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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Real-time correlation of crystallization and segmental order in conjugated polymers

Modulating the segmental order in the morphology of conjugated polymers is widely recognized as a crucial factor for achieving optimal electronic properties and mechanical deformability. However, it is worth noting that the segmental order is typically associated with the crystallization process, which can result in rigid and brittle long-range ordered crystalline domains. To precisely control the morphology, a comprehensive understanding of how highly anisotropic conjugated polymers form segmentally ordered structures with ongoing crystallization is essential, yet currently elusive. To fill this knowledge gap, we developed a novel approach with a combination of stage-type fast scanning calorimetry and micro-Raman spectroscopy to capture the series of specimens with a continuum in the polymer percent crystallinity and detect the segmental order in real-time. Through the investigation of conjugated polymers with different backbones and side-chain structures, we observed a generally existing phenomenon that the degree of segmental order saturates before the maximum crystallinity is achieved. This disparity allows the conjugated polymers to achieve good charge carrier mobility while retaining good segmental dynamic mobility through the tailored treatment. Moreover, the crystallization temperature to obtain optimal segmental order can be predicted based on T g and T m of conjugated polymers. In conclusion, this in-depth characterization study provides fundamental insights into the evolution of segmental order during crystallization, which can aid in designing and controlling the optoelectronic and mechanical properties of conjugated polymers.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Structure of native four-repeat satellite III sequence with non-canonical base interactions

Abstract Tandem-repetitive DNA (where two or more DNA bases are repeated numerous times) can adopt non-canonical secondary structures. Many of these structures are implicated in important biological processes. Human Satellite III (HSat3) is enriched for tandem repeats of the sequence ATGGA and is located in pericentromeric heterochromatin in many human chromosomes. Here, we investigate the secondary structure of the four-repeat HSat3 sequence 5′-ATGGA ATGGA ATGGA ATGGA-3′ using X-ray crystallography, NMR, and biophysical methods. Circular dichroism spectroscopy, thermal stability, native PAGE, and analytical ultracentrifugation indicate that this sequence folds into a monomolecular hairpin with non-canonical base pairing and B-DNA characteristics at concentrations below 0.9 mM. NMR studies at 0.05–0.5 mM indicate that the hairpin is likely folded-over into a compact structure with high dynamics. Crystallographic studies at 2.5 mM reveal an antiparallel self-complementary duplex with the same base pairing as in the hairpin, extended into an infinite polymer. The non-canonical base pairing includes a G–G intercalation sandwiched by sheared A–G base pairs, leading to a cross-strand four guanine stack, so called guanine zipper. The guanine zippers are spaced throughout the structure by A–T/T–A base pairs. Our findings lend further insight into recurring structural motifs associated with the HSat3 and their potential biological functions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Structure–Thermodynamic Relationship of a Polysaccharide Gel (Alginate) as a Function of Water Content and Counterion Type (Na vs Ca)

Biofilms are the predominant mode of microbial life on Earth, and so a deep understanding of microbial communities-and their impacts on environmental processes-requires a firm understanding of biofilm properties. Because of the importance of biofilms to their microbial inhabitants, microbes have evolved different ways of engineering and reconfiguring the matrix of extracellular polymeric substances (EPS) that constitute the main non-living component of biofilms. This ability makes it difficult to distinguish between the biotic and abiotic origins of biofilm properties. An important route toward establishing this distinction has been the study of simplified models of the EPS matrix. This study builds on such efforts by using atomistic simulations to predict the nanoscale (≤10 nm scale) structure of a model EPS matrix and the sensitivity of this structure to interpolymer interactions and water content. To accomplish this, we use replica exchange molecular dynamics (REMD) simulations to generate all-atom configurations of ten 3.4 kDa alginate polymers at a range of water contents and Ca–Na ratios. Simulated systems are solvated with explicitly modeled water molecules, which allows us to capture the discrete structure of the hydrating water and to examine the thermodynamic stability of water in the gels as they are progressively dehydrated. Our primary findings are that (i) the structure of the hydrogels is highly sensitive to the identity of the charge-compensating cations, (ii) the thermodynamics of water within the gels (specific enthalpy and free energy) are, surprisingly, only weakly sensitive to cation identity, and (iii) predictions of the differential enthalpy and free energy of hydration include a short-ranged enthalpic term that promotes hydration and a longer-ranged (presumably entropic) term that promotes dehydration, where short and long ranges refer to distances shorter or longer than ~0.6 nm between alginate strands.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Build Orientation Dependent Microstructure in Polymer Laser Sintering: Relationship to Part Performance and Evolution with Aging

Laser sintering (LS) is widely used to produce functional polymeric parts; however, the resulting parts are often limited by their porous structure, and performance of the part may be strongly anisotropic. Relating the structural features of parts to build process conditions or powder feedstock has been explored previously. In contrast, little is known regarding how the unique internal structures of LS parts evolve and relate to their performance later in their life cycle, for example, after use in a real-world operating environment. In this study, a tightly controlled LS build process and measurement campaign by standard X-ray computed tomography (XCT), supported by high-resolution synchrotron XCT, was used to benchmark the internal microstructure (e.g. porosity) as a function of four different build orientations in printed polyamide-12 (PA-12) parts. The initial performance of the parts after printing was characterized by tensile testing and dynamic mechanical analysis (DMA). Arrays of PA-12 parts in different build orientations were exposed to steam (under pressure) and air across multiple temperature and time points for the purposes of accelerated aging through oxidative and hydrolytic breakdown. Exposing parts to steam dramatically altered the internal microstructure and functional properties such as the glass transition temperature, tensile properties, and damping behavior. Notably, post-aging XCT revealed large microstructural changes after only 40 h of steam treatment relative to the as-printed specimens. Furthermore, pore reorganization and changes in crystallinity occurred regardless of whether the steam temperature was aggressive enough to induce a significant loss in mechanical properties. The build orientation dependence on the aging rate was minimal with the relative trend in performance persisting across most metrics among the different orientations even after aging.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Preparation and characterization of aminated co-solvent enhanced lignocellulosic fractionation lignin as a renewable building block for the synthesis of non-isocyanate polyurethanes

Lignin is a major bioresource from 2nd generation biorefinery process streams and from pulp and paper production that is still severely underutilized nowadays. Its natural polymeric and aromatic structures make it suitable as a potential building block for biopolymer production. Due to the growing environmental and health concerns over conventional polyurethane (PU) manufacturing processes that utilize toxic isocyanates, there is a great interest to develop a non-isocyanate PU (NIPU) route. Herein, we demonstrate a novel strategy that uses highly pure lignin isolated from co-solvent enhanced lignocellulosic fractionation (CELF) pretreatment of poplar wood to produce biobased NIPUs. In this strategy, hardwood poplar is firstly fractionated via a CELF pretreatment to produce a clean lignin stream that is rich in phenolics. The CELF lignin was then aminated by a Mannich reaction, and the aminated CELF lignin was finally reacted with bicyclic carbonates to yield an advanced NIPU. In this work, the structure, mechanical, and thermal properties of these novel NIPUs were elucidated by FTIR, NMR, tensile test, dynamic mechanical analysis (DMA), and thermogravimetric analysis (TGA). The mechanical properties of these lignin based NIPUs could be tuned from highly rigid to elastic polymers by simply modifying the lignin constituents of the polymer. The thermal stabilities of NIPUs were improved because of the addition of aminated lignin, and NIPU containing 55 and 23 wt% lignin showed the highest tensile strength (~1.2 MPa) and elongation at break (~140%), respectively. The results obtained in this study demonstrate that the reaction of cyclic carbonate with aminated lignin represents an interesting pathway for the synthesizing of lignin based NIPU with a relative high lignin content.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Unlocking hidden information in sparse small-angle neutron scattering measurements

Hypothesis Small-Angle Neutron Scattering (SANS) is a powerful technique for studying soft matter systems such as colloids, polymers, and lyotropic phases, providing nanoscale structural insights. However, its effectiveness is limited by low neutron flux, leading to long acquisition times and noisy data. Here, we hypothesize that Bayesian statistical inference using Gaussian Process Regression (GPR) can reconstruct high-fidelity scattering data from sparse measurements by leveraging intensity smoothness and continuity. Experiments and Simulations The method was benchmarked computationally and validated through SANS experiments on various soft matter systems, including wormlike micelles, colloidal suspensions, polymeric structures, and lyotropic phases. GPR-based inference was applied to both experimental and synthetic data to evaluate its effectiveness in noise reduction and intensity reconstruction. Findings GPR significantly enhances SANS data quality and therefore reducing measurement times by up to two orders of magnitude. This cost-effective approach maximizes experimental efficiency, enabling high-throughput studies and real-time monitoring of dynamic systems. It is particularly beneficial for weakly scattering and time-sensitive studies. Beyond SANS, this framework applies to other low-SNR techniques, including laboratory-based small-angle X-ray scattering and various dynamical scattering methods. Furthermore, it offers transformative potential for compact neutron sources, enhancing their viability for structural analysis in resource-limited settings.

Small angle neutron scattering↗
DOE OSTI2022

Production of β-ketoadipic acid from glucose in Pseudomonas putida KT2440 for use in performance-advantaged nylons

Biomass-derived chemicals can offer unique chemical functionality relative to petroleum-derived building blocks. To this end, here we report that β-ketoadipic acid (βKA), a C6 diacid with a β-ketone group, can be used as a performance-advantaged replacement for adipic acid in a nylon-6,6 analog. Building on our previous efforts to produce shikimate-derived products from carbohydrates, Pseudomonas putida KT2440 is engineered to produce βKA from glucose, achieving a 26 g/L titer. Following purification, βKA imparts an increase of 69 degrees C above the nylon-6,6 glass transition temperature and 20% reduced water permeability, equivalent to nylon-6,10. Molecular simulations predict that the enhanced thermal properties result from rigidity introduced by the β-ketone. Process analysis predicts that βKA can be produced for US$1.94/kg from sugars, requiring 63% less energy and emitting 43% less greenhouse gases than fossil-based adipic acid. Overall, this study illustrates the potential for βKA to serve as a useful building block for bio-based polymers.

09 BIOMASS FUELS↗
DOE OSTI2025

The Triple Catalytic Action of Tertiary Nitrogen Catalysts in Recyclable Epoxy-Anhydride Thermosets

The thermosetting polymer matrix in fiber reinforced composites is an important component for energy related applications, such as the lightweighting of vehicles or their use in wind and waterpower turbine blades, due to their ability to provide superior adhesion, stiffness, and applicability to a wide range of manufacturing processes. Despite these benefits, today's thermosets are widely considered to be unrecyclable; thus, there is a large interest in redesigning these materials to be inherently recyclable so that energy intensive production of fibers and monomers can be circumvented, bolstering composite manufacture supply chains. Polyester covalent adaptable networks (PECANs) are one such promising alternative to the incumbent, nonrecyclable epoxy-amine thermosets. PECANs can be formed from the ring-opening co-polymerization (ROCOP) of epoxy-anhydride monomer mixtures and subsequent curing at mild temperatures to exhibit similar performance to conventional epoxies while also possessing unique dynamic chemistries along the ester-hydroxyl backbone that are capable of transesterification and thus reprocessability. While significant advancements have been made in formulating these materials for improved mechanical properties or optimizing solvolysis and reprocessing strategies, less attention has been placed on the impact of the residing amine catalyst used to generate the polyester network. In this work, we evaluated the triple-catalytic efficacy of 12 tertiary amines that act as a curing (bulk ROCOP), a transesterification (internal bond exchange), and a deconstruction (methanolysis) catalyst for PECAN thermosets. Specifically, we first distinguish between chain-growth and step-growth polymerization mechanisms for epoxy-amine and epoxy-anhydride mechanisms. We also utilized density functional theory (DFT) to estimate the basicity (pKb) of each catalyst. Of the tested catalysts, the ROCOP of the studied PECAN network can be completed between 95 and 247 min (at 80 degrees C), with variable gelation phenomena. Additionally, the stress relaxation (transesterification metric) efficiency of the tested PECAN networks with alternative embedded catalysts ranged from 95% to 15% reduction in stress after 5 h at 200 degrees C, and the depolymerization efficacy ranged from 2.5% to 9.8% deconstruction after 36 h at 130 degrees C. Overall, the nitrogen-based moieties were demonstrated to influence polymerization kinetics, catalyze the dynamic transesterification exchange mechanism, and aid in the solvolysis of the thermosets at end-of-life.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Predicting the viscoplastic response of a crystallizing fluoropolymer using transient network theory

We employ a molecular theory of dynamic polymer networks to describe the viscoplastic response of rubbery FK-800, a thermoplastic copolymer of chlorotrifluoroethylene and vinylidene fluoride, over a broad range of thermal histories. The kinetics of crystallization at different annealing temperatures was modeled using a modified Avrami equation, whose parameters were found to evolve through simple relationships over the full temperature range of the rubbery state. By fitting experimental compression data, we discovered predictable trends for the physical parameters in our mechanical model over its full range of crystallinities (up to ≈20%) and provided insights based on molecular-level physics to justify them. Using this, an end-to-end model was developed to predict the yielding and post-yield behavior of rubbery FK-800 for arbitrary thermal histories. The model successfully predicted the highly nonlinear evolution of characteristic mechanical signatures (stiffness, yield point, post-yield drop) throughout the crystallization process. A statistical analysis of variance test was employed to determine that the measured variations in the mechanical behavior of rubbery FK-800 are primarily dictated by its fractional crystallinity, regardless of its exact thermal history.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Discovery of Innovative Polymers for Next-Generation Gas-Separation Membranes using Interpretable Machine Learning

Polymer membranes perform innumerable separations with far-reaching environmental implications. Despite decades of research on membrane technologies, 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 separation performance. Specifically, multitask ML models are trained on available experimental data to link polymer chemistry to gas permeabilities of He, H2, O2, N2, CO2, and CH4. Here, we interpret the ML models and extract chemical heuristics for membrane design, through Shapley Additive exPlanations (SHAP) analysis. We then screen over nine million hypothetical polymers through our models and identify thousands of candidates that lie well above current performance upper bounds. Notably, we discover hundreds of never-before-seen ultrapermeable polymer membranes with O2 and CO2 permeability greater than 104 and 105 Barrer, respectively. These hypothetical polymers are capable of overcoming undesirable trade-off relationship between permeability and selectivity, thus significantly expanding the currently limited library of polymer membranes for highly efficient gas separations. High-fidelity molecular dynamics simulations confirm the ML-predicted gas permeabilities of the promising candidates, which suggests that many can be translated to reality.

Yang, Jason↗
DOE OSTI2021

Activated penetrant dynamics in glass forming liquids: size effects, decoupling, slaving, collective elasticity and correlation with matrix compressibility

In this work, we employ the microscopic self-consistent cooperative hopping theory of penetrant activated dynamics in glass forming viscous liquids and colloidal suspensions to address new questions over a wide range of high matrix packing fractions and penetrant-to-matrix particle size ratios. The focus is on the mean activated relaxation time of smaller tracers in a hard sphere fluid of larger particle matrices. This quantity also determines the penetrant diffusion constant and connects directly with the structural relaxation time probed in an incoherent dynamic structure factor measurement. The timescale of the non-activated fast dissipative process is also studied and is predicted to follow power laws with the contact value of the penetrant–matrix pair correlation function and the penetrant–matrix size ratio. For long time penetrant relaxation, in the relatively lower packing fraction metastable regime the local cage barriers are dominant and matrix collective elasticity effects unimportant. As packing fraction and/or penetrant size grows, much higher barriers emerge and the collective elasticity associated with the correlated matrix dynamic displacement that facilitates penetrant hopping becomes important. This results in a non-monotonic variation with packing fraction of the degree of decoupling between the matrix and penetrant alpha relaxation times. The conditions required for penetrant hopping to become slaved to the matrix alpha process are determined, which depend mainly on the penetrant to matrix particle size ratio. By analyzing the absolute and relative importance of the cage and elastic barriers we establish a mechanistic understanding of the origin of the predicted exponential growth of the penetrant hopping time with size ratio predicted at very high packing fractions. A dynamics-thermodynamics power law connection between the penetrant activation barrier and the matrix dimensionless compressibility is established as a prediction of theory, with different scaling exponents depending on whether matrix collective elasticity effects are important. Quantitative comparisons with simulations of the penetrant relaxation time, diffusion constant, and transient localization length of tracers in dense colloidal suspensions and cold viscous liquids reveal good agreements. Multiple new predictions are made that are testable via future experiments and simulations. Extension of the theoretical approach to more complex systems of high experimental interest (nonspherical molecules, semiflexible polymers, crosslinked networks) interacting via variable hard or soft repulsions and/or short range attractions is possible, including under external deformation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Kinetic and Mechanistic Understanding of Boron-Containing Catalysts for the Production of Light Olefins through Selective Oxidation

In recent years, an abundance of natural gas obtained from shale deposits has created opportunities for the US chemical industry to establish new and more efficient processes for the production of chemical intermediates and polymers. For example, the replacement of petroleum-derived naphtha as a to shale-derived ethane as feedstocks has made the production of ethylene/polyethylene less costly. However, this shift in feedstock has led to lower production of propylene from steam crackers, and new “on-purpose” light olefin production technologies have been implemented to bridge the gap between propylene supply and demand. The most important of these processes is direct propane dehydrogenation (PDH), but catalyst deactivation and high temperatures lead to high capital and operating costs. Oxidative dehydrogenation of propane (ODHP) is an efficient alternative to PDH, but high selectivity to CO2 from previous metal oxide catalyst prevents implementation. Hexagonal boron nitride (hBN) and other boron-containing materials have been recently developed as highly selective catalysts for both ODHP and oxidative cracking, surpassing previous systems. Much is still unknown in regard to the mechanism and the dynamic surface changes that occur under reaction conditions. This research project aims to combine in situ/operando spectroscopic investigation and kinetic studies to elucidate the interplay between the proposed gas-phase mechanism and the surface structures on the working catalyst. These insights will be leveraged to create a framework for optimizing reaction conditions and material synthesis for the next generation of boron-containing selective oxidation catalysts.

02 PETROLEUM↗
DOE OSTI2021

Laser-driven flyer plate impact: Computational studies guided by experiments

We present a computational approach using a multimaterial, arbitrary Lagrangian–Eulerian code termed ALE3D to model the nanosecond/micrometer dynamics of the launch of 0.5–4.5 km/s laser-driven metal flyer plates and the impact with stationary targets of Pyrex and fused silica glasses, and Lexan and Plexiglas polymers, producing pressures in the target in the range of 5–20 GPa. The simulations are compared to experimental results where the flyer velocity profile and the velocity profile imparted to the target material were measured with high-speed velocimetry. The experimental flyer launch by a high-intensity pulsed laser is modeled by depositing heat into a thin vaporizable layer under the flyer plate. This model produces a flyer plate that has not been exposed to the laser pulse, allowing us to compare the properties of the real flyer to a simulated ideal flyer. The simulations of target impact are generally in good agreement with the experiment except at the highest impact velocities where the shock release process in the experiment is slower than that in the simulation. The cause of this disagreement is attributed to an inadequate description of the shock viscosity during the nanosecond unloading process.

Stekovic, Svjetlana (ORCID:0000000163878070)↗
DOE OSTI2022

The TPR domain of PgaA is a multifunctional scaffold that binds PNAG and modulates PgaB-dependent polymer processing

The synthesis of exopolysaccharides as biofilm matrix components by pathogens is a crucial factor for chronic infections and antibiotic resistance. Many periplasmic proteins involved in polymer processing and secretion in Gram-negative synthase dependent exopolysaccharide biosynthetic systems have been individually characterized. The operons responsible for the production of PNAG, alginate, cellulose and the Pel polysaccharide each contain a gene that encodes an outer membrane associated tetratricopeptide repeat (TPR) domain containing protein. While the TPR domain has been shown to bind other periplasmic proteins, the functional consequences of these interactions for the polymer remain poorly understood. Herein, we show that the C-terminal TPR region of PgaA interacts with the de-N-acetylase domain of PgaB, and increases its deacetylase activity. Additionally, we found that when the two proteins form a complex, the glycoside hydrolase activity of PgaB is also increased. To better understand structure-function relationships we determined the crystal structure of a stable TPR module, which has a conserved groove formed by three repeat motifs. Tryptophan quenching, mass spectrometry analysis and molecular dynamics simulation studies suggest that the crystallized TPR module can bind PNAG/dPNAG via its electronegative groove on the concave surface, and potentially guide the polymer through the periplasm towards the porin for export. Our results suggest a scaffolding role for the TPR domain that combines PNAG/dPNAG translocation with the modulation of its chemical structure by PgaB.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

The high explosives & affected targets (HEAT) dataset

Artificial Intelligence (AI) surrogate models offer a computationally efficient alternative to full-physics simulations, yet no existing datasets are publicly available for training, testing, and validation of machine learning models of the dynamics of high-explosive driven shocks through multiple materials. Shock propagation through materials is a computationally challenging problem because simulations must include material-specific equations of state (EOS) along with descriptions of other physical processes such as plastic deformation, phase change, damage processes, fluid instabilities, and multi-material interactions. Shocks are typically initiated by high-velocity impacts or explosive loading. The latter case necessitates the addition of models of reactive materials to represent high-explosive (HE) detonation. Here, to address the lack of an expansive dataset for multi-material shock propagation in the AI/ML community, we present the High-Explosives and Affected Targets (HEAT) Dataset. HEAT is a physics-rich collection of two-dimensional, cylindrically symmetric, simulations generated using an Eulerian, multi-material, shock-propagation code developed at Los Alamos National Laboratory. The dataset includes two partitions: (1) the expanding shock-cylinder (CYL) simulations, Figs. 1, and (2) the Perturbed Layered Interface (PLI) simulations, Fig. 2. Entries in both partitions consist of time series of arrays of thermodynamic fields (pressure, density, and temperature), kinematic fields (position and velocity), and additional fields that depend on thermodynamic and/or kinematic fields (e.g., material stress). Materials in the CYL partition include solids (aluminium, copper, depleted uranium, stainless steel, tantalum, and a generic polymer), a liquid (water), gases (air, nitrogen), and a generic detonating material (high explosive, HE). The PLI partition spans a highly varying geometry but consists of fixed materials across entries: Copper, aluminium, stainless steel, generic polymer, and generic HE. HEAT captures critical phenomena such as momentum transfer, shock propagation, plastic deformation, and thermal effects, making HEAT a valuable benchmark for development of AI/ML emulation of multi-material shock propagation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

An FEM-Based Peridynamic Model for Failure Analysis of Unidirectional Fiber-Reinforced Laminates

To predict the mixed damage modes of unidirectional fiber-reinforced polymer (FRP) laminates under dynamic loading, an FEM-based peridynamic model is introduced in this paper. Based on its geometric structure and material composition, a long fiber lamina is considered a transversely isotropic medium as a result of homogenization at the meso-scale. The laminated structure is modeled by stacking surface mesh layers with arbitrary fiber angles along the thickness direction. The peridynamic bonds between Gauss points connect the separated elements. These bonds are classified as inner-layer bonds and inter-layer bonds. To represent the anisotropy of a laminate, the micro-elastic modulus of the inner-layer and inter-layer bonds is calculated from the anisotropic engineering material constants separately. To capture complex failure behaviors of laminate structures, an empirical damage model is proposed for the tension/ compression breakage of peridynamic bonds. This damage model can control the in-plane and delamination failure process. Finally, benchmark tests are conducted to validate the elastic response of laminates under dynamic loading. In terms of damage analysis, the proposed model can capture the complex damage modes and resistive force of laminate structures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Controlling Ion Uptake in Carboxylated Mixed Conductors

Organic mixed ionic‐electronic conductors (OMIECs) have garnered significant attention due to their capacity to transport both ions and electrons, making them ideal for applications in energy storage, neuromorphics, and bioelectronics. However, charge compensation mechanisms during the polymer redox process remain poorly understood, and are often oversimplified as single‐ion injection with little attention to counterion effects. To advance understanding and design strategies toward next‐generation OMIEC systems, a series of p‐channel carboxylated mixed conductors is investigated. Varying side‐chain functionality, distinctive swelling character is uncovered during electrochemical doping/dedoping with model chao‐/kosmotropic electrolytes. Carboxylic acid functionalized polymers demonstrate strong deswelling and mass reduction during doping, indicating cation expulsion, while ethoxycarbonyl counterparts exhibit prominent mass increase, pointing to an anion‐driven doping mechanism. By employing operando grazing incidence X‐ray fluorescence (GIXRF), it is revealed that the carboxyl functionalized polymer engages in robust cation interaction, whereas ester functionalization shifts the mechanism towards no cation involvement. It is demonstrated that cations are pivotal in mitigating swelling by counterbalancing anions, enabling efficient anion uptake without compromising performance. These findings underscore the transformative influence of functionality‐driven factors and side‐chain chemistry in governing ion dynamics and conduction, providing new frameworks for designing OMIECs with enhanced performance and reduced swelling.

carboxylated polythiophenes↗
DOE OSTI2022

Discovery of Graphene-Water Membrane Structure: Toward High-Quality Graphene Process

It is widely accepted that solid-state membranes are indispensable media for the graphene process, particularly transfer procedures. But these membranes inevitably bring contaminations and residues to the transferred graphene and consequently compromise the material quality. This study reports a newly observed free-standing graphene-water membrane structure, which replaces the conventional solid-state supporting media with liquid film to sustain the graphene integrity and continuity. Experimental observation, theoretical model, and molecular dynamics simulations consistently indicate that the high surface tension of pure water and its large contact angle with graphene are essential factors for forming such a membrane structure. More interestingly, water surface tension ensures the flatness of graphene layers and renders high transfer quality on many types of target substrates. This report enriches the understanding of the interactions on reduced dimensional material while rendering an alternative approach for scalable layered material processing with ensured quality for advanced manufacturing.

36 MATERIALS SCIENCE↗