Logic

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A 1.1-nJ/Conversion RC-Discharge-Based Resistance Sensor With ±0.65% (3σ) 1 -Point Trimmed Inaccuracy in 0.18-μm CMOS Technology

A 1.1-nJ/Conversion RC-Discharge-Based Resistance Sensor With ±0.65% (3σ) 1 -Point Trimmed Inaccuracy in 0.18-μm CMOS Technology 150 150
Author(s): Mu Wu, Yihang Cheng, Xingli Cui, Sining Pan, Huaqiang Wu

Abstract:

This letter presents an energy-efficient RC discharge-based sensor readout circuit for sub-kilo-ohm resistance measurements. An SAR logic is implemented to adjust the DAC capacitor array to equalize the RC time constants of the resistance-sensing and DAC branches, thereby eliminating the high static current required to bias the small sensing resistor. …

Published in: IEEE Solid-State Circuits Letters
Page(s): 109 – 112
Year of Publication: 2026
Electronic ISSN: 2573-9603
DOI: 10.1109/LSSC.2026.3677301
Publisher: IEEE

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A 7-Level 18-Wire-State Trio-Signaling Transmitter for MIPI C-PHY 3.0 Interfaces

A 7-Level 18-Wire-State Trio-Signaling Transmitter for MIPI C-PHY 3.0 Interfaces 150 150
Author(s): Junyeong Lee, Myeongjin Oh, Kiwoon Kim, Jung-Hoon Chun

Abstract:

This letter presents a MIPI C-PHY v3.0 TX, which adopts trio-signaling using three wires per lane. Each line supports seven-level signaling, enabling 18 wire states to map 32-bit data into nine symbols, achieving 3.56 bits/symbol efficiency. Balanced coding maintains constant driver current, enhancing SSO noise immunity, and embedded clocking is achieved …

Published in: IEEE Solid-State Circuits Letters
Page(s): 101 – 104
Year of Publication: 2026
Electronic ISSN: 2573-9603
DOI: 10.1109/LSSC.2026.3672642
Publisher: IEEE

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A 14-nm Nonvolatile-Volatile-Fused Compute-In-Memory Macro Based on Logic-Compatible Flash for Plastic Neural Networks

A 14-nm Nonvolatile-Volatile-Fused Compute-In-Memory Macro Based on Logic-Compatible Flash for Plastic Neural Networks 150 150
Author(s): Weizeng Li, Linfang Wang, Zhidao Zhou, Zhi Li, Wang Ye, Junyu Zhu, Junzhe Shen, Bohan Wang, Hanghang Gao, Hongyang Hu, Jing Liu, Jinshan Yue, Jianguo Yang, Qing Luo, Qi Liu, Chunmeng Dou, Yang Chai, Ming Liu

Abstract:

Designing computing-in-memory (CIM) chips with synaptic plasticity can potentially support energy-efficient on-chip learning in edge devices for rapid local task adaptation. Its silicon implementation is challenging as it requires hybridizing nonvolatile and volatile memory (VM) and customized computational operations. In this work, we propose a plastic CIM (P-CIM) macro featuring: 1) …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 13
Year of Publication: 2026
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2026.3652940
Publisher: IEEE

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A 65-nm CMOS Machine-Learning-Enhanced Bandwidth-Efficient LiDAR

A 65-nm CMOS Machine-Learning-Enhanced Bandwidth-Efficient LiDAR 150 150
Author(s): Pooya Poolad, Foad Arvani, Bahaa Radi, Ping-Hsuan Hsieh, Tony Chan Carusone

Abstract:

We present a proof-of-concept light detection and ranging (LiDAR) signal processing architecture that integrates a machine-learning-enhanced processing unit (PU) with on-chip time-to-digital converters (TDCs) to reduce bandwidth and memory requirements in SPAD-based direct time-of-flight (dToF) systems. The proposed architecture fits a Gaussian mixture model (GMM) to photon arrival time distributions …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 11
Year of Publication: 2026
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2026.3652972
Publisher: IEEE

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An Approximate Digital CIM Macro With Low-Power Multiply-Add Units and Dynamic Sparse-Adaptive Configuring for Edge AI Inference

An Approximate Digital CIM Macro With Low-Power Multiply-Add Units and Dynamic Sparse-Adaptive Configuring for Edge AI Inference 150 150
Author(s): Xiaofeng Li, Yi Zhan, Purui Zhu, Rui Zhou, Jiayin Song, Heng You, Yumei Zhou, Shushan Qiao

Abstract:

This letter presents an approximate digital compute-in-memory (CIM) macro for low-power edge AI inference. It introduces three hierarchical innovations: 1) novel fused approximate multiply-add units (FAMUs) that reduces power and area consumption; 2) a bit-critical weight allocation architecture that optimally balances accuracy and hardware cost; and 3) a dynamic sparsity-adaptive configuration method to …

Published in: IEEE Solid-State Circuits Letters
Page(s): 45 – 48
Year of Publication: 2026
Electronic ISSN: 2573-9603
DOI: 10.1109/LSSC.2026.3652570
Publisher: IEEE

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A 3-nm FinFET 563-kbit 35.5-Mbit/mm2 Dual-Rail SRAM With 3.89-pJ/Access High Energy Efficient and 27.5-μW/Mbit One-Cycle Latency Low-Leakage Mode

A 3-nm FinFET 563-kbit 35.5-Mbit/mm2 Dual-Rail SRAM With 3.89-pJ/Access High Energy Efficient and 27.5-μW/Mbit One-Cycle Latency Low-Leakage Mode 150 150
Author(s): Yumito Aoyagi, Koji Nii, Makoto Yabuuchi, Tomotaka Tanaka, Kazuto Mizutani, Masaya Hamada, Yuichiro Ishii, Yen Chi Chou, Jun Cheng Liu, Chien-Yu Huang, Kang-Hui Peng, Yu-Hao Hsu, Isabel Wang, Hong-Chen Cheng, Hung-Jen Liao, Tsung-Yung Jonathan Chang

Abstract:

This article presents a high-density (HD) 6T SRAM macro designed in 3-nm FinFET technology with an extended dual-rail (XDR) architecture, addressing active energy and leakage for mobile applications. Two key innovations are introduced: the delayed-wordline in write operation (DEWL) technique and a one-cycle latency low-leakage access mode (1-CLM). The XDR …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 11
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3639747
Publisher: IEEE

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A 500 MS/s Robust 2b/cycle Pipelined-SAR ADC Achieving 64.6-dB SNDR and 82.6-dB SFDR With Linearity Enhancement Techniques

A 500 MS/s Robust 2b/cycle Pipelined-SAR ADC Achieving 64.6-dB SNDR and 82.6-dB SFDR With Linearity Enhancement Techniques 150 150
Author(s): Qiang Yu, Zheng Zhu, Lulu Zhang, Qin Huang, Yao Feng, Chao Liang, Biao Hu, Ling Du, Rongbin Yang, Shuangyi Wu, Qiang Li

Abstract:

This letter presents a 14-bit 500-MS/s 3-stage pipelined successive approximation register (SAR) analog-to-digital converter (ADC). By exploiting robust 2b/cycle SAR ADCs, this ADC incorporates significant voltage and time redundancy. High SFDR is achieved through several linearity enhancement techniques. First, a DAC splitting technique addresses the common-mode voltage matching …

Published in: IEEE Solid-State Circuits Letters
Page(s): 9 – 12
Year of Publication: 2026
Electronic ISSN: 2573-9603
DOI: 10.1109/LSSC.2025.3639322
Publisher: IEEE

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A High-Speed D-FF and a 11-Bit Up-Down Counter Using Unipolar Oxide TFTs on a Flexible Foil

A High-Speed D-FF and a 11-Bit Up-Down Counter Using Unipolar Oxide TFTs on a Flexible Foil 150 150
Author(s): Suyash Shrivastava, Pydi Ganga Bahubalindruni

Abstract:

This manuscript presents an experimental characterization of a novel high speed D flip-flop (D-FF). The circuit was fabricated on a $27\mu $ m thick flexible polyimide substrate using a nMOS only, single gate amorphous Indium-Gallium-Zinc-Oxide (a-IGZO) thin-film transistor (TFT) technology. Reliable response of the D-FF was noticed from measurements up to …

Published in: IEEE Solid-State Circuits Letters
Page(s): 373 – 376
Year of Publication: 2025
Electronic ISSN: 2573-9603
DOI: 10.1109/LSSC.2025.3636192
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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