Effect of Methyl Groups on Formation of Ordered or Layered Graphitic Materials from Aromatic Molecules.

Developing functionally complex carbon materials from small aromatic molecules requires an understanding of how the chemistry and structure of its constituent molecules evolve and crosslink, to achieve a tailorable set of functional properties. Here, molecular dynamics (MD) simulations are used to isolate the effect of methyl groups on condensation reactions during the oxidative process and evaluate the impact on elastic modulus by considering three monodisperse pyrene-based systems with increasing methyl group fraction. A parameter to quantify the reaction progression is designed by computing the number of new covalent bonds formed. Utilizing the previously developed MD framework, it is found that increasing methylation leads to an almost doubling of bond formation, a larger fraction of the new bonds oriented in the direction of tensile stress, and a higher basal plane alignment of the precursor molecules along the direction of tensile stress, resulting in enhanced tensile modulus. Additionally, via experiments, it is demonstrated that precursors with a higher fraction of methyl groups result in a higher alignment of molecules. Moreover, increased methylation results in the lower spread of single molecule alignment which may lead to smaller variations in tensile modulus and more consistent properties in carbon materials derived from methyl-rich precursors.

Effects of Salt on Phase Behavior and Rheological Properties of Alginate-Chitosan Polyelectrolyte Complexes.

Oppositely charged polyelectrolytes often form polyelectrolyte complexes (PECs) due to the association through electrostatic interactions. Obtaining PECs using natural, biocompatible polyelectrolytes is of interest in the food, pharmaceutical, and biomedical industries. In this work, PECs were prepared from two biopolymers, positively charged chitosan and negatively charged alginate. We investigate the changes in the structure and properties of PECs by adding sodium chloride (salt doping) to the system. The shear modulus of PECs can be tuned from ∼10 to 104 Pa by changing the salt concentration. The addition of salt led to a decrease in the water content of the complex phase with increasing shear modulus. However, at a very high salt concentration, the shear modulus of the complex phase decreased but did not lead to the liquid coacervate formation, typical of synthetic polyelectrolytes. This difference in phase behavior has likely been attributed to the hydrophobicity of chitosan and long semiflexible alginate and chitosan chains that restrict the conformational changes. Large amplitude oscillatory shear experiments captured nonlinear responses of PECs. The compositions of the PECs, determined as a function of salt concentration, signify the preferential partitioning of salt into the complex phase. Small-angle X-ray scattering of the salt-doped PECs indicates that the Kuhn length and radius of the alginate-chitosan associated structure qualitatively agree with the captured phase behavior and rheological data. This study provides insights into the structure-property as a function of salt concentration of natural polymer-based PECs necessary for developing functional materials from natural polyelectrolytes.

Transferring a Molecular Foundation Model for Polymer Property Predictions.

Transformer-based large language models have remarkable potential to accelerate design optimization for applications such as drug development and material discovery. Self-supervised pretraining of transformer models requires large-scale data sets, which are often sparsely populated in topical areas such as polymer science. State-of-the-art approaches for polymers conduct data augmentation to generate additional samples but unavoidably incur extra computational costs. In contrast, large-scale open-source data sets are available for small molecules and provide a potential solution to data scarcity through transfer learning. In this work, we show that using transformers pretrained on small molecules and fine-tuned on polymer properties achieves comparable accuracy to those trained on augmented polymer data sets for a series of benchmark prediction tasks.

An Ionomeric Renewable Thermoplastic from Lignin-Reinforced Rubber.

An ionomeric, leathery thermoplastic with high mechanical strength is prepared by a new thermal processing method from a soft, melt-processable rubber. Compositions made by incorporation of equal-mass lignin, a renewable oligomeric feedstock, in an acrylonitrile-butadiene rubber often yield weak rubbers with large lignin domains (1-2 µm). The addition of zinc chloride (ZnCl2 ) in such a composition based on sinapyl alcohol-rich lignin during a solvent-free synthesis induces a strong interfacial crosslinking between lignin and rubber phases. This compositional modification results in finely interspersed lignin domains (<100 nm) that essentially reinforce the rubbery matrix with a 10-22 °C rise in the glassy-to-rubbery transition temperature. The ion-modified polymer blends also show improved materials properties, like a 100% increase in ultimate tensile strength and an order of magnitude rise in Young's modulus. Coarse-grained molecular dynamics (MD) simulations verify the morphology and dynamics of the ionomeric material. The computed result also confirms that the ionomers have glassy characteristics.

Improving mechanical properties of carbon nanotube fibers through simultaneous solid-state cycloaddition and crosslinking.

Individual carbon nanotubes (CNTs) exhibit exceptional mechanical properties. However, difficulties remain in fully realizing these properties in CNT macro-assemblies, because the weak inter-tube forces result in the CNTs sliding past one another. Herein, a simple solid-state reaction is presented that enhances the mechanical properties of carbon nanotube fibers (CNTFs) through simultaneous covalent functionalization and crosslinking. This is the first chemical crosslinking proposed without the involvement of a catalyst or byproducts. The specific tensile strength of CNTFs obtained from the treatment employing a benzocyclobutene-based polymer is improved by 40%. Such improvement can be attributed to a reduced number of voids, impregnation of the polymer, and the formation of covalent crosslinks. This methodology is confirmed using both multiwalled nanotube (MWNT) powders and CNTFs. Thermogravimetric analysis, differential scanning calorimetry, x-ray photoelectron spectroscopy, and transmission electron microscopy of the treated MWNT powders confirm the covalent functionalization and formation of inter-tube crosslinks. This simple one-step reaction can be applied to industrial-scale production of high-strength CNTFs.

Neutron vibrational spectroscopic studies of novel tire-derived carbon materials.

Sulfonated tire-derived carbons have been demonstrated to be high value-added carbon products of tire recycling in several energy storage system applications including lithium, sodium, potassium ion batteries and supercapacitors. In this communication, we compared different temperature pyrolyzed sulfonated tire-derived carbons with commercial graphite and unmodified/non-functionalized tire-derived carbon by studying the surface chemistry and properties, vibrational spectroscopy of the molecular structure, chemical bonding such as C-H bonding, and intermolecular interactions of the carbon materials. The nitrogen adsorption-desorption studies revealed the tailored micro and meso pore size distribution of the carbon during the sulfonation process. XPS and neutron vibrational spectra showed that the sulfonation of the initial raw tire powders could remove the aliphatic hydrogen containing groups ([double bond splayed left]CH2 and -CH3 groups) and reduce the number of heteroatoms that connect to carbon. The absence of these functional groups could effectively improve the first cycle efficiency of the material in rechargeable batteries. Meanwhile, the introduced -SO3H functional group helped in producing terminal H at the edge of the sp2 bonded graphite-like layers. This study reveals the influence of the sulfonation process on the recovered hard carbon from used tires and provides a pathway to develop and improve advanced energy storage materials.

Amplifying Nanoparticle Reinforcement through Low Volume Topologically Controlled Chemical Coupling.

We present a streamlined method to covalently bond hydroxylated carbon nanotubes (CNOH) within a polyphenol matrix, all achieved through a direct, solvent-free process. Employing an extremely small concentration of CNOH (0.01% w/w) along with topologically contrasting linkers led to a maximum of 5-fold increase in modulus and a 25% enhancement in tensile strength compared to the unaltered matrix, an order of magnitude greater reinforcement (w/w) compared to state-of-the-art melt-processed nanocomposites. Through dynamic mechanical analysis, low field solid-state nuclear magnetic resonance spectroscopy, and molecular dynamics simulations, we uncovered the profound influence of linker's conformational degrees of freedom on the segmental dynamics and therefore the material's properties.

Investigating Permselectivity in PVDF Mixed Matrix Membranes Using Experimental Optimization, Machine Learning Segmentation, and Statistical Forecasting.

This research examines the correlation between interfacial characteristics and membrane distillation (MD) performance of copper oxide (Cu) nanoparticle-decorated electrospun carbon nanofibers (CNFs) polyvinylidene fluoride (PVDF) mixed matrix membranes. The membranes were fabricated by a bottom-up phase inversion method to incorporate a range of concentrations of CNF and Cu + CNF particles in the polymer matrix to tune the porosity, crystallinity, and wettability of the membranes. The resultant membranes were tested for their application in desalination by comparing the water vapor transport and salt rejection rates in the presence of Cu and CNF. Our results demonstrated a 64% increase in water vapor flux and a salt rejection rate of over 99.8% with just 1 wt % loading of Cu + CNF in the PVDF matrix. This was attributed to enhanced chemical heterogeneity, porosity, hydrophobicity, and crystallinity that was confirmed by electron microscopy, tensiometry, and scattering techniques. A machine learning segmentation model was trained on electron microscopy images to obtain the spatial distribution of pores in the membrane. An Autoregressive Integrated Moving Average with Explanatory Variable (ARIMAX) statistical time series model was trained on MD experimental data obtained for various membranes to forecast the membrane performance over an extended duration.

Deep-Learning Interatomic Potential Connects Molecular Structural Ordering to the Macroscale Properties of Polyacrylonitrile.

Polyacrylonitrile (PAN) is an important commercial polymer, bearing atactic stereochemistry resulting from nonselective radical polymerization. As such, an accurate, fundamental understanding of governing interactions among PAN molecular units is indispensable for advancing the design principles of final products at reduced processability costs. While ab initio molecular dynamics (AIMD) simulations can provide the necessary accuracy for treating key interactions in polar polymers, such as dipole-dipole interactions and hydrogen bonding, and analyzing their influence on the molecular orientation, their implementation is limited to small molecules only. Herein, we show that the neural network interatomic potentials (NNIPs) that are trained on the small-scale AIMD data (acquired for oligomers) can be efficiently employed to examine the structures and properties at large scales (polymers). NNIP provides critical insight into intra- and interchain hydrogen-bonding and dipolar correlations and accurately predicts the amorphous bulk PAN structure validated by modeling the experimental X-ray structure factor. Furthermore, the NNIP-predicted PAN properties, such as density and elastic modulus, are in good agreement with their experimental values. Overall, the trend in the elastic modulus is found to correlate strongly with the PAN structural orientations encoded in the Hermans orientation factor. This study enables the ability to predict the structure-property relations for PAN and analogues with sustainable ab initio accuracy across scales.

Tailoring Chemical Absorption-Precipitation to Lower the Regeneration Energy of a CO2 Capture Solvent.

Solvent-based CO2 capture consumes significant amounts of energy for solvent regeneration. To improve energy efficiency, this study investigates CO2 fixation in a solid form through solvation, followed by ionic self-assembly-aided precipitation. Based on the hypothesis that CO3 2- ions may bind with monovalent metal ions, we introduced Na+ into an aqueous hexane-1,6-diamine solution where CO2 forms carbamate and bicarbonate. Then, Na+ ions in the solvent act as a seed for ionic self-assembly with diamine carbamate to form an intermediate ionic complex. The recurring chemical reactions lead to the formation of an ionic solid from a mixture of organic carbamate/carbonate and inorganic sodium bicarbonate (NaHCO3 ), which can be easily removed from the aqueous solvent through sedimentation or centrifugation and heated to release the captured CO2 . Mild-temperature heating of the solids at 80-150 °C causes decomposition of the solid CO2 -diamine-Na molecular aggregates and discharge of CO2 . This sorbent regeneration process requires 6.5-8.6 GJ/t CO2 . It was also found that the organic carbamate/carbonate solid, without NaHCO3 , contains a significant amount of CO2 , up to 6.2 mmol CO2 /g-sorbent, requiring as low as 2.9-5.8 GJ/t CO2 . Molecular dynamic simulations support the hypothesis of using Na+ to form relatively less stable, yet sufficiently solid, complexes for the least energy-intensive recovery of diamine solvents compared to bivalent carbonate-forming ions.

Enhancing Composite Toughness Through Hierarchical Interphase Formation.

High strength and ductility are highly desired in fiber-reinforced composites, yet achieving both simultaneously remains elusive. A hierarchical architecture is developed utilizing high aspect ratio chemically transformable thermoplastic nanofibers that form covalent bonding with the matrix to toughen the fiber-matrix interphase. The nanoscale fibers are electrospun on the micrometer-scale reinforcing carbon fiber, creating a physically intertwined, randomly oriented scaffold. Unlike conventional covalent bonding of matrix molecules with reinforcing fibers, here, the nanofiber scaffold is utilized - interacting non-covalently with core fiber but bridging covalently with polymer matrix - to create a high volume fraction of immobilized matrix or interphase around core reinforcing elements. This mechanism enables efficient fiber-matrix stress transfer and enhances composite toughness. Molecular dynamics simulation reveals enhancement of the fiber-matrix adhesion facilitated by nanofiber-aided hierarchical bonding with the matrix. The elastic modulus contours of interphase regions obtained from atomic force microscopy clearly indicate the formation of stiffer interphase. These nanoengineered composites exhibit a ≈60% and ≈100% improved in-plane shear strength and toughness, respectively. This approach opens a new avenue for manufacturing toughened high-performance composites.

Three-dimensional printing of wood.

Natural wood has served as a foundational material for buildings, furniture, and architectural structures for millennia, typically shaped through subtractive manufacturing techniques. However, this process often generates substantial wood waste, leading to material inefficiency and increased production costs. A potential opportunity arises if complex wood structures can be created through additive processes. Here, we demonstrate an additive-free, water-based ink made of lignin and cellulose, the primary building blocks of natural wood, that can be used to three-dimensional (3D) print architecturally designed wood structures via direct ink writing. The resulting printed structures, after heat treatment, closely resemble the visual, textural, olfactory, and macro-anisotropic properties, including mechanical properties, of natural wood. Our results pave the way for 3D-printed wooden construction with a sustainable pathway to upcycle/recycle natural wood.

Pyrolysis pathways of sulfonated polyethylene, an alternative carbon fiber precursor.

Polyethylene is an emerging precursor material for the production of carbon fibers. Its sulfonated derivative yields ordered carbon when pyrolyzed under inert atmosphere. Here, we investigate its pyrolysis pathways by selecting n-heptane-4-sulfonic acid (H4S) as a model compound. Density functional theory and transition state theory were used to determine the rate constants of pyrolysis for H4S from 300 to 1000 K. Multiple reaction channels from two different mechanisms were explored: (1) internal five-centered elimination (Ei5) and (2) radical chain reaction. The pyrolysis of H4S was simulated with kinetic Monte Carlo (kMC) to obtain thermogravimetric (TGA) plots that compared favorably to experiment. We observed that at temperatures <550 K, the radical mechanism was dominant and yielded the trans-alkene, whereas cis-alkene was formed at higher temperatures from the internal elimination. The maximum rates of % mass loss became independent of initial È®H radical concentration at 440-480 K. Experimentally, the maximum % mass loss occurred from 440 to 460 K (heating rate dependent). Activation energies derived from the kMC-simulated TGAs of H4S (26-29 kcal/mol) agreed with experiment for sulfonated polyethylene (~31 kcal/mol). The simulations revealed that in this region, decomposition of radical HOSÈ®2 became competitive to α-H abstraction by HOSÈ®2, making È®H the carrying radical for the reaction chain. The maximum rate of % mass loss for internal elimination was observed at temperatures >600 K. Low-scale carbonization utilizes temperatures <620 K; thus, internal elimination will not be competitive. E(i)5 elimination has been studied for sulfoxides and sulfones, but this represents the first study of internal elimination in sulfonic acids.

Carbon nanofibers based carbon-carbon composite fibers.

Textile grade polyacrylonitrile (PAN) was used as a precursor material for carbon fiber preparation. E-beam irradiated polyacrylonitrile grafted carbon nanofibers were dispersed in polyacrylonitrile solution (dissolved in dimethyl formamide). Carbon nanofibers (CNF) infused polyacrylonitrile solution was wet spun on a lab-scale wet-spinning setup to form 50 to 70 µm diameter fibers with 3.2 wt.% CNF-PAN, 6.4 wt.% CNF-PAN, and neat PAN. Precursor fibers were characterized for thermal, mechanical and morphological properties using various techniques. Drawing the precursor fibers further enhanced polymer chain orientation and coalesced the voids, enhancing tensile strength and modulus by more than 150% compared to those of the undrawn fibers. Precursor composite fibers on carbonization showed enhanced strength, compared to that of pristine PAN fibers, by four times and stiffness by 14 times. The carbon-carbon composite fibers were further characterized with SEM/FIB, XRD and tensile strength. The property improvements were dependent on the uniform distribution of carbon nanofibers, and surface modification of carbon nanofibers further enabled their dispersion in the composite fibers. Furthermore, 3.2 wt.% CNFs in PAN fibers showed maximum improvement in properties compared to 6.4 wt.% CNF in PAN fibers, indicating that the property enhancements go through a maximum and then drop off due to challenge in getting uniform distribution of nanofibers.

Atoms to fibers: Identifying novel processing methods in the synthesis of pitch-based carbon fibers.

Understanding and optimizing the key mechanisms used in the synthesis of pitch-based carbon fibers (CFs) are challenging, because unlike polyacrylonitrile-based CFs, the feedstock for pitch-based CFs is chemically heterogeneous, resulting in complex fabrication leading to inconsistency in the final properties. In this work, we use molecular dynamics simulations to explore the processing and chemical phase space through a framework of CF models to identify their effects on elastic performance. The results are in excellent agreement with experiments. We find that density, followed by alignment, and functionality of the molecular constituents dictate the CF mechanical properties more strongly than their size and shape. Last, we propose a previously unexplored fabrication route for high-modulus CFs. Unlike graphitization, this results in increased sp3 fraction, achieved via generating high-density CFs. In addition, the high sp3 fraction leads to the fabrication of CFs with isometric compressive and tensile moduli, enabling their potential applications for compressive loading.

Understanding the Solution Dynamics and Binding of a PVDF Binder with Silicon, Graphite, and NMC Materials and the Influence on Cycling Performance.

The impact of the binding, solution structure, and solution dynamics of poly(vinylidene fluoride) (PVDF) with silicon on its performance as compared to traditional graphite and Li1.05Ni0.33Mn0.33Co0.33O2 (NMC) electrode materials was explored. Through refractive index (RI) measurements, the concentration of the binder adsorbed on the surface of electrode materials during electrode processing was determined to be less than half of the potentially available material resulting in excessive free binder in solution. Using ultrasmall-angle neutron scattering (USANS) and small-angle neutron scattering (SANS), it was found that PVDF forms a conformal coating over the entirety of the silicon particle. This is in direct contrast to graphite-PVDF and NMC-PVDF slurries, where PVDF only covers part of the graphite surface, and the PVDF chains make a network-like graphite-PVDF structure. Conversely, a thick layer of PVDF covers NMC particles, but the coating is porous, allowing for ion and electronic transport. The homogeneous coating of silicon breaks up percolation pathways, resulting in poor cycling performance of silicon materials as widely reported. These results indicate that the Si-PVDF interactions could be modified from a binder to a dispersant.

Fractionation of Lignin for Selective Shape Memory Effects at Elevated Temperatures.

We report a facile approach to control the shape memory effects and thermomechanical characteristics of a lignin-based multiphase polymer. Solvent fractionation of a syringylpropane-rich technical organosolv lignin resulted in selective lignin structures having excellent thermal stability coupled with high stiffness and melt-flow resistance. The fractionated lignins were reacted with rubber in melt-phase to form partially networked elastomer enabling selective programmability of the material shape either at 70 °C, a temperature that is high enough for rubbery matrix materials, or at an extremely high temperature, 150 °C. Utilizing appropriate functionalities in fractionated lignins, tunable shape fixity with high strain and stress recovery, particularly high-stress tolerance were maintained. Detailed studies of lignin structures and chemistries were correlated to molecular rigidity, morphology, and stress relaxation, as well as shape memory effects of the materials. The fractionation of lignin enabled enrichment of specific lignin properties for efficient shape memory effects that broaden the materials' application window. Electron microscopy, melt-rheology, dynamic mechanical analysis and ultra-small angle neutron scattering were conducted to establish morphology of acrylonitrile butadiene rubber (NBR)-lignin elastomers from solvent fractionated lignins.

Effect of the Ionic Liquid Structure on the Melt Processability of Polyacrylonitrile Fibers.

The production of high-strength carbon fibers is an energy-intensive process, where a significant cost involves the wet or dry-spinning of polyacrylonitrile (PAN) fiber precursors. Melt-spinning PAN fibers would allow for significant reduction in the production cost and production hazards. Ionic liquids (ILs) are an attractive fiber-processing medium because of their negligible vapor pressure and low toxicity. In addition, they are carbon-forming precursors; upon carbonization, residual ILs can enhance the carbon yield, although primarily useful for plasticized melt-spinning of PAN precursor fibers. In this research, we investigated the influence of the molecular structure of ILs and the control of plasticizing interactions with PAN during melt-spinning. The structural, thermal, and mechanical properties of the melt-spun PAN fibers were obtained by a combination of various characterization methods, such as differential scanning calorimetry, thermogravimetric analysis, Fourier transform infrared spectroscopy, scanning electron microscopy, X-ray diffraction, and mechanical testing. These results demonstrated that the IL structure and counteranions influence the PAN fiber formation. More specifically, ILs containing bromide counteranions produced PAN precursor fibers with increased mechanical properties compared to ILs containing chloride anions. Our research can provide a foundation to understand the influence of ILs on melt-spinning of PAN fibers and provides us the guidelines for a higher cost-/energy-efficient production of PAN-based carbon fibers.

Data of thermally active lignin-linkages and shape memory of lignin-rubber composites.

This data article presents the utilization of thermally dynamic covalent bonds of lignin linkages such as ß-O-4', Cα-O of ß-5' phenylcoumaran, and ß-ß resinol to modify the thermomechanical properties of high loading lignin-nitrile rubber composites. These thermally active lignin linkages can be triggered at 180 °C to generate free-radicals for crosslinking reactions. The evolution of crosslinking density was measured in-situ using dynamic mechanical analysis and rheological characterization. The shape programmability and shape recovery of these composites were determined by both ex-situ and in-situ methods. The thermally modified composites exhibited excellent shape memory properties. The data in this article are related to our recent research article entitled "Responsive lignin for shape memory applications" (Nguyen et al., 2018).

A tough and sustainable fiber-forming material from lignin and waste poly(ethylene terephthalate).

In this report we describe repurposing of recycled polyesters as a matrix for lignin-a biorefinery coproduct that is used as a solid fuel and needs to find higher value-to make sustainable high-performance thermoplastic materials. Brittle lignin oligomers, isolated from plant biomass, require a low-melting host polymer matrix to form a rigid and tough renewable material. We demonstrate controlled lignin dispersion and interfacial interactions in softened recycled polyethylene terephthalate (PET) using a simple solvent-free, melt-blending technique. To avoid lignin degradation and devolatilization during melt processing, it was thermally treated. Tall oil fatty acid was used to enable PET processability at low enough temperature to accommodate lignin without charring. Chemical analysis reveals reduction of aliphatic hydroxyl content from 2 mmol g-1 to 1.63 mmol g-1 and an increase of total phenolic hydroxyl moieties from 5.86 to 6.64 mmol g-1 and cleavage of ß-O-4 ether linkages due to thermal treatment. Structural transformation of lignin macromolecules during heat treatment was further confirmed by an increase in molar mass and improved thermal stability. Interfacial interactions between lignin and PET were assessed from mechanical properties and thermal analyses. Thermal treatment not only helps to improve the stability of lignin but also slightly reduces the size of the dispersed lignin domains via favored interfacial interactions with the PET matrix. These methods improve mechanical properties of the material. Further, incorporation of lignin in the plasticized PET matrix increases the ductility in the blended products. The method we discuss here utilizes industrial wastes and co-products, and it does not require solvent or toxic chemicals during the reactive extrusion process that yields complete conversion to products.