Molecular dynamics simulations on the wet/dry self-latching and electric fields triggered wet/dry transitions between nanosheets:A non-volatile memory nanostructure

We design a nanostructure composing of two nanoscale graphene sheets parallelly immersed in water.Using molecular dynamics simulations,we demonstrate that the wet/dry state between the graphene sheets can be self-latched;moreover,the wet→dry/dry→wet transition takes place when applying an external electric field perpendicular/parallel to the graphene sheets(E;/E;).This structure works like a flash memory device(a non-volatile memory):the stored information(wet and dry states)of the system can be kept spontaneously,and can also be rewritten by external electric fields.On the one hand,when the distance between the two nanosheets is close to a certain distance,the free energy barriers for the transitions dry→wet and wet→dry can be quite large.As a result,the wet and dry states are self-latched.On the other hand,an E;and an E;will respectively increase and decrease the free energy of the water located in-between the two nanosheets.Consequently,the wet→dry and dry→wet transitions are observed.Our results may be useful for designing novel information memory devices.

Design of an Electrically Written and Optically Read Non-volatile Memory Device Employing BiFeO3/Au Heterostructures with Strong Absorption Resonance

Exploiting new concepts for dense, fast, and nonvolatile random access memory with reduced energy consump- tion is a significant issue for information technology. Here we design an ＇electrically written and optically read＇ information storage device employing BiFeO3/A u heterostruetures with strong absorption resonance. The electro- optic effect is the basis for the device design, which arises from the strong absorption resonance in BiFeO3/Au heterostructures and the electrically tunable significant birefringence of the BiFeO3 film. We first construct a sim- ulation calculation of the BiFeO3/Au structure spectrum and identify absorption resonance and electro-optical modulation characteristics. Following a micro scale partition, the surface reflected light intensity of different polarization units is calculated. The results depend on electric polarization states of the BiFeO3 film, thus BiFeO3/Au heterostructures can essentially be designed as a type of electrically written and optically read infor- mation storage device by utilizing the scanning near-field optical microscopy technology based on the conductive silicon cantilever tip with nanofabricated aperture. This work will shed light on information storage technology.

Overview of one transistor type of hybrid organic ferroelectric non-volatile memory

Organic ferroelectric memory devices based on field effect transistors that can be configured between two stable states of on and off have been widely researched as the next generation data storage media in recent years.This emerging type of memory devices can lead to a new instrument system as a potential alternative to previous non-volatile memory building blocks in future processing units because of their numerous merits such as cost-effective process,simple structure and freedom in substrate choices.This bi-stable non-volatile memory device of information storage has been investigated using several organic or inorganic semiconductors with organic ferroelectric polymer materials.Recent progresses in this ferroelectric memory field,hybrid system have attracted a lot of attention due to their excellent device performance in comparison with that of all organic systems.In this paper,a general review of this type of ferroelectric non-volatile memory is provided,which include the device structure,organic ferroelectric materials,electrical characteristics and working principles.We also present some snapshots of our previous study on hybrid ferroelectric memories including our recent work based on zinc oxide nanowire channels.

A review of in situ transmission electron microscopy study on the switching mechanism and packaging reliability in non-volatile memory

Non-volatile memory(NVM)devices with non-volatility and low power consumption properties are important in the data storage field.The switching mechanism and packaging reliability issues in NVMs are of great research interest.The switching process in NVM devices accompanied by the evolution of microstructure and composition is fast and subtle.Transmission electron microscopy(TEM)with high spatial resolution and versatile external fields is widely used in analyzing the evolution of morphology,structures and chemical compositions at atomic scale.The various external stimuli,such as thermal,electrical,mechanical,optical and magnetic fields,provide a platform to probe and engineer NVM devices inside TEM in real-time.Such advanced technologies make it possible for an in situ and interactive manipulation of NVM devices without sacrificing the resolution.This technology facilitates the exploration of the intrinsic structure-switching mechanism of NVMs and the reliability issues in the memory package.In this review,the evolution of the functional layers in NVM devices characterized by the advanced in situ TEM technology is introduced,with intermetallic compounds forming and degradation process investigated.The principles and challenges of TEM technology on NVM device study are also discussed.

Bipolar resistive switching based on bis(8-hydroxyquinoline) cadmium complex:Mechanism and non-volatile memory application

Stable and persistent bipolar resistive switching was observed in an organic diode with the structure of indium-tin oxide （ITO）/bis（8-hydroxyquinoline） cadmium （Cdq2）/Al. Aggregate formation and electric field driven trapping and detrapping of charge carriers in the aggregate states that lie in the energy gap of the highest occupied molecular orbital （HOMO） and the lowest unoccupied molecular orbital （LUMO） of the organic molecule were proposed as the mechanism of the observed bipolar resistive switching, and this was solidly supported by the results of AFM investigations. Repeatedly set, read, and reset measurements demonstrated that the device is potentially applicable in non-volatile memories.

NEHASH:high-concurrency extendible hashing for non-volatile memory

Extendible hashing is an effective way to manage increasingly large file system metadata,but it suffers from low concurrency and lack of optimization for non-volatile memory(NVM).In this paper,a multilevel hash directory based on lazy expansion is designed to improve the concurrency and efficiency of extendible hashing,and a hash bucket management algorithm based on groups is presented to improve the efficiency of hash key management by reducing the size of the hash bucket,thereby improving the performance of extendible hashing.Meanwhile,a hierarchical storage strategy of extendible hashing for NVM is given to take advantage of dynamic random access memory(DRAM)and NVM.Furthermore,on the basis of the device driver for Intel Optane DC Persistent Memory,the prototype of high-concurrency extendible hashing named NEHASH is implemented.Yahoo cloud serving benchmark(YCSB)is used to test and compare with CCEH,level hashing,and cuckoo hashing.The results show that NEHASH can improve read throughput by up to 16.5%and write throughput by 19.3%.

Comparative evaluation of commercial Douchi by different molds:biogenic amines,non-volatile and volatile compounds

To provide new insights into the development and utilization of Douchi artificial starters,three common strains(Aspergillus oryzae,Mucor racemosus,and Rhizopus oligosporus)were used to study their influence on the fermentation of Douchi.The results showed that the biogenic amine contents of the three types of Douchi were all within the safe range and far lower than those of traditional fermented Douchi.Aspergillus-type Douchi produced more free amino acids than the other two types of Douchi,and its umami taste was more prominent in sensory evaluation(P<0.01),while Mucor-type and Rhizopus-type Douchi produced more esters and pyrazines,making the aroma,sauce,and Douchi flavor more abundant.According to the Pearson and PLS analyses results,sweetness was significantly negatively correlated with phenylalanine,cysteine,and acetic acid(P<0.05),bitterness was significantly negatively correlated with malic acid(P<0.05),the sour taste was significantly positively correlated with citric acid and most free amino acids(P<0.05),while astringency was significantly negatively correlated with glucose(P<0.001).Thirteen volatile compounds such as furfuryl alcohol,phenethyl alcohol,and benzaldehyde caused the flavor difference of three types of Douchi.This study provides theoretical basis for the selection of starting strains for commercial Douchi production.

An ultra-low-power area-efficient non-volatile memory in a 0.18μm 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）.

WOBTree:a write-optimized B+-tree for non-volatile memory

The emergence of non-volatile memory(NVM)has introduced new opportunities for performance optimizations in existing storage systems.To better utilize its byte-addressability and near-DRAM performance,NVM can be attached on the memory bus and accessed via load/store memory instructions rather than the conventional block interface.In this scenario,a cache line(usually 64 bytes)becomes the data transfer unit between volatile and non-volatile devices.However,the failure-atomicity of write on NVM is the memory bit width(usually 8 bytes).This mismatch between the data transfer unit and the atomicity unit may introduce write amplification and compromise data consistency of node-based data structures such as B+-trees.In this paper,we propose WOBTree,a Write-Optimized B+-Tree for NVM to address the mismatch problem without expensive logging.WOBTree minimizes the update granularity from a tree node to a much smaller subnode and carefully arranges the write operations in it to ensure crash consistency and reduce write amplification.Experimental results show that compared with previous persistent B+-tree solutions,WOBTree reduces the write amplification by up to 86× and improves write performance by up to 61× while maintaining similar search performance.

Formation of high density TiN nanocrystals and its application in non-volatile memories

Non-volatile memory based on TiN nanocrystal （TiN-NC） charge storage nodes embedded in SiO2 has been fabricated and its electrical properties have been measured. It was found that the density and size distribution of TiN-NCs can be controlled by annealing temperature. The formation of well separated crystalline TiN nano-dots with an average size of 5 nm is confirmed by transmission electron microscopy and x-ray diffraction, x-ray photoelectron spectroscopy confirms the existence of a transition layer of TiNxOy/SiON oxide between TiN-NC and SiO2, which reduces the barrier height of tunnel oxide and thereby enhances programming/erasing speed. The memory device shows a memory window of 2.5V and an endurance cycle throughout 10^5. Its charging mechanism, which is interpreted from the analysis of programming speed （dVth/dt） and the gate leakage versus voltage characteristics （Ig vs Vg）, has been explained by direct tunnelling for tunnel oxide and Fowler Nordheim tunnelling for control oxide at programming voltages lower than 9V, and by Fowler-Nordheim tunnelling for both the oxides at programming voltages higher than 9V.

Unimem: Runtime Data Management on Non-Volatile Memory-BasedHeterogeneous Main Memory for High Performance Computing

Non-volatile memory(NVM)provides a scalable and power-efficient solution to replace dynamic random access memory(DRAM)as main memory.However,because of the relatively high latency and low bandwidth of NVM,NVM is often paired with DRAM to build a heterogeneous memory system(HMS).As a result,data objects of the application must be carefully placed to NVM and DRAM for the best performance.In this paper,we introduce a lightweight runtime solution that automatically and transparently manages data placement on HMS without the requirement of hardware modifications and disruptive change to applications.Leveraging online profiling and performance models,the runtime solution characterizes memory access patterns associated with data objects,and minimizes unnecessary data movement.Our runtime solution effectively bridges the performance gap between NVM and DRAM.We demonstrate that using NVM to replace the majority of DRAM can be a feasible solution for future HPC systems with the assistance of a software-based data management.

Correlation between dominant bacterial community and non-volatile organic compounds during the fermentation of shrimp sauces

Shrimp sauce,one of the traditional salt-fermented food in China,has a unique flavor that is influenced by the resident microflora.The quality of salt-fermented shrimp sauce was evaluated in this work by determining the total volatile basic nitrogen(TVB-N),the amino acid nitrogen(AAN),organic acid,5’-nucleotide and free amino acids(FAA).Moreover,the dynamics of microbial diversity during processing was investigated by using high-throughput sequencing technology.The results showed that the AAN,TVB-N,organic acid,5’-nucleotide and FAA content were in range of 0.93-1.42 g/100 mL,49.91-236.27 mg/100 mL,6.65-20.68 mg/mL,3.51-6.56 mg/mL and 81.27-102.90 mg/mL.Among the microbial diversity found in the shrimp sauce,Tetragenococcus,Flavobacterium,Polaribacter,Haematospirillum and Staphylococcus were the predominant genera.Correlation analysis indicated that the bacteria Tetragenococcus and Staphylococcus were important in the formation of non-volatile compounds.Tetragenococcus positively correlated with a variety of FAAs;Staphylococcus positively correlated with 5’-nucleotides.The analysis indicated that Tetragenococcus and Staphylococcus were the core genera affecting non-volatile components.These findings indicate the dynamics of the bacterial community and non-volatile components inter-relationships during shrimp sauce fermentation and provide a theoretical basis for improving the fermentation process of shrimp sauce.

Extending SSD Lifespan with Comprehensive Non-Volatile Memory-Based Write Buffers

New non-volatile memory (NVM)technologies are expected to replace main memory DRAM (dynamic random access memory)in the near future.NAND flash technological breakthroughs have enabled wide adoption of solid state drives (SSDs)in storage systems.However,flash-based SSDs,by nature,cannot avoid low endurance problems because each cell only allows a limited number of erasures.This can give rise to critical SSD reliability issues.Since many SSD write operations eventually cause many SSD erase operations,reducing SSD write traffic plays a crucial role in SSD reliability. This paper proposes two NVM-based buffer cache policies which can work together in different layers to maximally reduce SSD write traffic:a main memory buffer cache design named Hierarchical Adaptive Replacement Cache (H-ARC)and an internal SSD write buffer design named Write Traffic Reduction Buffer (WRB).H-ARC considers four factors (dirty,clean, recency,and frequency)to reduce write traffic and improve cache hit ratios in the host.WRB reduces block erasures and write traffic further inside an SSD by effectively exploiting temporal and spatial localities.These two comprehensive schemes significantly reduce total SSD write traffic at each different layer (i.e.,host and SSD)by up to 3x.Consequently,they help extend SSD lifespan without system performance degradation.

Astrocytic endothelin-1 overexpression impairs learning and memory ability in ischemic stroke via altered hippocampal neurogenesis and lipid metabolism

Vascular etiology is the second most prevalent cause of cognitive impairment globally.Endothelin-1,which is produced and secreted by endothelial cells and astrocytes,is implicated in the pathogenesis of stroke.However,the way in which changes in astrocytic endothelin-1 lead to poststroke cognitive deficits following transient middle cerebral artery occlusion is not well understood.Here,using mice in which astrocytic endothelin-1 was overexpressed,we found that the selective overexpression of endothelin-1 by astrocytic cells led to ischemic stroke-related dementia(1 hour of ischemia;7 days,28 days,or 3 months of reperfusion).We also revealed that astrocytic endothelin-1 overexpression contributed to the role of neural stem cell proliferation but impaired neurogenesis in the dentate gyrus of the hippocampus after middle cerebral artery occlusion.Comprehensive proteome profiles and western blot analysis confirmed that levels of glial fibrillary acidic protein and peroxiredoxin 6,which were differentially expressed in the brain,were significantly increased in mice with astrocytic endothelin-1 overexpression in comparison with wild-type mice 28 days after ischemic stroke.Moreover,the levels of the enriched differentially expressed proteins were closely related to lipid metabolism,as indicated by Kyoto Encyclopedia of Genes and Genomes pathway analysis.Liquid chromatography-mass spectrometry nontargeted metabolite profiling of brain tissues showed that astrocytic endothelin-1 overexpression altered lipid metabolism products such as glycerol phosphatidylcholine,sphingomyelin,and phosphatidic acid.Overall,this study demonstrates that astrocytic endothelin-1 overexpression can impair hippocampal neurogenesis and that it is correlated with lipid metabolism in poststroke cognitive dysfunction.

Promotion of structural plasticity in area V2 of visual cortex prevents against object recognition memory deficits in aging and Alzheimer's disease rodents

Memory deficit,which is often associated with aging and many psychiatric,neurological,and neurodegenerative diseases,has been a challenging issue for treatment.Up till now,all potential drug candidates have failed to produce satisfa ctory effects.Therefore,in the search for a solution,we found that a treatment with the gene corresponding to the RGS14414protein in visual area V2,a brain area connected with brain circuits of the ventral stream and the medial temporal lobe,which is crucial for object recognition memory(ORM),can induce enhancement of ORM.In this study,we demonstrated that the same treatment with RGS14414in visual area V2,which is relatively unaffected in neurodegenerative diseases such as Alzheimer s disease,produced longlasting enhancement of ORM in young animals and prevent ORM deficits in rodent models of aging and Alzheimer’s disease.Furthermore,we found that the prevention of memory deficits was mediated through the upregulation of neuronal arbo rization and spine density,as well as an increase in brain-derived neurotrophic factor(BDNF).A knockdown of BDNF gene in RGS14414-treated aging rats and Alzheimer s disease model mice caused complete loss in the upregulation of neuronal structural plasticity and in the prevention of ORM deficits.These findings suggest that BDNF-mediated neuronal structural plasticity in area V2 is crucial in the prevention of memory deficits in RGS14414-treated rodent models of aging and Alzheimer’s disease.Therefore,our findings of RGS14414gene-mediated activation of neuronal circuits in visual area V2 have therapeutic relevance in the treatment of memory deficits.

The Impact of Opioid Drugs on Memory and Other Cognitive Functions: A Review

Background and Purpose: Opioids, used for centuries to alleviate pain, have become a double-edged sword. While effective, they come with a host of adverse effects, including memory and cognition impairment. This review delves into the impact of opioid drugs on cognitive functions, explores underlying mechanisms, and investigates their prevalence in both medical care and illicit drug use. The ultimate goal is to find ways to mitigate their potential harm and address the ongoing opioid crisis. Methods: We sourced data from PubMed and Google Scholar, employing search combinations like “opioids,” “memory,” “cognition,” “amnesia,” “cognitive function,” “executive function,” and “inhibition.” Our focus was on English-language articles spanning from the inception of these databases up to the present. Results: The literature consistently reveals that opioid use, particularly at high doses, adversely affects memory and other cognitive functions. Longer deliberation times, impaired decision-making, impulsivity, and behavioral disorders are common consequences. Chronic high-dose opioid use is associated with conditions such as amnesiac syndrome (OAS), post-operative cognitive dysfunction (POCD), neonatal abstinence syndrome (NAS), depression, anxiety, sedation, and addiction. Alarming trends show increased opioid use over recent decades, amplifying the risk of these outcomes. Conclusion: Opioids cast a shadow over memory and cognitive function. These effects range from amnesiac effects, lessened cognitive function, depression, and more. Contributing factors include over-prescription, misuse, misinformation, and prohibition policies. Focusing on correct informational campaigns, removing punitive policies, and focusing on harm reduction strategies have been shown to lessen the abuse and use of opioids and thus helping to mitigate the adverse effects of these drugs. Further research into the impacts of opioids on cognitive abilities is also needed as they are well demonstrated in the literature, but the mechanism is not often completely understood.

Design and implementation of dual-mode configurable memory architecture for CNN accelerator

With the rapid development of deep learning algorithms,the computational complexity and functional diversity are increasing rapidly.However,the gap between high computational density and insufficient memory bandwidth under the traditional von Neumann architecture is getting worse.Analyzing the algorithmic characteristics of convolutional neural network(CNN),it is found that the access characteristics of convolution(CONV)and fully connected(FC)operations are very different.Based on this feature,a dual-mode reronfigurable distributed memory architecture for CNN accelerator is designed.It can be configured in Bank mode or first input first output(FIFO)mode to accommodate the access needs of different operations.At the same time,a programmable memory control unit is designed,which can effectively control the dual-mode configurable distributed memory architecture by using customized special accessing instructions and reduce the data accessing delay.The proposed architecture is verified and tested by parallel implementation of some CNN algorithms.The experimental results show that the peak bandwidth can reach 13.44 GB·s^(-1)at an operating frequency of 120 MHz.This work can achieve 1.40,1.12,2.80 and 4.70 times the peak bandwidth compared with the existing work.

Enhanced Memory-Safe Linux Security Modules (eLSMs) for Improving Security of Docker Containers for Data Centers

The adoption of Docker containers has revolutionized software deployment by providing a lightweight and efficient way to isolate applications in data centers. However, securing these containers, especially when handling sensitive data, poses significant challenges. Traditional Linux Security Modules (LSMs) such as SELinux and AppArmor have limitations in providing fine-grained access control to files within containers. This paper presents a novel approach using eBPF (extended Berkeley Packet Filter) to implement a LSM that focuses on file-oriented access control within Docker containers. The module allows the specification of policies that determine which programs can access sensitive files, providing enhanced security without relying solely on the host operating system’s major LSM.

Optimized operation scheme of flash-memory-based neural network online training with ultra-high endurance

With the rapid development of machine learning,the demand for high-efficient computing becomes more and more urgent.To break the bottleneck of the traditional Von Neumann architecture,computing-in-memory(CIM)has attracted increasing attention in recent years.In this work,to provide a feasible CIM solution for the large-scale neural networks(NN)requiring continuous weight updating in online training,a flash-based computing-in-memory with high endurance(10^(9) cycles)and ultrafast programming speed is investigated.On the one hand,the proposed programming scheme of channel hot electron injection(CHEI)and hot hole injection(HHI)demonstrate high linearity,symmetric potentiation,and a depression process,which help to improve the training speed and accuracy.On the other hand,the low-damage programming scheme and memory window(MW)optimizations can suppress cell degradation effectively with improved computing accuracy.Even after 109 cycles,the leakage current(I_(off))of cells remains sub-10pA,ensuring the large-scale computing ability of memory.Further characterizations are done on read disturb to demonstrate its robust reliabilities.By processing CIFAR-10 tasks,it is evident that~90%accuracy can be achieved after 109 cycles in both ResNet50 and VGG16 NN.Our results suggest that flash-based CIM has great potential to overcome the limitations of traditional Von Neumann architectures and enable high-performance NN online training,which pave the way for further development of artificial intelligence(AI)accelerators.

The study of lithographic variation in resistive random access memory

Reducing the process variation is a significant concern for resistive random access memory(RRAM).Due to its ultrahigh integration density,RRAM arrays are prone to lithographic variation during the lithography process,introducing electrical variation among different RRAM devices.In this work,an optical physical verification methodology for the RRAM array is developed,and the effects of different layout parameters on important electrical characteristics are systematically investigated.The results indicate that the RRAM devices can be categorized into three clusters according to their locations and lithography environments.The read resistance is more sensitive to the locations in the array(~30%)than SET/RESET voltage(<10%).The increase in the RRAM device length and the application of the optical proximity correction technique can help to reduce the variation to less than 10%,whereas it reduces RRAM read resistance by 4×,resulting in a higher power and area consumption.As such,we provide design guidelines to minimize the electrical variation of RRAM arrays due to the lithography process.