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In this study, we prepare Cr-doped Sb 70 Se 30 (SS) thin films via the magnetron sputtering. The influence of Cr doping on the crystallization behavior and structure characteristics of the SS thin films is systematically studied using a combination of experimental analyzes and theoretical calculations. The results reveal that compared with SS thin films, Cr-doped SS thin films exhibit higher crystallization temperature, better data retention capability, larger crystallization activation energy, and reduced resistance drift coefficient. In addition, the incorporation of Cr effectively suppresses grain growth in the SS thin films and refines the grain size. The electrical transport properties of the Cr-doped SS thin films are analyzed using a Hall system. Both X-ray photoelectron spectroscopy and first-principles calculations indicate that Cr is more prone to occupy Sb atoms and form stronger Cr–Se bonds, consequently enhancing the stability of the SS thin films. Raman spectroscopy confirms that the introduction of Cr leads to a decrease in bond length and an increase in bond energy. Moreover, the Cr-doped SS thin film exhibits minimal volume fluctuations and a smoother surface morphology, resulting in enhanced interface performance and reliability. Taken together, these results indicate that the introduction of Cr is an effective strategy for optimizing the properties and modifying the structures of SS phase-change materials. [ABSTRACT FROM AUTHOR]

Disorder‐induced electronic localization is responsible for the OFF state of the Ovonic threshold switching (OTS) device, which is an indispensable component in the present 3D‐crossbar‐architecture phase‐change memory circuit. However, the atomic mechanism of the OTS device, especially the role of thermal effect, remains a long‐term open question. Recent researches suggest that the working current of the OTS ON‐state is often large enough to melt the adjacent phase‐change memory material in the OTS+PCM devices. Thus, Joule heating‐induced atomic/electronic structure transition in OTS materials must be seriously considered. Taking the typical OTS material GeSe as an example, first‐principles calculations reveal an unexpected electronic delocalization induced by the enhanced structural disorder upon solid‐liquid transition. Meanwhile, as the temperature rises, the band gap decreases or even closes, leading to an increase in carrier concentration. Therefore, the melting filament with high conductivity could be responsible for the holding‐ON state of OTS materials. The results in this study may provide possible explanations for some puzzles of OTS devices, such as the reasons for holding‐ON state and limited endurance. [ABSTRACT FROM AUTHOR]

The superlattices phase‐change memory (SL‐PCM), based on GeTe/Sb2Te3 superlattices (SLs), garners considerable attention within the academic community owing to its exceptional electrical properties. While the exact mechanism remains a topic of ongoing debate, researchers widely acknowledge that the presence of van der Waals (vdW) gap structures within SLs plays a pivotal role. However, the formation of vertical nanoparticles (VNPs) from the random orientation of Sb2Te3 and the substantial intermixing between GeTe and Sb2Te3 due to high‐temperature fabrication processes leads to pronounced elemental intermixing during electrical operations, causing a loss of SLs properties. This investigation uses atomic layer deposition techniques, specifically Sb‐atomic seed layer and periodic quintuple layers stacking, to address issues from random orientation Sb2Te3 grains and anomalous VNPs. This approach yields Sb2Te3 crystalline films with a high‐stability vdW gap structures. By leveraging these films, SLs with a preferred crystallographic orientation at a notable low temperature of 90 °C are successfully fabricated. The optimized SLs exhibit remarkable structural stability and mitigate alloy phase emergence during electrical operations, resulting in a 100‐fold enhancement in device durability. This work advances reliable SL‐PCM understanding and implementation, propelling this memory technology into the next generation. [ABSTRACT FROM AUTHOR]

Phase‐change random access memory (PCRAM) is one of the most technologically mature candidates for next‐generation non‐volatile memory and is currently at the forefront of artificial intelligence and neuromorphic computing. Traditional PCRAM exploits the typical phase transition and electrical/optical contrast between non‐crystalline and crystalline states of chalcogenide phase‐change materials (PCMs). Currently, traditional PCRAM faces challenges that vastly hinder further memory optimization, for example, the high‐power consumption, significant resistance drift, and the contradictory nature between crystallization speed and thermal stability, nearly all of them are related to the non‐crystalline state of PCMs. In this respect, a reversible crystalline‐to‐crystalline phase transition can solve the above problems. This review delves into the atomic structures and switching mechanisms of the emerging atypical crystalline‐to‐crystalline transitions, and the understanding of the thermodynamic and kinetic features. Ultimately, an outlook is provided on the future opportunities that atypical all‐crystalline phase transitions offer for the development of a novel PCRAM, along with the key challenges that remain to be addressed. [ABSTRACT FROM AUTHOR]

We have prepared Sb70Se30/HfO2 (SS/HO) multilayer thin films by magnetron sputtering method and studied the effect of the HO interlayer on the phase transition behavior of the SS thin films. The results indicate that the introduction of the HO interlayer not only enhances the crystallization temperature, data retention capability, and crystallization activation energy of the SS thin film but also reduces resistance drift and suppresses its crystallization. X-ray photoelectron spectroscopy shows that Sb atoms exhibit a preference for bonding with O atoms at multilayer interfaces, thereby forming stronger Sb–O bonds, which contribute to the thermal stability of multilayer thin films. The Raman results further confirm a reduction in bond length and an increase in bond energy. Furthermore, the SS/HO thin films exhibit enhanced substrate adhesion and a more uniform surface morphology. The study of crystallization kinetics reveals that the crystallization mechanism of SS/HO thin films is predominantly governed by one-dimensional growth. Moreover, the lower threshold switching voltage (1.65 V) in SS/HO thin films contributes to a reduction in power consumption during SET operations. All these findings collectively demonstrate that SS/HO thin films are anticipated to be excellent candidate materials for phase-change memory applications. [ABSTRACT FROM AUTHOR]

Ge‐rich Ge–Sb–Te (GGST) alloys are the most promising materials for phase‐change memory in embedded applications, being able to fulfill the tough data retention requirements of automotive and consumer markets. GGST alloys are sensitive to thermal budgets and spatial confinement; thus, memory device process integration and architecture can strongly impact their final electrical properties and reliability. Herein, exploiting a statistical methodology capable to extract quantitative metrics for evaluating by‐process segregation, the inhomogeneity of out‐of‐fab GGST material in function of process parameters is studied such as architecture and alloy composition. The present results with the already known source of segregation, namely the back‐end‐of‐line thermal budget, are compared providing a comprehensive description of the main modulating factors of segregation among these different process parameters. [ABSTRACT FROM AUTHOR]

The work is devoted to the study of the characteristics of the state control of a thin-film element based on a phase-change GeTe material. The properties of such an element have been controlled by the action of sequences of ultrashort laser pulses. This action leads to a rapid heating of the thin film element and provides a phase transition between states with a resistance different by several orders of magnitude. The dynamics of the resistance was studied using a high speed oscilloscope according to the scheme where the element under study was the voltage divider arm of a highly stable source. Three different types of conductivity switching were observed for 100 nm thin films. For low energy laser radiation, several distinct states were obtained in which the material film has predominantly semiconducting properties. As the energy of the optical pulses increases, the number of possible stable states determined by the specific conductivity of the material decreases to two, one of which (low resistance) is exclusively metallic properties. In all cases, the time taken to switch to a stable state does not exceed a few tens of nanoseconds for films up to 100 nm thick. The study has demonstrated that the structures described can be used to implement optically controlled memristive elements. In addition, the large number of possible allowable specific resistances of the element will make it possible to use it to increase the information capacity of memory cells based on phase-change materials or to implement optoelectronic neuromorphic systems.

Phase-change memory (PCM), recently developed as the storage-class memory in a computer system, is a new non-volatile memory technology. In addition, the applications of PCM in a non-von Neumann computing, such as neuromorphic computing and in-memory computing, are being investigated. Although PCM-based devices have been extensively studied, several concerns regarding the electrical, thermal, and structural dynamics of phase-change devices remain. In this article, aiming at PCM devices, a comprehensive review of PCM materials is provided, including the primary PCM device mechanics that underpin read and write operations, physics-based modeling initiatives and experimental characterization of the many features examined in nanoscale PCM devices. Finally, this review will propose a prognosis on a few unsolved challenges and highlight research areas of further investigation. We certify that the submitted manuscript is truly original, unpublished, and not being considered for publication elsewhere. [ABSTRACT FROM AUTHOR]

The conductivity drift of GST (Ge2Sb2Te5)-based PCM (Phase Change Memory) structures in the reset state hinders the development of multi-level PCM memories and their applications. Despite intensive research, the origin of this drift remains unclear. The results presented here of analysis, based on the JMAK and Maxwell-Wagner models, indicate that the current interpretation of the results of conductivity measurements of GST-based PCM structures in the reset state may cause ambiguity in determining the origin of the conductivity drift of these structures in this state. [ABSTRACT FROM AUTHOR]

Phase‐change materials have long been employed for rewriteable optical data storage at the industrial scale and are hailed as one of the most mature technologies for their applications in emerging nonvolatile memories. Memristors based on these materials have the potential to circumvent the long‐standing von Neumann bottleneck and offer significant computational advantage through neuromorphic computing. A very core fundamental concept that lies at the crux for such realization is their ability to offer multilevel cell (MLC) storage, in contrast to the binary counterpart. Yet, numerous challenges still remain to be tackled for their successful implementation in this regard. This work is a finite element analysis that particularly reports the polarity dependence of such MLC operation in the conventional mushroom geometry of devices employing this technology. The mechanism lying underneath is discussed and a perspective combining thermoelectric effects with the energy band diagrams resulting from metal–semiconductor contact formation is additionally put forth. [ABSTRACT FROM AUTHOR]

ABSTRACTPhase-change memory (PCM), recently developed as the storage-class memory in a computer system, is a new non-volatile memory technology. In addition, the applications of PCM in a non-von Neumann computing, such as neuromorphic computing and in-memory computing, are being investigated. Although PCM-based devices have been extensively studied, several concerns regarding the electrical, thermal, and structural dynamics of phase-change devices remain. In this article, aiming at PCM devices, a comprehensive review of PCM materials is provided, including the primary PCM device mechanics that underpin read and write operations, physics-based modeling initiatives and experimental characterization of the many features examined in nanoscale PCM devices. Finally, this review will propose a prognosis on a few unsolved challenges and highlight research areas of further investigation.

Phase‐change random‐access memory (PCRAM) devices suffer from pronounced resistance drift originating from considerable structural relaxation of phase‐change materials (PCMs), which hinders current developments of high‐capacity memory and high‐parallelism computing that both need reliable multibit programming. This work realizes that compositional simplification and geometrical miniaturization of traditional GeSbTe‐like PCMs are feasible routes to suppress relaxation. While to date, the aging mechanisms of the simplest PCM, Sb, at nanoscale, have not yet been unveiled. Here, this work demonstrates that in an optimal thickness of only 4 nm, the thin Sb film can enable a precise multilevel programming with ultralow resistance drift coefficients, in a regime of ≈10−4–10−3. This advancement is mainly owed to the slightly changed Peierls distortion in Sb and the less‐distorted octahedral‐like atomic configurations across the Sb/SiO2 interfaces. This work highlights a new indispensable approach, interfacial regulation of nanoscale PCMs, for pursuing ultimately reliable resistance control in aggressively‐miniaturized PCRAM devices, to boost the storage and computing efficiencies substantially. [ABSTRACT FROM AUTHOR]

The layered crystal structure of Cr2Ge2Te6 shows ferromagnetic ordering at the two‐dimensional limit, which holds promise for spintronic applications. However, external voltage pulses can trigger amorphization of the material in nanoscale electronic devices, and it is unclear whether the loss of structural ordering leads to a change in magnetic properties. Here, it is demonstrated that Cr2Ge2Te6 preserves the spin‐polarized nature in the amorphous phase, but undergoes a magnetic transition to a spin glass state below 20 K. Quantum‐mechanical computations reveal the microscopic origin of this transition in spin configuration: it is due to strong distortions of the CrTeCr bonds, connecting chromium‐centered octahedra, and to the overall increase in disorder upon amorphization. The tunable magnetic properties of Cr2Ge2Te6 can be exploited for multifunctional, magnetic phase‐change devices that switch between crystalline and amorphous states. [ABSTRACT FROM AUTHOR]

Understanding the nature of charge‐trapping defects in amorphous chalcogenide alloy‐based phase‐change memory materials is important for tailoring the development of multilevel memory devices with increased data storage density. Herein, hybrid density‐functional theory simulations have been employed to investigate electron‐ and hole‐trapping processes in melt‐quenched glassy models of four different Ge‐Sb‐Te compositions, namely, GeTe, Sb2Te3, GeTe4, and Ge2Sb2Te5. The calculations demonstrate that extra electrons and holes are spontaneously trapped, creating charge‐trapping centers in the bandgap of the amorphous materials. Over‐ and undercoordinated atoms, tetrahedral and "see‐saw" octahedral‐like geometries, fourfold rings, homopolar bonds, near‐linear triatomic configurations, and chain‐like motifs comprise the range of the defective atomic environments that have been identified in the structural patterns of the charge‐trapping sites inside the glassy networks. The results illustrate that charge trapping corresponds to an intrinsic property of the glassy Ge‐Sb‐Te systems, show the impact of electron and hole localization on the atomic bonding of these materials, and they may have important implications related to the operation of phase‐change electronic‐memory devices. [ABSTRACT FROM AUTHOR]

Storage density improvement is a key challenge for phase‐change memory (PCM) application for storage class memory (SCM). The high‐aspect‐ratio design in confined‐structure PCM enables controllable multilevel cell (MLC) operation. However, the increasing aspect‐ratio will cause too large energy consumption to successfully operate the PCM. The trade‐off of different aspect‐ratio sizes of Ge2Sb2Te5 (GST) nanowires (NWs) is investigated. Through COMSOL simulation and experiments, with the same Reset energy, the limit of aspect‐ratio decreases with increasing NWs lengths. In the meantime, larger Reset energy is required with a larger length for the same aspect‐ratio devices. Finally, the design range of the high aspect‐ratio is optimized in which the NWs length size is below 1.5 um and the aspect‐ratio ranges from 8:1 to 10:1. This work can provide guidance for the design of high‐aspect‐ratio 3D PCM with better MLC. [ABSTRACT FROM AUTHOR]

Herein, a finite element simulation framework for phase‐change memory devices that simultaneously solves for current continuity, electrothermal heating, and crystallization–amorphization dynamics using electrothermal models and dynamic material parameters that are functions of electric field and temperature is described. In this latest model, an electric field‐ and temperature‐dependent electrical conductivity model of stable amorphous Ge2Sb2Te5 (GST) obtained from experiments performed on GST line cells to study Read, Reset, and Set operations of mushroom cells is incorporated. The effects of current polarity, heater height, Reset pulse rise and fall times, access device configuration, and ambient temperature are analyzed. The simulation results predict a 2x change in Reset current requirements with different current polarity due to thermoelectric effects. Heater height plays a significant role in thermal losses; ≈16% decrease in Reset current for 4x increase in the heater height is obtained. Increase in the ambient temperature results in a linear decrease in the Reset power required to achieve the same Reset/Set resistance contrast. [ABSTRACT FROM AUTHOR]

Silicon photonics (SiPh) technology has facilitated the deployment of integrated photonics across different application domains, from ultra-fast communication in Datacom applications to energy-efficient optical computation in emerging hardware accelerators for machine learning. More recently, the integration of SiPh and phase change materials has created a unique opportunity to realize adaptable, reconfigurable, and programmable photonic platforms. In particular, the nonvolatile programmability in phase change materials has made them a promising candidate for implementing photonic memory cells and architectures. Accordingly, photonic memory systems and even in-memory photonic computing paradigms are on the rise, especially given their potential for improving data access in electronic and photonic processors. However, there are still many challenges in the design and fabrication of phase-change photonic integrated circuits, which need to be addressed. This article presents a comprehensive survey on the recent advances and challenges for the integration of phase change materials with contemporary photonic devices while focusing on the photonic memory application. In particular, we explore phase-change photonic memory from the material level to the architecture level by presenting an overview of different material-level characteristics of phase change materials with their optical, electrical, and thermal properties as well as their integration into SiPh devices and photonic memory architectures and their application for in-memory photonic computing. We also present a comparison with electronic memory and discuss open research challenges that must be addressed to further advance phase-change photonic memory towards successful integration into emerging computing systems.

Abstract Phase‐change random‐access memory (PCRAM) devices suffer from pronounced resistance drift originating from considerable structural relaxation of phase‐change materials (PCMs), which hinders current developments of high‐capacity memory and high‐parallelism computing that both need reliable multibit programming. This work realizes that compositional simplification and geometrical miniaturization of traditional GeSbTe‐like PCMs are feasible routes to suppress relaxation. While to date, the aging mechanisms of the simplest PCM, Sb, at nanoscale, have not yet been unveiled. Here, this work demonstrates that in an optimal thickness of only 4 nm, the thin Sb film can enable a precise multilevel programming with ultralow resistance drift coefficients, in a regime of ≈10−4–10−3. This advancement is mainly owed to the slightly changed Peierls distortion in Sb and the less‐distorted octahedral‐like atomic configurations across the Sb/SiO2 interfaces. This work highlights a new indispensable approach, interfacial regulation of nanoscale PCMs, for pursuing ultimately reliable resistance control in aggressively‐miniaturized PCRAM devices, to boost the storage and computing efficiencies substantially.

Abstract The layered crystal structure of Cr2Ge2Te6 shows ferromagnetic ordering at the two‐dimensional limit, which holds promise for spintronic applications. However, external voltage pulses can trigger amorphization of the material in nanoscale electronic devices, and it is unclear whether the loss of structural ordering leads to a change in magnetic properties. Here, it is demonstrated that Cr2Ge2Te6 preserves the spin‐polarized nature in the amorphous phase, but undergoes a magnetic transition to a spin glass state below 20 K. Quantum‐mechanical computations reveal the microscopic origin of this transition in spin configuration: it is due to strong distortions of the CrTeCr bonds, connecting chromium‐centered octahedra, and to the overall increase in disorder upon amorphization. The tunable magnetic properties of Cr2Ge2Te6 can be exploited for multifunctional, magnetic phase‐change devices that switch between crystalline and amorphous states.

High thermal stability, fast operation speed, low thickness variation, and low resistance drift of phase-change nanomaterials are the essential characteristics in phase-change memory (PCM) applications. In this work, we put forward a graphite carbon-doped Sb2Te (C-Sb2Te) chalcogenide with semiconductor process compatibility. Our results prove that the proposed C-Sb2Te has excellent thermal stability and high operation speed. More importantly, the thickness change and resistance drift are only 0.89% and 0.0149, respectively. The C-Sb2Te-based memory device exhibits a high switching speed to the instrument test limit (5 ns) with a large resistance ratio, low operation voltage (2 V), and low power consumption (6.9 pJ). The proposed C-Sb2Te nanostructure material exceeds both conventional Ge2Sb2Te5 and transition-metal-doped Sb2Te materials in terms of its performance. Ab initio molecular dynamics simulations reveal that C–C and C–Sb bonds as well as C–C chains are formed in C-Sb2Te, and C doping constrains phase transition in a small region and refines grains of C-Sb2Te, thus resulting in the high performance. Our study suggests that C-Sb2Te is a potential candidate for high-speed, high-thermal-stability, and high-reliability PCM applications. [ABSTRACT FROM AUTHOR]

Phase‐change semiconductor is one of the best candidates for designing nonvolatile memory, but it has never been realized in organic semiconductors until now. Here, a phase‐changeable and high‐mobility organic semiconductor (3,6‐DATT) is first synthesized. Benefiting from the introduction of electrostatic hydrogen bond (S···H), the molecular conformation of 3,6‐DATT crystals can be reversibly modulated by the electric field and ultraviolet irradiation. Through experimental and theoretical verification, the tiny difference in molecular conformation leads to crystalline polymorphisms and dramatically distinct charge transport properties, based on which a high‐performance organic phase‐change memory transistor (OPCMT) is constructed. The OPCMT exhibits a quick programming/erasing rate (about 3 s), long retention time (more than 2 h), and large memory window (i.e., large threshold voltage shift over 30 V). This work presents a new molecule design concept for organic semiconductors with reversible molecular conformation transition and opens a novel avenue for memory devices and other functional applications. [ABSTRACT FROM AUTHOR]

Sb2Te thin films were deposited on SiO2/Si (100) substrates by magnetron sputtering. We investigated the crystallization behavior of Sb2Te thin films for phase-change memory applications. The experimental results show that the optical reflectivity is increased by more than 30% before and after crystallization. The resistance is decreased at least 102 orders of magnitude in the crystallization process, which suggests the application potential of Sb2Te thin film as optoelectronic storage material. The computational results show that the local crystallization activation energy is 1.72 eV and the crystal growth velocity is 4.96 m s−1, confirming the strong crystallization tendency of Sb2Te thin film. We examined the features of amorphous local bonding and found that the local octahedral geometry is the structural origin of optoelectronic contrast and crystallization tendency. Furthermore, the presence of weak Sb-Sb, Sb-Te, and Te-Te bonds and high mobility of Sb atoms facilitate the high-speed and low-activation-energy crystallization. Hence, we suggested that reducing the number of octahedrons and introducing the strong chemical bonds could promote stable optoelectronic memory applications of Sb2Te thin film. [ABSTRACT FROM AUTHOR]

Abstract Phase‐change semiconductor is one of the best candidates for designing nonvolatile memory, but it has never been realized in organic semiconductors until now. Here, a phase‐changeable and high‐mobility organic semiconductor (3,6‐DATT) is first synthesized. Benefiting from the introduction of electrostatic hydrogen bond (S···H), the molecular conformation of 3,6‐DATT crystals can be reversibly modulated by the electric field and ultraviolet irradiation. Through experimental and theoretical verification, the tiny difference in molecular conformation leads to crystalline polymorphisms and dramatically distinct charge transport properties, based on which a high‐performance organic phase‐change memory transistor (OPCMT) is constructed. The OPCMT exhibits a quick programming/erasing rate (about 3 s), long retention time (more than 2 h), and large memory window (i.e., large threshold voltage shift over 30 V). This work presents a new molecule design concept for organic semiconductors with reversible molecular conformation transition and opens a novel avenue for memory devices and other functional applications.

Cloud computing is one of the emerging technology; it provides various services like Software as a Service, Platform as a Service, and Infrastructure as a Service on demand. It reduces the cost of traditional computing by renting the resources instead of buying them for a huge cost. The usage of cloud resources is increasing day by day. Due to the heavy workload, all users cannot get uninterrupted service at some time. And the response time of some users also gets increased. Resource allocation is one of the primary issues of a cloud environment, one of the challenging problems is improving scheduling performance and reducing waiting time performance. In this research work, a new approach is proposed to distribute the heavy workload to overcome this problem. In addition to that, the resource allocation of dynamic user requests is also taken into study. The Max-Min scheduling algorithm is modified concerning Dynamic Phase Change Memory (DPCM), and the Hyper switching algorithm is implemented to speed up the resource allocation process. The proposed DPCM algorithm provides efficient performance, improves scheduling results, and minimizes the waiting time. In the experimentation analysis, it is observed that this proposed approach optimizes the response time and waiting time of the dynamic user requests and distributes the workloads effectively, compared with other existing approaches. So the performance of the resource allocation process is improved, which enhances the efficiency of the cloud system. [ABSTRACT FROM AUTHOR]

An access-transistor-free (0T1R) structure has been reported to have great advantages in reducing the area of the phase-change memory cell, but leakage current has limited its application in large-scale arrays. In this study, a GeTe/InP heterostructure is proposed as the integration of a selector and phase-change cell in a 0T1R structure. The effect of establishing a GeTe/InP heterostructure is explored based on first-principles study, and the performance is further optimized by doping. The results show that, compared with GeTe, the band gap value of the GeTe/InP heterostructure decreases, and the space charge region forms at the interface, which effectively suppresses the leakage current of the 0T1R structure. In addition, to further improve the performance of GeTe/InP, group III-V elements are used as substitutional dopants at the P site. We find that when N and B dopants are used, the electrical conductivity of GeTe/InP and the charge transfer between interfaces are enhanced. The current–voltage characteristic curves show that the establishment of the GeTe/InP heterostructure and doping significantly improved the nonlinear coefficient of the phase-change memory cell, which can better suppress the leakage current in the 0T1R structure. [ABSTRACT FROM AUTHOR]

Phase‐change memory (PCM) belongs to the nonvolatile solid‐state memory techniques. Usually, a chalcogenide is sandwiched between two conductive electrodes and data are stored by setting each cell to a low‐resistance (crystalline) or a high‐resistance (amorphous) state. Switching between these states is relatively fast, which makes phase‐change random access memories (PCRAMs) highly interesting for nonvolatile memories. Multilevel cells, which can store more than 1 bit per cell, and multilayer high‐density memory arrays have also been reported as advantages of PCRAM. Writing currents and data retention, on the other hand, still show potential for optimization. This review gives an overview of the most recent developments in new material compositions and material‐related optimization of PCM in comparison with already produced PCM. [ABSTRACT FROM AUTHOR]

Phase‐change memory is one of the most promising candidates for the next generation nonvolatile memory, but their high power consumption and low reliability remain bottleneck problems that limit the data storage density and its storage‐class memory application. Here, an innovative phase change material with embedded self‐precipitated interfaces, where the nanoscale grains of phase change material are cut into interconnecting "crystal islands" by thermally stable self‐precipitated material with low thermal conductivity, is proposed. The precipitated material provides both thermal and atomic migration confinements in three dimensions. The thermal confinement enables low power consumption, and the atomic migration confinement enables high device reliability. The devices based on spontaneously phase‐separated O‐doped Sb2Te3 verify the material design, where Sb oxide acts as the precipitated heterogeneous phase and Sb–Te alloy as the phase change material. O‐doped Sb2Te3 device with 250 nm hole diameter shows an ultralow power consumption, down to a few hundreds of femtojoule, which is comparable with those of phase change nanowires. Besides, good thermal stability and low resistivity drift (drift coefficient 0.005) as well as excellent cycle endurance up to 108 times are also obtained at the same time. The doping fabrication process is quite compatible with current semiconductor industry. [ABSTRACT FROM AUTHOR]

The physical properties and device electrical properties of superlattice-like C/Sb phase change films are investigated. Compared with Sb monolayer films, the superlattice-like C/Sb films have preferable thermal stability, including higher crystallization temperature, longer data life, and larger crystallization activation energy. As the thickness of the carbon layer increases, the band gap gradually increases. X-ray photoelectron spectroscopy results show that C-Sb bonds exist in the C/Sb superlattice-like films. X-ray diffraction and atomic force microscope results show that the addition of carbon inhibits the grain growth, making the grain size smaller and inhibiting the crystallization of Sb materials. Phase-change memory devices based on [C(6nm)/Sb(4nm)]8 superlattice-like films have smaller threshold voltages and lower power consumption compared to Sb films. In conclusion, C/Sb superlattice-like films have high thermal stability and low power consumption. [ABSTRACT FROM AUTHOR]

Phase-change memory (PCM) is a promising non-volatile memory device due to its attractive properties such as fast access time and byte-addressability. However, PCM is still difficult to be used as a main memory because of its weakness in endurance and write disturbance. Conventional wear-leveling algorithms have attempted to handle short endurance, but they have not addressed the issue of write disturbance even though both issues are caused by write operations to PCM. This paper proposes a wear-leveling algorithm that addresses not only the endurance, but also the write disturbance. From the observation that the write disturbance errors and short endurance issues mostly take place in hot addresses, the proposed algorithm first detects hot addresses and maps them to ‘hot’ regions, which are customized memory regions designed to be robust to write disturbance errors and to support effective wear-leveling. The ‘hot’ region is not fixed to a specific part, but it moves over an entire memory space to make every cell belong to ‘hot’ regions in a uniform manner. On the other hand, cold addresses are mapped in ‘normal’ memory regions by simple linear mapping to reduce the hardware overhead. The proposed algorithm can reduce the write disturbance errors by more than 70% with only a slight instruction per cycle (IPC) degradation. Moreover, the wear-leveling performance is also enhanced by more than 3% compared to other wear-leveling algorithms.

[GeTe] m -[Sb 2 Te 3 ] n superlattice (GST-SL) is a promising material candidate to solve the critical problem of high-power consumption for phase-change memory technology. However, the switching mechanism is still under strong debate during the last decade. A key controversial question is that whether melting in GST-SL is possible. In this work, a large-scale machine learning interatomic potential (MLIP) molecular dynamics (MD) simulation with a one-order-of-magnitude larger atom number than that of conventional density functional theory (DFT) MD captures a unique partial melting behavior in GST-SL, where a sparse-nucleation-and-growth governed melting behavior is triggered by the flipping of atoms into van der Waals (vdW) gaps and forming cation-in-vdW-gap (CiV) defect as starting point, and then is slowly developed via propagating liquid-crystalline interfaces. In great contrast, the traditional melting of rock salt (RS)-GST occurs very fast due to instant homogeneous nucleation from high-density intrinsic vacancies distributed randomly in its cubic lattice. Therefore, the melting regions in GST-SL can be spatially localized in form of partial melting and are readily controlled. Moreover, the atomic distribution after melting in GST-SL is more chemical ordering than that in RS-GST. By the large-scale MLIP-MD, the present study provides a critical atomic insight into GST-SL phase-change behaviors that conventional DFT-MDs hardly achieve. This partial-melting nature in GST-SL helps explain the long-term-confused working principle of GST-SL-based phase-change memory, which will accelerate its application in the big-data era. [Display omitted] [ABSTRACT FROM AUTHOR]

Multi-Level Cell Phase Change Memory (MLC PCM) is a non-volatile memory technology that promises high-density data storage. However, MLC PCM suffers from long write latency because changing the state of each memory cell takes a long time and the number of cells that can be written concurrently is limited due to the relatively large size and power consumption of the write drivers. MLC PCM typically divides the write data into multiple cell groups to program cells in batches. The group mapping has a significant impact on the overall latency of write requests. Prior work proposed a group mapping technique for single-level cell (SLC) PCM based on the data pattern of a set of applications. In this work, a larger design space of group mapping is explored for MLC PCM. The specific group mapping for each benchmark is dynamically customized. Our technique leads to a 13.14% reduction in write latency compared to the state-of-the-art method (Du et al., 2013) and shows good temporal consistence in different benchmarks.

Two‐terminal‐based artificial synapses have attracted attention because their electronic properties can be applied to next‐generation computing. Herein, interfacial phase‐change memory (iPCM) devices based on sputter‐grown GeTe/Sb2Te3 are fabricated. The iPCM device exhibits excellent multilevel resistance switching via control of entropy by restricting the movement of Ge atoms. Based on this movement, the optimal pulse scheme and GeTe/Sb2Te3 layer are used to implement a tunable analog weight update of artificial synapses. The nonlinearity of 0.32 and 40 conductance states (GeTe/Sb2Te3)16 iPCM is achieved for long‐term potentiation and depression, respectively. This artificial synapse, which stably changes the gradual conductance value, has the potential for significant performance improvement of neuromorphic computing. [ABSTRACT FROM AUTHOR]

Innovative nanocomposites consisting of [(GeTe)4 nm/C1 nm]10 multilayers (MLs) deposited by magnetron sputtering are integrated in phase‐change memory (PCM) test devices with a "wall structure." Scanning transmission electron microscopy (STEM) shows that an ML structure, with crystallized GeTe layers, is kept after integration in as‐fabricated devices and also after an additional annealing of the devices at 425 °C. The programming current (RESET current) required to reach the high resistance state of [(GeTe)4 nm/C1 nm]10 ML devices decreases by 45% after annealing at 425 °C. The reduction in RESET current is 55% and the reduction in drift coefficient is about 40% in ML devices annealed at 425 °C compared to similar devices incorporating Ge2Sb2Te5. STEM imaging, coupled with nano‐beam electron diffraction and electron energy loss spectroscopy, of ML devices in the high resistance state shows that the RESET current reduction after annealing is correlated to a reduction of the amorphized volume. [ABSTRACT FROM AUTHOR]

A fully silicon‐integrated restricted Boltzmann machine (RBM) with an event‐driven contrastive divergence (eCD) training algorithm is implemented using novel stochastic leaky integrate‐and‐fire (LIF) neuron circuits and six‐transistor/2‐PCM‐resistor (6T2R) synaptic unit cells on 90 nm CMOS technology. To elaborate, designed a bidirectional, asynchronous, and parallel pulse‐signaling scheme over an analog‐weighted phase‐change memory (PCM) synapse array to enable spike‐timing‐dependent plasticity (STDP) as a local weight update rule based on eCD is designed. Building upon the initial version of this work, significantly more experimental details are added, such as the on‐chip characterization results of LIF and backward‐LIF (BLIF) and stochasticity of our random walk circuitry. The experimental characterization of these on‐chip stochastic neuron circuits shows a reasonable symmetricity between LIF and BLIF as well as the necessary stochasticity for spiking RBM operation. Fully hardware‐based image classification recorded 93% on‐chip training accuracy from 100 handwritten MNIST digit images. In addition, we experimentally demonstrated the generative characteristics of the RBM by reconstructing partial patterns on hardware. As each synapse and neuron execute its computations in an asynchronous and fully parallel fashion, the chip can perform data‐intensive machine learning (ML) tasks in a power‐efficient manner and take advantage of the sparseness of spiking. [ABSTRACT FROM AUTHOR]

Abstract Phase‐change memory (PCM) has been developed for three‐dimensional (3D) data storage devices, posing huge challenges to the thermal stability and reliability of PCM. However, the low thermal stability of Ge2Sb2Te5 (GST) limits further application. Here, we demonstrate PCM based on In0.9Ge2Sb2Te5 (IGST) alloy, showing 180°C 10‐years data retention, 6 ns set speed, one order of magnitude longer life time, and 75% reduced power consumption compared to GST‐based device. The In can occupy the cationic positions and the In‐Te octahedrons with good phase‐change properties can geometrically match well with the host Ge‐Te and Sb‐Te octahedrons, acting as nucleation centers to boost the set speed and enhance the endurance of IGST device. Introducing stable matched phase‐change octahedrons can be a feasible way to achieve practical PCMs.

A fully silicon‐integrated restricted Boltzmann machine (RBM) with an event‐driven contrastive divergence (eCD) training algorithm is implemented using novel stochastic leaky integrate‐and‐fire (LIF) neuron circuits and six‐transistor/2‐PCM‐resistor (6T2R) synaptic unit cells on 90 nm CMOS technology. To elaborate, designed a bidirectional, asynchronous, and parallel pulse‐signaling scheme over an analog‐weighted phase‐change memory (PCM) synapse array to enable spike‐timing‐dependent plasticity (STDP) as a local weight update rule based on eCD is designed. Building upon the initial version of this work, significantly more experimental details are added, such as the on‐chip characterization results of LIF and backward‐LIF (BLIF) and stochasticity of our random walk circuitry. The experimental characterization of these on‐chip stochastic neuron circuits shows a reasonable symmetricity between LIF and BLIF as well as the necessary stochasticity for spiking RBM operation. Fully hardware‐based image classification recorded 93% on‐chip training accuracy from 100 handwritten MNIST digit images. In addition, we experimentally demonstrated the generative characteristics of the RBM by reconstructing partial patterns on hardware. As each synapse and neuron execute its computations in an asynchronous and fully parallel fashion, the chip can perform data‐intensive machine learning (ML) tasks in a power‐efficient manner and take advantage of the sparseness of spiking.

The recent development of three‐dimensional semiconductor integration technology demands a key component—the ovonic threshold switching (OTS) selector to suppress the current leakage in the high‐density memory chips. Yet, the unsatisfactory performance of existing OTS materials becomes the bottleneck of the industrial advancement. The sluggish development of OTS materials, which are usually made from chalcogenide glass, should be largely attributed to the insufficient understanding of the electronic structure in these materials, despite of intensive research in the past decade. Due to the heavy first‐principles computation on disordered systems, a universal theory to explain the origin of mid‐gap states (MGS), which are the key feature leading to the OTS behavior, is still lacking. To avoid the formidable computational tasks, we adopt machine learning method to understand and predict MGS in typical OTS materials. We build hundreds of chalcogenide glass models and collect major structural features from both short‐range order (SRO) and medium‐range order (MRO) of the amorphous cells. After training the artificial neural network using these features, the accuracy has reached ~95% when it recognizes MGS in new glass. By analyzing the synaptic weights of the input structural features, we discover that the bonding and coordination environments from SRO and particularly MRO are closely related to MGS. The trained model could be used in many other OTS chalcogenides after minor modification. The intelligent machine learning allows us to understand the OTS mechanism from vast amount of structural data without heavy computational tasks, providing a new strategy to design functional amorphous materials from first principles. [ABSTRACT FROM AUTHOR]

Abstract The recent development of three‐dimensional semiconductor integration technology demands a key component—the ovonic threshold switching (OTS) selector to suppress the current leakage in the high‐density memory chips. Yet, the unsatisfactory performance of existing OTS materials becomes the bottleneck of the industrial advancement. The sluggish development of OTS materials, which are usually made from chalcogenide glass, should be largely attributed to the insufficient understanding of the electronic structure in these materials, despite of intensive research in the past decade. Due to the heavy first‐principles computation on disordered systems, a universal theory to explain the origin of mid‐gap states (MGS), which are the key feature leading to the OTS behavior, is still lacking. To avoid the formidable computational tasks, we adopt machine learning method to understand and predict MGS in typical OTS materials. We build hundreds of chalcogenide glass models and collect major structural features from both short‐range order (SRO) and medium‐range order (MRO) of the amorphous cells. After training the artificial neural network using these features, the accuracy has reached ~95% when it recognizes MGS in new glass. By analyzing the synaptic weights of the input structural features, we discover that the bonding and coordination environments from SRO and particularly MRO are closely related to MGS. The trained model could be used in many other OTS chalcogenides after minor modification. The intelligent machine learning allows us to understand the OTS mechanism from vast amount of structural data without heavy computational tasks, providing a new strategy to design functional amorphous materials from first principles.

Abstract Phase-change memory (PCM) has considerable promise for new applications based on von Neumann and emerging neuromorphic computing systems. However, a key challenge in harnessing the advantages of PCM devices is achieving high-speed operation of these devices at elevated temperatures, which is critical for the efficient processing and reliable storage of data at full capacity. Herein, we report a novel PCM device based on Ta-doped antimony telluride (Sb2Te), which exhibits both high-speed characteristics and excellent high-temperature characteristics, with an operation speed of 2 ns, endurance of > 106 cycles, and reversible switching at 140 °C. The high coordination number of Ta and the strong bonds between Ta and Sb/Te atoms contribute to the robustness of the amorphous structure, which improves the thermal stability. Furthermore, the small grains in the three-dimensional limit lead to an increased energy efficiency and a reduced risk of layer segregation, reducing the power consumption and improving the long-term endurance. Our findings for this new Ta–Sb2Te material system can facilitate the development of PCMs with improved performance and novel applications.

Phase‐change material (PCM) devices are one of the most mature nonvolatile memories. However, their high power consumption remains a bottleneck problem limiting the data storage density. One may drastically reduce the programming power by patterning the PCM volume down to nanometer scale, but that route incurs a stiff penalty from the tremendous cost associated with the complex nanofabrication protocols required. Instead, here a materials solution to resolve this dilemma is offered. The authors work with memory cells of conventional dimensions, but design/exploit a PCM alloy that decomposes into a heterogeneous network of nanoscale crystalline domains intermixed with amorphous ones. The idea is to confine the subsequent phase‐change switching in the interface region of the crystalline nanodomain with its amorphous surrounding, forming/breaking "nano‐bridges" that link up the crystalline domains into a conductive path. This conductive‐bridge switching mechanism thus only involves nanometer‐scale volume in programming, despite of the large areas in contact with the electrodes. The pore‐like devices based on spontaneously phase‐separated Ge13Sb71O16 alloy enable a record‐low programming energy, down to a few tens of femtojoule. The new PCM/fabrication is fully compatible with the current 3D integration technology, adding no expenses or difficulty in processing. [ABSTRACT FROM AUTHOR]

For high-performance data centers, huge data transfer, reliable data storage and emerging in-memory computing require memory technology with the combination of accelerated access, large capacity and persistence. As for phase-change memory, the Sb-rich compounds Sb7Te3 and GeSb6Te have demonstrated fast switching speed and considerable difference of phase transition temperature. A multilayer structure is built up with the two compounds to reach three non-volatile resistance states. Sequential phase transition in a relationship with the temperature is confirmed to contribute to different resistance states with sufficient thermal stability. With the verification of nanoscale confinement for the integration of Sb7Te3/GeSb6Te multilayer thin film, T-shape PCM cells are fabricated and two SET operations are executed with 40 ns-width pulses, exhibiting good potential for the multi-level PCM candidate. [ABSTRACT FROM AUTHOR]

This research is to design an effective prefetching method required for hybrid main memory systems consisting of dynamic random-access memory (DRAM) and phase-change memory (PCM) components, which can be especially used for big data applications and massive-scale computing environment. Conventional prefetchers perform adequately for regular memory access patterns. However, graph processing applications show extremely irregular memory access characteristics, causing some difficulty in predicting accurate prefetching operation. Therefore, an effective dynamical prefetching algorithm based on the regression method is proposed in this study. We have designed an intelligent prefetch engine that can identify any dynamic accessing characteristics in memory accessing sequences. Specifically, it can select regular, linear, or polynomial regression predictive analysis based on the memory access sequence characteristics, and also dynamically determine the number of pages required for any selected prefetching. We also present a DRAM-PCM hybrid memory structure that can reduce the energy consumption and resolve the thermal issue that hampers conventional DRAM memory systems. Experimental results indicate that the performance can increase by around 40%, compared to that of conventional DRAM memory structures. [ABSTRACT FROM AUTHOR]

The dimensions of amorphized regions in phase-change memory cells are critical parameters to design devices for different applications. However, these dimensions are difficult to be determined by direct imaging. In this work, the length of amorphized regions in multiple identical Ge2Sb2Te5 (GST) line cells was extracted from electrical measurements. After each cell was programmed to an amorphous state, a sequence of increasing-amplitude post-reset voltage pulses separated by low-amplitude read DC sweeps was applied. When a post-reset voltage pulse with sufficient amplitude was applied to a given cell, the measured current and the post-pulse resistance increased drastically, indicating that the cell re-amorphized after threshold switching, melting, and quenching. The amorphized length was calculated using the measured voltage at which the threshold switching occurred and the expected drifted threshold field at that time. The measured threshold voltage values and, hence, the extracted amorphized length, generally increase linearly with the programmed resistance levels. However, significant variability arises from the intrinsically unique crystallization and amorphization processes in these devices. For example, cells programmed to an amorphous resistance of approx. 50 MΩ show threshold voltage values of 5.5–7.5 V, corresponding to amorphized length values of 290–395 nm. This unpredictable programming feature in phase-change memory devices can be utilized in hardware security applications.

Memristive crossbar arrays can be used to realize matrix-vector multiplication (MVM) operations in constant time complexity by exploiting the Kirchhoff’s circuit laws. This is enabled by the parallel read of the entire array in a single time step. However, parallel writing is prohibitive in such arrays due to limitations on the current that could be accumulated along the wires. Hence, loading the matrix elements into such an array still incurs significant time penalty. Another key challenge is the achievable computational precision. To overcome these challenges, we propose a unit-cell array design where each unit-cell comprises four memristive devices each attached to a selection transistor. Moreover, the array is organized in such a way that the selection transistors can be turned on in a diagonal fashion. We experimentally demonstrated this concept by fabricating a $2\times 2$ unit-cell array based on projected phase-change memory (PCM) devices in 90 nm CMOS technology. It is shown that using the diagonal connections, the write operations can be parallelized while maintaining the current limit of the back-end-of-the-line metallization. Moreover, the increase in write time due to having more devices per unit-cell is minimized through a combination of single-shot and iterative programming schemes. Finally, we present experimental results on MVM operations that demonstrate improved computational precision exceeding that of a 4-bit fixed-point implementation. [ABSTRACT FROM AUTHOR]

[Display omitted] By controlling the amorphous-to-crystalline relative volume, chalcogenide phase-change memory materials can provide multi-level data storage (MLS), which offers great potential for high-density storage-class memory and neuro-inspired computing. However, this type of MLS system suffers from high power consumption and a severe time-dependent resistance increase ("drift") in the amorphous phase, which limits the number of attainable storage levels. Here, we report a new type of MLS system in yttrium-doped antimony telluride, utilizing reversible multi-level phase transitions between three states, i.e., amorphous, metastable cubic and stable hexagonal crystalline phases, with ultralow power consumption (0.6–4.3 pJ) and ultralow resistance drift for the lower two states (power-law exponent < 0.007). The metastable cubic phase is stabilized by yttrium, while the evident reversible cubic-to-hexagonal transition is attributed to the sequential and directional migration of Sb atoms. Finally, the decreased heat dissipation of the material and the increase in crystallinity contribute to the overall high performance. This study opens a new way to achieve advanced multi-level phase-change memory without the need for complicated manufacturing procedures or iterative programming operations. [ABSTRACT FROM AUTHOR]

The pressing need for data storage in the era of big data has driven the development of new storage technologies. As a prominent contender for next-generation memory, phase-change memory can effectively increase storage density through multilevel cell operation and can be applied to neuromorphic and in-memory computing. Herein, the structure and properties of Ta-doped MnTe thin films and their inherent correlations are systematically investigated. Amorphous MnTe thin films sequentially precipitated cubic MnTe 2 and hexagonal Te phases with increasing temperature, causing resistance changes. Ta doping inhibited phase segregation in the films and improved their thermal stability in the amorphous state. A phase-change memory cell based on a Ta 2.8% -MnTe thin film exhibited three stable resistive states with low resistive drift coefficients. The study findings reveal the possibility of regulating the two-step phase-change process in Ta-MnTe thin films, providing insight into the design of multilevel phase-change memory.