Andrea Redaelli

Reliability study of phase-change nonvolatile memories

A detailed investigation of the reliability aspects in nonvolatile phase-change memories (PCM) is presented, covering the basic aspects related to high density array NVM, i.e., data retention, endurance, program and read disturbs. The data retention capabilities and the endurance characteristics of single PCM cells are analyzed, showing that data can be stored for 10 years at 110/spl deg/C and that a resistance difference of two order of magnitude between the cell states can be maintained for more than 10/sup 11/ programming cycles. The main mechanisms responsible for instabilities just before failure as well as for final device breakdown are also discussed. Finally, the impact of read and program disturbs are clearly assessed, showing with experimental data and simulated results that the crystallization induced during the cell read out and the thermal cross-talk due to adjacent bits programming do not affect the retention capabilities of the PCM cells.

Electronic switching effect and phase-change transition in chalcogenide materials

The threshold switching mechanism in amorphous chalcogenides is investigated, showing experimental data that once and for all demonstrate its electronic nature. The physical mechanisms responsible for the switching to the highly conductive state are discussed and the impact of cumulative read-out pulses is also investigated, showing that phase-change transitions induced by usual reading operations in phase-change memory cells are completely negligible.

Electrothermal and phase-change dynamics in chalcogenide-based memories

We analyzed the programming dynamics in phase-change memory (PCM) cells. The chalcogenide phase-change mechanism and phase distribution in the programmed cell is studied by both experiments and a numerical model, which self-consistently addresses the electrical-thermal conduction phase transition. We show that the reset-set transition is strongly coupled to the electronic switching in the amorphous phase, thus supporting the need for a self-consistent electrothermal-phase transition model to correctly account for all experimental evidences.

Threshold switching and phase transition numerical models for phase change memory simulations

A comprehensive numerical model for chalcogenide glasses is presented, coupling a physically based electrical model able to reproduce the threshold switching with a local nucleation and growth algorithm to account for the phase transition dynamics. The main ingredients of the chalcogenide physics are reviewed and analyzed through simplified analytical models, providing a deeper insight on the origin of the threshold switching mechanism in chalcogenide glasses. A semiconductorlike three-dimensional full-coupled numerical implementation of the proposed model is finally presented and its capabilities to quantitatively reproduce the key elements of the Ge2Sb2Te5 chalcogenide physics are demonstrated in the framework of phase change memory device simulations.

Modeling of Programming and Read Performance in Phase-Change Memories—Part I: Cell Optimization and Scaling

One of the major concerns for the feasibility of phase-change memories is the reduction of the programming current. To this aim, several efforts have been dedicated both on cell geometry and on material engineering. This paper addresses programming-current minimization by the optimization of the cell geometry and materials, programming-current scaling, and the tradeoff between programming and readout performances of the cell. A general procedure to find the optimum-cell geometry is proposed and applied to a prototype vertical cell. Then, the evolution of program and read performances through technology nodes is analyzed by numerical simulations with the aid of an analytical model, for both the isotropic- and nonisotropic-scaling approaches. The two scaling approaches are discussed and compared in terms of program and read cell performances. Finally, material optimization is considered for further program-read improvement.

Intrinsic Data Retention in Nanoscaled Phase-Change Memories—Part I: Monte Carlo Model for Crystallization and Percolation

The amorphous phase of chalcogenide material in phase-change memories (PCMs) is subjected to spontaneous and thermal-activated crystallization. This represents a critical reliability issue and has to be carefully investigated and modeled for physically based projection of retention failure up to ten years. A new three-dimensional percolation model describing the statistical crystallization behavior in an intrinsic PCM cell for the amorphous state is developed. With this physical model, the authors were able to calculate the resistance evolution with time in the cell and the statistical distribution of retention failure times in a cell array. From the impact of geometrical parameters on the cell retention performance, PCM design guidelines to minimize data-loss effects can be obtained. The model allows the evaluation of nucleation and growth parameters and statistical extrapolations of intrinsic retention failure, which is shown in part 2

Intrinsic Data Retention in Nanoscaled Phase-Change Memories—Part II: Statistical Analysis and Prediction of Failure Time

The statistical spread of intrinsic data retention times in phase-change memory (PCM) cells is studied. Based on the crystallization and percolation model described in part 1, the crystalline grain size in the amorphous volume after data loss is extracted. From the temperature dependence of grain size, the authors calculate the statistical shape factor for the distribution of failure times, allowing a statistical prediction of data retention in PCM large arrays. The scaling and optimization issues with respect to failure time statistical spread are finally addressed

Modeling of Programming and Read Performance in Phase-Change Memories—Part II: Program Disturb and Mixed-Scaling Approach

The scaling analysis of phase-change memory (PCM) cells is an essential step toward validation as a competitive technology in terms of array density and current consumption. While the current scaling has been addressed in a companion paper, we focus here on the thermal crosstalk, namely, the temperature increase in 1 bit in the array while an adjacent cell is being programmed by a high-current reset pulse. This parasitic heating may lead to partial crystallization in the amorphous phase and to a consequent resistance decrease after cycling. Our analysis shows that the thermal crosstalk strongly depends on the scaling approach used, e.g., isotropic or nonisotropic scaling. A new mixed-scaling option for PCM cells is proposed, which provides the maximum decrease of programming current compatible with the reliability requirements deriving from the thermal crosstalk. The effects of this new scaling approach on the programmed volume and data retention are finally addressed.

A Phase Change Memory Compact Model for Multilevel Applications

In this letter, we show a compact model that describes the main electrical features of phase change memory (PCM) devices. The model coherently reproduces the behavior of both SET and RESET states with the description of the physics of involved phenomena for different bias and temperature conditions. For arbitrary programming pulses, the model is able to generate intermediate states with mixed phase distributions and, thus, with resistance values between the SET and RESET ones. The proposed model is therefore a precious tool for the design of multilevel PCM applications.

Experimental investigation of transport properties in chalcogenide materials through 1∕f noise measurements

Low-frequency noise spectral density in chalcogenide-based phase-change memory cells has been measured, discussing the role of trapping centers and static disorder as responsible for a noise level in the vitreous insulating state two orders of magnitude higher than in the ordered conducting polycrystalline one. The magnitude of 1∕f noise has been also studied as a function of the applied voltage and exploited to experimentally investigate the transport mechanisms in chalcogenide alloys, showing that the exponential increase of noise spectral density with voltage can be quantitatively explained by considering an avalanchelike multiplication phenomenon.