Search NASA⌕ Search

SEARCH · Search NASA

Results for “Bond dissociation”

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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A thermodynamic evaluation of metal halides for the recrystallization of Cu(In,Ga)Se 2

CdTe films are deposited at low temperatures and recrystallized to photovoltaic device quality using CdCl 2 treatments, leading to competitive manufacturing costs. Cu(In,Ga)Se 2 (CIGS) typically requires high-temperature, low-rate depositions to produce high-efficiency devices, resulting in higher costs. A similar metal halide treatment of CIGS has been demonstrated by us previously for some metal halide sources. To understand and optimize the process, a thermodynamic evaluation of candidate metal halides for such treatments is presented as a guide for their selection. By comparing bond dissociation energies, mono- and di-halide compounds are proposed to be ideal compounds to act as transport agents. Known recrystallization and temperature reduction benefits by Ag alloying suggests that Ag-halides should be used to aid transport of all species. The high vapor pressure and mobility of Ga compounds still poses a problem for metal halide treatment resulting in Ga etching and removal of intentional Ga gradients. Less severe but similar issues with In compounds may occur. As a result, Cu compounds have low vapor pressures which may limit transport, however, Cu is highly mobile in CIGS and recrystallization still occurs.

14 SOLAR ENERGY↗
DOE OSTI2026

Absolute photoionization cross sections of brominated organics and determination of an effective C—Br bond cross section

For this work, absolute photoionization cross sections for five brominated species were measured using multiplexed synchrotron photoionization mass spectrometry at the Advanced Light Source (Lawrence Berkeley National Laboratory). These data enable reliable detection of bromine-containing compounds and estimation of C—Br bond photoionization cross sections. Complementary electronic-structure calculations provided adiabatic ionization energies in good agreement with experiment, while thermochemical appearance energies were measured directly. Bond dissociation energies for key fragmentation pathways of the neutral parent molecules were also analyzed. At 11 eV, cross sections were 53.8 ± 7.50 Mb (sp 2 C—Br) and 48.8 ± 7.70 Mb (sp 3 C—Br).

Brominated compounds↗
DOE OSTI2025

PFOA catalytic reaction mechanisms on zerovalent iron (Fe 0 ): A DFT investigation

In this study, density functional theory (DFT) calculations with dispersion corrections are employed to investigate catalytic reactions of perfluorooctanoic acid (PFOA) onto zerovalent iron (Fe 0 ). The main goal of this investigation is to explain the reaction mechanisms, including bond dissociation energies, activation barriers, and rate-determining steps (RDSs), of PFOA degradation. Additionally, we aim to reveal the catalytic effects of Fe 0 by comparing the reaction energy profile for the degradation of PFOA both in solution (i.e., isolated) and after adsorption on Fe 0 . Along with investigating previously reported pathways, this study proposes a new PFOA degradation pathway on Fe0. Overall, the results revealed that Fe 0 plays a key role in the catalytic degradation of PFOA, significantly affecting the RDSs and increasing defluorination rates. For instance, the activation barrier for the decarboxylation step significantly decreased from 3.08 eV to 1.11 eV over the Fe0 surface, while the activation barrier for F dissociation decreased from ∼5 eV to 0.54 eV. Additionally, the proposed pathway in this study (i.e., successive defluorination) was found to be the most favorable pathway for PFOA degradation on Fe 0 . Taken together, the DFT results are consistent with reported experimental findings and provide critical insights that will help advance the design of catalysts for PFAS degradation.

Catalysis↗
DOE OSTI2022

Explicitly antisymmetrized neural network layers for variational Monte Carlo simulation

The combination of neural networks and quantum Monte Carlo methods has arisen as a promising path forward for highly accurate electronic structure calculations. Previous proposals have combined equivariant neural network layers with a final antisymmetric layer in order to satisfy the antisymmetry requirements of the electronic wavefunction. However, to date it is unclear if one can represent antisymmetric functions of physical interest, and it is difficult to precisely measure the expressiveness of the antisymmetric layer. Here, this work attempts to address this problem by introducing explicitly antisymmetrized universal neural network layers. This approach has a computational cost which increases factorially with respect to the system size, but we are nonetheless able to apply it to small systems to better understand how the structure of the antisymmetric layer affects its performance. We first introduce a generic antisymmetric (GA) neural network layer, which we use to replace the entire antisymmetric layer of the highly accurate ansatz known as the FermiNet. We demonstrate that the resulting FermiNet-GA architecture can yield effectively the exact ground state energy for small atoms and molecules. We then consider a factorized antisymmetric (FA) layer which more directly generalizes the FermiNet by replacing the products of determinants with products of antisymmetrized neural networks. We find, interestingly, that the resulting FermiNet-FA architecture does not significantly outperform the FermiNet. This strongly suggests that the sum of products of antisymmetries is a key limiting aspect of the FermiNet architecture. To explore this further, we investigate a slight modification of the FermiNet, called the full determinant mode, which replaces each product of determinants with a single combined determinant. We find that the full single-determinant FermiNet closes a large part of the gap between the standard single-determinant FermiNet and FermiNet-GA on small atomic and molecular problems. Surprisingly, on the nitrogen molecule at a dissociating bond length of 4.0 Bohr, the full single-determinant FermiNet can outperform the largest standard FermiNet calculation with 64 determinants.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Energy based fracture initiation criterion for strain-crystallizing rubber-like materials with pre-existing cracks

Fracture prediction is indispensable for polymers, like rubbers, which have a broad range of applications mainly due to their high extensibility. The phenomenon known as strain-induced crystallization further contributes to the fracture toughness of certain rubbers. Here in this study, a criterion based on internal bond energy, incorporating the effects of crystallization, is proposed to predict fracture initiation in rubber-like materials with pre-existing cracks. First, a multi-scale mechanical model is developed for characterizing the behavior of rubber when subjected to both uniaxial and biaxial deformation states. At the microscale, both the amorphous and crystalline chain segments are modeled as elastic in order to consider the energy contribution by the molecular bond distortions. This internal energy is considered along with the entropic and crystalline free energy for each chain. In the chain model, the effects of loading condition and the relative orientation of a chain on its crystallinity are taken into account. At the macroscopic scale, an existing crystallinity distribution function is adapted and a mixed finite element formulation with an augmented Lagrangian multiplier is utilized to impose the incompressibility constraint. A non-affine maximal advance path constraint based homogenization model is utilized for bridging the two scales. Its potential to account for anisotropy in the stretched network compels the model to be preferable due to its physical significance, for the purpose of fracture modeling. The rigidity of the crystallites is accounted for by proposing a crystallite distortion energy in addition to the critical bond dissociation energy, for fracture initiation to occur. The model is validated by comparison with existing experimental results for both crystallizing and non-crystallizing rubbers. In addition to its potential to predict the material behavior when subjected to uniaxial and biaxial loading, the capability of the model to quantitatively estimate the effect of crystallization on fracture initiation is also verified.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Engineering the fracture resistance of 2H-transition metal dichalcogenides using vacancies: An in-silico investigation based on HRTEM images

Vacancy engineering of 2H-transition metal dichalcogenides (2H-TMDs) has recently attracted great attention due to its potential to fine-tune the phonon and opto-electric properties of these materials. From a mechanical perspective, this symmetry-breaking process typically reduces the overall crack resistance of the material and adversely affects its reliability. However, vacancies can trigger the formation of heterogeneous phases that synergistically improve fracture properties. In this study, using MoSe2 as an example, we characterize the types and density of vacancies that can emerge under electron irradiation and quantify their effect on fracture. Molecular dynamic (MD) simulations, employing a re-parameterized Tersoff potential capable of accurately capturing bond dissociation and structural phase changes, reveal that isolated transition metal monovacancies or chalcogenide divacancies tend to arrest the crack tip and hence enhance the monolayer toughness. In contrast, isolated chalcogenide monovacancies do not significantly affect toughness. The investigation further reveals that selenium vacancy lines, formed by high electron dose rates, alter the crack propagating direction and lead to multiple crack kinking. Using atomic displacements and virial stresses together with a continuum mapping, displacement, strain, and stress fields are computed to extract mechanistic information, e.g., conditions for crack kinking and size effects in fracture events. The study also reveals the potential of specific defect patterns, “vacancy engineering,” to improve the toughness of 2H-TMDs materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Discerning structure sensitivity of Ni-core Pd-shell nanoparticles for enhanced nitrite reduction

Denitrification using Pd-based catalysts converts N-oxyanions into harmless products. However, the metal cost and scarcity are barriers to application. In this work, we synthesize water-suspended, structure-controlled Ni-core/Pd-shell nanoparticles (Ni@Pd NPs) that show Pd-catalyzed nitrite (NO 2 − ) reduction catalysis promoted by Ni. The NPs immobilized on Al 2 O 3 (0.47 wt % Pd and 0.74 wt % Ni) have higher NH 4 + selectivity and higher catalytic activity than wet-impregnated Pd/Al 2 O 3 (1.0 wt % Pd), i.e., 315.4 vs. 132.1 Lg surface Pd −1 min −1 . X-ray photoelectron spectroscopy (XPS) and CO-diffuse reflectance infrared Fourier transform spectroscopy (CO-DRIFTS) analyses show that Ni increases Pd electron density, which is proposed to lower the bond dissociation energy barrier for nitric oxide surface intermediate. Low-coordinated Pd atoms correlate to high activity and low NH 4 + selectivity. Using CatCost software, we estimate Ni@Pd/Al 2 O 3 to have a ∼40% lower manufacturing cost compared to wet-impregnated Pd/Al 2 O 3 . This rationally designed catalyst illustrates how nickel promotes Pd catalysis and how Pd usage can be lowered for denitrification and other hydrogenation reactions.

CO-DRIFTS↗
DOE OSTI2021

CFM-ID 4.0: More Accurate ESI MS/MS Spectral Prediction and Compound Identification

In the field of metabolomics, mass spectrometry (MS) is the method most commonly used for identifying and annotating metabolites. As this typically involves matching a given MS spectrum against an experimentally acquired reference spectral library, this approach is limited by the coverage and size of such libraries (which typically number in the thousands). These experimental libraries can be greatly extended by predicting the MS spectra of known chemical structures (which number in the millions) to create computational reference spectral libraries. To facilitate the generation of predicted spectral reference libraries we developed CFM-ID, a computer program that can accurately predict ESI-MS/MS spectrum for a given compound structure. CFM-ID is one of the best-performing methods for compound-to-mass-spectrum prediction, and also one of the top tools for in silico mass-spectrum-to-compound identification. This work improves CFM-ID’s ability to predict ESI-MS/MS spectra from compounds by: (1) learning parameters from features based on the molecular topology, (2) adding a new approach to ring cleavage that models such cleavage as a sequence of simple chemical bond dissociations and (3) expanding its hand-written rule-based predictor to cover more chemical classes, including acylcarnitines, acylcholines, flavonols, flavones, flavanones, and flavonoid glycosides. We demonstrate that this new version of CFM-ID (version 4.0) is significantly more accurate than previous CFM-ID versions, in terms of both EI-MS/MS spectral prediction and compound identification. CFM-ID 4.0 is available at http://cfmid4.wishartlab.com/ as a webservice and docker images can be downloaded at https://hub.docker.com/r/wishartlab/cfmid

Wang, Fei↗
DOE OSTI2022

Theoretical Modeling of Electrochemical Proton-Coupled Electron Transfer

Proton-coupled electron transfer (PCET) plays an essential role in a wide range of electrocatalytic processes. Here, a vast array of theoretical and computational methods have been developed to study electrochemical PCET. These methods can be used to calculate redox potentials and pKa values for molecular electrocatalysts, proton-coupled redox potentials and bond dissociation free energies for PCET at metal and semiconductor interfaces, and reorganization energies associated with electrochemical PCET. Periodic density functional theory can also be used to compute PCET activation energies and perform molecular dynamics simulations of electrochemical interfaces. Various approaches for maintaining a constant electrode potential in electronic structure calculations and modeling complex interactions in the electric double layer (EDL) have been developed. Theoretical formulations for both homogeneous and heterogeneous electrochemical PCET spanning the adiabatic, nonadiabatic, and solvent-controlled regimes have been developed and provide analytical expressions for the rate constants and current densities as functions of applied potential. The quantum mechanical treatment of the proton and inclusion of excited vibronic states have been shown to be critical for describing experimental data, such as Tafel slopes and potential dependent kinetic isotope effects. The calculated rate constants can be used as input to microkinetic models and voltammogram simulations to elucidate complex electrocatalytic processes.

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

Mechanochemistry of Group 4 Element-Based Metal–Organic Frameworks

Mechanochemical synthesis is emerging as an environmentally friendly yet efficient approach to preparing metal-organic frameworks (MOFs). Herein, we report our systematic investigation on the mechanochemical syntheses of Group 4 element-based MOFs. The developed mechanochemistry allows us to synthesize a family of Hf 4 O 4 (OH) 4 (OOC) 12 -based MOFs. Integrating [Zr 6 O 4 (OH) 4 (OAc)12] 2 and [Hf 6 O 4 (OH) 4 (OAc) 12 ] 2 under the mechanochemical conditions leads to a unique family of cluster-precise multimetallic MOFs that cannot be accessed by the conventional solvothermal synthesis. Finally, extensive efforts have not yielded an effective pathway for preparing Ti IV -derived MOFs, tentatively because of the relatively low Ti-O bond dissociation energy.

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

Aqueous TiO 2 Nanoparticles React by Proton-Coupled Electron Transfer

Redox reactions of aqueous colloidal TiO 2 4 nm nanoparticles (NPs) have been examined, including both citratecapped and uncapped NPs (c-TiO 2 and uc-TiO 2 ). Photoreduction gave stable blue colloidal c-TiO 2 R NPs with 10–60 electrons per particle. Equilibration of these reduced NPs with soluble redox reagents such as methylviologen (MV 2+ ) provided measurements of the colloid reduction potential as a function of pH. The potentials of c-TiO 2 from pH 2–9 varied linearly with pH, with a slope of –60 ± 5 mV/pH. Estimates of the potential at pH 12 were consistent with extrapolating that line to high pH. The reduction potentials did not correlate with the zeta potentials (ζ) or the surface charge of the NPs across this pH range. Similar reduction potentials were observed for c- and uc-TiO 2 at low pH even though they have quite different ζ potentials. These results show that the common surface-charging explanation of the pH dependence is not tenable in these systems. Oxidation of reduced c-TiO 2 R with the electron-transfer oxidant potassium triiodide (KI 3 ) occurred with a significant drop in pH, showing that protons were released when the electrons were removed from the NPs. Smaller pH drops were observed for the proton-coupled electron transfer (PCET) reagents O 2 (air) and 4-MeO-TEMPO (4-methoxy-2,2,6,6-tetramethylpiperine-1-oxy radical). The difference in the number of protons released with KI 3 vs O 2 and 4-MeO-TEMPO was roughly one proton per electron removed. Thus, the thermodynamically preferred reactivity of these colloidal TiO 2 NPs is PCET over the pH 2–13 range studied. The measured redox potentials refer to the chemical process TiO 2 + H + + e – → TiO 2 ·e – ,H + ; and therefore they do not correspond with an electronic energy such as a conduction band edge or flat band potential. The 1e – /1H + stoichiometry means that the TiO 2 reduction potentials correspond to a TiO 2 –H bond dissociation free energy (BDFE), determined to be 49 ± 2 kcal mol –1 . The PCET description is consistent with the pH dependence of E(TiO 2 /TiO 2 ·e – ,H + ), the release of protons upon oxidation, the lack of correlation with ζ potentials, the similarity of capped and uncapped NPs, and the small change in the potential and BDFE from the first to the last electron/proton pair (H atom) removed. Furthermore, this behavior is suggested to be the norm for redox-active oxide/water interfaces.

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

Route to Chemical Accuracy for Computational Uranium Thermochemistry

Benchmark spinor-based relativistic coupled-cluster calculations for the ionization energies of the uranium atom, the uranium monoxide molecule (UO), and the uranium dioxide molecule (UO 2 ) and for the bond dissociation energies of UO and UO 2 are reported. The accuracy of these calculations in the treatments of relativistic, electron correlation, and basis-set effects is analyzed. Furthermore, the intrinsic convergence of the computed results and the favorable comparison with the experimental values demonstrate the unique applicability of the spinor representation of quantum-chemical methods to open-shell uranium-containing atomic and molecular species with uranium oxidation states ranging from U(0) to U(V).

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

Toward DMC Accuracy Across Chemical Space with Scalable Δ-QML

In the past decade, quantum diffusion Monte Carlo (DMC) has been demonstrated to successfully predict the energetics and properties of a wide range of molecules and solids by numerically solving the electronic many-body Schrödinger equation. With O(N 3 ) scaling with the number of electrons N, DMC has the potential to be a reference method for larger systems that are not accessible to more traditional methods such as CCSD(T). Assessing the accuracy of DMC for smaller molecules becomes the stepping stone in making the method a reference for larger systems. We show that when coupled with quantum machine learning (QML)-based surrogate methods, the computational burden can be alleviated such that quantum Monte Carlo (QMC) shows clear potential to undergird the formation of high-quality descriptions across chemical space. We discuss three crucial approximations necessary to accomplish this: the fixed-node approximation, universal and accurate references for chemical bond dissociation energies, and scalable minimal amons-set-based QML (AQML) models. Numerical evidence presented includes converged DMC results for over 1000 small organic molecules with up to five heavy atoms used as amons and 50 medium-sized organic molecules with nine heavy atoms to validate the AQML predictions. Finally, numerical evidence collected for Δ-AQML models suggests that already modestly sized QMC training data sets of amons suffice to predict total energies with near chemical accuracy throughout chemical space.

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

Cholesky Decomposition-Based Implementation of Relativistic Two-Component Coupled-Cluster Methods for Medium-Sized Molecules

A Cholesky decomposition (CD)-based implementation of relativistic two-component coupled-cluster (CC) and equation-of-motion CC (EOM-CC) methods using an exact two-component Hamiltonian augmented with atomic-mean-field integrals (the X2CAMF scheme) is reported. Furthermore, the present CD-based implementation of X2CAMF-CC and EOM-CC methods employs atomic-orbital-based algorithms to avoid the construction of two-electron integrals and intermediates involving three and four virtual indices. The CD-based implementation extends the applicability of X2CAMF-CC and EOMCC methods to medium-sized molecules with the correlation of around 1000 spinors. Benchmark calculations for uranium-containing small molecules have been performed to assess the dependence of CC results with respect to the Cholesky threshold. A Cholesky threshold of 10 –4 is shown to maintain chemical accuracy. Example calculations to illustrate the capability of the CD-based relativistic CC methods are reported for the bond dissociation energy of the uranium hexafluoride molecule, UF 6 , with up to quadruple-zeta basis sets and the lowest excitation energy in solvated uranyl ion [UO 2 2+ (H 2 O) 12 ].

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

An Accurate, Affordable Density Functional Tight-Binding Model for Excited State Hydrocarbon Polymer Molecular Dynamics

We have developed a density functional tight-binding model for hydrocarbon excited state dynamics by referencing to high-level electronic structure theory and incorporating a many-body repulsive energy. We then validate our model against n-octane geometry optimizations, bond dissociation scans, and vibrational frequencies. Our model is approximately 10 3 times more efficient than hybrid time-dependent density functional theory calculations with comparable accuracy. In conclusion, our efforts enable longer timescale excited state simulations of photochemistry and scattering of incident radiation.

Chemical calculations↗
DOE OSTI2020

Improving Excited-State Potential Energy Surfaces via Optimal Orbital Shapes

In this work, we demonstrate that, rather than resorting to high-cost dynamic correlation methods, qualitative failures in excited-state potential energy surface predictions can often be remedied at no additional cost by ensuring that optimal molecular orbitals are used for each individual excited state. This approach also avoids the weighting choices required by state-averaging and dynamic weighting and obviates their need for expensive wave function response calculations when relaxing excited-state geometries. Although multistate approaches are of course preferred near conical intersections, other features of excited-state potential energy surfaces can benefit significantly from our single-state approach. In three different systems, including a double bond dissociation, a biologically relevant amino hydrogen dissociation, and an amino-to-ring intramolecular charge transfer, we show that state-specific orbitals offer qualitative improvements over the state-averaged status quo.

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

Interaction of Th with H 0/–/+ : Combined Experimental and Theoretical Thermodynamic Properties

In this work, high-level electronic structure calculations of the lowlying energy electronic states for ThH, ThH – , and ThH + are reported and compared to experimental measurements. The inclusion of spin–orbit coupling is critical to predict the ground-state ordering as inclusion of spin–orbit switches the coupled-cluster CCSD(T) ordering of the two lowest energy states for ThH and ThH + . At the multireference spin–orbit SO-CASPT2 level, the ground states of ThH, ThH – , and ThH + are predicted to be the 2 Δ 3/2 , 3 Φ 2 , and 3 Δ 1 states, respectively. The adiabatic electron affinity is calculated to be 0.820 eV, and the vertical detachment energy is calculated to be 0.832 eV in comparison to an experimental value of 0.87 ± 0.02 eV. The observed ThH – photoelectron spectrum has many transitions, which approximately correlate with excitations of Th + and/or Th. The adiabatic ionization energy of ThH including spin–orbit corrections is calculated to be 6.181 eV. The natural bond orbital results are consistent with a significant contribution of the Th + H – ionic configuration to the bonding in ThH. The bond dissociation energies for ThH, ThH – , and ThH + using the Feller–Peterson–Dixon approach were calculated to be similar for all three molecules and lie between 259 and 280 kJ/mol.

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

Development of a Reactive Force Field for Simulating Photoinitiated Acrylate Polymerization

Light-driven and photo-curable polymer based additive manufacturing (AM) has enormous potential due to its excellent resolution and precision. Acrylated radical chain-growth polymerized resins are widely used in photopolymer AM due to their fast kinetics, and often serve as a departure point for developing other resin materials for photopolymer-based AM technologies. For successful control of the photopolymer resins, the molecular basis of the acrylate free-radical polymerization has to be understood in detail. We present an optimized reactive force field (ReaxFF) for molecular dynamics (MD) simulations of acrylate polymer resins that captures radical polymerization thermodynamics and kinetics. The force field is trained against an extensive training set including density functional theory (DFT) calculations of reaction pathways along the radical polymerization from methyl acrylate to methyl butyrate, bond dissociation energies, and structures and partial charges of several molecules and radicals. We also found that it was critical to train the force field against an incorrect, nonphysical reaction pathway observed in simulations that used parameters not optimized for acrylate polymerization. As a result, the parameterization process utilizes a parallelized search algorithm, and the resulting model can describe polymer resin formation, crosslinking density, conversion rate, and residual monomers of the complex acrylate mixtures.

36 MATERIALS SCIENCE↗