摘要：Air-core magnetometers are amongst the most commonly used magnetic field detectors in biomedical instruments. They offer excellent sensitivity, low fabrication complexity and a robust, cost-effective solution. However, air-core magnetometers must be tailored to the specific application to achieve high sensitivity, which can be decisive in the accuracy of the diagnoses and the time required for the examination. Existing methods proposed for the design of air-core magnetometers are based on simplified models and simulations using a reduced number of variables, potentially leading to sensitivity that is suboptimal. To circumvent this we chose a method with fewer assumptions and a larger number of decision variables which employed a genetic algorithm, a global optimisation method. Experimental validation shows that the model is appropriate for the design of highly sensitive air-core magnetometers. Moreover, our results support the suitability of a genetic algorithm for optimization in this context. The new method described herein will be made publicly available via our website to facilitate the development of less costly biomedical instruments using air-core magnetometers with unprecedented sensitivity.
