# @ucberkeleyofficial on Instagram

- **Type:** Image
- **Original URL:** https://www.instagram.com/p/DNB3Y67h1im
- **Gondola URL:** https://gondola.cc/posts/64635434-ucberkeleyofficial-instagram
- **Thumbnail:** https://img.gondola.cc/tr:w-,h-,fo-auto/postThumbnails/5a21dfaaec.jpg
- **Posted:** 2025-08-06T21:46:03.000+00:00
- **Account Owner:** UC Berkeley (@ucberkeleyofficial) — https://gondola.cc/ucberkeleyofficial

## Caption

UC Berkeley professor Junqiao Wu has spent over a decade working with vanadium dioxide, a compound known for its ability to shift between insulating and metallic states. Now, his team has discovered a new application for this versatile material.

In a recent study, Wu and his team demonstrated how vanadium dioxide can also be used to help electronic sensors more efficiently interface with wet, salty systems — a persistent problem for scientists and engineers.

“This breakthrough could pave the way for simpler, more energy-efficient sensors and adaptive robots capable of operating in complex environments,” said Wu, the study’s principal investigator and the Chancellor’s Professor in the Department of Materials Science and Engineering. 

The innovative design uses phase-shifting material, which enables electronic sensors to function like biological neurons.

Wu explained that their memsensing technology may someday be useful in designing low-power aquatic robotics. Such robots could explore underwater or contaminated environments while adapting their movements like living organisms.

“In a broader sense, the underlying principles point toward the possibility of brain-inspired computing in wet environments — just like our own brain, which operates in a salty, aqueous medium,” he said. “In such systems, devices could sense, store and process chemical information spontaneously, all within a single, integrated platform.”

🔗 Full berkeley_engineering story linked in our bio: http://bit.ly/40UDfTt

#UCBerkeleyResearchImpact #BrainLikeBerkeley🧠

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## Tags

ucberkeleyresearchimpact, brainlikeberkeley

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