August 4, 2016

Stanford, SLAC Team Reveals Nanoscale Secrets of Rechargeable Batteries

An interdisciplinary team has developed a way to track how particles charge and discharge at the nanoscale, an advance that will lead to better batteries for all sorts of mobile applications.

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Devereaux was honored for contributions to materials science and was among seven Stanford-affiliated researchers named AAAS Fellows this year.

Thomas Devereaux
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Seen in atomic detail, the seemingly smooth flow of ions through a battery’s electrolyte is a lot more complicated.

Photo of the laser lab apparatus used in the hopping ions experiment.
News Feature

Researchers have discovered that crystals can twist when they are sandwiched between two substrates – a critical step toward exploring new material properties for...

This image shows a diffraction pattern of gold nanodics between substrates.
News Brief

Devereaux was honored for contributions to materials science and was among seven Stanford-affiliated researchers named AAAS Fellows this year.

Thomas Devereaux
News Feature

Seen in atomic detail, the seemingly smooth flow of ions through a battery’s electrolyte is a lot more complicated.

Photo of the laser lab apparatus used in the hopping ions experiment.
News Feature

Researchers have discovered that crystals can twist when they are sandwiched between two substrates – a critical step toward exploring new material properties for...

This image shows a diffraction pattern of gold nanodics between substrates.
News Feature

Strongly interacting electrons in quantum materials carry heat and charge in a way that’s surprisingly similar to what individual electrons do in normal metals...

An illustration shows electrons transporting heat from a warmer to a cooler area of a material.
News Brief

The American Physical Society recognized the SLAC and Stanford physicist for decades of groundbreaking work studying the strange behavior of electrons at the interfaces...

Photo - Harold Hwang
News Feature

The research reveals the potential for machine learning in understanding the complex behavior of quantum materials.

machine learning