Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Molecular solids”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Molecular dynamics simulation of metallic Al–Ce liquids using a neural network machine learning interatomic potential

Al-rich Al-Ce alloys have the possibility of replacing heavier steel and cast-irons for use in high-temperature applications. Knowledge about the structures and properties of Al-Ce alloys at liquid state is vital for optimizing the manufacture process to produce desired allows. However, reliable molecular dynamics simulation of Al-Ce alloy systems remains a great challenge due to the lack of accurate Al-Ce interatomic potential. In this work, an artificial neural network (ANN) deep machine learning (ML) method is used to develop a reliable interatomic potential for Al-Ce alloy. Ab initio molecular dynamics (AIMD) simulation data on Al-Ce liquid with small unit cell (~200 atoms) and on the known Al-Ce crystalline compounds are collected to train the interatomic potential using ANN-ML. The obtained ANN-ML model reproduces well the energies, forces, and atomic structure of Al 90 Ce 10 liquid and crystalline phases of Al-Ce compounds in comparison with ab initio results. The developed ANN-ML potential is applied in molecular dynamics simulations to study the structures and properties of metallic Al 90 Ce 10 liquid, which would provide useful insight for guiding experimental process to produce desired Al-Ce allows.

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

Stochastic and mixed density functional theory within the projector augmented wave formalism for simulation of warm dense matter

Stochastic density functional theory (DFT) and mixed stochastic-deterministic DFT are burgeoning approaches for the calculation of the equation of state and transport properties in materials under extreme conditions. In the intermediate warm dense matter regime, a state between correlated condensed matter and kinetic plasma, electrons can range from being highly localized around nuclei to delocalized over the whole simulation cell. The plane-wave basis pseudopotential approach is thus the typical tool of choice for modeling such systems at the DFT level. Unfortunately, stochastic DFT methods scale as the square of the maximum plane-wave energy in this basis. To reduce the effect of this scaling and improve the overall description of the electrons within the pseudopotential approximation, we present stochastic and mixed DFT approaches developed and implemented within the projector augmented wave formalism. In conclusion, we compare results between the different DFT approaches for both single-point and molecular dynamics trajectories and present calculations of self-diffusion coefficients of solid density carbon from 1 to 50 eV.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Atomistic simulations of the thermal conductivity of liquids

We present a method based on sinusoidal approach to equilibrium molecular dynamics (SAEMD) to compute the thermal conductivity of liquids Similar to nonequilibrium molecular dynamics, and unlike equilibrium simulations based on the Green-Kubo formalism, the method only requires the calculation of forces and total energies. The evaluation of heat fluxes and energy densities is not necessary, thus offering the promise of efficiently implementing first principles simulations based on density functional theory or deep molecular dynamics. Our approach is a generalization of SAEMD for solids, where the thermal conductivity is computed in the steady state, instead of a transient regime, thus properly taking into account diffusive terms in the heat equation. We present results for liquid water at ambient conditions and under pressure and discuss simulation requirements to obtain converged values of the thermal conductivity as a function of size and simulation time.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Detonation Waves in High Explosives

A material at high temperature can react or decompose. For an energetic material, the reaction is exothermic and releases chemical energy that would further increase the temperature. Under some circumstances, when a reaction is triggered, such a reaction can propagate and the material rapidly releases a large amount of energy giving rise to an explosion. Examples of such materials are aerosols, suspensions of solid particles or liquid droplets in a gas; such as coal dust, grain dust and fuel-air explosions. Frequently, explosions are due to accidents. A spectacularly destructive example is the recent explosion of a large quantity of ammonium nitrate (thousands of tons) in Beirut, Lebanon (August 2020); see for example Beirut explosion. Ammonium nitrate is used as a fertilizer. It and the aerosols are not considered to be explosives due to the limited conditions for which an explosion can occur. An aerosol gets the oxidizer from the surrounding air. Burning requires diffusion of the oxidizer to the particle surface where the reaction occurs. A large density of small particles is required for a fast enough reaction to support an explosion. In contrast, an explosive is an energetic material with both fuel and oxidizer mixed on a molecular scale (either premixed gases or within molecules of a solid). This allows fast enough reactions over a wide range of conditions to support a self-propagating reactive wave known as a detonation wave. A detonation wave can be controlled and an explosive used for useful purposes such as in mining, construction, demolition, explosive welding, argon flash lamp, pulsed power using a magnetic flux generator [see also Goforth et al., 2015], jet cutter with shaped charge, explosive art, and generating conditions to study the response of materials at high strain rates and high pressures [see for example, Marsh, 1980]. Explosives are also used in conventional munitions and nuclear weapons. The focus of this book is on the theory and phenomenology of solid high explosives (HEs); in particular, plastic-bonded explosives (PBXs). Some aspects of detonation wave theory are needed to interpret explosive data. Hence, the theory is presented before the detonation wave phenomenology. A familiarity with fluid flow, specifically the notion of shock waves and the shock loci are assumed. In the remainder of this chapter we give a brief overview on the basic properties of detonation waves and PBXs.

36 MATERIALS SCIENCE↗
DOE OSTI2023

ORNL_AISD_NiPt_108atoms

This dataset describes the nickel-platinum (NiPt) solid solution binary alloy, where the two constituent elements nickel (Ni) and platinum (Pt) are randomly placed on the face centered cubic (FCC) crystal structure, with the lattice constant of 3.840 angstroms. The dataset comprises data for crystal structures with 108 atoms with 1,900 configurations. The data set was generated for concentrations ranging from 0at% of Pt to 100at% of Pt in the NiPt binary system, with increasing the concentration of Pt in the system every 5at%. For each one of the chemical compositions, 100 random configurations were generated, each with a different random seed. Each of the output files contains the mass, type, atomic coordinates, energy per atom, and forces in x, y, and z directions respectively. For each atomic configuration, the output was collected every 150 steps during the minimization stage and every 1000 steps during the replica exchange stage. Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) [1], which is a molecular dynamics code, was used to generate data for NiPt alloy. The simulation used the interatomic potential for NiPt binary system 'MEAM_LAMMPS_KimSeolJi_2017_PtNi__MO_020840179467_001' [3] from the OpenKIM library (Open Knowledgebase of Interatomic Models) [2]. This potential was developed based on the second nearest-neighbor modified embedded-atom method (2NN MEAM). The simulation process begins with the generation of the random NiPt structure and follows with the short minimization and replica exchange simulation. The minimization procedure adjusts atomic coordinates and performs energy minimization, which typically leads to a local potential energy minimum. The method used for the minimization was the conjugate gradient algorithm. A short replica exchange (parallel tempering) simulation involves four replicas (ensembles) of a system and follows the minimization stage. Multiple snapshots of the configuration were collected during the minimization and replica exchange stages. NiPt alloy is interesting due to its magnetic and charge transfer properties [4]. The data is provided in a compressed zipped folders atoms108.zip. The zipped folder contains the data structured in the following way: - Ni_ground_state.cfg --> atomic configuration for the pure nickel - Pt_ground_state.cfg --> atomic configuration for the pure platinum - Pt#_filtered --> folders containing atomic configurations for #at% concentration of platinum. The folder contains 100 atomic configurations, each saved in a subfolder - Each subfolder named config* is associated with a specific atomic configuration. Each of these subfolders contains files with .cfg format, corresponding to outputs for each atomic configuration The total number of atomic configurations contained in atoms108.zip is 66,132. This dataset is an extension to the dataset ORNL_AISD_NiPt [5] that has been previously released with crystal structures of 256 atoms, 864 atoms, and 2,048 atoms, with the same methodology for data collection. References [1] https://www.lammps.org/ [2] https://openkim.org/ [3] https://openkim.org/id/MEAM_LAMMPS_KimSeolJi_2017_PtNi__MO_020840179467_001 [4] El-Gendy, Ahmed A. and Hampel, Silke and Büchner, Bernd and Klingeler, Rüdiger, Tuneable magnetic properties of carbon-shielded NiPt-nanoalloys, RSC Adv., volume 6, issue 57, pages 52427-52433, 2016, The Royal Society of Chemistry, doi:10.1039/C6RA05910D [5] M. Karabin, M. Lupo Pasini, and M. Eisenbach. ORNL_AISD_NiPt. United States: N. p., 2023. Web. doi:10.13139/OLCF/1958172.

36 MATERIALS SCIENCE↗
DOE OSTI2022

High‐Field NMR, Reactivity, and DFT Modeling Reveal the γ‐Al 2 O 3 Surface Hydroxyl Network**

Abstract Aluminas are strategic materials used in many major industrial processes, either as catalyst supports or as catalysts in their own right. The transition alumina γ‐Al 2 O 3 is a privileged support, whose reactivity can be tuned by thermal activation. This study provides a qualitative and quantitative assessment of the hydroxyl groups present on the surface of γ‐Al 2 O 3 at three different dehydroxylation temperatures. The principal [AlOH] configurations are identified and described in unprecedented detail at the molecular level. The structures were established by combining information from high‐field 1 H and 27 Al solid‐state NMR, IR spectroscopy and DFT calculations, as well as selective reactivity studies. Finally, the relationship between the hydroxyl structures and the molecular‐level structures of the active sites in catalytic alkane metathesis is discussed.

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

Coordination-Dependent Chemical Reactivity of TFSI Anions at a Mg Metal Interface

Charge transfer across the electrode–electrolyte interface is a highly complex and convoluted process involving diverse solvated species with varying structures and compositions. Despite recent advances in in situ and operando interfacial analysis, molecular specific reactivity of solvated species is inaccessible due to a lack of precise control over the interfacial constituents and/or an unclear understanding of their spectroscopic fingerprints. However, such molecular-specific understanding is critical to the rational design of energy-efficient solid–electrolyte interphase layers. We have employed ion soft landing, a versatile and highly controlled method, to prepare well-defined interfaces assembled with selected ions, either as solvated species or as bare ions, with distinguishing molecular precision. Equipped with precise control over interfacial composition, we employed in situ multimodal spectroscopic characterization to unravel the molecular specific reactivity of Mg solvated species comprising (i.e., bis(trifluoromethanesulfonyl)imide, TFSI – ) anions and solvent molecules (i.e., dimethoxyethane, DME/G1) on a Mg metal surface relevant to multivalent Mg batteries. In situ multimodal spectroscopic characterization revealed higher reactivity of the undercoordinated solvated species [Mg-TFSI-G1] + compared to the fully coordinated [Mg-TFSI-(G1) 2 ] + species or even the bare TFSI – . These results were corroborated by the computed reaction pathways and energy barriers for decomposition of the TFSI – within Mg solvated species relative to bare TFSI – . Finally, we evaluated the TFSI reactivity under electrochemical conditions using Mg(TFSI) 2 –DME-based phase-separated electrolytes representing different solvated constituents. Based on our multimodal study, we report a detailed understanding of TFSI – decomposition processes as part of coordinated solvated species at a Mg-metal anode that will aid the rational design of improved sustainable electrochemical energy technologies.

25 ENERGY STORAGE↗
DOE OSTI2022

1 H chemical shift anisotropy: a high sensitivity solid-state NMR dynamics probe for surface studies?

We report dynamics play significant roles in chemistry and biochemistry-molecular motions impact both large- and small-scale chemical reactions in addition to biochemical processes. In many systems, including heterogeneous catalysts, the characterization of dynamics remains a challenge. The most common approaches involve the solid-state NMR measurement of anisotropic interactions, in particular 2 H quadrupolar coupling and 1 H–X dipolar coupling, which generally require isotope enrichment. Due to the high sensitivity of 1 H NMR, 1 H chemical shift anisotropy (CSA) is a particularly enticing, and underexplored, dynamics probe. We carried out 1 H CSA and 1 H– 13 C dipolar coupling measurements in a series of model supported complexes to understand how 1 H CSA can be leveraged to gain dynamic information for heterogeneous catalysts. Mathematical descriptions are given for the dynamic averaging of the CSA tensor, and its dependence on orientation and asymmetry. The variability of the orientation of the tensor in the molecular frame, in addition to its magnitude and asymmetry, negatively impacts attempts to extract quantitative dynamic information. Nevertheless, 1 H CSA measurements can reveal useful qualitative insights into the motions of a particularly dilute site, such as from a surface species.

1H chemical shift anisotropy↗
DOE OSTI2021

Bimetallic Copper/Ruthenium/Osmium Complexes: Observation of Conformational Differences Between the Solution Phase and Solid State by Atomic Pair Distribution Function Analysis

Abstract High‐energy X‐ray scattering and pair distribution function analysis (HEXS/PDF) is a powerful method to reveal the structure of materials lacking long‐range order, but is underutilized for molecular complexes in solution. We demonstrate the application of HEXS/PDF with 0.26 Å resolution to uncover the solution structure of five bimetallic Cu I /Ru II /Os II complexes. HEXS/PDF of each complex in acetonitrile solution confirms the pairwise distances in the local coordination sphere of each metal center as well as the metal⋅⋅⋅metal distances separated by over 12 Å. The metal⋅⋅⋅metal distance detected in solution is compared with that from the crystal structure and molecular models to confirm that distortions to the metal bridging ligand are unique to the solid state. This work presents the first example of observing sub‐Ångström conformational differences by direct comparison of solution phase and solid‐state structures and shows the potential for HEXS/PDF in the determination of solution structure of single molecules.

Xie, Zhu‐Lin↗
DOE OSTI2024

Non-covalent planarizing interactions yield highly ordered and thermotropic liquid crystalline conjugated polymers

Controlling the multi-level assembly and morphological properties of conjugated polymers through structural manipulation has contributed significantly to the advancement of organic electronics. In this work, a redox active conjugated polymer, TPT–TT, composed of alternating 1,4-(2-thienyl)-2,5-dialkoxyphenylene (TPT) and thienothiophene (TT) units is reported with non-covalent intramolecular S⋯O and S⋯H–C interactions that induce controlled main-chain planarity and solid-state order. As confirmed by density functional theory (DFT) calculations, these intramolecular interactions influence the main chain conformation, promoting backbone planarization, while still allowing dihedral rotations at higher kinetic energies (higher temperature), and give rise to temperature-dependent aggregation properties. Thermotropic liquid crystalline (LC) behavior is confirmed by cross-polarized optical microscopy (CPOM) and closely correlated with multiple thermal transitions observed by differential scanning calorimetry (DSC). This LC behavior allows us to develop and utilize a thermal annealing treatment that results in thin films with notable long-range order, as shown by grazing-incidence X-ray diffraction (GIXD). Specifically, we identified a first LC phase, ranging from 218 °C to 107 °C, as a nematic phase featuring preferential face-on π–π stacking and edge-on lamellar stacking exhibiting a large extent of disorder and broad orientation distribution. A second LC phase is observed from 107 °C to 48 °C, as a smectic A phase featuring sharp, highly ordered out-of-plane lamellar stacking features and sharp tilted backbone stacking peaks, while the structure of a third LC phase with a transition at 48 °C remains unclear, but resembles that of the solid state at ambient temperature. Furthermore, the significance of thermal annealing is evident in the ∼3-fold enhancement of the electrical conductivity of ferric tosylate-doped annealed films reaching 55 S cm −1 . More importantly, thermally annealed TPT–TT films exhibit both a narrow distribution of charge-carrier mobilities (1.4 ± 0.1) × 10 −2 cm 2 V −1 s −1 along with a remarkable device yield of 100% in an organic field-effect transistor (OFET) configuration. This molecular design approach to obtain highly ordered conjugated polymers in the solid state affords a deeper understanding of how intramolecular interactions and repeat-unit symmetry impact liquid crystallinity, solution aggregation, solution to solid-state transformation, solid-state morphology, and ultimately device applications.

Chemistry↗
DOE OSTI2020

Intermediate Species in the Crystallization of Sodium Aluminate Hydroxy Hydrates

In highly alkaline “water-in-salt” Na 2 O/Al 2 O 3 /H 2 O solutions where the monomeric Al(OH) 4 - anion dominates, isolation of transitional species that seed crystallization of sodium aluminate salt hydrates has been challenging. For example, discrimination of dimeric [e.g., Al 2 O(OH) 6 2- ] from species via 27 Al nuclear magnetic resonance (NMR) spectroscopy is limited via fast interconversion through hydrolysis and condensation reactions. Despite this, using magic-angle spinning NMR ( 27 Al MAS NMR) at high magnetic field strengths (14.1 and 20.0 T) on crystals of nonasodium bis(hexahydroxyaluminate) trihydroxide hexahydrate [NSA, Na 9 [Al(OH) 6 ] 2 ·3(OH)·6(H 2 O)], we observed a 27 Al resonance consistent with Na 2 Al 2 O(OH) 6 . This tetrahedral dimeric species was also identified in the mother liquor by Raman spectroscopy while remaining expectedly unresolved by high-field liquid-state 27 Al NMR. Its substantial abundance in the mother liquor and as either an interstitial or an adsorbate on precipitated solids suggest that it plays a crucial role in NSA crystallization. Here, our detailed characterization, which includes single-pulse 27 Al MAS NMR, nutation 27 Al MAS NMR, and multiple quantum 27 Al MAS NMR, provides new molecular insights into how aluminate transitions from tetrahedral in solution to octahedral in solid. This understanding could ultimately lead to better predictions of aluminum phase change behavior in caustic sodium hydroxide with wide-ranging technological and environmental implications.

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

Probing electrolyte–silica interactions through simulations of the infrared spectroscopy of nanoscale pores

The structural and dynamical properties of nanoconfined solutions can differ dramatically from those of the corresponding bulk systems. Understanding the changes induced by confinement is central to controlling the behavior of synthetic nanostructured materials and predicting the characteristics of biological and geochemical systems. A key outstanding issue is how the molecular-level behavior of nanoconfined electrolyte solutions is reflected in different experimental, particularly spectroscopic, measurements. This is addressed here through molecular dynamics simulations of the OH stretching infrared (IR) spectroscopy of NaCl, NaBr, and NaI solutions in isotopically dilute HOD/D 2 O confined in hydroxylated amorphous silica slit pores of width 1–6 nm and pH ~2. In addition, the water reorientation dynamics and spectral diffusion, accessible by pump–probe anisotropy and two-dimensional IR measurements, are investigated. In this work, the aim is to elucidate the effect of salt identity, confinement, and salt concentration on the vibrational spectra. It is found that the IR spectra of the electrolyte solutions are only modestly blue-shifted upon confinement in amorphous silica slit pores, with both the size of the shift and linewidth increasing with the halide size, but these effects are suppressed as the salt concentration is increased. This indicates the limitations of linear IR spectroscopy as a probe of confined water. However, the OH reorientational and spectral diffusion dynamics are significantly slowed by confinement even at the lowest concentrations. The retardation of the dynamics eases with increasing salt concentration and pore width, but it exhibits a more complex behavior as a function of halide.

Mesoporous material↗
DOE OSTI2022

Ab Initio Phase Diagram of Chromium to 2.5 TPa

Chromium possesses remarkable physical properties such as hardness and corrosion resistance. Chromium is also a very important geophysical material as it is assumed that lighter Cr isotopes were dissolved in the Earth’s molten core during the planet’s formation, which makes Cr one of the main constituents of the Earth’s core. Unfortunately, Cr has remained one of the least studied 3d transition metals. In a very recent combined experimental and theoretical study (Anzellini et al., Scientific Reports, 2022), the equation of state and melting curve of chromium were studied to 150 GPa, and it was determined that the ambient body-centered cubic (bcc) phase of crystalline Cr remains stable in the whole pressure range considered. However, the importance of the knowledge of the physical properties of Cr, specifically its phase diagram, necessitates further study of Cr to higher pressure. In this work, using a suite of ab initio quantum molecular dynamics (QMD) simulations based on the Z methodology which combines both direct Z method for the simulation of melting curves and inverse Z method for the calculation of solid–solid phase transition boundaries, we obtain the theoretical phase diagram of Cr to 2.5 TPa. We calculate the melting curves of the two solid phases that are present on its phase diagram, namely, the lower-pressure bcc and the higher-pressure hexagonal close-packed (hcp) ones, and obtain the equation for the bcc-hcp solid–solid phase transition boundary. We also obtain the thermal equations of state of both bcc-Cr and hcp-Cr, which are in excellent agreement with both experimental data and QMD simulations. We argue that 2180 K as the value of the ambient melting point of Cr which is offered by several public web resources (“Wikipedia,” “WebElements,” “It’s Elemental,” etc.) is most likely incorrect and should be replaced with 2135 K, found in most experimental studies as well as in the present theoretical work.

equation of state↗
DOE OSTI2024

eReaxFF force field development for BaZr 0.8 Y 0.2 O 3-δ solid oxide electrolysis cells applications

The use of solid-oxide materials in electrocatalysis applications, especially in hydrogen-evolution reactions, is promising. However, further improvements are warranted to overcome the fundamental bottlenecks to enhancing the performance of solid-oxide electrolysis cells (SOECs), which is directly linked to the more-refined fundamental understanding of complex physical and chemical phenomena and mass exchanges that take place at the surfaces and in the bulk of electrocatalysis materials. Here, we developed an eReaxFF force field for barium zirconate doped with 20 mol% of yttrium, BaZr 0.8 Y 0.2 O 3-δ (BZY20) to enable a systematic, large-length-scale, and longer-timescale atomistic simulation of solid-oxide electrocatalysis for hydrogen generation. All parameters for the eReaxFF were optimized to reproduce quantum-mechanical (QM) calculations on relevant condensed phase and cluster systems describing oxygen vacancies, vacancy migrations, electron localization, water adsorption, water splitting, and hydrogen generation on the surfaces of the BZY20 solid oxide. Using the developed force field, we performed both zero-voltage (excess electrons absent) and non-zero-voltage (excess electrons present) molecular dynamics simulations to observe water adsorption, water splitting, proton migration, oxygen-vacancy migrations, and eventual hydrogen-production reactions. Based on investigations offered in the present study, we conclude that the eReaxFF force field-based approach can enable computationally efficient simulations for electron conductivity, electron leakage, and other non-zero-voltage effects on the solid oxide materials using the explicit-electron concept. Moreover, we demonstrate how the eReaxFF force field-based atomistic-simulation approach can enhance our understanding of processes in SOEC applications and potentially other renewable-energy applications.

08 HYDROGEN↗
DOE OSTI2020

Development of neural network force fields for corrosion studies

To fully understand the chemistry and physics of corrosion, novel methods of simulation must be developed. One approach is designing machine learning (ML) algorithms integrated with density functional theory to develop adaptive force fields to gain insight into corrosion behavior namely at the surface of metal oxides. Current methods of modeling corrosion are slow due to the computational cost of resolving both reaction mechanics and mass transport processes. Machine learning methods can be implemented to obtain structure-activity relationships at both the molecular and bulk scale while still retaining the accuracy of density functional theory (DFT) and significantly decreasing the time needed for simulations of complex chemical processes in the various environments of corrosion. Multiscale models are needed for corrosion studies to fully understand its processes not only at the atomic length scale (chemical bonding, energies, and forces), but also at the nano and meso length scales (solid-state physics and material science processes). Current methods of study include DFT, molecular dynamics, and Monte Carlo. The limitation of DFT is that only a small number of atoms or molecules can be simulated at that level of theory. Density functional theory is used to study the electronic structure of atoms and molecules, and calculate the force component of each atom. However, these calculations are limited to about 1000 atoms. Custom periodic boundary conditions (PBC) can be used to describe the various environments and defects that affect the atomic forces to produce a large data set from which a training set can be derived. Machine learning can be utilized to overcome the barrier of modeling macroscopic and multi-scale processes from ab initio calculations through the development of adaptive force fields. Local environments determine the atomic forces of a given system, therefore adaptive force fields must be created to produce reliable quantum mechanical calculations. This can be achieved by developing a learning algorithm that uses the mapped atomic forces or fingerprint as an input to produce energies and magnetic moments as output. A systematic approach was used to begin to build a data set in order to accurately describe the atomic forces in various environments. In Figure 4 below, a simple PBC cell of Fe{sub 2}O{sub 3} was first optimized. A surface optimization was performed next, followed by a hydroxylated surface optimization. Once this calculation has converged, the adsorption of halide species to the hydroxylated surface will be investigated. TensorFlow is an open source platform for machine learning developed by Google. Using a high level application program interface (API) such as Keras allows for building and training ML models easily in a number of different environments and languages. For this project, a neural network was developed within Anaconda in Python. Future Work: Further development of reference data set; Refining neural network and learning algorithm; Fingerprinting atomic environment to enable mapping of atomic force components; Choosing appropriate training set from reference data; Learning from training set and enabling non-linear mapping of training set fingerprints and the atomic forces; Estimation of uncertainty to identify ranges of outside applicability; Testing and analysis of molecular dynamic simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Bimetallic Copper/Ruthenium/Osmium Complexes: Observation of Conformational Differences Between the Solution Phase and Solid State by Atomic Pair Distribution Function Analysis

High-energy X-ray scattering and pair distribution function analysis (HEXS/PDF) is a powerful method to reveal the structure of materials lacking long-range order, but is underutilized for molecular complexes in solution. Here we demonstrate the application of HEXS/PDF with 0.26 Å resolution to uncover the solution structure of five bimetallic Cu I /Ru II /Os II complexes. HEXS/PDF of each complex in acetonitrile solution confirms the pairwise distances in the local coordination sphere of each metal center as well as the metal...metal distances separated by over 12 Å. The metal…metal distance detected in solution is compared with that from the crystal structure and molecular models to confirm that distortions to the metal bridging ligand are unique to the solid state. This work presents the first example of observing sub-Ångström conformational differences by direct comparison of solution phase and solid-state structures and shows the potential for HEXS/PDF in the determination of solution structure of single molecules.

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

High‐Field NMR, Reactivity, and DFT Modeling Reveal the γ‐Al 2 O 3 Surface Hydroxyl Network**

Abstract Aluminas are strategic materials used in many major industrial processes, either as catalyst supports or as catalysts in their own right. The transition alumina γ‐Al 2 O 3 is a privileged support, whose reactivity can be tuned by thermal activation. This study provides a qualitative and quantitative assessment of the hydroxyl groups present on the surface of γ‐Al 2 O 3 at three different dehydroxylation temperatures. The principal [AlOH] configurations are identified and described in unprecedented detail at the molecular level. The structures were established by combining information from high‐field 1 H and 27 Al solid‐state NMR, IR spectroscopy and DFT calculations, as well as selective reactivity studies. Finally, the relationship between the hydroxyl structures and the molecular‐level structures of the active sites in catalytic alkane metathesis is discussed.

Merle, Nicolas↗
DOE OSTI2021

Effect of surface properties and polymer chain length on polymer adsorption in solution

In polymer nanoparticle composites (PNCs) with attractive interactions between nanoparticles (NPs) and polymers, a bound layer of the polymer forms on the NP surface, with significant effects on the macroscopic properties of the PNCs. The adsorption and wetting behaviors of polymer solutions in the presence of a solid surface are critical to the fabrication process of PNCs. In this study, we use both classical density functional theory (cDFT) and molecular dynamics (MD) simulations to study dilute and semi-dilute solutions of short polymer chains near a solid surface. Using cDFT, we calculate the equilibrium properties of polymer solutions near a flat surface while varying the solvent quality, surface–fluid interactions, and the polymer chain lengths to investigate their effects on the polymer adsorption and wetting transitions. Using MD simulations, we simulate polymer solutions near solid surfaces with three different curvatures (a flat surface and NPs with two radii) to study the static conformation of the polymer bound layer near the surface and the dynamic chain adsorption process. Additionally, we find that the bulk polymer concentration at which the wetting transition in the poor solvent system occurs is not affected by the difference in surface–fluid interactions; however, a threshold value of surface–fluid interaction is needed to observe the wetting transition. We also find that with good solvent, increasing the chain length or the difference in the surface–polymer interaction relative to the surface–solvent interaction increases the surface coverage of polymer segments and independent chains for all surface curvatures. Finally, we demonstrate that the polymer segmental adsorption times are heavily influenced only by the surface–fluid interactions, although polymers desorb more quickly from highly curved surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗