Zhi Li

Quantum Film Process Engineer @STMicroelectronics

Fremont, CA, US
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WORK HISTORY

Aug 2021 — Present

Quantum Film Process Engineer @STMicroelectronics

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Fremont, CA, US

Designed 300/200mm wafer-level quantum film process for efficient photodetectors and image sensors. Managed quantum film process transfer between fabs in ST (Taiwan → Crolles, France). Responsible for reporting device test structure data and planning iterative device builds to optimize desired metrics. Planned and coordinated quantum film reliability tests to understand and improve device stability (e.g, HTOLi, HTS, scratch test, lasertan). Brought up and improved quality control…

EDUCATION

2012 — 2017

UC Santa Barbara

Doctor of Philosophy (Ph.D.), Chemistry

2005 — 2009

Tianjin University

Bachelor of Engineering - BE, Materials Science and Engineering

2009 — 2012

Nankai University

Master of Science - MS, Chemistry

ABOUT ZHI LI

Materials scientist with 15 years of hands-on experience designing, developing, and characterizing optical, semiconducting, and electronic materials, specialized in design and fabrication of high-performance thin-film photovoltaic devices. Proven achievements in the R&D of small-molecule solar cells with a record efficiency of 6.1% in 2011. Experienced in the design and synthesis of organic and inorganic compounds with desired photochemical and photophysical properties. Experienced and familiar with most characterization tools for small molecule identification. Proven achievement is synthesizing dinuclear transition metal carbonyl complexes to achieve near-IR carbon monoxide releasing in biological systems. Specialized in scaling up benchtop syntheses and designed corresponding high-throughput synthetic workflow. Proficient in programming liquid-handling robots to perform the syntheses of inorganic materials. Proven achievements are 1) designed and tested two robotic, synthetic workflows for metal halide perovskite materials. 2) lead an experiment team to perform reactions for perovskite materials and discovered 32 new materials. 3) developed several high-throughput characterization methods for the synthetic workflows. Currently focusing on using machine learning and active learning to accelerate new perovskite material discovery and design. Working with software engineers to develop experiment-management software. Mentoring students on deep learning image classification for metal halide perovskite crystals.

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