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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Adaptive Variational Quantum Imaginary Time Evolution Approach for Ground State Preparation

Abstract An adaptive variational quantum imaginary time evolution (AVQITE) approach is introduced that yields efficient representations of ground states for interacting Hamiltonians on near‐term quantum computers. It is based on McLachlan's variational principle applied to imaginary time evolution of variational wave functions. The variational parameters evolve deterministically according to equations of motions that minimize the difference to the exact imaginary time evolution, which is quantified by the McLachlan distance. Rather than working with a fixed variational ansatz, where the McLachlan distance is constrained by the quality of the ansatz, the AVQITE method iteratively expands the ansatz along the dynamical path to keep the McLachlan distance below a chosen threshold. This ensures the state is able to follow the quantum imaginary time evolution path in the system Hilbert space rather than in a restricted variational manifold set by a predefined fixed ansatz. AVQITE is used to prepare ground states of H 4 , H 2 O, and BeH 2 molecules, where it yields compact variational ansätze and ground state energies within chemical accuracy. Polynomial scaling of circuit depth with system size is shown through a set of AVQITE calculations of quantum spin models. Finally, quantum Lanczos calculations are demonstrated alongside AVQITE without additional quantum resource costs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Uncovering the mechanism of selective stabilization of high-energy diastereoisomers via inclusion

Abstract Supramolecular systems may be used to stabilize otherwise unstable isomers to find alternative synthetic pathways. It has been reported that cucurbit[8]uril can stabilize trans -I and trans -II Cu $$^{{\textrm{II}}}$$ II cyclam, whereas trans -III is the only non-substituted trans Cu $$^{{\textrm{II}}}$$ II cyclam diastereoisomer found outside of the host molecule experimentally. Quantum chemistry methods can provide valuable insight into the intermolecular interactions involved in these inclusion complexes. All five possible trans diastereoisomers of Cu $$^{{\textrm{II}}}$$ II cyclam were studied within the host molecule to calculate the interaction energy and free energy of association for each complex. The relative free energies of the five free cyclams confirm that trans -I and trans -II are the most energetically accessible diastereoisomers from the initial trans -III starting point. Energy decomposition analysis was used to identify the attractive and repulsive interactions between cyclam and cucurbit[8]uril and showed that trans -II encounters repulsive forces almost three times greater than trans -I, which may explain the 7:3 ratio of trans -I to trans -II within cucurbit[8]uril that occurs experimentally. Optimized complex geometries with trans -III, IV, and V show that the cyclams protrude out of cucurbit[8]uril, whereas trans -I and trans -II become more encapsulated and elongate the host, suggesting that the position of the cyclam is extremely important when forming non-covalent interactions. Our results agree with the experimental findings and provide greater insight into why the most stable isolated cyclam diastereoisomer, trans -III, does not form a complex.

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

Review of computational approaches to predict the thermodynamic stability of inorganic solids

Improvements in the efficiency and availability of quantum chemistry codes, supercomputing centers, and open materials databases have transformed the accessibility of computational materials design approaches. Thermodynamic stability predictions play a central role in the efficacy of these approaches and should be considered carefully. This review covers the fundamentals of calculating thermodynamic stability using first-principles methods. Stability is delineated into two main topics — stability with respect to decomposition into competing phases and stability with respect to phase transition into alternative structures at fixed composition. For each topic, a summary of the state-of-the-art is provided along with a tutorial overview of practical considerations. The application of machine learning to both kinds of stability predictions is also covered. Finally, the limitations of thermodynamic stability predictions are discussed within the context of predicting the synthesizability of materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A Stochastic Quasi-Newton Method in the Absence of Common Random Numbers

We present Q-SASS, a quasi-Newton method for unconstrained stochastic optimization that does not rely on common random numbers. Most existing quasi-Newton approaches leverage common random numbers to construct second-order updates. However, motivated by challenges in variational quantum algorithms—where such coordination is not possible—we consider the setting in which function values and gradients are accessible only through noisy probabilistic zeroth- and first-order oracles, and no common random numbers can be exploited. We derive high-probability tail bounds on the iteration complexity of our algorithm for nonconvex, convex, and strongly convex (more generally, those satisfying the PL condition) objective functions. Finally, we demonstrate the empirical benefits of our quasi-Newton updating scheme on both synthetic and quantum chemistry problems.

Complexity bound↗
DOE OSTI2026

Mixed-precision numerics in scientific applications: survey and perspectives

The explosive demand for artificial intelligence (AI) workloads has led to a significant increase in silicon area dedicated to lower-precision computations on recent high-performance computing hardware designs. However, mixed-precision capabilities, which can achieve performance improvements of up to 8x compared to double-precision in extreme compute-intensive workloads, remain largely untapped in most scientific applications. A growing number of efforts have shown that mixed-precision algorithmic innovations can deliver superior performance without sacrificing accuracy. These developments should prompt computational scientists to seriously consider whether their scientific modeling and simulation applications could benefit from the acceleration offered by new hardware and mixed-precision algorithms. In this survey, we (1) review progress across diverse scientific domains—fluid dynamics, weather and climate, quantum chemistry, and computational genomics—that have begun adopting mixed-precision strategies; (2) examine state-of-the-art algorithmic techniques such as iterative refinement, splitting and emulation schemes, and adaptive precision solvers; (3) assess their implications for accuracy, performance, and resource utilization; and (4) survey the emerging software ecosystem that enables mixed-precision methods at scale. We conclude with perspectives and recommendations on cross-cutting opportunities, domain-specific challenges, and the role of co-design between application scientists, numerical analysts, and computer scientists. Collectively, this survey underscores that mixed-precision numerics can reshape computational science by aligning algorithms with the evolving landscape of hardware capabilities.

Graphics processing units↗
DOE OSTI2022

A workflow for automatic generation and efficient refinement of individual pressure-dependent networks

Manual chemical kinetic model construction often requires modelists to at least implicitly guess all possible decay pathways and their relative fluxes for all important species. We present a workflow and associated tool for automatic generation and re finement of pressure-dependent networks that should enable modelists to efficiently and comprehensively identify decay pathways and estimate respective parameters for chemical species. This tool combines the capabilities of the Reaction Mechanism Generator (RMG) software to generate possible reaction paths, determine thermochemistry, approximate rate coefficients and estimate frequencies with the capabilities of the Arkane software to use quantum chemical parameters to compute thermochemistry and pressure dependent rates. A flux-based algorithm is used to decide which isomers to add to the network. Isomers added to the network are reacted to form other channels. When enough of the flux is accounted for by the isomers and bimolecular product channels, the generation process terminates to yield a comprehensive network. Network sensitivity analysis is applied to the network to identify the most important wells and barriers that can be refined using quantum chemistry calculations. Iterative refinement can then be used to achieve accuracy. The comprehensive network can be easily reduced using energy and flux-based algorithms to the most important channels and isomers in the network.

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

IrRep: Symmetry eigenvalues and irreducible representations of ab initio band structures

Here, we present IrRep – a Python code that calculates the symmetry eigenvalues of electronic Bloch states in crystalline solids and the irreducible representations under which they transform. As input it receives bandstructures computed with state-of-the-art Density Functional Theory codes such as VASP, Quantum Espresso, or Abinit, as well as any other code that has an interface to Wannier90. Our code is applicable to materials in any of the 230 space groups and double groups preserving time-reversal symmetry with or without spin-orbit coupling included, for primitive or conventional unit cells. This makes IrRep a powerful tool to systematically analyze the connectivity and topological classification of bands, as well as to detect insulators with non-trivial topology, following the Topological Quantum Chemistry formalism: IrRep can generate the input files needed to calculate the (physical) elementary band representations and the symmetry-based indicators using the [CheckTopologicalMat: https://www.cryst.ehu.es/cgi-bin/cryst/programs/magnetictopo.pl] routine of the Bilbao Crystallographic Server. It is also particularly suitable for interfaces with other plane-waves based codes, due to its flexible structure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

The kinetics of the reactions of ground-state NH with N 2 O and implications for ammonia combustion

Quantum chemistry and canonical transition state theory have been applied to derive rate constants k for reactions of 3 Σ − imidogen with nitrous oxide. 3 channels were quantified. The fastest leads to NNH+NO and may be summarized as k = 2.8 × 10 7 T 1.68 exp.(−23.1 kcal mol −1 /RT) cm 3 mole −1 s −1 . Two much slower pathways lead to N 2 + 3 HNO and spin-forbidden 1 HNO. Modeling of literature data, from an NH 3 /O 2 flame and jet-stirred reactor measurements on dilute NH 3 /N 2 O mixtures, with the new kinetic information suggests that these channels are too slow to consume N 2 O significantly, and confirms that a widely used proposed rate constant for NH+N 2 O overestimates the reactivity.

Marshall, Paul [University of North Texas, Denton,↗
DOE OSTI2020

Controllable depolymerization of lignin using carbocatalyst graphene oxide under mild conditions

Many efforts have been devoted to depolymerizing lignin to high-value aromatic monomers. However, a controllable and complete lignin inter-unit bond cleavage remains difficult because of the randomness in lignin structure and low selectivity in catalysis. Herein, we demonstrate that a sole carbocatalyst graphene oxide (GO) can selectively oxidize aryl- and alkyl-hydroxyl groups of lignin without the presence of any additional oxidizers, leading to lignin degradation under mild conditions. The results from lignin dimers, lignin oligomers, and organosolv lignin indicate that the depolymerization is catalyzed via an oxidative mechanism through an enol ether intermediate, a stable intermediate that has been chemically isolated here. Quantum chemistry calculations at the density functional theory level indicate that the phenolic –OH group in lignin facilitates the formation of radical cations and thus prohibits ring opening reactions, leading to the complete conversion of lignin dimers to guaiacol through the enol ether intermediate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Atmospheric clusters to nanoparticles: Recent progress and challenges in closing the gap in chemical composition

Aerosol nanoclusters (AN), defined here as molecular aggregates suspended in a gas with dimensions between 2 and 10 nm, are the link between substances that we think of as molecules, or the “gas phase,” and those that we consider as particles, or the “condensed phase.” The ability to measure and model the physical and chemical properties of size-resolved AN, which at present is rudimentary at best, is crucial for understanding how particles form and evolve in a number of environments that are natural or influenced by human activities. This review describes the current state-of-the-art for measuring and modeling the size-resolved composition of atmospheric AN. We focus specifically on instruments, many relying on mass spectrometry, that show promise for closing the measurement gap under atmospherically relevant conditions by increasing the size of measurable gas-phase clusters (bottom-up approaches) and by decreasing the size of measurable nanoparticles (top-down approaches). Theoretical methods for predicting AN composition have similarly relied on bottom-up approaches that extend the accuracy of quantum chemistry calculations to larger molecular systems, as well as top-down approaches that correct bulk composition aerosol models for size-dependent properties such as viscosity and volatility. Finally, current measurement and modeling challenges that must be overcome in order to close the gap are discussed.

42 ENGINEERING↗
DOE OSTI2024

Characterization of lignin-degrading enzyme PmdC, which catalyzes a key step in the synthesis of polymer precursor 2-pyrone-4,6-dicarboxylic acid

Pyrone-2,4-dicarboxylic acid (PDC) is a valuable polymer precursor that can be derived from the microbial degradation of lignin. The key enzyme in the microbial production of PDC is 4-carboxy-2-hydroxymuconate-6-semialdehyde (CHMS) dehydrogenase, which acts on the substrate CHMS. We present the crystal structure of CHMS dehydrogenase (PmdC from Comamonas testosteroni) bound to the cofactor NADP, shedding light on its three-dimensional architecture, and revealing residues responsible for binding NADP. Using a combination of structural homology, molecular docking, and quantum chemistry calculations, we have predicted the binding site of CHMS. Key histidine residues in a conserved sequence are identified as crucial for binding the hydroxyl group of CHMS and facilitating dehydrogenation with NADP. Mutating these histidine residues results in a loss of enzyme activity, leading to a proposed model for the enzyme's mechanism. These findings are expected to help guide efforts in protein and metabolic engineering to enhance PDC yields in biological routes to polymer feedstock synthesis.

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

The microwave spectra of the conformers of $\mathcal{n}$-butyl nitrate

We report the microwave spectrum of n-butyl nitrate was recorded in the 5 to 20 GHz frequency range using broadband chirp and narrowband pulse excitation molecular jet Fourier transform microwave spectrometers. A quantum chemistry structural analysis yielded thirteen stable conformers. Among them, the five most energetically stable conformers were observed in the experimental spectra. The most stable conformer features a butyl chain with an anti-gauche-anti conformation (AGA) where the γ-carbon atom is about 64° out of the nitrate plane. For this conformer, spectra of all 13 C and 15 N minor isotopologues could be measured. The conformer with a straight butyl chain (AAA), and three other conformers (GAA, GGA, and AGG) were also observed. Accurate rotational constants, centrifugal distortion constants, and 14 N nuclear quadrupole coupling constants could be deduced and compared to the theoretical values.

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

Persistent radicals in irradiated imidazolium ionic liquids probed by EPR spectroscopy

Long-lived radicals were observed in irradiated room temperature ionic liquids (RTILs) composed of the bis(trifluoromethylsulfonyl)imide anion (Tf 2 N - ) with 1-hexyl-3-methylimidazolium (hmim + ) and1-butyl-3-methylimidazolium (bmim+) cations. The EPR signal intensity increases within hours and the spectral pattern changes during the time after irradiation. The kinetics data obtained indicate the existence of at least two distinct radical cations that have different formation and decay rates. We demonstrate that oxygen does not react rapidly with the radical species formed. The bmim + Tf 2 N - was selectively deuterated at various positions which allowed us to suggest possible structures of the stable radicals formed. The first structure is a radical cation containing 2 nitrogens and 6 protons all with ca. 8.2 Gauss hyperfine splittings, and 2 protons with 2.8 Gauss splitting. The structure of the second radical cation is similar, but characterized by an odd number of hydrogens with ca. 8.2 Gauss splitting. Extensive quantum chemistry calculations were performed to attempt to identify the structure of these persistent radicals. The most likely candidates are imidazole radical cations having methyl groups at the nitrogen atoms and substituents in the second position of the imidazole ring.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Facile Oxidation of Ce(III) to Ce(IV) Using Cu(I) Salts

The synthesis, luminescence, and electrochemical properties of the Ce(III) compound, [(C 5 Me 5 )2(2,6- i Pr 2 C 6 H 3 O)Ce(THF)], 1, were investigated. Based on the electrochemical data, treatment of 1 with CuX (X = Cl, Br, I) results in the formation of the corresponding Ce(IV) complexes, [(C 5 Me 5 ) 2 (2,6- i Pr 2 C 6 H 3 O)Ce(X)]. Each complex has been characterized using NMR, IR, and UV−vis spectroscopy as well as structurally determined using X-ray crystallography. Additionally, the treatment of [(C 5 Me 5 ) 2 (2,6- i Pr 2 C 6 H 3 O)Ce(Br)] with AgF results in the formation of the putative [(C 5 Me 5 ) 2 (2,6- i Pr 2 C 6 H 3 O)Ce(F)]. Furthermore, the electronic structure of these Ce(IV)−X complexes was investigated by bond analyses and the Ce(IV)−F moiety using quantum chemistry NMR calculations.

Aromatic compounds↗
DOE OSTI2021

InteraChem: Virtual Reality Visualizer for Reactive Interactive Molecular Dynamics

Interactive molecular dynamics in virtual reality (IMD-VR) simulations provide a digital molecular playground for students as an alternative or complement to traditional molecular modeling kits or 2D illustrations. Previous IMD-VR studies have used molecular mechanics to enable simulations of macromolecules such as proteins and nanostructures for the classroom setting with considerable success. Here, we present the InteraChem molecular visualizer, intended for reactive IMD-VR simulation using semiempirical and ab initio methods. InteraChem visualizes not only the molecular geometry but also (1) isosurfaces such as molecular orbitals and electrostatic potentials and (2) two-dimensional graphs of time-varying simulation quantities such as kinetic/potential energy, internal coordinates, and user-applied force. Additionally, InteraChem employs speech recognition to facilitate user interaction and introduces a novel “atom happiness” visualization using emojis to indicate the energetic feasibility of a particular bonding arrangement. Furthermore, we include a set of accompanying exercises that we have used to teach chemical reactivity in small molecular systems.

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

Simplifying the Quantum World: Demonstrations for Young Learners in an Informal Setting

A set of modules for the informal learning of quantum science was developed. They include (1) Waves and Bottling Light in Quantum Dots, (2) Quantization of Energy Levels, (3) Particle-Wave Duality, (4) Magnetism and Electron Spin, and (5) Quantum Entanglement. Their teaching objective is to clarify concepts in quantum science, and they have been presented together as part of an hour-long show to ∼250 adults and school-age children. The learning outcomes of the modules were assessed by pre- and postevent quizzes as well as interactive clicker questions. The results suggest effective learning of all of the assessed concepts. These modules are detailed in a way that makes them deployable, together or in part, in other formal or informal settings to support the dissemination of information about quantum science to the general public.

electron spin↗
DOE OSTI2023

Multifidelity Neural Network Formulations for Prediction of Reactive Molecular Potential Energy Surfaces

Here, this paper focuses on the development of multifidelity modeling approaches using neural network surrogates, where training data arising from multiple model forms and resolutions are integrated to predict high-fidelity response quantities of interest at lower cost. We focus on the context of quantum chemistry and the integration of information from multiple levels of theory. Important foundations include the use of symmetry function-based atomic energy vector constructions as feature vectors for representing structures across families of molecules and single-fidelity neural network training capabilities that learn the relationships needed to map feature vectors to potential energy predictions. These foundations are embedded within several multifidelity topologies that decompose the high-fidelity mapping into model-based components, including sequential formulations that admit a general nonlinear mapping across fidelities and discrepancy-based formulations that presume an additive decomposition. Methodologies are first explored and demonstrated on a pair of simple analytical test problems and then deployed for potential energy prediction for C 5 H 5 using B2PLYP-D3/6-311++G(d,p) for high-fidelity simulation data and Hartree–Fock 6-31G for low-fidelity data. For the common case of limited access to high-fidelity data, our computational results demonstrate that multifidelity neural network potential energy surface constructions achieve roughly an order of magnitude improvement, either in terms of test error reduction for equivalent total simulation cost or reduction in total cost for equivalent error.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗