Structural Analysis of Nanoscale Network Materials Using Graph Theory

Biomimetic Aramid Nanofiber/β-FeOOH Composite Coating for Polypropylene Separators in Lithium-Sulfur Batteries

Aramid nanofibers (ANFs), with attractive mechanical and thermal properties, have attracted much attention as key building units for the design of high-performance composite materials. Although great progress has been made, the potential of ANFs as fibrous protein mimetics for controlling the growth of inorganic materials has not been fully revealed, which is critical for avoiding phase separation associated with typical solution blending. In this work, we show that ANFs could template the oriented growth of β-FeOOH nanowhiskers, which enables the synthesis of ANFs/β-FeOOH hybrids as composite coatings for polypropylene (PP) separators in Li-S batteries. The modified PP separator exhibits enhanced mechanical properties, heightened thermal performance, optimized electrolyte wettability, and improved ion conductivity, leading to superior electrochemical properties, including high initial specific capacity, better rate capability, and long cycling stability, which are superior to those of the commercial PP separators. Importantly, the addition of β-FeOOH to ANFs could further contribute to the suppression of lithium polysulfide shuttling by chemical immobilization, inhibition of the growth of lithium dendrites because of the intrinsic high modulus and hardness, and promotion of reaction dynamics due to the catalytic effect. We believe that our work may provide a potent biomimetic pathway for the development of advanced battery separators based on ANFs.

A Soft-Fiber Bioelectronic Device with Axon-Like Architecture Enables Reliable Neural Recording In Vivo under Vigorous Activities

Implantable neural devices that record neurons in various states, including static states, light activities such as walking, and vigorous activities such as running, offer opportunities for understanding brain functions and dysfunctions. However, recording neurons under vigorous activities remains a long-standing challenge because it leads to intense brain deformation. Thus, three key requirements are needed simultaneously for neural devices, that is, low modulus, low specific interfacial impedance, and high electrical conductivity, to realize stable device/brain interfaces and high-quality transmission of neural signals. However, they always contradict each other in current material strategies. Here, a soft fiber neural device capable of stably tracking individual neurons in the deep brain of medium-sized animals under vigorous activity is reported. Inspired by the axon architecture, this fiber neural device is constructed with a conductive gel fiber possessing a network-in-liquid structure using conjugated polymers and liquid matrices and then insulated with soft fluorine rubber. This strategy reconciles the contradictions and simultaneously confers the fiber neural device with low modulus (300 kPa), low specific impedance (579 kΩ µm2), and high electrical conductivity (32 700 S m-1) - ≈1-3 times higher than hydrogels. Stable single-unit spike tracking in running cats, which promises new opportunities for neuroscience is demonstrated.

Permanent fluidic magnets for liquid bioelectronics

Brownian motion allows microscopically dispersed nanoparticles to be stable in ferrofluids, as well as causes magnetization relaxation and prohibits permanent magnetism. Here we decoupled the particle Brownian motion from colloidal stability to achieve a permanent fluidic magnet with high magnetization, flowability and reconfigurability. The key to create such permanent fluidic magnets is to maintain a stable magnetic colloidal fluid by using non-Brownian magnetic particles to self-assemble a three-dimensional oriented and ramified magnetic network structure in the carrier fluid. This structure has high coercivity and permanent magnetization, with long-term magnetization stability. We establish a scaling theory model to decipher the permanent fluid magnet formation criteria and formulate a general assembly guideline. Further, we develop injectable and retrievable permanent-fluidic-magnet-based liquid bioelectronics for highly sensitive, self-powered wireless cardiovascular monitoring. Overall, our findings highlight the potential of permanent fluidic magnets as an ultrasoft material for liquid devices and systems, from bioelectronics to robotics.

Beyond nothingness in the formation and functional relevance of voids in polymer films

Voids-the nothingness-broadly exist within nanomaterials and impact properties ranging from catalysis to mechanical response. However, understanding nanovoids is challenging due to lack of imaging methods with the needed penetration depth and spatial resolution. Here, we integrate electron tomography, morphometry, graph theory and coarse-grained molecular dynamics simulation to study the formation of interconnected nanovoids in polymer films and their impacts on permeance and nanomechanical behaviour. Using polyamide membranes for molecular separation as a representative system, three-dimensional electron tomography at nanometre resolution reveals nanovoid formation from coalescence of oligomers, supported by coarse-grained molecular dynamics simulations. Void analysis provides otherwise inaccessible inputs for accurate fittings of methanol permeance for polyamide membranes. Three-dimensional structural graphs accounting for the tortuous nanovoids within, measure higher apparent moduli with polyamide membranes of higher graph rigidity. Our study elucidates the significance of nanovoids beyond the nothingness, impacting the synthesis‒morphology‒function relationships of complex nanomaterials.

Hierarchical and reconfigurable interfibrous interface of bioinspired Bouligand structure enabled by moderate orderliness

Introducing natural Bouligand structure into synthetics is expected to develop high-performance structural materials. Interfibrous interface is critical to load transfer, and mechanical functionality of bioinspired Bouligand structure yet receives little attention. Here, we propose one kind of hierarchical and reconfigurable interfibrous interface based on moderate orderliness to mechanically reinforce bioinspired Bouligand structure. The interface imparted by moderate alignment of adaptable networked nanofibers hierarchically includes nanofiber interlocking and hydrogen-bonding (HB) network bridging, being expected to facilitate load transfer and structural stability through dynamic adjustment in terms of nanofiber sliding and HB breaking-reforming. As one demonstration, the hierarchical and reconfigurable interfibrous interface is constructed based on moderate alignment of networked bacterial cellulose nanofibers. We show that the resultant bioinspired Bouligand structural material exhibits unusual strengthening and toughening mechanisms dominated by interface-microstructure multiscale coupling. The proposed interfibrous interface enabled by moderate orderliness would provide mechanical insight into the assembly of widely existing networked nanofiber building blocks toward high-performance macroscopic bioinspired structural assemblies.

Bioinspired pullulan-starch nanoplatelets nanocomposite films with enhanced mechanical properties

Inspired by the leaf-vein network structure, the pullulan-starch nanoplatelets (SNPs) bioinspired films with enhanced strength and toughness were successfully fabricated through a water evaporation-induced self-assembly technique. SNPs (SNP200 and SNP600) of two sizes were separated by differential centrifugation. Interactions between SNPs and pullulan during drying resulted in the vein-like network structure in both nanocomposite films when the appropriate amounts of SNP200 or SNP600 were added to pullulan, respectively. The TS and toughness values of pullulan with 1 % w/w SNP200 films reached up to 51.05 MPa and 69.65 MJ·m-3, which were 86 % and 223 % higher than those of the neat pullulan films, respectively. Moreover, the TS and toughness values of pullulan-SNP200 were significantly higher than those of pullulan-SNP600 films, when SNP content exceeded the 1 % w/w level. By applying a graph theory, the network structures were found to correlate with the mechanical properties of the pullulan-SNPs bioinspired films. The new strategy for designing starch nanoplatelets-based edible films that combine mechanical strength and toughness holds promises for the development of novel biobased composite materials for food packaging application.

Network of cyano-p-aramid nanofibres creates ultrastiff and water-rich hydrospongels

The structure-property paradox of biological tissues, in which water-rich porous structures efficiently transfer mass while remaining highly mechanically stiff, remains unsolved. Although hydrogel/sponge hybridization is the key to understanding this phenomenon, material incompatibility makes this a challenging task. Here we describe hydrogel/sponge hybrids (hydrospongels) that behave as both ultrastiff water-rich gels and reversibly squeezable sponges. The self-organizing network of cyano-p-aramid nanofibres holds approximately 5,000 times more water than its solid content. Hydrospongels, even at a water concentration exceeding 90 wt%, are hard as cartilage with an elastic modulus of 50-80 MPa, and are 10-1,000 times stiffer than typical hydrogels. They endure a compressive strain above 85% through poroelastic relaxation and hydrothermal pressure at 120 °C. This performance is produced by amphiphilic surfaces, high rigidity and an interfibrillar, interaction-driven percolating network of nanofibres. These features can inspire the development of future biofunctional materials.

Nanoscale Three-Dimensional Network Structure of a Mesoporous Particle Unveiled via Adaptive Multidistance Coherent X-ray Tomography

Mesoporous nanoparticles provide rich platforms to devise functional materials by customizing the three-dimensional (3D) structures of nanopores. With the pore network as a key tuning parameter, the noninvasive and quantitative characterization of these 3D structures is crucial for the rational design of functional materials. This has prompted researchers to develop versatile nanoprobes with a high penetration power to inspect various specimens sized a few micrometers at nanoscale 3D resolutions. Here, with adaptive phase retrievals on independent data sets with different sampling frequencies, we introduce multidistance coherent X-ray tomography as a noninvasive and quantitative nanoprobe to realize high-resolution 3D imaging of micrometer-sized specimens. The 3D density distribution of an entire mesoporous silica nanoparticle was obtained at 13 nm 3D resolution for quantitative physical and morphological analyses of its 3D pore structure. The morphological features of the whole 3D pore network and pore connectivity were examined to gain insight into the potential functions of the particles. The proposed multidistance tomographic imaging scheme with quantitative structural analyses is expected to advance studies of functional materials by facilitating their structure-based rational design.

A systematic review and comparison of automated tools for quantification of fibrous networks

Fibrous networks are essential structural components of biological and engineered materials. Accordingly, many approaches have been developed to quantify their structural properties, which define their material properties. However, a comprehensive overview and comparison of methods is lacking. Therefore, we systematically searched for automated tools quantifying network characteristics in confocal, stimulated emission depletion (STED) or scanning electron microscopy (SEM) images and compared these tools by applying them to fibrin, a prototypical fibrous network in thrombi. Structural properties of fibrin such as fiber diameter and alignment are clinically relevant, since they influence the risk of thrombosis. Based on a systematic comparison of the automated tools with each other, manual measurements, and simulated networks, we provide guidance to choose appropriate tools for fibrous network quantification depending on imaging modality and structural parameter. These tools are often able to reliably measure relative changes in network characteristics, but absolute numbers should be interpreted with care. STATEMENT OF SIGNIFICANCE: Structural properties of fibrous networks define material properties of many biological and engineered materials. Many methods exist to automatically quantify structural properties, but an overview and comparison is lacking. In this work, we systematically searched for all publicly available automated analysis tools that can quantify structural properties of fibrous networks. Next, we compared them by applying them to microscopy images of fibrin networks. We also benchmarked the automated tools against manual measurements or synthetic images. As a result, we give advice on which automated analysis tools to use for specific structural properties. We anticipate that researchers from a large variety of fields, ranging from thrombosis and hemostasis to cancer research, and materials science, can benefit from our work.

Synergistically Constructed Electromagnetic Network of Magnetic Particle-Decorated Carbon Nanotubes and MXene for Efficient Electromagnetic Shielding

Lightweight polymer-based nanostructured aerogels are crucial for electromagnetic interference (EMI) shielding to protect electronic devices and humans from electromagnetic radiation. The construction of three-dimensional (3D) conductive networks is crucial to realize the excellent electromagnetic shielding performance of polymer-based aerogels. However, it is difficult to realize the interconnection of different conductive fillers in the polymer matrix, which limits the further improvement of their performance. Herein, 3D ordered hierarchical porous Fe₃O₄-decorated carbon nanotube (Fe₃O₄@CNT)/MXene/cross-linked aramid nanofiber (c-ANF)/polyimide (PI) aerogels were prepared via a unidirectional freezing strategy. Benefiting from the magnetic loss effect of Fe₃O₄ magnetic nanoparticles, the conductive and dielectric loss effects of CNTs, and the multiple reflections induced by the 3D ordered hierarchical porous structure, the Fe₃O₄@CNTs/MXene/c-ANFs/PI (FMCP) aerogels with the same contents of 8 wt % of Fe₃O₄@CNTs and MXene exhibit a high absolute EMI shielding effectiveness (SE) of up to 67.42 dB and a microwave reflection (SE_R) of 0.60 dB. More importantly, the phase transition of a small amount of MXene to TiO₂ optimizes the impedance matching and transmission and then improves the microwave absorption. The FMCP aerogel has an outstanding normalized surface specific SE (SSE/t) which is up to 62,654 dB cm²·g^-1. Meantime, the FMCP aerogels also show super-elasticity and could maintain 91.72% of the maximum stress after 1000 cycles of compression release under a fixed deformation of 60%.

Modular Assembly of MXene Frameworks for Noninvasive Disease Diagnosis via Urinary Volatiles

Volatile organic compounds (VOCs) in urine are valuable biomarkers for noninvasive disease diagnosis. Herein, a facile coordination-driven modular assembly strategy is used for developing a library of gas-sensing materials based on porous MXene frameworks (MFs). Taking advantage of modules with diverse composition and tunable structure, our MFs-based library can provide more choices to satisfy gas-sensing demands. Meanwhile, the laser-induced graphene interdigital electrodes array and microchamber are laser-engraved for the assembly of a microchamber-hosted MF (MHMF) e-nose. Our MHMF e-nose possesses high-discriminative pattern recognition for simultaneous sensing and distinguishing of complex VOCs. Furthermore, with the MHMF e-nose being a plug-and-play module, a point-of-care testing (POCT) platform is modularly assembled for wireless and real-time monitoring of urinary volatiles from clinical samples. By virtue of machine learning, our POCT platform achieves noninvasive diagnosis of multiple diseases with a high accuracy of 91.7%, providing a favorable opportunity for early disease diagnosis, disease course monitoring, and relevant research.

Spanning Network Gels from Nanoparticles and Graph Theoretical Analysis of Their Structure and Properties

Gels self-assembled from colloidal nanoparticles (NPs) translate the size-dependent properties of nanostructures to materials with macroscale volumes. Large spanning networks of NP chains provide high interconnectivity within the material necessary for a wide range of properties from conductivity to viscoelasticity. However, a great challenge for nanoscale engineering of such gels lies in being able to accurately and quantitatively describe their complex non-crystalline structure that combines order and disorder. The quantitative relationships between the mesoscale structural and material properties of nanostructured gels are currently unknown. Here, it is shown that lead telluride NPs spontaneously self-assemble into a spanning network hydrogel. By applying graph theory (GT), a method for quantifying the complex structure of the NP gels is established using a topological descriptor of average nodal connectivity that is found to correlate with the gel's mechanical and charge transport properties. GT descriptions make possible the design of non-crystalline porous materials from a variety of nanoscale components for photonics, catalysis, adsorption, and thermoelectrics.

Structure and Performance Attributes Optimization and Ranking of Gamma Irradiated Polymer Hybrids for Industrial Application

The selection of suitable composite material for high-strength industrial applications, from the list of available alternatives, is a tedious task as it requires an optimized structural performance-based solution. This study aimed to optimize the concentration of fillers, i.e., vinyl tri-ethoxy silane and absorbed gamma-dose, to enhance the properties of an industrial scale polymer, i.e., ultra-high molecular weight polyethylene (UHMWPE). The UHMWPE hybrids, in addition to silane, were treated with (30, 65, and 100 kGy) gamma dose and then tested for ten application-specific structural and performance attributes. The relative importance of attributes based on an 11-point fuzzy conversation was used for establishing the material assessment graph and corresponding adjacency matrix. Afterwards, the normalized values of attributes were used to establish the decision matrix for each alternative. The normalization was performed after the identification of high obligatory valued (HOV) and low obligatory valued (LOV) attributes. After this, suitability index values (SIVs) were calculated for ranking the hybrids that revealed hybrids 65 kGy irradiated the hybrid as the best choice and ranked as first among the existing alternatives. The major responsible factors were higher oxidation strength, a dense cross-linking network, and elongation at break. The values of the aforementioned factors for 65 kGy irradiated hybrids were 0.24, 91, and 360 MPa, respectively, as opposed to 0.54, 75, and 324 MPa for 100 kGy irradiated hybrids, thus placing the latter in second place regarding higher values of Yield Strength and Young Modulus. Finally, it is believed that the reported results and proposed model in this study will improve preoperative planning as far as considering these hybrids for high-strength industrial applications including total joint arthroplasty, textile-machinery pickers, dump trucks lining ships, and harbors bumpers and sliding, etc.