As conventional structural materials reach their performance limits, one of the major scientifi c challenges for the 21st century is the development of new high performance, multifunctional materials to support advances in diverse strategic fi elds, ranging from building and transportation to energy and biotechnology. [ 1 ] In the process of evolution, nature has found ingenious ways to produce lightweight, strong, and high-performance materials with exceptional properties and functionalities. [ 2 ] Biological materials, such as tooth, bone, and nacre, are complex, hierarchical, heterogeneous nanocomposites providing superior mechanical properties and biocompatibility. Thus, mimicking the architecture of natural/biological materials and structures is a viable approach for designing new materials.Naturally occurring nacre's remarkably high toughness and resilience, given its composition of brittle, inorganic CaCO 3 and biopolymer proteins, has been widely recognized. Nacre is twice as strong and 1000-fold tougher than its constituents. [3][4][5][6][7] Several mechanisms have been reported that contribute to the strength and toughness of nacre. [4][5][6][7] The layered arrangement of platelet-shaped CaCO 3 crystals and proteins into a "bricks-andmortar" structure is the key to nacre's outstanding mechanical properties. [ 8 ] Platelet-like inorganic building blocks are essential elements in biomimetic artifi cial composites, especially when one aims to create a layered "bricks-and-mortar" micro-and/or nanostructure. In previous studies, however, natural clay minerals, ceramic Al 2 O 3 platelets, and TiO 2 layers were used merely to fabricate biologically inspired composites with high mechanical performance without focusing on other functionalities, such as electrical conductivity and biocompatibility. [ 1-3 , 8-15 ] On the other hand, graphene has attracted considerable interest in recent years owing to its extraordinary material properties. [16][17][18] A two-dimensional lattice of sp 2 -bonded carbon that is only one-atom thick, graphene exhibits remarkably high electrical conductivity, thermal conductivity, and mechanical properties that rival the in-plane values of graphite, making it an excellent candidate as the " bricks" for fabricating nacre-like composites.To date, nanosheets of graphene oxide (GO) or reduced graphene oxide (RGO) have been used as nanofi llers to improve the mechanical and electrical properties of polymers, in which the fi ller content is usually lower than 10 wt%. [19][20][21][22][23][24] For these nanocomposites, full exploitation of the extraordinary properties of graphene is limited by low GO or RGO content. For instance, the highest electrical conductivity of RGO/polymer composites reported is 51.2 S m − 1 , [ 24 ] two orders of magnitudes lower than most pure RGO sheets. On the other hand, for nacre, the platelet-shaped CaCO 3 is the dominant phase with a high content of 95 vol%. [ 3 ] We report the preparation of bio-inspired, nacre-like reduced poly(vinyl alcohol)/graphene oxide (R...

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In this letter, we analyze a two-stage cluster-then-l(1)-optimization approach for sparse representation of a data matrix, which is also a promising approach for blind source separation (BSS) in which fewer sensors than sources are present. First, sparse representation (factorization) of a data matrix is discussed. For a given overcomplete basis matrix, the corresponding sparse solution (coefficient matrix) with minimum l(1) norm is unique with probability one, which can be obtained using a standard linear programming algorithm. The equivalence of the l(1)-norm solution and the l(0)-norm solution is also analyzed according to a probabilistic framework. If the obtained l(1)-norm solution is sufficiently sparse, then it is equal to the l(0)-norm solution with a high probability. Furthermore, the l(1)- norm solution is robust to noise, but the l(0)-norm solution is not, showing that the l(1)-norm is a good sparsity measure. These results can be used as a recoverability analysis of BSS, as discussed. The basis matrix in this article is estimated using a clustering algorithm followed by normalization, in which the matrix columns are the cluster centers of normalized data column vectors. Zibulevsky, Pearlmutter, Boll, and Kisilev (2000) used this kind of two-stage approach in underdetermined BSS. Our recoverability analysis shows that this approach can deal with the situation in which the sources are overlapped to some degree in the analyzed domain and with the case in which the source number is unknown. It is also robust to additive noise and estimation error in the mixing matrix. Finally, four simulation examples and an EEG data analysis example are presented to illustrate the algorithm's utility and demonstrate its performance.

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It is well accepted that the microwave absorption performance (MAP) of carbon nanotubes (CNTs) can be enhanced via coating magnetic nanoparticles on their surfaces. However, it is still unclear if the magnetic coating structure has a significant influence on the microwave absorption behavior. In this work, nano-FeO compact-coated CNTs (FCCs) and FeO loose-coated CNTs (FLCs) are prepared using a simple solvothermal method. The MAP of the FeO-coated CNTs is shown to be adjustable via controlling the FeO nanocoating structure. The results reveal that the overall MAP of coated CNTs strongly depends on the magnetic coating structure. In addition, the FCCs show a much better MAP than the FLCs. It is shown that the microwave absorption difference between the FLCs and FCCs is due to the disparate complementarities between the dielectric loss and the magnetic loss, which are related to the coverage density of FeO nanoparticles on the surfaces of CNTs. For FCCs, the mass ratio of CNTs to Fe is then optimized to maximize the effective complementarities between the dielectric loss and the magnetic loss. Finally, a comparison is made with the literature on FeO-carbon-based composites. The FCCs at the optimized CNT to Fe ratio in the present work show the most effective specific RL (28.7 dB·mm) and the widest effective bandwidth (RL < -10 dB) (8.3 GHz). The excellent MAP of the as-prepared FCC sample is demonstrated to result from the consequent dielectric relaxation process and the improved magnetic loss. Consequently, the structure-property relationship revealed is significant for the design and preparation of CNT-based materials with effective microwave absorption.