Fractal Description of Electron Scattering in Solids: Several New Results and a Simple Modelization of the Fractal Dimension

The fractal behaviour of electron scattering in solids is studied with electron trajectories simulated by Monte Carlo simulations. More precisely, the Hausdorff-Besicovitch dimension is determined for several electrons trajectories simulated in solids of different compositions. Then, a simple model to compute the fractal dimension of electron trajectories in solids is presented, a model which raises a question concerning the maximum value of the backscattering coefficient. Results of Monte Carlo simulations of electron trajectories in several elements with total randomness for the polar and azimuthal angles of scattering are presented as a tentative answer to this question. Finally, the multi fractal behaviour of the energy distribution of backscattered electrons is presented

Direct-write electron beam lithography in silicon dioxide at low energy

Abstract : Electron beam lithography in silicon dioxide has been investigated with energies ranging from 0.5 up to 6 keV. The etch ratio of SiO2SiO2 has been studied and interpreted with regard to the limited penetration of electrons at such low energies. Monte Carlo simulations have been carried out to investigate the depth of penetration and the density of energy absorbed by SiO2SiO2. The etch ratio is also shown to depend on the dilution of the developer (a buffered hydrofluoric acid diluted in water). Finally, a possible application of low energy direct writing in silicon dioxide is described for the control of damascene processes, enabling the fabrication of nanodevices embedded in an insulator

Organization of silicon nanocrystals by localized electrochemical etching

Abstract : An approach to form a monolayer of organized silicon nanocrystals on a monocrystalline Si wafer is reported. Ordered arrays of nanoholes in a silicon nitride layer were obtained by combining electron beam lithography and plasma etching. Then, a short electrochemical etching current pulse led to formation of a single Si nanocrystal per each nanohole. As a result, high quality silicon nanocrystal arrays were formed with well controlled and reproducible morphologies. In future, this approach can be used to fabricate single electron devices

Spectroscopic ellipsometry on thin titanium oxide layers grown on titanium by plasma oxidation

Abstract : Electronic devices based on tunnel junctions require tools able to accurately control the thickness of thin metal and oxide layers on the order of the nanometer. This article shows that multisample ellipsometry is an accurate method to reach this goal on plain uniform layers, in particular for titanium. From these measurements, the authors carefully studied the oxidation rate of titanium thin films in an oxygen plasma. The authors found that the oxide thickness saturates at 5.4±0.4 nm5.4±0.4 nm after 10 min in the plasma with an ion acceleration power of 30 W. Increasing this power to 240 W increases the saturation value to 7.6±0.4 nm7.6±0.4 nm. An x-ray photoelectron spectroscopy study of the oxide has shown that the oxide created by O2O2 plasma is stoichiometric (TiO2)(TiO2). The developed model was also used to measure the thicknesses of titanium and titanium oxide layers that have been polished using a chemical mechanical planarization process and a material removal rate of 5.9 nm/min is found with our planarization parameters. I. INTRODUCTIO

Silicon nitride nanotemplate fabrication using inductively coupled plasma etching process

Abstract : In this work, we have investigated the fabrication of ordered silicon nitride nanohole arrays as part of an overall process aimed at producing organized silicon nanocrystals. The authors have demonstrated that it is possible to use inductively coupled plasma etching systems in order to etch nanometric layers, despite the fact that these systems are designed for deep and fast etching. A stable process is developed for shallow etching of silicon nitride nanoholes. The influence of different plasma etching parameters on silicon nitride nanohole properties is analyzed. 30 nm deep nanoholes of approximately 30 nm diameter, near vertical sidewalls and a good control of the selectivity are achieved. The overall process provides a simple and reproducible approach based on shallow inductively coupled plasma etching to obtain high quality nanosized silicon nitride templates. A suitable process for organized arrays of 10 nm diameter silicon nanocrystals realized by electrochemical etching is shown

Resistless electron beam lithography process for the fabrication of sub-50 nm silicide structures

We report on a study of the fabrication of submicron silicide structures with a resistless lithography technique. Several different metals can be used as a basis for producing silicide using this method; in this work, results will be discussed for both platinum and nickel silicide. The feasibility of producing nanostructures using polycrystalline silicon as a base growth layer for metal–oxide– semiconductor, and other device applications have also been demonstrated. Threshold doses for this method for submicron lines (<50 nm) and square areas were obtained in order to establish a framework for the fabrication of more complex devices. Preliminary electrical measurements were carried out which indicate that the resistivity of the silicide is 45 [mu omega] cm, and that the barrier height of the silicide/(high resistivity silicon) interface is 0.56 eV

Conductive filament evolution dynamics revealed by cryogenic (1.5 K) multilevel switching of CMOS-compatible Al2O3/TiO2 resistive memories

This study demonstrates multilevel switching at 1.5 K of Al2O3/TiO2-x resistive memory devices fabricated with CMOS-compatible processes and materials. The I-V characteristics exhibit a negative differential resistance (NDR) effect due to a Joule-heating-induced metal-insulator transition of the Ti4O7 conductive filament. Carrier transport analysis of all multilevel switching I-V curves show that while the insulating regime follows the space charge limited current (SCLC) model for all resistance states, the conduction in the metallic regime is dominated by SCLC and trap-assisted tunneling (TAT) for low- and high-resistance states respectively. A non-monotonic conductance evolution is observed in the insulating regime, as opposed to the continuous and gradual conductance increase and decrease obtained in the metallic regime during the multilevel SET and RESET operations. Cryogenic transport analysis coupled to an analytical model accounting for the metal-insulator-transition-induced NDR effects and the resistance states of the device provide new insights on the conductive filament evolution dynamics and resistive switching mechanisms. Our findings suggest that the non-monotonic conductance evolution in the insulating regime is due to the combined effects of longitudinal and radial variations of the Ti4O7 conductive filament during the switching. This behavior results from the interplay between temperature- and field-dependent geometrical and physical characteristics of the filament.Comment: 8 pages, 4 figure

Signals to Spikes for Neuromorphic Regulated Reservoir Computing and EMG Hand Gesture Recognition

Surface electromyogram (sEMG) signals result from muscle movement and hence they are an ideal candidate for benchmarking event-driven sensing and computing. We propose a simple yet novel approach for optimizing the spike encoding algorithm's hyper-parameters inspired by the readout layer concept in reservoir computing. Using a simple machine learning algorithm after spike encoding, we report performance higher than the state-of-the-art spiking neural networks on two open-source datasets for hand gesture recognition. The spike encoded data is processed through a spiking reservoir with a biologically inspired topology and neuron model. When trained with the unsupervised activity regulation CRITICAL algorithm to operate at the edge of chaos, the reservoir yields better performance than state-of-the-art convolutional neural networks. The reservoir performance with regulated activity was found to be 89.72% for the Roshambo EMG dataset and 70.6% for the EMG subset of sensor fusion dataset. Therefore, the biologically-inspired computing paradigm, which is known for being power efficient, also proves to have a great potential when compared with conventional AI algorithms.Comment: Accepted to International Conference on Neuromorphic Systems (ICONS 2021