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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Accurate quantum chemical calculations

An important goal of quantum chemical calculations is to provide an understanding of chemical bonding and molecular electronic structure. A second goal, the prediction of energy differences to chemical accuracy, has been much harder to attain. First, the computational resources required to achieve such accuracy are very large, and second, it is not straightforward to demonstrate that an apparently accurate result, in terms of agreement with experiment, does not result from a cancellation of errors. Recent advances in electronic structure methodology, coupled with the power of vector supercomputers, have made it possible to solve a number of electronic structure problems exactly using the full configuration interaction (FCI) method within a subspace of the complete Hilbert space. These exact results can be used to benchmark approximate techniques that are applicable to a wider range of chemical and physical problems. The methodology of many-electron quantum chemistry is reviewed. Methods are considered in detail for performing FCI calculations. The application of FCI methods to several three-electron problems in molecular physics are discussed. A number of benchmark applications of FCI wave functions are described. Atomic basis sets and the development of improved methods for handling very large basis sets are discussed: these are then applied to a number of chemical and spectroscopic problems; to transition metals; and to problems involving potential energy surfaces. Although the experiences described give considerable grounds for optimism about the general ability to perform accurate calculations, there are several problems that have proved less tractable, at least with current computer resources, and these and possible solutions are discussed.

Bauschlicher, Charles W., Jr.↗
NASA NTRS1997

Quantum Chemical Calculations

The current methods of quantum chemical calculations will be reviewed. The accent will be on the accuracy that can be achieved with these methods. The basis set requirements and computer resources for the various methods will be discussed. The utility of the methods will be illustrated with some examples, which include the calculation of accurate bond energies for SiF$_n$ and SiF$_n^+$ and the modeling of chemical data storage.

Bauschlicher, Charles W.↗
DOE OSTI2018

A new approach for the acceleration of large-scale serial quantum chemical calculations of docking complexes

A new approach to radical accelerate large-scale quantum chemical calculations of docking complexes, which require large computational times, is proposed. It takes into account the local nature of protein interaction with ligands and is based on a formation of special groups of atoms, which include the compactly located ligands and the protein atoms surrounding them. The procedure based on this approach allowed more than twice to reduce the time of a very resource-consuming calculation with respect to our previous high-speed semi-empirical method without a noticeable decrease in accuracy and provided a level of the time consumption appropriate for the large-scale serial calculations of such complexes.

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

Scaling Ensembles of Data-Intensive Quantum Chemical Calculations for Millions of Molecules

Deep learning models are efficient computational tools that can accelerate the inverse design of molecules with desired functional properties by generating predictions at a fraction of the time required by traditional quantum chemical approaches. To ensure that a model maintains accuracy and transferability across broad regions of the chemical space explored during the inverse design, it must be trained on massively large volumes of simulation data. This requires running large-scale ensemble quantum chemical calculations on high-performance computing (HPC) systems for data collection. However, the efficient execution of such large ensemble calculations and the management of large volumes of output data require tools that can judiciously utilize computational resources and manage metadata overhead on the file system. Therefore, we present a high-performance, scalable, ensemble management framework for performing data-intensive quantum chemical electronic structure calculations for organic molecules. This framework provides abstractions to plug different ab initio, first principles, and first principles-based semi-empirical methods and executes them efficiently at large scale on HPC systems. It dynamically distributes tasks to resources and uses tiered storage for managing large collections of files. We employed this framework to process over ten million organic molecules and generate open-source datasets that provide UV-vis absorption spectra by running time-dependent density-functional tight-binding calculations. It is the largest database containing molecular optical spectra that were simulated with quantum chemical methods in a consistent manner.

Mehta, Kshitij↗
DOE OSTI2023

Refining the thermochemical properties of CF, SiF, and their cations by combining photoelectron spectroscopy, quantum chemical calculations, and the Active Thermochemical Tables approach

Fluorinated species have a pivotal role in semiconductor material chemistry and some of them have been detected beyond the Earth's atmosphere. Achieving good energy accuracy on fluorinated species using quantum chemical calculations has long been a challenge. In addition, obtaining direct experimental thermochemical quantities has also proved difficult. Here, we report the threshold photoelectron and photoion yield spectra of SiF and CF radicals generated with a fluorine reactor. The spectra were analysed with the support of ab initio calculations, resulting in new experimental values for the adiabatic ionisation energies of both CF (9.128 ± 0.006 eV) and SiF (7.379 ± 0.009 eV). Using these values, the underlying thermochemical network of Active Thermochemical Tables was updated, providing further refined enthalpies of formation and dissociation energies of CF, SiF, and their cationic counterparts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Quantum Chemical Calculations of the Spectroscopic Properties and Nonlinear Optical Activity of 2,6-Dibromo-3-Chloro-4-Fluoroaniline

The Fourier transform infrared (FT-IR) and Fourier transform Raman (FT-Raman) spectra of 2,6-dibromo-3-chloro-4-fluoroaniline in the solid phase were recorded and analyzed. Quantum chemical calculations of the optimized molecular structure, energies, nonlinear optical (NLO) analysis, molecular surfaces, and vibrational analysis of this substance were performed. The obtained results on the geometric structure and vibrational frequencies were compared with the observed data. The calculated highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energies also confirm that charge transfer occurs within the molecule. The detailed vibrational assignments were performed using the HF and DFT calculations, and the potential energy distribution (PED) was obtained by the vibrational energy distribution analysis (VEDA4) program. Finally, the effects of the amino, bromo, chloro, and fluoro substituents on the vibrational frequencies were investigated.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Quantum chemically calculated Abraham parameters for quantifying and predicting polymer hydrophobicity

The leakage and accumulation of plastic in the environment is a significant and growing problem with numerous detrimental impacts and has led to a push toward the design and development of more environmentally benign materials. To this end, we have developed a quantum chemistry-based model for predicting the mobility of polymer materials from molecular structure. Hydrophobicity is used as a surrogate for mobility given that hydrophobic interactions drive much of the partitioning of contaminants in and out of various environmentally relevant compartments. To model polymer hydrophobicity, we adjusted a previously developed Quantum Chemically Calculated Abraham Parameter model to calculate Abraham parameters of small molecules from molecular structure information. The resulting model predicted the octanol-water partition coefficient (K OW ) of polymer repeating units with a root mean square error (RMSE) of 0.48 (log scale). Additionally, the hydrophobicity of high molecular weight polymer materials was captured through solubility parameters and Nile red staining experiments from the literature and predicted with RMSEs of 1.21 (J/cc) 0.5 and 3.42 nm, respectively. Finally, to test the environmental applicability of the model, the relative adsorption capacity of three polymers was predicted and used to unify sorption isotherms across multiple sorbates and polymer sorbents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Quantum chemical calculations to determine partitioning coefficients for HgCl 2 on iron-oxide aerosols

Gas-to-particle phase partitioning controls the pathways for oxidized mercury deposition from the atmosphere to the Earth's surface. The propensity of oxidized mercury species to transition between these two phases is described by the partitioning coefficient (K p ). Experimental measurements of K p values for HgCl 2 in the presence of atmospheric aerosols are difficult and time-consuming. Quantum chemical calculations, therefore, offer a promising opportunity to efficiently estimate partitioning coefficients for HgCl 2 on relevant aerosols. In this study, density functional theory (DFT) calculations are used to predict K p values for HgCl 2 on relevant iron-oxide surfaces. The model is first verified using a NaCl(100) surface, showing good agreement between the calculated (2.8) and experimental (29–43) dimensionless partitioning coefficients at room temperature. Then, the methodology is applied to six atmospherically relevant terminations of α-Fe 2 O 3 (0001): OH-Fe-R, (OH) 3 -Fe-R, (OH) 3 -R, O-Fe-R, Fe-O 3 -R, and O 3 -R (where R denotes bulk ordering). The OH-Fe-R termination is predicted to be the most stable under typical atmospheric conditions, and on this surface termination, a dimensionless HgCl 2 K p value of 5.2 x 10 3 at 295 K indicates a strong preference for the particle phase. Here this work demonstrates DFT as a promising approach to obtain partitioning coefficients, which can lead to improved models for the transport of mercury, as well as for other atmospheric pollutant species, through and between the anthroposphere and troposphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Shallow-circuit variational quantum eigensolver based on symmetry-inspired Hilbert space partitioning for quantum chemical calculations

Development of resource-friendly quantum algorithms remains highly desirable for noisy intermediate-scale quantum computing. Based on the variational quantum eigensolver (VQE) with unitary coupled-cluster Ansatz, we demonstrate that partitioning of the Hilbert space made possible by the point-group symmetry of the molecular systems greatly reduces the number of variational operators by confining the variational search within a subspace. In addition, we found that instead of including all subterms for each excitation operator, a single-term representation suffices to reach required accuracy for various molecules tested, resulting in an additional shortening of the quantum circuit by a factor of 4–8. With these strategies, VQE calculations on a noise-free quantum simulator achieve energies within a few meVs of those obtained with the full unitary coupled-cluster Ansatz with single and double excitations for the H 4 -square, H 4 -chain, and H 6 -hexagon molecules, while the number of cnot gates, a measure of the quantum-circuit depth, is reduced by a factor of as large as 35. Furthermore, we introduced an efficient “score” parameter to rank the excitation operators, so that the operators causing larger energy reduction can be applied first. Using the H 4 square and H 4 chain as examples, We demonstrated on noisy quantum simulators that the first few variational operators can bring the energy within the chemical accuracy, while additional operators do not improve the energy since the accumulative noise outweighs the gain from the expansion of the variational Ansatz.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Quantum Chemical Calculation of p K a s of Environmentally Relevant Functional Groups: Carboxylic Acids, Amines, and Thiols in Aqueous Solution

Developing accurate quantum chemical approaches for calculating p K a s is of broad interest. Useful accuracy can be obtained by using density functional theory (DFT) in combination with a polarizable continuum solvent model. However, some classes of molecules present problems for this approach, yielding errors greater than 5 p K units. Various methods have been developed to improve the accuracy of the combined strategy. These methods perform well but either do not generalize or introduce additional degrees of freedom, increasing the computational cost. The Solvation Model based on Density (SMD) has emerged as one of the most commonly used continuum solvent models. Nevertheless, for some classes of organic compounds, e.g., thiols, the p K a s calculated with the original SMD model show errors of 6–10 p K units, and we traced these errors to inaccuracies in the solvation free energies of the anions. To improve the accuracy of p K a s calculated with DFT and the SMD model, we developed a scaled solvent-accessible surface approach for constructing the solute–solvent boundary. By using a “direct” approach, in which all quantities are computed in the presence of the continuum solvent, the use of thermodynamic cycles is avoided. Furthermore, no explicit water molecules are required. Three benchmark data sets of experimentally measured p K a values, including 28 carboxylic acids, 10 aliphatic amines, and 45 thiols, were used to assess the optimized SMD model, which we call SMD with a scaled solvent-accessible surface (SMD sSAS ). Of the methods tested, the M06-2X density functional approximation, 6-31+G(d,p) basis set, and SMD sSAS solvent model provided the most accurate p K a s for each set, yielding mean unsigned errors of 0.9, 0.4, and 0.5 p K units, respectively, for carboxylic acids, aliphatic amines, and thiols. As a result, this approach is therefore useful for efficiently calculating the p K a s of environmentally relevant functional groups.

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

Towards a Description of the Ground State Properties of LiHm Complexes and Reaction Energetics of Hydrogenation of Small Li Clusters using VQE-based Quantum Chemical Calculations

<span style="font-family: Roboto; font-size: 11pt;">This presentation describes the utilization of the variational quantum eigensolver (VQE) using a unitary coupled cluster with singles and doubles (UCCSD) ansatz to simulate a series of LiH</span><sub style="font-family: Roboto; font-size: 11pt;">n</sub><span style="font-family: Roboto; font-size: 11pt;"> molecules (n=1-3), including their singly charged ions. The performance is considered using a simulator by systematically increasing system size, providing data to compare against future VQE calculations. The predicted energy profiles are in semi-quantitative agreement with highly accurate CCSD/FCI methods.</span>

quantum computing↗
DOE OSTI2019

On Achieving High Accuracy in Quantum Chemical Calculations of 3 d Transition Metal-Containing Systems: A Comparison of Auxiliary-Field Quantum Monte Carlo with Coupled Cluster, Density Functional Theory, and Experiment for Diatomic Molecules

According to the article, the bond dissociation energies of a set of 44 3d transition metal-containing diatomics are computed with phaseless auxiliary-field quantum Monte Carlo (ph-AFQMC) utilizing a correlated sampling technique. We investigate molecules with H, N, O, F, Cl, and S ligands, including those in the 3dMLBE20 database first compiled by Truhlar and co-workers with calculated and experimental values that have since been revised by various groups. In order to make a direct comparison of the accuracy of our ph-AFQMC calculations with previously published results from 10 DFT functionals, CCSD(T), and icMR-CCSD(T), we establish an objective selection protocol which utilizes the most recent experimental results except for a few cases with well-specified discrepancies. With the remaining set of 41 molecules, we find that ph-AFQMC gives robust agreement with experiment superior to that of all other methods, with a mean absolute error (MAE) of 1.4(4) kcal/mol and maximum error of 3(3) kcal/mol (parentheses account for reported experimental uncertainties and the statistical errors of our ph-AFQMC calculations). In comparison, CCSD(T) and B97, the best performing DFT functional considered here, have MAEs of 2.8 and 3.7 kcal/mol, respectively, and maximum errors in excess of 17 kcal/mol (for the CoS diatomic). While a larger and more diverse data set would be required to demonstrate that ph-AFQMC is truly a benchmark method for transition metal systems, our results indicate that the method has tremendous potential, exhibiting unprecedented consistency and accuracy compared to other approximate quantum chemical approaches.

Chemistry↗
DOE OSTI2023

Multi-level parallelization of quantum-chemical calculations

Here, strategies for multiple-level parallelizations of quantum-mechanical calculations are discussed, with an emphasis on using groups of workers for performing parallel tasks. These parallel programming models can be used for a variety ab initio quantum chemistry approaches, including the fragment molecular orbital method and replica-exchange molecular dynamics. Strategies for efficient load balancing on problems of increasing granularity are introduced and discussed. A four-level parallelization is developed based on a multi-level hierarchical grouping, and a high parallel efficiency is achieved on the Theta supercomputer using 131 072 OpenMP threads.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1981

Quantum chemical calculation of the equilibrium structures of small metal atom clusters

The application of ab initio quantum mechanical approaches in the study of metal atom clusters requires simplifying techniques that do not compromise the reliability of the calculations. Various aspects of the implementation of the effective core potential (ECP) technique for the removal of the metal atom core electrons from the calculation were examined. The ECP molecular integral formulae were modified to bring out the shell characteristics as a first step towards fulfilling the increasing need to speed up the computation of the ECP integrals. Work on the relationships among the derivatives of the molecular integrals that extends some of the techniques pioneered by Komornicki for the calculation of the gradients of the electronic energy was completed and a formulation of the ECP approach that quite naturally unifies the various state-of-the-art "shape- and Hamiltonian-consistent" techniques was discovered.

Kahn, L. R.↗
NASA NTRS1982

Quantum chemical calculation of the equilibrium structures of small metal atom clusters

Metal atom clusters are studied based on the application of ab initio quantum mechanical approaches. Because these large 'molecular' systems pose special practical computational problems in the application of the quantum mechanical methods, there is a special need to find simplifying techniques that do not compromise the reliability of the calculations. Research is therefore directed towards various aspects of the implementation of the effective core potential technique for the removal of the metal atom core electrons from the calculations.

Kahn, L. R.↗
DOE OSTI2018

Accurate geometries for “Mountain pass” regions of the Ramachandran plot using quantum chemical calculations

Unusual local arrangements of protein in Ramachandran space are not well represented by standard geometry tools used in either protein structure refinement using simple harmonic geometry restraints or in protein simulations using molecular mechanics force fields. In contrast, quantum chemical computations using small poly-peptide molecular models can predict accurate geometries for any well-defined backbone Ramachandran orientation. Additionally, for conformations along transition regions-$\phi$ from -60 to 60°-a very good agreement with representative high-resolution experimental X-ray (≤1.5 Å) protein structures is obtained for both backbone C -1 -N-C α angle and the nonbonded O -1 …C distance, while "standard geometry" leads to the "clashing" of O…C atoms and Amber FF99SB predicts distances too large by about 0.15 Å. These results confirm that quantum chemistry computations add valuable support for detailed analysis of local structural arrangements in proteins, providing improved or missing data for less understood high-energy or unusual regions.

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

An initial investigation of accuracy required for the identification of small molecules in complex samples using quantum chemical calculated NMR chemical shifts

The majority of primary and secondary metabolites in nature have yet to be identified, representing a major challenge for metabolomics studies that currently require reference libraries from analyses of authentic compounds. Using currently available analytical methods, complete chemical characterization of metabolomes is infeasible for both technical and economic reasons. For example, unambiguous identification of metabolites is limited by the availability of authentic chemical standards, which, for the majority of molecules, do not exist. Computationally predicted or calculated data are a viable solution to expand the currently limited metabolite reference libraries, if such methods are shown to be sufficiently accurate. For example, determining nuclear magnetic resonance (NMR) spectroscopy spectra in silico has shown promise in the identification and delineation of metabolite structures. Many researchers have been taking advantage of density functional theory (DFT), a computationally inexpensive yet reputable method for the prediction of carbon and proton NMR spectra of metabolites. However, such methods are expected to have some error in predicted 13 >C and 1 H NMR spectra with respect to experimentally measured values. This leads us to the question–what accuracy is required in predicted 13 C and 1 H NMR chemical shifts for confident metabolite identification? Using the set of 11,716 small molecules found in the Human Metabolome Database (HMDB), we simulated both experimental and theoretical NMR chemical shift databases. We investigated the level of accuracy required for identification of metabolites in simulated pure and impure samples by matching predicted chemical shifts to experimental data. We found 90% or more of molecules in simulated pure samples can be successfully identified when errors of 1 H and 13 C chemical shifts in water are below 0.6 and 7.1 ppm, respectively, and below 0.5 and 4.6 ppm in chloroform solvation, respectively. In simulated complex mixtures, as the complexity of the mixture increased, greater accuracy of the calculated chemical shifts was required, as expected. However, if the number of molecules in the mixture is known, e.g., when NMR is combined with MS and sample complexity is low, the likelihood of confident molecular identification increased by 90%.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗