This project develops a high-precision maskless lithography system consists of digital light processing, microlens / spatial filters arrays,precision servo-controlled motion technologies. Based on this maskless UV lithographic system, we are able to achieve UV patterning of arbitrarycomplicated 2D/3D microstructures for advanced IC substratepackaging.

Through the technique, SamplingPrediction of Lithography Overlay Errors, the costtime of overlay error measurement can be reduced to improve the process efficiency. We identify key sampling through clusteringmachine learning models,design a new sampling algorithm in photolithography process. Due to the complexity of wafermany training factors of wafer data, we combine the clustering algorithm with incremental learning to meet customers＇ unique needsachieve the goal of optimally samplingreducing the costs.

The DNN models of this technology include a LithoNet, an OPCNet,a layout novelty detection network. LithoNet is a learning-based pre-simulation model for layout-to-SEM contour prediction,OPCnet is a dual network of LithoNet for photomask optimization. Integrated with a well-trained LithoNet, our layout novelty detection network, consisting of a self-attention guided LithoNetan autoencoder, can check if there are layout patterns easily resulting in local distortions in contours of metal lines based on multi-modal (global-local) feature fusion.

"Developed a ferroelectric oxide (HZO) gate for gallium nitride transistor, resulting in high breakdown, high current densityhigh threshold voltage. Best Figure of Merit Performance in the world. Using unique stepper double exposure technology to produce ultra-small linewidth GaN transistors for high-frequency application with Ft300GHz, one of the leading team in the world This technology uses frequency resonance, class E amplifiershigh-frequency rectifier circuits to achieve one-to-many non-contact fast charging. Best in the society for wireless fast chargingmodules."