Ti掺杂对α″-Fe16N2相稳定性的影响

研究了掺杂Ti对α″-Fe₁₆N₂相稳定性的影响，发现适量Ti掺杂有利于α″-Fe₁₆N₂相的形成．理论分析表明，掺杂适量Ti元素后含Ti的α″-(Fe,Ti)₁₆N₂相的生成焓降低，使α″相的稳定性提高，也使α″相更易制备．Ti浓度为3—15at％的(FeTi)-N薄膜具有高饱和磁化强度，μ₀M_s=2.3—2.5T． 关键词：     

A laser extraction/combustion technique for in situ delta(13)C analysis of organic and inorganic materials

A CO(2) laser extraction system is described for in situ delta(13)C analysis of organic and inorganic materials. Carbonaceous compounds volatilized by the laser are quantitatively converted to CO(2) gas by a combustion furnace mounted after the sample chamber. Gases produced by the laser and combustion processes are swept by helium carrier gas and separated by a packed gas chromatography column prior to their introduction to an isotope ratio monitoring mass spectrometer. A sample of lentil bean was analyzed at a spatial resolution of 200 μm and yielded delta(13)C values with precision of +/- 0.3 per thousand. The accuracy of delta(13)C measurements was better than +/- 0.5 per thousand from NBS 22 (mineral oil), USGS 24 (graphite), and IAEA CO-1 (calcium carbonate). Copyright 1999 John Wiley & Sons, Ltd.     

Making thermodynamic models of mixtures predictive by machine learning: matrix completion of pair interactions

Predictive models of thermodynamic properties of mixtures are paramount in chemical engineering and chemistry. Classical thermodynamic models are successful in generalizing over (continuous) conditions like temperature and concentration. On the other hand, matrix completion methods (MCMs) from machine learning successfully generalize over (discrete) binary systems; these MCMs can make predictions without any data for a given binary system by implicitly learning commonalities across systems. In the present work, we combine the strengths from both worlds in a hybrid approach. The underlying idea is to predict the pair-interaction energies, as they are used in basically all physical models of liquid mixtures, by an MCM. As an example, we embed an MCM into UNIQUAC, a widely-used physical model for the Gibbs excess energy. We train the resulting hybrid model in a Bayesian machine-learning framework on experimental data for activity coefficients in binary systems of 1146 components from the Dortmund Data Bank. We thereby obtain, for the first time, a complete set of UNIQUAC parameters for all binary systems of these components, which allows us to predict, in principle, activity coefficients at arbitrary temperature and composition for any combination of these components, not only for binary but also for multicomponent systems. The hybrid model even outperforms the best available physical model for predicting activity coefficients, the modified UNIFAC (Dortmund) model.

Embedding matrix completion methods from machine learning in classical thermodynamic models creates powerful hybrid models for predicting properties of mixtures.     

Rotational viscosity of uniaxial molecules

Non-equilibrium molecular dynamics (NEMD) are used to calculate the vortex or rotational viscosity of fluids composed of uniaxial molecules. It is shown that the NEMD homogeneous spin flow algorithm proposed by Edberg, R., Evans, D. J., and Moriss, G. P., 1987, Molec. Phys., 62, 1357 considerably underestimates the vortex viscosity. A modified version of this algorithm is proposed and applied to liquid chlorine and nitrogen. The results are in good agreement with previous work using equilibrium or other NEMD methods, and also show that at high spin rates the vortex viscosity decreases with increase in magnitude of the external torque used to drive the spin flow.     

THE HADAMARD INEQUALITY FOR CONVEX FUNCTION VIA FRACTIONAL INTEGRALS

In this paper, we establish several inequalities for some differantiable mappings that are connected with the Riemann-Liouville fractional integrals. The analysis used in the proofs is fairly elementar...     

On the role of the definition of potential models in Gibbs ensemble phase equilibria simulations of the H2S-pentane mixture

The effect of treating explicitly the coulombic and polarization interactions is investigated through the calculation of the coexistence curve of the pentane-H₂S binary mixture. In this work, potential models have been developed for hydrogen sulphide and pentane, which include electrostatic sites—estimated from ab initio calculations—and polarizable sites—estimated from experimental data—in addition to Lennard-Jones sites. Compared to existing models, these new models have the same number of fitting parameters to experimental thermodynamic data. They are shown to correctly describe the coexistence curve of the pure compounds. When applied to the case of mixtures, together with Lorentz-Berthelot combining rules, they allow one to obtain a more accurate prediction of the coexisting compositions of the mixture. Furthermore, it is shown that the interaction energy in this kind of mixture cannot be properly described by using effective potential models usually considered for pure compounds.     

Equilibration rates and negative absolute temperatures for ultracold atoms in optical lattices

As highly tunable interacting systems, cold atoms in optical lattices are ideal to realize and observe negative absolute temperatures, T<0. We show theoretically that, by reversing the confining potential, stable superfluid condensates at finite momentum and T<0 can be created with low entropy production for attractive bosons. They may serve as "smoking gun" signatures of equilibrated T<0. For fermions, we analyze the time scales needed to equilibrate to T<0. For moderate interactions, the equilibration time is proportional to the square of the radius of the cloud and grows with increasing interaction strengths as atoms and energy are transported by diffusive processes.     

Struktur und Eigenschaften von Cd4SiS6 Zur Kenntnis von Cd4SiSe6

The structure of Cd₄SiS₆ (crystal data see ?Inhaltsübersicht”?) has been solved from single crystal X-ray data. SiS₄ and distorted CdS₄ tetrahedra (Si–S 2.101–2.132 Å, Cd–S 2.510–2.694 Å) are linked three-dimensionally by sharing corners in such a way that 2/3 of the S atoms have 2 Cd + 1 Si as bonded neighbors (pyramidal coordination), the rest is tetrahedrally cordinated by 4 Cd. The new defect tetrahedral structure, which is also representative for the isotypic series Cd₄GeS₆, Hg₄SiS₆ Hg₄GeS₆ and Cd₄GeSe₆, has a strongly distorted packing of the S atoms and shows no close relationship to known types. The Si–S bonds contain only very little π-contributions, similar to the Ge–S and Sn–S bonds in thiogermanates and -stannates. The vibrational spectra of Cd₄SiS₆ are reported and discussed. Cd₄SiSe₆, isotypic with Cd₄SiS₆, has been prepared by reaction of CdSe, Si and Se at 800–1000°.     

History Marginalization Improves Forecasting in Variational Recurrent Neural Networks

Deep probabilistic time series forecasting models have become an integral part of machine learning. While several powerful generative models have been proposed, we provide evidence that their associated inference models are oftentimes too limited and cause the generative model to predict mode-averaged dynamics. Mode-averaging is problematic since many real-world sequences are highly multi-modal, and their averaged dynamics are unphysical (e.g., predicted taxi trajectories might run through buildings on the street map). To better capture multi-modality, we develop variational dynamic mixtures (VDM): a new variational family to infer sequential latent variables. The VDM approximate posterior at each time step is a mixture density network, whose parameters come from propagating multiple samples through a recurrent architecture. This results in an expressive multi-modal posterior approximation. In an empirical study, we show that VDM outperforms competing approaches on highly multi-modal datasets from different domains.     

Darstellung,Struktur und Eigenschaften von Ag10Si3S11

Preparation, Crystal Structure and Properties of Ag₁₀Si₃S₁₁ The novel orange-red thiosilicate Ag₁₀Si₃S₁₁ is formed besides Ag₈SiS₆ by the high - temperature reaction between Ag₂S, Si and S. The single crystal structure analysis shows the compound to be silver orthothiosilicate thiodisilicate-(1:1) Ag₁₀(SiS₄)(Si₂S₇). The mean Si? S bond lengths are 2.137 Å for SiS₄^(4?) and 2.129 Å for the hitherto unknown Si₂S₇^(6?). The cation sublattice is slightly imperfect. inferring a certain mobility of the Ag⁺ ions. Ag₁₀Si₃S₁₁ crystallizes in the triclinic space group P1 . Lattice constants see ?Inhaltsübersicht”?. The vibrational spectrum (IR) shows absorptions within the characteristic spectral regions for asymmetric and symmetric stretching vibrations of the SiS₄ tetrahedra at 490–515 and 423–433 cm^?1.