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New memory puts new demands on process and equipment

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New memory puts new demands on process and equipment

New memory test socket will upgrade to test the new socket.

The global semiconductor industry is in the midst of a transition from the previous computing era to big data, artificial intelligence (AI) and the Internet of Things (IoT). However, the computational performance improvements and energy reduction required to achieve new artificial intelligence and IoT applications are the biggest challenges facing the industry. The most critical requirement may be to provide new memory manufacturing technologies.

In a seminar entitled "PCRAM/MRAM: Expectations/How to Manage Artificial Intelligence, In-Memory Computing and IoT", a joint seminar between France's CEA-Leti and Applied Materials, France, the delegates reported on the current challenges, Progress and new solutions, the most important of which is the need for more efficient calculations, as current energy consumption levels are not sustainable. In addition, different applications and market segments are driving different storage needs, technologies and strategies. Moreover, after years of development, process technology is ready to support the use of a variety of new memories in commercial applications.

The basic driving force of today's industrial roadmap is the huge data flow. By 2022, more than 10 zettabytes of data will need to be processed, stored, and transmitted, with approximately 90% of the data generated by IT devices. This sheer volume of data reflects the smarter edge applications market for smart speakers, wearables, industrial sensors and autonomous driving. At this stage, we are seeing the construction of various data centers are keeping up. If left uncontrolled, all of these processing and data transmission energy requirements may consume energy equivalent to the entire country.

According to industry, 90% of the energy consumed by memory is used to transfer data. Moving the memory closer to the calculation can alleviate this situation. In order to improve memory and computational performance and reduce power consumption, various strategies are being investigated, including memory optimized for edge computing and memory applications, new (SoC) chip packaging schemes, 3D packages using TSVs, and computations in memory ( In memory compute), these strategies have the potential to reduce energy consumption by a factor of eight.

There is no new type of memory that can handle all the different needs that produce such a large amount of data. From the perspective of new types of memory, including MRAM, PCRAM and RERAM are moving towards maturity to meet market demands. Each technology has its own application features, such as MRAM for edge computing and IoT applications, and PCRAM for cloud applications, but they all improve performance and reduce power consumption.

Applied Materials is working to provide new memory manufacturing technologies and equipment, especially MRAM (implemented by magnetization reversal of free layers in magnetic tunnel junctions) and PCRAM (phase change memory).

For MRAM fabrication, the main challenge is the deposition of the memory stack, usually done using PVD technology. Atomic precision and control require deposition of more than 10 different materials in ultra-thin layers of more than 30 layers, some of which can only reach a few angstroms in thickness. In order to maintain the integrity of critical, very thin magnetic tunnel junctions, damage-free etching and packaging techniques are required.

Like MRAM, PCRAM is also implemented in a variety of new materials that require innovation in PVD and etching technology. Because PCRAM is component-based (combined from three different elements), its materials are often very complex and thickness uniformity is critical. The key to the manufacturing process is the ability to adjust the material composition and minimize damage as the material changes phase. Process technology can be adjusted for high retention, temperature, high speed or high endurance of its components depending on the application.

The composition of the material stack determines the performance of the memory. Exposure to the atmosphere can cause contamination and damage due to the use of so many complex materials. It requires an ultra-high vacuum environment, so the solution must integrate process technology with measurement to ensure raw material integrity and control for mass production of material-related memory.


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