Minimisation of Parasitic Capacitance in Lumped-Element Electro-Absorption Modulators for High-Speed Optical Components

Mulcahy, Jack; Shi, Shengtai; Peters, Frank H.; Dai, Xing

doi:10.3390/photonics10080885

Cited by 2 publications

(1 citation statement)

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“…The grid design affects the wiring's parasitic capacitance and its projection area on the grid reference plane, where the latter also affects the former. In high-frequency circuits, it is essential to maintain the parasitic capacitance values as low as possible [38], as even small variations in this parameter can cause a significant frequency shift [39].…”

Section: Introductionmentioning

confidence: 99%

Fast Prediction Method for Scattering Parameters of Rigid-Flex PCBs Based on ANN

Mei,

Yuan,

Guo

et al. 2024

Sensors

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InGaAs detection systems have been increasingly used in the aerospace field, and due to the high signal-to-noise ratio requirements of short-wave infrared quantitative payloads, there is an urgent need for methods for the rapid and precise evaluation and the optimal design of these systems. The rigid-flex printed circuit board (PCB) is a vital component of InGaAs detectors, as its grid ground plane design parameters impact parasitic capacitance and thus affect weak infrared analog signals. To address the time-intensive and costly nature of design optimization achieved with simulations and experimental measurements, we propose an innovative method based on a neural network to predict the scattering parameters of rigid-flex boards for InGaAs detection links. This is the first study in which the effects of rigid-flex boards on weak infrared detection signals have been considered. We first obtained sufficient samples with software simulation. A backpropagation (BP) neural network prediction model was trained on existing sample sets and then verified on a rigid-flex board used in a crucial aerospace short-wave infrared quantitative mission. The model efficiently and accurately predicted high-speed interconnect scattering parameters under various rigid-flex board grid plane parameter conditions. The prediction error was less than 1% compared with a 3D field solver, indicating an overcoming of the iterative optimization inefficiency and showing improved design quality for InGaAs detection circuits.

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Section: Introductionmentioning

confidence: 99%