Browsing by Author "Chiu, Jung-Piao"

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A Novel Random Telegraph Signal Method to Study Program/Erase Charge Lateral Spread and Retention Loss in a SONOS Flash Memory
(2011-03-01)
Ma, Huan-Chi
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Chou, You-Liang
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Chiu, Jung-Piao
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Chung, Yueh-Ting
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Lin, Tung-Yang
A novel random telegraph signal (RTS) method is proposed to characterize the lateral distribution of injected charge in program and erase states in a NOR-type silicon-oxide-nitride-oxide-silicon Flash memory. The concept of this method is to use RTS to extract an oxide trap position in the channel and then to use the trap and RTS as internal probe to detect a local channel potential change resulting from injected charge during program/erase. By using this method, the lateral width of the injected charge-induced channel potential barrier is shown to be around 20 nm in channel hot electron (CHE) program. Our method also confirms that Channel Initiated Secondary ELectron (CHISEL) program has a broader injected charge distribution than CHE program. A mismatch of CHE program electrons and band-to-band tunneling erase holes is observed. Program-state V(t) retention loss models, charge vertical loss versus lateral migration, are reexamined by using this method. The polarity of a program-state charge distribution along the channel is explored within 10-20 program/erase cycles. Nitride charge vertical loss is verified by this method.
Characterization and modeling of trap number and creation time distributions under negative-bias-temperature stress
(2012-08-20)
Chiu, Jung-Piao
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Li, Chi-Wei
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Wang, Tahui
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電子工程學系及電子研究所
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Department of Electronics Engineering and Institute of Electronics
Individual trapped charge creations and a trap number in p-type metal-oxide-semiconductor field effect transistors (pMOSFETs) under negative bias temperature instability (NBTI) stress are investigated. We find that the characteristic times of a trapped charge creation scatter over several decades of time in small area pMOSFETs, which is attributed to an activation energy distribution in the reaction-diffusion (RD) model of NBTI. We develop a statistical model by combining the RD model with an extracted activation energy distribution to calculate a threshold voltage shift distribution at different NBTI stress times. Our model agrees with measured results very well. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4748108]
Design Space Analysis for Cross-Point 1S1MTJ MRAM: Selector-MTJ Cooptimization
(2020-08-01)
Chiang, Hung-Li
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Chen, Tzu-Chiang
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Song, Ming-Yuan
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Chen, Yu-Sheng
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Chiu, Jung-Piao
To increase the density of magnetoresistive random accessmemory (MRAM) beyond the 1T1MTJMRAM cell in use today, the design space for 1S1MTJ MRAM array is analyzed by cooptimizing both selectors and MTJs. Current low-resistance MTJs for 1T1MTJ MRAM are not suitable for 1S1MTJ MRAM. Threshold-type selectors would induce a strong read disturb on the MTJ due to the snapback voltage (V-TH-V-HOLD) when the selector is turned on. Also, exponential-type selectorswould degrade the read margin (RM) due to its large ON-state resistance. When using existing selectors to achieve a 1-M-bit 1S1MTJ array, it is necessary to adjust the product of resistance and area (RA) and the diameter of the MTJ. An MTJ with the RA = 15 Omega . mu m(2) and the diameter = 50 nm can meet the criterion of RM > 10% for both exponential-type selectors (exponential slope = 300-500 mV/decade with the current density similar to 1 MA/cm(2)) and threshold-type selectors (V-TH-V-HOLD similar to 250 mV). A design space accommodating a selector variation of around 1% can be found for MTJs with tunnel magnetoresistance ratio (TMR) < 250%. With an increased TMR of 250%-350% of the MTJ, the tolerance of variations for exponential-type selectors and threshold-type selectors can be improved to 2% and 4%, respectively. This provides a chance for the 1S1MTJ MRAM with existing selectors.
Statistical Characterization and Modeling of the Temporal Evolutions of Delta V-t Distribution in NBTI Recovery in Nanometer MOSFETs
(2013-03-01)
Chiu, Jung-Piao
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Liu, Yu-Heng
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Hsieh, Hung-Da
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Li, Chi-Wei
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Chen, Min-Cheng
NBTI trapped charge characteristics and recovery mechanisms are examined by a statistical study of individual trapped charge emissions in nanoscale HfSiON/metal gate pMOSFETs. We measure individual trapped charge emission times in NBTI recovery in a large number of devices. The characteristic time distributions of the first three emitted holes are obtained. The distributions can be well modeled by using a thermally-assisted tunnel (ThAT) detrapping model. NBTI trapped charge energy and spatial distributions and its activation energy distribution in the ThAT model are discussed and extracted. Based on the ThAT model and measured result of single-charge induced V-t shifts, we develop a statistical NBTI recovery Delta V-t evolution model. Our model can well reproduce the temporal evolutions of a Delta V-t distribution in a number of NBTI stressed nanometer MOSFETs in relaxation.
V-t Retention Distribution Tail in a Multitime-Program MLC SONOS Memory Due to a Random-Program-Charge-Induced Current-Path Percolation Effect
(2012-05-01)
Chung, Yueh-Ting
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Huang, Tzu-I
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Li, Chi-Wei
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Chou, You-Liang
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Chiu, Jung-Piao
A V-t retention distribution tail in a multitime-program (MTP) silicon-oxide-nitride-oxide-silicon (SONOS) memory is investigated. We characterize a single-program-charge-loss-induced Delta V-t in NOR-type SONOS multilevel cells (MLCs). Our measurement shows the following: 1) A single-charge-lossinduced Delta V-t exhibits an exponential distribution in magnitudes, which is attributed to a random-program-charge-induced current-path percolation effect, and 2) the standard deviation of the exponential distribution depends on the program-charge density and increases with a program V-t level in an MLC SONOS. In addition, we measure a V-t retention distribution in a 512-Mb MTP SONOS memory and observe a significant V-t retention tail. A numerical V-t retention distribution model including the percolation effect and a Poisson-distribution-based multiple-charge-loss model is developed. Our model agrees with the measured V-t retention distribution in a 512-Mb SONOS well. The observed V-t tail is realized mainly due to the percolation effect.