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At least 685 records · Page 38

Electrolyte–Electrocatalyst Interfacial Effects of Polymeric Materials for Tandem CO 2 Capture and Conversion Elucidated Using In Situ Electrochemical AFM

Integrating CO 2 capture and electrochemical conversion has been proposed as a strategy to reduce the net energy required for CO 2 regeneration in traditional CO 2 capture and conversion schemes and can be coupled with carbon-free renewable electricity. Polyethylenimine (PEI)-based materials have been previously studied as CO 2 capture materials and can be integrated in these reactive capture processes. PEI-based electrolytes have been found to significantly increase the CO 2 loading, and impact selectivity and rate of product formation when compared to the conventional aqueous electrolytes. However, the influence of these materials at the catalyst–electrode interface is currently not well understood. In this study, PEI-based electrolytes were prepared and their impact on the morphology of a silver electrode performing electrochemical CO 2 reduction (CO 2 R) was studied using in situ electrochemical atomic force microscopy (EC-AFM). The presence of PEI on the electrode surface could be distinguished based on nanomechanical properties (DMT modulus), and changes were observed as negative polarization was applied, revealing a reorganization of the PEI chains due to electrostatic interactions. These changes were impacted by the electrolyte composition, including the addition of supporting electrolyte KHCO 3 salt, as well as CO 2 captured by the PEI-based electrolyte, which minimized the change in surface mechanical properties and degree of PEI alignment on the electrode surface. The changes in surface mechanical properties were also dependent on the PEI polymer length, with higher molecular weight PEI showing different reconfiguration than the shorter polymer brushes. The study highlights that the choice of polymer material, the electrolyte composition, and CO 2 captured impact the nearelectrode environment, which has implications for CO 2 R, and presents EC-AFM as a new tool that can be used to probe the dynamic behavior of these interfaces during electrocatalysis.

36 MATERIALS SCIENCE↗

Self-Consistent Theory for Structural Relaxation, Dynamic Bond Exchange Times, and the Glass Transition in Polymeric Vitrimers

Here, we formulate a statistical mechanical theory for how dynamic bond exchange influences the activated hopping-driven relaxation of Kuhn segments in dynamically cross-linked networks or vitrimers over a wide range of temperatures and cross-link densities. The key new methodological aspect is to address in a self-consistent manner the dynamic consequences of bond exchange on the Kuhn segmental alpha relaxation, and vice versa. The predicted temperature dependence of the segmental alpha time of vitrimers at high temperatures remains the same as that of permanent networks, but at lower temperatures, a significant acceleration of relaxation occurs due to bond exchanges. From a mechanistic perspective, the vitrimer local cage barrier is very weakly affected by bond exchange, while the collective elastic barrier contribution decreases significantly in the deeply supercooled regime. The vitrimer glass transition temperature is predicted to grow linearly with the square root of the cross-link density, as previously found for permanent networks. Material-specific chemical effects such as cross-linker size relative to that of the normal Kuhn segment or special attraction of a cross-linker with polymers are crudely considered based on model calculations. The theory is quantitatively applied to recent experiments on dry ethylene vitrimers. Good agreements are found including that the bond exchange time follows an Arrhenius law at high enough temperatures but upward non-Arrhenius deviations emerge in the deeply supercooled regime, and a collapsed master curve of the segment alpha time exists over a wide range of cross-link densities and temperatures. Possible extensions to treat dynamic heterogeneity effects and penetrant transport in vitrimers are briefly discussed.

chemical calculations↗

Stretching of immersed polyelectrolyte brushes in shear flow

In this article, the way that polymer brushes respond to shear flow has important implications in various applications, including antifouling, corrosion protection, and stimuli-responsive materials. However, there is still much to learn about the behaviours and mechanisms that govern these responses. To address this gap in knowledge, our study uses in situ X-ray reflectivity to investigate how poly(styrene sulfonate) (PSS) brushes stretch and change in different environments, such as isopropanol (a poor solvent), water (a good solvent), and aqueous solutions containing various cations (Cs + , Ba 2+ , La 3+ , and Y 3+ ). We have designed a custom apparatus that exposes the PSS brushes to both tangential shear forces from the primary flow and upward drag forces from a secondary flow. Our experimental findings clearly show that shear forces have a significant impact on how the chains in PSS brushes are arranged. At low shear rates, the tangential shear force causes the chains to tilt, leading to brush contraction. In contrast, higher shear rates generate an upward shear force that stretches and expands the chains. By analysing electron density profiles obtained from X-ray reflectivity, we gain valuable insights into how the PSS brushes respond structurally, especially the role of the diffuse layer in this dynamic behaviour. Our results highlight the importance of the initial chain configuration, which is influenced by the solvent and cations present, in shaping how polymer brushes respond to shear flow. The strength of the salt bridge network also plays a crucial role in determining how easily the brushes can stretch, with stronger networks offering more resistance to stretching. Ultimately, our study aims to enhance our understanding of polymer physics at interfaces, with a particular focus on practical applications involving polymer brushes.

36 MATERIALS SCIENCE↗

Relating Geometric Nanoconfinement and Local Molecular Environment to Diffusion in Ionic Polymer Membranes

Understanding structure-diffusion relationships in ionic polymer membranes not only illuminates fundamental mechanisms for membrane transport, but also informs further membrane development. In this study, we employ NMR diffusometry and molecular dynamics (MD) simulations to investigate diffusion coefficients and activation energies of diffusion (Ea) for both a lithium-form perfluorosulfonic acid membrane and aqueous solutions of lithium triflate. NMR shows that, at high water/ion molar ratio (?), Ea for water diffusion is slightly lower in the membrane than in solution. Conversely, membrane transport exhibits much higher Ea at low hydration as compared to solutions. MD simulations of a model system consisting of carbon nanotubes with varying diameter reveal that Ea of diffusion clearly relates to both the geometric nanoconfinement of the hydrophilic pathways in the membrane as well as the local molecular environment. These results demonstrate that Ea of diffusion can serve as a revelatory tool for the study of molecular transport processes and the coupling of morphology with transport at the nanoscale. This study thus provides new insights and new experimental and computational models for understanding transport in a wide range of polymer membranes, such as those used in molecular separations applications.

Zhang, Rui↗

Molecular dynamics based study on the effects of cation size on the local structure and diffusion in polymerized ionic liquids

We have used coarse-grained molecular dynamics simulations to understand the effect of cation size on ion diffusion in polymerized ionic liquids at temperatures well above the glass transition temperature of the polymers. We investigated dependencies of the diffusion constant on the cation radius and static dielectric constant and interpreted these results in terms of underlying structural changes, and decoupling phenomenon. We have found non-monotonic effects of the cation radius on the diffusion constant, with a maximum at an intermediate radius resulting from two different size dependent effects. Changes in the radial distribution functions characterizing spatial distribution of cations with respect to anions result in a monotonic increase in the coordination number. This yields an increase in the effective interaction energy as a function of cation radius, which can explain the decrease in the diffusion constant. This increase is counteracted at small cation radii by a corresponding increase in decoupling of cation and anion dynamics. In addition, the diffusion constant is found to increase on increasing the static dielectric constant for all radii of the cations. These results highlight the significant role of decoupling in designing polymerized ionic liquids with an enhanced diffusion constant of cations.

Gillespie, Colin [ORNL] (ORCID:0000000320287080)↗

Robust Chemiresistive Behavior in Conductive Polymer/MOF Composites

Metal-organic frameworks (MOFs) are promising materials for gas sensing but are often limited to single-use detection. A hybridization strategy is demonstrated synergistically deploying conductive MOFs (cMOFs) and conductive polymers (cPs) as two complementary mixed ionic-electronic conductors in high-performing stand-alone chemiresistors. This work presents significant improvement in i) sensor recovery kinetics, ii) cycling stability, and iii) dynamic range at room temperature. The effect of hybridization across well-studied cMOFs is demonstrated based on 2,3,6,7,10,11-hexahydroxytriphenylene (HHTP) and 2,3,6,7,10,11-hexaiminotriphenylene (HITP) ligands with varied metal nodes (Co, Cu, Ni). A comprehensive mechanistic study is conducted to relate energy band alignments at the heterojunctions between the MOFs and the polymer with sensing thermodynamics and binding kinetics. The findings reveal that hole enrichment of the cMOF component upon hybridization leads to selective enhancement in desorption kinetics, enabling significantly improved sensor recovery at room temperature, and thus long-term response retention. This mechanism is further supported by density functional theory calculations on sorbate–analyte interactions. It is also found that alloying cPs and cMOFs enables facile thin film co-processing and device integration, potentially unlocking the use of these hybrid conductors in diverse electronic applications.

36 MATERIALS SCIENCE↗

Variable-Temperature Scattering and Spectroscopy Characterizations for Temperature-Dependent Solution Assembly of PffBT4T-Based Conjugated Polymers

The solution structure of conjugated polymers (CPs) from which the films are cast is critical for tailoring the thin-film morphology thus device performance. Here, we used multimodal variable-temperature scattering and spectroscopy tools to fully quantify the solution assembly of poly[(5,6-difluoro-2,1,3-benzothiadiazol-4,7-diyl)-alt-(3,3'''-dialkyl-2,2';5',2'';5'',2'''-quaterthiophen-5,5'''-diyl)] (PffBT4T) polymers with varying side-chain lengths at different assembly temperatures. The conformational and aggregation behaviors for PffBT4T-based CPs were found to be very sensitive to both temperature and side chain length using ultraviolet–visible (UV–vis) spectroscopy, nuclear magnetic resonance (NMR) spectroscopy, dynamic light scattering (DLS), and small-angle neutron scattering (SANS). We found that with slightly increasing side chain length from 2-octyldodecyl (C8C12) to 2-nonyltridecyl (C9C13), PffBT4T-based CPs show a significant decrease in aggregation-to-dissolved chain transition temperature (10 °C), degree of aggregation, enthalpy change of aggregation, and size of the aggregates in solution. At room temperature, PffBT4T polymer strongly aggregated to form fabric structure with the film thickness of a few nanometers in thickness and hundreds of nanometers in length, as probed by atomic force microscopy (AFM), transmission electronic microscopy (TEM), and dynamic light scattering (DLS). At the elevated temperature above the aggregation-to-dissolved chain transition temperature, PffBT4T is fully dissolved and adopts a semiflexible coil conformation with the persistence length of 3.1 nm for PffBT4T-C8C12 and a slightly increased persistence length of 3.4 nm for PffBT4T-C9C13, according to temperature-dependent SANS measurements. Longer side chains of PffBT4T-C9C13 also lead to less aggregation enthalpy gain compared with PffBT4T-C8C12. This work provides a solution structure manipulating strategy of CPs and thus will inspire the molecular design and processing protocols of CPs toward higher performance electronic devices.

36 MATERIALS SCIENCE↗

Temperature dependence of nuclear quantum effects on liquid water via artificial neural network model based on SCAN meta-GGA functional

We investigate the temperature dependence of nuclear quantum effects (NQEs) on structural and dynamic properties of liquid water by training a neural network force field using first-principles molecular dynamics (FPMD) based on the strongly constrained and appropriately normed meta-generalized gradient approximation exchange-correlation approximation. The FPMD simulation based on density functional theory has become a powerful computational approach for studying a wide range of condensed phase systems. However, its large computational cost makes it difficult to incorporate NQEs in the simulation and investigate temperature dependence of various properties. To circumvent this difficulty, we use an artificial neural network model and employ the thermostatted ring polymer MD approach for studying the temperature dependence of NQEs on various properties. The NQEs generally bring the radial distribution functions closer to the experimental measurements. Translational diffusivity and rotational dynamics of water molecules are both slowed down by the NQEs. The competing inter-molecular and intra-molecular quantum effects on hydrogen bonds, as discussed by Habershon, Markland, and Manolopoulos [J. Chem. Phys. 131(2), 024501 (2019)], can explain the observed temperature dependence of the NQEs on the dynamical properties in our simulation.

Yao, Yi (ORCID:0000000299576979)↗

Rheology of lignin and lignin-based solutions, dispersions, gels, polymer blends, and melts

Lignin is an abundant resource that finds application in energy and sustainable materials development. In addition to the utilization of lignin in three-dimensional (3D) printing and hydrogel production, recent studies have reported the use of lignin as a liquid fuel additive. The characterization of the rheological properties of lignin and its derivatives is a dynamic and evolving field, underpinned by advances in experimental, analytical, and modeling techniques. Here, this review provides a comprehensive overview of the recent progress in the study of lignin rheology, highlighting the interplay between structure, modification, and flow behavior in lignin-based solutions, dispersions, gels, polymer blends, and melts. A specific highlight of this review is how lignin concentration affects the rheological properties of lignin-based solutions and dispersions. Furthermore, the effect of lignin type on the properties of 3D-printed lignin-based composites is discussed. For polymer systems, this review discussed lignin-in-polymer solutions separately from lignin-filled polymer systems. Finally, challenges and perspectives on lignin rheology are presented.

Dispersions↗

Revealing structure and shaping priorities in plant and fungal cell wall architecture via solid-state NMR

Plant and fungal cell walls are essential for growth, adaptation, and survival, with their intricate architectures dictating both resistance to stress and susceptibility to antifungal or biomass-degrading strategies. Understanding how these walls are built, remodeled, and function at the molecular level is therefore central to both clinical and biotechnological applications. Solid-state nuclear magnetic resonance (ssNMR) has emerged as a uniquely powerful tool for this purpose, as it reveals the structure, dynamics, and interactions of intact biopolymers without disrupting their native organization. Using this approach, recent studies have shown how structural polymorphism, polymer-polymer interactions, and species-specific remodeling govern mechanical integrity, drug resistance, and stress adaptation. Applications highlighted here include lignin-carbohydrate packing during plant stem maturation, fungal wall reorganization under treatment by wall-targeting antifungals such as echinocandin and nikkomycin, and the functional diversity of glucans, chitins, and mannans. Together, these insights uncover conserved principles of polymer assembly across kingdoms while informing new opportunities for antifungal development and biomass utilization. Ongoing advances in sensitivity and resolution are expected to broaden the reach of ssNMR and further accelerate its role in linking structural heterogeneity to biosynthetic complexity and biological function.

Antifungal↗

Machine learning enables interpretable discovery of innovative polymers for gas separation membranes

Polymer membranes perform innumerable separations with far-reaching environmental implications. Despite decades of research, design of new membrane materials remains a largely Edisonian process. To address this shortcoming, we demonstrate a generalizable, accurate machine learning (ML) implementation for the discovery of innovative polymers with ideal performance. Specifically, multitask ML models are trained on experimental data to link polymer chemistry to gas permeabilities of He, H 2 , O 2 , N 2 , CO 2 , and CH 4 . We interpret the ML models and extract valuable insights into the contributions of different chemical moieties to permeability and selectivity. We then screen over 9 million hypothetical polymers and identify thousands that lie well above current performance upper bounds, including hundreds of never-before-seen ultrapermeable polymer membranes with O 2 and CO 2 permeability greater than 10 4 and 10 5 Barrers, respectively. High-fidelity molecular dynamics simulations confirm the ML-predicted gas permeabilities of the promising candidates, which suggests that many can be translated to reality.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mapping structures and dynamics with frequency-correlated diffusion exchange

Understanding molecular motion in diffusion-driven complex environments is critical for designing sustainable materials and improving chemical processes. Here, we introduce a multidimensional nuclear magnetic resonance (NMR) method that captures how molecular populations exchange across different dynamic regimes. By extending the modulated gradient spin-echo technique to include frequency-frequency correlations, our approach reveals diffusion pathways that are otherwise obscured in heterogeneous systems. Implemented on a unilateral NMR magnet, the method eliminates gradient pulsing constraints and accesses dynamics in the kilohertz regime. We apply this technique to swelling and acid-catalyzed deconstruction of cross-linked and linear polymers to observe how structural heterogeneity evolves over time. By linking molecular motion to topology and chemical state, we extract physical metrics such as fractal surface dimensionality and reaction wavefront velocity, properties inaccessible with standard diffusion measurements. This work expands the capabilities of NMR for probing soft matter, with implications for polymer recycling and materials design.

Fricke, Sophia N. [University of California, Berke↗

Nonlinear Shear Rheology of Entangled Polymer Rings

Steady-state shear viscosity η($\bar{γ}$) of unconcatenated ring polymer melts as a function of the shear rate $\bar{γ}$ is studied by a combination of experiments, simulations, and theory. Experiments using polystyrenes with Z ≈ 5 and Z ≈ 11 entanglements indicate weaker shear thinning for rings compared to linear polymers exhibiting power law scaling of shear viscosity η ~ $\bar{γ}$ –0.56 ± 0.02 , independent of chain length, for Weissenberg numbers up to about 10 2 . Nonequilibrium molecular dynamics simulations using the bead-spring model reveal a similar behavior with η ~ $\bar{γ}$ -0.57 ± 0.08 for 4 ≤ Z ≤ 57. Viscosity decreases with chain length for high $\bar{γ}$. In our experiments, we see the onset of this regime, and in simulations, which we extended to Wi ~ 10 4 , the nonuniversality is fully developed. In addition to a naive scaling theory yielding for the universal regime η ~ $\bar{γ}$ –0.57 , we developed a novel shear slit model explaining many details of observed conformations and dynamics as well as the chain length-dependent behavior of viscosity at large $\bar{γ}$. The signature feature of the model is the presence of two distinct length scales: the size of tension blobs and much larger thickness of a shear slit in which rings are self-consistently confined in the velocity gradient direction and which is dictated by the size of a chain section with relaxation time 1/$\bar{γ}$. These two length scales control the two normal stress differences. In this model, the chain length-dependent onset of nonuniversal behavior is set by tension blobs becoming as small as about one Kuhn segment. This model explains the approximate applicability of the Cox–Merz rule for ring polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reversible Reactions, Mesh Size, and Segmental Dynamics Control Penetrant Diffusion in Ethylene Vitrimers

The diffusion of two aromatic dyes with nearly identical sizes was measured in ethylene vitrimers with precise linker lengths and borate ester cross-links using fluorescence recovery after photobleaching (FRAP). One dye possessed a reactive hydroxyl group, while the second was inert. The reaction of the hydroxyl group with the network is slow relative to the hopping times of the dye, resulting in a large slowdown by a factor of 50 for a reactive probe molecule. A kinetic model was fit to the fluorescence intensity data to determine rate constants for the reversible reaction of the dye from the network, which confirms the role of slow reaction kinetics. A second network cross-linker was also investigated with a substituted boronic ester showing ∼10,000 times faster exchange kinetics. In this system, the two dyes show the same diffusion coefficient, as the reaction is no longer the rate-limiting step. The role of dense meshes on small and large dyes is also discussed in the context of the existing theories. Finally, these results highlight the potential of dynamic networks to control penetrant transport through synergistic effects of the mesh size, dynamic bond kinetics, and penetrant–network interactions.

confinement↗

Enhancing Thermal Transport in Polymeric Composites Via Engineered Noncovalent Filler–Polymer Interactions

Understanding thermal transport mechanisms in polymeric composites allows us to expand the boundaries of thermal conductivity in them, either increasing it for more efficient heat dissipation or decreasing it for better thermal insulation. But, these mechanisms are not fully understood. Systematic experimental investigations remain limited. Practical strategies to tune the interfacial thermal resistance (ITR) between fillers and polymers and the thermal conductivity of composites remain elusive. Here, we studied the thermal transport in representative polymer composites, using polyethylene (PE) or polyaniline (PANI) as matrices and graphite as fillers. PANI, with aromatic rings in its backbone, interacts with graphite through strong noncovalent π–π stacking interactions, whereas PE lacks such interactions. We can then quantify how π–π stacking interactions between graphite and polymers enhance thermal transport in composites. PE/graphite and PANI/graphite composites with the same 1.5% filler volume fractions show a ∼22.82% and ∼34.85% enhancement in thermal conductivity compared to pure polymers, respectively. Calculated ITRs in PE/graphite and PANI/graphite are ~6 x 10 -8 m 2 KW -1 and ~1 x 10 -8 m 2 KW -1 , respectively, highlighting how π–π stacking interactions reduce ITR. Molecular dynamics (MD) simulations suggest that π–π stacking interactions between PANI chains and graphite surfaces enhance alignment of PANI's aromatic rings with graphite surfaces. This allows more carbon atoms from PANI chains to interact with graphite surfaces at a shorter distance compared to PE chains. Finally, our work indicates that tuning the π–π stacking interactions between polymers and fillers is an effective approach to reduce the ITR and enhance the thermal conductivity of composites.

atoms↗