlAs and In0.8Ga0.2As/AlAs. Based on results analysis, Table simulation had been successfully
simulated I-V characteristics of experimental GaAs/AlAs and In0.8Ga0.2As/AlAs better than Polynomial simulation
Variability in Resistive Memories
This research was supported by project B-TIC-624-UGR20 funded by the
Consejería de Conocimiento, Investigación y Universidad, Junta de
Andalucía (Spain) and the FEDER program. F.J.A. acknowledges grant
PGC2018-098860-B-I00 and PID2021-128077NB-I00 financed by MCIN/
AEI/10.13039/501100011033/FEDER and A-FQM-66-UGR20 financed by
the Consejería de Conocimiento, Investigación y Universidad, Junta de
Andalucía (Spain) and the FEDER program. M.B.G. acknowledges the
Ramón y Cajal Grant No. RYC2020-030150-I. M.L. and M.A.V. acknowl-
edge generous support from the King Abdullah University of Science
and Technology. A.N.M., N.V.A., A.A.D., M.N.K. and B.S. acknowledge
the Government of the Russian Federation under Megagrant Program
(agreement no. 074-02-2018-330 (2)) and the Ministry of Science and
Higher Education of the Russian Federation under “Priority-2030”
Academic Excellence Program of the Lobachevsky State University of
Nizhny Novgorod (N-466-99_2021-2023). The authors thank D.O.
Filatov, A.S. Novikov, and V.A. Shishmakova for their help in studying
the dependence of MFPT on external voltage (Section 4). The devices
in Section 4 were designed in the frame of the scientific program of
the National Center for Physics and Mathematics (project “Artificial intel-
ligence and big data in technical, industrial, natural and social systems”)
and fabricated at the facilities of Laboratory of memristor nanoelectronics
(state assignment for the creation of new laboratories for electronics
industry). E.M. acknowledges the support provided by the European proj-
ect MEMQuD, code 20FUN06, which has received funding from the
EMPIR programme co-financed by the Participating States and from
the European Union’s Horizon 2020 research and innovation programme.Resistive memories are outstanding electron devices that have displayed a large
potential in a plethora of applications such as nonvolatile data storage, neuro-
morphic computing, hardware cryptography, etc. Their fabrication control and
performance have been notably improved in the last few years to cope with the
requirements of massive industrial production. However, the most important
hurdle to progress in their development is the so-called cycle-to-cycle variability,
which is inherently rooted in the resistive switching mechanism behind the
operational principle of these devices. In order to achieve the whole picture,
variability must be assessed from different viewpoints going from the experi-
mental characterization to the adequation of modeling and simulation techni-
ques. Herein, special emphasis is put on the modeling part because the accurate
representation of the phenomenon is critical for circuit designers. In this respect,
a number of approaches are used to the date: stochastic, behavioral, meso-
scopic..., each of them covering particular aspects of the electron and ion
transport mechanisms occurring within the switching material. These subjects
are dealt with in this review, with the aim of presenting the most recent
advancements in the treatment of variability in resistive memories.Junta de Andalucía B-TIC-624-UGR20 PID2021-128077NB-I00European CommissionMCIN/AEI/FEDER A-FQM-66-UGR20 PGC2018-098860-B-I00Spanish Government RYC2020-030150-IKing Abdullah University of Science & TechnologyGovernment of the Russian Federation under Megagrant Program 074-02-2018-330 (2)Ministry of Science and Higher Education of the Russian Federation under "Priority-2030" Academic Excellence Program of the Lobachevsky State University of Nizhny Novgorod N-466-99_2021-2023European project MEMQuD 20FUN06EMPIR programmeEuropean Union's Horizon 2020 research and innovation programm
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