Nil Davy will defend his thesis on March 25th, 2024 at 14:00 p.m., (amphi JP. DOM – IMS Laboratory) on the subject : “ InP Double Heterojunction Bipolar Transistor (InP DHBT) optimization for very high-speed integrated circuits”.
In the era of information technology, we are witnessing a continuous increase in the volume of exchanged data. This comes with a constant need to enhance the bandwidth of optical and radio-frequency communication systems. The ongoing demand for increased bandwidth requires the design of faster circuits capable of supporting the growing data traffic. These circuits, in turn, must rely on ever-faster electronic component technologies. It is in this context that InP double-heterojunction bipolar transistors (DHBTs) are developed. Thanks to the properties of III-V semiconductors, these components can operate at very high frequencies (> 500 GHz) while maintaining a relatively high breakdown voltage (> 4V).
This thesis focus on improving the performances of these components. We will begin by addressing the improvement of high-frequency measurements of transistors to evaluate their frequency performance. We will delve into various choices associated with measurements (calibration, de-embedding, RF probe) and introduce new measurement pads. In the second part, we will develop an analytical model, taking into account the specifics of the design and technology of the device. Once calibrated on measurements, this model will be used to determine the main axes for improving performances. Next, we will study the performances of several epitaxial structures with the aim of reducing electron transit time while maximizing frequency performance. A new structure, optimized to maximize the transition frequency without degrading the maximum oscillation frequency, will be proposed. Subsequently, we will investigate the physical phenomena limiting the breakdown voltage of the transistor. Finally, we will focus on the self-heating phenomenon that degrades transistor performance. We will propose a thermal resistance model and associated improvement strategies.
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