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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Atomistic simulations and machine learning of solute grain boundary segregation in Mg alloys at finite temperatures

Understanding solute segregation thermodynamics is the first step in investigating grain boundary (GB) properties, such as strong yttrium (Y) effects on grain growth and texture evolution in micro-scale polycrystalline magnesium (Mg) alloys. To estimate the average GB segregation behavior in low-solute-concentration Mg alloys (e.g., 2 at.% Y), a state-of-the-art spectral approach is applied based on a per-site segregation energy spectrum for Y solute atoms at zero K obtained from molecular statistics (MS) simulations of ~10 4 GB sites in Mg symmetric tilt GBs (STGBs). Although selected MS simulation results are consistent with verification by density functional theory (DFT) calculations, estimates of average segregation tendency based on the zero-K energy spectrum deviate from experimental observations. To resolve this problem, thermodynamic integration (TI) methods based on molecular dynamics (MD) simulations are used to determine the per-site segregation free energies of Y at representative GB sites, which show contributions beyond harmonic approximations can be important for certain GB sites at high temperatures. A surrogate model of per-site segregation free energy is constructed from a small set of TI data points using stacking cross-validation regressors and physics-informed descriptors. This model is applied to predict the Y segregation free energy spectra for thousands of GB sites in Mg STGBs with uncertainty quantification. Finally, the average segregation tendency predicted by the spectral approach based on the free energy spectra agrees well (within the uncertainty range) with experimental observations for micro-scale polycrystalline Mg alloys at typical thermomechanical processing temperatures (500 ~ 800 K), where thermodynamic equilibrium states are likely to be achieved due to fast diffusion.

Atomistic simulations↗
DOE OSTI2025

An energetic link between order and strength in metals: A nanocrystalline strength limit in high-entropy alloys and intermetallic compounds

The metallurgy and materials communities have long understood and exploited fundamental links between chemical and structural ordering in metallic solids to tailor their mechanical properties. We extend these ideas to include prediction of the nanocrystalline strength limit in high-entropy alloys and intermetallic compounds, where a breakdown occurs in the classical Hall-Petch strengthening behavior. The highest reported strength achievable through alloying has rapidly climbed and given rise to new classifications of materials with extraordinary properties, with a notable case being nanocrystalline metals. High-entropy alloys (chemically disordered, concentrated solid solutions) and intermetallic compounds are two boundary cases of how tailored order can be used to manipulate mechanical behavior. Here, we show that the complex electronic-structure mechanisms governing the peak strength of alloys and pure metals can be reduced to a few physically meaningful parameters based on their atomic arrangements and used – with no fitting parameters – to predict the maximum strength of these materials. This includes a generalized energy-based accounting for the degree of structural and chemical ordering that allows for rapid and reasonably accurate prediction of peak strength (validated in the nanocrystalline limit) as a function of temperature. Predictions of maximum strength based on the activation energy (with all materials properties derived from DFT calculations or experiments) for a stress-driven transition to an amorphous state is shown to accurately describe the breakdown in Hall-Petch behavior at the smallest crystallite sizes for pure metals, intermetallic compounds, high-entropy alloys, and metallic glasses. Further, this activation energy is also shown to be directly proportional to interstitial electronic charge density, which is a good predictor of ductility, stiffness (moduli), and phase stability in high-entropy alloys and solid metals generally. The proposed framework suggests the possibility of coupling ordering and intrinsic strength to mechanisms like dislocation nucleation, hydrogen embrittlement, and transport properties, such as through correlations between the activation energies for amorphization with stacking-fault and grain boundary energies. It additionally opens the prospect for greatly accelerated structural materials design and development to address materials challenges limiting more sustainable and efficient use of energy.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Tailoring microstructures with mild magnetic-field processing: A case study of CuNiFe alloys

Combined experimental and computational investigations of the CuNiFe spinodal system confirm that application of a mild magnetic field during thermal treatment alters elemental redistribution and the resulting microstructure, relative to that obtained from zero-field annealing. Spinodal decomposition of a Cu 40 Ni 42 Fe 18 alloy was initiated during thermal treatment at 773 K, conducted either under zero field or modest (60 mT) magnetic f ield conditions for up to 200 h. Periodic (~10 nm) chemical modulations into Cu-rich and NiFe-rich regions were observed under both conditions, with the amplitude and wavelength of the segregated regions increasing with treatment time. However, magnetic field annealing resulted in a more than twofold increase in the amplitude of elemental modulations relative to zero-field conditions – consistent with enhanced diffusional f luxes during spinodal decomposition – while the modulation wavelength remained largely unaffected. These microstructural differences are reflected in various extrinsic magnetic properties. In parallel, first-principles DFT calculations indicate that long-range ferromagnetic order, as induced by an applied magnetic field, substantially alters the strength and nature of atomic interactions, enhancing the thermodynamic instability of the CuNiFe solid solution. Collectively, these results suggest that incorporating a mild (millitesla-level) magnetic field – distinct from the strong (tesla-level) fields commonly used in prior studies – during thermal processing has the potential to deliver enhanced control of microstructures for targeted engineering outcomes.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Influence of residual chlorine on Ru/TiO 2 active sites during CO 2 methanation

Titania-supported ruthenium (Ru/TiO 2 ) is an established catalyst for the hydrogenation of carbon dioxide to methane (Sabatier reaction). Chlorine contamination, owed to the RuCl 3 precursor, is demonstrated to have a detrimental impact on methanation activity. After calcination and reduction the catalyst contains residual chlorine, shown by XPS. An aqueous ammonia wash removes Cl without leaching Ru. The washed catalysts exhibit improvements in CH 4 site-time yields. Low Ru loading catalysts encounter the greatest activity enhancements after washing (~4.5-fold). DFT calculations indicate that chlorine and CO 2 directly compete for adsorption on Ru step sites, with Cl impeding the adsorption of CO 2 at under-coordinated sites and at higher Cl coverages. H 2 -chemisorption/TPR show that Cl removal lowers the onset of low temperature H 2 dissociation on Ru. Finally, DRIFTS provide evidence that the removal of Cl facilitates low temperature dissociative binding of CO 2 , indicated by the formation of surface bound linear CO species.

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

Dual-atom Ag 2 /graphene catalyst for efficient electroreduction of CO 2 to CO

Electrochemical reduction of CO 2 into value-added carbon compounds offers a promising strategy to mitigate global warming, but present challenges for chemistry due to the poor selectivity and stability of electrocatalysts. In this work, we report a dual-atom Ag 2 /graphene catalyst featuring well-defined AgN 3 -AgN 3 active site for CO 2 electrochemical reduction. This dual-atom catalyst can drive CO 2 reduction reaction at a potential as high as -0.25 V, and exhibit excellent CO Faradic efficiency up to 93.4 % with a current density of 11.87 mA cm -2 at -0.7 V and long-term stability, far surpassing the single-atom Ag 1 /graphene and the traditional silver nanoparticle catalysts. Finally, DFT calculations reveal that the dual-atom Ag site lowers the barrier for the formation of *COOH by stabilizing the *CO 2 through the concomitant interactions with the C and an O atom of CO 2 , resulting in excellent catalytic performance.

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

HCOOH Decomposition on Sub-Nanometer Pd 6 Cluster Catalysts: The Effect of Defective Boron Nitride Supports Through First Principles

The catalytic properties of a hexagonal boron nitride- (h-BN) supported Pd 6 sub-nanometer cluster in the context of formic acid (HCOOH) decomposition were studied by means of periodic Density Functional Theory (DFT) calculations. The effect of support defectivity – boron (h-B v N) and nitrogen (h-BN v ) monovacancies – on the competition between the formate (HCOO)- and carboxyl (COOH)-mediated decomposition pathways was analyzed. Defects are responsible for charge-transfer leading to a positively or negatively charged cluster, and open new reactive channels in which vacancy-mediated dehydrogenation pathways can occur. Pd 6 cluster reconstructions, induced by the adsorption of reaction intermediates and by the presence of monovacancies in the support, greatly stabilize the formation of CO from COOH, which could drastically decrease the selectivity towards hydrogen production. Here, a simplified descriptor-based analysis, based on selected thermochemical quantities calculated on charged cluster models, suggests that Pd 6 sub-nanometer clusters supported on pristine h-BN and h-BN v can be more selective than Pd 6 supported on defective h-B v N towards HCOOH dehydrogenation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Efficient Pd on carbon catalyst for ammonium formate dehydrogenation: Effect of surface oxygen functional groups

Formate solution is one of a kind promising liquid organic hydrogen carrier but suffers from kinetic challenges. This study investigates the kinetics of the surfacefunctionalized Pd on carbon catalysts for formate dehydrogenation and the impact of O-functional groups. Here, the fraction of the distinguished O-functional groups was modulated by the different concentrated HNO 3 solutions treatment or by H 2 reduction. This study shows that the O-functional groups play critical roles in dispersing Pd nanoparticles and decreasing the activation energy for dehydrogenation. Density functional theory (DFT) calculation reveals that most O-functional groups enhance formate adsorption on the Pd active site. However, the existence of C=O groups consumes reducing agents and hinders the formation of metallic Pd. The electron transfer from Pd to oxygen functional groups is unfavorable to dehydrogenation. The as-prepared Pd5/re-ACA (reduced activated carbon washed by acid) exhibited significant activity with a higher turnover frequency of 13,511 h -1 than commercial Pd/C.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

In-situ exsolution of bimetallic CoFe nanoparticles on (La,Sr)FeO 3 perovskite: Its effect on electrocatalytic oxidative coupling of methane

This study presents in-situ reduction of lanthanum strontium cobalt ferrite (LSCF) perovskite as an effective method for modifying its surface properties and enhancing its electrocatalytic reactivity for oxidative coupling of methane (OCM). The evolution of hetero-phases during the reduction of LSCF resulted in CoFe nanoparticles being formed at the surface. The in-situ reduced LSCF cell for OCM could be operated in either an ion pump or a fuel cell mode. High selectivity of 63% and 10.2% were reported for C 2+ hydrocarbons and C 3 H 6 , respectively. DFT calculations on LSCF and CoFe revealed that the high selectivity of C 2+ hydrocarbons on the LSCF primarily stems from the presence of CoFe nanoparticles. In-situ DRIFTS conducted under CH 4 proved that complete oxidation of CH 4 can be effectively inhibited by reducing LSCF, and control of oxygen supply is an important parameter for selective conversion of CH 4 to higher order hydrocarbon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Using ethanol and isopropanol as biomass model compounds for understanding bond scission mechanisms over Cu/Mo 2 N catalysts

The conversion of biomass compounds into fuels and chemicals is an important step towards a more sustainable future. This work combines results from model surfaces and powder catalysts to demonstrate Cu-modified mo- lybdenum nitride (Cu/Mo 2 N) as a selective catalyst for dehydrogenation of the biomass model compounds, ethanol and isopropanol. Results from model surfaces showed that while Mo2N led to unselective decomposition via both dehydrogenation and dehydration, the addition of Cu increased the dehydrogenation activity and selectivity. DFT calculations showed how Cu influenced the structures of active sites, adsorbate interactions, and thus the product selectivity. Batch reactor studies on corresponding powder catalysts confirmed the trend that Cu modification increased dehydrogenation activity, and in situ X-ray absorption spectroscopy elucidated the Cu oxidation state under reaction conditions. Further, this work demonstrates a strategy for promoting dehydrogenation over Mo 2 N-based catalysts, as well as the feasibility of using model surfaces to guide the design of industrially relevant catalysts.

09 BIOMASS FUELS↗
DOE OSTI2024

Catalytic production of δ-valerolactone (DVL) from biobased 2-hydroxytetrahydropyran (HTHP) – Combined experimental and modeling study

δ-Valerolactone (DVL) is a five-carbon (C5) cyclic ester that can undergo ring-opening polymerization to yield high-performance, biocompatible polyesters. But current market prices of C5 chemicals like DVL are very high due to poor availability of C5 feedstock in petroleum. Herein, we demonstrate a novel route to DVL synthesis via dehydrogenation of biomass-derived 2-hydroxytetrahydropyran (HTHP) over Cu/SiO 2 without the use of toxic reagents. Since HTHP exists in thermal equilibrium with 3,4-dihydropyran (DHP) via dehydration, and with 2,2’-oxybis(tetrahydropyran) and 5-(tetrahydropyran-2-yloxy)pentanal via acetalization, we have also determined the thermochemistry (ΔH rxn and ΔG rxn ) of each competing reaction using density functional theory (DFT) calculations at the M06-2X/cc-pVTZ level. Finally, by developing a kinetic model of all 8 reactions involved, we have achieved 84% selectivity to DVL at 150°C in a packed bed reactor for over 72 hours of time on stream.

42 ENGINEERING↗
DOE OSTI2025

Electrosynthesis of high purity ethylene using high-index facet Cu 2 O nanocrystals electrocatalyst

Electrochemical CO 2 reduction reaction (eCO2RR) to multi-carbon (C 2+ ) products with copper-based catalysts is often limited by poor selectivity. This challenge arises from the concurrent formation of various intermediates, dictated by the atomic arrangement and electronic properties of surface atoms. In this study, we found that copper (I) oxide (Cu 2 O) nanocrystals with 50 facets (50F-NC), predominantly featuring (211) facets that offers high density of under-coordinated sites, demonstrate superior ethylene (C 2 H 4 ) selectivity of 92% ± 2 with an overall current density of 212 mA/cm 2 at -650 mV vs RHE. Furthermore, after one month of storage in a 1 M KOH electrolyte, this catalyst demonstrated a C 2 H 4 Faradaic efficiency of 87% highlighting its stabile structure under strong alkaline environments. Here, operando electrochemical Raman spectroscopy revealed enhanced CO* intermediate coverage on the 50F-NC catalyst, correlating with improved C-C coupling. SEM, TEM, and XPS analyses, along with DFT calculations, suggested that Cu sites on the (211) facet of 50F-NC and those at the Cu/Cu 2 O interface formed in-situ due to the surface reconstruction during the reaction, are likely active sites for effective C-C coupling and sustained high-rate C 2 H 4 production.

Cu nano particle↗
DOE OSTI2026

Selective oxidation of 3-hydroxypropionic acid to malonic acid over Pd/C: Mechanistic and kinetic study

Malonic acid (MA) is a high-value dicarboxylic acid with strong industrial demand, yet its current production heavily relies on petrochemical feedstocks. Here, we report the first systematic study for sustainable production of MA via oxidation of 3-hydroxypropionic acid (3-HP) with a Pd/Carbon catalyst. The effects of oxidant type (O 2 and H 2 O 2 ), pH, and temperature on the reaction chemistry were comprehensively evaluated. Guided by experimental observation and DFT-calculated thermochemical energetics, reaction networks for 3-HP oxidation with both oxidants are proposed and validated through kinetic modeling. MA was identified as the primary oxidation product, while further oxidation yields acetic acid and oxalic acid. The kinetic model validated the network, displaying excellent agreement (R 2 > 0.95). Kinetic observations also enabled a direct comparison between O 2 and H 2 O 2 and revealed their distinct behaviors. The model was further developed into a temperature-time map, providing insight into conditions that maximize MA production. Malonic acid selectivity of 56.9 % and yield of 50.5 % were achieved at 3 bar oxygen, equimolar NaOH:3-HP ratio, and 50 °C.

3-hydroxypropionic acid↗
DOE OSTI2024

Orientation-dependent structural properties during growth and growth mechanism of CoO films

The orientation-dependent local structural properties of CoO films on sapphire substrates during growth were investigated through linearly-polarized extended X-ray absorption fine structure (EXAFS) measurements. Specifically, CoO(1 1 1) and (100) crystals with a rock-salt structure (Fm3m) were epitaxially grown on alpha-Al2O3(0001) and (1012) substrates, respectively, at 700 degrees C using a radio-frequency sputtering system. The local structural properties of CoO films in the in-plane and out-of-plane orientations were quantitatively determined using linearly-polarized EXAFS at the Co K-edge during growth. The EXAFS analysis revealed that during the initial stages of growth, the local structural properties exhibit significant differences compared to thick films, with short atomic distances and large (small) Debye-Waller factors observed in the out-of-plane (in-plane) orientations. The local structural strain mostly diminished when approximately 20 CoO layers accumulated on the substrate. Density functional theory (DFT) calculations further supported these findings by confirming that cobalt atoms initially form stable bonds with the sapphire surface, leading to the simultaneous growth of oxygen and cobalt layers in a coordinated manner through layer-by-layer growth.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Site-specific surface reactivity on SnO 2 : Evaluating selective atomic layer deposition processes

Area selective atomic layer deposition (AS-ALD) is a bottom-up synthesis approach with potential for deposition with molecular level precision. Here, the site-specific hydration of metal oxide substrates, combined with surface H 2 O-selective ALD processes, provides a potentially powerful path to targeted synthesis. Density functional theory (DFT) calculations are used to predict the thermodynamics of ALD precursor reactivity and hydration for (001), (101), (110), and (100) rutile SnO 2 facets as a function of temperature. Trimethylaluminum (TMA) and dimethyl aluminum isopropoxide (DMAI) dimers are predicted to react with both dehydrated and hydrated SnO 2 (001), (101), and (110) facets at ALD-relevant temperatures, while the SnO 2 (100) facet is predicted to be uniquely unreactive with TMA and DMAI monomers as well as dehydrate near 177 °C making this facet more amenable to targeted ALD. In situ ellipsometric studies of Al 2 O 3 ALD on polycrystalline SnO 2 at 150 °C are consistent with the computational predictions of rapid and unselective nucleation, in stark contrast to inhibited and selective ALD on isostructural rutile TiO 2 .

Atomic Layer Deposition↗
DOE OSTI2025

Site-specific surface reactivity on MgO for atomic layer deposition via selective hydration

Atomic layer deposition (ALD) is a powerful technique for thin film synthesis, offering atomic-scale precision and conformality. While ALD of MgO has been widely studied for applications in energy storage and microelectronics, its potential as surface on which deposition may be selective and defects repaired remains underexplored. Here, we present a combined theoretical and experimental investigation of MgO surface hydration and its implications for targeted ALD growth using water and dimethyl aluminum isopropoxide (DMAI) as reactants. We perform density functional theory (DFT) calculations to examine molecular and dissociative H 2 O adsorption on MgO (100) terraces and step-edge sites, including pristine surfaces and those with Mg/O vacancies. Reaction Gibbs free energies are calculated under various conditions to quantify surface reactivity. Our findings reveal facet- and defect-dependent hydration behaviors that align with experimental ALD growth trends on MgO (100). This study provides a molecular-level understanding of MgO surface chemistry critical for optimizing ALD processes for thin film growth and defect repair.

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

Inverse design of two-dimensional graphene/h-BN hybrids by a regressional and conditional GAN

Design of materials with desired properties is currently laborious and heavily relies on intuition of researchers through a trial-and-error process. To tackle this challenge, in this work we propose a novel regressional and conditional generative adversarial network (RCGAN) for inverse design of representative two-dimensional materials, the graphene and boron-nitride (BN) hybrids. RCGAN incorporates a supervised regressor network, thus overcoming the common technical barrier in the traditional unsupervised GANs, which cannot generate data when fed with continuous and quantitative labels. RCGAN can autonomously generate graphene/BN hybrids given any target bandgap values. These structures are distinguished from the ones used for training and exhibit high diversity for a given bandgap. Moreover, they exhibit high fidelity, yielding bandgaps within ~10% MAE F of the desired bandgaps as validated by density functional theory (DFT) calculations. Analysis by the principle component analysis (PCA) and modified locally linear embedding (MLLE) reveals that the generator has successfully generated structures following the statistical distribution of the real structures. It implies the possibility of the RCGAN in recognizing physical rules hidden in the high-dimensional data. The novel strategy for designing regressional GAN architecture together with the successful application to inverse design of materials would inspire further exploration in research fields beyond materials.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A deep learning interatomic potential developed for atomistic simulation of carbon materials

Interatomic potentials based on neural-network machine learning method have attracted considerable attention in recent years owing to their outstanding ability to balance the accuracy and efficiency in atomistic simulations. In this work, a neural-network potential (NNP) for carbon is generated to simulate the structural properties of various carbon structures. The potential is trained using a database consisting of crystalline and liquid structures obtained by the first-principles density functional theory (DFT) calculations. The developed potential accurately predicts the energies and forces in crystalline and liquid carbon structures, the energetic stability of defected graphene, and the structures of amorphous carbon as the function of density. As a result, the excellent accuracy and transferability of the NNP provide a promising tool for accurate atomistic simulations of various carbon materials with faster speed and much lower cost.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Evolution of PTCDA-derived seeds prior to graphene nanoribbon growth on Ge(001)

The synthesis of graphene nanoribbons (GNRs) can be realized via CH4 chemical vapor deposition (CVD) on substrates such as Ge(001) that promote highly anisotropic growth kinetics. Small polycyclic aromatic hydrocarbons (PAHs) are first sublimed onto Ge near room temperature to form graphene-like seeds that subsequently initiate GNR growth with CH4 exposure at 1173 K. The behaviors of PAHs in the time in between their sublimation onto Ge and GNR growth are unclear. Here, we study an archetypical PAH, perylene-3,4,9,10-tetracarboxyl acid dianhydride (PTCDA), on Ge(001) using both scanning tunneling microscopy (STM) and density functional theory (DFT) to characterize PAH conformation, surface diffusivity, and clustering, versus temperature. PTCDA becomes mobile above 673 K (consistent with a DFT calculated diffusion barrier of 2.01 eV). The mobile PTCDA molecules meet, cluster, and fuse at Ge step edges. These clusters have an apparent height of 0.4 nm, similar to small graphene islands, and grow laterally with increasing temperature – reaching 1.2 – 2.1 nm in width at 1173 K, consistent with the seed size extrapolated from CVD experiments. These results provide a plausible picture for how PTCDA forms seeds for anisotropic GNR CVD and show that PAHs with reduced surface diffusivity and inter-molecular reactivity are needed to enable more monodisperse PAH-seeded GNR synthesis.

36 MATERIALS SCIENCE↗