SK hynix to change wafer cutting for HBM4 memory and 400-layer NAND flash, pushing new limits

SK hynix to reportedly change wafer cutting for its next-gen HBM4 memory and 400-layer NAND flash, as they're becoming increasingly thin.

SK hynix to change wafer cutting for HBM4 memory and 400-layer NAND flash, pushing new limits
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TL;DR: SK hynix is reportedly planning to introduce femto-second grooving and full-cut processes to its HBM4 and 400-layer and higher NAND flash, a move required as semiconductors get thinner and thinner, and more advanced as the months fly by.

SK hynix is reportedly changing its wafer cutting process for next-generation memory manufacturing, paving the way for its new HBM4 and 400-layer and higher NAND flash memory as they become increasingly thin, pushing existing processes to their absolute limits.

In a new story from ETnews picked up by insider @Jukanrosleve on X, industry sources have said that SK hynix plans to introduce femto-second grooving and full-cut processes for HBM4 wafer cutting. The news was confirmed by the South Korean memory manufacturer in discussing a Joint Evaluation Project (JEP) for new wafer cutting equipment with laser equipment partners.

It's reported that technology tests are already underway with some partners, with an industry official saying: "SK hynix is planning a major change to its existing wafer cutting methods and is discussing numerous technical solutions with partners".

SK hynix has until now used mechanical cutting (with a blade) or stealth dicing technologies to cut wafers, with mechanical cutting involving slicing the wafer with a diamond wheel, while stealth dicing separates the wafer by creating internal cracks. These methods have been the dominant technologies for cutting wafers into individual chips (dies) after circuit patterns are drawn.

However, the difficulty has increased over time as wafers for advanced semiconductors are becoming progressively thinner. Mechanical cutting is primarily used for wafer thicknesses of around 100 micrometers (㎛), while stealth dicing for around 50㎛. SK hynix's new HBM4 memory is even thinner, with HBM4 wafers at 20-30㎛.

An industry official said: "If a cutting method inappropriate for the wafer thickness is used, foreign particles can be generated, or micro-cracks can easily form in the wafer, which can negatively affect semiconductor yield".

SK hynix is set to switch over to femto-second laser grooving and full-cut methods for HBM4 and 400-layer and high NAND flash, with femto-second lasers generating ultra-short laser pulses, lasting "one-quadrillionth of a second", which reduces defects, and allows for highly precise wafer cutting. SK Hynix has put forward two methods as candidates: pre-grooving the parts that need to be cut, or completely separating the wafer at once with a laser (full cut).

SK hynix plans to use this method for both HBM4 and 400-layer and higher NAND, with 400-layer NAND onwards, the "cell" area for data storage and the "peripheral" circuit area that drives it are implemented on different wafers. These two wafers must be incredibly thin, and they needed to be bonded together.

As the company shifts towards its wafer cutting process, the spread of femto-second laser technology in the semiconductor industry is expected to accelerate. TSMC, Micron, and Samsung Electronics have previously adopted femto-second lasers for advanced semiconductor wafer cutting.

SK hynix remarked about the process change, saying: "various options are under consideration, but nothing has been specifically decided yet".

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News Source:etnews.com

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Anthony joined TweakTown in 2010 and has since reviewed 100s of tech products. Anthony is a long time PC enthusiast with a passion of hate for games built around consoles. FPS gaming since the pre-Quake days, where you were insulted if you used a mouse to aim, he has been addicted to gaming and hardware ever since. Working in IT retail for 10 years gave him great experience with custom-built PCs. His addiction to GPU tech is unwavering and has recently taken a keen interest in artificial intelligence (AI) hardware.

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