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Emerging memory explained: MRAM, ReRAM, PCM

Emerging memory technologies explained in plain language: how MRAM, ReRAM and phase-change memory store data, their pros and cons and where they are used today.

Deep techPublished

Emerging memory technologies store information in a physical property of a material, such as magnetisation, electrical resistance or atomic structure, rather than as stored electric charge. The three best-known families are MRAM (magnetoresistive RAM), ReRAM (resistive RAM) and PCM (phase-change memory). All of them are non-volatile, meaning they keep data without power, and they are being developed to close the gap between fast but volatile working memory and slower, denser flash storage.

Why new kinds of memory?

Computers use a hierarchy of memories, each with a compromise between speed, capacity, cost and energy:

Memory Speed Keeps data without power Typical use
SRAM Very fast No Caches inside processors
DRAM Fast No Main working memory
NAND flash Slower, especially for writing Yes SSDs, memory cards, phones
Embedded flash Moderate Yes Program storage in microcontrollers
MRAM, ReRAM, PCM Between DRAM and flash, depending on design Yes Embedded memory, specialised products, research

Two pressures drive interest in alternatives. First, embedded flash becomes harder to integrate as chip manufacturing shrinks to smaller structures. Second, moving data between memory and processor costs a large share of energy in modern computing, which motivates memories that sit closer to the logic or even compute inside the memory.

MRAM: storing bits in magnetism

MRAM stores each bit in a magnetic tunnel junction: two ferromagnetic layers separated by a very thin insulating barrier. One layer has a fixed magnetic orientation, the other can be switched. When both point in the same direction, electrical resistance is low; when they point in opposite directions, it is higher. Reading means measuring that resistance.

Modern variants such as spin-transfer torque MRAM (STT-MRAM) switch the free layer with a spin-polarised current, and spin-orbit torque MRAM (SOT-MRAM) is a research direction that separates the read and write paths.

  • Strengths: fast, very high endurance, non-volatile, robust against radiation, compatible with standard chip processes.
  • Limitations: more complex manufacturing, lower density than flash, and a trade-off between how long data is retained and how much energy writing takes.

ReRAM: switching resistance in an oxide

ReRAM cells consist of a thin insulating layer, often a metal oxide, between two electrodes. Applying a voltage forms or dissolves a tiny conductive path, often called a filament, which switches the cell between high and low resistance.

  • Strengths: simple structure, low-voltage operation, potential for dense 3D stacking, and the ability to store intermediate resistance levels, which is interesting for analogue and neuromorphic computing.
  • Limitations: variability from cell to cell and cycle to cycle, and endurance that is generally lower than MRAM.

PCM: from glass to crystal

Phase-change memory uses materials, typically chalcogenide alloys, that can switch between an amorphous (disordered, high resistance) and a crystalline (ordered, low resistance) state. A short, strong current pulse melts and quickly cools a small volume into the amorphous state; a longer, gentler pulse lets it crystallise.

The same family of materials was long used in rewritable optical discs, where the two phases reflect light differently.

  • Strengths: mature physics, good scalability, multiple resistance levels per cell.
  • Limitations: relatively high write energy because of the heating, and a gradual drift of resistance over time in the amorphous state.

Where the industry stands

The picture changes quickly, so treat this as an overview as of October 2026, not a market report:

  • Several large semiconductor foundries offer embedded MRAM in their process portfolios, aimed at microcontrollers, automotive and low-power devices.
  • Embedded ReRAM is offered or announced by foundries and specialised IP companies, with a broad ecosystem around it.
  • A high-profile storage-class memory product line based on a resistive cross-point technology was discontinued in the early 2020s, which showed how hard it is to compete with DRAM and flash on cost.
  • Research continues on other candidates, such as ferroelectric memories, and on using resistive memories for in-memory and neuromorphic computing.

How to follow this field

If you want to dig deeper, start with review articles and conference proceedings in device physics and electronics; a structured literature search in databases such as IEEE Xplore helps. Major device conferences publish many first results, and our guide to submitting to a conference and giving the talk explains how such meetings work. Because memory research is close to industry, patents matter here too; see patents for researchers. And if you are preparing your own results, how to publish a research paper walks through the process.

Frequently asked questions

What does non-volatile memory mean?

Non-volatile memory keeps its data when the power is switched off. Flash memory in USB sticks and SSDs is non-volatile; the DRAM working memory in a computer is volatile and loses its content without power.

Is MRAM already used in products?

Yes. Standalone MRAM chips have been available for years for specialised applications, and several semiconductor foundries offer embedded MRAM as an option in their manufacturing processes, for example for microcontrollers and automotive chips. Adoption is growing but still limited compared with flash and DRAM.

Will these technologies replace DRAM and SSDs?

Not in the foreseeable future in general-purpose computers. DRAM and NAND flash are extremely mature and cheap per bit. Emerging memories are more likely to fill specific niches, such as replacing embedded flash or enabling new computing approaches.

What is in-memory computing?

In-memory computing performs some calculations directly inside memory arrays instead of moving data back and forth to a processor. Resistive memories such as ReRAM and PCM are studied for this because their conductance can represent numerical weights in neural networks. Much of this work is still at research stage.