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Posts Tagged ‘non-volatile memory’

XPoint NVM Array Process Engineering

Wednesday, October 18th, 2017

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By Ed Korczynski, Sr. Technical Editor

Now that TECHINSIGHTS has published a teardown of a 3D XPoint array, we have seen cross-section transmission electron micrographs (TEM) of the device. From first principles of process engineering, we can make educated guesses as to the process flows and challenges in creating this type of non-volatile memory (NVM) integrated circuit (IC). Evolution of device technology over more than fifteen years has resulted in cross-point arrays connecting precise stacks of chalcogenide materials. Intel with “Optane” and Micron with “QuantX” branded ICs can now claim success in commercializing what has always looked good in R&D but was notoriously difficult to make in high-volume manufacturing (HVM).

Figure 1 shows the TEM cross-section, parallel to the wordline direction, of a XPoint memory cell array taken from an Intel Optane product. There are two levels of cross-point cell-stacks, connected in the middle by bitlines (orthogonal to the wordlines). The upper- and lower-wordlines have been analyzed as tungsten (W) metal with tungsten-nitride (WN) barriers. The memory cell material is a variant on a germanium-antimony-teluride (GeSbTe or “GST”) chalcogenide glass, while the selector material is made with arsenic-silicon-germanium-selenide.

Fig. 1: Cross-section TEM of Intel XPoint NVM array in the wordline direction, showing two levels of memory cell stacks separated by bitline arrays. (Source: greyscale image by TechInsights, color commentary by Ed Korczynski)

Details about the device architecture and memory circuitry are included in the Solid State Technology online blog post by TechInsights’ senior technical fellow Dr. Jeongdong Choe, “Comparing XPoint memory architecture with NAND and DRAM products”. In his presentation at the 2017 Flash Memory Summit, Choe disclosed that the composition of the memory material is Ge0.12Sb0.29Te0.54:Si0.05 and the selector material is As0.29Si0.17Ge0.10Se0.44 while there have been no public mentions yet of what materials are used as buffers to electrodes.

As explained in the Ed’s Threads blog post on June 22nd of this year under the title “PCM + ReRAM = OUM as XPoint,” there has been confusion regarding used of Phase-Change Memory (PCM) material in a device that has a completely different architecture, different switching mechanism, and different performance than what are now known as standard PCM ICs. In standard PCM chips, high current-flow through a bit cell heats up a small mass of material until it changes phase (from crystalline to amorphous or vice-versa). In XPoint arrays, a small current-flow through a bit cell causes ions and atoms to re-arrange following voltage potentials until it changes resistivity, while it is not yet public knowledge how much change happens in material phase. Intel has said that the resistance change is not due to conductive “filament” formation in the GeSbTe:Si but due to some change in the “bulk” of the material.

Processing Speculations

From a HVM perspective, all cross-bar memory architectures share similar constraints and opportunities to design for relatively low-cost and high-yield:

1)     Use PVD blanket layers of complex material stacks as memory and selector and buffers,

2)     Use lithography to mask memory cells in a regular two-dimensional array,

3)     Use ion-beam or chemically-neutral plasma to etch pillars of complex material stacks,

4)     Use ALD/CVD and spin-on-dielectrics to gap-fill electrical isolation around pillars, and

5)     Use dielectric CMP to prepare for metal deposition.

Physical Vapor Deposition (PVD) or “sputtering” processing is based on sublimating a solid material “target” inside a vacuum chamber, which provides a relatively fast and inexpensive way to coat surfaces. Thickness uniformity is typically excellent wafer-to-wafer, while within-wafer uniformity is controlled by process chamber and target geometries. The major concern with PVD using multi-component targets—such as the four element GeSbTe:Si—is that different elements sublimate at different rates such that targets “age” and experience slight predictable composition changes over time. PVD target aging can be compensated for by cleverly varying the ratio of the different elements through the thickness of the target.

When integrating PCM materials into NVM devices, the ability to use a blanket 2D PVD deposition is an inherent advantage over ALD into nano-scale 3D features:  faster, cheaper, and potentially more repeatable if target aging can be managed. Patterning of the memory cell stack requires excellent control over ion directionality to prevent sidewall erosion within the material stack. As can be seen in Figure 1, the sidewalls of the GST:Si are slightly recessed from the thin dark layers directly above and below, indicating a well-controlled process with relatively higher removal rate during etching/milling.

Dielectric gap-fill into what appears to be ~10:1 aspect-ratio features is certainly one of the integration challenges of this process flow. The cross-section shows at least one conformal barrier layer is used in the dielectric isolation between array elements and between bitlines. Dielectric ALD is likely used for barrier formation, while spin-on dielectric (SOD) technology likely provides the gap-filling capability. If the metal interconnects for the CMOS circuitry below the array are built using copper, then a 400°C upper limit on process temperatures would be required for all array fabrication.

Future R&D

Milind Weling, expert in materials/device innovation and senior vice president of programs and operations for Intermolecular, presented at the 2017 Flash Memory Summit on the company’s ability to accelerate the pace of R&D experimentation for the complex materials stacks needed in XPoint memory arrays. In an exclusive interview with SemiMD, Weling discussed the inherent challenges of finding the ideal material within a multi-element compositional space.

“We’ve been working on selectors, and a single-element material is almost useless. What you need is at least a binary, maybe a quaternary, and some people experiment with targets composed of up to seven elements! Once we find a composition that is interesting in our R&D tool, our customers create large targets for their HVM tools.” Figure 2 shows a wafer with 28 isolated circular regions within which different PVD compositions can be independent controlled in a custom R&D tool made by Intermolecular. This tool allows a complete design-of-experiments within a ternary compositional space to be run on a single 300mm-diameter silicon wafer.

Fig. 2: Site-isolated circular regions on a 300-mm silicon wafer A) can each have a different composition within B) a ternary phase diagram when deposited in a special PVD R&D tool. Chalcogenide alloys explored as memory and selector materials in cross-bar NVM arrays may have more than three elements. (Source: Intermolecular)

The materials stack is necessarily complex to be able to form chalcogenide-based NVM cells, and even more complex when buffers are added to allow for integration with CMOS-compatible materials. “Each memory cell is two electrodes sandwiching a GST-type of material, and the selector is two electrodes with one ‘magic’ layer,” explained Weling. “Except for the novel ‘magic’ selector, most of the other materials used in the stack have precedent as unit-process steps in HVM of DRAM or NAND. The difficulty is in tuning the compositions of all layers simultaneously.”

—E.K.

[DISCLOSURE:  Ed Korczynski has no ongoing business relationship with nor owns any equity in Intermolecular.]

SiPs Simplify Wireless IoT Design

Thursday, February 16th, 2017

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By Dave Lammers, Contributing Editor

It takes a range of skills to create a successful business in the Internet of Things space, where chips sell for a few dollars and competition is intense. Circuit design and software support for multiple wireless standards must combine with manufacturing capabilities.

Daniel Cooley, senior vice president of IoT products at Silicon Labs

Daniel Cooley, senior vice president and general manager of IoT products at Silicon Labs (Austin, Tx.), said three trends are impacting the manufacture of IoT end-node devices, which usually combine an MCU, an RF transceiver, and embedded flash memory.

“There is an explosion in the amount of memory on embedded SoCs, both RAM and non-volatile memory,” said Cooley. Today’s multi-protocol wireless software stacks, graphics processing, and security requirements routinely double or quadruple the memory sizes of the past.

Secondly, while IoT edge devices continue to use trailing-edge technologies, nonetheless they also are moving to more advanced nodes. However, that movement is partially gated by the availability of embedded flash.

Thirdly, pre-certified system-in-package (SiP) solutions, running a proven software stack, “are becoming much more important,” Cooley said. These SiPs typically encapsulate an MCU, an integrated antenna and shielding, power management, crystal oscillators, and inductors and capacitors. While Silicon Labs has been shipping multi-chip modules for many years, SiPs are gaining favor in part because they can be quickly deployed by engineers with relatively little expertise in wireless development, he said.

“Personally, I believe that very advanced SIPs increasingly will be standard products, not anything exotic. They are a complete solution, like a PCB module, but encased with a molding compound. The SiP manufacturers are becoming very sophisticated, and we are ready to take that technology and apply it more broadly,” he said.

For example, Silicon Labs recently introduced a Bluetooth SiP module measuring 6.5 by 6.5 mm, designed for use in sports and fitness wearables, smartwatches, personal medical devices, wireless sensor nodes, and other space-constrained connected devices.

“We have built multi-chip packages – those go back to the first products of the company – but we haven’t done a fully certified module with a built-in antenna until now. A SiP module simplifies the go-to-market process. Customers can just put it down on a PCB and connect power and ground. Of course, they can attach other chips with the built-in interfaces, but they don’t need anything else to make the Bluetooth system work,” Cooley said.

“Designing with a certified SiP module supports better data throughput, and improves reliability as well. The SiP approach is especially beneficial for end-node customers which “haven’t gone through the process of launching a wireless product in in the market,” Cooley said.

System-in-package (SiP) solutions ease the design cycle for engineers using Bluetooth and low low-energy wireless networks. (Source: Silicon Laboratories).

The SiP packages a wireless SoC with an antenna and multiple other components in a small footprint.

Control by voice

The BGM12x Blue Gecko SiP is aimed at Bluetooth-enabled applications, a genre that is rapidly expanding as ecosystems like the Amazon Echo, Apple HomeKit, and Google Home proliferate.

The BGM12x Blue Gecko SiP is aimed at Bluetooth-enabled applications

Matt Maupin is Silicon Labs’ product marketing manager for mesh networking products, which includes SoCs and modules for low-power Zigbee and Thread wireless connectivity. Asked how a home lighting system, for example, might be connected to one of the home “ecosystems” now being sold by Amazon, Apple, Google, Nest, and others, Maupin said the major lighting suppliers, such as OSRAM, Philips, and others, often use Zigbee for lighting, rather than Bluetooth, because of Zigbee’s mesh networking capability. (Some manufactures use Bluetooth low energy (BLE) for point-to-point control from a phone.)

“The ability for a device to connect directly relies on the same protocols being used. Google and Amazon products do not support Zigbee or Thread connectivity at this time,” Maupin explained.

Normally, these lighting devices are connected to a hub. For example, Amazon’s Echo and Google’s Home “both control the Philips lights through the Philips hub. Communication happens over the Ethernet network (wireless or wired depending on the hub).  The Philips hub also supports HomeKit so that will work as well,” he said.

Maupin’s home configuration is set up so the Philips lights connect via Zigbee to the Philips hub, which connects to an Ethernet network. An Amazon Echo is connected to the Ethernet Network by WiFi.

“I have the Philips devices at home configured via their app. For example, I have lights in my bedroom configured differently for me and my wife. With voice commands, I can control these lamps with different commands such as ‘Alexa, turn off Matt’s lamp,’ or ‘Alexa, turn off the bedroom lamps.’”

Alexa communicates wirelessly to the Ethernet Network, which then goes to the Philips hub (which is sold under the brand name Philips Hue Bridge) via Ethernet, where the Philips hub then converts that to Zigbee to control that actual lamps. While that sounds complicated, Maupin said, “to consumers, it is just magic.”

A divided IoT market

Sandeep Kumar, senior vice president of worldwide operations

IoT systems can be divided into the high-performance number crunchers which deal with massive amounts of data, and the “end-node” products which drive a much different set of requirements. Sandeep Kumar, senior vice president of worldwide operations at Silicon Labs, said RF, ultra-low-power processes and embedded NVM are essential for many end-node applications, and it can take several years for foundries to develop them beyond the base technology becoming available.

“40nm is an old technology node for the big digital companies. For IoT end nodes where we need a cost-effective RF process with ultra-low leakage and embedded NVM, the state of the art is 55nm; 40 nm is just getting ready,” Kumar said.

Embedded flash or any NVM takes as long as it does because, most often, it is developed not by the foundries themselves but by independent companies, such as Silicon Storage Technology. The foundry will implement this IP after the foundry has developed the base process. (SST has been part of Microchip Technology since 2010.) Typically, the eFlash capability lags by a few years for high-volume uses, and Kumar notes that “the 40nm eFlash is still not in high-volume production for end-node devices.”

Similarly, the ultra-low-leakage versions of a technology node take time and equipment investments, as well as cooperation from IP partners. Foundry customers and the fabless design houses must requalify for the low-leakage processes. “All the models change and simulations have to be redone,” Kumar said.

“We need low-leakage for the end applications that run on a button cell (battery), so that a security door or motion sensor, for example, can run for five to seven years. After the base technology is developed, it typically takes at least three years. If 40nm was available several years ago, the ultra-low-leakage process is just becoming available now.

“And some foundries may decide not to do ultra-low-leakage on certain technology nodes. It is a big capital and R&D investment to do ultra-low-leakage. Foundries have to make choices, and we have to manage that,” Kumar said.

The majority of Silicon Labs’ IoT product volume is in 180nm, while other non-IoT products use a 55nm process. The line of Blue Gecko wireless SoCs currently is on 90nm, made in 300mm fabs, while new designs are headed toward more advanced process nodes.

Because 180nm fabs are being used for MEMS, sensors and other analog-intensive, high-volume products, there is still “somewhat of a shortage” of 180nm wafers, Kumar said, though the situation is improving. “It has gotten better because TSMC and other foundries have added capacity, having heard from several customers that the 180nm node is where they are going to stay, or at least stay longer than they expected. While the foundries have added equipment and capital, it is still quite tight. I am sure the big MEMS and sensor companies are perfectly happy with 180nm,” Kumar said.

A testing advantage

IoT is a broad-based market with thousands of customers and a lot of small volume customizations. Over the past decade Silicon Labs has deployed a proprietary ultra-low-cost tester, developed in-house and used in internal back-end operations in Austin and Singapore at assembly and test subcontractors and at a few outside module makers as well. The Silicon Labs tester is much more cost effective than commercially available testers, an important cost advantage in a market where a wireless MCU can sell in small volumes to a large number of customers for just a few dollars.

“Testing adds costs, and it is a critical part of our strategy. We use our internally developed tester for our broad-based products, and it is effective at managing costs,” Kumar said.

The Week in Review: September 5, 2014

Friday, September 5th, 2014

Contour Semiconductor, Inc. announced it has been awarded three new patents to back its Diode Transistor Memory (DTM) technology, the world’s lowest production-cost, non-volatile memory technology.

Fujitsu Semiconductor America announced that Shinichi “James” Machida, who led the company from late 2008 until spring of 2011, has been named as the new president and CEO of FSA.

ProPlus Design Solutions announced Samsung Electronics has extended its partnership with ProPlus through the deployment of ProPlus’ BSIMProPlus modeling platform for its 14nm FinFET SPICE modeling.

Analog Devices, Inc. introduced the first and only MEMS gyroscope specified to withstand temperatures of up to 175 degrees Celsius commonly encountered by oil and gas drilling equipment.

GLOBALFOUNDRIES, a provider of advanced semiconductor manufacturing technology, announced that Louis “Lou” Lupin has joined the company as senior vice president and chief legal officer.

Credo Semiconductor announced the appointment of Jeff Twombly as vice president of sales and business development.

Taiwanese chipmakers, LED manufacturers, and Outsourced Semiconductor Assembly and Test (OSAT) firms will spend firm nearly $24 billion in the next two years on equipment and materials, powering excitement for SEMICON Taiwan 2014, which opened this week in Taipei.

United Microelectronics Corporation and Fujitsu Semiconductor Limited announced an agreement for UMC to become a minority shareholder of a newly formed subsidiary of Fujitsu Semiconductor that will include its 300mm wafer manufacturing facility located in Kuwana, Mie, Japan.

Rudolph Technologies, Inc. announced that the SUNY College of Nanoscale Science and Engineering (CNSE), Albany, NY, has selected its Discover Enterprise Yield Management Software (YMS) to provide an integrated data warehouse and analytics system for the Global 450 Consortium (G450C) equipment development program.