Preprint / Version 4

Semiconductor Switching Theory: Formalizing Semiconductor Switching Dynamics and Bridging Circuit Theory, Conservation Laws, and Semiconductor Physics

##article.authors##

  • Wucheng Ying Electrical Engineering Division, Department of Engineering, University of Cambridge
  • Hui Zhao College of Intelligent Robotics and Advanced Manufacturing, Fudan University
  • Jinwei Qi School of Microelectronics, Xi'an Jiaotong University, Xi'an, China
  • Ameer Janabi Electrical Engineering Division, Department of Engineering, University of Cambridge
  • Ziheng Yu
  • Yanfeng Shen
  • Biao Zhao
  • Teng Long Electrical Engineering Division, Department of Engineering, University of Cambridge

DOI:

https://doi.org/10.31224/5474

Keywords:

power electronics, switching analysis, Transistors, electrical and electronic engineering

Abstract

Global electricity demand is expected to more than double by 20501-8, driven by emerging loads including AI data centres,3,4 electrified transport5,6, heat pumps7,  electrolytic hydrogen production8 and robotics2. The global sustainability urgently demands green electrical and electronic engineering (EEE), where semiconductors are central components. However, since 19479, semiconductor switching has remained largely empirical or phenomenological, owing to the lack of a unified causal-deterministic formulation of switching dynamics and a bridge between macroscopic and microscopic perspectives. Consequently, it imposes fundamental limits on semiconductor science, engineering and downstream applications, whilst leaving these domains to traditionally evolve separately. Here we present Semiconductor Switching Theory (SST), which formalizes semiconductor switching dynamics within a unified causal-deterministic formulation and bridges circuit theory10, conservation laws and semiconductor physics. Its demonstrated implications include laying the foundation for the theoretical system, including fundamental modelling, deterministic predictability and causal-mechanistic interpretability. For example, SST yields a switching-energy-loss model (errors: 0.88–11.60%), which achieves a 17-fold average error reduction compared to the conventional model (errors: 34.41–80.05%); SST enables unprecedented causal-mechanistic interpretability of switching waveforms as manifestations of underlying switching dynamics. Furthermore, its prospective implications include informing semiconductor science, engineering and downstream applications, whilst laying the foundation for bridging these traditionally separate domains, including through future cross-disciplinary integrated research and future cross-hierarchical co-design. SST may help identify directions across disciplines such as semiconductor materials,11,12 chip design,13,14 packaging,15,16 reliability,17,18 thermal management;19,20 downstream applications such as power electronics; and may extend across EEE sub-fields, including higher-frequency communication, computation devices and integrated circuits.21,22

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Posted

2025-09-29 — Updated on 2026-05-15

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Version justification

Significant revision has been made - including the title and content.