This paper demonstrates a new type of magnetic sensor using a perpendicular spin transfer torque magnetic tunnel junction. The sensing element has a cylindrical shape of 50 nanometers in diameter and is to our knowledge among the smallest magnetic sensor ever reported. This paper describes the principle of operation of the sensing element and the associated signal processing electronics, which delivers a signal proportional to the external magnetic field. Experimental results are detailed and compared to state-of-the-art commercially available integrated magnetic sensors as well as published magnetoresistive sensors based on magnetic tunnel junctions with comparable size. The measured sensitivity of the developed sensor is 1.28 V/T, and its dynamic range reaches 80 mT. The measured noise level is 21.8 μT/√Hz. Two different operating principles of the proposed sensor are described and compared, one based on a time-to-digital converter and one based on a pulse-width-modulated signal. Both methods require only standard microelectronics components, which are suitable for a monolithic integration of the sensing element with its conditioning electronics. Subsequent improvements of the sensing element as well as conditioning electronics are required to further lower the noise level. The sensing element and its conditioning electronics are compatible with fabrication processes already used in magnetic random-access memory fabrication. This opens the way to mass production and addresses various markets such as consumer electronics, automotive, industrial sensing, physics experiments or medical devices.

This paper presents a tracking system using magnetometers, possibly integrable in a deep brain stimulation (DBS) electrode. DBS is a treatment for movement disorders where the position of the implant is of prime importance. Positioning challenges during the surgery could be addressed thanks to a magnetic tracking. The system proposed in this paper, complementary to existing procedures, has been designed to bridge preoperative clinical imaging with DBS surgery, allowing the surgeon to increase his/her control on the implantation trajectory. Here the magnetic source required for tracking consists of three coils, and is experimentally mapped. This mapping has been performed with an in-house three-dimensional magnetic camera. The system demonstrates how magnetometers integrated directly at the tip of a DBS electrode, might improve treatment by monitoring the position during and after the surgery. The three-dimensional operation without line of sight has been demonstrated using a reference obtained with magnetic resonance imaging (MRI) of a simplified brain model. We observed experimentally a mean absolute error of 1.35 mm and an Euclidean error of 3.07 mm. Several areas of improvement to target errors below 1 mm are also discussed.

We recently demonstrated the possibility to model and to simulate biological functions using hardware description languages (HDLs) and associated simulators traditionally used for microelectronics. Nevertheless, those languages are not suitable to model and simulate space-dependent systems described by partial differential equations. However, in more and more applications space- and time-dependent models are unavoidable. For this purpose, we investigated a new modeling approach to simulate molecular diffusion on a mesoscopic scale still based on HDL. Our work relies on previous investigations on an electrothermal simulation tool for integrated circuits, and analogies that can be drawn between electronics, thermodynamics, and biology. The tool is composed of four main parts: a simple but efficient mesher that divides space into parallelepipeds (or rectangles in 2D) of adaptable size, a set of interconnected biological models, a SPICE simulator that handles the model and Python scripts that interface the different tools. Simulation results obtained with our tool have been validated on simple cases for which an analytical solution exists and compared with experimental data gathered from literature. Compared with existing approaches, our simulator has three main advantages: a very simple algorithm providing a direct interface between the diffusion model and biological model of each cell, the use of a powerful and widely proven simulation core (SPICE) and the ability to interface biological models with other domains of physics, enabling the study of transdisciplinary systems.