The Influence of Angstrom-Scale Roughness on the Laser-Induced Damage Threshold of Single-Crystal ZnGeP2

Magnetorheological processing was applied to polish the working surfaces of single-crystal ZnGeP2, in which a non-aqueous liquid with the magnetic particles of carbonyl iron with the addition of nanodiamonds was used. Samples of a single-crystal ZnGeP2 with an Angstrom level of surface roughness were received. The use of magnetorheological polish allowed the more accurate characterization of the possible structural defects that emerged on the surface of a single crystal and had a size of ~0.5–1.5 μm. The laser-induced damage threshold (LIDT) value at the indicated orders of magnitude of the surface roughness parameters was determined not by the quality of polishing, but by the number of point depressions caused by the physical limitations of the structural configuration of the crystal volume. These results are in good agreement with the assumption made about a significant effect of the concentration of dislocations in a ZnGeP2 crystal on LIDT.

The Influence of the Angstrom-scale Roughness on the Laser-induced Damage Threshold of the ZnGeP2 Single Crystal

Magnetorheological processing was applied to polish the working surfaces of the ZnGeP2 single crystal, in which a non-aqueous liquid with magnetic particles of carbonyl iron with the addition of nanodiamonds was used. Samples of a single crystal ZnGeP2 with an angstrom level of surface roughness were received. the use of MRP has allowed more accurately characterizing possible structural defects that have emerged on the surface of a single crystal and have a size of ~ 0.5-1.5 μm. the LIDT value at the indicated or-ders of magnitude of the surface roughness parameters is determined not by the quality of polishing, but by the number of point depressions caused by physical limitations of the structural configuration of the crystal volume. These results are in good agreement with the assumption made about a significant effect of the concentration of dislocations in a ZnGeP2 crystal on LIDT.

Stochastic hydration of a high-nitrogen-content molecular compound recrystallized under pressure

Partial hydration of organic compounds can be achieved by high-pressure crystallization. This has been demonstrated for the high-nitrogen-content compound 6-chloro-1,2,3,4-tetrazolo[1,5-b]pyridazine (C4H2N5Cl), which becomes partly hydrated by isochoric crystallizations below 0.15 GPa. This hydrate, C4H2N5Cl·xH2O, is isostructural with the ambient-pressure phase α of C4H2N5Cl, but the crystal volume is somewhat larger than that of the anhydrate. At 0.20 GPa, the α-C4H2N5Cl anhydrate phase transforms abruptly into a new higher-symmetry phase, α′; the transformation is clearly visible due to a strong contraction of the crystals. The hydrate α-C4H2N5Cl·xH2O can also be isothermally compressed up to 0.30 GPa before transforming to the α′-C4H2N5Cl·xH2O phase. The isochoric recrystallization of C4H2N5Cl above 0.18 GPa yields a new anhydrous phase β, which, on releasing pressure, transforms back to the α phase below 0.15 GPa. The structural transition from the α to the β phase is destructive for the single crystal and involves a large volume drop and significant elongation of all the shortest intermolecular distances which are the CH...N and CH...Cl hydrogen bonds, as well as the N...N contacts. The α-to-α′ phase transition increases the crystal symmetry in the subgroup relation; however, there are no structural nor symmetry relations between phases α and β.

Calculation and experimental verification of force-magnetic coupling model of magnetised rail based on density functional theory

Metal magnetic memory (MMM) is a widely used non-destructive electromagnetic detection technology. However, the analysis of its underlying principle is still insufficient. The mechanical and magnetic coupling model is a reasonable standpoint from which to study the principle of MMM. In this paper, a mechanical and magnetic coupling model of steel material is established based on density functional theory (DFT) using the CASTEP first-principles analysis software. In order to simulate the practical working environment, the residual magnetism in the rail is assumed to change with the stress on the rail. By applying different stresses to the model, the relationship between the atomic magnetic moment, the lattice constant and stress is explored, as well as the causes of magnetic signals in the stress concentration zone. It is revealed that the atomic magnetic moment and the crystal volume decrease with the increase in compressive stress. The magnetic signal on the surface of the magnetised metal component decreases with the increase in compressive stress, while the tensile stress shows the opposite tendency. Generally speaking, the change in atomic magnetic moment and crystal volume caused by lattice distortion under stress can be seen as the fundamental reason for the change in magnetic signal on the surface of the magnetised metal. The bending experiment of the rail shows that the normal magnetic field decreases with the increase in compressive stress in the stress concentration zone. The conclusion is verified by experiments.

Morphological, Structural, and Optical Bandgap Characterization of Extracted ZnO Nanoparticles from Commercial Paste

ZnO nanoparticles (NPs) were extracted from a commercial paste in both colloidal and precipitate forms. The Zetasizer analysis performed on the colloid showed ZnO NPs ranging from ∼30 nm to ∼100 nm. Thin films of ZnO were deposited on glass substrates by spin-coating technique from a mixture of the extracted colloid and precipitate. The scanning electron microscope (SEM) images showed uniformly arranged, mesoporous, and nanostructured ZnO particles of different shapes, with an estimated film thickness of 0.67 μm. Analysis by energy dispersive X-ray spectroscopy (EDS) and X-ray diffraction analysis (XRD) confirmed the presence of ZnO in the films, with no impurities or remnants of other materials. The XRD analysis showed a polycrystalline nature of the films and identified a pure phase formation of the hexagonal wurtzite structure. The average crystallite size calculated from the diffraction peaks is ∼43.25 nm. The calculated crystal tensile strain is 1.954 × 10−3, which increases the crystal volume by 0.728% compared with the crystal volume of standard ZnO. The calculated crystal parameters are a = b = 3.258 Å and c = 5.217 Å. The calculated dislocation density (d) and bond length Zn–O (L) are 5.35 × 10−4 nm−2 and 2.695 Å, respectively. Ultraviolet-visible absorption spectra showed an optical band gap of ∼3.80 eV.

Physical Processes during the Formation of Silicon-Lithium p-i-n Structures Using Double-Sided Diffusion and Drift Methods

In this paper, we described a method of double-sided diffusion and drift of lithium-ions into monocrystalline silicon for the formation of the large-sized, p-i-n structured Si(Li) radiation detectors. The p-i-n structure is a p-n junction with a doped region, where the “i-region” is between the n and the p layers. A well-defined i-region is usually associated with p or n layers with high resistivities. The p-i-n structure is mostly used in diodes and in some types of semiconductor radiation detectors. The uniqueness of this method is that, in this method, the processes of diffusion and drift of lithium-ions, which are the main processes in the formation of Si(Li) p-i-n structures, are produced from both flat sides of cylindrical-shaped monocrystalline silicon, at optimal temperature (T = 420 °C) conditions of diffusion, and subsequently, with synchronous supply of temperature (from 55 to 100 °C) and reverse bias voltage (from 70 to 300 V) during drift of lithium-ions into silicon. Thus, shortening the manufacturing time of the detector and providing a more uniform distribution of lithium-ions in the crystal volume. Since, at present, the development of manufacturing of large-sized Si(Li) detectors is hindered due to difficulties in obtaining a uniformly compensated large area and time-consuming manufacturing process, the proposed method may open up new possibilities in detector manufacturing.

Observation of substrate diffusion and ligand binding in enzyme crystals using high-repetition-rate mix-and-inject serial crystallography

Here, we illustrate what happens inside the catalytic cleft of an enzyme when substrate or ligand binds on single-millisecond timescales. The initial phase of the enzymatic cycle is observed with near-atomic resolution using the most advanced X-ray source currently available: the European XFEL (EuXFEL). The high repetition rate of the EuXFEL combined with our mix-and-inject technology enables the initial phase of ceftriaxone binding to the Mycobacterium tuberculosis β-lactamase to be followed using time-resolved crystallography in real time. It is shown how a diffusion coefficient in enzyme crystals can be derived directly from the X-ray data, enabling the determination of ligand and enzyme–ligand concentrations at any position in the crystal volume as a function of time. In addition, the structure of the irreversible inhibitor sulbactam bound to the enzyme at a 66 ms time delay after mixing is described. This demonstrates that the EuXFEL can be used as an important tool for biomedically relevant research.

Predicting Perovskite Performance with Multiple Machine-Learning Algorithms

Perovskites have attracted increasing attention because of their excellent physical and chemical properties in various fields, exhibiting a universal formula of ABO3 with matching compatible sizes of A-site and B-site cations. In this work, four different prediction models of machine learning algorithms, including support vector regression based on radial basis kernel function (SVM-RBF), ridge regression (RR), random forest (RF), and back propagation neural network (BPNN), are established to predict the formation energy, thermodynamic stability, crystal volume, and oxygen vacancy formation energy of perovskite materials. Combined with the fitting diagrams of the predicted values and DFT calculated values, the results show that SVM-RBF has a smaller bias in predicting the crystal volume. RR has a smaller bias in predicting the thermodynamic stability. RF has a smaller bias in predicting the formation energy, crystal volume, and thermodynamic stability. BPNN has a smaller bias in predicting the formation energy, thermodynamic stability, crystal volume, and oxygen vacancy formation energy. Obviously, different machine learning algorithms exhibit different sensitivity to data sample distribution, indicating that we should select different algorithms to predict different performance parameters of perovskite materials.

Optical Control of Superlattices States Formed Due to Electronic Phase Separation in Multiferroic Eu0.8Ce0.2Mn2O5

The effect of optical pumping and magnetic field on properties of the electronic phase separation regions, which are the multiferroic semiconductor heterostructures in the form of superlattices, have been studied in Eu0.8Ce0.2Mn2O5. These superlattices are formed due to self-organization in a dielectric crystal matrix as a result of the competing internal interactions balance and occupy a small crystal volume. The dynamical equilibrium states of superlattices are initially formed during cycling of as-grown samples in a magnetic field. The superlattices in such states are ferromagnetic and electrically neutral. Sets of ferromagnetic resonances were observed from individual layers of superlattices. Their features give rise information on properties of these layers and of a superlattice as a whole. The differences in the parameters of these resonances were due to different distributions of Mn3+ and Mn4+ ions in individual superlattices layers. It has been found that optical pumping having different powers allows us to control of multiferroic properties of superlattices layers by changing their magnetic and electric properties. It is shown that, under certain conditions, it is possible to significantly increase the temperatures at which multiferroic heterostructures exist.

Structural and computational investigation of an imine-based propeller-shaped macrocyclic cage

In this study, we present the synthesis, spectroscopic and structural characterization of self-assembling gem-dimethyl imine based molecular cage (IMC). Self-assembling macrocycles and cages have well-defined cavities and have extensive functionalities ranging from energy storage, liquid crystals, and catalysts to water splitting photo absorber. IMC has large voids i.e., 25% of the total crystal volume thus could accommodate wide substrates. The synthesized imine-based molecular cages are stabilized by coaxial π bonded networks and long-range periodic van der Waal and non-bonded contacts as observed from the crystal structure. IMC also has typical properties of soft condensed matter materials, hence theoretical prediction of stress and strain tensor along with thermophysical properties were computed on crystal system and were found to be stable. Molecular dynamics revealed IMC is stabilized by, strong interactions between the interstitial phenyl rings. Density functional theory (DFT) based physicochemical properties were evaluated and has band gap of around 2.38ev (520 nm) similar to various photocatalytic band gap materials.