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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Gas-phase ion-molecule interactions in a collision reaction cell with triple quadrupole-inductively coupled plasma mass spectrometry: Investigations with N 2 O as the reaction gas

Nitrous oxide (N 2 O) was used as a reaction gas to investigate the gas phase ion-molecule interactions using the Agilent 8900 QQQ-ICP-MS. A multi-element standard containing 45 elements with masses ranging from 9 to 208 u was measured in the presence and absence of N 2 O. The main product ion species observed were oxides and nitrides. Comparison of the N 2 O reaction results with similar measurements conducted with O 2 revealed that N 2 O was more effective at forming oxides in general: the elements Cd and Pb were shown to produce oxides with N 2 O where the reaction did not occur with O 2 . Nitrous oxide was also shown to produce a significant amount of nitride species in a few cases. The general reactivity was shown to be consistent with density functional theory (DFT)-predicted reaction enthalpies, such that all predicted exothermic reactions produced product ions at levels at least 1% of the unreacted ion. Our results show that reaction enthalpy is a reasonable predictor of reactivity with N2O on the timescales of the interactions in non-thermal ICP-MS/MS systems. Our work demonstrates the utility of two relatively new platforms (commercial elemental ICP-MS/MS and EMSL Arrows interface to the NWChem program suite), which allows for the study of a large number of elements within a short period. While DFT with the basis sets utilized here is not the most accurate computational method, it is also not computationally expensive and is shown to be suitable for predicting gas phase reactivity in the QQQ-ICP-MS for the majority of ions studied. Here, the ease and rapidity of data collection and DFT calculations has the potential to be very impactful for the identification of targeted reaction chemistries to be leveraged for analytical method development, such as for the inline separation of isobaric interferences from analytes of interest.

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

Description of global EGAM in the maximum of local frequency during current ramp-up discharges in DIII-D

Energetic-particle-induced geodesic acoustic modes, EGAMs (Fu, Phys. Rev. Let., vol. 101, 2008, pp. 185002), driven by neutral beam injection (NBI), have been observed in many DIII-D tokamak experiments (Nazikian et al., Phys. Rev. Lett., vol. 101, 2008, pp. 185001). This mechanism has been theoretically investigated in (Qiu et al., Plasma Phys. Control. Fusion, vol. 52, 2010, pp. 095003), using a sharp energetic particle distribution function, and in (Qu et al., Plasma Phys. Control. Fusion, vol. 59, 2017, pp. 055018), where the dispersion relation and eigenmode behaviour were obtained for the situation of early beam scenario, that is, for times smaller than the beam slowing down time. In this work, we extend these studies determining the eigenmode for beyond the slowing down time, in a scenario with reverse safety factor q profile, where a small concentration of energetic ions can produce an off-axis maximum in the GAM dispersion relation. Here, the characteristics of EGAM are analytically studied with the drift kinetic equation together with the MHD code NOVA. The toroidal energetic ion transit frequency, coupled with the GAM frequency, produces the maximum in the dispersion relation where the eigenmode can be found. The quantitative correspondence of experimental results with the predictions of the proposed model is analysed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Designing Sequence-Defined Peptoids for Biomimetic Control over Inorganic Crystallization

Crystallization defines what the world is all about, ranging from biomineralization in living organisms to various materials in our lives. During these processes, biomineralization set a superexcellent example of the additive-controlled crystallization. However, the high complexity and low stability of peptides and proteins preclude their wide applications in controlling inorganic crystallization beyond the biological systems. Peptoids are one type of sequence-defined biomimetic polymers with a simple structure, high stability, protein-like molecular recognition, and distinctive self-assembly properties. They provide a promising alternative to mimic peptides and proteins for controlling inorganic crystallization and extend its application to predictive materials synthesis. In this review article, we extract the main concepts of peptoid engineering and highlight the recent advances in peptoid-controlled inorganic crystallization. Our focus is to understand the principles of sequence engineering that lead to the predictable physiochemical properties of these substances, which will give insights into other inorganic systems.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Computationally Accelerated Discovery of High Entropy Pyrochlore Oxides

High entropy ceramics provide enhanced flexibility for tailoring a wide range of physical properties, emerging from the diverse chemical and configurational degrees of freedom. Expanding upon the endeavors of recently synthesized high entropy ceramics in rock salt, fluorite, spinel, and perovskite structures, we explore the relative feasibility of formation of high entropy pyrochlore oxides, A 2 B 2 O 7 , with multication occupancy of the B-site, estimated from first-principles-based thermodynamic descriptors. Subsequently, we used Monte Carlo simulations to estimate the phase composition, oxygen vacancy concentration, and local ionic segregation as a function of temperature and oxygen partial pressure. In synergy with the theoretical calculations, we have investigated the synthesis of several multicomponent oxides with a pyrochlore composition, related to our computational investigations, resulting in four phase pure and one 97.4% pure high entropy pyrochlore oxides. Ultimately, our approach allows us to evaluate potential impurity phases, ionic disorder, and oxygen vacancy concentration in response to the experimental variables, thereby making realistic predictions that can direct and accelerate experimental synthesis of novel multicomponent ceramics.

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

Exploration, Prediction, and Experimental Verification of Structure and Optoelectronic Properties in I 2 -Eu-IV-X 4 (I = Li, Cu, Ag; IV = Si, Ge, Sn; X = S, Se) Chalcogenide Semiconductors

Recently, there has been extensive research into photovoltaic, thermoelectric, and nonlinear optical applications of chalcogenide semiconductors within the large set of defect-resistant I 2 -II-IV-X4 (I = Li, Cu, Ag; II = Ba, Sr, Eu, Pb; IV = Si, Ge, Sn; X = S, Se) compounds. Five Eu-including compounds have previously been reported within this family, but a comparative study of possible structures and electronic properties of all 18 Eu-based combinations is still absent. Herein, we use hybrid density functional theory to study rare-earth-including I 2 -II-IV-X 4 semiconductors with Eu on the II site, in order to further understand this family and test the geometric tolerance factor approach (reported in our previous work) as a tool for predicting potential stable structures. We investigate how the exchange mixing parameter of the HSE06 density functional, α, affects the energetic positions of electronic levels, especially of the localized f-electron orbitals near the band edges of the extended semiconductor structures, using literature photoemission and band gap data of EuS for comparison. Lowest-energy quaternary structure candidates, energy band structures, and densities of states are computationally predicted for all 18 materials. Based on its predicted photovoltaics-relevant band gap, the previously unknown compound Cu 2 EuSnSe 4 was selected and synthesized. Furthermore, the experimental structure, lattice parameters, and band gap of Cu 2 EuSnSe 4 are consistent with the computational predictions, confirming a 1.55 eV band gap.

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

Phosphine Ligand Binding and Catalytic Activity of Group 10–14 Heterobimetallic Complexes

We report heterobimetallic complexes have attracted much interest due to their broad range of structures and reactivities as well as unique catalytic abilities. Additionally, these complexes can be utilized as single-source precursors for the synthesis of binary intermetallic compounds. An example is the family of bis(pyridine-2-thiolato)dichloro-germanium and tin complexes of group 10 metals (Pd and Pt). The reactivity of these heterobimetallic complexes is highly tunable through substitution of the group 14 element and the neutral ligand bound to the transition metal. Here, we study the binding energies of three different phosphorous-based ligands, PR 3 (R = Bu, Ph, and OPh) by density functional theory and restricted Hartree–Fock methods. The PR 3 ligand-binding energies follow the trend of PBu 3 > PPh 3 > P(OPh) 3 , in agreement with their sigma-bonding ability. These results are confirmed by ligand exchange experiments monitored with 31 P NMR spectroscopy, in which a weaker binding PR 3 ligand is replaced with a stronger one. Furthermore, we demonstrate that the heterobimetallic complexes are active catalysts in the Negishi coupling reaction, where stronger binding PR 3 ligands inhibit access to an active site at the metal center. Similar strategies could be applied to other complexes to better understand their ligand-binding energetics and predict their reactivity as both precursors and catalysts.

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

Creation of Polymer Datasets with Targeted Backbones for Screening of High-Performance Membranes for Gas Separation

A simple approach was developed to computationally construct a polymer dataset by combining simplified molecular-input line-entry system (SMILES) strings of a targeted polymer backbone and a variety of molecular fragments. This method was used to create 14 polymer datasets by combining seven polymer backbones and molecules from two large molecular datasets (MOSES and QM9). Polymer backbones that were studied include four polydimethylsiloxane (PDMS) based backbones, poly(ethylene oxide) (PEO), poly(allyl glycidyl ether) (PAGE), and polyphosphazene (PPZ). The generated polymer datasets can be used for various cheminformatics tasks, including high-throughput screening for gas permeability and selectivity. This study utilized machine learning (ML) models to screen the polymers for CO2/CH4 and CO2/N2 gas separation using membranes. Several polymers of interest were identified. Here the results highlight that employing an ML model fitted to polymer selectivities leads to higher accuracy in predicting polymer selectivity compared to using the ratio of predicted permeabilities.

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

Nonempirical Range-Separated Hybrid Functional with Spatially Dependent Screened Exchange

Electronic structure calculations based on density functional theory (DFT) have successfully predicted numerous ground-state properties of a variety of molecules and materials. However, exchange and correlation functionals currently used in the literature, including semilocal and hybrid functionals, are often inaccurate to describe the electronic properties of heterogeneous solids, especially systems composed of building blocks with large dielectric mismatch. Here, in this study, we present a dielectric-dependent range-separated hybrid functional, screened-exchange range-separated hybrid (SE-RSH), for the investigation of heterogeneous materials. We define a spatially dependent fraction of exact exchange inspired by the static Coulomb-hole and screened-exchange (COHSEX) approximation used in many-body perturbation theory, and we show that the proposed functional accurately predicts the electronic structure of several nonmetallic interfaces, three- and two-dimensional, pristine, and defective solids and nanoparticles.

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

Accurate Prediction of Adiabatic Ionization Potentials of Organic Molecules using Quantum Chemistry Assisted Machine Learning

In previous work (Dandu et al., J. Phys. Chem. A, 2022, 126, 4528–4536), we were successful in predicting accurate atomization energies of organic molecules using machine learning (ML) models, obtaining an accuracy as low as 0.1 kcal/mol compared to the G4MP2 method. In this work, we extend the use of these ML models to adiabatic ionization potentials on data sets of energies generated using quantum chemical calculations. Atomic specific corrections that were found to improve atomization energies from quantum chemical calculations have also been used in this study to improve ionization potentials. Here, the quantum chemical calculations were performed on 3405 molecules containing eight or fewer non-hydrogen atoms derived from the QM9 data set, using the B3LYP functional with the 6–31G(2df,p) basis set for optimization. Low-fidelity IPs for these structures were obtained using two density functional methods: B3LYP/6–31+G(2df,p) and ωB97XD/6–311+G(3df,2p). Highly accurate G4MP2 calculations were performed on these optimized structures to obtain high-fidelity IPs to use in ML models based on the low-fidelity IPs. Our best performing ML methods gave IPs of organic molecules within a mean absolute deviation of 0.035 eV from the G4MP2 IPs for the whole data set. This work demonstrates that ML predictions assisted by quantum chemical calculations can be used to successfully predict IPs of organic molecules for use in high throughput screening.

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

Thermodynamics–Structure–Dynamics Correlations and Nonuniversal Effects in the Elastically Collective Activated Hopping Theory of Glass-Forming Liquids

We employ the microscopic Elastically Collective Nonlinear Langevin Equation (ECNLE) theory of activated dynamics in combination with crystal-avoiding simulations to study four inter-related questions for metastable monodisperse hard sphere fluids. The first is how significantly improved integral equation theory structural input (Modified-Verlet (MV) closure) changes the dynamical predictions of ECNLE theory. The main consequence is a modest enhancement of the importance of the collective elastic barrier relative to its local cage contribution, which increases the alpha relaxation time and fragility relative to prior results based on the Percus–Yevick closure. Second, ECNLE-MV theory predictions for the alpha time and self-diffusion constant in the metastable regime are quantitatively compared to our new simulations. The small adjustment of a numerical prefactor that enters the collective elastic barrier leads to quantitative agreement over three decades. Third, using the more accurate MV structural input, ECNLE theory is shown to predict thermodynamics–structure–dynamics “correlations” based on various long and short wavelength scalar properties all related to static two-point collective density fluctuations. The logarithm of the alpha relaxation time scales as a power law with these scalar metrics with an exponent that is significantly lower in the less dense noncooperative activated regime compared to the very dense highly cooperative regime. However, the discovered correlation of activated relaxation with a thermodynamic property (dimensionless compressibility) is not causal in ECNLE theory, but rather reflects a strong connection between the local structural quantities that quantify kinetic constraints in the theory with the amplitude of long wavelength density fluctuations. Fourth, the consequences of chemically specific nonuniversalities associated with the onset condition and relative importance of collective elasticity are studied. In conclusion, the predicted thermodynamics–structure–dynamics correlations are found to be robust, albeit with nontrivial shifts of the onset condition.

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

Unraveling Electronic Trends in O* and OH* Surface Adsorption in the MO 2 Transition-Metal Oxide Series

Understanding the bond strength of O* and OH* intermediates to metal-oxide surfaces is key to predicting the catalytic activity in oxygen-based electrochemistry. Here, we uncover highly non-linear trends in O* and OH* adsorption energies across the 3d, 4d, and 5d series of MO 2 transition-metal (TM) oxide surfaces computed within Hubbard- U corrected density functional theory (DFT + U ). Investigating the electronic structure with crystal orbital Hamiltonian populations (COHP) of the relevant metal–oxygen bonds reveals that the spin-dependent coupling strength between metal-d and oxygen-2p atomic orbitals together with the extent of filling of bonding and anti-bonding orbitals are the primary contributors to the adsorption energy. Importantly, we show that the integrated COHP obtained purely from bulk calculations is a highly accurate descriptor for surface adsorption energetics that captures trends across the group 5–12 TM oxide series within 0.19–0.36 eV. Our results suggest a pathway to prediction of adsorption energies for an arbitrary metal–ligand catalyst system.

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

Predictions of Boron Phase Stability Using an Efficient Bayesian Machine Learning Interatomic Potential

Thermodynamic phase stability of three elemental boron allotropes, i.e., α-B, β-B, and γ-B, was investigated using a Bayesian interatomic potential trained via a sparse Gaussian process (SGP). SGP potentials trained with datasets from on-the-fly active learning achieve quantum mechanical level accuracy when employed in molecular dynamics simulations to predict wide-ranging thermodynamic, structural, and vibrational properties. The simulated phase diagram (500~1400 K and 0~16 GPa) agrees with experimental measurements. The SGP-based MD simulations also successfully predicted that the B13 defect is critical in stabilizing β-B below 700 K. At higher temperatures, the entropy becomes the dominant factor, making β-B the more stable phase over α-B. Furthermore, this Letter demonstrates that SGP potentials based on a training set consisting of defect-free-only systems could make correct predictions of defect-related phenomena in solid-state crystals, paving the path to investigate crystal phase stability and transitions.

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

Elucidating the Mechanism of Helium Evaporation from Liquid Water

Here, we investigate the evaporation of trace amounts of helium solvated in liquid water using molecular dynamics simulations and theory. Consistent with experimental observations, we find a super-Maxwellian distribution of kinetic energies of evaporated helium. This excess of kinetic energy over typical thermal expectations is explained by an effective continuum theory of evaporation based on a Fokker–Planck equation, parametrized molecularly by a potential of mean force and position-dependent friction. Using this description, we find that helium evaporation is strongly influenced by the friction near the interface, which is anomalously small near the Gibbs dividing surface due to the ability of the liquid–vapor interface to deform around the gas particle. Our reduced description provides a mechanistic interpretation of trace gas evaporation as the motion of an underdamped particle in a potential subject to a viscous environment that varies rapidly across the air–water interface. From it we predict the temperature dependence of the excess kinetic energy of evaporation, which is yet to be measured.

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

CACTUS: Chemistry Agent Connecting Tool Usage to Science

Large language models (LLMs) have shown remarkable potential in various domains but often lack the ability to access and reason over domain-specific knowledge and tools. In this article, we introduce Chemistry Agent Connecting Tool-Usage to Science (CACTUS), an LLM-based agent that integrates existing cheminformatics tools to enable accurate and advanced reasoning and problem-solving in chemistry and molecular discovery. We evaluate the performance of CACTUS using a diverse set of open-source LLMs, including Gemma-7b, Falcon-7b, MPT-7b, Llama3-8b, and Mistral-7b, on a benchmark of thousands of chemistry questions. Our results demonstrate that CACTUS significantly outperforms baseline LLMs, with the Gemma-7b, Mistral-7b, and Llama3-8b models achieving the highest accuracy regardless of the prompting strategy used. Moreover, we explore the impact of domain-specific prompting and hardware configurations on model performance, highlighting the importance of prompt engineering and the potential for deploying smaller models on consumer-grade hardware without a significant loss in accuracy. By combining the cognitive capabilities of open-source LLMs with widely used domain-specific tools provided by RDKit, CACTUS can assist researchers in tasks such as molecular property prediction, similarity searching, and drug-likeness assessment.

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

High-Throughput Screening and Accurate Prediction of Ionic Liquid Viscosities Using Interpretable Machine Learning

Ionic liquids (ILs) are a novel group of green solvents with great promise for various industrial applications, including carbon capture and lignocellulosic biomass deconstruction. However, the use of ILs at the industrial scale remains challenging due to their high viscosities at ambient temperatures. To develop ILs with lower viscosities, a systematic study of their quantitative structure–property relationship (QSPR) is desirable. Here, we developed four machine learning (ML) models to predict viscosity at various temperature and pressure ranges, trained over a wide range of ILs consisting of various cationic and anionic families. ML methods including two-factor polynomial regression (two-factor PR), support vector regression (SVR), feed-forward neural networks (FFNN), and categorical boosting (CATBoost) were developed based on features that have proven useful in previous ML studies: COSMO-RS (conductor-like screening model for real solvents)-derived surface screening charge densities (sigma profiles). FFNN and CATBoost were the most accurate in predicting IL viscosities with lower average absolute relative deviation and higher R2 values on the test set. Tanimoto similarity scores were calculated to characterize the chemical space and structural similarity of the investigated ions. Furthermore, SHapley Additive exPlanation (SHAP) analysis was employed to interpret the ML results. Temperature, the polar area of ILs, and the nonpolar regions of ions are key features that influence the viscosity predictions. Importantly, the IL viscosity prediction here is the most accurate reported to date.

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

Complex regulation in a Comamonas platform for diverse aromatic carbon metabolism

Critical to a sustainable energy future are microbial platforms that can process aromatic carbons from the largely untapped reservoir of lignin and plastic feedstocks. Comamonas species present promising bacterial candidates for such platforms because they can use a range of natural and xenobiotic aromatic compounds and often possess innate genetic constraints that avoid competition with sugars. However, the metabolic reactions of these species are underexplored, and the regulatory mechanisms are unknown. Here we identify multilevel regulation in the conversion of lignin-related natural aromatic compounds, 4-hydroxybenzoate and vanillate, and the plastics-related xenobiotic aromatic compound, terephthalate, in Comamonas testosteroni KF-1. Transcription-level regulation controls initial catabolism and cleavage, but metabolite-level thermodynamic regulation governs fluxes in central carbon metabolism. Quantitative 13 C mapping of tricarboxylic acid cycle and cataplerotic reactions elucidates key carbon routing not evident from enzyme abundance changes. This scheme of transcriptional activation coupled with metabolic fine-tuning challenges outcome predictions during metabolic manipulations.

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

Solvation and oxidation effects on the crystal structure and morphology of tetraoxolene-based materials

Owing to their rich redox behavior and strong metal chelating ability, tetraoxolene ligands have been established as one of the foundational building blocks for multifunctional metal–organic materials. Here, we show how simple and often overlooked synthetic parameters can be used to control the structures of transition metal and lanthanide-based metal–tetraoxolene materials across multiple length scales. Through the synthesis of twelve new compounds, we provide a comprehensive survey detailing how the choice of solvent, initial ligand redox state, and in situ oxidant impact the local coordination geometry and chain architecture, as well as the crystal size and shape (e.g., rods vs. platelets). This work represents an important step towards the synthesis of new metal–tetraoxolene materials with predictable architectures and, therefore, targeted functionality.

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

The role of collective elasticity on activated structural relaxation, yielding, and steady state flow in hard sphere fluids and colloidal suspensions under strong deformation

In this work, we theoretically study the effect of external deformation on activated structural relaxation and aspects of the nonlinear mechanical response of glassy hard sphere fluids in the context of elastically collective nonlinear Langevin equation theory. This microscopic force-based approach describes activated relaxation as a coupled local–nonlocal event involving caging and longer range collective elasticity, with the latter becoming more important and ultimately dominant with increasing packing fraction under equilibrium conditions. The central new question we address is how this physical picture of activated relaxation, and the relative importance of local caging vs collective elasticity physics, depends on external deformation. Theoretical predictions are presented for deformation-induced enhancement of mobility, the onset of relaxation speed up at remarkably low values of stress, strain, or shear rate, apparent power law thinning of the steady state structural relaxation time and viscosity, a non-vanishing activation barrier in the shear thinning regime, an apparent Herschel–Bulkley form of the rate dependence of the steady state shear stress, exponential growth of different measures of a dynamic yield or flow stress with the packing fraction, and reduced fragility and dynamic heterogeneity under deformation. The results are contrasted with experiments and simulations, and qualitative or better agreement is found. An overarching conclusion is that deformation strongly reduces the importance of longer range collective elastic effects relative to the local caging aspect for most, but not all, physical questions, with deformation-dependent fragility and dynamic heterogeneity phenomena being qualitatively sensitive to collective elasticity. Overall, nonlinear rheology is predicted to be a more local problem than quiescent structural relaxation, albeit with deformation-modified activated processes still important.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗