非易失铁电存储器的进展和若干问题

铁电薄膜与半导体集成,产生了新一代非易失存储器。它的功耗之小,写入速度之快,可重写次数之多以及抗辐照能力之强是目前任何一种半导体存储器所不及的。文章介绍了非易失铁电存储器的原理、特点、进展和应用,并讨论了这类存储器在进入大规模商业生产时所面临的若干材料、工艺和器件失效等问题。     

An ultra-low-power area-efficient non-volatile memory in a 0.18 μ m single-poly CMOS process for passive RFID tags

This paper presents an ultra-low-power area-efficient non-volatile memory(NVM) in a 0.18μm singlepoly standard CMOS process for passive radio frequency identification(RFID) tags.In the memory cell,a novel low-power operation method is proposed to realize bi-directional Fowler-Nordheim tunneling during write operation. Furthermore,the cell is designed with PMOS transistors and coupling capacitors to minimize its area.In order to improve its reliability,the cell consists of double floating gates to store the data,and the 1 kbit NVM was implemented in a 0.18μm single-poly standard CMOS process.The area of the memory cell and 1 kbit memory array is 96μm~2 and 0.12 mm~2,respectively.The measured results indicate that the program/erase voltage ranges from 5 to 6 V.The power consumption of the read/write operation is 0.19μW/0.69μW at a read/write rate of (268 kb/s)/(3.0 kb/s).     

适用于无源射频标签的低功耗单栅非挥发性存储器

针对低成本、低功耗无源射频电子标签,采用SMIC 0.18μm标准CMOS工艺设计实现了单栅、576bit的非挥发性存储器.存储器单元基于双向Fowler-Nordheim隧穿效应原理并采用普通的pMOS晶体管实现;编程/擦写时间为10ms/16bit.芯片实现块编程和擦写功能,通过提出一种新型的敏感放大器而实现了读功耗的优化.在电源电压为1.2V,数据率为640kHz时,读操作平均消耗电流约为0.8μA.     

A Bist Scheme for Non-Volatile Memories

A new BIST scheme for on-chip testing of non-volatile memories and based on signature analysis is presented. The signature of the whole memory, whose content can be changed selectively by the user, is dynamically self-learned by the memory and it is saved in a dedicated memory location. Either such a signature can be externally compared with the expected one in order to check for the programming operation, or it can be used for comparison purposes when data retention must be self-tested.     

EEPROM Diagnosis Based on Threshold Voltage Embedded Measurement

Knowing, that the threshold voltage of the EEPROM memory cells is a key parameter to determine the overall performance of the memory, a built in structure to extract this information is a very relevant choice to fast diagnose the failure in the memory. Thus, the objective of this paper is to present a built in self-diagnosis of EEPROM memory cells, based on threshold voltage extraction. In order to extract the threshold voltage, the modified circuit and the associated test sequence are presented. Based on the threshold voltage extraction, complementary information is proposed to improve the classical memory diagnosis methodology.This revised version was published online in March 2005 with corrections to the cover date.     

Chemical Characterization of Three Accessions of Brassica juncea L. Extracts from Different Plant Tissues

Indian mustard or Brassica juncea (B. juncea) is an oilseed plant used in many types of food (as mustard or IV range salad). It also has non-food uses (e.g., as green manure), and is a good model for phytoremediation of metals and pesticides. In recent years, it gained special attention due to its biological compounds and potential beneficial effects on human health. In this study, different tissues, namely leaves, stems, roots, and flowers of three accessions of B. juncea: ISCI 99 (Sample A), ISCI Top (Sample B), and “Broad-leaf” (Sample C) were analyzed by HPLC-PDA/ESI-MS/MS. Most polyphenols identified were bound to sugars and phenolic acids. Among the three cultivars, Sample A flowers turned were the richest ones, and the most abundant bioactive identified was represented by Isorhamnetin 3,7-diglucoside (683.62 µg/100 mg dry weight (DW) in Sample A, 433.65 µg/100 mg DW in Sample B, and 644.43 µg/100 mg DW in Sample C). In addition, the most complex samples, viz. leaves were analyzed by GC-FID/MS. The major volatile constituents of B. juncea L. leaves extract in the three cultivars were benzenepropanenitrile (34.94% in Sample B, 8.16% in Sample A, 6.24% in Sample C), followed by benzofuranone (8.54% in Sample A, 6.32% in Sample C, 3.64% in Sample B), and phytone (3.77% in Sample B, 2.85% in Sample A, 1.01% in Sample C). The overall evaluation of different tissues from three B. juncea accessions, through chemical analysis of the volatile and non-volatile compounds, can be advantageously taken into consideration for future use as dietary supplements and nutraceuticals in food matrices.     

Separation and identification of volatile and non-volatile compounds of wine by sorbent extraction and capillary gas chromatography

Sorbent extraction technology was used to separate the volatile and non-volatile components of wine. The extracts were analyzed by capillary gas chromatography.     

Improvement in refractive-index change in LiNbO3：Ce：Cu by applying an external electric field

By jointly solving two-centre material equations with a nonzero external electric field and coupled-wave equations, we have numerically studied the dependence of the non-volatile holographic recording in LiNbO3：Ce：Cu crystals on the external electric field. The dominative photovoltaic effect of the non-volatile holographic recording in doubly doped LiNbO3 crystals is directly verified. And an external electric field that is applied in the positive direction along the c-axis （or a large one in the negative direction of the c-axis） in the recording phase and another one that is applied in the negative direction of the c-axis in the fixing phase are both proved to benefit strong photorefractive performances. Experimental verifications are given with a small electric field applied externally.     

Comparison between Pt/TiO2/Pt and Pt/TaOX/TaOY/Pt based bipolar resistive switching devices

Nonvolatile memories have emerged in recent years and have become a leading candidate towards replacing dynamic and static random-access memory devices. In this article, the performances of TiO₂ and TaO₂ nonvolatile memristive devices were compared and the factors that make TaO₂ memristive devices better than TiO₂ memristive devices were studied. TaO₂ memristive devices have shown better endurance performances (10⁸ times more switching cycles) and faster switching speed (5 times) than TiO₂ memristive devices. Electroforming of TaO₂ memristive devices requires~4.5 times less energy than TiO₂ memristive devices of a similar size. The retention period of TaO₂ memristive devices is expected to exceed 10 years with sufficient experimental evidence. In addition to comparing device performances, this article also explains the differences in physical device structure, switching mechanism, and resistance switching performances of TiO₂ and TaO₂ memristive devices. This article summarizes the reasons that give TaO₂ memristive devices the advantage over TiO₂ memristive devices, in terms of electroformation, switching speed, and endurance.     

Memristive SRAM cell of seven transistors and one memristor

In this work, a novel memristive SRAM cell is designed using seven transistors and one memristor (7T1M). In this 7T1M SRAM cell, the non-volatile functionality is achieved by adding a single memristor and a transistor to the design of a volatile SRAM cell. The designing of the 7T1M SRAM cell also introduces VCTRL which allows bidirectional current flowing through the memristor, instead of relying on complementary input sources which would require more design components. In this article, memristive SRAM cells available from the literature are simulated using the same simulation environment for a fair comparison. Simulations show that the 7T1M SRAM cell has the least power consumption against other memristive SRAM cells in the literature. The 7T1M SRAM cell operates with an average switching speed of 176.21 ns and an average power consumption of 2.9665 μW. The 7T1M SRAM cell has an energy-delay-area product value of 1.61, which is the lowest among the memristive SRAM cells available in the literature.