Selective Passivation of GeO2/Ge Interface Defects in Atomic Layer Deposited High-k MOS Structures.

Effective passivation of interface defects in high-k metal oxide/Ge gate stacks is a longstanding goal of research on germanium metal-oxide-semiconductor devices. In this paper, we use photoelectron spectroscopy to probe the formation of a GeO2 interface layer between an atomic layer deposited Al2O3 gate dielectric and a Ge(100) substrate during forming gas anneal (FGA). Capacitance- and conductance-voltage data were used to extract the interface trap density energy distribution. These results show selective passivation of interface traps with energies in the top half of the Ge band gap under annealing conditions that produce GeO2 interface layer growth. First-principles modeling of Ge/GeO2 and Ge/GeO/GeO2 structures and calculations of the resulting partial density of states (PDOS) are in good agreement with the experiment results.This work was supported in part by the Stanford Initiative for Nanoscale Materials and Processes (INMP). This work was performed at the National Synchrotron Light Source and the Stanford Synchrotron Radiation Laboratory, which are supported by the US Department of Energy. Additional support was provided by the National Institute of Standards and Technology.This is the accepted manuscript. The final version is available at http://pubs.acs.org/doi/abs/10.1021/acsami.5b06087

A Marr's Three‐Level Analytical Framework for Neuromorphic Electronic Systems

Neuromorphic electronics, an emerging field that aims for building electronic mimics of the biological brain, holds promise for reshaping the frontiers of information technology and enabling a more intelligent and efficient computing paradigm. As their biological brain counterpart, the neuromorphic electronic systems are complex, having multiple levels of organization. Inspired by David Marr's famous three-level analytical framework developed for neuroscience, the advances in neuromorphic electronic systems are selectively surveyed and given significance to these research endeavors as appropriate from the computational level, algorithmic level, or implementation level. Under this framework, the problem of how to build a neuromorphic electronic system is defined in a tractable way. In conclusion, the development of neuromorphic electronic systems confronts a similar challenge to the one neuroscience confronts, that is, the limited constructability of the low-level knowledge (implementations and algorithms) to achieve high-level brain-like (human-level) computational functions. An opportunity arises from the communication among different levels and their codesign. Neuroscience lab-on-neuromorphic chip platforms offer additional opportunity for mutual benefit between the two disciplines

A new opportunity for the emerging tellurium semiconductor: making resistive switching devices

Abstract: The development of the resistive switching cross-point array as the next-generation platform for high-density storage, in-memory computing and neuromorphic computing heavily relies on the improvement of the two component devices, volatile selector and nonvolatile memory, which have distinct operating current requirements. The perennial current-volatility dilemma that has been widely faced in various device implementations remains a major bottleneck. Here, we show that the device based on electrochemically active, low-thermal conductivity and low-melting temperature semiconducting tellurium filament can solve this dilemma, being able to function as either selector or memory in respective desired current ranges. Furthermore, we demonstrate one-selector-one-resistor behavior in a tandem of two identical Te-based devices, indicating the potential of Te-based device as a universal array building block. These nonconventional phenomena can be understood from a combination of unique electrical-thermal properties in Te. Preliminary device optimization efforts also indicate large and unique design space for Te-based resistive switching devices

Structural changes during the switching transition of chalcogenide selector devices

Ovonic threshold switches are a favored choice for chalcogenide-based amorphous (a-) GeSex selector devices used in cross-point arrays of nonvolatile memories. Previous models of their nonlinear high-field conduction proposed a largely electronic-only switching mechanism, within a fixed density of electronic states. Here, we use a density functional molecular-dynamics supercell calculation to show that the high-current excited state configuration of a-GeSex has structural changes such as additional Ge-Ge bonds and overcoordinated Ge sites, giving lower effective mass, more delocalized conduction states, and a lower ON resistance.We acknowledge the funding from the EC H2020 project Phase change switch