31 research outputs found
Spin Crossover in a Series of Non-Hofmann-Type Fe(II) Coordination Polymers Based on [Hg(SeCN)3]-; or [Hg(SeCN)4]2-; Building Blocks
This document is the Accepted Manuscript version of a Published Work that appeared in final form in
Inorganic Chemistry, copyright © American Chemical Society after peer review and technical editing by the publisher.
To access the final edited and published work see https://pubs.acs.org/doi/10.1021/acs.inorgchem.1c00802.[EN] Self-assembly of [Hg(SeCN)(4)](2)-tetrahedral building blocks, iron(II) ions, and a series of bis-monodentate pyridyltype bridging ligands has afforded the new heterobimetallic Hg-II-Fe-II coordination polymers {Fe[Hg(SeCN)(3)](2)(4,4'-bipy)(2)}(n) (1), {Fe[Hg(SeCN)(4)](tvp)}(n) (2), {Fe[Hg(SeCN)(3)](2)(4,4'-azpy)(2)}(n) (3), {Fe[Hg(SeCN)(4)](4,4'-azpy)(MeOH)} n (4), {Fe[Hg(SeCN)(4)](3,3'- bipy)} n (5) and {Fe[Hg(SeCN)4](3,3'-azpy)}(n) (6) (4,4-bipy = 4,4'-bipyridine, tvp = trans-1,2-bis(4-pyridyl)ethylene, 4,4'-azpy = 4,4'-azobispyridine, 3,3-bipy = 3,3'bipyridine, 3,3'-azpy = 3,3'-azobispyridine). Single-crystal X-ray analyses show that compounds 1 and 3 display a two-dimensional robust sheet structure made up of infinite linear [(FeL)n]2n+ (L = 4,4'-bipy or 4,4'-azpy) chains linked by in situ formed {[Hg(L)(SeCN)(3)](2)}(2)-anionic dimeric bridges. Complexes 2 and 4-6 define three-dimensional networks with different topological structures, indicating, in combination with complexes 1 and 3, that the polarity, length, rigidity, and conformation of the bridging organic ligand play important roles in the structural nature of the products reported here. The magnetic properties of complexes 1 and 2 show the occurrence of temperature-and light-induced spin crossover (SCO) properties, while complexes 4-6 are in the high-spin state at all temperatures. The current results provide a new route for the design and synthesis of new SCO functional materials with non-Hofmann-type traditional structures.This work was supported by the Natural Science Foundation of China (21671121and 21773006), the Spanish Ministerio de Ciencia e Innovacion (MICINN) and FEDER funds (PID2019-106147GB-I00), and Unidad de Excelencia Maria de Maeztu (CEX2019-000919-M).Cao, T.; Valverde-Muñoz, FJ.; Duan, X.; Zhang, M.; Wang, P.; Xing, L.; Sun, F.... (2021). Spin Crossover in a Series of Non-Hofmann-Type Fe(II) Coordination Polymers Based on [Hg(SeCN)3]-; or [Hg(SeCN)4]2-; Building Blocks. Inorganic Chemistry. 60(15):11048-11057. https://doi.org/10.1021/acs.inorgchem.1c008021104811057601
Reduced Dimension Based Two-Dimensional DOA Estimation with Full DOFs for Generalized Co-Prime Planar Arrays
In this paper, we investigate the problem of two-dimensional (2D) direction-of-arrival (DOA) estimation for generalized co-prime planar arrays. The classic multiple signal classification (MUSIC)-based methods can provide a superior estimation performance, but suffer from a tremendous computational burden caused by the 2D spectral search. To this end, we reduce the 2D problem into a one-dimensional (1D) one and propose a reduced dimension partial spectral search estimation method, which can compress the search region into a small 1D sector. Moreover, the proposed method can utilize the full information of the entire array without degrees-of-freedom loss. Furthermore, an iterative approach is also proposed to reduce complexity and improve performance. Simulation results show that the proposed methods can provide improved performance with substantially reduced complexity, as compared to other state-of-the-art methods
Reduced Dimension Based Two-Dimensional DOA Estimation with Full DOFs for Generalized Co-Prime Planar Arrays
In this paper, we investigate the problem of two-dimensional (2D) direction-of-arrival (DOA) estimation for generalized co-prime planar arrays. The classic multiple signal classification (MUSIC)-based methods can provide a superior estimation performance, but suffer from a tremendous computational burden caused by the 2D spectral search. To this end, we reduce the 2D problem into a one-dimensional (1D) one and propose a reduced dimension partial spectral search estimation method, which can compress the search region into a small 1D sector. Moreover, the proposed method can utilize the full information of the entire array without degrees-of-freedom loss. Furthermore, an iterative approach is also proposed to reduce complexity and improve performance. Simulation results show that the proposed methods can provide improved performance with substantially reduced complexity, as compared to other state-of-the-art methods
Decarboxylative Alkynyl Termination of Palladium-Catalyzed Catellani Reaction: A Facile Synthesis of α‑Alkynyl Anilines via <i>Ortho</i> C–H Amination and Alkynylation
A palladium-catalyzed
synthesis of α-alkynyl anilines is
reported. The reaction proceeds via Catellani <i>ortho</i> C–H amination followed by decarboxylative alkynylative amination.
Different terminal alkyne precursors were screened, and it was found
that alkynyl carboxylic acids were superior over other alkynes, which
led to operationally simple reaction conditions (no gradual addition
of alkynes) and broad substrate scope. The reactivity of three different
components matched well; as a result, relatively higher reaction temperature
could be used, greatly shortening the reaction time to 4 h from the
previously reported 144 h
A Low-Complexity ESPRIT-Based DOA Estimation Method for Co-Prime Linear Arrays
The problem of direction-of-arrival (DOA) estimation is investigated for co-prime array, where the co-prime array consists of two uniform sparse linear subarrays with extended inter-element spacing. For each sparse subarray, true DOAs are mapped into several equivalent angles impinging on the traditional uniform linear array with half-wavelength spacing. Then, by applying the estimation of signal parameters via rotational invariance technique (ESPRIT), the equivalent DOAs are estimated, and the candidate DOAs are recovered according to the relationship among equivalent and true DOAs. Finally, the true DOAs are estimated by combining the results of the two subarrays. The proposed method achieves a better complexity–performance tradeoff as compared to other existing methods
Solving total-variation image super-resolution problems via proximal symmetric alternating direction methods
Abstract The single image super-resolution (SISR) problem represents a class of efficient models appealing in many computer vision applications. In this paper, we focus on designing a proximal symmetric alternating direction method of multipliers (SADMM) for the SISR problem. By taking full exploitation of the special structure, the method enjoys the advantage of being easily implementable by linearizing the quadratic term of subproblems in the SISR problem. With this linearization, the resulting subproblems easily achieve closed-form solutions. A global convergence result is established for the proposed method. Preliminary numerical results demonstrate that the proposed method is efficient and the computing time is saved by nearly 40% compared with several state-of-the-art methods
Sparsity-Based DOA Estimation of Coherent and Uncorrelated Targets With Flexible MIMO Radar
Improved Spatial Differencing Scheme for 2-D DOA Estimation of Coherent Signals with Uniform Rectangular Arrays
This paper proposes an improved spatial differencing (ISD) scheme for two-dimensional direction of arrival (2-D DOA) estimation of coherent signals with uniform rectangular arrays (URAs). We first divide the URA into a number of row rectangular subarrays. Then, by extracting all the data information of each subarray, we only perform difference-operation on the auto-correlations, while the cross-correlations are kept unchanged. Using the reconstructed submatrices, both the forward only ISD (FO-ISD) and forward backward ISD (FB-ISD) methods are developed under the proposed scheme. Compared with the existing spatial smoothing techniques, the proposed scheme can use more data information of the sample covariance matrix and also suppress the effect of additive noise more effectively. Simulation results show that both FO-ISD and FB-ISD can improve the estimation performance largely as compared to the others, in white or colored noise conditions
Computationally Efficient 2D DOA Estimation with Uniform Rectangular Array in Low-Grazing Angle
In this paper, we propose a computationally efficient spatial differencing matrix set (SDMS) method for two-dimensional direction of arrival (2D DOA) estimation with uniform rectangular arrays (URAs) in a low-grazing angle (LGA) condition. By rearranging the auto-correlation and cross-correlation matrices in turn among different subarrays, the SDMS method can estimate the two parameters independently with one-dimensional (1D) subspace-based estimation techniques, where we only perform difference for auto-correlation matrices and the cross-correlation matrices are kept completely. Then, the pair-matching of two parameters is achieved by extracting the diagonal elements of URA. Thus, the proposed method can decrease the computational complexity, suppress the effect of additive noise and also have little information loss. Simulation results show that, in LGA, compared to other methods, the proposed methods can achieve performance improvement in the white or colored noise conditions