The influence of processing parameters of aluminum oxide (Al₂O₃) and lanthanum oxide (La₂O₃) gate dielectric is investigated. Trimethylaluminum (TMA) and tris(isopropylcyclopentadienyl) lanthanum [La(iPrCp)₃] were used as precursors separately, and H₂O was used as oxidant. The ultra-thin La_{1 − x} Al _x O₃ gate dielectric films are deposited on p-type silicon substrates by atom layer deposition (ALD) for different pulse ratios of precursors. Effects of different La/Al precursor pulse ratios on the physical properties and electrical characteristics of La_{1 − x} Al _x O₃ films are studied. The preliminary testing results indicate that the increase of La precursor pulse can improve the characteristics of film, which has significant effects on the dielectric constant, equivalent oxide thickness (EOT), electrical properties, and stability of film.

In this study, the physical and electrical characteristics of Al₂O₃/La₂O₃/Al₂O₃/Si stack structures affected by the thickness of an Al₂O₃barrier layer between Si substrate and La₂O₃layer are investigated after a rapid thermal annealing (RTA) treatment. Time of flight secondary ion mass spectrometry (TOF-SIMS) and X-ray photoelectron spectroscopy (XPS) tests indicate that an Al₂O₃barrier layer (15 atomic layer deposition (ALD) cycles, approximately 1.5 nm) plays an important role in suppressing the diffusion of silicon atoms from Si substrate into the La₂O₃layer during the annealing process. As a result, some properties of La₂O₃dielectric degenerated by the diffusion of Si atoms are improved. Electrical measurements (C-V,J-V) show that the thickness of Al₂O₃barrier layer can affect the shift of flat band voltage (V_FB) and the magnitude of gate leakage current density.

The four-wheel drive robot has a coupling relationship between the four wheels due to the characteristics of the wheel train distribution. During the operation, there are problems with the stability and control accuracy of the robot’s overall motion. To solve this problem, this paper constructs an adaptive control algorithm based on cognitive computing. We use real-time sensor data as learning samples for online learning, and obtain new sample averages, new feature values, feature vectors, and new subspaces. This information is stored in the semantic long-term memory by projecting the newly read sample into the subspace obtained in the previous calculation. In addition, fuzzy control and partial discharge control are combined to correct the stored information online. Taking into account the distribution characteristics of the wheel system structure, we reasonably allocate the overall error to a single wheel, which will convert the overall error correction into a single wheel error correction. The simulation experiment in the Matlab-Simulink environment shows that after using the fuzzy adaptive controller for error correction, the error value of the robot’s linear velocity and angular velocity is between −1 and 1.5. In addition, the followability and the performance of tracking the target are obviously improved, and the accuracy of robot motion control is improved.

In this paper, we investigate the problem of the heavy computational burden of the direction-of-arrival (DoA) estimation for the noncircular (NC) signals. A novel low-complexity direction-of-arrival estimation algorithm for NC signals via subspace rotation technique (SRT) is proposed. The proposed algorithm divides the noise subspace matrix along its row direction into two submatrices, and the SRT is performed to get a new reduced-dimension noise subspace. Then, utilizing the separation of variables and the orthogonality between the reduced-dimension noise subspace and the space spanned by the columns of the extended manifold matrix, a new one-dimensional spectral search function is derived to estimate DoAs. As the size of the block matrices of the noise subspace matrix has a great impact on the computational complexity of the spectral search, the optimal number of rows of the block matrices is determined. The proposed algorithm not only avoids the two-dimensional spectral search but also efficiently removes the redundancy computations in the one-dimensional spectral search. Theoretical analysis and simulation results show that the proposed algorithm can significantly improve the computational efficiency on the premise of ensuring the accuracy of DoA estimation for the NC signals, especially in scenarios where large numbers of sensors are applied.