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The non-ideal characteristics at the interfaces of anti-ferroelectric (AFE) film and electrodes will greatly affect the potential performance in the way to embedded dynamic random-access memory applications. In this paper, we have proposed a high-performance AFE TiN/HfxZr1−xO2/TiN capacitor fabricated by fully atomic layer deposition grown and alcohol-thermal high-pressure annealing methods that have been employed to avoid exposure to the ambient atmosphere and cure the interface defects induced by the inevitable oxidization of electrodes. Due to the high improvement of the interface quality, the capacitors based on ultra-thin (∼6 nm) AFE film show competitive memory performances, such as low operating voltage (−0.6/1.8 V), high speed (10 ns), long retention time (103 s), and high endurance (1012). The final benchmark demonstrates that the proposed AFE TiN/HfxZr1−xO2/TiN capacitor is a promising candidate toward the next generation high-speed and high-density embedded memory. [ABSTRACT FROM AUTHOR]

To ensure the speed, recall, and precision of the algorithm to solve the algorithm's measurement failure due to the problem of high underdetermination and the deviation of some outgoing lines from accessible nodes, the ideal resistance method is proposed to diagnose the corrosion of the grounding grid. The information extraction algorithm, a two-way heuristic network resistance diagnosis method, is added. A non-linear multi-objective optimization model of the deviation between the measured potential and the real potential is established. This paper puts forward that the grounding network's fault diagnosis is analogous to a neural network's training process, which makes full use of the excellent robustness and rapidity of a neural network training method. Simultaneously, the algorithm adds the retraining method combined with the field excavation in training and proves its feasibility through the Grobner basis codimension theory in algebraic geometry. Through result verification, it is found that the new algorithm can avoid the inversion failure caused by the algorithm failure due to the lack of accessible nodes and the abnormal part of input data at the same time as a fast solution. [ABSTRACT FROM AUTHOR]

The activation function is a crucial part for memristive neural networks. For the first time, we propose a memristor-based activation function by using the natural non-linear characteristics of the memristor itself. Compared to the virtual ground circuit in traditional memristive neural networks, the feedback resistance was replaced by the W/TaOx/Ru memristor with no additional expense. Simulation results demonstrate that the proposed memristor-based activation function can achieve a performance similar to that of traditional activation functions on the Mixed National Institute of Standards and Technology database. In addition, an improvement in the recognition rate of up to 2% can be obtained in different neuromorphic networks by modulating the non-linearity of the memristor. Furthermore, the memristor-based activation function can also receive a 94% recognition rate even considering the non-ideal factors of the device. [ABSTRACT FROM AUTHOR]

Magnesium fluoride is a promising candidate for resistive-switching random access memory (RRAM) with biodegradable property. However, the underlying resistive-switching (RS) mechanism and conduction mechanism in MgF2 material is still not fully studied, which limits the further performance optimization. In this work, we have demonstrated the rectification and bipolar RS behaviors in Ti/MgF2/Pt device. The un-Formed device exhibits stable rectifying characteristics, with a rectifying ratio of ∼103 at ±3 V. Furthermore, transition from rectification mode to RS behavior can be achieved by a Forming process. Then the analogue switching properties with high uniformity was obtained with quasi-DC sweeps, and gradual modulation of multi-state was further realized. At last, the conduction and switching mechanism was discussed. [ABSTRACT FROM AUTHOR]

Thermodynamic pathways and reaction initiation mechanisms of shocked TNT (2, 4, 6-trinitrotoluene, formula C6H2(NO2)3CH3) with shock velocities in the range of 6 -10 km⋅s-1 using the first-principles-based ReaxFF reactive force field molecular dynamics and the multiscale shock technique (MSST) are reported in this paper. The decomposition reactions occur at a shock velocity of 7 km⋅s-1 or higher. The shock initiation pressure, 25.1 GPa, is obtained from Rankine−Hugoniot relation. According to the link between macroscopic shock initiation and microscopic chemical reaction events, the formation of TNT-dimer and decomposition to C7H5O5N3 are the dominant initial route for shock induced reaction initiation. At shock speeds equal to or higher than 8km⋅s-1, TNT-dimer is formed and subsequently decomposed to C7H5O5N3, NO2 and NO. The quantity of NO2 molecules reaches maximum when TNT molecules decompose completely. Furthermore, when NO2 molecules are consumed fully, the volume of reaction system begins to expand. TNT molecules are dimerized at each shock condition, and the quantity of dimers is the largest at a shock initiation velocity of 7 km⋅s-1. Finally, the formation and evolution of carbon-containing clusters in shocked TNT are analyzed. [ABSTRACT FROM AUTHOR]