Self‐assembly is a powerful tool for constructing supramolecular materials for many applications, ranging from energy harvesting to biomedicine. Among the methods to prepare supramolecular materials ...for biomedical applications, enzyme‐instructed self‐assembly (EISA) has several advantages. Herein, the unique properties and advantages of EISA in preparing biofunctional supramolecular nanomaterials and hydrogels from peptides are highlighted. EISA can trigger molecular self‐assembly in situ. Therefore, using overexpression enzymes in disease sites, supramolecular materials can be formed in situ to improve the selectivity and efficacy of the treatment. The precursor may be involved during the EISA process, and it is actually a two‐component self‐assembly process. The precursor can help to stabilize the assembled nanostructures of hydrophobic peptides formed by EISA. More importantly, the precursor may determine the outcome of molecular self‐assembly. Recently, it was also observed that EISA can kinetically control the peptide folding and morphology and cellular uptake behavior of supramolecular nanomaterials. With the combination of other methods to trigger molecular self‐assembly, researchers can form supramolecular nanomaterials in a more precise mode and sometimes under spatiotemporal control. EISA is a powerful and unique methodology to prepare supramolecular biofunctional materials that cannot be generated from other common methods.
Enzyme‐instructed self‐assembly (EISA) has several unique properties and advantages in preparing biofunctional supramolecular nanomaterials from peptides. Recent progress in this area is reviewed, with a focus on in situ EISA, precursor involved EISA, controlling peptide folding by EISA, and the combination of other methods with EISA. The perspectives and challenges are also discussed.
Nanofluidics derived from low‐dimensional nanosheets and protein nanochannels are crucial for advanced catalysis, sensing, and separation. However, polymer nanofluidics is halted by complicated ...preparation and miniaturized sizes. This work reports the bottom‐up synthesis of modular nanofluidics by confined growth of ultrathin metal–organic frameworks (MOFs) in a polymer membrane consisting of zwitterionic dopamine nanoparticles (ZNPs). The confined growth of the MOFs on the ZNPs reduces the chain entanglement between the ZNPs, leading to stiff interfacial channels enhancing the nanofluidic transport of water molecules through the membrane. As such, the water permeability and solute selectivity of MOF@ZNPM are one magnitude improved, leading to a record‐high performance among all polymer nanofiltration membranes. Both the experimental work and the molecular dynamics simulations confirm that the water transport is shifted from high‐friction‐resistance conventional viscous flow to ultrafast nanofluidic flow as a result of rigid and continuous nanochannels in MOF@ZNPM.
A rigid‐scaffold‐reinforced polymeric nanoparticles’ interfacial channel strategy is proposed for fabricating nanofluidic membranes that exhibit water permeance and dye/salt selectivity that are 1–2 orders of magnitude higher than conventional polymeric membranes. The unprecedented separation performance is due to the paradigm shift of water transport from conventional viscous flow to ultrafast nanofluidic flow in the membrane nanofluidics.
Through featuring a historical review of the L2 speaking assessment scales applied in related studies, this paper targets at providing responses for the following three questions (a) How are the ...scales assessing L2 speaking anxiety developed and adapted in related research? (b) What are the frequently adopted methods for validating speaking anxiety scales? (c) How is L2 speaking anxiety represented and interpreted with a dynamic approach? Based on analyzing the development process of frequently-used scales for assessing test anxiety, foreign language classroom anxiety, and speaking anxiety, the author classified the scales into three categories: test-based scales measuring speaking anxiety, classroom-based scales measuring speaking anxiety, and activity-based scales measuring L2 speaking anxiety. As for the scale validation methods, Classical Testing Theory (CTT) and Rasch measurement were introduced as two major statistical paradigms for guaranteeing the reliability of the scales. This paper also summarizes the emerging themes generalized from research focusing speaking anxiety assessment, where the dynamic approach is discussed as a guideline to interpret the relationship among anxiety, language performance, and other factors involved in language learning. This paper ends with highlighting possible directions for anxiety-related research in the future, where technology intervention and the “positivity ratio” might become new attempts for pedagogical design.
Active carbons have unique physicochemical properties, but their conductivities and surface to weight ratios are much poorer than graphene. A unique and facile method is innovated to chemically ...process biomass by “drilling” holes with H2O2 and exfoliating into graphene‐like nanosheets with HAc, followed by carbonization at a high temperature for highly graphitized activated carbon with greatly enhanced porosity, unique pore structure, high conductivity, and large surface area. This graphene‐like carbon exhibits extremely high specific capacitance (340 F g−1 at 0.5 A g−1) and high specific energy density (23.33 to 16.67 W h kg−1) with excellent rate capability and long cycling stability (remains 98% after 10 000 cycles), which is much superior to all reported carbons including graphene. Synthesis mechanism for deriving biomass into porous graphene‐like carbons is discussed in detail. The enhancement mechanism for the porous graphene‐like carbon electrode reveals that rationally designed meso‐ and macropores are very critical in porous electrode performance, which can network micropores for diffusion freeways, high conductivity, and high utilization. This work has universal significance in producing highly porous and conductive carbons from biomass including biowastes for various energy storage/conversion applications.
A graphene‐like porous activated carbon derived from a biomass fabricated, rationally designed chemical process, followed by carbonization at high temperature, exhibits a specific capacitance of 340 F g−1 at 0.5 A g−1 and high specific energy density (23.33–16.67 W h kg−1), with excellent capacity retention after 10 000 cycles, superior to other carbon electrodes.
This paper presents the compact and efficient Matlab codes for the concurrent topology optimization of multiscale composite structures not only in 2D scenario but also considering 3D cases. A ...modified SIMP approach (Sigmund 2007) is employed to implement the concurrent topological design, with an energy-based homogenization method (EBHM) to evaluate the macroscopic effective properties of the microstructure. The 2D and 3D Matlab codes in the paper are developed, using the 88-line 2D SIMP code (Struct Multidisc Optim 43(1): 1–16, 2011) and the 169-line 3D topology optimization code (Struct Multidisc Optim 50(6): 1175–1196, 2014), respectively. This paper mainly contributes to the following four aspects: (1) the code architecture for the topology optimization of cellular composite structures (ConTop2D.m and ConTop3D.m), (2) the code to compute the 3D iso-parametric element stiffness matrix (elementMatVec3D.m), (3) the EBHM to predict the macroscopic effective properties of 2D and 3D material microstructures (EBHM2D.m and EBHM3D.m), and (4) the code to calculate the sensitivities of the objective function with respect to the design variables at two scales. Several numerical examples are tested to demonstrate the effectiveness of the Matlab codes, which are attached in the Appendix, also offering an entry point for new comers in designing cellular composites using topology optimization.
Land-use change is a significant driver of ecosystem service changes. This paper explores how land-use change affects water-related ecosystem services (e.g., water yield, water purification, and soil ...conservation) in the Guishui River Basin, Beijing, China. Water-related ecosystem services in the Basin are vitally important for Beijing, which currently faces a severe water crisis. Understanding the impacts of land-use change on water-related ecosystem services is essential for effectively managing this crisis. To this end, the study first analyzed land-use change and corresponding variations in water-related ecosystem services in the Basin from 1980 to 2011. The analysis showed that increases in woodland and construction land enhanced water yield and soil conservation services while reforestation and urbanization degraded water purification services. The paper then developed four spatially-explicit land-use scenarios, corresponding to water conservation, agricultural expansion, a combination, and soil conservation. Each scenario quantified the impact of future land-use changes on water-related ecosystem services. This research found that water purification and soil conservation services increased under both the water conservation and soil conservation scenarios, while these services decreased under the agricultural expansion scenario. Water yield also increased under the soil conservation scenario. Overall, the paper shows that ecosystem services are spatially specific and greatly affected by different scenarios. This finding underscores the value of studies to improve land management practices. In particular, this research would be useful for those policymakers and stakeholders that intend to forecast the impacts of alternative land-use policies on water-related ecosystem services. The limitations and shortcomings of this study, including accuracy in estimating ecosystem services, are discussed.
•This paper assessed the land-use change from 1980 to 2011.•Four future land-use scenarios were developed.•The impact of past and future land-use changes on ecosystem services was examined.•The InVEST model was selected to quantify the changes in ecosystem services.
Polydimethylsiloxanes (PDMS) foam as one of next‐generation polymer foam materials shows poor surface adhesion and limited functionality, which greatly restricts its potential applications. ...Fabrication of advanced PDMS foam materials with multiple functionalities remains a critical challenge. In this study, unprecedented self‐adhesive PDMS foam materials are reported with worm‐like rough structure and reactive groups for fabricating multifunctional PDMS foam nanocomposites decorated with MXene/cellulose nanofiber (MXene/CNF) interconnected network by a facile silicone foaming and dip‐coating strategy followed by silane surface modification. Interestingly, such self‐adhesive PDMS foam produces strong interfacial adhesion with the hybrid MXene/CNF nano‐coatings. Consequently, the optimized PDMS foam nanocomposites have excellent surface super‐hydrophobicity (water contact angle of ≈159o), tunable electrical conductivity (from 10−8 to 10 S m−1), stable compressive cyclic reliability in both wide‐temperature range (from −20 to 200 oC) and complex environments (acid, sodium, and alkali conditions), outstanding flame resistance (LOI value of >27% and low smoke production rate), good thermal insulating performance and reliable strain sensing in various stress modes and complex environmental conditions. It provides a new route for the rational design and development of advanced PDMS foam nanocomposites with versatile multifunctionalities for various promising applications such as intelligent healthcare monitoring and fire‐safe thermal insulation.
Polydimethylsiloxanes (PDMS) foam usually exhibits poor surface adhesion and limited functionality, restricting the potential applications. Here, self‐adhesive PDMS foams with worm‐like rough structure and reactive groups are fabricated by a facile silicone foaming approach. Decorating with MXene/cellulose nanofiber interconnected network and using silane modification, exceptional multifunctionalities PDMS nanocomposites are prepared, showing versatile applications in thermal insulating and smart sensing fields.
•A reasonable classification of nodes in 3D material microstructures is developed to formulate boundary constraint equations.•A new 3D periodic boundary formulation is developed to formulate an ...effective 3D energy-based homogenization method.•An effective design method is proposed for 3D micro-structured materials to attain extreme mechanical properties.•The optimized 3D micro-structured materials are featured with smooth boundaries and clear interfaces without the post-processing mechanism.
This paper proposes an effective method for the design of 3D micro-structured materials to attain extreme mechanical properties, which integrates the firstly developed 3D energy-based homogenization method (EBHM) with the parametric level set method (PLSM). In the 3D EBHM, a reasonable classification of nodes in periodic material microstructures is introduced to develop the 3D periodic boundary formulation consisting of 3D periodic boundary conditions, 3D boundary constraint equations and the reduced linearly elastic equilibrium equation. Then, the effective elasticity properties of material microstructures are evaluated by the average stress and strain theorems rather than the asymptotic theory. Meanwhile, the PLSM is applied to optimize microstructural shape and topology because of its positive characteristics, like the perfect demonstration of geometrical features and high optimization efficiency. Numerical examples are provided to demonstrate the advantages of the proposed design method. Results indicate that the optimized 3D material microstructures with expected effective properties are featured with smooth structural boundaries and clear interfaces.
The novel sulfomethylated lignin-grafted-polyacrylic acid (SL-g-PAA) hydrogel was fabricated in this work via a facile and green synthetic strategy for the efficient removal of heavy metal ions from ...wastewater, and then successively reused for chemiluminescence (CL). The sulfomethylation of lignin was first performed to improve its water solubility and introduce numerous active sites for adsorption of heavy metal ions. The as-synthesized SL-g-PAA hydrogel with high content of lignin exhibited the highly efficient and rapid removal of various metal ions from simulated wastewater. More importantly, the spent hydrogel (M2+@SL-g-PAA) after adsorption was reused for the first time to develop a new CL system by an ingenious strategy, in which these metal ions adsorbed on M2+@SL-g-PAA act as heterogeneous catalytic sites to catalyze the CL reaction between N-(4-aminobutyl)-N-ethylisoluminol (ABEI) and H2O2. The resultant CL system displayed high CL intensity and long duration time, which could be observed by naked eye in the dark and lasted for > 24 h. The combination of facile fabrication process, renewable raw materials, and ingenious strategy for successive application in adsorption and CL endows this lignin-based composite hydrogel with a great potential for application in wastewater treatment, biological imaging and cold light sources.
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•A lignin-based hydrogel was fabricated by a facile and green synthetic strategy.•SL-g-PAA exhibited efficient and rapid removal of heavy metal ions from wastewater.•Spent hydrogel after adsorption was reused for the first time to develop CL system.•A highly intensive and long-lasting CL system was obtained by an ingenious design.•A new strategy for successive application of lignin-based hydrogels was presented.
In this paper, we study unmanned aerial vehicle (UAV) assisted mobile edge computing (MEC) with the objective to optimize computation offloading with minimum UAV energy consumption. In the considered ...scenario, a UAV plays the role of an aerial cloudlet to collect and process the computation tasks offloaded by ground users. Given the service requirements of users, we aim to maximize UAV energy efficiency by jointly optimizing the UAV trajectory, the user transmit power, and computation load allocation. The resulting optimization problem corresponds to nonconvex fractional programming, and the Dinkelbach algorithm and the successive convex approximation (SCA) technique are adopted to solve it. Furthermore, we decompose the problem into multiple subproblems for distributed and parallel problem solving. To cope with the case when the knowledge of user mobility is limited, we adopt a spatial distribution estimation technique to predict the location of ground users so that the proposed approach can still be applied. Simulation results demonstrate the effectiveness of the proposed approach for maximizing the energy efficiency of UAV.