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From Ferroelectric Material Optimization to Neuromorphic Devices
Advanced Materials ( IF 27.4 ) Pub Date : 2022-08-26 , DOI: 10.1002/adma.202206042 Thomas Mikolajick 1, 2 , Min Hyuk Park 3 , Laura Begon-Lours 4 , Stefan Slesazeck 1
Advanced Materials ( IF 27.4 ) Pub Date : 2022-08-26 , DOI: 10.1002/adma.202206042 Thomas Mikolajick 1, 2 , Min Hyuk Park 3 , Laura Begon-Lours 4 , Stefan Slesazeck 1
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Due to the voltage driven switching at low voltages combined with nonvolatility of the achieved polarization state, ferroelectric materials have a unique potential for low power nonvolatile electronic devices. The competitivity of such devices is hindered by compatibility issues of well-known ferroelectrics with established semiconductor technology. The discovery of ferroelectricity in hafnium oxide changed this situation. The natural application of nonvolatile devices is as a memory cell. Nonvolatile memory devices also built the basis for other applications like in-memory or neuromorphic computing. Three different basic ferroelectric devices can be constructed: ferroelectric capacitors, ferroelectric field effect transistors and ferroelectric tunneling junctions. In this article first the material science of the ferroelectricity in hafnium oxide will be summarized with a special focus on tailoring the switching characteristics towards different applications.The current status of nonvolatile ferroelectric memories then lays the ground for looking into applications like in-memory computing. Finally, a special focus will be given to showcase how the basic building blocks of spiking neural networks, the neuron and the synapse, can be realized and how they can be combined to realize neuromorphic computing systems. A summary, comparison with other technologies like resistive switching devices and an outlook completes the paper.
中文翻译：
从铁电材料优化到神经形态设备
由于低电压下的电压驱动开关与所实现的极化状态的非易失性相结合，铁电材料对于低功率非易失性电子器件具有独特的潜力。众所周知的铁电体与现有半导体技术的兼容性问题阻碍了此类设备的竞争力。氧化铪铁电性的发现改变了这一状况。非易失性器件的自然应用是作为存储单元。非易失性存储设备还为内存或神经形态计算等其他应用奠定了基础。可以构造三种不同的基本铁电器件：铁电电容器、铁电场效应晶体管和铁电隧道结。在本文中，首先将总结氧化铪铁电性的材料科学，特别关注针对不同应用定制开关特性。然后，非易失性铁电存储器的现状为研究内存计算等应用奠定了基础。最后，将特别重点展示如何实现尖峰神经网络的基本构建模块（神经元和突触）以及如何将它们组合起来以实现神经形态计算系统。总结、与电阻开关器件等其他技术的比较以及展望结束了本文。
更新日期：2022-08-26
中文翻译：
从铁电材料优化到神经形态设备
由于低电压下的电压驱动开关与所实现的极化状态的非易失性相结合，铁电材料对于低功率非易失性电子器件具有独特的潜力。众所周知的铁电体与现有半导体技术的兼容性问题阻碍了此类设备的竞争力。氧化铪铁电性的发现改变了这一状况。非易失性器件的自然应用是作为存储单元。非易失性存储设备还为内存或神经形态计算等其他应用奠定了基础。可以构造三种不同的基本铁电器件：铁电电容器、铁电场效应晶体管和铁电隧道结。在本文中，首先将总结氧化铪铁电性的材料科学，特别关注针对不同应用定制开关特性。然后，非易失性铁电存储器的现状为研究内存计算等应用奠定了基础。最后，将特别重点展示如何实现尖峰神经网络的基本构建模块（神经元和突触）以及如何将它们组合起来以实现神经形态计算系统。总结、与电阻开关器件等其他技术的比较以及展望结束了本文。
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