Operation Regimes and Design Principles of Delta-E Effect Sensors

TL;DR

This study systematically investigates delta-E effect sensors, revealing three operation regimes influenced by magnetic layer geometry, which are crucial for optimizing sensitivity and noise performance in weak magnetic field detection.

Contribution

The paper provides a comprehensive experimental and simulation analysis of how magnetic layer geometry affects delta-E sensor regimes, enabling targeted performance optimization.

Findings

Identified three distinct operation regimes: electronic noise, magnetic noise, and nonlinearities.

Demonstrated how magnetic layer thickness shifts regime boundaries.

Provided insights for tailoring sensor design to improve detection limits.

Abstract

Delta-E effect-based magnetoelectric sensors have emerged as promising technology for detecting weak magnetic fields at low frequencies. However, the performance of such sensors remains difficult to predict, as signal and noise characteristics are dictated by interdependent parameters such as magnetic layer geometry, magnetic microstructure, and loss. In this work, we present a systematic experimental study of sub-mm-sized delta-E effect sensors, comprising 24 device configurations that vary in magnetic layer thickness and lateral dimensions. The sensors are statistically analyzed to identify the influence of magnetic layer geometry on performance through a combination of measurements and simulations. Our findings reveal three distinct operation regimes - dominated by electronic noise, magnetic noise, and nonlinearities - whose boundaries shift systematically with magnetic layer thickness. This regime behavior governs the trade-offs between sensitivity and noise, ultimately determining the sensor's limit of detection. Based on these results, the dependency of the regime boundaries on key device parameters is discussed in detail, providing fundamental insights for tailoring sensor performance. As such, this study establishes a necessary foundation for targeted performance optimization and the scalable design of advanced delta-E effect sensor systems.