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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Diethylenetriamine-functionalized graphene oxide: Insights into ion adsorption and applications in rare earth element separation

The growing demand for critical minerals and materials requires atom- and energy-efficient, selective separations to overcome the challenges posed by the similar chemical and physical properties of the rare earth elements (REEs) and their low concentrations in unconventional domestic feedstocks. Here, in this study, we developed diethylenetriamine-functionalized graphene oxide (DETA-GO) as a membrane material for REE adsorption and separation. Synthesis conditions were optimized to maximize nitrogen incorporation while also preserving GO dispersibility for facile membrane fabrication. We investigated the mechanism of amine functionalization, the nitrogen-bonding configurations, the organization of the interlayer transport channels, and the resulting effects on ion and water transport for REE separations. Neat-GO and DETA-GO multilayer laminate membranes were fabricated by vacuum filtration onto polymer supports. To investigate the effects of amine functionalization, the membranes were characterized using scanning electron microscopy, Raman, Fourier transform infrared, and X-ray photoelectron spectroscopy, as well as grazing-incidence X-ray diffraction measurements. Ion permeation experiments with representative lanthanum (La 3+ ) and ytterbium (Yb 3+ ) solutions revealed enhanced ion adsorption and water transport through DETA-GO membranes compared to neat-GO. The strong affinity of the membranes for multivalent REEs was also validated with conductivity and inductively coupled plasma mass spectrometry measurements. Atomistic insight into the role of amine functionalization in modulating nanochannel architecture and long-term stability, optimizing adsorption sites, and regulating REE and water transport was obtained using classical molecular dynamics simulations. Collectively, our joint experimental and theoretical study demonstrates the potential of DETA-GO membranes for selective REE separations, offering insights into ion-binding mechanisms, water-transport properties, and nanochannel optimization for the recovery of critical materials from aqueous feedstocks.

Adsorbent↗
DOE OSTI2020

Determining the hydration energetics on carbon-supported Ru catalysts: An adsorption calorimetry and density functional theory study

Fundamental knowledge on the energetics at the interface between a water layer and a metal catalyst is essential so as to understand the roles that water can play in the synthesis, activation and regeneration of noble metal-based catalysts. Here, we report the direct measurement of the enthalpy of water adsorption (Δh ads ) on activated carbon (C) and activated C-supported Ru nanoparticles, which are promising catalyst as applied to the hydrogenation/hydrodeoxygenation (HDO) of oxygenates (phenolics, aldehydes, etc.). Specifically, the near-zero coverage enthalpy of water adsorption on a C-supported Ru catalyst is -75.3 ± 0.4 kJ/(mol water), suggesting favorable water–metal binding. This is much more exothermic than that on C, which has an enthalpy of adsorption of -50.3 ± 1.3 kJ/(mol water). Despite the favorable initial binding, the magnitudes of enthalpies of water condensation on C and Ru-C indicate that overall, their surfaces are both hydrophobic. Moreover, the experimentally-measured near-zero coverage water adsorption enthalpy at the Ru sites is in very good agreement with our density functional theory based calculations. At low coverages, we obtain a water binding energy of -61.7 kJ/(mol water), which increases to -78.1 kJ/(mol water) at saturation. Complementary results are also obtained from a thermal analysis, which employed a thermogravimetric analysis–differential scanning calorimetry–mass spectrometry (TG-DSC-MS), a spectroscopic investigation using ex situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and a morphological evaluation with transmission electron microscopy (TEM). We point out that in carbon-supported metal catalysts, such as Ru-C, a strong hydration at near-zero coverage and relative weak water-surface interactions occurs upon saturation. Such heterogeneity is essential and crucial for catalytic hydrogenation/HDO reactions that involve balanced interactions among the water-rich reactant mixture and nonpolar organic products.

09 BIOMASS FUELS↗
DOE OSTI2022

Effect of surface acidity modulation on Pt/Al 2 O 3 single atom catalyst for carbon monoxide oxidation and methanol decomposition

With ideal metal utilization efficiency and homogeneous active sites, single atom catalysts (SACs) have attracted extensive attention in heterogeneous catalysis field. The performance of SACs is highly dependent on the local coordination environment of metal single atoms. However, few works reported the effect of surface acidity modification on the performance of SACs such as Pt SACs which have been widely studied nowadays. In this work, a Pt/Al 2 O 3 SAC has been successfully prepared using a bayerite Al(OH) 3 as support through simple IWI method for Pt loading. Through post-modification of Pt/Al 2 O 3 with acidic WO 3 and basic MgO, the surface acidity of Pt/Al 2 O 3 was tuned. Here, activity of CO oxidation and methanol decomposition on the modified catalysts has been evaluated. It was found that the catalytic performance was highly related to the surface acidity of Pt SACs. Basic MgO modified Pt/Al 2 O 3 performed better in CO oxidation under the reaction condition with H 2 O. Acidic WO 3 modified Pt/Al 2 O 3 showed superior activity in methanol decomposition. Detailed characterization and in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) study suggested that the positive H 2 O effect on CO oxidation was due to the mitigated formation of bicarbonate species on Pt/Al 2 O 3 and WO 3 /Pt/Al 2 O 3 catalysts and the promoted desorption of carbonate species from MgO/Pt/Al 2 O 3 . The superior methanol decomposition performance on WO 3 /Pt/Al 2 O 3 was owing to its abundant oxygen vacancies and high resistance to carbonate accumulation. This study highlights the importance of surface acidity modulation of Pt SACs in heterogeneous catalysis and suggests that fine-tuning the surface acidity can be an effective strategy in new SACs development.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Activity and selectivity for CO 2 methanation of clusters and nanoplates of ruthenium dispersed on ceria: In-situ studies with XAFS and DRIFTS

The performance of Ru/CeO 2 catalysts under CO 2 hydrogenation conditions was studied using in situ X-ray absorption fine structure (XAFS) and diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) to understand the structural evolution and chemical nature of each component under reaction conditions. The catalysts were prepared using a reverse microemulsion method that maximized the dispersion of RuOx particles on ceria. A RuO x → Ru transformation was observed upon exposure of the RuO x /CeO 2 systems to H 2 at 250 °C. For a sample with 5% molar Ru, two-dimensional clusters (2-4 atoms) of Ru formed on top of the ceria support. An increase in the loading of ruthenium to 20% molar led to the formation of nanoplates of the metal 2-3 atomic layers thick. Both Ru structures were highly dispersed on ceria. They were oxidized after exposure to CO 2 at 250 °C. However, under CO 2 /H 2 mixture, they remained in a metallic state as two-dimensional clusters and nanoplates. In situ DRIFTS studies, the 5% and 20% Ru/CeO 2 catalysts showed distinct reaction intermediates when exposed to CO 2 or CO 2 /H 2 (1/4) reaction mixtures. Normalized to the Ru molar percentage, the 5% Ru/CeO 2 system was the most active catalyst exhibiting a selectivity of ~ 60% CH 4 and 40% CO at 250 °C. On the other hand, under the same reaction conditions, the 20% Ru/CeO 2 system was less active but had a CH 4 selectivity close to 80%. In conclusion, these results highlight the importance of the structure of the metallic Ru particles as a factor that determines the catalytic performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Elucidating the speciation of extracted lanthanides by diglycolamides

Many studies over the past few decades have been devoted to addressing the application of diglycolamides (DGAs) for hydrometallurgical-based, f-element separations. Work to date has shown the molecular structure of a DGA derivative can have a significant impact on intra-lanthanide partitioning patterns. More recent studies have pushed towards probing the structure function relationship of the lanthanide-DGA complex to enable the design of more efficient lanthanide separation systems. Spectroscopic techniques, such as UV–Visible, Fourier Transformed Infrared Spectroscopy (FT-IR), Nuclear Magnetic Resonance (NMR), and Extended X-ray Absorption Fine Structure (EXAFS), provide information regarding the inner-sphere coordination of a given lanthanide-DGA complex. Scattering techniques, such as Dynamic Light Scattering (DLS), Small-Angle X-ray Scattering (SAXS), and Small-Angle Neutron Scattering (SANS), address nanoscale structures including aggregate sizes and morphology. Here, this review assesses the current state-of-knowledge regarding lanthanide-DGA hydrometallurgical (i.e., solvent extraction systems) interrogated using spectroscopic and scattering techniques to characterize the extracted Ln 3+ DGA species. Of particular interest to this review is the impact of varied diluents, inclusion and variation of phase modifiers, and DGA derivatization on system characteristics. While there has been extensive literature on the application of DGAs for f-element separations, the literature lacks a collective assessment of the speciation of Ln 3+ in the organic phase. This review provides new insights into the field of DGA separations, explicitly with an application to intra-lanthanide separations. Specifically, this review illustrates the importance of both the co-extraction anion (Cl - , NO 3 - , or ClO 4 - ) as it pertains to both the aggregate size and Ln 3+ distribution coefficient. It is evident the ability of the anion to disrupt the hydrogen bonding network limits both aggregate size and distribution coefficients according to the Hoffmeister series. This suggests the importance of the large, softer anions with a low charge-to-surface area ratio on encouraging hydrogen bond interactions. In addition, the co-extracted cation (H + vs Na + ) is important for mitigating transfer of Ln 3+ from the aqueous to the organic phase through extensive hydrogen bonding networks. These networks are responsible for forming supramolecular aggregates where a change in morphology is observed with increasing concentrations of H + and/or Ln 3+ in the organic phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Printed graphene oxide-based membranes for gas separation and carbon capture

Graphene oxide (GO)-based separation membranes have demonstrated the great potential to separate molecules and ions by the interlayer spacing with tunable nano-sized channels. The scalable fabrication of GO-based gas separation membranes, however, remains challenging, although a few preparation approaches have been reported. Here in this work, we present for the first time that the co-solvent ink-jet printing, as a fast and scalable method, can be utilized for scalable GO-based gas separation membrane preparation. Large-area (>100 cm 2 ), ultrathin, and high-quality GO membrane was successfully deposited on commercial polysulfone (PS) support, and characterized by scanning electron microscopy, X-ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, and X-ray diffraction, et al., Selective hydrogen (H 2 ) and helium (He) transport over carbon dioxide (CO 2 ) and nitrogen (N 2 ) was demonstrated for the printed GO membrane. To further explore the separation potential of the printed GO-based gas membrane, additives for facilitated molecular transport were incorporated during the membrane printing process. By inserting CO 2 -philic agents into the printed GO membrane, highly efficient separation of CO 2 from N 2 was achieved with CO 2 /N 2 selectivity of 70 and CO 2 permeance as high as 2,500 GPU. The strategy proposed here may provide guidance for large-scale GO-based gas separation membrane production and a versatile approach for applying other functional 2-dimensional materials towards the membrane separation application.

42 ENGINEERING↗
DOE OSTI2023

Optimization and understanding of ZnO nanoarray supported Cu-ZnO-Al 2 O 3 catalyst for enhanced CO 2 -methanol conversion at low temperature and pressure

Cu-ZnO-Al 2 O 3 is the most widely applied catalyst for CO 2 hydrogenation to methanol. However, it is still a challenge to produce methanol using this catalyst under low-temperature (<250 °C) and low-pressure (<10 bar) conditions with desirable yield and selectivity. In this work, by tuning the experimental processing parameters such as solvent, loading amount, and annealing temperature, highly improved ZnO nanoarray supported Cu-ZnO-Al 2 O 3 catalysts have been successfully demonstrated. Here, by using organic solvent (N,N-dimethylformamide (DMF), acetone, or isopropanol) for dip-coating loading process instead of deionized (DI) water, Cu-ZnO-Al 2 O 3 nanocatalysts was comparatively better dispersed on the nanorod array support with populated and abundant active sites, thus enhancing the methanol yield. With the control of the loading amount and annealing temperature, finely distributed Cu nanoparticles were obtained on the ZnO nanorod surfaces to enhance the interactions between Cu and ZnO nanorod surfaces. Further improvement of the catalyst performance is demonstrated by tuning the reaction space velocity. At 200 °C and 10 bar conditions, the optimized catalyst achieved a methanol yield of 6.46 mol h –1 kg –1 with 100 % selectivity. The good stability after prolonged testing of the catalysts demonstrates the potential practical implementation. The in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) measurements under the 1 bar reveal that the CO 2 hydrogenation to methanol on the ZnO nanoarray supported Cu-ZnO-Al 2 O 3 catalyst follows the CO reaction pathway, due to the surface oxygen vacancies on ZnO nanorods which facilitate CO 2 dissociation.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Constructing efficient CuO x -CeO 2 catalyst for NO reduction by CO: New insights into the structure–activity relationship

CuO-CeO 2 based materials have been recognized as promising substitutes for precious metal catalysts in emission control field due to their superior redox property and low cost. In this work, by optimizing the deposition process of CeO 2 and CuO onto γ-Al 2 O 3 , highly dispersed CuO clusters on unique CeO 2 -Al 2 O 3 support with small CeO 2 particles (7Cu-Ce/CeAl) were successfully constructed for efficient NO reduction by CO, which exhibited much higher NO removal efficiency and N 2 selectivity than CuO catalysts supported on γ-Al 2 O 3 (7Cu/Al) and conventional CeO 2 -Al 2 O 3 support (7Cu/CeAl). Moreover, H 2 O showed limited inhibition effect on the catalytic performance of 7Cu-Ce/CeAl catalyst. With the help of Raman spectra, X-ray absorption spectroscopy, in situ diffuse reflectance infrared Fourier transform spectroscopy, etc., it was clearly revealed that the abundant Cu + /Ce 3+ paired sites with surface synergetic oxygen vacancies (SSOV) on 7Cu-Ce/CeAl catalyst could effectively facilitate the adsorption and activation of CO and NO, thus significantly enhancing the NO removal efficiency.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Superhydrophobic to superhydrophilic wettability transition of functionalized SiO 2 nanoparticles

The superhydrophobic and superhydrophilic surfaces and their transitions are of great interest for the production of self-cleaning, anti-biofouling, or corrosion-resistant materials. This research reports the wettability transition from superhydrophobic to superhydrophilic SiO 2 nanoparticles functionalized with 1H, 1H, 2H, 2H-perfluorooctyltriethoxysilane (POTS) and induced by temperature. The functionalization of these nanoparticles was confirmed by Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy (XPS), and transmission electron microscopy. The functionalization of SiO 2 nanoparticles with POTS resulted in superhydrophobic surfaces with water contact angles up to 157°. A sudden transition to superhydrophilic behavior with water contact angles (WCA) below 5° was observed when the sample was heat-treated at 500 °C, despite the presence of fluorine on the surface of these nanoparticles, as confirmed by XPS and transmission electron microscopy. XPS suggested that the transition was caused by the change in orientation of the fluoroalkyl molecules and its partial decomposition due to the loss of the –CF 3 group, resulting in shorter chains with a tail-end group with C–O bonds, which promoted the superhydrophilicity.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Metal oxide-promoted calcium cuprate catalysts for diol oxidative dehydrocyclization to lactones

Here, this work investigates structure-function relationships in electronically tunable, redox-active, basic Cu-Ca mixed metal oxide catalysts for oxidative dehydrocyclization of liquid diols to lactones. Compositional screening identified Ni 2+ and Zn 2+ as effective promoters that increase the surface Cu 2+ population by ∼1.7× and Cu-normalized activity for liquid 1,4-butanediol conversion to γ-butyrolactone by ∼3–4×. In situ Raman spectroscopy, in situ X-ray absorption spectroscopy (XAS), in situ diffuse-reflectance Fourier transform infrared spectroscopy (DRIFTS), ex situ X-ray diffraction (XRD), and H 2 -temperature-programmed reduction (H 2 -TPR) show that Ni 2+ or Zn 2+ incorporation promotes the formation of Ca 0.82 Cu 1.00 O 2 nanoparticles under mild calcination conditions. This cuprate phase features stronger and shorter Cu–O bonds (1.90 Å) than inactive bulk CuO (1.95 Å) and square-planar Cu 2+ O 4 sites with enhanced d z2 electrophilicity, strengthening alkoxy adsorption. Pyridine-DRIFTS confirms the purely basic nature of the catalyst surface, while methanol-DRIFTS indicates Cu 2+ surface enrichment with Ni or Zn promotion, where Cu–O(Ca)–Cu sites can exist as amorphous domains or a truncation layer on crystalline nanoparticles.

09 BIOMASS FUELS↗
DOE OSTI2025

The structure of high-Mg alkali-bearing aluminosilicate glasses investigated in situ at ambient and high pressure by multi-angle energy dispersive X-ray diffraction and infrared microspectroscopy

The structural properties of synthetic high-Mg alkali-bearing aluminosilicate glasses analogues of natural picritic-to-komatiitic magmas were investigated in situ by multiangle energy dispersive X-ray diffraction at 2.1 GPa and ambient pressure and by Fourier Transform infrared spectroscopy up to 5.4 GPa in a cycle of compression and decompression experiments. Our results show that the intermediate range ordering of the glass structure at 2.1 GPa is 3.14 Å, increasing to 3.19 Å when decompressed. The local structure shows T-O lengths of 1.66 Å (2.1 GPa) and 1.65 Å (ambient pressure), T-T distances of 3.19 Å at high pressure, which lengthen to 3.21 Å at ambient pressure, causing the T-O-T angle of 147° determined at 2.1 GPa to widen to 154° upon decompression. The deconvoluted infrared spectra result in the presence of Q 1 , Q 2 , Q 3 populations in the aluminosilicate spectral region, whose proportions remain relatively unchanged up to 5.4 GPa. The structural response of the investigated glasses to cold-compression does not involve changes in polymerization, but rather a shrinking and compaction of the structure as evidenced by the Qn species shifting to higher wavenumbers as a function of pressure. The structural properties determined from X-ray diffraction for this glass composition are discussed together with those of glasses emerging from previous studies to highlight a compositional dependence mainly dictated by the amount of SiO 2 and Al 2 O 3 .

glass structure↗
DOE OSTI2022

Removable coatings: Thermal stability and decontamination of steel surfaces from 241 Am

This study presents a comparative analysis of several strippable materials for decontamination of steel surfaces from 241 Am. The strippable coatings were chosen to have a history of application, to be commercially available, easily handled and have different composition and formulation. Carbon steel and stainless steel surfaces (coupons) were utilized as the most representative industrial materials, and the experimental series were expanded to include the rusting treatment of these surfaces as it is common for decommissioned old nuclear facilities. The experiments followed the path of pre-screening of the strippable materials (easiness of application, peeling etc.), their characterization with Fourier-transform infrared (FTIR) spectroscopy and thermogravimetric analysis (TGA), decontamination factors (DF) or removal efficiencies for different types of steel surfaces, and enhancement of the removal efficiencies of the select strippable coatings via amendment with EDTA. As a result, DF and removal efficiencies for stainless steel (both pristine and with rusting treatment) are higher than for pristine carbon steel, and decontamination factors and removal efficiencies are higher for pristine than for rusted carbon steel across all the coatings. It is also shown that EDTA amendment can improve DF and removal efficiency for a strippable coating (i.e., CC Strip), however other factors should also be considered. Thus, the coating CC Strip exhibited easiness in handling and high DF (up to 97% when EDTA-amended), but its drying period was the longest among the rest of the materials and its thermal decomposition indicates on a risk of intense release of heat in case of a fire event.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A comprehensive and fair comparison of two neural operators (with practical extensions) based on $\mathrm{FAIR}$ data

Neural operators can learn nonlinear mappings between function spaces and offer a new simulation paradigm for real-time prediction of complex dynamics for realistic diverse applications as well as for system identification in science and engineering. Herein, we investigate the performance of two neural operators, which have shown promising results so far, and we develop new practical extensions that will make them more accurate and robust and importantly more suitable for industrial-complexity applications. The first neural operator, DeepONet, was published in 2019 (Lu et al., 2019), and its original architecture was based on the universal approximation theorem of Chen & Chen (1995). The second one, named Fourier Neural Operator or FNO, was published in 2020, and it is based on parameterizing the integral kernel in the Fourier space. DeepONet is represented by a summation of products of neural networks (NNs), corresponding to the branch NN for the input function and the trunk NN for the output function; both NNs are general architectures, e.g., the branch NN can be replaced with a CNN or a ResNet. According to Kovachki et al. (2021), FNO in its continuous form can be viewed conceptually as a DeepONet with a specific architecture of the branch NN and a trunk NN represented by a trigonometric basis. In order to compare FNO with DeepONet computationally for realistic setups, we develop several extensions of FNO that can deal with complex geometric domains as well as mappings where the input and output function spaces are of different dimensions. We also develop an extended DeepONet with special features that provide inductive bias and accelerate training, and we present a faster implementation of DeepONet with cost comparable to the computational cost of FNO, which is based on the Fast Fourier Transform. Here we consider 16 different benchmarks to demonstrate the relative performance of the two neural operators, including instability wave analysis in hypersonic boundary layers, prediction of the vorticity field of a flapping airfoil, porous media simulations in complex-geometry domains, etc. We follow the guiding principles of FAIR (Findability, Accessibility, Interoperability, and Reusability) for scientific data management and stewardship. The performance of DeepONet and FNO is comparable for relatively simple settings, but for complex geometries the performance of FNO deteriorates greatly. We also compare theoretically the two neural operators and obtain similar error estimates for DeepONet and FNO under the same regularity assumptions.

42 ENGINEERING↗
DOE OSTI2023

Probabilistic-learning-based stochastic surrogate model from small incomplete datasets for nonlinear dynamical systems

We consider a high-dimensional nonlinear computational model of a dynamical system, parameterized by a vector-valued control parameter, in the presence of uncertainties represented by an uncontrolled parameter modeled by a vector-valued random variable, and possibly with stochastic excitation. The objective is to construct a statistical surrogate model where the input is any deterministic value of the control parameter, and the output is a vector-valued observation of the computational model, which is a random vector whose probability measure is updated using a target dataset. To construct this statistical surrogate model, the stochastic response of the computational model must be built, which is a vector-valued time-discretized stochastic process in high dimension, depending on the control parameter. It is assumed that the computational cost of a single evaluation of the deterministic model is high. For the probabilistic updating, we consider a subset of the components of the observation of the computational model, defined as the “identification observation” of the computational model, for which a small target dataset is available. Therefore, the target dataset is associated with partial observability, corresponding to an incomplete data case. Given a prior probability model of the random control and uncontrolled parameters, a training dataset is constructed, consisting of realizations of the random triplet composed of the stochastic response, the random identification observation, and the random control parameter. Since the computational cost of a single evaluation of the deterministic model is assumed to be large, the training dataset is also of small size. The main challenges in this problem are the high dimensionality, partial observability leading to incomplete data in the target dataset for the identification observation of the computational model (which is not sufficient to identify the computational stochastic responses), and the availability of a small training dataset. To address these challenges, we propose a methodology based on statistical methods for constructing necessary reduced representations, direct probabilistic learning under constraints using probabilistic learning on manifolds (PLoM) constrained by the target dataset, and the use of a weak formulation of the Fourier transform of probability measures. Statistical conditioning is also employed to explore the learned dataset. The constructed predictive statistical surrogate model can be implemented in the context of online computation. Here, we apply this approach to a problem of nonlinear stochastic dynamics in high dimensions within the framework of deformable solids mechanics.

Engineering↗
DOE OSTI2024

Effect of non-uniform void distributions on the yielding of metals

High-throughput (several thousand) calculations have been carried out to investigate the yield behavior of porous materials with randomly distributed pores, porosity levels over four orders of magnitude and up to a hundred pores per simulation box. To this end, a Galerkin based fast Fourier transform (FFT) formulation was enhanced to deal with high phase contrast materials. In addition, GPU parallelization was employed in solving the governing equation for strain fluctuations using a Krylov iterative solver. Emphasis is laid on the conditions under which percolation of plastically non-deforming zones through the porous network emerge, a regime termed unhomogeneous yielding. By way of contrast, the regime where the plastic strain fluctuations (associated with the heterogeneous void-matrix aggregate) fall below the percolation threshold is defined as homogeneous yielding. Here, we find that nonuniform pore distributions only affect unhomogeneous yielding and have a universal softening effect. The extent of this distribution softening is analyzed as a function of porosity, cell size and number of realizations. Whether the uncovered universal distribution softening has direct implications on failure resistance of porous materials is discussed.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

Infrared nanoimaging and nanospectroscopy of electrochemical energy storage materials and interfaces

Electrochemical interfaces are central to the function and performance of energy storage devices. Thus, the development of new methods to characterize these interfaces, in conjunction with electrochemical performance, is essential for bridging the existing knowledge gaps and accelerating the development of energy storage technologies. Of particular need is the ability to characterize surfaces or interfaces in a non-destructive way with adequate resolution to discern individual structural and chemical building blocks. To this end, sub-diffraction-limit low-energy infrared optical probes that exploit near-field interactions within atomic force microscopy platforms, such as pseudoheterodyne nanoimaging, photothermal nanoimaging and nanospectroscopy, and nanoscale Fourier transform infrared spectroscopy, are all powerful emerging techniques. These are capable of non-destructive surface probing and imaging at nanometer resolution. This review outlines recent efforts to characterize ex situ, in situ, and operando electrode materials and electrochemical interfaces in rechargeable batteries with these advanced infrared near-field probes.

25 ENERGY STORAGE↗
DOE OSTI2024

Effect of plasma treatment on LMPAEK/CF tape and composites manufactured by automated tape placement (ATP)

Automated tape placement (ATP) process is widely used in aerospace for its advanced process control and multi-axis capabilities but faces issues like limited choice of materials and suboptimal tape consolidation. This study investigates air plasma treatment on ATP carbon fiber thermoplastic feedstock tape to address these challenges. The effects on low melt Polyaryletherketone/carbon fiber unidirectional tape (LMPAEK/CF UD tape) were analyzed. Treated and untreated tapes were used to fabricate composites and evaluated for physical, thermal, mechanical, and interfacial properties. Atomic force microscopy (AFM), X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared (FTIR) analyses revealed surface roughness changes (on LMPAEK), extent of oxidation, and the presence of hydroxyl/carboxyl groups. Composites from plasma-treated tapes showed a 7.6% increase in tensile strength, 8% in tensile modulus, 18% in flexural strength, and 8.3% in flexural modulus. Further, the interlaminar shear strength improved by 18.7%. Failure analysis showed untreated composites failed via inter-ply and fiber-matrix delamination, while treated composites experienced matrix cracking and fiber breakage. This study highlights atmospheric plasma treatment as a solution to ATP’s limitations, significantly enhancing LMPAEK/CF UD tape composites’ properties.

36 MATERIALS SCIENCE↗