Traditional Trade-off Research Articles

Complementary Distant and Active Site Mutations Simultaneously Enhance Catalytic Activity and Thermostability of α-Galactosidase.

The industrial applications of enzymes are limited due to the activity-stability trade-off, which implies that the improvement of thermostability often accompanies decreased activity. This study presents a dual-strategy approach to simultaneously improve the catalytic efficiency and thermostability of α-galactosidase galV from Anoxybacillus vitaminiphilus WMF1. Our integrated method combines computational analysis with enzyme property prediction to selectively target and modify the catalytic region and residues that are distant from the active site. We identified and experimentally validated mutations that improve activity without compromising stability and further increased thermostability through additional distant-site mutations. The resulting mutant enzyme variant N549Q/T550N/Y634F demonstrated a 6.2-fold increase in catalytic efficiency and a 3.2-fold improvement in the half-life at 65 °C. Molecular dynamics (MD) simulations supported the structural basis for the observed enhancements. This approach offers a refined strategy for engineering α-galactosidases with improved industrial applicability, overcoming the traditional trade-offs between enzyme activity and stability. Hydrolytic activity toward raffinose family oligosaccharides (RFOs) was validated using soymilk as a model substrate, demonstrating significant practical potential.

The Validity of the Phillips Curve Relationship: An Econometric Study on Moroccan Data

The Phillips curve is a key tool in the formulation of economic policies. The primary objective of this study is to examine the validity of this curve in the Moroccan context. To this end, we employ an ARDL model, applied to annual data covering the period from 1991 to 2023. The results reveal a co-integration relationship, indicating a stable and long-term link between inflation and unemployment. However, contrary to the classical predictions of the Phillips curve, the analysis shows a significant positive impact of inflation on unemployment: a 1% increase in unemployment leads to a 1.22% rise in inflation in the short term, and 1.51% in the long term. These findings challenge the applicability of the Phillips curve in Morocco, highlighting that local economic dynamics deviate from the traditional trade-off between inflation and unemployment. This divergence underscores the urgent need to redefine Morocco's economic policies by adopting integrated and balanced monetary and fiscal strategies to effectively address these two major challenges.

Breaking the Trade-Off Between Electrical Conductivity and Mechanical Strength in Bulk Graphite Using Metal-Organic Framework-Derived Precursors.

High-performance bulk graphite (HPBG) that simultaneously integrates superior electrical conductivity and excellent strength is in high demand, yet it remains critical and challenging. Herein a novel approach is introduced utilizing MOF-derived nanoporous metal/carbon composites as precursors to circumvent this traditional trade-off. The resulting bulk graphite, composed of densely packed multilayered graphene sheets functionalized with diverse cobalt forms (nanoparticles, single atoms, and clusters), exhibits unprecedented electrical conductivity in all directions (in-plane: 7311 S cm⁻¹, out-of-plane: 5541 S cm⁻¹) and excellent mechanical strength (flexural: 101.17±5.73MPa, compressive: 151.56±2.53MPa). Co nanoparticles act as autocatalysts and binders, promoting strong interlayer adhesion among highly graphitized graphene layers via spark plasma sintering. The strong nano-interfaces between graphite and Co-create critical bridges between graphene nanosheets, facilitating highly efficient electron migration and enhanced strength and stiffness of the assembled bulk nanocomposites. Leveraging these exceptional properties, practical demonstrations highlight the immense potential of the robust material for applications demanding superior electromagnetic interference shielding and efficient heating. An innovative approach, which effectively decouples electrical conductivity from mechanical properties, paves the way for the creation of HPBGs tailored for diverse application sectors.

Metal-Organic Framework with Polar Pore Surface Designed for Purification of Both Natural Gas and Ethylene.

The advancement of high-value CH4 purification technology within the natural gas industry is paramount for industrial processes. Herein, we constructed ZJNU-402, a new porous material characterized by permanent porosity, as an effective adsorbent for separating C3H8/CH4 and C2H6/CH4 mixtures. The findings reveal an outstanding C3H8 adsorption capacity of 68 cm3 g-1 and a moderate C2H6 adsorption rate of 42 cm3 g-1, with a notably lower CH4 adsorption rate of 11 cm3 g-1. Noteworthy is the exceptional selectivity of ZJNU-402 for C3H8/CH4 and C2H6/CH4, standing at 375 and 31, respectively, surpassing many previously documented high-performance adsorbents and breaking the traditional trade-off between adsorption capacity and separation selectivity. Adsorption heat calculations show that compared with CH4 molecules, C3H8 and C2H6 molecules form stronger bonds with the skeleton, resulting in excellent separation performance. In addition, the breakthrough experiment of ZJNU-402 can also completely separate the ternary component C3H8/C2H6/CH4 mixture to obtain 99.95 % high-purity methane. At the same time, ZJNU-402 also has excellent structural stability, excellent recyclability, and low isosteric adsorption heat. Consequently, ZJNU-402 exhibits substantial potential for augmenting the efficacy of natural gas enrichment processes.

Substantially Improving CO2 Permeability and CO2/CH4 Selectivity of Matrimid Using Functionalized-Ti3C2Tx.

Mixed-matrix membranes (MMMs) with favorable interfacial interactions between dispersed and continuous phases offer a promising approach to overcome the traditional trade-off between permeability and selectivity in membrane-based gas separation. In this study, we developed free-standing MMMs by embedding pristine and surface-modified Ti3C2Tx MXenes into Matrimid 5218 polymer for efficient CO2/CH4 separation. Two-dimensional Ti3C2Tx with adjustable surface terminations provided control over these critical interfacial interactions. Characterization (Raman spectroscopy, XPS, DSC, FTIR) indicated the formation of hydrogen bonds between the termination groups on Ti3C2Tx and the carbonyl groups of Matrimid, promoting enhanced compatibility and dispersion of MXenes within the polymer matrix. The resulting MMMs with 5 wt % Ti3C2Tx showed a 67% increase in CO2 permeability and an 84% enhancement in CO2/CH4 selectivity compared to pristine Matrimid membranes. Surface modification of Ti3C2Tx using [3-(2-aminoethylamino)propyl]trimethoxysilane (AEAPTMS) further enhanced compatibility, leading to MMMs with 140% higher CO2 permeability and 130% greater CO2/CH4 selectivity. Molecular simulations suggested that AEAPTMS functionalization improved interfacial interactions with Matrimid chains, increasing the affinity of MXenes toward CO2 molecules. Additionally, the elongation of gas pathways, polymer chain disruption, and the presence of interlayer nanogalleries contributed positively to the enhanced separation performance. This work provides insights into tailoring nanomaterial-polymer interfaces to address the challenges of gas separation, paving the way for environmentally friendly CO2 separation technologies.

Wearable optical coherence tomography angiography probe with extended depth of field.

Optical coherence tomography (OCT) is widely utilized to investigate brain activities and disorders in anesthetized or restrained rodents. However, anesthesia can alter several physiological parameters, leading to findings that might not fully represent the true physiological state. To advance the understanding of brain function in awake and freely moving animals, the development of wearable OCT probes is crucial. We aim to address the challenge of insufficient depth of field (DOF) in wearable OCT probes for brain imaging in freely moving mice, ensuring high lateral resolution while capturing brain vasculature across varying heights. We integrated diffractive optical elements (DOEs) capable of generating beams with an extended DOF into a wearable OCT probe. This design effectively overcomes the traditional trade-off between lateral resolution and DOF, enabling the capture of detailed angiographic images in a dynamic and uncontrolled environment. The enhanced wearable OCT probe achieved a lateral resolution superior to within a axial range. This setup allowed for high-resolution optical coherence tomography angiography (OCTA) imaging with extended DOF, making it suitable for studying brain vasculature in freely moving mice. The incorporation of DOEs into the wearable OCT probe represents a significant advancement in wearable biomedical imaging. This technology facilitates the acquisition of high-resolution angiographic images with an extended DOF, thus enhancing the ability to study brain function in awake and naturally behaving animals.

Renovating Stability and Performance in Magnetorheological Fluids Through Particle Size and Shape Anisotropy.

Magnetorheological (MR) fluids are smart materials consisting of magnetic particles in a non-magnetic medium, undergoing phase transitions under a magnetic field to generate yield stress. However, sedimentation and limited particle content hinder their industrial application, balancing high yield stress with stability. This study introduces an innovative MR slurry using Sendust particles, achieving superior yield stress and sedimentation stability compared to traditional systems. Flake Sendust particles demonstrate enhanced yield stress at low magnetic fields due to their lower demagnetization factor, outperforming bulk Sendust despite lower packing volumes. These findings emphasize the critical role of particle morphology in optimizing MR fluid performance. The slurry maintains its magnetorheological properties while offering tunable yield stress, making it suitable for diverse applications. This research addresses traditional trade-offs in MR fluid design, paving the way for advanced MR slurries in sensors, actuators, energy harvesters, haptic devices, and biomedical systems.

Nonuniversal Dynamics of Hyperbranched Metallo-Supramolecular Polymer Networks by the Spontaneous Formation of Nanoparticles.

Various transient and permanent bonds are commonly combined in increasingly complex hierarchical structures to achieve biomimetic functions, along with high mechanical properties. However, there is a traditional trade-off between mechanical strength and biological functions like self-healing. To fill this gap, we develop a metallo-supramolecular polymer hydrogel based on the hyperbranched poly(ethylene imine) (PEI) backbone and phenanthroline ligands, which have unexpectedly high plateau modulus at low concentrations. Rheological measurements demonstrate nonuniversal metal-ion-specific dynamics, with significantly larger plateau moduli, longer relaxation times, and stronger temperature dependencies, compared to equivalent networks based on model-type telechelic precursors, which cannot be explained by the theory of linear viscoelasticity. TEM images reveal the in situ mineralization of metal ions, which nucleate by the ligand complexation and grow thanks to the spontaneous reducing effect of the PEI backbone. Evidently, the complex lifetime works against Ostwald ripening, resulting in the formation of thermodynamically stable smaller particles. This trend is followed by time-dependent network buildup measurements and is confirmed by a kinetic model for particle formation and aggregation. The spontaneous formation of particles with complex lifetime-dependent sizes can explain the nonuniversal dynamics through the interaction of polymer segments and particles at the nanoscale. This work describes how the polymer backbone can affect the strength and stability of supramolecular bonds, promising for combining high mechanical properties and self-healing comparable to natural tissues.

Mechanical and Electrical Conductivity Properties of Graphene/Cu Interfaces: A Theoretical Insight.

For graphene/copper (Gr/Cu) composites, achieving high-quality interfaces between Gr and Cu (strong interfacial bonding strength and excellent electron transport performance) is crucial for enabling their widespread applications in electronic devices. This study employs first-principles calculations and the nonequilibrium Green's function method to systematically investigate the mechanical and electrical conductivity properties of Cu(111)/Gr/Cu(111) interfaces with various stacking sequences and different forms of Gr. For these interface systems, the binding energy, separation work, charge transfer, and electrical conductivity across the interface were obtained. The results show that the top-fcc interface exhibits superior interfacial properties, characterized by relatively high binding energy (-3.00 eV/C atom) and separation work (≥0.78 J/m2), a small interfacial distance (2.85 Å), and enhanced electron transport capacity (2.12 G0/nm2). A bilayer form of Gr significantly reduces electronic conductance across the Gr/Cu interface by nearly 2.46 orders of magnitude. Furthermore, point defects in Gr, especially single-vacancy defects, disrupt the traditional trade-offs between mechanical and electrical performance, simultaneously enhancing mechanical performance by 7.50-124.36% and electrical performance by 33.02%. Additionally, stress mechanisms have been proposed to further enhance the interfacial electrical conductivity of Gr/Cu composites. The present study provides a theoretical basis for exploring the engineering applications of Gr/Cu composite materials.

Creating ultra-strong and recyclable green plastics from marine-sourced alginate-chitosan nanowhisker nanocomposites for controlled release urea fertilizer

In response to the pressing environmental challenge posed by petroleum-derived plastics, the development of green plastics derived from all-biomass nanocomposites offers promising solutions. However, conventional nanocomposites often prioritize enhanced stiffness at the expense of flexibility. We introduce sodium alginate (SA)/chitosan nanowhisker (CSW) nanocomposites, derived entirely from marine-sourced all-biomass, to create ultra-strong and flexible green plastics. Through the synergistic interaction between SA and CSW, these nanocomposites demonstrate simultaneous stiffening and toughening, overcoming the traditional trade-off. Two key mechanisms contribute: geometric reinforcement from the needle-like structure of CSW and electrostatic reinforcement at the interface between oppositely charged CSW and SA. Compared to control SA, the SA/CSW nanocomposites exhibit remarkable enhancements in tensile modulus, strength, and stretchability, by 49%, 85%, and 55%, respectively (7.6 GPa, 223.3 MPa, 14.7%). Cellulose nanocrystals, serving as a control, only stiffen the nanocomposites, adhering to the typical trade-off. Biodegradability in compost can be tailored based on the type of nanofillers. Due to the water resistance of CSW, SA/CSW nanocomposites are proven effective for the controlled release of urea fertilizer in agricultural applications. With recyclability and superior mechanical properties, these marine-sourced green plastics offer a sustainable alternative to conventional plastics, promising significant impact in the eco-plastic industry.

Quantitative model for grain boundary effects on strength-electrical conductivity relation

Fine-long shaped grains have been proved to be an efficient design approach to overcome the traditional trade-off relation between strength and electrical conductivity (EC) of metal wires. However, quantitative models linking grain shape parameters to both strength and EC remain scarce, limiting the precise optimization of material properties. In this study, grain boundaries (GBs) were classified into parallel or perpendicular ones to establish the quantitative models. Accordingly, a novel model for calculating the EC of fine-long shaped grains was proposed by first parallel-connecting the parallel GBs with the matrix, then series-connecting them with the vertical GBs. The EC calculated using this new model shows a small error band of only 0.5 %, indicating an excellent accuracy of EC calculation. Besides, a quantitative model for calculating the strength based on grain width was also developed. Consequently, the general effects of grain shape parameters including grain width, grain length, grain volume and grain aspect ratio on the strength and EC were quantitatively revealed. This work does not only advance the principle for achieving high strength and high EC through fine-long shaped grains from a qualitative concept to a quantitative framework but also offers valuable insights for the quantitative analysis of GB effects on strength and EC in other materials.

Effective and efficient coded aperture cone-beam computed tomography via generative adversarial U-Net

Coded aperture cone-beam computed tomography (CBCT) represents a crucial method for acquiring high-fidelity three-dimensional (3D) tomographic images while reducing radiation exposure. However, projections are non-uniformly and discontinuously sampled with the coded apertures placed in front of the x-ray source, leading to very small reconstruction scale and time-intensive iterations. In this study, an alternative approach to reconstruct coded aperture CBCT based on generative adversarial U-net is proposed to effectively and efficiently reconstruct large scale 3D CBCT images. Our method entails predicting complete and uniform projections from incomplete and non-uniform coded projections, enabling the requirement of continuity for the use of analytical algorithms in 3D image reconstruction. This novel technique effectively mitigates the traditional trade-off between image fidelity and computational complexity inherent in conventional coded aperture CBCT reconstruction methods. Our experimental results, conducted using clinical datasets comprising CBCT images from 102 patients at Nanjing Medical University, demonstrate that high-quality CBCT images with voxel dimensions of 400 × 400 × 400 can be reconstructed within 35 s, even when 95% of projections are blocked, yielding images with PSNR values exceeding 25dB and SSIM values surpassing 0.85.

Breaking the trade-off between proton conductivity and mechanical stability through liquid-crystal-modified aramid fibers in sulfonated polyether ether ketone membranes

In the quest for sustainable and high-performance hydrogen fuel cells, proton exchange membranes (PEMs) stand as a pivotal research focus. To overcome the significant challenge posed by the traditional trade-offs between proton conductivity and mechanical stability, this work introduces liquid-crystal-modified aramid fibers (DBAF) with highly ordered molecular arrangements and abundant sulfonic acid groups on the side chains as proton-hopping sites into a sulfonated poly (ether ether ketone) (SPEEK) matrix. The inclusion of components not only improves the proton conductivity of the membrane, but also boosts its mechanical strength. The results of our study demonstrate that the externally attached sulfonic acid groups create extra channels for the transport of protons. Additionally, the organized and consistently stable hydrogen-bond network enables the Grotthuss transport mechanism within the SPEEK membrane. The 1 wt% DBAF-SPEEK composite membrane exhibits a maximum proton conductivity of 0.23 S cm−1 at 80 °C, representing a 64% increase over the baseline SPEEK membrane's 0.14 S cm−1. Simultaneously, the tensile strength at normal room temperature is 39.7 MPa, exhibiting an improvement of 86% compared to the initial value of 21.3 MPa. Additionally, the swelling ratio is lowered by 18.69%. Compared with the baseline membrane, the DBAF-enhanced SPEEK composite membrane exhibits superior mechanical stability and proton conductivity within a moderate temperature range (30–80 °C). Consequently, this work offers valuable insights for the development of novel proton-conductive materials.

Membrane - Safe and Performant Data Access Controls in Apache Spark in the Presence of Imperative Code

Data Governance is an increasingly critical feature of modern cloud database systems, enabling administrators to set granular access policies on their data. AWS customers want to define row or column filtering on their blob storage data and access it using popular tools such as Apache Spark. AWS EMR provides a managed and serverless solution that lets users run Spark jobs in the AWS cloud with imperative and declarative programming against their data, while securely enforcing the fine-grained access controls defined on those datasets. Spark runs its compiler and scheduler alongside the user application and embeds user-defined functions in query plans, giving a threat actor direct access to its memory space. This introduces attack vectors such as information disclosure or privilege escalation during policy enforcement, in addition to well-researched threats such as SQL side channel attacks. In this paper, we present Membrane: a novel approach to secure query plans with declarative and imperative code. The innovation comes from splitting the Spark driver in two in order to rewrite query plans with security boundaries while avoiding traditional tradeoffs when using container isolation techniques. The approach described herein enables applying fine grained data access controls to both SQL and map-reduce Spark jobs, with negligible performance and cost differences.

Versatile crop yield estimator

Accurate production estimates, months before the harvest, are crucial for all parts of the food supply chain, from farmers to governments. While methods have been developed to use satellite data to monitor crop development and production, they typically rely on official crop statistics or ground-based data, limiting their application to the regions where they were calibrated. To address this issue, a new method called VeRsatile Crop Yield Estimator (VeRCYe) has been developed to estimate wheat yield at the pixel and field levels using satellite data and process-based crop models. The method uses the Leaf Area Index (LAI) as the linking variable between remotely sensed data and APSIM crop model simulations. In this process, the sowing dates of each field were detected (RMSE = 2.6 days) using PlanetScope imagery, with PlanetScope and Sentinel-2 data fused into a daily 3 m LAI dataset, enabling VeRCYe to overcome the traditional trade-off between satellite data that has either high temporal or high spatial resolution. The method was evaluated using 27 wheat fields across the Australian wheatbelt, covering a wide range of pedo-climatic conditions and farm management practices across three growing seasons. VeRCYe accurately estimated field-scale yield (R2 = 0.88, RMSE = 757 kg/ha) and produced 3 m pixel size yield maps (R2 = 0.32, RMSE = 1213 kg/ha). The method can potentially forecast the final yield (R2 = 0.78–0.88) about 2 months before the harvest. Finally, the harvest dates of each field were detected from space (RMSE = 2.7 days), indicating when and where the estimated yield would be available to be traded in the market. VeRCYe can estimate yield without ground calibration, be applied to other crop types, and used with any remotely sensed LAI information. This model provides insights into yield variability from pixel to regional scales, enriching our understanding of agricultural productivity.

Capital structure in Latin America: institutional and macroeconomic effects

PropósitoEste estudio analiza la influencia de los factores institucionales y macroeconómicos, además de los factores a nivel de empresa, en la estructura de capital de las empresas industriales cotizadas latinoamericanas (LATAM). El objetivo es proporcionar evidencia empírica sobre las empresas latinoamericanas desde (1) la perspectiva de las teorías tradicionales trade-off y pecking order, y (2) desde los enfoques que introducen el impacto de los factores institucionales y macroeconómicos en el análisis.Diseño/metodología/enfoqueEl análisis empírico adopta una metodología econométrica, utilizando datos de panel de empresas de Argentina, Brasil, Chile, Colombia, México y Perú, de 2008 a 2018.HallazgosLos resultados indican que, además de las características a nivel de empresa, las características institucionales y macroeconómicas de los países influyen en la estructura de capital de las empresas latinoamericanas.Limitaciones/implicaciones de la investigaciónEl estudio presenta algunas limitaciones, principalmente se centra en empresas cotizadas provenientes de solo seis países de LATAM, debido a la falta de datos. Sería recomendable realizar estudios similares con factores de gobierno corporativo, con empresas familiares y PYMES.Implicaciones prácticasLos resultados pueden servir de referencia para los agentes económicos y profesionales, animándolos a considerar la evolución de las variables institucionales y macroeconómicas a la hora de tomar decisiones. Académicamente, nuestros hallazgos verifican la validez de las teorías convencionales y la relevancia de incorporar variables institucionales externas en el marco de la estructura de capital.Originalidad/valorLa importancia de esta investigación radica en analizar la estructura de capital de empresas en un área geográfica poco explorada, LATAM, incluyendo factores institucionales y macroeconómicos y utilizando la nueva base de datos Orbis.

Novel Class of Crystal/Glass Ultrafine Nanolaminates with Large and Tunable Mechanical Properties.

The control of local heterogeneities in metallic glasses (MGs) represents an emerging field to improve their plasticity, preventing the propagation of catastrophic shear bands (SBs) responsible for the macroscopically brittle failure. To date, a nanoengineered approach aimed at finely tuning local heterogeneities controlling SB nucleation and propagation is still missing, hindering the potential to develop MGs with large and tunable strength/ductility balance and controlled deformation behavior. In this work, we exploited the potential of pulsed laser deposition (PLD) to synthesize a novel class of crystal/glass ultrafine nanolaminates (U-NLs) in which a ∼4 nm thick crystalline Al separates 6 and 9 nm thick Zr50Cu50 glass nanolayers, while reporting a high density of sharp interfaces and large chemical intermixing. In addition, we tune the morphology by synthesizing compact and nanogranular U-NLs, exploiting, respectively, atom-by-atom or cluster-assembled growth regimes. For compact U-NLs, we report high mass density (∼8.35 g/cm3) and enhanced and tunable mechanical behavior, reaching maximum values of hardness and yield strength of up to 9.3 and 3.6 GPa, respectively. In addition, we show up to 3.6% homogeneous elastoplastic deformation in compression as a result of SB blocking by the Al-rich sublayers. On the other hand, nanogranular U-NLs exhibit slightly lower yield strength (3.4 GPa) in combination with enhanced elastoplastic deformation (∼6%) followed by the formation of superficial SBs, which are not percolative even at deformations exceeding 15%, as a result of the larger free volume content within the cluster-assembled structure and the presence of crystal/glass nanointerfaces, enabling to accommodate SB events. Overall, we show how PLD enables the synthesis of crystal/glass U-NLs with ultimate control of local heterogeneities down to the atomic scale, providing new nanoengineered strategies capable of deep control of the deformation behavior, surpassing traditional trade-off between strength and ductility. Our approach can be extended to other combinations of metallic materials with clear interest for industrial applications such as structural coatings and microelectronics (MEMS and NEMS).

Strengthening-Durable Trade-Off and Self-Healing, Recyclable Shape Memory Polyurethanes Enabled by Dynamic Boron-Urethane Bonds.

Addressing the demand for integrating strength and durability reinforcement in shape memory polyurethane (SMPU) for diverse applications remains a significant challenge. Here a series of SMPUs with ultra-high strength, self-healing and recyclability, and excellent shape memory properties through introducing dynamic boron-urethane bonds are synthesized. The introducing of boric acid (BA) to polyurethane leading to the formation of dynamic covalent bonds (DCB) boron-urethane, that confer a robust cross-linking structure on the SMPUs led to the formation of ordered stable hydrogen-bonding network within the SMPUs. The flexible crosslinking with DCB represents a novel strategy for balancing the trade-off between strength and durability, with their strengths reaching up to 82.2MPa while also addressing the issue of durability in prolonged usage through the provision of self-healing and recyclability. The self-healing and recyclability of SMPU are demonstrated through rapid dynamic exchange reaction of boron-urethane bonds, systematically investigated by dynamic mechanical analysis (DMA). This study sheds light on the essential role of such PU with self-healing and recyclability, contributing to the extension of the PU's service life. The findings of this work provide a general strategy for overcoming traditional trade-offs in preparing SMPUs with both high strength and good durability.

Retrospective Analysis of Structure-Property Relationship of Emergent Metallo-Supramolecular Polymer Networks.

Metallo-supramolecular polymer networks (MSPNs) are fabricated from the crosslinking of polymers by discrete supramolecular coordination complexes. Due to the availability of various coordination complexes, e. g., 2D macrocycles and 3D nanocages, the MSPNs have been recently developed with broadly tunable visco-elasticity and enriched functions inherited from the coordination complexes. The coordination complexes possess enriched topologies and unique structural relaxation dynamics, rendering them the capability to break the traditional tradeoffs of polymer systems for the design of materials with enhanced mechanical performance. The structure-property relationship studies are critical for the material-by-design of MSPNs, while the spatiotemporal investigations are desired for the exploration of dynamics information. The work summarizes recent studies on the unique ligand-exchange kinetics and the multi-level structural relaxation dynamics of MSPNs. The MSPNs' mechanical properties can be quantitatively correlated with the dynamics for understanding the structure-property relationship. This concept will not only serve to attract more researchers to engage in the study of the structure-activity relationship of MSPNs but also inspire innovative research findings pertaining to the application of MSPNs.

Enhancing the Conductivity and Thermoelectric Performance of Semicrystalline Conducting Polymers through Controlled Tie Chain Incorporation.

Conjugated polymers are promising materials for thermoelectric applications, however, at present few effective and well-understood strategies exist to further advance their thermoelectric performance. Here a new model system is reported for a better understanding of the key factors governing their thermoelectric properties: aligned, ribbon-phase poly[2,5-bis(3-dodecylthiophen-2-yl)thieno[3,2-b]thiophene] (PBTTT) doped by ion-exchange doping. Using a range of microstructural and spectroscopic methods, the effect of controlled incorporation of tie-chains between the crystalline domains is studied through blending of high and low molecular weight chains. The tie chains provide efficient transport pathways between crystalline domains and lead to significantly enhanced electrical conductivity of 4810 S cm-1, which is not accompanied by a reduction in Seebeck coefficient or a large increase in thermal conductivity. Respectable power factors of 173 µW m-1 K-2 are demonstrated in this model system. The approach is generally applicable to a wide range of semicrystalline conjugated polymers and could provide an effective pathway for further enhancing their thermoelectric properties and overcome traditional trade-offs in optimization of thermoelectric performance.