IEEE Journal on Exploratory Solid-State Computational Devices and Circuits

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Antiferromagnetic Programmable Neuron: Structure, Training, and Pattern Recognition Applications

Antiferromagnetic Programmable Neuron: Structure, Training, and Pattern Recognition Applications 150 150
Author(s): I. Sotnyk, O. Prokopenko

Abstract:

Artificial neurons based on antiferromagnetic (AFM) spin Hall oscillators (SHOs) are promising elements for creating ultra-fast, energy-efficient neuromorphic computing systems. These structures can generate picosecond spikes in response to dc and ac electric currents, thereby mimicking the reaction of biological neurons to an external stimuli. However, conventional AFM neurons have …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 1 – 1
Year of Publication: 2025
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2025.3633490
Publisher: IEEE

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Integrated Spatiotemporal Multiscale-Multiphysics-Uncertainty Simulation for Controlling Variability in RRAM Devices

Integrated Spatiotemporal Multiscale-Multiphysics-Uncertainty Simulation for Controlling Variability in RRAM Devices 150 150
Author(s): Ziyan Liao, Zhiheng Huang, Min Xiao, Yuezhong Meng, Hui Yan, Yang Liu

Abstract:

Resistive random access memory (RRAM) is a leading candidate for next-generation nonvolatile memory and neuromorphic computing. However, its performance is limited by inherent switching variability and uncertainties in spatiotemporal multiscale materials and processes. This study integrates multiphysics and multiscale modeling with uncertainty quantification (UQ) to systematically address these limitations and …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 1 – 1
Year of Publication: 2025
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2025.3633067
Publisher: IEEE

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Energy-Efficient Logic-in-Memory and Neuromorphic Computing in Raised Source and Drain MOSFETs

Energy-Efficient Logic-in-Memory and Neuromorphic Computing in Raised Source and Drain MOSFETs 150 150
Author(s): Md. Hasan Raza Ansari, Bashayr Alqahtani, Naveen Kumar, Vihar Georgiev, Nazek El-Atab

Abstract:

This work highlights the potential application of raised source and drain (RSD) MOSFETs-based charge trapping memory (CTM) for next-generation computing applications. This simulation study presents a double-gate (DG)-RSD MOSFET technology with a short gate length (50 nm) to significantly improve the performance of logic-in-memory (LIM) and neuromorphic computing (NC) systems. …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 197 – 204
Year of Publication: 2025
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2025.3630217
Publisher: IEEE

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Integrating Atomistic Insights With Circuit Simulations via Transformer-Driven Symbolic Regression

Integrating Atomistic Insights With Circuit Simulations via Transformer-Driven Symbolic Regression 150 150
Author(s): Md Rahatul Islam Udoy, Jack Hutchins, Shamiul Alam, Catherine Schuman, Ahmedullah Aziz

Abstract:

This article introduces a framework that establishes a cohesive link between the first principles-based simulations and circuit-level analyses using a machine learning-based compact modeling platform. Starting with atomistic simulations, the framework examines the microscopic details of material behavior, forming the foundation for later stages. The generated datasets, with molecular insights, …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 179 – 187
Year of Publication: 2025
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2025.3624662
Publisher: IEEE

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Impact of Aging, Self-Heating, and Parasitics Effects on NSFET and CFET

Impact of Aging, Self-Heating, and Parasitics Effects on NSFET and CFET 150 150
Author(s): Swati Deshwal, Sufia Shahin, Anirban Kar, Yogesh S. Chauhan, Hussam Amrouch

Abstract:

This work presents a comparative analysis of complementary field-effect transistor (CFET) and nanosheet FET (NSFET) architectures, with a focus on self-heating effects (SHEs), negative bias temperature instability (NBTI), hot carrier degradation (HCD), and the impact of back-end-of-line (BEOL) parasitics on standard cell performance. NBTI degradation is modeled using a framework …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 188 – 196
Year of Publication: 2025
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2025.3624653
Publisher: IEEE

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A SPICE-Compatible Compact Model of Ferroelectric Diode

A SPICE-Compatible Compact Model of Ferroelectric Diode 150 150
Author(s): Musaib Rafiq, Mohammad Sajid Nazir, Ateeb Naseer, Yogesh Singh Chauhan, Shubham Sahay

Abstract:

In this work, for the first time, we present a SPICE-compatible compact model of ferroelectric (FE) diodes to enable their design exploration for diverse applications, including memory and unconventional computing paradigms. We propose modified Schottky barrier and hopping models for capturing the on- and off-mode operations of the FE diode, …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 166 – 170
Year of Publication: 2025
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2025.3624212
Publisher: IEEE

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Quantum Field Theory Model for Spin-Based Devices Using 2-D van der Waals Materials

Quantum Field Theory Model for Spin-Based Devices Using 2-D van der Waals Materials 150 150
Author(s): Axel I. Saenz Rodriguez, Oksana Ostroverkhova, Pallavi Dhagat

Abstract:

We explore the effects of layered geometries of 2-D quantum spin systems as a method to tune and control material properties for spintronic devices. We analyze the dispersion relation of a 2-D quantum spin system with a shifted bilayer square lattice through the linear spin wave (LSW) approximation of quantum …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 171 – 178
Year of Publication: 2025
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2025.3624217
Publisher: IEEE

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1.58-b FeFET-Based Ternary Neural Networks: Achieving Robust Compute-In-Memory With Weight-Input Transformations

1.58-b FeFET-Based Ternary Neural Networks: Achieving Robust Compute-In-Memory With Weight-Input Transformations 150 150
Author(s): Imtiaz Ahmed, Akul Malhotra, Revanth Koduru, Sumeet Kumar Gupta

Abstract:

Ternary weight neural networks (TWNs), with weights quantized to three states (−1, 0, and 1), have emerged as promising solutions for resource-constrained edge artificial intelligence (AI) platforms due to their high energy efficiency with acceptable inference accuracy. Further energy savings can be achieved with TWN accelerators utilizing techniques such as compute-in-memory (CiM) and …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 157 – 165
Year of Publication: 2025
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2025.3621160
Publisher: IEEE

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Comprehensive Device to System Co-Design for SOT-MRAM at the 7 nm Node

Comprehensive Device to System Co-Design for SOT-MRAM at the 7 nm Node 150 150
Author(s): Piyush Kumar, Da Eun Shim, Azad Naeemi

Abstract:

This work presents a comprehensive spin-orbit torque (SOT)-based magnetic random access memory (MRAM) design at the 7 nm technology node, spanning from device-level characteristics to system-level power performance area (PPA). At the device level, we show the tradeoffs among the write current, error rate, and time, based on mircomagnetic simulations. …

Published in: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Page(s): 139 – 147
Year of Publication: 2025
Electronic ISSN: 2329-9231
DOI: 10.1109/JXCDC.2025.3621279
Publisher: IEEE

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