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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 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Atomistic modeling of energy band alignment in CdSeTe surfaces

Atomistic modeling based on Desnity Functional Theory (DFT)- 1/2 method coupled with surface Green’s function has been employed to investigate the energy band alignment results in cadmium selenium telluride (CdSeTe) surfaces. The structural and electronic properties of the bulk ternary alloy were established before cleaving the CdSeTe low index surface facets. The dependency of atomic-scale electronic features on different plane orientations was explored by studying the energy band alignment diagrams in the unreconstructed and reconstructed surfaces. While the low index CdSeTe surface geometry reconstructions replicate the CdTe surface geometries, the energy band alignment features of the unreconstructed and reconstructed CdSeTe surfaces differ from those observed in CdTe low index surfaces. The structurally relaxed reconstructed CdSeTe surface results in purely flat bands as opposed to an internal cusp feature observed in CdTe surfaces. The presence of an internal energy cusp in CdTe(111) surfaces is expected to play a key role in enhancing the hole charge transport towards the back of CdTe-only solar cell device and the absence of such feature in CdSeTe surface may explain one of the reason for the lower performance of CdSeTe-only solar cell seen experimentally.

36 MATERIALS SCIENCE↗
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 OSTI2024

Synthesis of aviation biofuel precursors from biomass-derived ketones: Substrate adsorption configuration-catalytic activity

The production of aviation biofuel precursors from biomass-derived ketones by heterogeneous catalysis has been hindered by the low catalytic activity. Herein, a series of Cu-doped metal oxide catalysts were prepared for the conversion of biomass-derived ketones to aviation biofuel precursors. Solvent-free cyclopentanone conversion via aldol condensation reached 91.1 % over Cu/Al 2 O 3 with 100 % selectivity toward dimer and trimer oxygenated species, all of which are aviation biofuel precursors. This catalyst primarily contains Cu 2 O and Cu nanoparticles which are uniformly dispersed across the Al 2 O 3 surface. From in situ DRIFTS and DFT results, the incorporation of Cu species onto Al 2 O 3 not only increased the diversity of Lewis acidic sites, but also changed the adsorption of C = O groups, which lead to the increased aldol condensation activity of Cu/Al 2 O 3 . In conclusion, this study provides insight on the design of heterogeneous catalysts suitable for the solvent-free synthesis of aviation biofuel precursors from biomass-derived ketones.

Adsorption configuration↗
DOE OSTI2023

Thermodynamic modeling of the Nb-Ni system with uncertainty quantification using PyCalphad and ESPEI

Here, the Nb–Ni system is remodeled with uncertainty quantification (UQ) using software tools of PyCalphad and ESPEI (the Extensible, Self-optimizing Phase Equilibria Infrastructure) with the presently implemented capability of modeling site fraction based on Wyckoff positions. The five- and three-sublattice models are used to model the topologically close pack (TCP) μ-Nb 7 Ni 6 and δ-NbNi 3 phases according to their Wyckoff positions. The inputs for CALPHAD-based thermodynamic modeling include the thermochemical data as a function of temperature predicted by first-principles and phonon calculations based on density functional theory (DFT), ab initio molecular dynamics (AIMD) simulations, together with phase equilibrium and site fraction data in the literature. In addition to phase diagram and thermodynamic properties, the CALPHAD-based predictions of site fractions of Nb in μ-Nb 7 Ni 6 agree well with experimental data. Furthermore, the UQ estimation using the Markov Chain Monte Carlo (MCMC) method as implemented in ESPEI is applied to study the uncertainty of site fraction in μ-Nb 7 Ni 6 and enthalpy of mixing (ΔH mix ) in liquid.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Exploring the role of electronic structure on photo-catalytic behavior of carbon-nitride polymorphs

A fully self-consistent density-functional theory (DFT) with improved functionals is used herein to provide a comprehensive account of structural, electronic, and optical properties of C 3 N 4 polymorphs. Using our recently developed van Leeuwen-Baerends (vLB) corrected local-density approximation (LDA), we implemented LDA + vLB within full-potential N th -order muffin-tin orbital (FP-NMTO) method and show that it improves structural properties and band gaps compared to semi-local functionals (LDA/GGA). We demonstrate that the LDA + vLB predicts band-structure and work-function for well-studied 2D-graphene and bulk-Si in very good agreement with experiments, and more exact hybrid functional (HSE) calculations as implemented in the Quantum-Espresso (QE) package. The structural and electronic-structure (band gap) properties of C 3 N 4 polymorphs calculated using FP-NMTO-LDA + vLB is compared with more sophisticated hybrid-functional calculations. We also perform detailed investigation of photocatalytic behavior using QE-HSE method of C 3 N 4 polymorphs through work-function, band (valence and conduction) position with respect to water reduction and oxidation potential. Our results show $γ$-C 3 N 4 as the best candidate for photocatalysis among all the C 3 N 4 polymorphs but it is dynamically unstable at ‘zero’ pressure. We show that $γ$-C 3 N 4 can be stabilized under hydrostatic-pressure, which improves its photocatalytic behavior relative to water reduction and oxidation potentials.

36 MATERIALS SCIENCE↗
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

Resonant Raman in armchair graphene nanoribbons from first-principles

Resonant Raman spectra of armchair graphene nanoribbons (AGNRs) are computed using Density Functional Theory (DFT) and third-order perturbation theory. Results are benchmarked against available experimental data and compared to previously used theoretical approaches based on the Placzek approximation. Comparable agreement with experiments is found for both previously and presently used methods. In addition, a numerical analysis is carried out to provide a justification for the resonant modeling method based on the use of the frequency-dependent dielectric tensor in the Placzek approximation. Finally, this work also provides additional predictions and references for wide AGNRs that might be investigated with Raman scattering experiments in the future.

42 ENGINEERING↗
DOE OSTI2024

Molecular origin of viscoelasticity and influence of methylation in mesophase pitch

The viscoelastic and thermomechanical properties of pitches are responsible for their melt-spinning behavior, which is a critical step for manufacturing high-performance pitch-based carbon fibers. Here, we systematically explore the impact of methyl group modifications on the viscoelastic and thermal properties of mesophase pitches. We employ a range of atomistic modeling approaches, including Density Functional Theory (DFT), Density Functional Tight Binding (DFTB), and Classical Molecular Mechanics (MM), to provide detailed insights into the molecular interactions and structural changes. Further, our results revealed the molecular mechanisms that promote layered structures leading to the anisotropic nature of the viscoelastic behavior of mesophase pitch. Furthermore, we propose a modified molecular representation of naphthalene-based mesophase pitch based on the analysis of x-ray diffraction measurements. This study provides fundamental insights into the molecular structures of mesophase pitch and the role of methyl groups controlling its viscosity, which offer valuable insights into mesophase-based carbon fiber production.

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

Molecular simulation using transfer-learned potentials for the disordered nanoscale structure of nitrogen-doped nanoporous carbons

Machine learning (ML)-based molecular dynamics (MD) simulations of the formation of a class of N-doped nanoporous carbons are performed to assess their disordered partially graphitized nanoscale structure. The study is motivated by the effectiveness of so-called nitrogen assembly carbons (NACs) for catalysis applications. Benchmark simulations for pure-C disordered graphitic systems reveal the importance of reliably capturing the vdW component of the potentials in order to accurately describe the tendency for layering of disordered graphene-like sheets. In our modeling, this is achieved by a transfer learning strategy incorporating features of the energetics from the optB88-vdW DFT functional into potentials initially trained with a less expensive functional, thereby providing a superior description of the pure-C systems. Generation from MD simulations of realistic partially graphitized structures is significantly more challenging for N-doped versus for pure C systems. However, such structures are achieved by a tailored MD simulation protocol mimicking the experimental synthesis process and in particular incorporating an annealing and subsequent quenching stages. Simulated PXRD patterns effectively reproduce the features of experimental observations for NACs, including the appearance of a prominent but broad (002) peak at around 25, and the development of another weaker feature associated with in-layer ordering of mixed C-N graphene-like sheets.

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

Strain dependent electronic and optical responses of penta-BCN monolayer

We report here, structural, dynamic, and mechanical stability in pentagonal boron carbon nitride (p-BCN) monolayer, a new member of direct bandgap two-dimensional (2D) semiconductor. The identified visible range bandgap with excellent mechanical strength allows it to be a promising candidate material in optoelectronics, nanomechanics, and optomechanical sensors. By employing density functional theory (DFT), we reveal a unique geometrical reconstruction with rigidity in B–N and C–N bond lengths with applied strain. These quasi-sp 3 hybridized short and strong covalent bonding and unique geometry support the monolayer to possess extraordinary mechanical response. The desired bandgap is manipulated by loading the biaxial strain. Most importantly, our predictions on p-BCN show excellent optical response such as good static dielectric constant and refractive index, strong optical absorption (up to 1.08 x 10 5 cm -1 in VR and 7.01 x 10 cm -1 in UV) with small energy loss and reflectance both appearing in visible and ultraviolet regions (UV). The desired optical response along with the blue and red shift is demonstrated by tailoring with tensile and compressive strain. The predicted strong optical anisotropy provides it’s application in polarized photodetection.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Simulation of multi-shell fullerenes using Machine-Learning Gaussian Approximation Potential

Multi-shell fullerenes ”buckyonions ” were simulated, starting from initially random configurations, using a density-functional-theory (DFT)-trained machine-learning carbon potential within the Gaussian Approximation Potential (GAP) Framework [Volker L. Deringer and Gábor Csányi, Phys. Rev. B 95, 094203 (2017)]. Fullerenes formed from seven different system sizes, ranging from 60 ~ 3774 atoms, were considered. The buckyonions are formed by clustering and layering starting from the outermost shell and proceeding inward. Inter-shell cohesion is partly due to interaction between delocalized π electrons protruding into the gallery. The energies of the models were validated ex post facto using density functional codes, VASP and SIESTA , revealing an energy difference within the range of 0.02 - 0.08 eV/atom after conjugate gradient energy convergence of the models was achieved with both methods.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Discovery of single-atom alloy catalysts for CO 2 -to-methanol reaction by density functional theory calculations

The transformations of CO 2 molecules into valuable products are of increasing interest due to the negative impact of anthropogenic CO 2 emissions on global warming. The CO 2 -to-methanol hydrogenation is an economically profitable reaction of carbon fixation, but it still steps away from widespread industrialization because of the lack of efficient and selective catalysts. Recently, single-atom alloy (SAA) catalysts have been developed to work remarkably in CO 2 hydrogenation reactions. Doping isolated single atoms into metallic catalyst can dramatically alter the catalytic performance of the host. Here, we have performed a screening discovery on Ru and 6 RuX (X = Fe, Co, Ni, Cu, Ir and Pt) SAAs using density functional theory (DFT) computations. We considered 13 possible elementary reactions in 4 possible reaction pathways on Ru and all RuX surfaces. In the computed mechanisms, we found that the formation of *H 2 COOH and *HCOO intermediates plays a critical role in determining catalysts’ activities. Doping Co and Pt isolated single atoms into Ru surface can thermodynamically and kinetically facilitate these intermediates formation processes, eventually promoting the production of methanol. The combination of weak binding and enhanced charge redistribution on RuCo and RuPt surfaces give them improved catalytic activities over pure Ru. This work will ultimately facilitate the discovery and development of SAAs for CO 2 to methanol, serving as guidance to experiments and theoreticians alike.

25 ENERGY STORAGE↗
DOE OSTI2020

First-principle investigation on catalytic hydrogenation of benzaldehyde over Pt-group metals

We report that understanding the hydrogenation of organic compounds in the aqueous phase has always been fundamentally important for improving carbon neutral pathways to fuels and value-added chemicals. In this study, we investigated both thermodynamic and kinetic profiles of benzaldehyde hydrogenation over the Pd(111) and Pt(111) metal surfaces using density functional theory (DFT) and ab initio molecular dynamic (AIMD) simulations. The adsorption of H 2 shows the mixed preference of H adsorption sites on the Pt(111), while the fcc adsorption site is dominant for H on the Pd(111). When benzaldehyde is added to the systems, we observe a strong reduction of benzaldehyde on charged Pd (111) surface compared with that on neutral surface. In contrast, charged state of the Pt(111) surface does not change their interaction. Subsequent hydrogenation reaction of benzaldehyde over Pd(111), proceeding via Langmuir-Hinshelwood mechanism, is affected by two major factors: the presence of H 2 O solvent and surface charge. The presence of H 2 O solvent greatly reduces the activation energy of C-H and O-H bond formation during the hydrogenation process. Furthermore, the hydrogenation step via C-H bond formation is preferred thermodynamically and kinetically over O-H bond formation during thermocatalytic hydrogenation, while the opposite trend holds true during electrocatalytic hydrogenation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Revealing the interplay between “intelligent behavior” and surface reconstruction of non-precious metal doped SrTiO 3 catalysts during methane combustion

The impact of surface reconstruction of a model perovskite, SrTiO 3 (STO), on CH 4 activation for combustion and oxidative coupling was previously revealed that the reaction rate was proportional to the creation of Srterminated step sites. Doped perovskites (SrTi 1-x M x O 3 , M=metal dopant) present yet another form of reconstruction throughout the surface and the bulk, where the metal dopant can migrate in and out of the perovskite lattice, also known as "intelligent behavior". In this work, understanding the interplay between perovskite surface reconstruction (surface termination) and the "intelligent behavior" is tackled for the first time, and the catalytic consequences are probed with CH 4 combustion as a model reaction. A set of experimental techniques, including XRD, Raman spectroscopy, X-ray adsorption spectroscopy, kinetic measurements, as well as DFT calculations were used to understand the catalytic behavior of the reconstructed surfaces of Ni and Cu-doped STO for methane combustion. Here, we found that during methane oxidation, the diffusion of Ni and Cu into the lattice due to the "intelligent behavior" is accompanied by Sr enrichment on the surface of the perovskite. This Srenrichment process is reversible when Cu or Ni species exsolute as clusters/nanoparticles upon H 2 treatment. Such a surface reconstruction is found to greatly impact the catalytic activity of doped perovskites towards methane combustion.

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

Molecular structure models of amorphous bismuth and cerium carboxylate catalyst precursors

As our societal need for materials and energy has grown, so has our need for catalyst processes in hydrogen production. A major function in these applications, for both homogenous and heterogeneous catalysis processes, is the synthesis of an active metal catalyst. It must first be soluble to control the physical properties of the metal being used. Recent work in metal precursors has begun to turn toward these metal carboxylate types of material. Here, structural models are proposed for bismuth 2-ethylhexanoate and 2,2-dimethyloctanoate and cerium 2-ethylhexanoate. The bismuth compounds have been characterized at different ratios of bismuth to carboxylate as solutions of the free acids. Their structures are most consistent with a Bi 4 (RCO 2 ) 12 motif where the Bi ions are arranged in a flattened tetrahedron with Bi – Bi distances of about 4.3 Å. There is evidence for Bi – O – Bi linkages at low free acid concentrations. The cerium compound is most consistent with a linear tetracerium molecule where the Ce – Ce distances repeat at about 4.3 Å out to 16.4 Å. The models were generated by analogy with known crystal structures and compared to high-energy x-ray scattering data. To further evaluate the models, DFT calculations were made, and the equilibrium geometries were compared. The vibrational spectra calculated from those geometries are presented and compared to the experimental results. Magnetization vs. temperature data was collected on the cerium compound, and its behavior was consistent with the proposed model. A geometrical approach to determining the dimensionality and relative positions of the metal ions in these structures is presented.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗