Amorphous GaOx based charge trap memory device for neuromorphic applications

In this work, we demonstrate a 3-terminal field-effect based charge trap memory device with an amorphous-GaOx (a-GaOx) layer fabricated at a low deposition temperature of 250°C. Utilizing the long life-time traps in the a-GaOx/Al2O3 stack, we study the charge trap memory effect in the field effect devices. We observe more than one order of magnitude in channel current difference for two memory states with a retention of more than 102 s and endurance of 100 cycles. Our work paves a way for embedded a-GaOx memories for neuromorphic applications

Cycling Waveform Dependent Wake-Up and ON/OFF Ratio in Al2O3/Hf0.5Zr0.5O2 Ferroelectric Tunnel Junction Devices

The wake-up behavior and ON/OFF current ratio of TiN–Al2O3–Hf0.5Zr0.5O2–W ferroelectric tunnel junction (FTJ) devices were investigated for different wake-up voltage waveforms. We studied triangular and square waves, as well as square pulse trains of equal or unequal voltage amplitudes for positive and negative polarities. We find that the wake-up behavior in these FTJ stacks is highly influenced by the field cycling waveform. A square waveform is observed to provide wake-up with the lowest number of cycles, concomitantly resulting in higher remnant polarization and a higher ON/OFF ratio in the devices, compared to a triangular waveform. We further show that wake-up is dependent on the number of cycles rather than the total time of the applied electric field during cycling. We also demonstrate that different voltage magnitudes are necessary for positive and negative polarities during field cycling for efficient wake-up. Utilizing an optimized waveform with unequal magnitudes for the two polarities during field cycling, we achieve a reduction in wake-up cycles and a large enhancement of the ON/OFF ratio from ∼5 to ∼35 in our ferroelectric tunnel junctions

Insights on the variability of Cu filament formation in the SiO2 electrolyte of quantized-conductance conductive bridge random access memory devices

Conductive bridge random access memory devices such as Cu/SiO2/W are promising candidates for applications in neuromorphic computing due to their fast, low-voltage switching, multiple-conductance states, scalability, low off-current, and full compatibility with advanced Si CMOS technologies. The conductance states, which can be quantized, originate from the formation of a Cu filament in the SiO2 electrolyte due to cation-migration-based electrochemical processes. A major challenge related to the filamentary nature is the strong variability of the voltage required to switch the device to its conducting state. Here, based on a statistical analysis of more than hundred fifty Cu/SiO2/W devices, we point to the key role of the activation energy distribution for copper ion diffusion in the amorphous SiO2. The cycle-to-cycle variability is modeled well when considering the theoretical energy landscape for Cu diffusion paths to grow the filament. Perspectives of this work point to developing strategies to narrow the distribution of activation energies in amorphous SiO2

A fully automatized method for the unambiguous wavelength-by-wavelength determination of the thickness and optical property of a very thin film with a transparent range

Spectroscopic ellipsometry is a powerful method with high surface sensitivity that can be used to monitor the growth of even sub-monolayer film. However, the analysis of ultrathin films is complicated by the correlation of the dielectric constant and the thickness. This problem is usually resolved by fixing one or the other value, limiting the information that can be extracted. Here, we propose a method to determine unambiguously the refractive index, extinction coefficient and thickness of a film when a transparent range is available in the energy range investigated. We decompose the analysis in three steps. First, the thickness of the film is determined from the transparent range of the film. Then, knowing the thickness of the layer, an initial estimation of the refractive index and extinction coefficient is made based on a first-order Taylor expansion of the ellipsometric ratio. Finally, using this estimation, a numerical regression is done to ensure the convergence of the fit towards the solution. A theoretical example of the method is given for two different thicknesses of TiO2 films. Finally, the method is applied to the experimental data measured during the atomic layer deposition of a thin film of Hf0.5Zr0.5O2 grown on Si. The thickness, refractive index and extinction coefficient are retrieved with a high precision in the energy range of 3.5 - 6.5 eV. A detailed analysis is presented on the accuracy of the retrieved values and their dependency on random and systematic errors for different energy ranges

A fully automatized method for the unambiguous wavelength-by-wavelength determination of the thickness and optical property of a very thin film with a transparent range

Spectroscopic ellipsometry is a powerful method with high surface sensitivity that can be used to monitor the growth of even sub-monolayer films. However, analysis of ultrathin films is complicated by the correlation between the dielectric constant and thickness. This problem is usually resolved by fixing one or the other value, limiting the information that can be extracted. Here, we propose a method to determine unambiguously the refractive index, extinction coefficient, and thickness of a film when a transparent range is available in the energy range investigated. We decompose the analysis in three steps. First, the thickness of the film is determined from the transparent range of the film. Then, knowing the thickness of the layer, an initial estimation of the refractive index and extinction coefficient is made based on a first-order Taylor expansion of the ellipsometric ratio. Finally, using this estimation, a numerical iteration is done to ensure convergence of the fit toward the solution. A theoretical example of the method is given for two different thicknesses of TiO2 films. Finally, the method is applied to the experimental data measured during the atomic layer deposition of a thin film of Hf0.5Zr0.5O2 grown on Si. The thickness, refractive index, and extinction coefficient are retrieved with high precision (respectively, 0.01 and 0.002) in the energy range of 3.5–6.5 eV. A detailed analysis is presented on the accuracy of the retrieved values and their dependency on random and systematic errors for different energy ranges

A Ferroelectric Tunnel Junction-based Integrate-and-Fire Neuron

Event-based neuromorphic systems provide a low-power solution by using artificial neurons and synapses to process data asynchronously in the form of spikes. Ferroelectric Tunnel Junctions (FTJs) are ultra low-power memory devices and are well-suited to be integrated in these systems. Here, we present a hybrid FTJ-CMOS Integrate-and-Fire neuron which constitutes a fundamental building block for new-generation neuromorphic networks for edge computing. We demonstrate electrically tunable neural dynamics achievable by tuning the switching of the FTJ device

Nature of Nitrogen Incorporation in BiVO4 Photoanodes through Chemical and Physical Methods

In recent years, BiVO4 has been optimized as a photoanode material to produce photocurrent densities close to its theoretical maximum under AM1.5 solar illumination. Its performance is, therefore, limited by its 2.4 eV bandgap. Herein, nitrogen is incorporated into BiVO4 to shift the valence band position to higher energies and thereby decreases the bandgap. Two different approaches are investigated: modification of the precursors for the spray pyrolysis recipe and post-deposition nitrogen ion implantation. Both methods result in a slight red shift of the BiVO4 bandgap and optical absorption onset. Although previous reports on N-modified BiVO4 assumed individual nitrogen atoms to substitute for oxygen, X-ray photoelectron spectroscopy on the samples reveals the presence of molecular nitrogen (i.e., N-2). Density functional theory calculations confirm the thermodynamic stability of the incorporation and reveal that N-2 coordinates to two vanadium atoms in a bridging configuration. Unfortunately, nitrogen incorporation also results in the formation of a localized state of approximate to 0.1 eV below the conduction band minimum of BiVO4, which suppresses the photoactivity at longer wavelengths. These findings provide important new insights on the nature of nitrogen incorporation into BiVO4 and illustrate the need to find alternative lower-bandgap absorber materials for photoelectrochemical energy conversion applications

The Electrode-Ferroelectric Interface as the Primary Constraint on Endurance and Retention in HZO-Based Ferroelectric Capacitors

Ferroelectric hafnium-zirconium oxide is one of the most relevant CMOS-compatible materials for next-generation, non-volatile memory devices. Nevertheless, performance reliability remains an issue. With TiN electrodes (the most reported electrode material), Hf-Zr-based ferroelectric capacitors struggle to provide reliable retention due to electrode-ferroelectric interface interactions. Although Hf-Zr-based ferroelectric capacitors are fabricated with other electrodes, the focus is predominantly directed toward obtaining a large ferroelectric response. The impact of the electrodes on data retention for these ferroelectrics remains underreported and greater insight is needed to improve device reliability. Here, a comprehensive set of electrodes are evaluated with emphasis on the core ferroelectric memory reliability metrics of endurance, retention, and imprint. Metal-ferroelectric-metal capacitors comprised of a Hf0.5Zr0.5O2 layer deposited between different combinations of nitride (TiN, TiAlN, and NbN), pure metal (W), and oxide (MoO2, RuO2, and IrO2) top and bottom electrodes are fabricated for the investigation. From the electrical, physical, and structural analysis, the low reactivity of the electrode with the ferroelectric is found to be key for improved reliability of the ferroelectric capacitor. This understanding of interface properties provides necessary insight for the broad implementation of Hf-Zr-based ferroelectrics in memory technology and, overall, boosts the development of next-generation memories

Roadmap on ferroelectric hafnia- and zirconia-based materials and devices

Ferroelectric hafnium and zirconium oxides have undergone rapid scientific development over the last decade, pushing them to the forefront of ultralow-power electronic systems. Maximizing the potential application in memory devices or supercapacitors of these materials requires a combined effort by the scientific community to address technical limitations, which still hinder their application. Besides their favorable intrinsic material properties, HfO2–ZrO2 materials face challenges regarding their endurance, retention, wake-up effect, and high switching voltages. In this Roadmap, we intend to combine the expertise of chemistry, physics, material, and device engineers from leading experts in the ferroelectrics research community to set the direction of travel for these binary ferroelectric oxides. Here, we present a comprehensive overview of the current state of the art and offer readers an informed perspective of where this field is heading, what challenges need to be addressed, and possible applications and prospects for further development

Monolithic integration of functional oxides on semiconductors

16-18 Mars 2015International audienceno abstrac