Personal Information
Professor Supervisor of Doctorate Candidates
Honors and Titles : Excellent Doctoral Thesis of Peking University
Humboldt Fellow
National Talents Plan
Scientific Research
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- Accelerating Photostability Evaluation of Perovskite Films through Intelligent Spectral Learning-Based Early Diagnosis.ACS Energy Letters.2024,9:662–670
- Polymer-acid-metal quasi-ohmic contact for stable perovskite solar cells beyond a 20,000-hour extrapolated lifetime.Nature Communications.2024,15:2314
- A bilayer conducting polymer structure for planar perovskite solar cells with over 1,400 hours operational stability at elevated temperatures..Nature Energy.2021,7:144-152
- Discovery of stability reversal in perovskites using high-throughput robotic learning..Nature Communications.2021,12:2191
- Strain-activated photo-induced halide segregation in mixed-halide perovskite solids.Nature Communications(9):1607
- Perovskite seeding growth of formamidinium-lead-iodide-based perovskites for efficient and stable solar cells..Nature Communications.2018,9:1607
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H&M Group
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Our Vision
New materials are the basis of the scientific and technological revolution. The development of new materials has gradually transitioned from simple materials to a wide variety of multi-element and multi-phase complex material systems, such as high-entropy alloys etc.. The traditional experimental trial-and-error paradigm is no longer effective in developing a large number of new but powerful complex functional materials; therefore, it is urgent to develop a new research paradigm in materials science.
The Zhao Group @UESTC is mainly engaged in the development of "High-throughput Experiment + Machine Learning" intelligent experimental platform and the applications of complex semiconductor materials and electronic devices. High-throughput experiments can realize the preparation and characterization of complex materials and devices, while machine learning provides the capability of real-time analysis, optimization and interpretation of big data produced by high-throughput experiments. The core tools of high-throughput experiments include automated multi-channel pipetting systems, drop/spin coating methods, fluorescence detection, UV-vis-IR absorption spectroscopy, photoelectric detection, expectation-maximization-based spectroscopy analysis, Gaussian-Process Regression algorithm, SHAP explainer etc.. Our devices include novel metal-halide perovskite semiconductors, organic semiconductors and colloidal quantum dots for photovoltaic, sensing and detection applications.
Our Tools
High-speed multi-channel pipetting system | Solution-processed films via drop-casting spin-coating
High-throughput spectroscopic analysis | Machine learning and model explainer
Our devices
Solution-processed solar cells | Molecule-specific sensors | Low/high-energy photodetecto
We are hiring! Positions for PhD sutdents, Postdocs, Ms students who are interested in complex semiconductors, optoelectronic devices, high-throughput experiments, machine learning, big data, statistics, optical spectroscopy
Location: Qingshuihe Campus:No.2006, Xiyuan Ave, West Hi-Tech Zone, 611731 | Chengdu, Sichuan, P.R.China
