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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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Elucidating interfacial active sites in ruthenium–boron nitride nanotube catalysts for efficient low-temperature ammonia-to-hydrogen conversion

Tailoring the interaction between metal nanoparticles and catalyst support presents a prominent strategy to enhance both the activity and durability in hydrogen (H 2 ) production catalysts. In this work, ruthenium nanoparticles (NPs) supported on boron nitride nanotubes (Ru/BNNT) are introduced as efficient and thermally robust catalysts for low-temperature ammonia (NH 3 ) decomposition. The unique curvature and ionic nature of BNNTs enable uniform Ru dispersion and metal-support interactions (MSIs), resulting in exceptional H 2 generation efficiency and long-term operational stability. In-situ transmission electron microscopy (TEM) reveals remarkable thermal resistance of Ru/BNNT with minimal nanoparticle sintering, while density functional theory (DFT) calculations uncover a dual-site mechanism in which interfacial Ru atoms promote NH 3 dissociation and adjacent Ru sites facilitate 2H* recombination and H 2 desorption. This cooperative interaction between metal NPs and the BNNT support underpins the outstanding catalytic performance and durability observed. In conclusion, the findings highlight the strategic potential of BNNTs as versatile supports for high-performance and stable catalysts in sustainable H 2 energy conversion and related catalytic processes.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Fracture properties and microstructure formation of hardened alkali-activated slag/fly ash pastes

This study presents a comprehensive experimental investigation on the fracture properties of hardened alkali-activated slag/fly ash (AASF) pastes in relation to the microstructure formation and reaction product composition. The main reaction product in AASF is C-(N-)A-S-H gel along with minor hydrotalcite phase, with the polymerization of C-(N-)A-S-H gel substantially governed by its Ca/Si ratio. Strong positive correlations are identified between the Ca/Si ratios of C-(N-)A-S-H gel and the fracture properties K{sub Ic} (J{sub tip}), whereas, the compressive strength of AASF pastes is primarily determined by its capillary porosity (>0.01 μm). The disagreements between the Ca/Si ratios and corresponding intrinsic mechanical properties of C-(N-)A-S-H gel as proof by contradiction indicate that the fracture properties K{sub Ic} (J{sub tip}) of AASF pastes could be dominated by a cohesion/adhesion-based mechanism. These findings provide promising guidance for fine-tuning the fracture properties of AASF and also advise on the tailoring strategies for high-performance composite such as strain-hardening geopolymer composite.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Intrinsic self-stressing and low carbon Engineered Cementitious Composites (ECC) for improved sustainability

Highlights: • A self-stressing criterion for ECC was established and experimentally verified. • An intrinsic self-stressing ECC was developed by utilizing LC3 and CSA cement. • Initial maximum expansion and later expansion loss were successfully tailored. • Expansion mechanism was identified by XRD patterns. • Self-stressing ECC has 64% of the carbon footprint of conventional concrete. Engineered Cementitious Composites (ECC) is an emerging cementitious composite material with ultra-high ductility. However, its higher cement dosage limits its material greenness and leads to concerns with drying shrinkage. In this research, an ECC utilizing limestone calcined clay cement (LC3) and calcium sulphoaluminate cement (CSA) is investigated, focusing on minimizing the material's embodied carbon while enhancing its durability with intrinsic self-stressing functionality. A self-stressing criterion is theoretically established and experimentally verified. X-ray diffraction patterns reveal an ettringite quantity that modulates the initial expansion and later expansion-reversal of LC3-CSA-ECC to support a persistent self-stressing mechanism. LC3-CSA-ECC has a lower (64%) carbon footprint and similar embodied energy compared to conventional concrete. When combined with the durability advantage (tiny crack, high ductility of 5.5%, and self-stressing function), this low carbon self-stressing ECC holds promise as a sustainable repair material that lowers the embodied and operational carbon in civil infrastructure.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Thermal energy storage in concrete: Review, testing, and simulation of thermal properties at relevant ranges of elevated temperature

This study examines the thermal performance of concrete used for thermal energy storage (TES) applications. The influence of concrete constituents (aggregates, cementitious materials, and fibers) on the thermal conductivity and specific heat are summarized based on literature and via experimentation at elevated temperatures. It is indicated that concrete with siliceous aggregate, low water/cement ratios, and steel fibers produces better overall thermal properties. The results of literature review and laboratory testing are used for numerical simulation to evaluate the impact of concrete thermal property variability on TES capabilities. The TES module consists of the heat exchanger and surrounding concrete as the storage media. Both idealized cases without heat loss and realistic cases with insulation and heat losses are considered. Furthermore, the result shows that conventional concrete mixes can be tailored to decrease the module charge/discharge durations and increase the amount of thermal energy storage.

25 ENERGY STORAGE↗
DOE OSTI2020

A perspective on challenges and opportunities in developing high entropy-ultra high temperature ceramics

The emergence of a new class of high entropy ultra-high temperature ceramics (HE-UHTCs) is expected to possess exceptionally superior mechanical, oxidation, and erosion resistance as compared to conventional UHTCs. The improvement in the properties of HE-UHTCs is attributed to the high configurational entropy of the multi-component system stabilized into a single-phase, but with little discussion on entropy contributions. This perspective article presents a viewpoint on the critical scientific question regarding the actual role entropy plays in stabilizing and enhancing the thermo-mechanical properties of a multi-component system. The high throughput first-principle calculations, which can provide the entropy formation ability (EFA) of thermodynamically stable HE-UHTCs, can prove to be valuable toolset to this puzzle. HE-UHTCs show enhancement in the mechanical properties much higher than the predicted rule of the mixture, which cannot traditionally be explained by a mere solid solution formation effect. Additionally, isothermal oxidation studies of HE-UHTCs limited to furnace testing state remarkable oxidation resistance which is attributed to the passivity of complex, layered structure, and composition of the oxide scale. However, whether all the constituents in the HE-UHTC system react simultaneously or preferential oxidation takes place needs to be addressed. To address all these issues, an integrated computational and experimental approach has been postulated towards designing a thermal protection system (TPS) for re-entry applications. Succeeding the approach will provide new opportunities in the compositional space of HE-UHTCs with tailored properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Emerging continuous SiC fibers for high-temperature applications

Silicon carbide (SiC) fibers are responsible for the ultimate strength and toughness of SiC-fiber reinforced composites in harsh environments. The development of a new generation of continuous SiC fibers continues to advance the mechanical properties of composite materials. Tyranno™ SA4 fiber was recently released as a successor of Tyranno™ SA3 fiber. Laser-driven chemical vapor deposition (LCVD) has been adopted as an alternative fiber processing route to synthesizing high-strength SiC fiber with tailorable small diameters and chemical compositions. Both Tyranno™ SA4 and laser-driven CVD fibers show very high tensile strength, about 4 GPa in the as-fabricated condition. The degradation of thermal stability and strength due to annealing in an inert environment were similar for Tyranno™ SA3 and SA4 fibers because of their similar carbon-rich, crystalline microstructure. Silicon-rich fibers produced by LCVD possessed heterogeneous crystallinity, which was attributed to laser power distribution and showed microstructural instability at 1500 °C and above. Finally, the new SiC fibers demonstrated an increase in as-fabricated strength but faced the same challenges in environmental resistance as the traditional SiC fibers do.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The role of size and structure of catalytic active sites in polyolefin hydrogenolysis

The increasing amount of plastic waste poses serious environmental problems that threaten both ecosystems and human well-being. Hydrogenolysis has been widely studied as an effective approach for converting polyolefins into high-value liquids and waxy fuels. Their multifaceted reaction mechanism, including dehydrogenation, C–C bond cleavage, and hydrogenation, highlights the need for sophisticated catalyst design. The suppression of methane production, a persistent challenge in polyolefin hydrogenolysis, requires precise control of the cleavage site and inhibition of successive C–C bond cleavage. This delicate balance is achieved by carefully tuning the size and structure of metals. In this review, we investigate the effects of the size and structure of active sites on their catalytic activity and selectivity for the hydrogenolysis of polyolefins, including polyethylene and polypropylene. In conclusion, a fundamental understanding of hydrogenolysis mechanisms, combined with strategic synthetic methodologies, is crucial for creating efficient catalysts with tailored properties.

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

Cooperative Effects Associated with High Electrolyte Concentrations in Driving the Conversion of CO2 to C2H4 on Copper

Compared to a conventional electrolyte concentration of 1 M HCOOK, the use of a highly concentrated 7.1 M HCOOK electrolyte increases the Faradaic efficiency (FE) ratio of C2H4/CO from 2.2 +- 0.3 to 18.3 +- 4.8 at -1.08 V vs. reversible hydrogen electrode (RHE) on a Cu gas-diffusion electrode. Based on electrochemical analysis and ab initio molecular dynamics (AIMD) simulation, the identity and concentration of the cation and anion play more important roles in controlling the CO2R reaction pathway than the bulk CO2 solubility and the bulk pH of electrolytes. In situ attenuated reflectance surface enhanced infrared absorption spectroscopy (ATR-SEIRAS) suggests that, unlike 1 M HCOOK, the *CO-bridge-binding mode on Cu is dominant in 7.1 M HCOOK electrolyte, which potentially results in less CO release and higher yield of C2H4. This study demonstrates that although we can tailor the electrolyte composition to shift product selectivity, the factors that control the product selectivity are numerous and cannot be distilled down into one correlated property-reactivity relationship.

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

Molecular basis of C-S bond cleavage in the glycyl radical enzyme isethionate sulfite-lyase

Desulfonation of isethionate by the bacterial glycyl radical enzyme (GRE) isethionate sulfite-lyase (IslA) generates sulfite, a substrate for respiration that in turn produces the disease-associated metabolite hydrogen sulfide. Here, we present a 2.7 Å resolution X-ray structure of wild-type IslA from Bilophila wadsworthia with isethionate bound. In comparison with other GREs, alternate positioning of the active site β strands allows for distinct residue positions to contribute to substrate binding. These structural differences, combined with sequence variations, create a highly tailored active site for the binding of the negatively charged isethionate substrate. Through the kinetic analysis of 14 IslA variants and computational analyses, we probe the mechanism by which radical chemistry is used for C-S bond cleavage. This work further elucidates the structural basis of chemistry within the GRE superfamily and will inform structure-based inhibitor design of IsIA and thus of microbial hydrogen sulfide production.

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

Bulk Grain-Boundary Materials from Nanocrystals

Grain-boundary engineering is pivotal to fully utilize the mechanical, electrical, and thermal-transport properties of various materials. However, current methods in metallurgy rely almost exclusively on top-down approaches, making precise grain-boundary engineering, especially at nanoscale, difficult to achieve. Herein, we report a method to produce tailored grain-boundary conditions with nanoscale precision from colloidal metal nanocrystals through surface treatment followed by a pressure-sintering process. The resulting bulk grain-boundary materials (which we call “nanocrystal coins”) possess a metal-like appearance and conductivity while inheriting the original domain features of the nanocrystal building blocks. In this work, nanoindentation measurements confirmed the superior mechanical hardness of the obtained materials. Further, we use this method to fabricate, for the first time, a single-component bulk metallic glass from amorphous palladium nanoparticles. Our discovery may spur the development of new materials whose functionality crucially depends on the domain configuration at nanoscale, such as superhard materials, thermoelectric generators, and functional electrodes.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Electrocatalytic grafting of polyvinyl chloride plastics

Polyvinyl chloride (PVC) plastics require high loadings of plasticizers and stabilizers to achieve commercially useful bulk properties. However, these non-covalent additives leach from PVC over time, resulting in the loss of their tailored functionality. This work details the electrocatalytic functionalization of PVC to covalently graft plasticizing additives directly onto the polymer backbone. Here, mechanistic insights guided the design of electrocatalysts capable of modifying C–Cl bonds of PVC under mild conditions with high selectivity while suppressing side reactions such as elimination and chain scission. Functional groups that mimic PVC plasticizers are covalently installed into the backbone of PVC to create new materials with distinct bulk properties from the original polymer. The degree of polymer grafting is easily controlled by simply changing the redox capacity that is passed during electrolysis. This strategy is employed to create chemically- and leach-resistant PVC materials by directly electrolyzing mixtures of consumer PVC products

Zackasee, Jordan L.S.↗
DOE OSTI2024

Rapid design of bacteriophage cocktails to suppress the burden and virulence of gut-resident carbapenem-resistant Klebsiella pneumoniae

Antibiotic use can lead to the expansion of multi-drug-resistant pathobionts within the gut microbiome that can cause life-threatening infections. Selective alternatives to conventional antibiotics are in dire need. Here, in this work, we describe a Klebsiella PhageBank for the tailored design of bacteriophage cocktails to treat multi-drug-resistant Klebsiella pneumoniae. Using a transposon library in carbapenem-resistant K. pneumoniae, we identify host factors required for phage infection in major Klebsiella phage families. Leveraging the diversity of the PhageBank, we formulate phage combinations that eliminate K. pneumoniae with minimal phage resistance. Optimized cocktails selectively suppress the burden of K. pneumoniae in the mouse gut and drive the loss of key virulence factors that act as phage receptors. Phage-mediated diversification of bacterial populations in the gut leads to co-evolution of phage variants with higher virulence and broader host range. Altogether, the Klebsiella PhageBank charts a roadmap for phage therapy against a critical multidrug-resistant human pathogen.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Dynamic beam shaping—Improving laser materials processing via feature synchronous energy coupling

Today, tailored laser beams are rarely used and thus an opportunity to optimize existing or introduce new processes is missed. New methods of dynamic beam shaping have the potential to change that in future. This keynote paper deals with methods allowing a transient energy input into the workpiece at such time scales that the underlying interaction processes are guided towards the desired result. It shows principles, categorizes necessary system technology, and gives application examples to familiarize the reader with the topic. It postulates that time-scale-dependent coupling between transient energy input and addressed process features is key for achieving the optimum.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Recyclability of reversible polymer networks over a Dozen reprocessing cycles

Reversible polymer networks capable of reversible reactions along their backbone provide a promising strategy for addressing waste management challenges associated with conventional thermoset products. However, reversible polymer networks cannot be recycled infinitely. Unavoidable side reactions eventually cause significant degradation of mechanical properties or loss of recyclability. This study aims to answer a simple yet critical question on reversible polymer network systems: how many reprocessing cycles can be achieved before profound mechanical degradation or a loss of recyclability? The recyclability of Diels–Alder (DA) network samples was evaluated by repeating consistent reprocessing cycles until they were no longer reprocessable. To enhance their recyclability, the chemical structure of the maleimide precursor was tailored to mitigating side reactions by maleimide homopolymerization. Remarkably, by employing a maleimide precursor with alkyl substitutions on its phenyl group, the DA network system attained 12 reprocessing cycles using injection molding at 160 °C without significant degradation of mechanical properties. However, the 13th reprocessing cycle did not succeed. Rheological analysis revealed the accumulation of non-reversible bonds within the network structure during repeated reprocessing, despite fairly consistent mechanical properties under operating conditions. This study demonstrates that the rational design of the maleimide precursor is an effective means to enhance the reprocessability of DA networks.

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

Online adaptive basis refinement and compression for reduced-order models via vector-space sieving

In many applications, projection-based reduced-order models (ROMs) have demonstrated the ability to provide rapid approximate solutions to high-fidelity full-order models (FOMs). However, there is no a priori assurance that these approximate solutions are accurate; their accuracy depends on the ability of the low-dimensional trial basis to represent the FOM solution. As a result, ROMs can generate inaccurate approximate solutions, e.g., when the FOM solution at the online prediction point is not well represented by training data used to construct the trial basis. To address this fundamental deficiency of standard model-reduction approaches, this work proposes a novel online-adaptive mechanism for efficiently enriching the trial basis in a manner that ensures convergence of the ROM to the FOM, yet does not incur any FOM solves. The mechanism is based on the previously proposed adaptive $h$-refinement method for ROMs, but improves upon this work in two crucial ways. First, the proposed method enables basis refinement with respect to any orthogonal basis (not just the Kronecker basis), thereby generalizing the refinement mechanism and enabling it to be tailored to the physics characterizing the problem at hand. Second, the proposed method provides a fast online algorithm for periodically compressing the enriched basis via an efficient proper orthogonal decomposition (POD) method, which does not incur any operations that scale with the FOM dimension. We report these two features allow the proposed method to serve as (1) a failsafe mechanism for ROMs, as the method enables the ROM to satisfy any prescribed error tolerance online (even in the case of inadequate training), and (2) an efficient online basis-adaptation mechanism, as the combination of basis enrichment and compression enables the basis to adapt online while controlling its dimension.

42 ENGINEERING↗
DOE OSTI2024

A fast and accurate domain decomposition nonlinear manifold reduced order model

Here, this paper integrates nonlinear-manifold reduced order models (NM-ROMs) with domain decomposition (DD). NM ROMs approximate the full order model (FOM) state in a nonlinear-manifold by training a shallow, sparse autoencoder using FOM snapshot data. These NM-ROMs can be advantageous over linear-subspace ROMs (LS-ROMs) for problems with slowly decaying Kolmogorov n-width. However, the number of NM-ROM parameters that need to be trained scales with the size of the FOM. Moreover, for “extreme-scale” problems, the storage of high-dimensional FOM snapshots alone can make ROM training expensive. To alleviate the training cost, this paper applies DD to the FOM, computes NM-ROMs on each subdomain, and couples them to obtain a global NM-ROM. This approach has several advantages: Subdomain NM-ROMs can be trained in parallel, involve fewer parameters to be trained than global NM-ROMs, require smaller subdomain FOM dimensional training data, and can be tailored to subdomain specific features of the FOM. The shallow, sparse architecture of the autoencoder used in each subdomain NM-ROM allows application of hyper-reduction (HR), reducing the complexity caused by nonlinearity and yielding computational speedup of the NM-ROM. This paper provides the first application of NM-ROM (with HR) to a DD problem. In particular, this paper details an algebraic DD reformulation of the FOM, training a NM-ROM with HR for each sub domain, and a sequential quadratic programming (SQP) solver to evaluate the coupled global NM-ROM. Theoretical convergence results for the SQP method and a priori and a posteriori error estimates for the DD NM-ROM with HR are provided. The proposed DD NM-ROM with HR approach is numerically compared to a DD LS-ROM with HR on the 2D steady-state Burgers’ equation, showing an order of magnitude improvement in accuracy of the proposed DD NM-ROM over the DD LS-ROM.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Predicting non-linear stress–strain response of mesostructured cellular materials using supervised autoencoder

Recent breakthroughs in advanced manufacturing capabilities have made it possible to design and print sophisticated topologies of cellular structures using diverse engineering materials such as metals, polymers, and ceramics. In these architectured materials, it is often desirable to tailor the mechanical properties by altering the unit cell topology. This necessitates an in-depth understanding of how the topology of the unit cell structure affects the macroscopic behavior of the material in both the linear and the non-linear regimes encountered under large compression. Here, we have developed a machine learning (ML) approach capable of accelerating the prediction of the stress–strain response of a polymer-based cellular structure under uniaxial confined compression. As part of generating the training data for ML, 60,000 mesostructures were generated using a relatively novel approach based on cellular automata, and their corresponding stress–strain responses were obtained from the finite element simulations. Principal component analysis (PCA) was used to reduce the dimensionality of the stress–strain curves. With only 20 principal components, PCA captured 99.89% of the variance in the stress–strain curves while reducing the dimensionality by 5X. ML using supervised autoencoder was able to successfully speed up the prediction of the non-linear stress–strain response of a unit cell by up to 4600X. The proposed method can serve as an efficient data generation tool and a rapid means for predicting the structure–property relationship through accelerated forward modeling of cellular materials under compaction, in cases where the macroscopic stress–strain response is governed by the unit-cell topology.

36 MATERIALS SCIENCE↗
DOE OSTI2025

An end-to-end deep learning method for solving nonlocal Allen–Cahn and Cahn–Hilliard phase-field models

Here, we propose an efficient end-to-end deep learning method for solving nonlocal Allen–Cahn (AC) and Cahn–Hilliard (CH) phase-field models. One motivation for this effort emanates from the fact that discretized partial differential equation-based AC or CH phase-field models result in diffuse interfaces between phases, with the only recourse for remediation is to severely refine the spatial grids in the vicinity of the true moving sharp interface whose width is determined by a grid-independent parameter that is substantially larger than the local grid size. In this work, we introduce non-mass conserving nonlocal AC or CH phase-field models with regular, logarithmic, or obstacle double-well potentials. Because of non-locality, some of these models feature totally sharp interfaces separating phases. The discretization of such models can lead to a transition between phases whose width is only a single grid cell wide. Another motivation is to use deep learning approaches to ameliorate the otherwise high cost of solving discretized nonlocal phase-field models. To this end, loss functions of the customized neural networks are defined using the residual of the fully discrete approximations of the AC or CH models, which results from applying a Fourier collocation method and a temporal semi-implicit approximation. To address the long-range interactions in the models, we tailor the architecture of the neural network by incorporating a nonlocal kernel as an input channel to the neural network model. We then provide the results of extensive computational experiments to illustrate the accuracy, predictive capabilities, and cost reductions of the proposed method.

42 ENGINEERING↗