Engineering topics

Wu, Changming

Publications and source records attributed to Wu, Changming.

2 records

DOE OSTI2024

Post-processing of phase change material in a zero-change commercial silicon photonic process

Integration of phase change material (PCM) with photonic integrated circuits can transform large-scale photonic systems by providing non-volatile control over phase and amplitude. The next generation of commercial silicon photonic processes can benefit from the addition of PCM to enable ultra-low power, highly reconfigurable, and compact photonic integrated circuits for large-scale applications. Despite all the advantages of PCM-based photonics, today’s commercial foundries do not provide them in their silicon photonic processes yet. We demonstrate the first-ever electrically programmable PCM device that is monolithically post-processed in a commercial foundry silicon photonics process using a few fabrication steps and coarse-resolution photolithography. These devices achieved 1.4 dB/μm of amplitude switching contrast using a thin layer of 12.5 nm GeSbTe in this work. We have also characterized the reconfiguration speed as well as repeatability of these devices over 20,000 switching cycles. Our solution enables non-volatile photonic VLSI systems that can be fabricated at low cost and high reliability in a commercial foundry process, paving the way for the development of non-volatile programmable photonic integrated circuits for a variety of emerging applications.

Optics↗

DOE OSTI2020

On-the-fly closed-loop materials discovery via Bayesian active learning

Active learning—the field of machine learning (ML) dedicated to optimal experiment design—has played a part in science as far back as the 18th century when Laplace used it to guide his discovery of celestial mechanics. In this work, we focus a closed-loop, active learning-driven autonomous system on another major challenge, the discovery of advanced materials against the exceedingly complex synthesis-processes-structure-property landscape. We demonstrate an autonomous materials discovery methodology for functional inorganic compounds which allow scientists to fail smarter, learn faster, and spend less resources in their studies, while simultaneously improving trust in scientific results and machine learning tools. This robot science enables science-over-the-network, reducing the economic impact of scientists being physically separated from their labs. The real-time closed-loop, autonomous system for materials exploration and optimization (CAMEO) is implemented at the synchrotron beamline to accelerate the interconnected tasks of phase mapping and property optimization, with each cycle taking seconds to minutes. We also demonstrate an embodiment of human-machine interaction, where human-in-the-loop is called to play a contributing role within each cycle. This work has resulted in the discovery of a novel epitaxial nanocomposite phase-change memory material.

36 MATERIALS SCIENCE↗