Flash memories: the best of two worlds

Pashley, R.; Lai, Sheng-Chih

doi:10.1109/6.45032

Cited by 10 publications

(4 citation statements)

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“…Real QD memory device based on the above-mentioned dot structure can be fabricated like a field effect transistor structure with the float gates, which is very similar to the Flash device [2]. The QD memory device makes use of the conductivity of a channel between the source and the drain gates and the channel may be realized by inserting a 2-D hole gas layer close to the QDs, whose structure is similar to that of our previous report using a 2-D electron gas layer close to the dots [17].…”

Section: Resultsmentioning

confidence: 99%

“…S O FAR the most widely used and well-developed semiconductor memory devices have been dynamic random access memory (DRAM) [1] and the Flash memory [2], which store information by making use of capacitance and the float gate, respectively. DRAM has a high power consumption due to a large number of the stored charge carriers (>10 4 ) and needs to be refreshed.…”

Section: Introductionmentioning

confidence: 99%

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540-meV Hole Activation Energy for GaSb/GaAs Quantum Dot Memory Structure Using AlGaAs Barrier

Cui

Zhang

et al. 2013

IEEE Electron Device Lett.

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We report on a memory structure that only makes use of holes as the storage charges based on type-II GaSb/GaAs quantum dots (QDs) using an AlGaAs barrier. The C-V measurements confirm existence of quantum states in the GaSb dots and reveal the applied bias voltage range for the write/erase process by charging/discharging the QDs. A large hole activation energy value of 540 meV is obtained for the device measured by deep level transient spectroscopy. Our results indicate that type-II GaSb/GaAs QD system is a promising candidate for future memory devices.Index Terms-Barrier confinement, GaSb/GaAs, quantum dot memory, thermal activation energy.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

540-meV Hole Activation Energy for GaSb/GaAs Quantum Dot Memory Structure Using AlGaAs Barrier

Cui

Zhang

et al. 2013

IEEE Electron Device Lett.

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“…Researchers have shown that they can write information into quantum dot memory in just nanoseconds. Memory is divided into two forms: DRRAM and Flash [ 163 , 164 ]. Computers use DRAM, for short-term memory, but data does not persist for long and must be refreshed over 100 times per second to maintain its memory.…”

Section: Reviewmentioning

confidence: 99%

Overview of emerging nonvolatile memory technologies

et al. 2014

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Nonvolatile memory technologies in Si-based electronics date back to the 1990s. Ferroelectric field-effect transistor (FeFET) was one of the most promising devices replacing the conventional Flash memory facing physical scaling limitations at those times. A variant of charge storage memory referred to as Flash memory is widely used in consumer electronic products such as cell phones and music players while NAND Flash-based solid-state disks (SSDs) are increasingly displacing hard disk drives as the primary storage device in laptops, desktops, and even data centers. The integration limit of Flash memories is approaching, and many new types of memory to replace conventional Flash memories have been proposed. Emerging memory technologies promise new memories to store more data at less cost than the expensive-to-build silicon chips used by popular consumer gadgets including digital cameras, cell phones and portable music players. They are being investigated and lead to the future as potential alternatives to existing memories in future computing systems. Emerging nonvolatile memory technologies such as magnetic random-access memory (MRAM), spin-transfer torque random-access memory (STT-RAM), ferroelectric random-access memory (FeRAM), phase-change memory (PCM), and resistive random-access memory (RRAM) combine the speed of static random-access memory (SRAM), the density of dynamic random-access memory (DRAM), and the nonvolatility of Flash memory and so become very attractive as another possibility for future memory hierarchies. Many other new classes of emerging memory technologies such as transparent and plastic, three-dimensional (3-D), and quantum dot memory technologies have also gained tremendous popularity in recent years. Subsequently, not an exaggeration to say that computer memory could soon earn the ultimate commercial validation for commercial scale-up and production the cheap plastic knockoff. Therefore, this review is devoted to the rapidly developing new class of memory technologies and scaling of scientific procedures based on an investigation of recent progress in advanced Flash memory devices.

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“…Other analog memory architectures make use of special, and often proprietary, fabrication techniques to implement analog memory functions [4] , [5]. These methods are based on structures optimized for commercial digital EEPROM technologies [6]. Manuscript Our research is directed toward the development of a viable method of storing neural network weights in analog form.…”

Section: Introductionmentioning

confidence: 99%

Comparison of floating gate neural network memory cells in standard VLSI CMOS technology

Durfee

Shoucair

1992

IEEE Trans. Neural Netw.

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Several floating gate MOSFET structures, for potential use as analog memory elements in neural networks, have been fabricated in a standard 2 mum double-polysilicon CMOS process. Their physical and programming characteristics are compared with each other and with similar structures reported in the literature. None of the circuits under consideration require special fabrication techniques. The criteria used to determine the structure most suitable for neural network memory applications include the symmetry of charging and discharging characteristics, programming voltage magnitudes, the area required, and the effectiveness of geometric field enhancement techniques. This work provides a layout for an analog neural network memory based on previously unexplored criteria and results. The authors have found that the best designs (a) use the poly1 to poly2 oxide for injection; (b) need not utilize ;field enhancement' techniques; (c) use poly1 to diffusion oxide for a coupling capacitor; and (d) size capacitor ratios to provide a wide range of possible programming voltages.

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Flash memories: the best of two worlds

Cited by 10 publications

References 0 publications

540-meV Hole Activation Energy for GaSb/GaAs Quantum Dot Memory Structure Using AlGaAs Barrier

540-meV Hole Activation Energy for GaSb/GaAs Quantum Dot Memory Structure Using AlGaAs Barrier

Overview of emerging nonvolatile memory technologies

Comparison of floating gate neural network memory cells in standard VLSI CMOS technology

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