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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Predictive Model of Charge Mobilities in Organic Semiconductor Small Molecules with Force-Matched Potentials

Charge mobility of crystalline organic semiconductors (OSC) is limited by local dynamic disorder. Recently, the charge mobility for several high mobility OSCs, including TIPS-pentacene, were accurately predicted from a density functional theory (DFT) simulation constrained by the crystal structure and the inelastic neutron scattering spectrum, which provide direct measures of the structure and the dynamic disorder in the length scale and energy range of interest. However, the computational expense required for calculating all of the atomic and molecular forces is prohibitive. In this work, we demonstrate the use of density functional tight binding (DFTB), a semiempirical quantum mechanical method that is 2 to 3 orders of magnitude more efficient than DFT. We show that force matching a many-body interaction potential to DFT derived forces yields highly accurate DFTB models capable of reproducing the low-frequency intricacies of experimental inelastic neutron scattering (INS) spectra and accurately predicting charge mobility. We subsequently predicted charge mobilities from our DFTB model of a number of previously unstudied structural analogues to TIPS-pentacene using dynamic disorder from DFTB and transient localization theory. The approach we establish here could provide a truly rapid simulation pathway for accurate materials properties prediction, in our vision applied to new OSCs with tailored properties.

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

Method for accurately predicting solvation structure

Accurately predicting the molecular structure of solutions is a fundamental scientific challenge. Using quantum mechanical density functional theory (DFT) to make these predictions is hindered by significant variation depending on which DFT functional is used. Here, we present a simple metric that can determine the reliability of a DFT functional for predicting solvation structure. We then show that including a simple interaction term to correct this metric leads to quantitative agreement with experimental measurements of liquid structure. We demonstrate the utility of this method by using it to accurately describe the hydration structure around the Na+ a

basis sets, molecular structure, cluster chemistry↗
DOE OSTI2021

Phase Equilibrium of Water with Hexagonal and Cubic Ice Using the SCAN Functional

Machine learning models are rapidly becoming widely used to simulate complex physicochemical phenomena with ab initio accuracy. Here, we use one such model as well as direct density functional theory (DFT) calculations to investigate the phase equilibrium of water, hexagonal ice (Ih), and cubic ice (Ic), with an eye toward studying ice nucleation. The machine learning model is based on deep neural networks and has been trained on DFT data obtained using the SCAN exchange and correlation functional. We use this model to drive enhanced sampling simulations aimed at calculating a number of complex properties that are out of reach of DFT-driven simulations and then employ an appropriate reweighting procedure to compute the corresponding properties for the SCAN functional. This approach allows us to calculate the melting temperature of both ice polymorphs, the driving force for nucleation, the heat of fusion, the densities at the melting temperature, the relative stability of ices Ih and Ic, and other properties. We find a correct qualitative prediction of all properties of interest. In some cases, quantitative agreement with experiment is better than for state-of-the-art semiempirical potentials for water. Furthermore, our results also show that SCAN correctly predicts that ice Ih is more stable than ice Ic.

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

Force-Free Identification of Minimum-Energy Pathways and Transition States for Stochastic Electronic Structure Theories

Here, the accurate mapping of potential energy surfaces (PESs) is crucial to our understanding of the numerous physical and chemical processes mediated by atomic rearrangements, such as conformational changes and chemical reactions, and the thermodynamic and kinetic feasibility of these processes. Stochastic electronic structure theories, e.g., Quantum Monte Carlo (QMC) methods, enable highly accurate total energy calculations that in principle can be used to construct the PES. However, their stochastic nature poses a challenge to the computation and use of forces and Hessians, which are typically required in algorithms for minimum-energy pathway (MEP) and transition state (TS) identification, such as the nudged elastic band (NEB) algorithm and its climbing image formulation. Here, we present strategies that utilize the surrogate Hessian line-search method, previously developed for QMC structural optimization, to efficiently identify MEP and TS structures without requiring force calculations at the level of the stochastic electronic structure theory. By modifying the surrogate Hessian algorithm to operate in path-orthogonal subspaces and at saddle points, we show that it is possible to identify MEPs and TSs by using a force-free QMC approach. We demonstrate these strategies via two examples, the inversion of the ammonia (NH 3 ) molecule and the nucleophilic substitution (S N 2) reaction F – + CH 3 F → FCH 3 + F – . We validate our results using Density Functional Theory (DFT)- and Coupled Cluster (CCSD, CCSD(T))-based NEB calculations. We then introduce a hybrid DFT-QMC approach to compute thermodynamic and kinetic quantities, free energy differences, rate constants, and equilibrium constants that incorporates stochastically optimized structures and their energies, and show that this scheme improves upon DFT accuracy. Our methods generalize straightforwardly to other systems and other high-accuracy theories that similarly face challenges computing energy gradients, paving the way for highly accurate PES mapping, transition state determination, and thermodynamic and kinetic calculations at significantly reduced computational expense.

Iyer, Gopal R.↗
DOE OSTI2024

Systematic Improvement of Quantum Monte Carlo Calculations in Transition Metal Oxides: sCI-Driven Wavefunction Optimization for Reliable Band Gap Prediction

Accurate determination of the electronic properties of correlated oxides remains a significant challenge for computational theory. Traditional Hubbard-corrected density functional theory (DFT+U) frequently encounters limitations in precisely capturing electron correlation, particularly in predicting band gaps. We introduce a systematic methodology to enhance the accuracy of diffusion Monte Carlo (DMC) simulations for both ground and excited states, focusing on LiCoO 2 as a case study. By employing a selected configuration interaction (sCI) approach, we demonstrate the capability to optimize wavefunctions beyond the constraints of single-reference DFT+U trial wavefunctions. Here, we show that the sCI framework enables accurate prediction of band gaps in LiCoO 2 , closely aligning with experimental values and substantially improving traditional computational methods. The study uncovers a nuanced mixed state of t 2g and e g orbitals at the band edges that is not captured by conventional single-reference methods, further elucidating the limitations of PBE+U in describing d-d excitations. Our findings advocate for the adoption of beyond-DFT methodologies, such as sCI, to capture the essential physics of excited-state wavefunctions in strongly correlated materials. The improved accuracy in band gap predictions and the ability to generate more reliable trial wavefunctions for DMC calculations underscore the potential of this approach for broader applications in the study of correlated oxides. This work not only provides a pathway for more accurate simulations of electronic structures in complex materials but also suggests a framework for future investigations of the excited states of other challenging systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Transfer Learning Meets Embedded Correlated Wavefunction Theory for Chemically Accurate Molecular Simulations: Application to Calcium Carbonate Ion Pairing

Achieving chemical accuracy for molecular simulations remains a central challenge in computational chemistry. Here, we present an embedded correlated wavefunction transfer learning (ECW-TL) framework for accurately simulating molecular dynamics in the condensed phase. ECW-TL incorporates high-level electron exchange and correlation effects in ECW theory while preserving the training and computational efficiency of machine-learned interatomic potentials. We demonstrate the framework on Ca 2+ –CO 3 2– ion pairing in aqueous solution, a key process underlying CO 2 mineralization in seawater. As proof of principle, we first show that fine-tuning a DFT-revPBE-D3(BJ) baseline model with embedded-DFT-SCAN data reproduces the DFT-SCAN free-energy surface within 1 kcal/mol across all solvation states. Extending the framework to embedded MP2 and localized natural-orbital CCSD(T) further refines the free-energy profile, revealing the crucial role of exact electron exchange and correlation in determining ion-pair stability and structure. The computed ion-pair association free energy is in quantitative agreement with experimental measurements, further validating the accuracy of the ECW-TL framework. ECW-TL thus provides a general, data-efficient route for transferring CW accuracy to efficient simulations of complex aqueous and interfacial chemical processes.

cluster chemistry↗
DOE OSTI2020

Robust, Accurate, and Efficient: Quantum Embedding Using the Huzinaga Level-Shift Projection Operator for Complex Systems

Using wave function (WF) in density functional theory (DFT) embedding methods provides a framework for performing localized, high-accuracy WF calculations on a system, while not incurring the full computational cost of the WF calculation on the full system. To effectively partition a system into localized WF and DFT subsystems, we utilize the Huzinaga level-shift projection operator within an absolutely localized basis. In this work, we study the ability of the absolutely localized Huzinaga level-shift projection operator method to study complex WF and DFT partitions, including partitions between multiple covalent bonds, a double bond, and transition-metal–ligand bonds. We find that our methodology can accurately describe all of these complex partitions. Additionally, we study the robustness of this method with respect to the WF method, specifically where the embedded systems were described using a multiconfigurational WF method. We found that the method is systematically improvable with respect to both the number of atoms in the WF region and the size of the basis set used, with energy errors less than 1 kcal/mol. Additionally, we calculated the adsorption energy of H2 to a model of an iron metal–organic framework (Fe-MOF-74) to within 1 kcal/mol compared to CASPT2 calculations performed on the full model while incurring only a small fraction of the full computational cost. In conclusion, this work demonstrates that the absolutely localized Huzinaga level-shift projection operator method is applicable to very complex systems with difficult electronic structures.

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

Phonon Spectroscopy in Antimony and Tellurium Oxides

α-Sb 2 O 3 (senarmontite), β-Sb 2 O 3 (valentinite), and α-TeO 2 (paratellurite) are compounds with pronounced stereochemically active Sb and Te lone pairs. The vibrational and lattice properties of each have been previously studied but often lead to incomplete or unreliable results due to modes being inactive in infrared or Raman spectroscopy. Here in this paper, we present a study of the relationship between bonding and lattice dynamics of these compounds. Mössbauer spectroscopy is used to study the structure of Sb in α-Sb 2 O 3 and β-Sb 2 O 3 , whereas the vibrational modes of Sb and Te for each oxide are investigated using nuclear inelastic scattering, and further information on O vibrational modes is obtained using inelastic neutron scattering. Additionally, vibrational frequencies obtained by density functional theory (DFT) calculations are compared with experimental results in order to assess the validity of the utilized functional. Good agreement was found between DFT-calculated and experimental density of phonon states with a 7% scaling factor. The Sb–O–Sb wagging mode of α-Sb 2 O 3 whose frequency was not clear in most previous studies is experimentally observed for the first time at ~340 cm -1 . Softer lattice vibrational modes occur in orthorhombic β-Sb 2 O 3 compared to cubic α-Sb 2 O 3 , indicating that the antimony bonds are weakened upon transforming from the molecular α phase to the layer-chained β structure. The resulting vibrational entropy increase of 0.45 ± 0.1 kB/Sb 2 O 3 at 880 K accounts for about half of the α–β transition entropy. The comparison of experimental and theoretical approaches presented here provides a detailed picture of the lattice dynamics in these oxides beyond the zone center and shows that the accuracy of DFT is sufficient for future calculations of similar material structures.

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

Dinuclear Complexes of Uranyl, Neptunyl, and Plutonyl: Structures and Oxidation States Revealed by Experiment and Theory

Dinuclear perchlorate complexes of uranium, neptunium, and plutonium were characterized by reactivity and DFT, with results revealing structures containing pentavalent, hexavalent, and heptavalent actinyls, and actinyl-actinyl interactions (AAIs). Electrospray ionization produced native complexes [(AnO 2 ) 2 (ClO 4 ) 3 ] - for An:An = U:U, Np:Np, Pu:Pu, and Np:Pu, which are intuitively formulated as actinyl(V) perchlorates. However, DFT identified lower-energy structures [(AnO 2 )(AnO 3 )(ClO 4 ) 2 (ClO 3 )] - comprising a perchlorate fragmented to ClO 3 , actinyl(VI) cation An VI O 2 2+ , and neutral AnO 3 . For U:U and Np:Np, and Np in Np:Pu, the coordinated AnO 3 is calculated as actinyl(VI) with an equatorial oxo, [O yl =An VI =O yl ][=O eq ], whereas for Pu:Pu, it is plutonyl(V) oxyl, [O yl =Pu V =O yl ][-O eq • ]. The implied lower stability of Pu VI versus Np VI indicates weaker Pu=O eq versus Np=O eq bonding. Adsorption of O 2 by the U:U complex suggests oxidation of U V to U VI , corroborating the assignment of perchlorate [(An V O 2 ) 2 (ClO 4 ) 3 ] - . DFT predicts the O 2 adducts are [(An VI O 2 )(O 2 )(An VI O 2 )(ClO 4 ) 3 ] - with actinyls oxidized from +V to +VI by bridging peroxide, O 2 2- . In accordance with reactivity, O 2- addition is computed as substantially exothermic for U:U and least favorable for Pu:Pu. Collision-induced dissociation of native complexes eliminated ClO 2 to yield [(AnO 2 )(O) 2 (AnO 2 )(ClO 4 ) 2 ] - , in which fragmented O atoms bridge as oxyl O -• and oxo O 2- to yield uranyl(VI) and plutonyl(VI), or as oxos O 2- to yield neptunyl(VII), [O yl =Np VII =O yl ] 3+ .

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

Influence of substituents on the vectorial difference static dipole upon excitation in synthetic bacteriochlorins

Organic dye aggregates have been shown to exhibit exciton delocalization in natural and synthetic systems. Such dye aggregates show promise in the emerging area of quantum information science (QIS). We believe that the difference static dipole (Δd) is an essential dye parameter in the development of molecular QIS systems. However, a foundational understanding of the structural factors influencing Δd remains elusive. Bacteriochlorins play a vital role in photosynthesis due to their exceptional photophysical properties. Therefore, bacteriochlorins are particularly suitable dyes for the construction of aggregate systems for QIS. Synthetic bacteriochlorins further offer stability and tunability via chemical modifications. Here, the influence of substituents on the Δd of monomeric (non-aggregated) dyes was investigated via density functional theory (DFT) and time-dependent (TD-)DFT in a set of 5-methoxybacteriochlorins progressively substituted with ethynyl, phenyl, and phenylethynyl substituents at the 3,13- and 3,13,15-positions of the macrocycle. Symmetrically substituted 5-methoxybacteriochlorins were shown to have the largest Δd. The increase in Δd in the series of dyes was largely due to changes in orientation of the static dipole upon excitation rather than large changes in magnitude. In addition, the transition dipole (μ) and the angle between Δd and μ (ζ) were calculated. Three 5-methoxybacteriochlorins with high predicted Δd and μ were synthesized and characterized spectroscopically. The trend in Δd values empirically determined using the solvatochromic Stokes shift method was comparable with the DFT calculations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Structural Changes in Metal Chalcogenide Nanoclusters Associated with Single Heteroatom Incorporation

Atomically precise nanoclusters (NCs) are promising building blocks for designing materials and interfaces with unique properties. By incorporating heteroatoms into the core, the electronic and magnetic properties of NCs can be precisely tuned. To accurately predict these properties, density functional theory (DFT) is often employed, making the rigorous benchmarking of DFT results particularly important. In this study, we present a benchmarking approach based on metal chalcogenide NCs as a model system. We synthesized a series of bimetallic, iron-cobalt chalcogenide NCs [Co 6-x Fe x S 8 (PEt 3 ) 6 ] + (x = 0-6) (PEt = triethyl phosphine) and investigated the effect of heteroatoms in the octahedral metal chalcogenide core on their size and electronic properties. Using ion mobility-mass spectrometry (IM-MS), we observed a gradual increase in the collision cross section (CCS) with an increase in the number of Fe atoms in the core. DFT calculations combined with trajectory method CCS simulations successfully reproduced this trend, revealing that the increase in cluster size is primarily due to changes in metal-ligand bond lengths, while the electronic properties of the core remain largely unchanged. Moreover, this method allowed us to exclude certain multiplicity states of the NCs, as their CCS values were significantly different from those predicted for the lowest-energy structures. Here, this study demonstrates that gas-phase IM-MS is a powerful technique for detecting subtle size differences in atomically precise NCs, which are often challenging to observe using conventional NC characterization methods. Accurate CCS measurements are established as a benchmark for comparison with theoretical calculations. The excellent correspondence between experimental data and theoretical predictions establishes a robust foundation for investigating structural changes of transition metal NCs of interest to a broad range of applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Ensemble Effects on Hydroxide Bond Dissociation Free Energies in Polyoxovanadate Clusters

Understanding structure-property relationships is foundational to numerous modern chemistries, such as proton-coupled electron transfer (PCET). However, an experimentally measured property is the result of the behavior from an ensemble of molecules. Neglecting ensemble effects, especially under complex chemical environments, may obfuscate these relationships and lead to discrepancies between theory and experiment. In this work, we demonstrate the impact of configurational entropy and local chemical environments on hydroxide bond dissociation free energies [BDFE- (O−H)] for a set of polyoxovanadate nanoclusters, at ambient conditions. The O−H bond strengths are investigated via density functional theory (DFT) coupled with statistical thermodynamic analysis and bilinear modeling, and compared with previous experimental results on the same systems, namely electrochemical solutions of: [V 6 O 13−x (OH) x (TRIOL R ) 2 ] −2 (x = 2, 4, 6; R = NO 2 , Me) and [V 6 O 11−x (OMe) 2 (OH) x (TRIOL NO 2 ) 2 ] −2 (x = 2, 4). Interestingly, we find that ensemble effects, even at room temperature, can account for a significant portion of the BDFE(O−H) trend with the degree of reduction via H atom binding, which cannot be fully captured by single-structure, static DFT calculations. Moreover, we find that the ensemble effects may be replicated statistically, requiring only enumeration of energetically accessible H-binding sites. With the ensemble effects resolved, we present a simple bilinear model to reconcile remaining biases between experiment and ensemble-informed theory, which corelate with clusterspecific electronic environment differences. The bilinear model achieves outstanding accuracy vs experiments with a root-mean squared error of 0.4 kcal/mol. Finally, based on the physicochemical characteristics of hydrogen interaction with polyoxometalates, we present a simple methodology that captures the BDFE(O−H) trend while dramatically reducing required DFT calculations by 98% and achieving accuracy within 1 kcal/mol. Overall, this work elucidates the roles and structural origins of configurational entropy and chemical effects on polyoxometalate hydroxide bond energies, with potential applicability to various atomically precise metal oxide systems. Importantly, it introduces models for rapid and highly accurate property calculations in connection with experiments.

Cluster chemistry↗
DOE OSTI2021

Using Neural Network Force Fields to Ascertain the Quality of Ab Initio Simulations of Liquid Water

Accurately simulating the properties of bulk water, despite the apparent simplicity of the molecule, is still a challenge. In order to fully understand and reproduce its complex phase diagram, it is necessary to perform simulations at the ab initio level, including quantum mechanical effects both for electrons and nuclei. This comes at a high computational cost, given that the structural and dynamical properties tend to require long timescales and large simulation cells. In this work, we evaluate the errors that density functional theory (DFT)-based simulations routinely incur into due time- and size-scale limitations. These errors are evaluated using neural-network-trained force fields that are accurate at the level of DFT methods. We compare different exchange and correlation potentials for properties of bulk water that require large timescales. Here we show that structural properties are less dependent on the system size and that dynamical properties such as the diffusion coefficient have a strong dependence on the simulation size and timescale. Our results facilitate comparisons of DFT-based simulation results with experiments and offer a path to discriminate between model and convergence errors in these simulations.

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

Accurate Force Field for Carbon Dioxide–Silica Interactions Based on Density Functional Theory

Fluid–silica interfaces are ubiquitous in chemistry, occurring in both natural geochemical environments and practical applications ranging from separations to catalysis. Simulations of these interfaces have been, and continue to be, a significant avenue for understanding their behavior. A constraining factor, however, is the availability of accurate force fields. Most simulations use traditional “mixing rules” to determine nonbonded dispersion interactions, an approach that has not been critically examined. Here, in this study, we present Lennard-Jones parameters for the interaction of carbon dioxide with silica interfaces that are optimized to reproduce density functional theory (DFT)-based binding energies. The modeling is based on the recently developed silica-DDEC force field, whose atomic charges are consistent with DFT calculations. Standard mixing rules are found to predict weaker CO 2 binding to silica than that obtained from DFT, an effect corrected by the optimized parameters given here. This behavior extends to other silica force fields (Clayff and Gulmen-Thompson), and the present Lennard-Jones parameters improve their performance as well. The effects of improved Lennard-Jones parameters on the structural and dynamical properties of condensed CO 2 in silica slit pores are also examined.

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

Modeling the Behavior of Complex Aqueous Electrolytes Using Machine Learning Interatomic Potentials: The Case of Sodium Sulfate

Understanding the structure and thermodynamics of solvated ions is essential for advancing applications in electrochemistry, water treatment, and energy storage. While ab initio molecular dynamics methods are highly accurate, they are limited by short accessible time and length scales whereas classical force fields struggle with accuracy. Herein, we explore the structure and thermodynamics of complex monovalent-divalent ion pairs using Na 2 SO 4 (aq) as a case study by applying a machine learning interatomic potential (MLIP) trained on density functional theory (DFT) data. Our MLIP-based approach reproduces key bulk properties such as density and radial distribution functions of water. We provide the hydration structure of the sodium and sulfate ions in the 0.1–2 M concentration range and the one-dimensional and two-dimensional potentials of mean force for the sodium–sulfate ion pairing at the low concentration limit (0.1 M), which are inaccessible to DFT. At low concentrations, the sulfate ion is strongly solvated, leading to the stabilization of solvent-separated ion pairs over contact ion pairs. Minimum energy pathway analysis revealed that coordinating two sodium ions with a sulfate ion is a multistep process whereby the sodium ions coordinate to the sulfate ion sequentially. Finally, we demonstrate that MLIPs allow the study of solvated ions beyond simple monovalent pairs with DFT-level accuracy in their low concentration limit (0.1 M) via statistically converged properties from ns-long simulations.

anions↗
DOE OSTI2020

Effect of TiO x Substrate Interactions on the Electrocatalytic Oxygen Reduction Reaction at Au Nanoparticles

Here, we report a robust model for studying electrocatalytic reactions at metal nanoparticles (NPs) in contact with metal oxide surfaces. The metal oxide layer (TiO x ) is prepared by atomic layer deposition, and it is sufficiently thin that it does not hinder electron transfer from the underlying conductive electrode to the supported AuNP electrocatalysts. In advance of the experiments, density functional theory (DFT) predicted that direct contact between AuNPs and TiO x would lead to enhanced activity for the oxygen reduction reaction (ORR). DFT attributes the observed ORR enhancement to partial charge transfer from oxygen vacancies within the TiO x film to the supported AuNPs and hence formation of anionic Au species. The experimental findings are in near quantitative agreement with the DFT results. Specifically, compared to isolated AuNPs, decreases of ~ 100 and ~ 50 mV in the ORR onset potential are observed experimentally for AuNPs supported on TiO 1.9 and TiO 2.0 films, respectively.

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

In Situ Studies of Methanol Decomposition Over Cu(111) and Cu2O/Cu(111): Effects of Reactant Pressure, Surface Morphology, and Hot Spots of Active Sites

The dissociative adsorption of methanol was investigated on Cu(111) and ultrathin Cu 2 O films. We employed synchrotron-based Ambient Pressure X-ray Photoelectron Spectroscopy (AP-XPS) and Scanning Tunneling Microscopy (STM) to study the dynamics of gas–solid interactions, and calculations based on Density Functional Theory (DFT) were used to examine the reaction path. C 1s XPS spectra revealed that methanol underwent dissociative adsorption on plain Cu(111) to form methoxy (CH 3 O), formaldehyde (H 2 CO), and formate (HCOO) at a pressure range of 0.5–10 mTorr, with these species remaining on the surface after evacuation. This was accompanied by the appearance of a low coverage (~0.05 ML) of O ads in the O 1s which can be considered a highly active site for methanol activation. The high activity is apparent by a coverage of 0.8 ML of methoxy at room temperature. STM was unable to image these species at room temperature as they were highly mobile on metallic copper. In contrast, for CH 3 OH on Cu 2 O/Cu(111), STM showed clear hot spots for reaction and a complex array of adsorption structures. On the oxide substrate, there was decomposition of methanol to H 2 CO, CH 3 O, HCOO, and hydrocarbon species (CH x ) due to the subsequent interactions of methanol with lattice oxygen. Cu(111) remained entirely saturated with decomposition products under 10 mTorr of methanol (θ ≈ 0.97 ML), whereas the Cu 2 O overlayer was saturated at a much lower coverage (θ ≈ 0.30 ML). STM revealed rows and step edges of Cu 2 O decorated with decomposition products and metallic Cu islands ~5 nm in size. The difference in activity between Cu(111) and Cu 2 O/Cu(111) is attributed to the significant amount of O present on the oxide surface. Additionally, Density Functional theory (DFT) calculations described the XPS measurements well, showing a likely methanol dissociation to *CH 3 O and therefore a surface reduction. More importantly, the DFT results revealed that it was the chemisorbed oxygen on Cu 2 O/Cu(111) which oxidized the dissociated *CH 3 O to *HCOO and eventually CO 2 , while the reaction only involving upper oxygen on the Cu 2 O hexagonal ring led to the formation of H 2 CO.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Ab-Initio Investigation of Finite Size Effects in Rutile Titania Nanoparticles with Semilocal and Nonlocal Density Functionals

In this work, we employ hybrid and generalized gradient approximation (GGA) level density functional theory (DFT) calculations to investigate the convergence of surface properties and electronic gap of rutile titania nanoparticles with particle size. The surface energies and electronic gaps are calculated for cuboidal particles with minimum dimension ranging from 3.7 Angstrom (24 atoms) to 10.3 Angstrom (384 atoms) using a highly-parallel real-space DFT code to enable hybrid level DFT calculations of larger nanoparticles than are typically practical. We deconvolute the geometric and electronic finite size effects in surface energy, and evaluate the influence of defects on electronic gap and density of states (DOS). The electronic finite size effects in surface energy vanish when the minimum length scale of the nanoparticles becomes greater than 10 Angstrom. We show that this length scale is consistent with a computationally efficient numerical analysis of the characteristic length scale of electronic interactions. The surface energy of nanoparticles having minimum dimension beyond this characteristic length can be approximated using slab calculations that account for the geometric defects. In contrast, the finite size effects on the electronic gap and DOS is highly dependent on the shape and size of these particles. Furthermore, the DOS for cuboidal particles and more realistic particles constructed using the Wulff algorithm reveal that defect states within the electronic gap play a key role in determining the eigen value distribution of nanoparticles and the electronic gap does not converge to the bulk limit for the particle sizes investigated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗