Enhancement of Crystal Growth in Molten Salts by a Cocrystallization Agent: Synthesis and Luminescent Properties of Ce- and Eu-Doped La(SiS)I.

In this study, we present the growth of large (SiS)I ( = La, Ce) crystals, both undoped and doped with Ce and Eu. The synthesis process involves the utilization of an arc-melted precursor in conjunction with sulfur and KI. We investigate the role of Zr, Nb, Mo, and Ir as cocrystallization agents, facilitating the growth of relatively large (up to 6-7 mm) crystals.

[Effect of hyperoxic inhalations for athletes of different sports, including those who had COVID-19, when training in the middle altitude].

Objective: To identify hyperoxic inhalations on the functional state of the cardiorespiratory system of athletes of different sports, who have previously had COVID-19, when training in the middle altitude.

Material And Methods: The study included 64 elite athletes during the preparatory period. The studies were conducted in Kislovodsk in the middle altitude (1240 meters) on the Maloe Sedlo mountain, in the conditions of training camps.

[Robotic mechanotherapy in a complex of procedures for the functional state recovery of the neuromuscular system and peripheral hemodynamics in track-and-field athletes].

Unlabelled: The background of the study is caused by the need to develop methods of drug-free neuromuscular system and peripheral hemodynamics recovery of athletes to optimize their functioning after intense physical activity in current conditions of high sporting competition.

Objective: To develop a program of comprehensive recovery of neuromuscular apparatus and hemodynamics of the lower limbs of track-and-field athletes during intense physical activity, including mechanotherapy on the robotic biomechanical complex with biological feedback and to evaluate its efficacy, comparing with a standard recovery program.

Material And Methods: The study involved 23 track-and-field athletes (the mean age 24.

Machine Learning-Guided Discovery of Ternary Compounds Containing La, P, and Group 14 Elements.

We integrate a deep machine learning (ML) method with first-principles calculations to efficiently search for the energetically favorable ternary compounds. Using La-Si-P as a prototype system, we demonstrate that ML-guided first-principles calculations can efficiently explore crystal structures and their relative energetic stabilities, thus greatly accelerate the pace of material discovery. A number of new La-Si-P ternary compounds with formation energies less than 30 meV/atom above the known ternary convex hull are discovered.