Network Skeleton Research Articles

Preparation a three-dimensional hierarchical graphene/stearic acid as a phase change materials for thermal energy storage

Three-dimensional hierarchical graphene (3DHG) was compounded with stearic acid (SA) to obtain SA/3DHG composite phase change materials (PCMs). The specific surface area and pore volume of 3DHG are 393 m2 g−1 and 0.57 m3 g−1. The phase-transition temperatures of SA/3DHG composites keep at 69 ± 1 °C with different adding amounts of 3DHG, meanwhile SA/3DHG-3 possesses the melting enthalpy of 189.7 J·g−1 and solidifying enthalpy of 188.8 J·g−1. 3DHG shows significant enhancement on the thermal properties and shape stability of SA. The thermal conductivity of SA/3DHG-3 reaches to 0.93 W·m−1·K−1, which is as high as 2.8 times of pure SA (0.33 W·m−1·K−1). The investigations of XRD and FTIR indicate that no chemical but physical combination occurs between SA and graphene. 3DHG has substantial meso-porous/macro-porous structure for packaging SA to form the irregular core–shell structure. The hierarchical pores are also beneficial to the graded thermal transfer inside SA/3DHG composite PCMs. The efficiency of heating process from 25 °C to 90 °C was improved by about 57%. Furthermore, the 3D network skeleton built up by graphene sheets can form an effective and connected heat transfer paths for SA, thus improves the endothermic and exothermic efficiency of SA/3DHG composite PCMs. This work emphasizes the 3D hierarchical structure of graphene and provides a promising way to prepare composite PCMs with high large storage density and heat transfer efficiency.

Fiber-supported alumina separator for achieving high rate of high-temperature lithium-ion batteries

More and more application scenarios of rechargeable batteries like lithium-ion batteries are set up in high-temperature environments, such as large-scale energy storage, aerospace, oil extraction industry, etc. Besides of electrolyte, the separator is also a vital part of the battery's sustainable operation at high temperature working condition, however traditional polyolefin separators and even ceramic-coated polyolefin separators have poor thermal stability. This article provides a fiber-supported aluminum oxide separator with improved flexibility and thermal stability because of the introduced flexible SiC fiber network skeleton. The ceramic separator exhibits electrochemical performance equivalent to commercial separators at room temperature. What's more, with high-temperature electrolyte system, its conductivity at 120 °C reaches 5.12 mS cm−1, which is 3 times higher than that at room temperature, so that the LiFePO4 half-cell has excellent rate performance that still maintains a specific capacity of 140 mAh g−1 for 200 cycles under a rate of 20C at 120 °C. Specially, the half-cell containing the high temperature stable fiber-supported aluminum oxide separator realizes cycles of charging at a high temperature with high rate as 20C and discharging at a room temperature with normal rate of 1C, which is of great guiding significance to practical application.

Facile Fabrication of Mechanically Strong and Thermal Resistant Polyimide Aerogels with an Excess of Cross-Linker

ABSTRACT In this study, we report the effect of the number of formulated repeat units (n), the type of diamine and the cross-linker content on pore morphology, structure and mechanical properties of vacuum-dried polyimide aerogels. Morphology observations demonstrate that an excess of cross-linker is conducive to increase the pore size, strengthen and stiffen the network to avoid the collapse and suppress the irreversible shrinkage during the vacuum drying procedure. For 2,2'-dimethylbenzidine derived aerogels, the pore diameter increases with increasing cross-linker content or decreasing n. The shrinkage is higher in aerogels derived from 4,4'-oxidianiline due to the chain rigidity and mobility difference compared to rigid diamine-based aerogels, resulting in lower porosity and higher density. Compared with those previously reported aerogels with the same backbone chemistries, vacuum dried polyimide aerogels herein show higher compressive strength and Young’s modulus resulting from higher density and coarser skeleton networks. More importantly, isothermal aging results reveal very low increasement of shrinkage and density occurring over the aging period, which even can be ignored. The facile, low-cost vacuum drying procedure, dramatically improved mechanical properties, and superior thermal resistance will broaden the practical applications of polyimide aerogels.

Preparation of High Hardness Transparent Coating with Controllable Refractive Index by Sol-Gel Technology

SiO2/ZrO2 and SiO2/ZrO2/Al2O3 composite organic–inorganic coatings were prepared by the sol-gel technology. The structure of the coating was characterized by IR, particle size analyzer, SEM, and AFM, respectively. The results showed that ZrO2, SiO2 (inorganic component), and siloxane had undergone a hydrolytic condensation reaction, and the composite organic–inorganic coatings were formed with -O-M-O- (M is Si, Zr) as molecular skeleton network structure. Adding an appropriate ratio of ZrO2 sol, no agglomeration and phase separation occurred, which could significantly improve the refractive index, hardness, and light transmittance of the coatings. Al2O3 sol could greatly improve the friction resistance of the composite organic–inorganic coatings, and the Bayer ratio of the composite coatings could reach 7.86. By adjusting the proportioning of composite sol solution, the refractive index of the composite transparent coatings could be controlled from 1.52 to 1.65.

Microstructure and mechanical properties of Cu joints soldered with a Sn-based composite solder, reinforced by metal foam

In this study, Ni foam, Cu coated Ni foam and Cu-Ni alloy foams were used as strengthening phases for pure Sn solder. Cu-Cu joints were fabricated by soldering with these Sn-based composite solders at 260 °C for different times. The tensile strength of pure Sn solder was improved significantly by the addition of metal foams, and the Cu-Ni alloy/Sn composite solder exhibited the highest tensile strength of 50.32 MPa. The skeleton networks of the foams were gradually dissolved into the soldering seam with increasing soldering time, accompanied by the massive formation of (Cu,Ni)6Sn5 phase in the joint. The dissolution rates of Ni foam, Cu coated Ni foam and Cu-Ni alloy foams into the Sn matrix increased successively during soldering. An increased dissolution rate of the metal foam leads to an increase in the Ni content in the soldering seam, which was found to be beneficial in refining the (Cu,Ni)6Sn5 phase and inhibiting the formation of the Cu3Sn IMC layer on the Cu substrate surface. The average shear strength of the Cu joints was improved with increasing soldering time, and a shear strength of 61.2 MPa was obtained for Cu joints soldered with Cu-Ni alloy/Sn composite solder for 60 min.

Skeleton Network Extraction and Analysis on Bicycle Sharing Networks

Skeleton network extraction has been adopted unevenly in transportation networks whose nodes are always represented as spatial units. In this article, the TPks skeleton network extraction method is proposed and applied to bicycle sharing networks. The method aims to reduce the network size while preserving key topologies and spatial features. The authors quantified the importance of nodes by an improved topology potential algorithm. The spatial clustering allows to detect high traffic concentrations and allocate the nodes of each cluster according to their spatial distribution. Then, the skeleton network is constructed by aggregating the most important indicated skeleton nodes. The authors examine the skeleton network characteristics and different spatial information using the original networks as a benchmark. The results show that the skeleton networks can preserve the topological and spatial information similar to the original networks while reducing their size and complexity.

Extracting Skeleton of the Global Terrorism Network Based on m-Modified Topology Potential

Skeleton network extraction is a crucial context in studying the core structure and essential information on complex networks. The objective of this paper is to introduce the novel network extraction method, namely, TPKS-skeleton, for investigating the global terrorism network. Our method aims to reduce the network’s size while preserving key topology and spatial features. A TPKS-skeleton comprises three steps: node evaluation, similarity-based clustering, and skeleton network reconstruction. The importance of skeleton nodes is quantified by the improved topology potential algorithm. Similarity-based clustering is then integrated to allow detecting high incident concentrations and allocating the important nodes according to the event features and spatial distribution. Finally, the skeleton network can be reconstructed by aggregating high-influential nodes from each cluster and their simplified edges. To verify the efficiency of the proposed method, we carry out three classes of a network assessment framework: node-equivalence assessment, network-equivalence assessment, and spatial information assessment. For each class, various assessment indexes were performed using the original network as a benchmark. The results verify that our proposed TPKS-skeleton outperforms other competitive methods in particular node-equivalence by Spearman rank correlation and high network structural-equivalence defined by quadratic assignment procedure. In the spatial perspective, the TPKS-skeleton network preserves reasonably all kinds of spatial information. Our study paves the way to extract the optimal skeleton of the global terrorism network, which might be beneficial for counterterrorism and network analysis in wider areas.

Hierarchical polypyrrole/graphene/melamine composite foam for highly compressible all-solid-state supercapacitors

Nanostructured carbon materials have shown promising applications for energy storage because of their high capacitive characteristic. However, developing three-dimensional (3D) hierarchical carbon materials with both high compressibility and capacitance is still challenging. Herein, we report the fabrication of hierarchical polypyrrole (PPy)/graphene (reduced graphene oxide (G) and holey reduced graphene oxide (h-G))/melamine composite foam through a simple template method. By systematically optimizing the mass ratios of the G/h-G and the sizes of the PPy nanoparticles (PPy NPs), the as-prepared composite electrode displays a gravimetric capacitance of 422.6 F g−1 at a current density of 0.5 A g−1. Due to the interconnected h-G/G network and elastic melamine foam (MF) skeleton, the as-prepared composite electrode also shows compressible performance, which can be compressed to a strain of 60% and completely recover to its original shape when released. When the composite electrodes are assembled to a compressible supercapacitor which shows a stable capacitance under different compressive strains (0%, 25%, 50% and 75%) and a long-term compression test at 50% strain for 100 cycles. Therefore, the successful preparation of compressible composite electrode should open many opportunities in compressible and durable energy storage devices.

Critical Network Structures and Medical Ecology Mechanisms Underlying Human Microbiome-Associated Diseases.

SummaryA fundamental problem in studies on human microbiome-associated diseases (MADs) is to understand the relationships between microbiome structures and health status of hosts. For example, species diversity metrics have been routinely evaluated in virtually all studies on MADs, yet a recent meta-analysis revealed that, in only approximately one-third of the cases, diversity and diseases were related. In this study, we ask whether Hubbell's neutral theory (supplemented with the normalized stochasticity ratio [NSR]) or critical microbiome network structures may offer better alternatives. Whereas neutral theory and NSR focus on stochastic processes, we use core/periphery and high-salience skeleton networks to evaluate deterministic, asymmetrical niche effects, assuming that all species or their interactions were not “born” equal and focusing on non-neutral, critical network structures. We found that properties of critical network structures are more indicative of disease effects. Finally, seven findings (mechanisms, interpretations, and postulations) regarding medical ecology mechanisms underlying MADs were summarized.

A new sight into the glass forming ability caused by doping on Ba- and Ti-site in BaTi2O5 glass

La- and Nb-doped BaTi2O5 (BT2) spherical glasses were prepared by a containerless aerodynamic levitation method and their glass-forming regions were established. It is found that La-doping on the Ba-site (network-modifier) and Nb-doping on the Ti-site (network-former) show distinct difference in the glass-forming region: less than 10 % La can replace Ba whereas 40 % Nb can incorporate into BT2 glass. The distinction in glass-forming ability induced by La- and Nb-doping is discussed mainly from the structural arrangement of the glass. Raman spectroscopy analysis shows that La-doping elongates the short Ti–O bonds in the distorted [TiO5] polyhedra and thus relaxes the network. Nb-doping introduces [NbO6] polyhedra into BT2 and there exists a critical doping level (20 %), below which incorporation of Nb into BT2 relaxes the [TiOn] polyhedra by shortening the long Ti–O bond and above which [NbO6] starts to participate in the network skeleton construction resulting in a dramatic change in the glass structure, which is supported by the dramatic change in the exothermic peak on the DTA curves. This work triggers the speculation that the network-modifiers in BT2 glass possess a very important role in the structure of network-former skeleton than those in glasses based on traditional network-former oxides such as SiO2, GeO2 and B2O3, which may provide a useful strategy for modifying the properties of these novel glasses by chemical doping.

Experimental investigation of a new weak-gel-type clay-free and water-based drilling fluid with high-temperature and high-salt resistance for determining its optimized formulation

ABSTRACT In this study, based on a viscosity and gel-strength improving agent synthesized in a laboratory, a weak-gel-type clay-free and water-based drilling fluid was developed experimentally to optimize the selection of filtration loss reducer, inhibitor, plugging agent, and lubricant. Performance evaluation tests demonstrated its stable performance at temperatures up to 160°C and salt contents up to 30%. In addition, it exhibits excellent inhibition and lubricity; the rolling recovery rate of cuttings is as high as 93.6%, and the extreme pressure lubrication coefficient is as low as 0.07. The internal network structure of the weak-gel-type clay-free and water-based drilling fluid under different temperatures and salt contents was investigated through environmental scanning electron microscopy. Results showed that its microstructure comprises a three-dimensional network, in which sol particles are wrapped or embedded at the network structure nodes. Its network density and skeleton became thinner as temperature increased, whereas they became coarse and loose as the salt content increased. However, it still maintained a three-dimensional network structure at temperatures up to 160°C and salt contents up to 30%, which enable it to exhibit a unique rheological property. Results of this study provide a new drilling fluid technique for multilateral and horizontal well drilling operations in high-temperature and high-salt environments.

Deep Temporal Analysis for Non-Acted Body Affect Recognition

Affective computing is a field of great interest in many computer vision applications, including video surveillance, behaviour analysis, and human-robot interaction. Most of the existing literature has addressed this field by analysing different sets of face features. However, in the last decade, several studies have shown how body movements can play a key role even in emotion recognition. The majority of these experiments on the body are performed by trained actors whose aim is to simulate emotional reactions. These unnatural expressions differ from the more challenging genuine emotions, thus invalidating the obtained results. In this paper, a solution for basic non-acted emotion recognition based on 3D skeleton and Deep Neural Networks (DNNs) is provided. The proposed work introduces three majors contributions. First, unlike the current state-of-the-art in non-acted body affect recognition, where only static or global body features are considered, in this work also temporal local movements performed by subjects in each frame are examined. Second, an original set of global and time-dependent features for body movement description is provided. Third, to the best of out knowledge, this is the first attempt to use deep learning methods for non-acted body affect recognition. Due to the novelty of the topic, only the UCLIC dataset is currently considered the benchmark for comparative tests. On the latter, the proposed method outperforms all the competitors.

Super-hydrophobic poly (lactic acid) by controlling the hierarchical structure and polymorphic transformation

Focus on the design and execution of super-hydrophobic strategies, the phase control methodology, that is, solvent-volatilization and crystallization induced phase separation at low temperature (−15 °C), is proposed to construct three dimension (3D) poly(lactic-acid) (PLA) porous structures, denser stereo-complexed crystals (SCs) protrusions and bi-continuous SCs fibrillary networks in poly(L-lactic acid)/poly(D-lactic acid) (PLLA/PDLA) blends for the first time. We show that generating hierarchical structures are keys to enable the super-hydrophobicity, instead of traditionally adding fillers. By comparing the interfacial configurations of PLA pores with different PDLA content, it is shown that numerous SCs protrusions on the skeleton of 3D pores with 30% PDLA, especially for the bi-continuous SCs fibrillary networks with 50% PDLA, very different from the porous morphology of pure PLLA. The controllable PLA chains sharply facilitate the formation of SCs protrusions by the hydrogen bonding, which give rise to the limited time to growth ordered and large-sized lamellae. Of particular interests are our first establishments of developing uniform SCs protrusions on the internal 3D porous skeleton and multi-scale 3D fibrillary network structure for stereo-complex PLA, which afford the inner hydrophobic coincidence with the surface even after processed one-hour (1 h) by ultrasound in water. Therefore, we hypothesize that the key factor influencing super-hydrophobicity of the PLLA/PDLA films are 3D pores and bi-continuous SCs fibrillary networks combined with the roughly crystalline surface structure resembling rugged protrusions, leading to the water contact angle (CA) up to 155°. Moreover, the icing-resistance and thermal degradation behavior are highly obvious. This work firstly pave the way to polymer-derived networks with combination of self-constructed crystallization protrusions and bi-continuous 3D fibrillary network structure by hydrogen bonding for elegant implementation of super-hydrophobic characteristics other than the traditional addition of fillers.

Preparation and Adsorption Properties of Magnetic Composite Microspheres Containing Metal–Organic Double Network Structure

Acrylamide, sodium alginate and ferroferric oxide were used as raw materials to prepare polyacrylamide/calcium alginate/ferroferric oxide magnetics composite microspheres with metal–organic double network skeleton structure. Chemical structure, thermal stability, crystallization ability, specific surface area and pore structure, surface morphology of the microspheres were characterized by Fourier transform infrared spectroscopy (FTIR), thermogravimetric analyzer (TGA), X-ray diffractometer (XRD), specific surface area analyzer (BET) and scanning electron microscope (SEM). The effects of pH value, temperature, amount of adsorbent and triiron tetroxide on the adsorption of methylene blue (MB) were studied. At the same time, the experiments of reusability were also carried out multiple adsorption/desorption cycles on the adsorption of MB by microspheres. The maximum adsorption capacity was 71.6 mg/g. Adsorption kinetics studies show that the quasi-first-order kinetic model can be better fit the experimental data, and the Freundlich isotherm model fits a good correlation with MB adsorption. In addition, after 5 adsorption/desorption cycles, the removal rate of the adsorbent was maintained at about 94.6%, indicating that it can be reused.

Siloxane based copolymer sulfur as binder-free cathode for advances lithium-sulfur batteries

One of the reasons why lithium-sulfur batteries have not yet been commercialized is a great attenuation of the capacity, although their theoretical capacity is ultrahigh. To alleviate this problem, we developed multifunctional organic matter, 3-aminopropyltriethoxysilane (APS), for preparing a uniform hybrid consists of silica 3D network skeleton and copolymerized sulfur nanoparticles (cpS). In this hybrid, abundant amidogen in APS induced polymerization with sulfur, which formed uniform copolymerized sulfur nanoparticles (nano sulfur), restraining the shuttle effect of polysulfides. Meanwhile, polycondensation APS not only acted as an efficiently binder, affording compact cathodes, but also formed a stable 3D silica structure to encapsulate sulfur nanoparticles, relieving the volume change of sulfur. Consequently, this binder-free cpS composite exhibited much enhanced electrochemical performances, including a high capacity of 1187.8 mAh·g−1 at 0.1 C and a low capacity fading of 0.0654% per cycle for 500 cycles at 1 C. This study paved the way for high-energy-density batteries by simply applying a low-cost, environmentally-friendly, powerful network polymer cathode material.

SCNrank: spectral clustering for network-based ranking to reveal potential drug targets and its application in pancreatic ductal adenocarcinoma

BackgroundPancreatic ductal adenocarcinoma (PDAC) is the most common pancreatic malignancy. Due to its wide heterogeneity, PDAC acts aggressively and responds poorly to most chemotherapies, causing an urgent need for the development of new therapeutic strategies. Cell lines have been used as the foundation for drug development and disease modeling. CRISPR-Cas9 plays a key role in every step-in drug discovery: from target identification and validation to preclinical cancer cell testing. Using cell-line models and CRISPR-Cas9 technology together make drug target prediction feasible. However, there is still a large gap between predicted results and actionable targets in real tumors. Biological network models provide great modus to mimic genetic interactions in real biological systems, which can benefit gene perturbation studies and potential target identification for treating PDAC. Nevertheless, building a network model that takes cell-line data and CRISPR-Cas9 data as input to accurately predict potential targets that will respond well on real tissue remains unsolved.MethodsWe developed a novel algorithm ‘Spectral Clustering for Network-based target Ranking’ (SCNrank) that systematically integrates three types of data: expression profiles from tumor tissue, normal tissue and cell-line PDAC; protein-protein interaction network (PPI); and CRISPR-Cas9 data to prioritize potential drug targets for PDAC. The whole algorithm can be classified into three steps: 1. using STRING PPI network skeleton, SCNrank constructs tissue-specific networks with PDAC tumor and normal pancreas tissues from expression profiles; 2. With the same network skeleton, SCNrank constructs cell-line-specific networks using the cell-line PDAC expression profiles and CRISPR-Cas 9 data from pancreatic cancer cell-lines; 3. SCNrank applies a novel spectral clustering approach to reduce data dimension and generate gene clusters that carry common features from both networks. Finally, SCNrank applies a scoring scheme called ‘Target Influence score’ (TI), which estimates a given target’s influence towards the cluster it belongs to, for scoring and ranking each drug target.ResultsWe applied SCNrank to analyze 263 expression profiles, CRPSPR-Cas9 data from 22 different pancreatic cancer cell-lines and the STRING protein-protein interaction (PPI) network. With SCNrank, we successfully constructed an integrated tissue PDAC network and an integrated cell-line PDAC network, both of which contain 4414 selected genes that are overexpressed in tumor tissue samples. After clustering, 4414 genes are distributed into 198 clusters, which include 367 targets of FDA approved drugs. These drug targets are all scored and ranked by their TI scores, which we defined to measure their influence towards the network. We validated top-ranked targets in three aspects: Firstly, mapping them onto the existing clinical drug targets of PDAC to measure the concordance. Secondly, we performed enrichment analysis to these drug targets and the clusters there are within, to reveal functional associations between clusters and PDAC; Thirdly, we performed survival analysis for the top-ranked targets to connect targets with clinical outcomes. Survival analysis reveals that overexpression of three top-ranked genes, PGK1, HMMR and POLE2, significantly increases the risk of death in PDAC patients.ConclusionSCNrank is an unbiased algorithm that systematically integrates multiple types of omics data to do potential drug target selection and ranking. SCNrank shows great capability in predicting drug targets for PDAC. Pancreatic cancer-associated gene candidates predicted by our SCNrank approach have the potential to guide genetics-based anti-pancreatic drug discovery.

Control of the particle microstructure during the synthesis of bulk‐polymerized transparent methacrylate‐acrylonitrile‐butadiene‐styrene resin

AbstractA series of methacrylate‐acrylonitrile‐butadiene‐styrene (MABS) resins was prepared using bulk polymerization. The polarity of the continuous phase and the compatibility of two phases were changed by adjusting the methyl methacrylate (MMA) content, choosing values that were close to styrene‐butadiene rubber solubility value. The possibility of controlling the microstructure of the MABS resin by changing the polarity of the components and the compatibility of two phases was assessed. The dynamic mechanical analysis shows that the compatibility of two phases varies with the MMA content. The morphological analysis shows that increasing MMA contents results in a gradual decrease in the sub‐inclusion structure with a network skeleton of rubber particles, and that all the particles become solid rubber when the MMA content reaches 75%. The sub‐inclusion structure reappears but does not have a network skeleton when the MMA content is 90%. The impact strength and morphological analysis indicate that the solid rubber particles and the sub‐inclusion structure with a network skeleton provide excellent toughness, while the sub‐inclusion structure without a network skeleton does not. In contrast, the transmittance of the ABS resin first increased and then decreased with increasing MMA content.

Preparation of Chiral Stationary Phase by Dynamic Grafting BSA on the Organic-Silica Hybrid Monolithic Column Based on Schiff-Base Reaction

The prepared hybrid monolithic column (HMC) with epoxy groups on the surface was reacted with polyethyleneimine, and then reacted with glutaraldehyde. The chiral monolithic column was prepared by dynamically grafting bovine serum albumin (BSA) onto the newly modified HMC by Schiff-base reaction. The obtained chiral monolithic column was characterized by SEM and IR. The effects of the concentration of the BSA solution, flow rate and grafting time on the grafting amount were optimized. The properties of chiral monolithic column were tested with benzoin as the chiral object. The results showed that the obtained grafting amount of BSA was 56.1 mg/g under the optimized conditions. The chiral monolithic column had homogeneous network skeleton structure and good reusability. The method of preparing chiral monolithic column had good reproducibility.

Synthesis of monolithic carbon aerogels with high mechanical strength via ambient pressure drying without solvent exchange

A simple, fast and cost-effective method for monolithic carbon aerogels (CAs) preparation was proposed through sol-gel polycondensation of resorcinol with formaldehyde in a basic aqueous solution followed by ambient pressure drying without solvent exchange, and carbonization. The microstructure and network strength of CAs were tailored by adjusting the catalyst concentration ([resorcinol]/[sodium carbonate] in the range of 300–2000), water content ([deionized water]/[resorcinol] equals to 17 and 24, respectively), and gelation temperature (Tgel in the range of 30−90 °C). Resultantly, the CAs with a wide range of density (0.30–1.13 g/cm3), high specific surface area (465−616 m2/g), high compressive strength (6.5–147.4 MPa) and low thermal conductivity (0.065-0.120 Wm−1 K−1) were obtained in this work. Moreover, the large-sized CAs (100 × 100 × 20 mm3) can also be prepared by this method since the formed robust skeleton network can resist shrinkage/collapse of pore structure and prevent cracking during drying. The improved mechanical strength and monolithic forming abilities could be mainly attributed to the uniform arrangement of carbon particles and pores, fine particle size, abundant network structure and enhanced particle neck.

Microstructure evolution and damage mechanism of layered titanium matrix composites under tensile loading

In order to better guide the design of layered metal matrix composites, the failure mechanism of a kind of Ti based layered composite was investigated. The results showed that this layered composites possessed better uniform deformation ability compared with the materials of each layer. Increasing the hard composite layer thickness led to the enhancement of tensile strength but descend of deformation ability. The micro-cracks in the Ti layer provided plasticity, while the unique network microstructure in the composite layer restrained the slip bands from the network central region. These slip bands propagated through network skeleton and caused TiB whiskers fracture and interface debonding between the metallic matrix and TiB whiskers. Numerical simulation indicated that interface cracks in the composite layer were prone to propagate first. Larger composite layer thickness led to crack convergence more likely to occur and thus resulted in the drop of ductility with increasing the hard composite layer thickness.