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[paper] Organic Transistor Memory Based on Black Phosphorus Quantum Dots

P. Kumari, J. Ko, V. R. Rao, S. Mhaisalkar and W. L. Leong

Non-Volatile Organic Transistor Memory Based on Black Phosphorus Quantum Dots as Charge Trapping Layer,

in IEEE Electron Device Letters, vol. 41, no. 6, pp. 852-855, June 2020

doi: 10.1109/LED.2020.2991157

Abstract: High performance organic nano-floating gate transistor memory (NFGTM) has important prerequisites of low processing temperature, solution–processable layers and charge trapping medium with high storage capacity. We demonstrate organic NFGTM using black phosphorus quantum dots (BPQDs) as a charge trapping medium by simple spin-coating and low processing temperature ( 120 °C). The BPQDs with diameter of 12.6 ± 1.5 nm and large quantum confined bandgap of ~2.9 eV possess good charge trapping ability. The organic memory device exhibits excellent memory performance with a large memory window of 61.3 V, write-read-erase-read cycling endurance of 10 3 for more than 180 cycles and reliable retention over 10,000 sec. In addition, we successfully improved the memory retention to ON/OFF current ratio 10E4 over 10,000 sec by introducing PMMA as the tunneling layer.

 

FIG: a.) Schematic of bottom gate top contact NFGTM device; b.) Band diagram explaining memory mechanism under positive gate bias 

Acknowledgement: W.L. Leong would like to acknowledge funding support from her NTU start-up grant (M4081866), Ministry of Education (MOE) under AcRF Tier 1 grant (2016-T1-002- 097), Tier 2 grant (2018-T2-1-075), ASTAR AME IAF-ICP Grant (No.I1801E0030) and A*STAR AME Young Individual Research Grant (Project No. A1784c019).

[paper] IoT Vision empowered by EH-MEMS and RF-MEMS

Internet of things (IoT); internet of everything (IoE); tactile internet; 5G
A (not so evanescent) unifying vision empowered 
by EH-MEMS (energy harvesting MEMS) and RF-MEMS (radio frequency MEMS)

 Jacopo Iannacci
Fondazione Bruno Kessler (FBK) in Trento (IT)

Sensors and Actuators A: Physical 272 (2018): 187-198

Abstract: This work aims to build inclusive vision of the Internet of Things (IoT), Internet of Everything (IoE), Tactile Internet and 5G, leveraging on MEMS technology, with focus on Energy Harvesters (EH-MEMS) and Radio Frequency passives (RF-MEMS). The IoT is described, stressing the pervasivity of sensing/actuating functions. High-level performances 5G will have to score are reported. Unifying vision of the mentioned paradigms is then built. The IoT evolves into the IoE by overtaking the concept of thing. Further step to Tactile Internet requires significant reduction in latency, it being enabled by 5G.

The discussion then moves closer to the hardware components level. Sets of specifications driven by IoT and 5G applications are derived. Concerning the former, the attention is concentrated on typical power requirements imposed by remote wireless sensing nodes. Regarding the latter, a set of reference specifications RF passives will have to meet in order to enable 5G is developed. Once quantitative targets are set, a brief state of the art of EH-MEMS and RF-MEMS solutions is developed, targeting the IoT and 5G, respectively. In both scenarios, it will be demonstrated that MEMS are able to address the requirements previously listed, concerning EH from various sources and RF passive components.

FIG: Scheme of the pillar drivers supporting evolution of the IoT into IoE andTactile Internet.
Some relevant IoT technology enablers are indicated.

In conclusion, the frame of reference depicted in this work outlines a relevant potential borne by EH-MEMS and RF-MEMS solutions within the unified scenario of IoT, IoE, Tactile Internet and 5G, making the forecast of future relentless growth of MEMS-based devices, more plausible and likely to take place.

[paper] SPICE PCM Model

A SPICE Model of Phase Change Memory for Neuromorphic Circuits

Xuhui Chen¹, Huifang Hu¹, Xiaoqing Huang¹, Weiran Cai², Ming Liu³ (Fellow, Ieee), Chung Lam⁴,  Xinnan Lin¹ (Member, IEEE), Lining Zhang⁵ (Senior Member, IEEE)

and Mansun Chan⁶ (Fellow, IEEE)

¹The Shenzhen Key Lab of Advanced Electron Device and Integration, ECE, Peking University Shenzhen Graduate School, Shenzhen 518055 CN
²Institute of Microscale Optoelectronics, Shenzhen University, Shenzhen 518061 CN
³Key Laboratory of Microelectronics Devices and Integration Technology, Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, and the University of Chinese Academy of Sciences, Beijing 100049 CN
⁴Jiangsu Advanced Memory Technology Co., Ltd, Huaian 223302 CN
⁵School of Electronic and Computer Engineering, Peking University, Shenzhen 518055, CN
⁶HKUST Shenzhen Research Institute, Shenzhen 518057, China, and Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, HK

doi: 10.1109/ACCESS.2020.2995907

Abstract: A phase change memory (PCM) model suitable for neuromorphic circuit simulations is developed. A crystallization ratio module is used to track the memory state in the SET process, and an active region radius module is developed to track the continuously varying amorphous region in the RESET process. To converge the simulations with bi-stable memory states, a predictive filament module is proposed using a previous state in iterations of nonlinear circuit matrix under a voltage-driven mode. Both DC and transient analysis are successfully converged in circuits with voltage sources. The spiking-timedependent- plasticity (STDP) characteristics essential for synaptic PCM are successfully reproduced with SPICE simulations verifying the model’s promising applications in neuromorphic circuit designs. Further on, the developed PCM model is applied to propose a neuron circuit topology with lateral inhibitions which is more bionic and capable of distinguishing fuzzy memories. Finally, unsupervised learning of handwritten digits on neuromorphic circuits is simulated to verify the integrity of models in a large-scale-integration circuits. For the first time in literature an emerging memory model is developed and applied successfully in neuromorphic circuit designs, and the model is applicable to flexible designs of neuron circuits for further performance improvements. 

FIG: Schematic diagram of commonly used PCM mushroom structure

URL: https://IEEExplore.IEEE.org/stamp/stamp.jsp?tp=&arnumber=9097232&isnumber=6514899

[paper] Graphene/4H-SiC/Graphene MSM UV-photodetector

An optimized Graphene/4H-SiC/Graphene MSM UV-photodetector operating
in a wide range of temperature 

H. Bencherif ¹, L. Dehimi1 ², G. Messina ³, P. Vincent ⁴, F. Pezzimenti ³, F. G. Della Corte ^{3 1}Laboratory of Metallic and Semiconductor Materials, University of Biskra, Biskra, DZ

²Faculty of Science, University of Batna 1, DZ

³DIIES, Mediterranea University of Reggio Calabria, Reggio Calabria, IT

⁴School of Electronics Engineering, KNU, 80 Daehakro, Buk-gu, Daegu, 702-701, KP

Abstract: In this paper, .an accurate analytical model has been developed to optimize the performance of an Interdigitated Graphene Electrode/p-silicon carbide (IGE/p-4H-SiC) Metal semiconductor Metal (MSM) photodetector operating in a wide range of temperatures. The proposed model considers different carrier loss mechanisms and can reproduce the experimental results well. An overall assessment of the electrodes geometrical parameters’ influence on the device sensitivity and speed performances was executed. Our results confirm the excellent ability of the suggested Graphene electrode system to decrease the unwanted shadowing effect. A responsivity of 238 μA/W was obtained under 325-nm illumination compared to the 16.7 μA/W for the conventional Cr-Pd/p-SiC PD. A photocurrent to- dark-current ratio (PDCR) of 5.75 × 105 at 300K and 270 at 500K was distinguished. The response time was found to be around 14 μs at 300K and 54.5 μs at 500K. Furthermore, the developed model serves as a fitness function for the multi objective optimization (MOGA) approach. The optimized IGE/p-4H-SiC MSM-PD design not only exhibits higher performance in terms of PDCR (7.2×105), responsivity (430A/cm2) and detectivity (1.3×1014 Jones) but also balances the compromise between ultrasensitive and high-speed figures of merit with a response time of 4.7 μs. Therefore, the proposed methodology permits to realize ultra-sensitive, high-speed SiC optoelectronic devices for extremely high temperature applications. 

FIG: a) Energy band diagram of Graphene/p-SiC/Graphene structure, b) Cross-sectional view of the suggested IGE/4H-SiC MSM UV-PD with interdigitated electrodes

Acknowledgments: This work was supported by DGRSDT Of Ministry of Higher education of Algeria. The work was done in the unit of research of materials and renewable energies (URMER).