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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Nature of Electronically Excited States of Furocoumarins

A comprehensive study of spectral-luminescent and photophysical properties of coumarin sensitizers is performed using the methods of quantum chemistry, electron spectroscopy, and fluorescence. A comparative study of photophysical processes occurring in 8-methoxypsoralen (8-MOP) and 4,9-dimethoxy-7-methylfuro [3,2-g][1] benzofuran-5-1 (khellin) is performed using the quantum-chemical software package based on the semi-empirical method of intermediate neglect of differential overlap with original spectroscopic parameterization. The dependences of the fluorescent properties and reactivity of the compounds on the geometry and composition of the solvation shell of molecules are established. It is shown that incorporation of additional methoxy groups in the structure of molecules has the strongest effect on the spectral-luminescent characteristics of khellin compared with 8-MOP.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Continuum Electrostatics Approaches to Calculating pKas and Ems in Proteins

Proteins change their charge state through protonation and redox reactions as well as through binding charged ligands. The free energy of these reactions are dominated by solvation and electrostatic energies and modulated by protein conformational relaxation in response to the ionization state changes. Although computational methods for calculating these interactions can provide very powerful tools for predicting protein charge states, they include several critical approximations of which users should be aware. This chapter discusses the strengths, weaknesses, and approximations of popular computational methods for predicting charge states and understanding their underlying electrostatic interactions. The goal of this chapter is to inform users about applications and potential caveats of these methods as well as outline directions for future theoretical and computational research.

biomolecules↗
DOE OSTI2026

Actinium–DOTA coordination in water from hybrid ML/MM: Structure, free energies, and water-exchange pathways

Quantitative simulation of trivalent ƒ-block chelates in water remains challenging because bonded and non-bonded force-field models make different approximations for coordination structure, exchange dynamics, and ion–ligand interactions in highly charged systems. Here, we develop a hybrid machine-learning/molecular-mechanics (ML/MM) framework for Ac 3+ –DOTA in explicit solvent by training an E(3)-equivariant neural network potential (MACELES) on mechanically embedded QM/MM data for Ac aquo and Ac–DOTA species and coupling it to NAMD 2.14 with particle-mesh Ewald electrostatics. Nanosecond ML/MM trajectories remain numerically stable and preserve chelate integrity, yielding a compact DOTA inner shell with an inner-sphere water coordination number of CN Ac,O w ≈ 1.7 arising from a dynamic equilibrium between one- and two-water states (37.5% and 59.9% of frames; three waters 2.5%). A 5 ns potential of mean force shows two low-lying basins at CN Ac,O w ≈ 1 and CN Ac,O w ≈ 2. DFT end-state free energies are consistent with the ML/MM profile, and DFT minimum-energy paths provide a qualitative electronic-structure reference for the observed basin connectivity. State-resolved kinetics reveal picosecond water-exchange pathways that couple hydration changes to transient DOTA arm fluctuations, and training-set comparisons show that temperature-matched Ac–DOTA data optimize energy/force accuracy while more diverse solvated data improve charge prediction. Overall, the present hybrid ML/MM model provides a practical description of Ac 3+ –DOTA hydration thermodynamics and short-time exchange behavior in explicit water at MD-like cost.

Actinium↗
DOE OSTI2017

Crystal structure and thermodynamic dissection of chitin oligosaccharide binding to the LysM module of chitinase-A from Pteris ryukyuensis

Highlights: • Crystal structure of a LysM module from Pteris ryukyuensis chitinase-A (PrLysM2) was determined at a resolution of 1.8 Å. • LysM module recognizes chitin oligosaccharides in a shallow groove on the molecule. • Thermodynamic dissection of the binding energetics of (GlcNAc){sub 6} to PrLysM2 was carried out. • The binding site comprises of five sugar-binding subsites. We determined the crystal structure of a LysM module from Pteris ryukyuensis chitinase-A (PrLysM2) at a resolution of 1.8 Å. Structural and binding analysis of PrLysM2 indicated that this module recognizes chitin oligosaccharides in a shallow groove comprised of five sugar-binding subsites on one side of the molecule. The free energy changes (ΔG{sub r}°) for binding of (GlcNAc){sub 6}, (GlcNAc){sub 5}, and (GlcNAc){sub 4} to PrLysM2 were determined to be −5.4, −5,4 and −4.6 kcal mol{sup −1}, respectively, by ITC. Thermodynamic dissection of the binding energetics of (GlcNAc){sub 6} revealed that the driving force is the enthalpy change (ΔH{sub r}° = −11.7 ± 0.2 kcal/mol) and the solvation entropy change (−TΔS{sub solv}° = −5.9 ± 0.6 kcal/mol). This is the first description of thermodynamic signatures of a chitin oligosaccharide binding to a LysM module.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Ion-specific effects influencing the dissolution of tricalcium silicate

It has been recently demonstrated that the dissolution kinetics of tricalcium silicate (C{sub 3}S) is driven by the deviation from its solubility equilibrium. In this article, special attention is paid to ions relevant in cement chemistry likely to interact with C{sub 3}S. In order to determine whether specific effects occur at the interface C{sub 3}S–water, particular efforts have been made to model ion activities using Pitzer's model. It has been found that monovalent cations and monovalent anions interact very little with the surface of C{sub 3}S. On the other side, divalent anions like sulfate slow down the dissolution more strongly by modifying the surface charging of C{sub 3}S. Third, aluminate ions covalently bind to surface silicate monomers and inhibit the dissolution in mildly alkaline conditions. The formation and the breaking of these bonds depend on pH and on [Ca{sup 2+}]. Thermodynamic calculations performed using DFT combined with the COSMO-RS solvation method support the experimental findings.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Modeling of aqueous species interaction energies prior to nucleation in cement-based gel systems

Arguably the most ubiquitous construction material in modern civilization, concrete is enabling the development of megacities around the globe together with increasing living standards in developing nations. However, the exact formation mechanisms of the strength-giving calcium-rich gels remain a topic of debate. Using density functional modeling, we simulate the fundamental solution-based building blocks of cement hydrates (calcium ions and silicate and aluminate monomers) and their propensity to form pair-wise complexes with bonding environments characteristic of those found in calcium-silicate-hydrate, calcium-alumino-silicate-hydrate and sodium-containing calcium-alumino-silicate-hydrate gels, as assessed from Gibbs free energies of chemical reactions. By accurately simulating the high pH pore solution chemistry in Portland cements and related systems, along with discrete solvation of the species, we hypothesize potential early age formation routes of the gels and discuss limitations and future work associated with this approach.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Solid-state interphases design for high-safety, high-voltage and long-cyclability practical batteries via ethylene carbonate-free electrolytes

In this study, ethylene carbonate (EC) plays a crucial role in current electrolytes for batteries. However, EC reacts exothermically with the electrode to trigger thermal runaway and undergoes continuous oxidative decomposition at high voltages, hindering it application for next-generation batteries. Here we report a simple and effective strategy to design sulfolane(SL)-based electrolyte with reshaped anions-dominated solvation structure, forming highly stable inorganic-dominated electrode-electrolyte interphases that efficiently stabilize nickel-rich cathode and graphite anode. Compared with the conventional electrolyte, practical pouch-type LiNi 0.8 Co 0.1 Mn 0.1 O 2 |Graphite cell with SL-based electrolyte significantly improve self-generated heat T 1 and thermal runaway triggering T 2 by 9.6 and 42.0 °C, respectively. More surprisingly, the pouch cell with SL-based electrolyte exhibits outstanding capacity retention of 88 % after 1000 cycles charged up to 4.5 V. The study brings new insights for unlocking advanced electrolyte candidates to build next-generation practical safer high-energy batteries.

25 ENERGY STORAGE↗
DOE OSTI2014

Diffusion-controlled reactions modeling in Geant4-DNA

Context Under irradiation, a biological system undergoes a cascade of chemical reactions that can lead to an alteration of its normal operation. There are different types of radiation and many competing reactions. As a result the kinetics of chemical species is extremely complex. The simulation becomes then a powerful tool which, by describing the basic principles of chemical reactions, can reveal the dynamics of the macroscopic system. To understand the dynamics of biological systems under radiation, since the 80s there have been on-going efforts carried out by several research groups to establish a mechanistic model that consists in describing all the physical, chemical and biological phenomena following the irradiation of single cells. This approach is generally divided into a succession of stages that follow each other in time: (1) the physical stage, where the ionizing particles interact directly with the biological material; (2) the physico-chemical stage, where the targeted molecules release their energy by dissociating, creating new chemical species; (3) the chemical stage, where the new chemical species interact with each other or with the biomolecules; (4) the biological stage, where the repairing mechanisms of the cell come into play. This article focuses on the modeling of the chemical stage. Method This article presents a general method of speeding-up chemical reaction simulations in fluids based on the Smoluchowski equation and Monte-Carlo methods, where all molecules are explicitly simulated and the solvent is treated as a continuum. The model describes diffusion-controlled reactions. This method has been implemented in Geant4-DNA. The keys to the new algorithm include: (1) the combination of a method to compute time steps dynamically with a Brownian bridge process to account for chemical reactions, which avoids costly fixed time step simulations; (2) a k–d tree data structure for quickly locating, for a given molecule, its closest reactants. The performance advantage is presented in terms of complexity, and the accuracy of the new algorithm is demonstrated by simulating radiation chemistry in the context of the Geant4-DNA project. Application The time-dependent radiolytic yields of the main chemical species formed after irradiation are computed for incident protons at different energies (from 50 MeV to 500 keV). Both the time-evolution and energy dependency of the yields are discussed. The evolution, at one microsecond, of the yields of hydroxyls and solvated electrons with respect to the linear energy transfer is compared to theoretical and experimental data. According to our results, at high linear energy transfer, modeling radiation chemistry in the trading compartment representation might be adopted.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Understanding fluorine-free electrolytes via small-angle X-ray scattering

Fluorine-free electrolytes have attracted great attention because of its low-cost and environmental friendliness. However, so far, little is known about the solution structures of these electrolytes. Here, we compare the solvation phenomenon of sodium tetraphenylborate (NaBPh 4 ) salt dissolved in organic solvents of propylene carbonate (PC), 1,2-dimethoxyethane (DME), acetonitrile (ACN) and tetrahydrofuran (THF). Small-angle X-ray scattering (SAXS) reveals a unique two-peak structural feature in this salt concentrated PC electrolyte, while solutions using other solvents only have one scattering peak. Molecular dynamics (MD) simulations further reveal that there are anion-based clusters in addition to the short-range charge ordering in the concentrated NaBPh4/PC electrolyte. Raman spectroscopy confirms the existence of considerable contact ion pairs (CIPs). Here, this work emphasizes the importance of global and local structural analysis, which will provide valuable clues for understanding the structure performance relationship of electrolytes.

25 ENERGY STORAGE↗
DOE OSTI2014

Stability of the solid electrolyte Li{sub 3}OBr to common battery solvents

Graphical abstract: The stability of the anti-perovskite phase Li{sub 3}OBr has been assessed in a variety of battery solvents. - Highlights: • Lithium stable solid electrolyte Li{sub 3}OBr unstable to polar organic solvents. • Solvation with no dissolution destroys long-range structure. • Ion exchange with protons observed. - Abstract: Recently a new class of solid lithium ion conductors was reported based on the anti-perovskite structure, notably Li{sub 3}OCl and Li{sub 3}OBr. For many beyond lithium-ion battery uses, the solid electrolyte is envisioned to be in direct contact with liquid electrolytes and lithium metal. In this study we evaluated the stability of the Li{sub 3}OBr phase against common battery solvents electrolytes, including diethylcarbonate (DEC) and dimethylcarbonate (DMC), as well as a LiPF{sub 6} containing commercial electrolyte. In contact with battery-grade organic solvents, Li{sub 3}OBr was typically found to be insoluble but lost its crystallinity and reacted with available protons and in some cases with the solvent. A low temperature heat treatment was able to restore crystallinity of the samples; however evidence of proton ion exchange was conserved.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Dielectric relaxation of neodymium chloride in water and in methanol

In this work, an open-ended coaxial probe was used to study the dielectric relaxation of neodymium chloride (NdCl 3 ) in water and in methanol at room temperature over the frequency range 0.2–40.0 GHz. An equivalent circuit model based on the antenna model was used to obtain the dielectric spectra with the effective removal of spurious effects. This extends the use of the open-ended coaxial probe technique for highly conductive substances. The structural and thermodynamic parameters obtained from the dielectric spectra of aqueous NdCl 3 solutions suggest that solvent-separated ion pairs and solvent-shared ion pairs dominate the low-frequency behavior at low concentrations. In methanol, solvent-shared ion pair relaxation modes were detected. No contact pair relaxation was observed in either solvent. Under all conditions, Nd 3+ was strongly solvated, as reflected by its high effective hydration number. The estimated association constant of NdCl 3 in water at infinite dilution was within the literature values and was lower than that observed in methanol.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

JDFTx: Software for joint density-functional theory

Density-functional theory (DFT) has revolutionized computational prediction of atomic-scale properties from first principles in physics, chemistry and materials science. Continuing development of new methods is necessary for accurate predictions of new classes of materials and properties, and for connecting to nano- and mesoscale properties using coarse-grained theories. JDFTx is a fully-featured open-source electronic DFT software designed specifically to facilitate rapid development of new theories, models and algorithms. Using an algebraic formulation as an abstraction layer, compact C++11 code automatically performs well on diverse hardware including GPUs (Graphics Processing Units). This code hosts the development of joint density-functional theory (JDFT) that combines electronic DFT with classical DFT and continuum models of liquids for first-principles calculations of solvated and electrochemical systems. In addition, the modular nature of the code makes it easy to extend and interface with, facilitating the development of multi-scale toolkits that connect to ab initio calculations, e.g. photo-excited carrier dynamics combining electron and phonon calculations with electromagnetic simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Delamination mechanism study of large size waste printed circuit boards by using dimethylacetamide

Highlights: • Dimethylacetamide (DMA) dissolved the epoxy resin of printed circuit boards (WPCB). • PCBs of 1, 4, 9 and 16 cm{sup 2} were delaminated in 150, 180, 300 and 420 min, respectively. • Peaks of epoxy resin and DMA were evident in the NMR spectra. • Shift in C=O, OH peaks of DMA & resin, respectively was registered w.r.t. time. • Hydrogen bonding between C=O of DMA and OH of resin results in the dissolution. - Abstract: Present work investigates the recycling of waste printed circuit boards (PCBs) by cracking of its multi-layered structure by using dimethylacetamide (DMA). The study shows that cracking and separation of layers of PCBs increases as the temperature increases; and decreases as the surface area of PCBs increases. After separation of layers, the used solvent was analyzed by proton and carbon nuclear magnetic resonance spectroscopy (NMR) to understand the dissolution phenomenon of resin. Further, NMR and Fourier transform infrared spectroscopy analysis of DMA sample after 1 h, 2 h, 3 h, 4 h and 8 h of reaction with PCBs at 433 K and PCB:DMA ratio (wt/vol) of 3:10 has been carried out to investigate the mechanism of dissolution of resin. These studies revealed that hydroxyl group of PCBs polymeric chain participates in hydrogen bonding with parent carbonyl group of DMA molecule that results in the solvation of resin. Possible chemical reaction based on the above finding has been discussed. Using this technique, separation of the metallic fraction without application of any energy intensive mechanical pre-processing is possible.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Discovery of Energy Storage Molecular Materials Using Quantum Chemistry-Guided Multiobjective Bayesian Optimization

Redox flow batteries (RFBs) are a promising technology for stationary energy storage applications due to their flexible design, scalability, and low cost. In RFBs, energy is carried in flowable redoxactive materials (redoxmers) which are stored externally and pumped to the cell during operation. Further improvements in the energy density of RFBs necessitates redoxmer designs with wider redox potential windows and higher solubility. Additionally, designing redoxmers with a fluorescence-enabled self-reporting functionality allows monitoring of the state of health of RFBs. To accelerate the discovery of redoxmers with desired properties, state-of-the- art machine learning ( ML) methods, such as multiobjective Bayesian optimization (MBO), are useful. Here, we first employed density functional theory calculations to generate a database of reduction potentials, solvation free energies, and absorption wavelengths for 1400 redoxmer molecules based on a 2,1,3-benzothiadiazole (BzNSN) core structure. From the computed properties, we identified 22 Pareto-optimal molecules that represent best trade-off among all of the desired properties. We further utilized these data to develop and benchmark an MBO approach to identify candidates quickly and efficiently with multiple targeted properties. With MBO, optimal candidates from the 1400-molecule data set can be identified at least 15 times more efficiently compared to the brute force or random selection approach. Importantly, we utilized this approach for discovering promising redoxmers from an unseen database of 1 million BzNSN-based molecules, where we discovered 16 new Pareto-optimal molecules with significant improvements in properties over the initial 1400 molecules. Furthermore, we anticipate that this active learning technique is general and can be utilized for the discovery of any class of functional materials that satisfies multiple desired property criteria.

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

Reconciling Work Functions and Adsorption Enthalpies for Implicit Solvent Models: A Pt (111)/Water Interface Case Study

Implicit solvent models are a computationally efficient method of representing solid/liquid interfaces prevalent in electrocatalysis, energy storage, and materials science. However, electronic structure changes induced at the metallic surface by the dielectric continuum are not fully understood. To address this, we perform DFT calculations for the Pt(111)/water interface, in order to compare Poisson–Boltzmann continuum solvation methods with ab initio molecular dynamics (AIMD) simulations of explicit solvent. We show that the implicit solvent cavity can be parametrized in terms of the electric dipole moment change at the equilibrated explicit Pt/water interface to obtain the potential of zero charge (PZC). We also compare the accuracy of aqueous enthalpies of adsorption of phenol on Pt(111) using geometry and charge density based dielectric cavitation methods. The ability to parametrize the cavity according to individual atoms, as afforded in the geometry based approach, is key to obtaining accurate enthalpy changes of adsorption under aqueous conditions. Additionally, we show that the electronic structure changes induced by explicit solvent and our proposed implicit solvent parametrization scheme yield comparable density difference profiles and d-band projected density of states. We therefore demonstrate the capability of implicit solvent approaches to capture both the energetics of adsorption processes and the main electronic effects of aqueous solvent on the metallic surface. Therefore, this work provides a scheme for computationally efficient simulations of interfacial processes for applications in areas such as heterogeneous catalysis and electrochemistry.

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

Minimal Experimental Bias on the Hydrogen Bond Greatly Improves Ab Initio Molecular Dynamics Simulations of Water

Experiment Directed Simulations (EDS) is a method within a class of techniques seeking to improve molecular simulations by minimally biasing the system Hamiltonian to reproduce certain experimental observables. In a previous application of EDS to ab initio molecular dynamics (AIMD) simulation based on electronic density functional theory (DFT), the AIMD simulations of water were biased to reproduce its experimentally derived solvation structure. In particular, by solely biasing the O-O pair correlation functions, other structural and dynamical properties that were not biased were improved. In this work, the hypothesis is tested that directly biasing the OH pair correlation (and hence the H-O∙∙∙H hydrogen bonding), will provide an even better improvement of DFT-based water properties in AIMD simulations. The logic behind this hypothesis is that for most electronic DFT descriptions of water the hydrogen bonding is known to be deficient due to anomalous charge transfer and over polarization in the DFT. Using recent advances to the EDS learning algorithm, we thus train a minimal bias on AIMD water that reproduces the O-H radial distribution function derived from the highly accurate MB-pol model of water. Finally, it is then confirmed that biasing the O-H pair correlation alone can lead to improved AIMD water properties, with structural and dynamical properties in even closer to experiment than the previous EDS-AIMD model.

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

Nuclear–Electronic Orbital QM/MM Approach: Geometry Optimizations and Molecular Dynamics

Hybrid quantum mechanical/molecular mechanical (QM/MM) methods allow simulations of chemical reactions in atomistic solvent and heterogeneous environments such as proteins. Herein, the nuclear–electronic orbital (NEO) QM/MM approach is introduced to enable the quantization of specified nuclei, typically protons, in the QM region using a method such as NEO-density functional theory (NEO-DFT). This approach includes proton delocalization, polarization, anharmonicity, and zero-point energy in geometry optimizations and dynamics. Expressions for the energies and analytical gradients associated with the NEO-QM/MM method, as well as the previously developed polarizable continuum model (NEO-PCM), are provided. Geometry optimizations of small organic molecules hydrogen bonded to water in either dielectric continuum solvent or explicit atomistic solvent illustrate that aqueous solvation can strengthen hydrogen-bonding interactions for the systems studied, as indicated by shorter intermolecular distances at the hydrogen-bond interface. We then performed a real-time direct dynamics simulation of a phenol molecule in explicit water using the NEO-QM/MM method. Furthermore, these developments and initial examples provide the foundation for future studies of nuclear–electronic quantum dynamics in complex chemical and biological environments.

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

Hybrid Quantum Mechanical, Molecular Mechanical, and Machine Learning Potential for Computing Aqueous-Phase Adsorption Free Energies on Metal Surfaces

Performing reliable computer simulations of elementary processes occurring at metal–water interfaces is pivotal for novel catalyst design in sustainable energy applications. Computational catalyst design hinges on the ability to reliably and efficiently compute the potential energy surface (PES) of the system. Here, due to the large system sizes needed for studying processes at liquid water–metal interfaces, these systems can currently not be described using density functional theory (DFT). In this work, we used a hybrid quantum mechanical, molecular mechanical, and machine learning potential for studying the adsorption behavior of phenol, atomic hydrogen, 2-butanol, and 2-butanone on the (0001) facet of Ru under reducing conditions when Ru is not oxidized. Specifically, we describe the adsorbate and the surrounding metal atoms at the DFT level of theory. Here, we also considered the electrostatic field effect of the water molecules on adsorbate–metal interactions. Next, for the water–water and water–adsorbate interactions, we used established classical force fields. Finally, for the water–Ru surface interaction, for which no reliable force fields have been published, we used Behler–Parrinello high-dimensional neural network potentials (HDNNPs). Employing this setup, we used our explicit solvation for metal surface (eSMS) approach to compute the aqueous-phase effect on the low-coverage adsorption of selected molecules and atoms on the (0001) facet of Ru. In agreement with previous experimental and computational studies of oxygenated molecules over transition metal facets, we found that liquid water destabilizes the tested adsorbates on Ru(0001). Interestingly, our findings indicate that adsorbates on Ru are less affected by the presence of an aqueous phase than on other transition metals (e.g., Pt), highlighting the necessity of experimental investigations of Ru-based catalytic systems in liquid water.

Adsorption↗