A Switch in the Hydrophobic/Hydrophilic Gas-Adsorption Character of Prussian Blue Analogues: An Affinity Control for Smart Gas Sorption

Porous coordination polymers are molecule-based materials presenting a high degree of tunability, which offer many advantages for targeted applications over conventional inorganic materials. This work demonstrates that the hydrophilic/hydrophobic character of Prussian blue analogues having a lipophilic feature may be tuned to optimize the gas adsorption properties. The role of the coordinatively unsaturated metal sites is emphasized through a combination of theoretical and experimental study of water, ethanol, and n-hexane adsorption.     

Periodic Néel skyrmion transport

In this work, we have used the MuMax3 software to simulate devices consisting of a ferromagnetic thin film placed over a heavy metal thin film. The devices are two interconnected partial-disks where a Néel domain wall is formed in the disks junction. In our simulations we investigate devices with disk radius $r=50$ nm and different distance d between the disks centers (from $d=12$ nm to $d=2R=100$ nm). By applying strong sinusoidal external magnetic fields, we find a mechanism able to create, annihilate and even manipulate a skyrmion in each side of the device. This mechanism is discussed in terms of interactions between skyrmion and domain wall. The Néel domain wall formed in the center of the device interacts with the Néel skyrmion, leading to a process of transporting a skyrmion from one disk to the other periodically. Our results have relevance for potential applications in spintronics such as logical devices.     

$$\mathcal {F}_\pi $$Fπ-residuality of generalized Baumslag–Solitar groups

Archiv der Mathematik - A generalized Baumslag–Solitar group is a finitely generated group that acts on a tree with infinite cyclic edge and vertex stabilizers. A group G is residually a...     

Comparison of fast field-cycling magnetic resonance imaging methods and future perspectives

ABSTRACT

Fast field-cycling (FFC) nuclear magnetic resonance relaxometry is a well-established method to determine the relaxation rates as a function of magnetic field strength. This so-called nuclear magnetic relaxation dispersion gives insight into the underlying molecular dynamics of a wide range of complex systems and has gained interest especially in the characterisation of biological tissues and diseases. The combination of FFC techniques with magnetic resonance imaging (MRI) offers a high potential for new types of image contrast more specific to pathological molecular dynamics. This article reviews the progress in FFC-MRI over the last decade and gives an overview of the hardware systems currently in operation. We discuss limitations and error correction strategies specific to FFC-MRI such as field stability and homogeneity, signal-to-noise ratio, eddy currents and acquisition time. We also report potential applications with impact in biology and medicine. Finally, we discuss the challenges and future applications in transferring the underlying molecular dynamics into novel types of image contrast by exploiting the dispersive properties of biological tissue or MRI contrast agents.     

Intramolecular Hydroamination of Selenoalkynes to 2-Selenylindoles in the Absence of Catalyst

In this work, a series of 2-chalcogenylindoles was synthesized by an efficient methodology, starting from chalcogenoalkynes, including a previously unreported tellurium indole derivative. For the first time, these 2-substituted chalcogenylindoles were obtained in the absence of metal catalyst or base, under thermal conditions only. In addition, the results described herein represent a methodology with inverse regioselectivity for the chalcogen functionalization of indoles.     

The Landscape of the Spiked Tensor Model

We consider the problem of estimating a large rank-one tensor u ^⊗k ∈ (ℝⁿ)^⊗k , k ≥ 3 , in Gaussian noise. Earlier work characterized a critical signal-to-noise ratio λ  _Bayes = O(1) above which an ideal estimator achieves strictly positive correlation with the unknown vector of interest. Remarkably, no polynomial-time algorithm is known that achieved this goal unless λ ≥ Cn^{(k − 2)/4} , and even powerful semidefinite programming relaxations appear to fail for 1 ≪ λ ≪ n^{(k − 2)/4} . In order to elucidate this behavior, we consider the maximum likelihood estimator, which requires maximizing a degree-k homogeneous polynomial over the unit sphere in n dimensions. We compute the expected number of critical points and local maxima of this objective function and show that it is exponential in the dimensions n , and give exact formulas for the exponential growth rate. We show that (for λ larger than a constant) critical points are either very close to the unknown vector u or are confined in a band of width Θ(λ^{−1/(k − 1)}) around the maximum circle that is orthogonal to u . For local maxima, this band shrinks to be of size Θ(λ^{−1/(k − 2)}) . These “uninformative” local maxima are likely to cause the failure of optimization algorithms. © 2019 Wiley Periodicals, Inc.