Quasi-Periodic Growth of One-Dimensional Copper Boride on Cu(110).

An unexplored material of copper boride has been realized recently in two-dimensional form at a (111) surface of the fcc copper crystal. Here, one-dimensional (1-D) boron growth was observed on the Cu(110) surface, as probed by atomically resolved scanning probe microscopy. The 1-D copper boride was composed of quasi-periodic atomic chains periodically aligned parallel to each other, as confirmed by Fourier transform analysis. The 1-D growth unexpectedly proceeded across surface steps in a self-assembled manner and extended over several 100 nm. The long-range formation of a 1-D quasi-periodic structure on a surface has been theoretically modeled as a 1-D quasi-crystal and the predicted conditions matched the structural parameters obtained by the experimental work here. The quasi-periodic 1-D copper boride system enabled a way to examine 1-D quasi-crystallinity on an actual material.

Associated factors for multidimensional attitudes and behaviors of reproductive health toward pregnancy among early and late adolescents in Tanzania: a cross-sectional study.

BACKGROUND: Adolescent pregnancy is a serious reproductive health problem in Tanzania. However, the risk factors for multidimensional attitudes and behaviors of reproductive health toward pregnancy in Tanzanian adolescents remain unexplored. METHODS: We collected baseline characteristics and information on attitudes and behaviors of reproductive health from 4161 Tanzanian adolescents in all 54 primary and secondary schools in the Korogwe district. We applied mixed effect multiple regression analyses stratified by sex to find the factors related to reproductive health attitudes and behaviors toward pregnancy. RESULTS: In female students, regarding the attitudes of reproductive health, higher age, hope for marriage in the future, a talk with a parent about sex or pregnancy, and a higher hope score were significantly associated with a lower score. For the behaviors of reproductive health, higher age, a talk with a parent about sex or pregnancy, time to talk with a parent about daily life, and a higher hope score were significantly associated with a lower score. In male students, regarding the attitudes of reproductive health, a higher hope score was significantly associated with a lower score. For the behaviors of reproductive health, higher age, time to talk with a parent about daily life, and a higher hope score was significantly associated with a lower score. CONCLUSIONS: The heterogeneous factor-outcomes association between female and male students suggested that sex-specialized interventions may be required to change their risky attitudes or behaviors of reproductive health. Although we cannot conclude as points of intervention, our study suggested that it may be practical to improve parent-adolescents communication about sex or reproductive health and change adolescents' views of pregnancy or marriage for gaining financial or social status.

The long-term effects of reproductive health education among primary and secondary school students: a longitudinal quasi-experimental study in rural Tanzania.

BACKGROUND: Adolescent pregnancy remains a major global health issue, increasing the risk of complications during pregnancy and childbirth in mothers and babies. In Tanzania, adolescent pregnancy threatens girls' education and makes it difficult for them to obtain a proper job; hence, the majority fall into poverty. Previous studies have developed and conducted reproductive health education for adolescent students; however, they evaluated only the effect immediately after education. Therefore, this study investigated the effects of reproductive health education on attitudes and behaviors toward reproductive health among adolescent girls and boys one year after the intervention in rural Tanzania. METHODS: A longitudinal quasi-experimental study was conducted with 3295 primary and secondary students (2123 in the intervention group, 1172 in the control group) from three purposefully selected wards in Korogwe District. In the intervention group, the students received reproductive health education. We used paper-based questionnaires to evaluate the effect of the adolescent education program on attitudes and behaviors toward reproductive health education. To analyze the association between the intervention and each outcome, mixed-effect multiple regression analyses was conducted. RESULTS: The mean age, primary school proportion, and female proportion of the intervention and the control group was 13.05 (standard deviation (SD) 1.59), 14.14 (SD 1.7), 77.9% and 34.3%, and 54.2% and 52.6%, respectively. There was no statistically significant effect of reproductive health education on adolescent health attitudes and behaviors in the multiple regression analyses (coefficient: - 0.24 (95% confidence interval (CI): - 0.98 to 0.50), coefficient: 0.01 (95%CI: - 0.42 to 0.43)). CONCLUSION: A statistically significant effect of reproductive health education on adolescent health attitudes and behaviors was not found. An effective reproductive health education intervention to improve the attitude and behaviors of reproductive health among Tanzania adolescents in the long term remain to be determined, particularly in real-world settings. Trial registration The National Institute for Medical Research, Tanzania (NIMR/HQ/R.8a/Vol. IX988).

Adolescent pregnancy increases the risk of complications during pregnancy and childbirth, which could cause death among 15­19-year-old girls. In Tanzania, one in four adolescents aged 15­19 began childbearing. However, there is no officially recognized curriculum for reproductive health in schools. Additionally, cultural and traditional norms prevent parents from discussing sexuality with their children. A solution to this issue is for a third party, such as a non-profit organization, to provide adolescents with adequate reproductive health education in schools. Previous studies have developed and evaluated a reproductive health education program and found significant effects on improved knowledge and behavior among adolescent girls and boys immediately after the intervention. This study examined the effects of reproductive health education on adolescents` attitudes and behavior toward reproductive health one year after the intervention in rural Tanzania. We could not find a statistically significant effect of reproductive health education on adolescents' attitudes and behavior during a one-year period in the multiple regression analyses. These results could have been influenced by the location of the intervention, contents, period of evaluation, and other potentially unknown factors.

Prediction of a Cyclic Hydrogenated Boron Molecule as a Promising Building Block for Borophane.

We have extensively searched for a cyclic hydrogenated boron molecule that has a three-center two-electron bond at the center. Using first-principles calculations, we discovered a stable molecule of 2:4:6:8:-2H-1,5:1,5-µH-B8H10 and propose its existence. This molecule can be regarded as a building block for sheets of topological hydrogen boride (borophane), which was recently theoretically proposed and experimentally discovered. The electronic structure of the cyclic hydrogenated boron molecule is discussed in comparison with that of cyclic hydrogenated carbon molecules.

Effects of density and composition on the properties of amorphous alumina: A high-dimensional neural network potential study.

Amorphous alumina (a-AlOx), which plays important roles in several technological fields, shows a wide variation of density and composition. However, their influences on the properties of a-AlOx have rarely been investigated from a theoretical perspective. In this study, high-dimensional neural network potentials were constructed to generate a series of atomic structures of a-AlOx with different densities (2.6 g/cm3-3.3 g/cm3) and O/Al ratios (1.0-1.75). The structural, vibrational, mechanical, and thermal properties of the a-AlOx models were investigated, as well as the Li and Cu diffusion behavior in the models. The results showed that density and composition had different degrees of effects on the different properties. The structural and vibrational properties were strongly affected by composition, whereas the mechanical properties were mainly determined by density. The thermal conductivity was affected by both the density and composition of a-AlOx. However, the effects on the Li and Cu diffusion behavior were relatively unclear.

Dependence of a cooling rate on structural and vibrational properties of amorphous silicon: A neural network potential-based molecular dynamics study.

Amorphous materials have variable structural order, which has a significant influence on their electronic, transport, and thermal properties. However, this difference in structure has rarely been investigated by atomistic modeling. In this study, a high-quality machine-learning-based interatomic potential was used to generate a series of atomic structures of amorphous silicon with different degrees of disorder by simulated cooling from the melt with different cooling rates (1011-1015 K/s). We found that the short- and intermediate-range orders are enhanced with decreasing cooling rate, and the influence of the structural order change is in excellent agreement with the experimental annealing process in terms of the structural, energetic, and vibrational properties. In addition, by comparing the excess energies, structure factors, radial distribution functions, phonon densities of states, and Raman spectra, it is possible to determine the corresponding theoretical model for experimental samples prepared with a certain method and thermal history.

Spectrum adapted the expectation-maximization algorithm for high-throughput peak shift analysis.

We introduce a spectrum-adapted expectation-maximization (EM) algorithm for high-throughput analysis of a large number of spectral datasets by considering the weight of the intensity corresponding to the measurement energy steps. Proposed method was applied to synthetic data in order to evaluate the performance of the analysis accuracy and calculation time. Moreover, the proposed method was performed to the spectral data collected from graphene and MoS2 field-effect transistors devices. The calculation completed in less than 13.4 s per set and successfully detected systematic peak shifts of the C 1s in graphene and S 2p in MoS2 peaks. This result suggests that the proposed method can support the investigation of peak shift with two advantages: (1) a large amount of data can be processed at high speed; and (2) stable and automatic calculation can be easily performed.

Comparison of different machine learning models for the prediction of forces in copper and silicon dioxide.

Recently, the machine learning (ML) force field has emerged as a powerful atomic simulation approach because of its high accuracy and low computational cost. However, there have been relatively fewer applications to multicomponent materials. In this study, we construct and compare ML force fields for both an elemental material (Cu) and binary material (SiO2) with varied inputs and regression models. The atomic environments are described by structural fingerprints that take into account the bond angle, and then, different ML techniques, including linear regression, a neural network and a mixture model method, are used to learn the structure-force relationship. We found that using angular structural fingerprints and a mixture model method significantly improves the accuracy of ML force fields. Additionally, we discuss an effective structural fingerprint auto-selection method based on the least absolute shrinkage and selection operator and the genetic algorithm. The atomic simulations conducted for ML force fields are in excellent agreement with ab initio calculations. As a result of the simulation with our ML force field for the structural and vibrational properties of amorphous SiO2, simulated annealing with a slow cooling rate improved the ring statistics in the amorphous structure and the phonon density of states.

Study of Li atom diffusion in amorphous Li3PO4 with neural network potential.

To clarify atomic diffusion in amorphous materials, which is important in novel information and energy devices, theoretical methods having both reliability and computational speed are eagerly anticipated. In the present study, we applied neural network (NN) potentials, a recently developed machine learning technique, to the study of atom diffusion in amorphous materials, using Li3PO4 as a benchmark material. The NN potential was used together with the nudged elastic band, kinetic Monte Carlo, and molecular dynamics methods to characterize Li vacancy diffusion behavior in the amorphous Li3PO4 model. By comparing these results with corresponding DFT calculations, we found that the average error of the NN potential is 0.048 eV in calculating energy barriers of diffusion paths, and 0.041 eV in diffusion activation energy. Moreover, the diffusion coefficients obtained from molecular dynamics are always consistent with those from ab initio molecular dynamics simulation, while the computation speed of the NN potential is 3-4 orders of magnitude faster than DFT. Lastly, the structure of amorphous Li3PO4 and the ion transport properties in it were studied with the NN potential using a large supercell model containing more than 1000 atoms. The formation of P2O7 units was observed, which is consistent with the experimental characterization. The Li diffusion activation energy was estimated to be 0.55 eV, which agrees well with the experimental measurements.

The electronic structure of quasi-free-standing germanene on monolayer MX (M = Ga, In; X = S, Se, Te).

For the first time by using the ab initio density functional theory, the stability and electronic structures of germanene on monolayer GaS, GaSe, GaTe and InSe have been investigated. Germanene preserves its buckled-honeycomb structure on all the studied substrates similar to the free-standing case. Moreover, germanene stays neutral and preserves its Dirac-cone-like band structure on monolayer GaTe and InSe. In these two cases, a bandgap of 0.14-0.16 eV opens at the Dirac point of germanene, while the effective masses remain as small as 0.05-0.06 times the free-electron mass. The estimated carrier mobility is up to 2.2 × 10(5) cm(2) V(-1) s(-1). These features show that monolayer GaTe and InSe are promising as substrates for germanene devices.

Machine Learning-Assisted Survey on Charge Storage of MXenes in Aqueous Electrolytes.

Pseudocapacitance is capable of both high power and energy densities owing to its fast chemical adsorption with substantial charge transfer. 2D transition-metal carbides/nitrides (MXenes) are an emerging class of pseudocapacitive electrode materials. However, the factors that dominate the physical and chemical properties of MXenes are intercorrelated with each other, giving rise to challenges in the quantitative assessment of their discriminating importance. In this perspective, literature data on the specific capacitance of MXene electrodes in aqueous electrolytes is comprehensively surveyed and analyzed using machine-learning techniques. The specific capacitance of MXene electrodes shows strong dependency on their interlayer spacing, where confined H2O in the interlayer space should play a key role in the charge storage mechanism. The electrochemical behavior of MXene electrodes is overviewed based on atomistic insights obtained from data-driven approaches.

Negative dielectric constant of water confined in nanosheets.

Electric double-layer capacitors are efficient energy storage devices that have the potential to account for uneven power demand in sustainable energy systems. Earlier attempts to improve an unsatisfactory capacitance of electric double-layer capacitors have focused on meso- or nanostructuring to increase the accessible surface area and minimize the distance between the adsorbed ions and the electrode. However, the dielectric constant of the electrolyte solvent embedded between adsorbed ions and the electrode surface, which also governs the capacitance, has not been previously exploited to manipulate the capacitance. Here we show that the capacitance of electric double-layer capacitor electrodes can be enlarged when the water molecules are strongly confined into the two-dimensional slits of titanium carbide MXene nanosheets. Using electrochemical methods and theoretical modeling, we find that dipolar polarization of strongly confined water resonantly overscreens an external electric field and enhances capacitance with a characteristically negative dielectric constant of a water molecule.

Scanning tunnelling spectroscopy of superconductivity on surfaces of LiTi2O4(111) thin films.

Unique superconductivity at surfaces/interfaces, as exemplified by LaAlO3/SrTiO3 interfaces, and the high transition temperature in ultrathin FeSe films, have triggered intense debates on how superconductivity is affected in atomic and electronic reconstructions. The surface of superconducting cubic spinel oxide LiTi2O4 is another interesting system because its inherent surface electronic and atomic reconstructions add complexity to superconducting properties. Investigations of such surfaces are hampered by the lack of single crystals or high-quality thin films. Here, using low-temperature scanning tunnelling microscopy and spectroscopy, we report an unexpected small superconducting energy gap and a long coherence length on the surface of LiTi2O4(111) epitaxial thin films. Furthermore, we find that a pseudogap opening at the Fermi energy modifies the surface superconductivity. Our results open an avenue for exploring anomalous superconductivity on the surface of cubic transition-metal oxides, where the electronic states are spontaneously modulated involving rich many-body interactions.