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At least 127 records · Page 7

Miktoarm Star Polymers: Synthesis and Applications

Polymers with precisely controlled structure and function are in high demand across a diverse array of applications spanning the life sciences and nanotechnology. One prototypical example is a class of branched block copolymers known as miktoarm stars (μ-stars), which contain two or more arm compositions connected at a common junction. Miktoarm stars have attracted considerable attention since their physical properties can be different from conventional linear block copolymers. This perspective highlights the latest developments and historical context in the field of miktoarm star polymers, including design strategies, synthetic techniques, and advanced characterization tools used to avoid common preparation pitfalls and tailor properties for emerging applications. Furthermore, our contemporary perspective on μ-star polymers is a resource for inspiring future research into this exciting class of materials at the intersection of chemistry, physics, and advanced technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Coupling and Decoupling between Stickers and Backbones in Associating Polymers with Terminally Functionalized Side Chains

Associating polymers have recently attracted tremendous attention as self-healing polymers due to the dynamic reversibility of sticker association–dissociation processes. These sticker dynamics inevitably slow significantly as segmental dynamics decelerate below the glass transition temperature that limits the operational temperatures of associating polymers. Using broadband dielectric spectroscopy on a new set of associating polymers composed side chains of various lengths and terminal carboxylic-acid sticker functionality, we discovered an unexpected decoupling near the glass transition (T g ) between the slower backbone and fast sticker motions. These two motions have distinct activation energies for the motion of the sulfur linkage adjacent to the backbone (~22 to 26 kJ/mol) and the carboxylic acid groups (~5 to 8 kJ/mol). A second decoupling appears in the polymer with the longest side chain length at T g – 20 K, reflecting the dynamics of various carboxylic acid binding configurations. Furthermore, our findings open the door to design associating polymers with the capability of sticker association/dissociation at low temperatures.

36 MATERIALS SCIENCE↗

Design Principles for Using Amphiphilic Polymers To Create Microporous Water

Aqueous dispersions of microporous nanocrystals with dry, gas-accessible pores—referred to as “microporous water”—enable high densities of gas molecules to be transported through water. For many applications of microporous water, generalizable strategies are required to functionalize the external surface of microporous particles to control their dispersibility, stability, and interactions with other solution-phase components—including catalysts, proteins, and cells—while retaining as much of their internal pore volume as possible. Here, in this work, we establish design principles for the noncovalent surface functionalization of hydrophobic metal–organic frameworks with amphiphilic polymers that render the particles dispersible in water and enhance their hydrolytic stability. Specifically, we show that block co-polymers with persistence lengths that exceed the micropore aperture size of zeolitic imidazolate frameworks (ZIFs) can dramatically enhance ZIF particle dispersibility and stability while preserving porosity and >80% of the theoretical O 2 carrying capacity. Moreover, enhancements in hydrolytic stability are greatest when the polymer can form strong bonds to exposed metal sites on the external particle surface. More broadly, our insights provide guidelines for controlling the interface between polymers and metal–organic framework particles in aqueous environments to augment the properties of microporous water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

De Novo Design of Molecular Recognition for Sequence Defined Polymers

The proposed research aims at developing a computational framework that allows the de novo design of sequence defined polymers for molecular recognition. This framework will include the prediction of the 1) accessible backbone conformational space in solution environments for small to medium polymer length and 2) how side chains of different size and functionality can be used to design convergent or divergent receptor configurations. A structural database inspired by the protein database will be build that can be used to construct larger scaffolds based on smaller sequences

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Engineered Polymer Architectures for Thermo–Responsive Desiccants in Dehumidification Applications

Humidity control is relevant to many processes in buildings and manufacturing and is responsible for over 600 million tons of CO 2 annually. As such, desiccants that can efficiently remove moisture from air can greatly reduce emissions. A new class of desiccant materials, thermo–responsive desiccants, has been of increased interest in the literature. These materials are generally based on thermo–responsive polymers and exhibit a temperature–dependent isotherm, an attribute that is small in traditional desiccants. In this work, seven key parameters needed to create an effective thermo–responsive polymer desiccant are identified using a combination of modeling and experimental data. Further, it is found that more thermo–responsiveness is not necessarily better for energy efficiency, and that an optimal, “medium” value is desired. Additionally, polymer composition and architecture play key roles in adjusting the seven key parameters. Finally, based on findings from both modeling and experimental work, guidelines on synthesizing future thermo–responsive polymer desiccants are presented.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Rational Design of Novel Biomimetic Sequence-Defined Polymers for Mineralization Applications

Silica biomineralization is a naturally occurring process, wherein organisms use proteins and other biological structures to direct the formation of complex, hierarchical nanostructures. Discovery and characterization of such proteins and their underlying mechanisms spurred significant efforts to identify routes for biomimetic mineralization that reproduce the exquisite shapes and size selectivities found in nature. A common strategy has been the use of short peptide sequences with chemistry mimicking those found in natural systems, such as the use of the silaffin-derived R5 peptide. While progress has been made using this approach, there are many limitations that have prevented breakthroughs in biomimicry. To advance our ability to use charged macromolecules for silica formation, we propose to use sequence-defined synthetic polymers known as peptoids, or N-substituted polyglycines, which present significant capability for the precise tuning of sequence and structure beyond what can often be achieved with peptides alone. This study presents a computationally predicted design of these polymers that leads to the controlled formation of silica nanomaterials. We investigate surface adsorption and the mineralization process through analysis of binding mechanisms and energetics of the R5 system. Next, we synthesized two R5-inspired peptoids and validated our prediction in the design of mineralization polymers through characterization using surface plasmon resonance and electron microscopy. Here, this computationally guided study holds great promise for designing new sequences with unprecedented control of the placement of chemical functional groups, thus allowing for further unraveling of silicification mechanisms and the eventual design of sequence-defined synthetic polymers leading to the predictive synthesis of nanostructured functional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dihydroxyterephthalate—A Trojan Horse PET Counit for Facile Chemical Recycling

Abstract Here, low‐energy poly(ethylene terephthalate) (PET) chemical recycling in water: PET copolymers with diethyl 2,5‐dihydroxyterephthalate (DHTE) undergo selective hydrolysis at DHTE sites, autocatalyzed by neighboring group participation, is demonstrated. Liberated oligomeric subchains further hydrolyze until only small molecules remain. Poly(ethylene terephthalate‐ stat ‐2,5‐dihydroxyterephthalate) copolymers were synthesized via melt polycondensation and then hydrolyzed in 150–200 °C water with 0–1 wt% ZnCl 2 , or alternatively in simulated sea water. Degradation progress follows pseudo‐first order kinetics. With increasing DHTE loading, the rate constant increases monotonically while the thermal activation barrier decreases. The depolymerization products are ethylene glycol, terephthalic acid, 2,5‐dihydroxyterephthalic acid, and bis(2‐hydroxyethyl) terephthalate dimer, which could be used to regenerate virgin polymer. Composition‐optimized copolymers show a decrease of nearly 50% in the Arrhenius activation energy, suggesting a 6‐order reduction in depolymerization time under ambient conditions compared to that of PET homopolymer. This study provides new insight to the design of polymers for end‐of‐life while maintaining key properties like service temperature and mechanical properties. Moreover, this chemical recycling procedure is more environmentally friendly compared to traditional approaches since water is the only needed material, which is green, sustainable, and cheap.

36 MATERIALS SCIENCE↗

Applying machine learning and quantum chemistry to predict the glass transition temperatures of polymers

Glass transition temperature (T g ) is important for understanding the physical and mechanical properties of a polymer material because it relates to the thermal energy required to transition between a hard glassy state and a soft rubbery one. Over the years, various models have been developed for predicting this thermal property from molecular structure to aid in designing novel polymers in selected classes. This work builds on those efforts by utilizing both machine learning (ML) and quantum chemistry (QC) techniques to develop models that can predict T g values from the molecular structure under different data availability scenarios and for a wide variety of polymer types. For the ML model, a graph convolutional network (GCN) was used to map topological polymer features; this model was trained against a dataset of more than 7500 T g values and resulted in a root mean square error (RMSE) of 38.1 °C. The QC-based regression model was trained on 83 T g values and produced an RMSE of 34.5 °C. In conclusion, this work demonstrated that while both model techniques produce accurate predictions and are suitable for different data availability scenarios, the QC-based regression model offered a more interpretable model framework with significantly less training data.

36 MATERIALS SCIENCE↗

Impact of Side Chain Chemistry on Lithium Transport in Mixed Ion–Electron-Conducting Polymers

We discuss how typical design strategies for mixed ion-electron conduction in polymers have focused on overall ionic conductivity, without specificity for anion vs. cation conduction. Here, we demonstrate that side chain chemistry can be used to control Li+ conductivity in semiconducting polymers. This design principle is significant for applications which require Li+ specific transport, such as Li-ion batteries. We show that a polythiophene functionalized with an ionic liquid side chain demonstrates higher conductivity and lithium transference than a more commonly studied ether-functionalized P3AT derivative. Poly(3-(6’-(N-methylimidazolium) hexyl)thiophene TFSI–) (P3HT-Im+TFSI–) can solvate and conduct ions up to salt concentrations of r=1.0 (where r = [moles of salt]/[moles of monomer]) while achieving ionic conductivity of ≈10–3 S/cm at 80°C, and a lithium transference number of 0.36. On the other hand, poly(3¬-(methoxyethoxyethoxymethyl) thiophene) (P3MEEMT) shows a peak conductivity of ≈10–5 S/cm at r=0.05 and 80°C, with near zero lithium transport. This work shows that multiple high dielectric moieties can be used to drive ion conduction in semiconducting polymers, but diffuse, cationic side chains such as imidazolium are preferred for Li-ion conduction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Covalent adaptable polymer networks with CO 2 -facilitated recyclability

Cross-linked polymers with covalent adaptable networks (CANs) can be reprocessed under external stimuli owing to the exchangeability of dynamic covalent bonds. Optimization of reprocessing conditions is critical since increasing the reprocessing temperature costs more energy and even deteriorates the materials, while reducing the reprocessing temperature via molecular design usually narrows the service temperature range. Exploiting CO 2 gas as an external trigger for lowering the reprocessing barrier shows great promise in low sample contamination and environmental friendliness. Herein, we develop a type of CANs incorporated with ionic clusters that achieve CO 2 -facilitated recyclability without sacrificing performance. The presence of CO 2 can facilitate the rearrangement of ionic clusters, thus promoting the exchange of dynamic bonds. The effective stress relaxation and network rearrangement enable the system with rapid recycling under CO 2 while retaining excellent mechanical performance in working conditions. This work opens avenues to design recyclable polymer materials with tunable dynamics and responsive recyclability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Thermomechanical Analysis of Polysulfone-Nanodiamond Mixed Matrix Membranes

Idaho National Laboratory is developing a polymer membrane designed to concentrate oxygen from air to assist in cleaner coal combustion and other gasification processes. These membranes were formed by adding nanodiamond particles to enhance their transport properties. This study focuses on the thermomechanical analysis (TMA) of these membranes to probe the behavior between the nanodiamond particles and the polymer.

20 FOSSIL-FUELED POWER PLANTS↗

Tuning polymer-backbone coplanarity and conformational order to achieve high-performance printed all-polymer solar cells

Abstract All-polymer solar cells (all-PSCs) offer improved morphological and mechanical stability compared with those containing small-molecule-acceptors (SMAs). They can be processed with a broader range of conditions, making them desirable for printing techniques. In this study, we report a high-performance polymer acceptor design based on bithiazole linker (PY-BTz) that are on par with SMAs. We demonstrate that bithiazole induces a more coplanar and ordered conformation compared to bithiophene due to the synergistic effect of non-covalent backbone planarization and reduced steric encumbrances. As a result, PY-BTz shows a significantly higher efficiency of 16.4% in comparison to the polymer acceptors based on commonly used thiophene-based linkers (i.e., PY-2T, 9.8%). Detailed analyses reveal that this improvement is associated with enhanced conjugation along the backbone and closer interchain π-stacking, resulting in higher charge mobilities, suppressed charge recombination, and reduced energetic disorder. Remarkably, an efficiency of 14.7% is realized for all-PSCs that are solution-sheared in ambient conditions, which is among the highest for devices prepared under conditions relevant to scalable printing techniques. This work uncovers a strategy for promoting backbone conjugation and planarization in emerging polymer acceptors that can lead to superior all-PSCs.

14 SOLAR ENERGY↗

Controlled catalyst-transfer polymerization in graphene nanoribbon synthesis

Exercising direct control over the unusual electronic structures arising from quantum confinement effects in graphene nanoribbons (GNRs) is intimately linked to geometric boundary conditions imposed by the structure of the ribbon. Besides composition and position of substitutional dopant atoms, the symmetry of the unit cell, width, length, and termination of a GNR govern its electronic structure. Here, we present a rational design that integrates each of these interdependent variables within a modular bottom-up synthesis. Our hybrid chemical approach relies on a catalyst-transfer polymerization that establishes excellent control over length, width, and end groups. Complemented by a surface-assisted cyclodehydrogenation step, uniquely enabled by matrix-assisted direct (MAD) transfer protocols, geometry and functional handles encoded in a polymer template are faithfully mapped onto the structure of the corresponding GNR. Bond-resolved scanning tunneling microscopy (BRSTM) and spectroscopy (STS) validate the robust correlation between polymer template design and GNR electronic structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

AI‐Accelerated Optimization of Self‐Assembled Organic Mixed Ionic‐Electronic Conductors (OMIEC) (Final Report)

This document describes research activities, products and outcomes of a DOE-funded program to help accelerate development of Organic Mixed Ionic Electronic Conductors (OMIECs) using neutron scattering and high-throughput experimentation. OMIECs are organic materials that conduct both ionic and electronic charge carriers. For these new OMIEC materials, self-assembling ion-conducting block copolymers (BCPs) are used as a structural template for electronic conducting polymers. This forms OMIECs with long-range structural order that can help facilitate long-range electronic transport. The conductive properties of OMIECs are closely associated with their structure, which is affected by solution conditions and polymer macromolecular designs. Thus high-throughput experimentation has been implemented to explore this large design space effectively. The BCP-CP OMIEC systems explored are composed of ion-conducting diblock or triblock copolymers containing polyethylene oxide (PEO), di(ethylene glycol) ethyl ether acrylate (DEGEEA) or poly(ethylene glycol) methyl ether acrylate) (PEGMEA) hydrophilic blocks. These blocks will be coupled with either polypropylene oxide (PPO) or polyheptafluorobutyl acrylate (PHFBA) hydrophobic blocks to drive assembly. The electronic conducting component consists of several different types of conjugated polymers. Small angle scattering of neutrons and X-rays (SANS/SAXS) as well as electrochemical analysis have been coupled with modern algorithms for autonomous research using artificial intelligence (AI).

36 MATERIALS SCIENCE↗

Design and Analysis of a Floating-Wind Shallow-Water Mooring System Featuring Polymer Springs

This paper presents a mooring system design featuring polymer springs for the VolturnUS-S 15-MW reference floating wind turbine in site conditions for the New York Bight at a 50-m water depth. Polymer springs have a nonlinear stress-strain curve that allows a stiffer response at low loads and a more flexible response at higher loads, potentially reducing peak mooring line tensions. The mooring dynamics model MoorDyn has been extended to model springs with nonlinear tension-strain curves from a user-inputted look-up table. This MoorDyn modeling advancement is verified against OrcaFlex simulation results. Using MoorDyn's updated capabilities, a spring-equipped catenary mooring system is designed for the 15-MW floating system, along with a baseline catenary mooring system that does not use polymer springs. The floating wind turbine simulator OpenFAST is used to simulate the mooring systems in design-driving load cases to show the effect of polymer springs on key dynamic behaviours. The results show that the spring-equipped design reduces peak tensions by up to 60%, whereas the turbine offsets stay within a maximum of 7.2 m, which is still a reasonable offset limit for cable considerations. The reduction in peak tensions results in a significant decrease in damage equivalent loads - on the order of 50% for upwind lines in fully loaded conditions. These results show that polymer springs can effectively reduce peak tensions and fatigue loads in mooring systems at shallow water depths.

floating offshore wind↗

Revisiting the Role of Mobile Ion Size for the Activation Barrier of Charge Transport in Single Ion Conducting Polymers

The development of polymer electrolytes for energy storage and conversion technologies requires a fundamental understanding of the material parameters controlling the energy barriers for ion transport. In glassy polymers, these activation barriers are usually extracted by using Arrhenius procedures. However, our recent studies of single ion conducting polymers reveal that this traditional Arrhenius description provides anomalously small prefactors, an issue that is widely disregarded in the literature. Here, to address it, an alternative approach was introduced for extracting the effective activation barrier E by imposing a physically valid limit (∼10 –13 s) for the ion hopping attempt time. Two consequences of this recent approach are that in polymer electrolytes (i) E is significantly (∼30–40%) lower than the barrier estimated using traditional Arrhenius fits and (ii) E displays significant temperature dependence even in the glassy state. Under these circumstances, we are revisiting the role of ion size, glass transition temperature T g , and dielectric and elastic constants of the polymer matrix on the effective activation barriers for ion transport as extracted using the recently proposed approach and highlight the differences from the picture that previously emerged based on simplistic apparent Arrhenius analysis. To this end, we investigate cation transport in three families of single ion conducting trifluoromethane sulfonimide-based polyanions with varied T g . Our results indicate that E decreases with mobile cation size and is highly sensitive to changes in the dielectric permittivity of the matrix, even for large cations. These insights call for revisions of many earlier results based on apparent Arrhenius fits as the proposed approach can provide more accurate guidance for the design of polymer electrolytes with enhanced ionic conductivity.

energy barrier↗

Concerted Electron-Ion Transport by Polyacrylonitrile Elucidated with Reactive Deep Learning Potentials

Charge transport in polymers, such as polyacrylonitrile (PAN), is crucial for electronics and energy storage. For instance, PAN can transport cations e.g., Li + , by facilitating dynamic cation-nitrile coordination in batteries. However, little is known regarding the underlying role of complex reactive polymer configurations. Herein, we develop a deep-learning potential, trained on ab initio energies and forces of nonequilibrium reactive PAN configurations, to unravel the kinetics of PAN cyclization initiated by a nucleophile (OH – dissociated from LiOH) attacking the terminal nitrile carbon. We find, based on the reaction free-energetics, rates, and charge analysis, that the nucleophile attack producing the first ring is the rate-limiting step, which subsequently triggers Li + -coupled electron transfer along the PAN backbone, causing ∼10 4 times faster sequential ring-formation of the remaining nitriles. PAN’s extended configurations, where dipolar and H-bonding interactions are minimal, enable such rapid kinetics. By validating our computational findings with IR and NMR experiments, we establish a pathway for designing reactive polymers with enhanced charge transport for energy applications.

Chahal-Crockett, Rajni [Oak Ridge National Laborat↗

Tracking Spatiotemporal Electric Potential in Batteries Using High-Resolution Operando X‑ray Transmission Imaging

The formation of significant concentration gradients across electrolytes in batteries affects the rate at which electrochemical reactions occur. In this work, we use high-resolution operando X-ray transmission imaging to capture spatiotemporal salt concentration profiles c(x,t) in a symmetric cell comprising a polymer electrolyte sandwiched between two lithium–indium alloy electrodes during a constant-current experiment followed by open-circuit relaxation. The decay of open-circuit potential is related to the concentration dependence of the potential across concentration cells, U. We show how operando c(x,t) data can be used to calculate the spatiotemporal electric potential “inside” the polarized electrolyte. We track the spatial- and time-dependent cell potential during the constant-current step and distinguish its two contributions: a concentration overpotential governed by U. and an ohmic contribution governed by ionic conductivity. Over most of the time window, the concentration overpotential dominates. At steady state, it is a factor of 7 larger than the ohmic contribution. Such findings indicate that efforts to design new polymer electrolytes should focus on minimizing concentration gradients.

Electrical conductivity↗