Work

Radiation-Hardened—AI-Accelerated Custom IC Design Methodology

Year: 2025

Type: article

Abstract: In this work, a radiation hardened - AI accelerated custom IC design methodology is proposed. The methodology employs reinforcement learning (RL) to optimize the IC design process, integrating radiation dosage performance degradation assessments and radiation-hardened-by-design (RHBD) MOSFET cell implementations at both schematic and layout levels. This approach streamlines the development of radiation-immune silicon products by embedding artificial intelligence to accelerate the design process and advanced radiation hardening strategies directly into the standard design flow. To validate the proposed framework, a charge-sensitive amplifier (CSA) based on a folded-cascode architecture is designed and assessed in a 180 nm standard CMOS process, demonstrating the efficiency of the methodology in radiation-resilient analog front-end systems.

Source: IEEE Access

DOI: 10.1109/access.2025.3574058

Authors: Vasiliki Gogolou, Savvas Karipidis, Eleni Papageorgiou, Anastasios Michailidis, Thomas Noulis

Institution: Aristotle University of Thessaloniki

Language: English

Topic: Radiation Effects in Electronics

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,075