A multi-port grid array antenna (GAA) system with an optimized dielectric radome is proposed to enhance the beam steering coverage. Based on the patterns of a nine-port GAA, a dielectric radome is designed to enhance the beam steering coverage to 60° (±30°). The enhancement is validated by assembling the GAA and a 3D-printed radome using Acrylonitrile Butadiene Styrene (ABS) material at 28 GHz.

In this paper, we've developed an inverse design framework for optical thin-films assisted by Generative Pre-trained Transformers (GPT). As a Large Language Models (LLMs)-powered tool, this creates an integrated platform for users to perform various functions related to inverse design on thin-films using an accessible and unique natural language interface via the assistant tool. With the consultant tool, users can query important design information and receive relevant answers to enhance the design knowledge of optical thin-films. This platform proves capable of speeding up design of thin-film structures compared to traditional ways and can also save many hours for repeated knowledge querying. The developed platform significantly reduces the resources and time (~3 x) for designers in developing optical thin-films to reach an optimal design. This will allow the thin-films' applications to be brought to the market faster and with increased efficiency.

In this paper, we present a novel method for the generative design of pixelated microstrip Millimeter-Wave (mm-wave) circuit components. Our approach utilizes a primary meandering transmission line, which is connected to the input and output/terminated ports, with random small pixelated patches surrounding the primary transmission line as perturbations. A 2D Convolutional Neural Network (CNN) incorporating a Convolutional Block Attention Module (CBAM) is trained and employed as a forward solver to predict the input impedance of the circuit component. Additionally, a Variational Autoencoder (VAE) is trained to generate new pixelated microstrip mm-wave circuit component patterns by sampling from the latent space, thereby extending beyond the original training dataset. By leveraging the CNN-based forward solver for impedance prediction and the VAE for pattern generation, we can inversely generate the mm-wave circuit component design that meets specific input impedance requirements.

The collective acoustic pressure output of a piezoelectric ultrasound transducer array is limited by the residual stress induced non-uniformity of resonant frequencies among neighboring transducers. This limits the performance of array-level applications such as mid-air haptic feedback and range-finding. We propose a novel design with sector-shaped slits in the Lead Zirconate Titanate (PZT) layer of the transducer to not only reduce the sensitivity to residual stresses by 2.1×, but also to boost the baseline acoustic pressure output by 9.4 × as demonstrated by finite element analysis. Our patented design can be combined with the recent sputtered PZT platform to enable smaller transducer arrays with fewer transducers and high acoustic pressure output to enable future integration into mobile devices.

Piezoelectric ultrasound transducers have been commercialized by industry. However, the trade-off between acoustic pressure output and the sensitivity of resonant frequencies to the non-uniformity of residual stresses in the piezoelectric layer (known as stress sensitivity) has not been fully addressed. We present a novel combination of our patented slitted membrane design with our Sodium Niobate piezoelectric material. Our combination not only reduces the stress sensitivity by 4.9×, but also increases the acoustic pressure output by 35×. This brings our figure-of-merit to ($4.9\times 35$) 172× improvement over fully clamped Aluminum Nitride membranes.

Fast Fourier Transform (FFT) is an essential algorithm for numerous scientific and engineering applications. It is key to implement FFT in a high-performance and energy-efficient manner. In this paper, we leverage the properties of ultrasonic wave propagation in silicon for FFT computation. We introduce SonicFFT: A system architecture for ultrasonic-based FFT acceleration. To evaluate the benefits of SonicFFT, a compact-model based simulation framework that quantifies the performance and energy of an integrated system comprising of digital computing components interfaced with an ultrasonic FFT accelerator has been developed. We also present mapping strategies to compute 2D FFT utilizing the accelerator. Simulation results show that SonicFFT achieves a$2317\times$system-level energy-delay product benefits-a simultaneous$117.69\times$speedup and$19.69\times$energy reduction-versus state-of-the-art baseline all-digital configuration.