Monte Carlo simulations have been widely used by microscopists for the last few decades. In the beginning it was a tedious and slow process, requiring a high level of computer skills from users and long computational times. Recent progress in the microelectronics industry now provides researchers with affordable desktop computers with clock rates greater than 3 GHz. With this type of computing power routinely available, Monte Carlo simulation is no longer an exclusive or long (overnight) process. The aim of this paper is to present a new user‐friendly simulation program based on the earlier CASINO Monte Carlo program. The intent of this software is to assist scanning electron microscope users in interpretation of imaging and microanalysis and also with more advanced procedures including electron‐beam lithography. This version uses a new architecture that provides results twice as quickly. This program is freely available to the scientific community and can be downloaded from the website: www.gel.usherb.ca/casino. SCANNING 29: 000‐000, 2007.

Monte Carlo softwares are widely used to understand the capabilities of electron microscopes. To study more realistic applications with complex samples, 3D Monte Carlo softwares are needed. In this article, the development of the 3D version of CASINO is presented. The software feature a graphical user interface, an efficient (in relation to simulation time and memory use) 3D simulation model, accurate physic models for electron microscopy applications, and it is available freely to the scientific community at this website:www.gel.usherbrooke.ca/casino/index.html. It can be used to model backscattered, secondary, and transmitted electron signals as well as absorbed energy. The software features like scan points and shot noise allow the simulation and study of realistic experimental conditions. This software has an improved energy range for scanning electron microscopy and scanning transmission electron microscopy applications. SCANNING 33:135–146, 2011.

Silicon co-integration offers compelling scaleup opportunities for quantum computing. In this framework, cryogenic temperature is required for the coherence of solid-state quantum devices. This study reports the characterization of an N-MOS quantum-dot dedicated structure below 100 mK. The device under test is built in thin silicon film fabricated with 28 nm high-k metal gate ultra-thin body and ultra-thin buried oxide (UTBB) advanced CMOS technology. The MOS structure is functional with improved performances at cryogenic temperature. The results open new research avenues in CMOS co-integration for quantum computing applications within the FD-SOI platform.

Neural networks are powerful tools for solving complex problems, but finding the right network topology for a given task remains an open question. Biology uses neurogenesis and structural plasticity to solve this problem. Advanced neural network algorithms are mostly relying on synaptic plasticity and learning. The main limitation in reconciling these two approaches is the lack of a viable hardware solution that could reproduce the bottom-up development of biological neural networks. Here, we show how the dendritic growth of PEDOT:PSS-based fibers through AC electropolymerization can implement structural plasticity during network development. We find that this strategy follows Hebbian principles and is able to define topologies that leverage better computing performances with sparse synaptic connectivity for solving non-trivial tasks. This approach is validated in software simulation, and offers up to 61% better network sparsity on classification and 50% in signal reconstruction tasks.

Resistive switching and transport mechanisms of Al₂O₃/TiO_2−x memristor crosspoint devices have been investigated at cryogenic temperatures down to 1.5 K, for the future development of memristor-based cryogenic electronics. We report successful resistive switching of our devices in the temperature range of 300–1.5 K. The current–voltage curves exhibit negative differential resistance effects between 130 K and 1.5 K, attributed to a metal–insulator transition of the Ti₄O₇ conductive filament. The resulting highly nonlinear behavior is associated with an I_ON/I_OFF diode ratio of 84 at 1.5 K, paving the way for selector-free cryogenic passive crossbars. Temperature-dependent thermal activation energies related to the conductance at low bias (20 mV) are extracted for memristors in a low resistance state, suggesting hopping-type conduction mechanisms. Finally, the transport mechanism analysis at 1.5 K indicates that for all resistance states, the conduction follows the space-charge limited current model in low fields, whereas trap-assisted tunneling dominates in higher fields.