Ab-initio Modeling of CBRAM Cells: from Ballistic Transport Properties to Electro-Thermal Effects

We present atomistic simulations of conductive bridging random access memory (CBRAM) cells from first-principles combining density-functional theory and the Non-equilibrium Green's Function formalism. Realistic device structures with an atomic-scale filament connecting two metallic contacts have been constructed. Their transport properties have been studied in the ballistic limit and in the presence of electron-phonon scattering, showing good agreement with experimental data. It has been found that the relocation of few atoms is sufficient to change the resistance of the CBRAM by 6 orders of magnitude, that the electron trajectories strongly depend on the filament morphology, and that self-heating does not affect the device performance at currents below 1 $\mu$A.Comment: 6 figures, conferenc

CP2K: An electronic structure and molecular dynamics software package - Quickstep: Efficient and accurate electronic structure calculations

CP2K is an open source electronic structure and molecular dynamics software package to perform atomistic simulations of solid-state, liquid, molecular, and biological systems. It is especially aimed at massively parallel and linear-scaling electronic structure methods and state-of-the-art ab initio molecular dynamics simulations. Excellent performance for electronic structure calculations is achieved using novel algorithms implemented for modern high-performance computing systems. This review revisits the main capabilities of CP2K to perform efficient and accurate electronic structure simulations. The emphasis is put on density functional theory and multiple post–Hartree–Fock methods using the Gaussian and plane wave approach and its augmented all-electron extension

Investigation of the Electrode Materials in Conductive Bridging RAM from First-Principle

Conductive bridging random access memories (CBRAM) are emerging non-volatile data storage devices whose switching mechanisms are not fully understood. Here, we present a modelling framework based on ab-initio simulations to investigate CBRAM cells. It combines density-functional theory and the Non-equilibrium Greens Function formalism. Realistic metallic filaments connecting two electrodes are constructed and their ballistic transport characteristics studied. For a given filament the type of counter electrode material has little influence on the magnitude of the ON-state current, but affects its spatial distribution. The conductance mainly depends on the material of the active electrode and the shape of the thinnest part of the filament

Combining linear-scaling DFT with subsystem DFT in born-oppenheimer and ehrenfest molecular dynamics simulations: From molecules to a virus in solution

In this work, methods for the efficient simulation of large systems embedded in a molecular environment are presented. These methods combine linear-scaling (LS) Kohn–Sham (KS) density functional theory (DFT) with subsystem (SS) DFT. LS DFT is efficient for large subsystems, while SS DFT is linear scaling with a smaller prefactor for large sets of small molecules. The combination of SS and LS, which is an embedding approach, can result in a 10-fold speedup over a pure LS simulation for large systems in aqueous solution. In addition to a ground-state Born–Oppenheimer SS+LS implementation, a time-dependent density functional theory-based Ehrenfest molecular dynamics (EMD) using density matrix propagation is presented that allows for performing nonadiabatic dynamics. Density matrix-based EMD in the SS framework is naturally linear scaling and appears suitable to study the electronic dynamics of molecules in solution. In the LS framework, linear scaling results as long as the density matrix remains sparse during time propagation. However, we generally find a less than exponential decay of the density matrix after a sufficiently long EMD run, preventing LS EMD simulations with arbitrary accuracy. The methods are tested on various systems, including spectroscopy on dyes, the electronic structure of TiO₂ nanoparticles, electronic transport in carbon nanotubes, and the satellite tobacco mosaic virus in explicit solution

Microcanonical RT-TDDFT simulations of realistically extended devices

ISSN:0021-9606ISSN:1089-769

Ultra compact electrochemical metallization cells offering reproducible atomic scale memristive switching

Here we show electrochemical metallization cells with compact dimensions, excellent electrical performance, and reproducible characteristics. An advanced technology platform has been developed to obtain Ag/SiO2/Pt devices with ultra-scaled footprints (15 × 15 nm2), inter-electrode distances down to 1 nm, and a transition from the OFF to ON resistance state relying on the relocation of only few atoms. This technology permits a well-controlled metallic filament formation in a highly confined field at the apex of an atomic scale tip. As a consequence of this miniaturization process, we achieve set voltages around 100 mV, ultra-fast switching times of 7.5 ns, and write energies of 18 fJ. Furthermore, we demonstrate very good cell-to-cell uniformity and a resistance extinction ratio as high as 6 · 105. Combined ab-initio quantum transport simulations and experiments suggest that the manufactured structures exhibit reduced self-heating effects due to their lower dimensions, making them very promising candidates as next-generation (non-)volatile memory components

Charge transport in semiconductors assembled from nanocrystal quantum dots

The potential of semiconductors assembled from nanocrystals has been demonstrated for a broad array of electronic and optoelectronic devices, including transistors, light emitting diodes, solar cells, photodetectors, thermoelectrics, and phase change memory cells. Despite the commercial success of nanocrystal quantum dots as optical absorbers and emitters, applications involving charge transport through nanocrystal semiconductors have eluded exploitation due to the inability to predictively control their electronic properties. Here, we perform large-scale, ab initio simulations to understand carrier transport, generation, and trapping in strongly confined nanocrystal quantum dot-based semiconductors from first principles. We use these findings to build a predictive model for charge transport in these materials, which we validate experimentally. Our insights provide a path for systematic engineering of these semiconductors, which in fact offer previously unexplored opportunities for tunability not achievable in other semiconductor systems.ISSN:2041-172