Irradiation with Argon Ions of Cr/4H-SiC Photodetectors

Semiconductors - The results of the effect of irradiation with Ar ions on the structural, electrophysical, and optical characteristics of ultraviolet Cr/4H-SiC photodetectors in the spectral range...     

State of hydropower installations in Armenia after the Spitak earthquake

Translated from Gidrotekhnicheskoe Stroitel'stvo, No. 8, pp. 21–25, August, 1989.     

Diversity of Properties of Device Structures Based on Group-III Nitrides,Related to Modification of the Fractal-Percolation System

A fractal-percolation system that includes extended defects and random fluctuations in the alloy composition is formed during the growth of device structures based on Group-III nitrides. It is established that the specific features of this system are determined not only by the growth conditions. It is shown that the diversity of the electrical and optical properties of InGaN/GaN LEDs (light-emitting diodes) emitting at wavelengths of 450–460 and 519–530 nm, as well as that of the electrical properties of AlGaN/GaN HEMT (high-electron-mobility transistor) structures, is due to modification of the properties of the fractal-percolation system both during the growth process and under the action of the injection current and irradiation. The influence exerted by these specific features on the service life of light-emitting devices and on the reliability of AlGaN/GaN HEMT structures is discussed.

     

Design and Operation of the Motorized Spindle in a Multifunctional Machine Tool

The design and adaptive control of a motorized spindle in a multifunctional machine tool is considered. Means of ensuring effective operation of the machine tool are discussed.     

A Study of the Residual Gas Composition in the Vacuum System of the Cyclotron of the Ioffe Physical Technical Institute

Technical Physics Letters - Mass spectra of residual gas molecules in vacuum system of the cyclotron of the Ioffe Physical Technical Institute (St. Petersburg) were obtained under various...     

Verifying the geometric precision of machine tools

A method is proposed for determining the basic tests of the geometric precision of a metal-cutting machine so as to assess the influence of its error on the precision of the manufactured parts.     

Real-Time Diagnostics of Metal-Cutting Machines by Means of Recurrent LSTM Neural Networks

Real-time diagnostics of modules in metal-cutting machines may be based on neural-network algorithms for simulation of the standard process, identification of defects, and the introduction of corrections in the cutting machine’s control system. The machining conditions in normal operation of the machine are recorded by means of a trained neural network with long short-term memory (LSTM network). In real-time operation, the difference between the standard neural-network model and the actual process characteristics is used to determine the type of defect and the module of the machine where it occurs on the basis of a second neural network, the classification unit.