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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 73 records · Page 4

NEXAFS Spectroscopy of P3HT and PBTTT at the Sulfur K-Edge

The sulfur K-edge near-edge X-ray absorption fine-structure (NEXAFS) spectra of the common conjugated polymers P3HT and PBTTT are studied from both experimental and theoretical perspectives. Experimental angle-resolved spectra are measured to characterize both the dominant peaks and the dichroism of the polymers. First-principles calculations using the density functional theory-based many-body X-ray absorption spectroscopy (MBXAS) method are performed for the two polymers as well as for the thiophene and thienothiophene units that make up the conjugated backbones of these polymers. Through this combined approach, we are able to confidently assign the observed peaks to specific molecular orbitals and identify the orientation of their transition dipole moments (TDMs) with respect to the coordinate frame of the polymer backbone. Here, in particular, we are able to establish the character and orthogonal nature of the three main low-energy peaks at: (i) 2473.5 eV, 1s → (S–C)­π* with TDM along the π-stacking direction; (ii) 2474.1 eV, 1s → (S–C)­σ* with TDM along the backbone; and (iii) 2475.4 eV, 1s → (S–C)­σ* with TDM perpendicular to the first two. By performing both gas-phase and solid-state simulations, and with reference to the NEXAFS spectra of thiophene and thienothiophene building blocks, the influences of polymerization and molecular packing are also explored.

Chantler, Paul Alexander [Monash University, Clayt↗

Soil Sensors in Agriculture: From Unsustainable to Biodegradable

Commercially available bi-metallic temperature sensors have long exploited differential thermal expansions between materials to produce an actuation-induced readout from a bi-metal helix. When dispersed in agricultural land, electronic components are used to transmit information at the cost of an increased environmental footprint. This paper briefly recaps the proposed sensor, which employs a biodegradable bi-material helix composed of a polymer and metal. Proposed polymer sheetings of cellulose acetate and polylactic acid are characterized via TGA, DMA, and DSC to evaluate plasticizer content, shrinkage, and an appropriate sensor work-use range. Finally, the deflection of non-biodegradable bi-polymer strips is quantified for various combinations to determine if bi-polymer deflection is possible.

47 OTHER INSTRUMENTATION↗

Systematic study of radioluminescence and light propagation effects in scintillating nanoguide materials

Nanoguide optical waveguides are thermally processed materials based on polymers that have different refractive indices. Scintillating versions of these materials have been under development since 2019 and feature PMMA as the low refractive index constituent and Organic Glass Scintillator-polymer blends as the high index component. Characterization efforts to date have focused on the functional characteristics of nanoguide pertaining to its envisioned use in high-resolution transmission radiography applications.

36 MATERIALS SCIENCE↗

Hydrogen Production, Grid Integration, and Scaling for the Future

The project will explore near and long-term visions towards the commercialization of grid integrated electrolysis systems to inform deployment across the planning, procurement, and operation stages of hydrogen production on the grid. It will leverage NREL's state-of-the-art 1.25 MW polymer electrolyte membrane (PEM) electrolyzer system to characterize system performance in relevant scenarios, also creating a digital twin for emulation in the Advanced Research on Integrated Energy Systems (ARIES) virtual environment and performing hardware-in-the-loop (HIL) testing of pilot scale, decentralized, and centralized hydrogen systems.

electrolysis systems↗

Confusion-Driven Machine Learning of Structural Phases of a Flexible, Magnetic Stockmayer Polymer

We use a semisupervised, neural-network-based machine learning technique, the confusion method, to investigate structural transitions in magnetic polymers, which we model as chains of magnetic colloidal nanoparticles characterized by dipole–dipole and Lennard-Jones interactions. As input for the neural network, we use the particle positions and magnetic dipole moments of equilibrium polymer configurations, which we generate via replica-exchange Wang–Landau simulations. We demonstrate that by measuring the classification accuracy of neural networks, we can effectively identify transition points between multiple structural phases without any prior knowledge of their existence or location. We corroborate our findings by investigating relevant conventional order parameters. Our study furthermore examines previously unexplored low-temperature regions of the phase diagram, where we find new structural transitions between highly ordered helicoidal polymer configurations.

36 MATERIALS SCIENCE↗

Insights into Preceramic Polymer-Based Additive Manufacturing Inks via Rheological and Scattering Studies of Preceramic Polymer-Grafted Nanoparticles Suspended in Polycarbosilane

Preceramic polymers (PCPs) offer advantages in producing ceramics due to their processability and ability to tailor the final chemistry of the produced material. However, challenges such as volumetric shrinkage and mass loss during pyrolysis often result in polymer-derived ceramics containing pores and cracks. PCP-grafted ceramic nanoparticles (PCPGNPs) have been proposed and studied as a route to mitigate the shrinkage issues associated with neat PCPs. Prior studies on PCPGNPs have principally focused on the synthesis and characterization of neat materials. Dispersing PCPGNPs in commercial preceramic polymer is another attractive, but underexplored, route to control the rheological and char yield properties of PCP systems. In this work, a systematic rheological study of commercial PCP (SMP-877) and PCPGNP (silica with poly(1,1-dimethylpropylsilane) corona) mixtures was executed to develop design rules for the processing of such systems. A rheological study demonstrated the effect of increasing particle concentration on network formation with percolation occurring between 50 and 60 wt %. Samples above the percolation threshold exhibited higher viscosities and rapid shear thinning thus demonstrating their direct-write printability. X-ray photon correlation spectroscopy (XPCS) corroborated the rheology and showed two diffusive modes when the material was above percolation. Mixtures of PCPGNPs and SMP-877 had synergistically higher char yields upon thermal treatment and pyrolysis. XPCS and rheological measurements during thermal treatment identified thermal jamming of the polymer grafts as a key factor in improving the char yield. In conclusion, with the insights gained here, we expect these mixed systems to provide attractive feedstocks for polymer-derived ceramics, with proof-of-principal application as feedstocks for direct ink write (DIW) additive manufacturing.

36 MATERIALS SCIENCE↗

Development of Mixed Matrix Membranes by Using NH 2 ‐Functionalized UiO‐66 and [APTMS][AC] Ionic Liquid for the Separation of CO 2

The ever‐escalating CO 2 concentration in the atmosphere calls for accelerated development and deployment of carbon capture processes to reduce emissions. Mixed matrix membranes (MMMs), which are fabricated by incorporating the beneficial properties of highly selective inorganic fillers into a polymer matrix, have exhibited significant progress and the ability to enhance the performance of a membrane for gas separation. In this research, an amine‐based ionic liquid (IL) [APTMS][AC] was prepared, which has greater CO 2 affinity and greater solubility due to its amine moiety. The metal–organic framework (MOF) UiO‐66 with a multidimensional crystalline structure was used as a filler due to its appropriate porosity and tunable properties, and it was functionalized with NH 2 . MOFs were further modified with an IL to prepare UiO‐66@IL and UiO‐66‐NH 2 @IL, and MMMs incorporating each MOF were fabricated with the polymer Pebax‐1657. All the prepared membranes and MOFs were characterized to predict their separation efficiency. Several characterization techniques, namely, FTIR spectroscopy, XRD, and SEM, were used to successfully synthesize UiO‐66@IL and UiO‐66‐NH 2 @IL composites and confirmed proper dispersion and excellent polymer‒filler compatibility at filler loadings ranging from 0 to 30 wt.%. The separation performances were investigated, and the results showed that the incorporation of RTIL with the highly crystalline structure and large surface area of UiO‐66 enhanced the separation efficiency of the membrane. The permeability of CO 2 for all fabricated membranes continuously increased with increasing filler concentration, wherein the permeability was comparatively high for the UiO‐66‐NH 2 MMMs. The CO 2 /CH 4 selectivity improved by 35%, 54%, and 60%, respectively, for UiO‐66@IL, UiO‐66‐NH 2 , and UiO‐66‐NH 2 @IL MMMs compared to simple UiO‐66 for CO 2 /CH 4 and by 28%, 36%, and 63%, respectively, for CO 2 /N 2 , with an increase in filler loading in the MMMs.

Khalid, Hafiza Mamoona (ORCID:0009000135165855)↗

Identification and characterization of substrate- and product-selective nylon hydrolases

Enzymes can rapidly and selectively hydrolyze diverse natural and anthropogenic polymers, but few have been shown to hydrolyze synthetic polyamides. Here, in this work, we synthesized and characterized a panel of 95 enzymes from the N-terminal nucleophile hydrolase superfamily with 30%–50% pairwise amino acid identity. We found that nearly 40% of the enzymes had substantial nylon hydrolase activity, but there was no relationship between phylogeny and activity, nor any evidence of prior evolutionary selection for nylon hydrolysis. Several newly identified hydrolases showed substrate selectivity, generating up to 20-fold higher product titers with nylon-6,6 versus nylon-6. However, the yield was still less than 1%, necessitating further optimization before potential applications. Finally, we determined the crystal structure and oligomerization state of a nylon-6,6-selective hydrolase to elucidate structural factors that could affect activity and selectivity. These new enzymes provide insights into nylon hydrolase evolution and opportunities for analysis and engineering of improved hydrolases.

nylon↗

Effect of Specimen Thickness on Fracture Toughness and Plane Stress to Plane Strain Transition in Medium-Density Polyethylene

This study investigates the effect of specimen thickness on fracture toughness and the transition from plane stress to plane strain conditions in Medium-Density Polyethylene (MDPE) using Single Edge Notched Bend (SENB) specimens. Three thickness groups (7.5 mm, 9.0 mm, and 12.1 mm) were tested following ASTM D5045 protocol. Conditional stress intensity factors (KQ) increased from 2.2 MPavm to 2.8 MPavm with increasing thickness, demonstrating significant size dependency. Confocal microscopy revealed a 34% reduction in maximum crack tip opening displacement (CTOD) from 0.478 mm to 0.314 mm as thickness increased, with plastic zone lateral extent decreasing by 32%. This quantitative evidence validates Irwin's theoretical prediction of plastic zone size transition from plane stress r_y˜ (1/2p) (K_I/s_y )^2 to plane strain conditions r_y˜ (1/6p) (K_I/s_y )^2.Scanning electron microscopy confirmed progressive suppression of shear lips and evolution from ductile tearing with extensive polymer chain drawing in thin specimens to localized crazing in thick specimens. Despite all specimens satisfying the ASTM D5045 criterion (B = 2.5(KQ/s_y )^2 ) ,residual shear lips persisted even in the thickest specimens, demonstrating that nominal size requirements alone are insufficient for achieving complete plane strain conditions in highly ductile polymers. The findings emphasize the necessity of integrated analytical and morphological assessment for valid fracture toughness characterization, with critical implications for life assessment and integrity prediction in thick-section polymer components such as natural gas distribution pipelines.

Medium-Density Polyethylene↗

A characterization of recombinant Arabidopsis FRIABLE1 (FRB1) reveals robust rhamnogalacturonan-I rhamnosyltransferase activity and critical catalytic residues

Plant cell walls are glycan-rich extracellular matrices that fundamentally impact essential cellular processes, such as growth, adhesion, and cell shape acquisition. Understanding plant cell wall glycans requires the identification and characterization of the biosynthetic enzymes that produce these polymers. Most successful in vitro protein expression studies of plant cell wall glycosyltransferases have relied on insect, fungal/yeast, or human cell expression systems, whereas prokaryotic expression systems have been generally unsuccessful. Here, we show that Arabidopsis FRIABLE1 (FRB1)/rhamnogalacturonan-I rhamnosyltransferase 8 (RRT8) can be produced in Escherichia coli RosettaGami2 cells as N-terminal maltose-binding protein fusion proteins containing C-terminal 6X-His-tags. We also report the catalytic constants of FRB1/RRT8 with apparent K M and K cat values of 226 μM and 33 min -1 for UDP-Rhamnose and 117 μM and 28.7 min -1 for rhamnogalacturonan-I (RG-I), respectively. We examine the catalytic activities of mutated FRB1/RRT8 proteins based on an AlphaFold 3-generated FRB1/RRT8 protein structural model with a virtually docked UDP-Rha donor. Enzymatic characterization of the mutated and wildtype FRB1/RRT8 protein confirmed that mutation of predicted catalytic site amino acid residues resulted in a 20-fold reduction in RRT activity. FRB1 also robustly polymerizes RG-I in combination with RG-I galacturonosyltransferase 1. These results show how a robust E. coli expression system combined with artificial intelligence tools can be used to increase understanding of plant cell wall glycosyltransferase structure and function.

glycosyltransferase↗

On the effect of strain rate during the cyclic compressive loading of liquid crystal elastomers and their 3D printed lattices

Nematic liquid crystal elastomers (LCEs) are a unique class of network polymers with the potential for enhanced mechanical energy absorption and dissipation capacity over conventional network polymers because they exhibit both conventional viscoelastic behavior and soft-elastic behavior (nematic director changes under shear loading). This additional inelastic mechanism makes them appealing as candidate damping materials in a variety of applications from vibration to impact. The lattice structures made from the LCEs provide further mechanical energy absorption and dissipation capacity associated with packing out the porosity under compressive loading. Understanding the extent of mechanical energy absorption, which is the work per unit mass (or volume) absorbed during loading, versus dissipation, which is the work per unit mass (or volume) dissipated during a loading cycle, requires measurement of both loading and unloading response. Here, in this study, a bench-top linear actuator was employed to characterize the loading-unloading compressive response of polydomain and monodomain LCE polymers and polydomain LCE lattice structures with two different porosities (nominally, 62% and 85%) at both low and intermediate strain rates at room temperature. As a reference material, a bisphenol-A (BPA) polymer with a similar glass transition temperature (9 °C) as the nematic LCE (4 °C) was also characterized at the same conditions for comparing to the LCE polymers. Based on the loading-unloading stress-strain curves, the energy absorption and dissipation for each material at different strain rates (0.001, 0.1, 1, 10 and 90 s -1 ) were calculated with considerations of maximum stress and material mass/density. The strain-rate effect on the mechanical response and energy absorption and dissipation behaviors was determined. The energy dissipation ratio was also calculated from the resultant loading and unloading stress-strain curves. All five materials showed significant but different strain rate effects on energy dissipation ratio. The solid LCE and BPA materials showed greater energy dissipation capabilities at both low (0.001 s -1 ) and high (above 1 s -1 ) strain rates, but not at the strain rates in between. The polydomain LCE lattice structure showed superior energy dissipation performance compared with the solid polymers especially at high strain rates.

36 MATERIALS SCIENCE↗

Dynamic Strength and Equation of State of Epon 828 and Diethanolamine (DEA) Polymer Epoxy Under Shock Loading

Polymers are increasingly utilized in engineering applications that can experience high loading rates, necessitating increased understanding of their response under such conditions. The tamped Richtmyer-Meshkov Instability (RMI) method was used to characterize the equation of state and dynamic strength of the polymer Epon 828 cured with Diethanolamine (DEA). Plate impact experiments that drove a uniaxial shock compression wave across a sinusoidally corrugated metal-polymer interface were performed to generate shock stresses from 4-12 GPa and strain rates of approximately 1/s in the polymer. X-ray phase contrast imaging recorded the shock motion in the polymer and subsequent interface evolution. Analysis of this data yielded the polymer equation of state and, in conjunction with numerical modeling, the dynamic strength. The equation of state was validated against one-dimensional plate impact experiments from existing literature. The dynamic strength was compared to prior data for Epon 828 and related polymers at lower strain rates and found to exhibit significant strain rate and pressure-hardening effects. The strength of the Epon 828 polymer at 10 6 1/s was found to be approximately 1.5 GPa, suggesting that it is comparable to the strength of high strength metals at these dynamic conditions.

Equation of state↗

Structural and physicochemical insights into pH-responsive poly(DEAEMA- co -HEMA)-grafted mesoporous silica nanoparticles

Mesoporous silica nanoparticles (SiO 2 ) grafted with responsive polymer shells are versatile hybrid systems. Understanding their three-dimensional organization in the hydrated state remains a significant challenge. Here, in this study, SiO 2 nanoparticles were functionalized with a poly(DEAEMA-co-HEMA) shell via a “grafting-from” polymerization strategy in aqueous media. Successful surface modification was confirmed by FTIR, thermogravimetric analysis, transmission electron microscopy, X-ray photoelectron spectroscopy, N 2 sorption, and ζ-potential, yielding grafting contents of 22% (p1 DEAEMA-co-HEMA ) and 49% (p2 DEAEMA-co-HEMA ). Small-angle neutron scattering (SANS) with solvent contrast variation was employed to elucidate the solution-state core–shell architecture of p1 and p2 hybrids at pH 2, where the grafted polymer shell is protonated and highly hydrated. Near contrast matching of the silica core, theoretically estimated at 58% D 2 O, suppressed the scattering intensity, enhancing sensitivity to the polymer shell. Constrained core–shell ellipsoid modeling across solvent contrasts revealed a systematic increase in shell thickness, overall particle dimensions, and shell anisotropy with increasing grafting content. In solution, the hydrated polymer shells were markedly more extended and structurally anisotropic than suggested by dry-state techniques structural characterization, highlighting the importance of solution-state structural analysis for accurately describing grafted polymer architectures.

Core-shell biomaterials↗

Data-Driven Tailoring Optimization of Thermoset Polymers Using Ultrasonics and Machine Learning

Thermoset polymers are highly demanded for their structural robustness, thermal stability, and chemical resistance. Tailoring the properties of these polymers for high-performance applications is often preferred to designing brand-new polymers. However, the traditional destructive techniques used to characterize their properties as a function of manufacturing parameters are expensive and time-consuming. A novel non-destructive, data-driven method leveraging ultrasonics and machine learning techniques to tailor the properties of thermosets as a function of the manufacturing parameters is demonstrated. Thermoset epoxy samples with varying curing temperatures (15–40 °C) and curing agent amounts (±40%) were manufactured and tested. Their curing kinetics were monitored by determining the sound speed in the material in real time, while the longitudinal modulus of the samples was determined post-cure. Machine learning models were developed using a k-nearest neighbors algorithm. These models were implemented to predict the curing and final elastic properties using the manufacturing parameters, i.e., stoichiometry and curing temperature, and vice versa. Understanding and modeling how these parameters affect the cure kinetics and final properties will allow for efficient and reliable optimization of thermoset tailoring and manufacturing.

36 MATERIALS SCIENCE↗

Influence of strain-rate on the response of elastomeric architected materials

Architected materials have shown substantial promise in impact mitigation and protective applications, and there has accordingly been great interest in better characterizing their response at elevated strain rates due to impact. There remains ambiguity regarding the contribution of inertial and material responses to strain rate sensitivity, and, in particular, when these effects begin to gain dominance in the impact response of an architected material. The response of soft polymer architected materials as a function of strain rate, in particular, has been little investigated. We characterize the experimental impact response of four soft polymer architected lattice geometries across varying strain rates in the intermediate strain rate regime (∼10 3 s −1 ) using split-Hopkinson pressure bar loading and high speed video characterization of the resulting deformation fields. In conclusion, our results highlight the interplay of influence between constituent material, lattice geometry, length scale, and strain rate in determining the onset of significant inertia effects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗