Study of the crystal field and rare-earth magnetism in YF3:Yb3+

The electron paramagnetic resonance spectra (X-band, f ~ 9.42 GHz) of Yb3+ ions have been measured at temperature 15 K in YF3:Yb3+ single crystals. The principal values of the g-tensors, gb = g1 = 1.67, g2 = 2.42, g3 = 5.41, and directions n1 = [0, 1, 0], n2 = [±sin(54.8°), 0, cos(54.8°)], n3 = [∓sin(35.2°), 0, cos(35.2°)] of the corresponding principal axes for the Yb3+ ions which replace Y3+ ions at two magnetically nonequivalent sites with the local Cs symmetry in the orthorhombic crystal lattice have been obtained from analysis of the angular dependences of the spectra taken in the static magnetic fields lying in the crystallographic (bc) and (ac) planes. Experimental data are interpreted in the frameworks of the crystal field theory. Using the obtained set of crystal field parameters for Yb3+ ions in the YF3 host related to the crystallographic system of coordinates, we can reproduce satisfactorily the crystal field energies of Yb3+ ions determined earlier from optical measurements

Estimation of Imageability Ratings of English Words Using Neural Networks

The article considers the problem of imageability ratings estimation of English words using artificial neural networks. To train and test the models, we use data of several freely available psycholinguistic databases. We compared two approaches based on different vector representations of words. The first approach uses pre-trained fastText vectors. The second one utilizes explicit word vectors built on the basis of co-occurrence statistics with the most frequent words extracted from the Google Books Ngram corpus. We employed the MRC Psycholinguistic Database to obtain the value of Spearman's correlation coefficient between imageability ratings and their estimations. The highest resulting value equaled 0.882. This significantly improves the results obtained in previous works. The approach proposed in this paper can be used to create large dictionaries with imageability ratings, which is important for many practical problems

Grammatical Evolution for Neural Network Optimization in the Control System Synthesis Problem

Grammatical evolution is a perspective branch of the genetic programming. It uses evolutionary algorithm based search engine and Backus - Naur form of domain-specific language grammar specifications to find symbolic expressions. This paper describes an application of this method to the control function synthesis problem. Feed-forward neural network was used as an approximation of the control function, that depends on the object state variables. Two-stage algorithm is presented: grammatical evolution optimizes neural network structure and genetic algorithm tunes weights. Computational experiments were performed on the simple kinematic model of a two-wheel driving mobile robot. Training was performed on a set of initial conditions. Results show that the proposed algorithm is able to successfully synthesize a control function. © 2017 The Authors

Grammatical Evolution for Neural Network Optimization in the Control System Synthesis Problem

Grammatical evolution is a perspective branch of the genetic programming. It uses evolutionary algorithm based search engine and Backus - Naur form of domain-specific language grammar specifications to find symbolic expressions. This paper describes an application of this method to the control function synthesis problem. Feed-forward neural network was used as an approximation of the control function, that depends on the object state variables. Two-stage algorithm is presented: grammatical evolution optimizes neural network structure and genetic algorithm tunes weights. Computational experiments were performed on the simple kinematic model of a two-wheel driving mobile robot. Training was performed on a set of initial conditions. Results show that the proposed algorithm is able to successfully synthesize a control function. © 2017 The Authors

Neural Network Recognition of Russian Noun and Adjective Cases in the Google Books Ngram Corpus

The article proposes a solution to the problem of automatic recognition of Russian noun and adjective cases in the Google Books Ngram corpus. The recognition was performed by using information on word co-occurrence statistics extracted from the corpus. Explicit Word Vectors composed of frequencies of ordinary and syntactic bigrams that include a given word were fed to the input of the recognizer. Comparative testing of several types of vector representation and preliminary data normalization were carried out. The trained model was a multi-layer perceptron with a softmax output layer. To train and test the model, we selected 50000 adjectives and 50000 nouns that were most frequently used in the Google Books Ngram Russian subcorpus between 1920 and 2009. Parts of speech and cases were determined using the OpenCorpora electronic morphological dictionary. The recognition accuracy of the cases obtained using the trained neural network model was 96.45% for the nouns and 99.63% for the adjectives

Study of the crystal field in CeF3 and CeF3:Pr3+

The crystal field analysis based on calculations in the framework of the semi phenomenological exchange charge model was carried out. The set of crystal field parameters for Ce3+ and Pr3+ ions in the matrix CeF3 related to the crystallographic system of coordinates has been obtained and used to reproduce satisfactory the crystal field energies of Ce3+ and Pr3+ ions

Functional coating preparation based on zinc oxide using low temperature plasma

© 2020 Published under licence by IOP Publishing Ltd. The work describes the synthesis of superhydrophobic coating based on zinc oxide with a UV-driven reversible switching between hydrophilic and hydrophobic properties. A coating of vertically oriented acicular crystals of zinc oxide with dimensions of 1-2 μm in length and 50-200 nm in width on a metal substrate was obtained. According to the phase composition and morphology, the crystals correspond to zinc oxide-zincite. The contact angle for the coating after its exposure in a box isolated from daylight for 14 days is 150 °, while for the control metal substrate, the contact angle is 40 °. It is shown that the use of low temperature Ar plasma of low pressure allows changing the surface topography of acicular nanocrystals due to etching of their vertices and edges

Magnetic properties of powders LiTbF4 and TbF3

Samples LiTbF4 and TbF3 were synthesized by modified methods of colloidal chemistry. The magnetization of these samples was measured in the external magnetic field at 100 Oe and 1 T and in temperature range 2-300 K. Temperatures of phase transition to the magnetic ordering dipolar ferromagnet state were determined for synthesized samples

Spectral and magnetic properties of impurity Tm3+ ions in YF3

Stark structure of 3H6, 3H5, 3H4, 3F4, 3F3, 3F2 and 1G4 multiplets of impurity non-Kramers Tm3+ ions in the orthorhombic YF3 crystal has been determined from luminescence studies. High frequency electron paramagnetic resonance (EPR) spectra (~ 207 GHz) of Tm3+ ions have been measured at temperature 4.2 K in external magnetic field applied perpendicular to the b-axis of YF3:Tm3+ single crystal. The results of measurements are interpreted in the frameworks of the crystal field theory. The set of crystal field parameters related to the crystallographic system of coordinates of the YF3 lattice has been obtained and used to reproduce satisfactory the crystal field energies and the EPR spectra