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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 217 records · Page 12

Probing radical–molecule interactions with a second generation energy decomposition analysis of DFT calculations using absolutely localized molecular orbitals

Intermolecular interactions between radicals and closed-shell molecules are ubiquitous in chemical processes, ranging from the benchtop to the atmosphere and extraterrestrial space. While energy decomposition analysis (EDA) schemes for closed-shell molecules can be generalized for studying radical–molecule interactions, they face challenges arising from the unique characteristics of the electronic structure of open-shell species. In this work, we introduce additional steps that are necessary for the proper treatment of radical–molecule interactions to our previously developed unrestricted Absolutely Localized Molecular Orbital (uALMO)-EDA based on density functional theory calculations. A “polarize-then-depolarize” (PtD) scheme is used to remove arbitrariness in the definition of the frozen wavefunction, rendering the ALMO-EDA results independent of the orientation of the unpaired electron obtained from isolated fragment calculations. The contribution of radical rehybridization to polarization energies is evaluated. It is also valuable to monitor the wavefunction stability of each intermediate state, as well as their associated spin density profiles, to ensure the EDA results correspond to a desired electronic state. The examples suggest that this second generation uALMO-EDA is a useful tool for furthering one's understanding of both energetic and property changes associated with radical–molecule interactions.

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Splitting of multiple hydrogen molecules by bioinspired diniobium metal complexes: a DFT study

Splitting of molecular hydrogen (H 2 ) into bridging and terminal hydrides is a common step in transition metal chemistry. In this paper, we propose a novel organometallic platform for cleavage of multiple H 2 molecules, which combines metal centers capable of stabilizing multiple oxidation states, and ligands bearing positioned pendant basic groups. Using quantum chemical modeling, we show that low-valent, early transition metal diniobium(II) complexes with diphosphine ligands featuring pendant amines can favorably uptake up to 8 hydrogen atoms, and that the energetics are favored by the formation of intramolecular dihydrogen bonds. This result suggests new possible strategies for the development of hydrogen scavenger molecules that are able to perform reversible splitting of multiple H 2 molecules.

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Synthesis, crystal structure, EPR, and DFT studies of an unusually distorted vanadium(ii) complex

We report the synthesis and structure of the most highly distorted four-coordinate d 3 ion known to date that also serves as the second known example of a bis(biphenolato) transition metal complex. We demonstrate the application of density functional theory to calculate the magnetic parameters derived from the experimental and simulated EPR spectra.

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Detection of multi-reference character imbalances enables a transfer learning approach for virtual high throughput screening with coupled cluster accuracy at DFT cost

Appropriately identifying and treating molecules and materials with significant multi-reference (MR) character is crucial for achieving high data fidelity in virtual high-throughput screening (VHTS). Despite development of numerous MR diagnostics, the extent to which a single value of such a diagnostic indicates the MR effect on a chemical property prediction is not well established. We evaluate MR diagnostics for over 10 000 transition-metal complexes (TMCs) and compare to those for organic molecules. We observe that only some MR diagnostics are transferable from one chemical space to another. By studying the influence of MR character on chemical properties (i.e., MR effect) that involve multiple potential energy surfaces (i.e., adiabatic spin splitting, ΔE H–L , and ionization potential, IP), we show that differences in MR character are more important than the cumulative degree of MR character in predicting the magnitude of an MR effect. Motivated by this observation, we build transfer learning models to predict CCSD(T)-level adiabatic ΔE H–L and IP from lower levels of theory. By combining these models with uncertainty quantification and multi-level modeling, we introduce a multi-pronged strategy that accelerates data acquisition by at least a factor of three while achieving coupled cluster accuracy (i.e., to within 1 kcal mol –1 MAE) for robust VHTS.

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