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This is why we are here.

Research

Research Themes

Our lab research focus on charge transport and failure mechanism in electroceramics for next-generation energy technologies. The primary focus lies in the fundamental understanding of charge transport at interfaces and the failure mechanisms in novel energy storage and conversion systems.


1. Charge Transport / Transfer in Electroceramics

Charge transport and transfer in electroceramics has implications for a broad range of materials and technologies such as solid oxide fuel cells, solid state batteries, and memristors. However, many questions remain unanswered due to the insufficient of fundamental understanding.

  • Can the ionic conductivity of electroceramics be further enhanced? If yes, what mechanism and methods can offer?
  • What is the coupled mechanism and synergistic effect involving charge, photons, phonons, and more?
  • Is there a literally ionic superconductor?

2. Operando and Multimodal Characterization

In advanced electrochemical systems, ex-situ characterization methods are widely used to study interfacial or bulk behaviors of active materials including morphology, chemistry, and crystallinity. However, the ex-situ characterization requires disassembling electrochemical cells, post-treating samples, and transferring to characterization tools without available air-free transfer vessels, which might alter the real chemical and structural information and create a discrepancy between studies.

Therefore, it is essential to apply operando and multimodal characterization in understanding dynamic behavior in electrochemical systems. But…

  • How can we design a suitable platform to achieve this?
  • Is there a feasible approach to develop a multimodal method capable of encompassing all material properties comprehensively?
     

3. High-throughput Discovery of Novel Energy Materials

Machine learning and AI-assisted methods have found extensive application in the field of advanced energy technologies. These techniques are employed for diverse purposes, including performance prediction, failure analysis, and materials discovery.

However, several critical questions are emerging…

  • Do we understand the science behind the materials that AI suggests?
  • How quickly can we test and confirm them in the lab?
  • How much can we trust AI—and in turn, does AI trust us?