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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
DOE OSTI2023

The Structural Characterisation and DFT-Aided Interpretation of Vibrational Spectra for Cyclo(l-Cys-d-Cys) Cyclic Dipeptide in a Solid State

Cyclic dipeptides with two intramolecular peptide bonds forming a six-membered 2,5-diketopiperazine ring are gaining significant attention due to their biological and chemical properties. Small changes in the local geometry of such molecules (from cis to trans) can lead to significant structural differences. This work presents the results of a study of cyclo(l-Cys-d-Cys), a dipeptide comprising two cysteine molecules in opposite chiral configurations, with the functional groups situated at both sides of the diketopiperazine ring. X-ray diffraction (XRD) experiment revealed that the molecule crystallises in the $P$-1 space group, which includes the centre of inversion. The IR and Raman vibrational spectra of the molecule were acquired and interpreted in terms of the potential energy distribution (PED) according to the results of density functional theory (DFT) calculations. The DFT-assisted analysis of energy frameworks for the hydrogen bond network within molecular crystals was performed to support the interpretation of X-ray structural data. The optimisation of the computational model based on three-molecule geometry sections from the crystallographic structure, selected to appropriately reflect the intermolecular interactions responsible for the formation of 1D molecular tapes in cyclo(l-Cys-d-Cys) crystal, allowed for better correspondence between theoretical and experimental vibrational spectra. This work can be considered the first complete structural characterisation of cyclo(l-Cys-d-Cys), complemented via vibrational spectroscopy results with full band assignment aided with the use of the DFT method.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Significant Efficiency Enhancements in Non‐Y Series Acceptors by the Addition of Outer Side Chains

Abstract Most current highly efficient organic solar cells utilize small molecules like Y6 and its derivatives as electron acceptors in the photoactive layer. In this work, a small molecule acceptor, SC8‐IT4F, is developed through outer side chain engineering on the terminal thiophene of a conjugated 6,12‐dihydro‐dithienoindeno[2,3‐d:2′,3′‐d′]‐s‐indaceno[1,2‐b:5,6‐b′]dithiophene (IDTT) central core. Compared to the reference molecule C8‐IT4F, which lacks outer side chains, SC8‐IT4F displays notable differences in molecule geometry (as shown by simulations), thermal behavior, single‐crystal packing, and film morphology. Blend films of SC8‐IT4F and the polymer donor PM6 exhibit larger carrier mobilities, longer carrier lifetimes, and reduced recombination compared to C8‐IT4F, resulting in improved device performance. Binary photovoltaic devices based on the PM6:SC8‐IT4F films reveal an optimal efficiency over 15%, which is one of the best values for non‐Y type small molecule acceptors (SMAs). The resultant devices also show better thermal and operational stability than the control PM6:L8‐BO devices. SC8‐IT4F and its blend exhibit a higher relative degree of crystallinity and π coherence length, compared to C8‐IT4F samples, beneficial for charge transport and device performance. The results indicate that outer side chain engineering on existing small electron acceptors can be a promising molecular design strategy for further pursuing high‐performance organic solar cells.

He, Qiao [Department of Chemistry and Centre for P↗
DOE OSTI2024

Geometry-complete diffusion for 3D molecule generation and optimization

Abstract Generative deep learning methods have recently been proposed for generating 3D molecules using equivariant graph neural networks (GNNs) within a denoising diffusion framework. However, such methods are unable to learn important geometric properties of 3D molecules, as they adopt molecule-agnostic and non-geometric GNNs as their 3D graph denoising networks, which notably hinders their ability to generate valid large 3D molecules. In this work, we address these gaps by introducing the Geometry-Complete Diffusion Model (GCDM) for 3D molecule generation, which outperforms existing 3D molecular diffusion models by significant margins across conditional and unconditional settings for the QM9 dataset and the larger GEOM-Drugs dataset, respectively. Importantly, we demonstrate that GCDM’s generative denoising process enables the model to generate a significant proportion of valid and energetically-stable large molecules at the scale of GEOM-Drugs, whereas previous methods fail to do so with the features they learn. Additionally, we show that extensions of GCDM can not only effectively design 3D molecules for specific protein pockets but can be repurposed to consistently optimize the geometry and chemical composition of existing 3D molecules for molecular stability and property specificity, demonstrating new versatility of molecular diffusion models. Code and data are freely available on GitHub .

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

Effective many-body interactions in reduced-dimensionality spaces through neural network models

Accurately describing properties of challenging problems in physical sciences often requires complex mathematical models that are unmanageable to tackle head on. Therefore, developing reduced-dimensionality representations that encapsulate complex correlation effects in many-body systems is crucial to advance the understanding of these complicated problems. However, a numerical evaluation of these predictive models can still be associated with a significant computational overhead. To address this challenge, in this paper we discuss a combined framework that integrates recent advances in the development of active-space representations of coupled cluster (CC) downfolded Hamiltonians with neural network approaches. The primary objective of this effort is to train neural networks to eliminate the computationally expensive steps required for evaluating hundreds or thousands of Hugenholtz diagrams, which correspond to multidimensional tensor contractions necessary for evaluating a many-body form of downfolded effective Hamiltonians. Using small molecular systems (the H 2 O and HF molecules) as examples, we demonstrate that training neural networks employing effective Hamiltonians for a few nuclear geometries of molecules can accurately interpolate or extrapolate their forms to other geometrical configurations characterized by different intensities of correlation effects. We also discuss differences between effective interactions that define CC downfolded Hamiltonians with those of bare Hamiltonians defined by Coulomb interactions in the active spaces. Published by the American Physical Society 2024

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

OrbNet Denali: A machine learning potential for biological and organic chemistry with semi-empirical cost and DFT accuracy

We present OrbNet Denali, a machine learning model for an electronic structure that is designed as a drop-in replacement for groundstate density functional theory (DFT) energy calculations. The model is a message-passing graph neural network that uses symmetryadapted atomic orbital features from a low-cost quantum calculation to predict the energy of a molecule. OrbNet Denali is trained on a vast dataset of 2.3 × 10 6 DFT calculations on molecules and geometries. This dataset covers the most common elements in biochemistry and organic chemistry (H, Li, B, C, N, O, F, Na, Mg, Si, P, S, Cl, K, Ca, Br, and I) and charged molecules. OrbNet Denali is demonstrated on several well-established benchmark datasets, and we find that it provides accuracy that is on par with modern DFT methods while offering a speedup of up to three orders of magnitude. For the GMTKN55 benchmark set, OrbNet Denali achieves WTMAD-1 and WTMAD-2 scores of 7.19 and 9.84, on par with modern DFT functionals. For several GMTKN55 subsets, which contain chemical problems that are not present in the training set, OrbNet Denali produces a mean absolute error comparable to those of DFT methods. For the Hutchison conformer benchmark set, OrbNet Denali has a median correlation coefficient of R 2 = 0.90 compared to the reference DLPNO-CCSD(T) calculation and R 2 = 0.97 compared to the method used to generate the training data (ωB97X-D3/def2- TZVP), exceeding the performance of any other method with a similar cost. Similarly, the model reaches chemical accuracy for noncovalent interactions in the S66x10 dataset. For torsional profiles, OrbNet Denali reproduces the torsion profiles of ωB97X-D3/def2-TZVP with an average mean absolute error of 0.12 kcal/mol for the potential energy surfaces of the diverse fragments in the TorsionNet500 dataset.

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

Utilizing Quantum Cascade Lasers for Ultranarrow Velocity Resolution and Quantum-State Selectivity in Molecular Beam Scattering and Spectroscopy

Here, we demonstrate the capability of a narrow linewidth quantum cascade laser (QCL) to selectively excite a very narrow velocity range of nitric oxide (σ ≤ 7(3) m/s) with a pure ro-vibrational quantum state. By implementing a counter-propagating geometry, the molecules are selectively excited according to the Doppler shift of the ro-vibrational transition frequency such that the velocity width associated with the excited molecules depends only on the QCL linewidth. We demonstrate a velocity distribution limited by the effective linewidth of our free-running QCL (Γ = 3.2 MHz). Our development provides a cost-effective, flexible approach to resolve quantum-state selective chemical dynamics with excellent velocity resolution in a wide variety of molecules with infrared-active transitions. This technique has been formulated to provide ultrahigh collisional energy resolution in molecular beams to delineate final quantum-state product pairs in studies of molecular collisions.

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

Single-Molecule Vibrational Characterization of Binding Geometry Effects on Isocyanide–Metal Interactions

Isocyanide−metal binding is governed by σ-donation and π-back-bonding, which affects the isocyanide stretching energy, a characteristic probe for ligand−metal interactions. While extensive correlations exist between structure and spectroscopy in molecular isocyanide−metal systems, interactions of isocyanide with crystalline metallic surfaces, where ligands often bind in various geometries, remain underexplored. Conventional vibrational spectroscopies such as infrared and Raman spectroscopies lack the molecular-scale resolution to distinguish this binding inhomogeneity. In contrast, inelastic electron tunneling spectroscopy with scanning tunneling microscopy (STM-IETS) directly visualizes ligand adsorption geometries and their vibrational signatures. Using STM-IETS, we investigate a metal-adsorbed m -terphenyl isocyanide ligand and find that the adsorption geometry on Cu(100) induces a significant shift in isocyanide stretching frequency, more prominent than replacing Cu(100) with Ag(111). Density functional theory confirms that this shift arises from atomic-scale variations in coordination environments. This study elucidates how precise binding influences the vibrational fingerprints of isocyanide ligands, an often-overlooked factor in understanding the isocyanide−metal interplay.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Studying f-Electron Contributions in Thorium and Uranium Containing Molecules

The pure rotational spectra of several actinide-containing compounds have been improved upon and, in two cases, been recorded for the first time. The diatomic molecules HfS and ThS have been studied in their ground electronic states but high vibrationally excited states. The results have yielded very accurate locations of the minima of the potential energy curves. The asymmetric molecules OThS and UO2S have been prepared by laser ablation synthesis and their pure rotational spectra recorded for the first time. Precise information pertinent to the geometric and electronic structure of these molecules has been obtained and is compared with other, newly recorded and related species such as OCeS.

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

Kohn-Sham Solver (KSSOLV) v2.0

KSSOLV is a MATLAB toolbox for solving Kohn-Sham density functional theory based electronic structure eigenvalue problems. It uses an object oriented features of MATLAB to represent atom, molecules, wavefunctions and Hamiltonians and their operations. It is designed to make it easier for users to prototype and test new algorithms for solving the Kohn-Sham problem. KSSOLV2.0 contains significant improvement over the original KSSOLV described in a paper published in ACM Transaction on Mathematical Software (attached). In addition to performing ground state calculation for small molecules, it can also perform geometry optimization for both molecules and solids. It uses standard pseudopotentials and implements local density approximation, generalized gradient approximation and hybrid functionals. Future releases will also include time-dependent DFT and post DFT calculations such as the GW quasi-particle energy calculation and Bethe-Salpeter equation solver for optical absorption.

Yang, Chao↗
DOE OSTI2025

All-electron molecular tunnel ionization based on the weak-field asymptotic theory in the integral representation

Tunnel ionization (TI) underlies many important ultrafast processes, such as high-harmonic generation andstrong-field ionization. Among the existing theories for TI, many-electron weak-field asymptotic theory (ME-WFAT) is by design capable of accurately treating many-electron effects in TI. An earlier version of ME-WFATrelied on an accurate representation of the asymptotic tail of the orbitals, which hindered its implementation inGaussian-basis-set-based quantum chemistry programs. In this work, we reformulate ME-WFAT in the integralrepresentation, which makes the quality of the asymptotic tail much less critical, hence greatly facilitating itsimplementation in standard quantum chemistry packages. The integral reformulation introduced here is thereforemuch more robust when applied to molecules with arbitrary geometry. Here, we present several case studies, amongwhich is the CO molecule where some earlier theories disagree with experiments. Here we find that ME-WFATproduces the largest ionization probability when the field points from C to O, as experiments suggest. Anattractive feature of ME-WFAT is that it can be used with various types of multielectron methods whether ofdensity functional or multiconfiguration types, this inturn facilitates tunnel ionization calculation in systems exhibiting a strong multireference character.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Two excited-state datasets for quantum chemical UV-vis spectra of organic molecules

Abstract We present two open-source datasets that provide time-dependent density-functional tight-binding (TD-DFTB) electronic excitation spectra of organic molecules. These datasets represent predictions of UV-vis absorption spectra performed on optimized geometries of the molecules in their electronic ground state. The GDB-9-Ex dataset contains a subset of 96,766 organic molecules from the original open-source GDB-9 dataset. The ORNL_AISD-Ex dataset consists of 10,502,904 organic molecules that contain between 5 and 71 non-hydrogen atoms. The data reveals the close correlation between the magnitude of the gaps between the highest occupied molecular orbital (HOMO) and the lowest unoccupied molecular orbital (LUMO), and the excitation energy of the lowest singlet excited state energies quantitatively. The chemical variability of the large number of molecules was examined with a topological fingerprint estimation based on extended-connectivity fingerprints (ECFPs) followed by uniform manifold approximation and projection (UMAP) for dimension reduction. Both datasets were generated using the DFTB+ software on the “Andes” cluster of the Oak Ridge Leadership Computing Facility (OLCF).

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

Mechanistic Advantages of Organotin Molecular EUV Photoresists

Here, extreme ultraviolet (EUV)-induced radiation exposure chemistry in organotin-oxo systems, represented by the archetypal [(R-Sn) 12 O 14 (OH) 6 ](A) 2 cage, has been investigated with density functional theory. Upholding existing experimental evidence of Sn-C cleavage-dominant chemistry, computations have revealed that either electron attachment or ionization can single-handedly trigger tin-carbon bond cleavage, partially explaining the current EUV sensitivity advantage of metal oxide systems. We have revealed that tin atoms at different parts of the molecule react differently to ionization and electron attachment and have identified such selectivity as a result of local coordination chemistry instead of the macro geometry of the molecule. An ionization-deprotonation pathway has also been identified to explain the observed evolution of an anion conjugate acid upon exposure and anion mass dependence in resist sensitivity.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2020

General Protocol for the Accurate Prediction of Molecular 13 C/ 1 H NMR Chemical Shifts via Machine Learning Augmented DFT

An accurate prediction of NMR chemical shifts at affordable computational cost is very important for different types of structural assignments in experimental studies. Density functional theory (DFT) and gauge-including atomic orbital (GIAO) are two of the most popular computational methods for NMR calculation, yet they often fail to resolve ambiguities in structural assignments. In this work, we present a new method that uses machine learning (ML) techniques (DFT + ML) that significantly increases the accuracy of 13 C/ 1 H NMR chemical shift prediction for a variety of organic molecules. The input of the generalizable DFT + ML model contains two critical parts: one is a vector providing insights into chemical environments, which can be evaluated without knowing the exact geometry of the molecule; the other one is the DFT-calculated isotropic shielding constant. The DFT + ML model was trained with a data set containing 476 13 C and 270 1 H experimental chemical shifts. For the DFT methods used here, the root mean square deviations (RMSDs) for the errors between predicted and experimental 13 C/ 1 H chemical shifts can be as small as 2.10/0.18 ppm, which is much lower than those from simple DFT (5.54/0.25 ppm), or DFT + linear regression (LR) (4.77/0.23 ppm) approaches. It also has a smaller maximum absolute error than two previously proposed NMR-predicting ML models. The robustness of the DFT + ML model is tested on two classes of organic molecules (TIC10 and hyacinthacines), where the correct isomers were unambiguously assigned to the experimental ones. Overall, the DFT + ML model shows promise for structural assignments in a variety of systems, including stereoisomers, that are often challenging to determine experimentally.

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

Understanding Fragmentation of Organic Small Molecules in Atom Probe Tomography

In atom probe tomography of molecular organic materials, field ionization of either entire molecules or molecular fragments can occur, but the mechanism governing this behavior was not previously understood. This work explains when a doubly ionized small molecule organic material is expected to undergo fragmentation. Here, we find that multiple detection events arising from post-ionization fragmentation of a parent molecular dication into two daughter ions is well explained by the free energy and geometries of the molecules computed using density functional theory. Of the systems studied, exergonic free energies for formation of the daughter ions, smaller activation energies for dissociation, and increases in bond length are all found to be quantitative predictors for ion fragmentation. This work expands the applicability of atom probe tomography to organic materials by increasing the fundamental understanding of processes occurring during this analysis technique.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Structural and Spectroscopic Analysis of Ln(II) 18-crown-6 and Benzo-18-crown-6 Complexes (Ln = Sm, Eu, Yb)

Three Ln 2+ 18-crown-6 complexes of the formula Ln(18-crown-6)I 2 (Ln = Sm, Eu, Yb) were isolated from the explicit synthesis of the corresponding LnI 2 salts with 18-crown-6 and tetrabutylammonium tetraphenylborate in organic media under air-free conditions. Each metal complex forms a distorted hexagonal bipyramidal geometry and crystallizes in the monoclinic space group P2 1 /n. Comparatively, crystallization of Ln(benzo-18-crown-6)I 2 (Ln = Sm, Eu, Yb) from the reaction of LnI2 with tetrabutylammonium tetraphenylborate and benzo-18-crown-6 in THF/ethanol under similarly air-free conditions yields two polymorphs. The first form, α, crystallizes in the monoclinic space group P2 1 /c (or the nonstandard setting P2 1 /n for α-Yb); whereas the second polymorph, β, crystallizes in P$\bar{1}$. While the geometries of the molecules only vary slightly, the molecular packing and intramolecular contacts are quite different. In the structure of β, π–π interactions between the benzo- moieties of adjacent molecules are observed, whereas these interactions are absent in α. Despite the similarities in these classically 4f n+1 lanthanide systems, the complexes display distinct spectroscopic features in their respective absorption and photoluminescence spectra. Broadband 5d → 4f photoluminescence was observed for the Sm and Eu compounds in the NIR region and UV–visible region, respectively. None of the three Yb compounds exhibit photoluminescence UV–visible-NIR region; however, a unique photooxidation event was observed resulting in characteristic Yb(III) 4f → 4f transitions in the NIR region of the absorption spectra of these compounds. Finally, these findings are discussed along with structural comparisons of the 18-crown-6 and benzo-18-crown-6 compounds as well as other reported Ln(II) crown complexes in the literature.

crystals↗
DOE OSTI2023

Linearized Pair-Density Functional Theory for Vertical Excitation Energies

Multiconfiguration pair-density functional theory (MC-PDFT) is a computationally efficient method that computes the energies of electronic states in a state specific or state average framework via an on-top functional. However, MC-PDFT does not include state interaction among these states since the final energies do not come from the diagonalization of an effective model-space Hamiltonian. Recently, multistate extensions such as linearized PDFT (L-PDFT) have been developed to accurately model the potentials near conical intersections and avoided crossings. However, there has not been any systematic study evaluating their performance for predicting vertical excitations at the equilibrium geometry of a molecule, when the excited states are generally well separated. In this paper, we report the performance of L-PDFT on the extensive QUESTDB data set of vertical excitations using a database of automatically selected active spaces. We show that L-PDFT performs well on all these excitations and successfully reproduces the performance of MC-PDFT. These results further demonstrate the potential of L-PDFT, as its scaling is constant with the number of states included in the state-average manifold, whereas MC-PDFT scales linearly in this regard.

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

Analysis of the bonding in tetrahedrane and phosphorus-substituted tetrahedranes

The bonding structures of tetrahedrane, phosphatetrahedrane, diphosphatetrahedrane and triphosphatetrahedrane are studied by employing an intrinsic quasi-atomic orbital analysis. Ethane, cyclopropane and tetrahedral P 4 are employed as reference systems. The orbital analysis is paired with the computation of strain energies via isodesmic reactions. The results show that the increase in geometric strain upon transition from ethane to cyclopropane to tetrahedrane weakens the CC bonds, despite leading to shorter C–C interatomic distances. With the increase in strain, the orbitals centered on C and involved in the bonding of the cage structure are observed to have elevated p-character, and the orbital structure of C deviates from sp 3 hybridization. The systematic substitution of CH groups by P atoms in the cage structure of tetrahedrane leads to stronger CC bonds, larger angles in the cage structures of the resulting phosphatetrahedranes, lower p-character in the orbitals involved in the bonding of the cages, and lower strain energies. It is found that P is more amenable to strained molecular arrangements than is C, and that the propensity of a given atom to hybridize s and p functions, or the lack thereof, has implications in the stability of molecules with strained geometries. The combination of the calculations presented here with the existing literature provides insight into the apparent propensity of tetrahedrane and P 4 to ‘break’ their tetrahedral structures. Trends in the bonding interactions, such as bond strengths, s- and p-orbital characters and charge transfer are identified and related to the strain energy observed in each of the analyzed systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗