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New method could slash computer memory energy use by orders of magnitude

New method could slash computer memory energy use by orders of magnitude

New Capabilities

University of Edinburgh researchers design magnetic pulses that flip bits with far less energy

Yesterday: Findings reported widely

Overview

Updated 1 hour ago

Every time a computer flips a bit from 0 to 1, it spends energy. Researchers at the University of Edinburgh have found a way to make that flip dramatically cheaper by treating the magnetic pulse that does the switching as a math optimization problem.

Simulations suggest the method could cut switching energy by up to 100x compared with today's leading memory technologies, bringing devices close to the Landauer limit, the thermodynamic floor for processing a single bit. That matters because data centers powering AI already consume enormous electricity, and demand keeps climbing.

Why it matters

If the method works in hardware, AI data centers could cut memory energy use by 100x, approaching physics' fundamental limit.

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Key Indicators

100x
Potential energy reduction
Up to two orders of magnitude less energy for magnetic switching in simulations
3
Memory technologies compared
DRAM, STT-MRAM, and SOT-MRAM all show higher switching energy in simulations
2026
Publication year
Published in Advanced Materials on September 6, 2026

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People Involved

Organizations Involved

Timeline

2 events Latest: Yesterday
  1. Findings reported widely

    Latest Media coverage

    ScienceDaily and tech outlets report the research, highlighting the potential 100x energy reduction for memory switching.

  2. Paper published in Advanced Materials

    Publication

    The University of Edinburgh team publishes its optimal control framework for magnetic switching in van der Waals magnets.

Historical Context

3 moments from history that rhyme with this story — and how they unfolded.

1961

Landauer's principle (1961)

Rolf Landauer at IBM showed that erasing one bit of information must dissipate at least kT ln(2) of energy, about 0.017 electronvolts at room temperature. This set a thermodynamic floor for all computing.

Then

The result was largely theoretical for decades, with real devices consuming millions of times more energy per operation.

Now

The Landauer limit became a benchmark for energy-efficient computing research, and the Edinburgh team's work is explicitly measured against it.

Why this matters now

The Edinburgh team's simulations bring magnetic switching within striking distance of this fundamental limit.

1988

Giant magnetoresistance discovery (1988)

Albert Fert and Peter Grünberg independently discovered that tiny magnetic field changes produce large resistance changes in layered materials. The finding won the 2007 Nobel Prize in Physics.

Then

Within a decade, GMR read heads appeared in commercial hard drives, enabling a rapid increase in storage density.

Now

GMR became the foundation of spintronics and showed how fundamental magnetism research can transform the storage industry.

Why this matters now

Like GMR, the Edinburgh framework is a fundamental physics insight that could take years to reach commercial hardware, but could reshape memory technology if it does.

2000s

STT-MRAM development (2000s)

Spin-transfer torque magnetic random access memory moved from lab demonstrations to commercial products over more than a decade. Companies like Everspin brought STT-MRAM to market, but adoption was slow.

Then

STT-MRAM found niche applications in embedded systems and industrial storage.

Now

The technology showed that magnetic memory can compete with DRAM and flash, but the path from research to market is long.

Why this matters now

The Edinburgh team's framework targets the same class of magnetic memory, and the STT-MRAM timeline shows how long experimental validation and commercialization can take.

Sources

(4)