Memory Devices for Flexible and Neuromorphic Device Applications

Kim, Dongshin; Kim, Ik-Jyae; Lee, Jang‐Sik

doi:10.1002/aisy.202000206

Cited by 14 publications

(13 citation statements)

References 201 publications

(379 reference statements)

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“…[26] In addition, many researchers have focused on doping engineering, interfacial stress, oxygen vacancies, and surface energy to enhance the ferroelectric properties of HfO 2 films. [27,28] Figure 1 shows the effect of HfO 2 crystal structure on the ferroelectricity, the device structure of the HfO 2 as well as the device application.In this paper, the effect of HfO 2 crystal structure on the device electrical properties will be briefly introduced, and the method of HfO 2 epitaxial growth and failure mechanism of HfO 2 -based device will be summarized. At the same time, we concluded the progress of first principle calculation of the HfO 2 ferroelectric properties.…”

mentioning

confidence: 99%

Ferroelectric Hafnium Oxide Films for In‐Memory Computing Applications

Wang

et al. 2022

Adv Elect Materials

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Traditional von Neumann architecture is facing severe challenges due to separated physical structure of memory and processing units, which inspires the development of in‐memory computing electronics. Intriguingly, as a kind of complementary metal‐oxide‐semiconducor compatible ferroelectric material, HfO2 is widely studied based on first‐principles calculation in the semiconductor field, showing great potential in constructing emerging electronics. Different structures including ferroelectric diode, ferroelectric field effect transistor, and ferroelectric tunnel junctions based on HfO2 are proposed for in‐memory computing application. Here, this work reviews the progress of HfO2 from materials to devices, including crystal structure, fatigue mechanism, first‐principles calculation, and neuromorphic computing application of HfO2‐based device. This work can provide a reference for the HfO2 ferroelectric device development for next‐generation in‐memory computing applications.

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mentioning

confidence: 99%

Ferroelectric Hafnium Oxide Films for In‐Memory Computing Applications

Wang

et al. 2022

Adv Elect Materials

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“…In addition to inorganic and organic materials, 2D materials have recently received extensive attention due to their unique structural characteristics, good mechanical flexibility, and excellent electrical properties (Kim et al, 2021a;Meng et al, 2021). Plenty of 2D materials such as graphene (Sun et al, 2017), transition metal dichalcogenides (TMD) (Feng et al, 2019;Zhao et al, 2018) and boron nitride (BN) (Ge et al, 2021;Qian et al, 2017;Siddiqui et al, 2017) and fabulous thermal stability (Figure 3A) (Wang et al, 2018a).…”

Section: Flexible Two-dimensional Materials Memristive Arraysmentioning

confidence: 99%

Flexible and Stretchable Memristive Arrays for in-Memory Computing

Liu

Cao

Qian

et al. 2022

Front. Nanotechnol.

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With the tremendous progress of Internet of Things (IoT) and artificial intelligence (AI) technologies, the demand for flexible and stretchable electronic systems is rapidly increasing. As the vital component of a system, existing computing units are usually rigid and brittle, which are incompatible with flexible and stretchable electronics. Emerging memristive devices with flexibility and stretchability as well as direct processing-in-memory ability are promising candidates to perform data computing in flexible and stretchable electronics. To execute the in-memory computing paradigm including digital and analogue computing, the array configuration of memristive devices is usually required. Herein, the recent progress on flexible and stretchable memristive arrays for in-memory computing is reviewed. The common materials used for flexible memristive arrays, including inorganic, organic and two-dimensional (2D) materials, will be highlighted, and effective strategies used for stretchable memristive arrays, including material innovation and structural design, will be discussed in detail. The current challenges and future perspectives of the in-memory computing utilizing flexible and stretchable memristive arrays are presented. These efforts aim to accelerate the development of flexible and stretchable memristive arrays for data computing in advanced intelligent systems, such as electronic skin, soft robotics, and wearable devices.

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“…[365][366][367] The synthetic synapses to detect strain, touch and pressure can be helpful to avoid injuries or damages, or for human-machine interactions and communication. [368] For example, piezoelectric nanogenerators can link spatiotemporal strain information with artificial intelligence to detect perception, [369] but require flexible data storage, with large memory capacity, fast processing speed, complex data computation, [370] and ultra-low energy consumption. [371] All these features are still far from the realization in current soft robots.…”

Section: Proprioception and Control System For Soft Robotsmentioning

confidence: 99%

A Perspective on Cephalopods Mimicry and Bioinspired Technologies toward Proprioceptive Autonomous Soft Robots

Giordano

Carlotti

Mazzolai

2021

Adv Materials Technologies

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scientific community. [1][2][3][4][5][6][7] Regardless, every time a living being reveals novel adaptive and dynamically reactive mimicry behavior, it inspires and fosters futuristic and unexpected technological outcomes. [8][9][10][11][12] At the biological level, the visual crypsis is the ability of a species to resemble the surroundings by matching the coloration and the geometrical patterns of the habitat. In this sense, a living being can control its appearance optically (thanks to arranged and optimized structures at the mesoscopic scale, by means of pigmentation, or emissive elements) and morphologically (it can show wrinkles and textures on the body to evade detection or observation). [13][14][15][16][17][18] Both these mechanisms are characterized by a time response that ranges from milliseconds to hundreds of seconds. In nature, several species take advantage of cryptic abilities, as, e.g., in cephalopods, [7] crustaceans, [19] reptilians, [1,20,21] insects, [22,23] birds, [24,25] shells, [26,27] plants, [28,29] among many. The biotic color changing and body patterning relate to reproductive, communicative, and defensive and/or predatory strategies. Unfortunately, the nervous or central control-chain system that steers these behaviors in animals and plants, is still somehow fogged for scientists. [7,[30][31][32] A complete knowledge about their central information process systems, can open to astonishing developments in many scientific branches, from neurobiology [33,34] to quantum biology. [35] Undoubtedly, the most debated case of study in the natural world are cephalopods, which not only are highly evolved and specialized in fast adaptive color changing displays, but also are able to actuate their skin to generate 3D patterns, when exposed to specific mechanical, thermal, optical, or chemical stimuli. Soft muscular arrangements, [36][37][38] spatially distributed and expandable absorbing components (namely chromatophores), [39,40] iridescent elements (namely irido phores), [41,42] and bright white scatterers (namely leucophores) [43] are responsible for textural, postural and color changing. Moreover, octopuses are a remarkable intelligent species, able, for example, to open a jar or avoid predators in the order of seconds. [44] Thus, cephalopods are usually regarded as a perfect example of embodied intelligence, [45] thanks to the symbiosis between their body's mechanics and morphology, and the distributed sensory neuro-motor-control system. Their "learning", "mechanical" and "material intelligence" will be our lodestars along this review, resulting in a fascinating connection between Octopus skin is an amazing source of inspiration for bioinspired sensors, actuators and control solutions in soft robotics. Soft organic materials, biomacromolecules and protein ingredients in octopus skin combined with a distributed intelligence, result in adaptive displays that can control emerging optical behavior, and 3D surface textures with rough geometries, with a remarkably high control speed (≈ms). To be able ...

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Memory Devices for Flexible and Neuromorphic Device Applications

Cited by 14 publications

References 201 publications

Ferroelectric Hafnium Oxide Films for In‐Memory Computing Applications

Ferroelectric Hafnium Oxide Films for In‐Memory Computing Applications

Flexible and Stretchable Memristive Arrays for in-Memory Computing

A Perspective on Cephalopods Mimicry and Bioinspired Technologies toward Proprioceptive Autonomous Soft Robots

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