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At least 577 records · Page 32

Ion-Conducting Dynamic Solid Polymer Electrolyte Adhesives

Cross-linked polymer electrolytes containing structurally dynamic disulfide bonds have been synthesized to investigate their combined ion transport and adhesive properties. Dynamic network polymers of varying cross-link densities are synthesized via thiol oxidation of a bisthiol monomer, 2,2'-(ethylenedioxy)diethanethiol, and tetrathiol cross-linker, pentaerythritol tetrakis(3-mercaptopropionate). At optimal loading of lithium bis(trifluoromethane-sulfonyl-imide) (LiTFSI) salt, the ionic conductivities (σ) at 90 °C are about 1 × 10–4 and 1 × 10–5 S/cm at the lowest and highest cross-linking, respectively. Notably, in comparison to the equivalent nondynamic network, the dynamic network shows a positive deviation in σ above 90 °C, which suggests the enhancement of ion transport occurs from the difference in structural relaxation on account of the dissociation of disulfide bonds. Lap shear adhesion and conductivity tests on ITO-coated glass substrates reveal the dynamic network exhibits a higher adhesive shear strength of 0.2 MPa (vs 0.03 MPa for the nondynamic network) and higher σ after the application of external stimulus (UV light or heat). The adhesive strength and σ are stable over multiple debonding/rebonding cycles and, thus, demonstrating the utility of these structurally dynamic networks as solid polymer electrolyte adhesives.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Reducing delamination of an electron-transporting polymer from a metal oxide for electrochemical applications

Delamination of the electron-transporting polymer N2200 from indium tin oxide (ITO) in aqueous electrolytes is mitigated by modifying ITO with an azide-functionalized phosphonic acid (PA) which, upon UV irradiation, reacts with the polymer. Here, the optical, electrochemical, and spectroelectrochemical properties of N2200 thin films are retained in aqueous and non-aqueous media.

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Two Mesoporous Domains Are Better Than One for Catalytic Deconstruction of Polyolefins

Catalytic hydrogenolysis of polyolefins into valuable liquid, oil, or wax-like hydrocarbon chains for second-life applications is typically accompanied by the hydrogen-wasting co-formation of low value volatiles, notably methane, that increase greenhouse gas emissions. Catalytic sites confined at the bottom of mesoporous wells, under conditions in which the pore exerts the greatest influence over the mechanism, are capable of producing less gases than unconfined sites. A new architecture was designed to emphasize this pore effect, with the active platinum nanoparticles embedded between linear, hexagonal mesoporous silica and gyroidal cubic MCM-48 silica (mSiO 2 /Pt/MCM-48). This catalyst deconstructs polyolefins selectively into ~C 20 –C 40 paraffins and cleaves C–C bonds at a rate (TOF = 4.2 ± 0.3 s –1 ) exceeding that of materials lacking these combined features while generating negligible volatile side products including methane. The time-independent product distribution is consistent with a processive mechanism for polymer deconstruction. In contrast to time- and polymer length-dependent products obtained from non-porous catalysts, mSiO 2 /Pt/MCM-48 yields a C 28 -centered Gaussian distribution of waxy hydrocarbons from polyolefins of varying molecular weight, composition, and physical properties, including low-density polyethylene, isotactic polypropylene, ultrahigh-molecular-weight polyethylene, and mixtures of multiple, post-industrial polyolefins. Here, coarse-grained simulation reveals that the porous-core architecture enables the paraffins to diffuse away from the active platinum site, preventing secondary reactions that produce gases.

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Anomalous dips in reflection spectra of optical polymers deposited on plasmonic metals

Abstract We have studied reflection spectra of dye-doped and undoped polymers deposited onto Ag and Au substrates and found anomalous dips in the UV spectral range. On top of Ag substrates, the λ ∼ 375 nm dips were observed in undoped PMMA, PVP, and PS polymers as well as PMMA doped with Rh590 and HITC laser dyes. In silver-based samples, the spectral positions of the observed reflection dips were close to singularities in the refractive indexes of surface plasmon polaritons (SPPs) propagating at the interface between Ag and polymer. The latter singularities can tentatively explain the λ ∼ 375 nm reflection dips, if the scattering of Ag and polymeric films is large enough to launch SPP without any prism or grating. The dips observed in reflection of Rh590:PMMA and HITC:PMMA on top of Au, were more pronounced than those on Ag, broader, shifted to shorter wavelengths, and their spectral positions had large standard deviations. Furthermore, no anomalous dips in gold-based samples were observed in the reflection spectra of undoped PMMA, PVP, and PS polymers, and a modest singularity in the SPP refractive index, predicted theoretically at λ ∼ 500 nm, cannot explain the dips in the UV reflection spectra observed experimentally. It appears likely that the origin of the reflection dips on top of Au substrates is different from that on top of Ag substrates.

36 MATERIALS SCIENCE↗

Structure and Dispersion of Free and Grafted Polymer in Nanoparticle Organic Hybrid Materials-Based Solutions by Small-Angle Neutron Scattering

Liquid-like Nanoscale Organic Hybrid Materials or NOHMs consisting of polymer grafted nanoparticles have shown great promise in applications, such as electrochemistry and gas separation, due to their enhanced conductivity, tunability, and negligible vapor pressure. Recently, NOHMs are considered to be used as novel electrolytes in Redox Flow Batteries (RFBs). However, to employ NOHMs in redox flow batteries as electrolytes, it is important to understand the conformation and dispersion of NOHMs in the electrochemical milieu. In this work, we report the use of small-angle neutron scattering to probe the structure and dispersion of Jeffamine M2070 polymer grafted to a SiO 2 nanoparticle in an aqueous solution with and without the presence of a supporting electrolyte. Our results indicate that, in the aqueous environment, there exists a large amount of free polymer in the solution that is not grafted to the functionalized nanoparticles. These protonated free polymers, dispersed in the aqueous solvent, may also strongly interact with the grafted polymer layer and greatly affect the neat structure of NOHMs. Thus, there also exist polymers identified as “interacting” polymers to distinguish them from tethered or truly free polymers in the fluid system. The presence of supporting electrolyte shows a greater effect on the structure of NOHMs-based fluid as it not only alters the structure of the free polymer but also hinders the interaction of the polymer with the functionalized nanoparticles. Moreover, the change in the interaction of the Jeffamine M2070 with the functionalized nanoparticles due to the addition of supporting electrolyte has revealed a drastic change in the viscosities of NOHM solutions. Overall, the dispersion of the free polymer, the interaction of the interacting polymer with grafted polymer, and the change in conformation of free polymer and grafted layers with the addition of supporting electrolyte provide valuable insight into the overall scenario of the electrochemical environment of NOHMs. These results can be applied to fine-tune the structure of liquid-like NOHMs and will aid in a better understanding of their performance as potential electrolytes in RFBs.

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Imaging a solvent-swollen polymer gel network by open liquid transmission electron microscopy

Visualizing the network of a solvent-swollen polymer gel remains problematic. To address this challenge, open transmission electron microscopy (TEM) was applied to thin gel films permeated by a nonvolatile ionic liquid. The targeted physical gels were prepared by cooling concentrated solutions of poly(ethylene glycol) in 1-ethyl-3-methyl imidazolium ethyl sulfate [EMIM][EtSO 4 ]. During the cooling, gelation occurred by a frustrated crystallization of the dissolved polymer, leading to a percolated, solvent-permeated semicrystalline network in which nanoscale polymer crystals acted as crosslinks. Crystalline features ranging from ~5 to ~200 nm were observed, with the visible network strands dominantly consisting of long curvilinear crystallites of ~15–20 nm diameter. Nascent spherulites irregularly decorated the network, creating a complex structural hierarchy that complicated analyses. Lacking diffraction contrast, TEM did not visualize the many disordered, fully solvated PEG chains present in the voids between crystals. Finally, recognizing that a network's three dimensionality is ambiguous when assessed through two-dimensional microscopy projections, a small gel region was studied by TEM tomography, revealing a nearly isotropic three-dimensional arrangement of the curvilinear crystallites, which displayed remarkably uniform cylindrical cross sections.

36 MATERIALS SCIENCE↗

Overview of Elastic Orthotropic Fiber Reinforced Polymer Modular Damage Model for Library of Advanced Materials for Engineering (LAMÉ)

This memo includes the documentation sections for the Library of Advanced Materials for Engineering (LAMÉ) manual for a fiber reinforced polymer composite damage model (Elastic_Orthotropic_FRP_Modular_Damage) in advance of the next Sierra/SM and LAMÉ release consistent with the transition of the model from development to a production capability. This new model capability provides both a set of physically based orthotropic damage criteria as well as orthotropic material softening for woven fiber reinforced polymer composite materials. The documentation sections include short sections on theory, implementation, verification, and user guidance to prescribe the model in a Sierra/SM input file.

36 MATERIALS SCIENCE↗

Partial Solvation of Lithium Ions Enhances Conductivity in a Nanophase-Separated Polymer Electrolyte

In this study, we demonstrate that a multiblock lithium-ion-conducting polymer can be swollen with ethylene carbonate solvent to increase the conductivity relative to the dry polymer material by nearly 4 orders of magnitude. This increase is due to the partial solvation of lithium ions by ethylene carbonate, which leads to Li + diffusion along the solvent–polymer interface. This differs from the vehicular transport mechanism for lithium ions in pure solvent. We use a combination of broadband dielectric spectroscopy, X-ray scattering, and all-atom molecular dynamics simulations to probe the effect of the solvent on the polymer morphology and to elucidate the mechanism of lithium ion transport.

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Polymerization of Terminal Acetylenes by a Bulky Monophosphine-Palladium Catalyst

A well-defined palladium complex [(tBuXPhos)Pd(Me)(BAr f )] bearing a bulky monophosphine ligand was synthesized and fully characterized. X-ray diffraction analysis shows that the 1,3,5-triisopropylaryl group of the dialkylbiaryl phosphine ligand exhibits a weak η 6 -interaction with the Pd(II) center. This catalyst exhibits excellent functional group tolerance and polymerizes propargyl esters containing benzoyl and acetyl groups, propargyl methyl ether, propargyl alcohol, benzyl acetylene, and phenyl acetylene to yield polymers with M n values in the range of 5–15 kDa with monomodal molecular weight distributions between ca. 1.4 and 2.1.

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Physics augmented machine learning discovery of composition-dependent constitutive laws for 3D printed digital materials

Multi-material 3D printing, particularly through polymer jetting, enables the fabrication of digital materials by mixing distinct photopolymers at the micron scale within a single build to create a composite with tunable mechanical properties. Here, this work presents an integrated experimental and computational investigation into the composition-dependent mechanical behavior of 3D printed digital materials. We experimentally characterize five formulations, combining soft and rigid UV-cured polymers under uniaxial tension and torsion across three strain and twist rates. The results reveal nonlinear and rate-dependent responses that strongly depend on composition. To model this behavior, we develop a physics-augmented neural network (PANN) that combines a partially input convex neural network (pICNN) for learning the composition-dependent hyperelastic strain energy function with a quasi-linear viscoelastic (QLV) formulation for time-dependent response. The pICNN ensures convexity with respect to strain invariants while allowing non-convex dependence on composition. To enhance interpretability, we apply $L_0$ sparsification. For the time-dependent response, we introduce a multilayer perceptron (MLP) to predict viscoelastic relaxation parameters from composition. The proposed model accurately captures the nonlinear, rate-dependent behavior of 3D printed digital materials in both uniaxial tension and torsion, achieving high predictive accuracy for interpolated material compositions. This approach provides a scalable framework for automated, composition-aware constitutive model discovery for multi-material 3D printing.

Constitutive modeling↗

Effect of Added Salt on Disordered Poly(ethylene oxide)-Block-Poly(methyl methacrylate) Copolymer Electrolytes

In this report we studied the effect of salt addition on a diblock copolymer system with a negative Flory-Huggins interaction parameter, χ, indicative of attractive interactions between the two blocks. The system studied is poly(ethylene oxide)-block-poly(methyl methacrylate) (PEO-PMMA) with added lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) salt. We studied two asymmetric block copolymers, PEO-PMMA(10-33) and PEO-PMMA(10-64), where the numbers refer to the molar masses of the blocks in kg mol -1 . The small-angle X-ray scattering (SAXS) profiles for PEO-PMMA(10-33) were featureless at all salt concentrations. In contrast, PEO-PMMA(10-64) exhibited SAXS peaks when the salt concentration was between 0.22 ≤ m (mol Li/kg polymer) ≤ 0.44. The appearance of SAXS peaks only in PEO-PMMA(10-64) is consistent with the predictions of ionic self-consistent field theory developed by de la Cruz and co-workers, which predicts that in systems with negative χ, ordered phases are only found when the volume fraction of the ionic block is about 10%.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structure–Function Relationships in Sequence-Controlled Copolymers for Rare Earth Element Chelation

The ability to tune material function through primary sequence is a defining feature of biological macromolecules, allowing precise control over structure and target interactions in complex aqueous environments. However, translating sequence–structure–function relationships to synthetic macromolecules is challenging due to their dispersity in sequence, conformation, and composition. Here, we report systematic studies of amphiphilic polymer chelators designed to probe how composition and patterning influence binding affinity and selectivity for rare earth elements (REEs), a series of technologically relevant metals with challenging separation profiles. A library of copolymers varying hydrophobic monomer composition and patterning was synthesized via reversible addition–fragmentation chain transfer (RAFT) polymerization, spanning statistical, gradient, and block architectures. REE binding was quantified using a high-throughput colorimetric assay, and reconstruction of polymer ensembles using kinetic stochastic simulations enabled quantitative comparisons of sequence heterogeneity, linking local monomer colocalization to emergent REE binding. Further, we investigated the role of different hydrophobic comonomers in tuning metal coordination, with binding trends linked to structural features that influence binding site desolvation. Complementary dynamic light scattering (DLS) and small-angle X-ray scattering (SAXS) measurements showed that both polymer and monomer architecture modulate metal-induced conformational changes, and that multichain assembly behavior emerges beyond critical hydrophobic thresholds. Sequence control also altered REE selectivity, with nonmonotonic differences observed across compositionally identical polymers with different sequence architectures. Together, these findings establish design principles that connect polymer sequence and structure to binding performance, guiding the design of macromolecular chelators with enhanced affinity and selectivity for applications in separations, sensing, and catalysis.

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Applications of Fracture Mechanics to Quantitative Accelerated Life Testing of Plastic Encapsulated Microelectronics

Accelerated testing must address the failure mechanisms active within the devices undergoing tests in order to assess lifetimes in a meaningful way. The assumption of constant temperature, thermally activated lifetime, based upon the Arrhenius assumptions, does not always provide the necessary understanding to interpret accelerated tests in microelectronics. Plastic encapsulants, dielectric polymers, and underfill materials are subject to delamination and cracking with thermal cycling. Crack propagation during use environment exposure, drives the potential for failure of microelectronic devices and is therefore a necessary focal point in qualification and life testing. This paper reviews the available research in the application of fracture mechanics to this class of problems in microelectronics including relevant test data. In addition, useful acceleration factor models are derived for polymer crack propagation based on principles of linear elastic fracture mechanics. Further, a simple approach to estimating the minimum temperature cycling ranges, necessary to propagate a crack, is also presented. Finally, a methodology of applying acceleration factors to develop testing plans is shown, with an example in spaceflight for a cubesat in low Earth orbit. Overall, this is a paper that shows a useful and appropriate process for creating physics of failure based life testing for delamination and cracking failures in microelectronic polymers in a temperature cycling environment.

Accelerated testing↗

Extensional Rheology Experiment Developed to Investigate the Rheology of Dilute Polymer Solutions in Microgravity

A fundamental characteristic of fluid is viscosity; that is, the fluid resists forces that cause it to flow. This characteristic, or parameter, is used by manufacturers and end-users to describe the physical properties of a specific material so that they know what to expect when a material, such as a polymer, is processed through an extruder, a film blower, or a fiber-spinning apparatus. Normally, researchers will report a shear viscosity that depends on the rate of an imposed shearing flow. Although this type of characterization is sufficient for some processes, simple shearing experiments do not provide a complete picture of what a processor may expect for all materials. Extensional stretching flows are common in many polymer-processing operations such as extrusion, blow molding, and fiber spinning. Therefore, knowledge of the complete rheological (ability to flow and be deformed) properties of the polymeric fluid being processed is required to accurately predict and account for the flow behavior. In addition, if numerical simulations are ever able to serve as a priori design tools for optimizing polymer processing operations such as those described above, an accurate knowledge of the extensional viscosity of a polymer system and its variation with temperature, concentration, molecular weight, and strain rate is critical.

Logsdon, Kirk A.↗

Using Flory–Huggins-informed human-in-the-loop Bayesian optimization to map the phase diagram of polymer blends

Mapping the phase diagram of polymer blends is an essential step in controlling the structure–property relationship of polymer-based materials. However, traditional grid-based approaches are inefficient and rely on subjective judgements for terminating the experimental campaign. Artificial intelligence-guided experimentation offers a compelling alternative, especially when data-driven decision-making is interfaced with established polymer thermodynamics to improve efficiency and interpretability. Here, we introduce a physics-informed Bayesian optimization approach to guide the mapping of the phase diagram of a model blend containing poly(methyl methacrylate) and poly(styrene-ran-acrylonitrile). Physical information is derived from a Flory–Huggins representation of the spinodal curve, which is integrated into the Bayesian optimization process as a structured prior mean that acts as a soft constraint. Implemented as a human-in-the-loop workflow, the approach leverages optical imaging of film cloudiness with iterative Gaussian process surrogate modeling and a parameter selection decision policy to identify the composition-temperature conditions for sequential iterations. Convergence of kernel and Flory–Huggins-based hyperparameters provided a stopping criterion, ensuring an objective and interpretable termination of the experimental campaign. The framework recovered the known lower critical solution temperature (∼160 °C), while increasing material efficiency through targeted sampling. This work establishes a proof-of-concept for the application of Bayesian optimization workflows to study polymer blend miscibility.

36 MATERIALS SCIENCE↗

Helical Covalent Polymers with Unidirectional Ion Channels as Single Lithium-Ion Conducting Electrolytes

Single-ion conducting polymer electrolytes have attracted great attention as safe alternatives to liquid electrolytes in high energy density lithium-ion batteries. Herein, we report the first example of a crystalline anionic helical polymer as a single lithium-ion conducting solid polymer electrolyte (SPE). Single-crystal X-ray analysis shows that the polymer folds into densely packed double helices, with bundles of unidirectional negatively charged channels formed that can facilitate lithium-ion transportation. Such a helical covalent polymer ( HCP) exhibits excellent room temperature lithium-ion conductivity (1.2 x 10 -3 S cm -1 ) in the absence of external lithium salts, a high transference number (0.84), low activation energy (0.14 eV), and a wide electrochemical stability window (0.2-5 V). We found that nonflammable, nonvolatile ionic liquid can serve as a solvating medium and excellent conductivity enhancer (>1000 times increase). These ion-conducting properties are comparable to the best polyethylene oxide-based polymer electrolytes mixed with lithium salts. Finally, we show that the solvated HCP SPE enables the reversible cycling of an all-solid-state cell prepared with a high-voltage NMC 811 cathode. Our study opens up new possibilities for developing next-generation high-performance solid-state electrolytes.

25 ENERGY STORAGE↗

Artificial Intelligence for Conjugated Polymers

Conjugated polymers have garnered significant attention due to their diverse applications in electronics, photonics, and energy storage. However, realizing their full potential poses a formidable challenge, as their design has historically relied on iterative adjustments and continuous inspiration from researchers. Traditional methods often struggle to efficiently navigate their vast chemical landscape. In this work, the application of artificial intelligence (AI), specifically machine learning (ML), needs to be discussed in the realm of conjugated polymers. Our paper emphasizes the importance of understanding the structure–property relationships of these polymers and how ML can facilitate property prediction and inverse-design. We delve into various chemical fingerprints, structural descriptors, and ML algorithms, showcasing their utility across a spectrum of applications, including simulations, glass transition temperature determination, photovoltaics, reorganization energy for charge transport, photocatalysts, and sensors. Finally, we give some outlooks in this filed and propose unexplored areas within the field that hold the potential to benefit from ML techniques.

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