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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

In-situ synthesized N-doped ZnO for enhanced CO 2 sensing: Experiments and DFT calculations

Chemiresistive CO 2 sensing is attractive due to low cost and ease of chip-level integration. Our previous studies (Yong Xia, 2021) showed the well-developed ZnO material fabricated by in-situ annealing exhibited good CO 2 sensing performance. Here, we have expanded on those studies, including CO 2 cyclic tests under both dry air and N 2 background whereby a much higher response to CO 2 in N 2 background was observed. In this study, detailed density functional theory calculations were conducted to understand the behavior. The results indicated nitrogen doping is mainly responsible for the observed response. In the presence of pre-adsorbed O 2 , N-doped ZnO can no longer interact with CO 2 , which agrees well with the observation of higher response in N 2 background. Furthermore, density of states analysis showed N sp 2 hybridized orbital and N 2p orbital of the N dopant mixed with sp 2 hybridized orbital of C atom and 2p orbitals of C/O atoms in CO 2 to form σ and π bonds, respectively. However, they mixed with O 2s/2p orbitals of O atom in O 2 when pre-adsorbed O 2 was present, hindering CO 2 interaction with N-doped ZnO, and resulting in limited response in air. The illustrated mechanism does not only further the understanding of metal oxide-based CO 2 sensing, but also guide the design of new functional materials for CO 2 sensing or capture.

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

Toward Quantum Chemical Free Energy Simulations of Platinum Nanoparticles on Titania Support

Platinum nanoparticles (Pt-NPs) supported on titania surfaces are costly but indispensable heterogeneous catalysts because of their highly effective and selective catalytic properties. Therefore, it is vital to understand their physicochemical processes during catalysis to optimize their use and to further develop better catalysts. However, simulating these dynamic processes is challenging due to the need for a reliable quantum chemical method to describe chemical bond breaking and bond formation during the processes but, at the same time, fast enough to sample a large number of configurations required to compute the corresponding free energy surfaces. Density functional theory (DFT) is often used to explore Pt-NPs; nonetheless, it is usually limited to some minimum-energy reaction pathways on static potential energy surfaces because of its high computational cost. In this work, we report a combination of the density functional tight binding (DFTB) method as a fast but reliable approximation to DFT, the steered molecular dynamics (SMD) technique, and the Jarzynski equality to construct free energy surfaces of the temperature-dependent diffusion and growth of platinum particles on a titania surface. In particular, we present the parametrization for Pt-X (X = Pt, Ti, or O) interactions in the framework of the second-order DFTB method, using a previous parametrization for titania as a basis. The optimized parameter set was used to simulate the surface diffusion of a single platinum atom (Pt 1 ) and the growth of Pt 6 from Pt 5 and Pt 1 on the rutile (110) surface at three different temperatures (T = 400, 600, 800 K). The free energy profile was constructed by using over a hundred SMD trajectories for each process. We found that increasing the temperature has a minimal effect on the formation free energy; nevertheless, it significantly reduces the free energy barrier of Pt atom migration on the TiO 2 surface and the transition state (TS) of its deposition. In a concluding remark, the methodology opens the pathway to quantum chemical free energy simulations of Pt-NPs’ temperature-dependent growth and other transformation processes on the titania support.

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

Role of High-Spin Species and Pendant Amines in Electrocatalytic Alcohol Oxidation by a Nickel Phosphine Complex

We report the development of active and efficient electrocatalysts for oxidation of alcohols using earth-abundant metals will aid the progress towards a renewable energy economy. Here we present a detailed mechanistic study of electrocatalytic benzyl alcohol oxidation by a molecular nickel complex containing pendant amines using a combination of kinetic studies, NMR spectroscopy, and density functional theory. The catalyst preferentially binds alcohol in high-spin octahedral geometry, but this complex is not readily deprotonated by exogeneous base and inhibits catalysis. Dissociation of one or more solvent ligands returns the complex to a low-spin state that can be deprotonated. Kinetic modeling indicates the off-cycle high-spin intermediate lowers the catalytic turnover frequency by a factor of eight, suggesting that substantial gains in activity can be attained by improvements to the catalyst coordination geometry. In a second finding, we demonstrate the pendant amine of the catalyst only functions as a proton relay for the potential-determining step, oxidation of a nickel hydride intermediate, but does not have a substantial impact on the overall rate for oxidation of benzyl alcohol to benzaldehyde. This result contradicts the common expectation for pendant amines to participate in rate-limiting proton transfer reactions.

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

Highly transferable atomistic machine-learning potentials from curated and compact datasets across the periodic table

Machine learning atomistic potentials trained using density functional theory (DFT) datasets allow for the modeling of complex material properties with near-DFT accuracy while imposing a fraction of its computational cost. The curation of the DFT datasets can be extensive in size and time-consuming to train and refine. In this study, we focus on addressing these barriers by developing minimalistic and flexible datasets for many elements in the periodic table regardless of their mass, electronic configuration, and ground state lattice. These DFT datasets have on average, ~4000 different structures and 27 atoms per structure, which we found sufficient to maintain the predictive accuracy of DFT properties and notably with high transferability. We envision these highly curated training sets as starting points for the community to expand, modify, or use with other machine learning atomistic potential models, whatever may suit individual needs, further accelerating the utilization of machine learning as a tool for material design and discovery.

42 ENGINEERING↗
DOE OSTI2025

High-Pressure Electrides: A Quantum Chemical Perspective

It has long been assumed that all matter will adopt simple close-packed lattices and become metallic under pressure, in accordance with the Thomas–Fermi–Dirac (TFD) model. However, this model struggles to explain pressure-driven complex structural transitions that have been observed in elements, including sodium, challenging our conventional understanding of compressed matter. Moreover, in stark contrast to the TFD model, first-principles calculations suggest that various elements and compounds become electrides under pressure. Electrides, characterized by concentrations of charge density at interstitial regions, can be thought of as ionic compounds where electrons behave as the anions. Though ambient-pressure molecular electrides have been extensively studied via experiments and computations, high-pressure electrides (HPEs) are not well-understood. The identification and characterization of HPEs have been, to date, based purely on theory, including topological analysis of the electron density and the electron localization function. Here, we review these theoretical analysis tools and suggest guidelines that can be used to classify systems as electrides. Moreover, we describe models used to rationalize the electronic structure of HPEs, drawing parallels with ambient-pressure molecular systems, and encourage the development of experimental techniques that provide evidence for the theoretically calculated charge localization.

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

Graph-theoretical KMC Framework for Calculating Effective Diffusivity in TPBAR Components: Effective Diffusivity of Tritium in α-Zr Grain Boundaries

We report the development of a computer simulation tool based on the Graph-theoretical kinetic Monte Carlo (GT-KMC) approach that can be used to simulate diffusion and derive effective diffusivity of species in complex structures of TPBAR components. The GT-KMC framework was implemented in AKSOME, an on-lattice self-learning kinetic Monte Carlo tool developed at PNNL and was previously used to study solute diffusion in metal alloys. This newly developed tool will be helpful in simulating atom diffusion and extracting their effective diffusivities in grain boundaries and interfaces in various TPBAR components. Once benchmarked, the tool will be used to simulate the diffusion of tritium (hydrogen) along grain boundaries in α-Zr using the activation energy barrier data previously obtained from Density Functional Theory calculations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Efficient Modeling of Structural, Electronic, and Optical Properties of Silver and Gold Metal Nanoclusters and Alloys Using Optimized SCC-DFTB Parameters

Computation of optical properties using conventional time-dependent density functional theory (TD-DFT) is time-consuming and memory-intensive. In this study, we investigate the accuracy and efficiency of the density functional tight binding (DFTB) framework with newly optimized Slater–Koster (SK) parameters for modeling the structural, electronic properties, and absorption spectra of silver and gold nanoclusters and their alloys. Our investigation of the ground state (GS) properties demonstrates that the newly developed GS-SK parameters enable DFTB to closely approximate DFT-calculated bond lengths for octahedron, tetrahedron, icosahedra, and truncated octahedron with sizes Ag n /Au n (n = 19, 20, 38, 55), nanoclusters and Ag 20 /Au 20 nanoalloys, with a maximum deviation of approximately 0.15 Å. Formation energy results indicate that the GS-SK parameters can closely estimate changes in formation energies with alloy composition, and the comparison of electronic structures for Ag 20 , Au 20 , and AgAu alloy nanoclusters using the DFTB approximation reveals good agreement in the projected density of states (DOS) profiles and energy levels. A second set of SK parameters, ES-SK, has been developed to describe excited state (ES) properties, including the absorption spectra of silver octahedron Ag 19 , tetrahedral Ag n (n = 20, 56, 84), truncated octahedron Ag 38 , and icosahedra Ag 55 closed-shell clusters and their gold and alloy counterparts over a broad range of alloy compositions. This parametrization uses TD-DFTB calculations and fine-tunes the d and p eigenvalues by comparing them to reference absorption spectra from first-principles TD-DFT. This enables the generation of absorption spectra that closely match the reference spectra when plasmon excitation is dominant, as demonstrated by studying the plasmonic properties of icosahedral Ag n and Au n (n = 309 and 561) nanoparticles. This includes the rapid loss in plasmon quality when Au partially replaces Ag in alloy clusters. Furthermore, these results provide a foundation for addressing computational bottlenecks in plasmonics and with new prospects for applications in the quantum plasmonics for bimetallic alloys.

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

Spin‐State and Clustering Effects in Fe‐Complex Negolytes for Near‐Neutral Aqueous Redox Flow Batteries

Cost-effective redox-active materials are essential for advancing redox flow batteries (RFBs). Iron, with its abundance and suitability as a redox couple, is a promising candidate; however, achieving stable and fast redox reactions in aqueous RFBs remains a challenge. Here, this study presents an Fe-based negolyte stabilized by a hexadentate ligand, where Fe–ligand bonds are enhanced through intermolecular interactions. The sulfonate-substituted Fe complex exhibits a formal potential of −0.44 V versus Ag/AgCl and an exceptionally high rate constant of 0.69 cm s −1 . Near-neutral RFBs incorporating 0.5 M Fe complex show excellent cycling stability, with no discernible capacity fading over 300 cycles. This performance is attributed to intermolecular hydrogen bonds that reinforce Fe–ligand coordination and promote the formation of stable trimeric clusters. Operando electrochemical Raman spectroscopy and density functional theory reveal that π-backdonation from Fe(II) to the imino-phenolate moiety further stabilizes the complex after reduction. In contrast, the hydroxyl-substituted complex exhibits inferior stability due to weaker hydrogen bonding and less pronounced π-backdonation. These findings underscore the importance of ligand design and intermolecular interactions in developing cost-effective, high-performance redox-active materials for aqueous RFBs.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Operando X-ray Diffraction Studies of the Mg-Ion Migration Mechanisms in Spinel Cathodes for Rechargeable Mg-Ion Batteries

A promising high-voltage spinel oxide cathode material MgCrMnO 4 with 18% Mg/Mn inversion was synthesized successfully. A new custom operando battery device was designed to study the cation migration mechanisms of the MgCrMnO 4 cathode using 0.1 M Mg(TPFA) 2 electrolyte dissolved in triglyme and activated carbon as the anode. For the first time in multivalent batteries, high-quality operando diffraction data enabled the accurate quantification of cation contents in the host structure. Besides the exceptional reversibility of 12% Mg 2+ insertion in Mg 1- x CrMnO 4 ( x ≤ 1), a partially reversible insertion of excess Mg 2+ during overdischarging was also observed. Moreover, the insertion/extraction reaction was experimentally shown to be accompanied by a series of cation redistributions in the spinel framework, which were further supported by density functional theory calculations. Furthermore, the inverted Mn is believed to be directly involved in the cation migrations, which would cause voltage hysteresis and irreversible structural evolution after overdischarging. Tuning the Mg/Mn inversion rate could provide a direct path to further optimize spinel oxide cathodes for Mg-ion batteries, and more generally, the operando techniques developed in this work should play a key role in understanding the complex mechanisms involved in multivalent ion insertion systems.

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

Topography inversion in scanning tunneling microscopy of single-atom-thick materials from penetrating substrate states

Scanning tunneling microscopy (STM) is one of the indispensable tools to characterize surface structures, but the distinction between atomic geometry and electronic effects based on the measured tunneling current is not always straightforward. In particular, for single-atomic-thick materials (graphene or boron nitride) on metallic substrates, counterintuitive phenomena such as a larger tunneling current for insulators than for metal and a topography opposite to the atomic geometry are reported. Using first-principles density functional theory calculations combined with analytical modeling, we reveal the critical role of penetrating states of metallic substrates that surpass 2D material states, hindering the measurement of intrinsic 2D materials states and leading to topography inversion. Our finding should be instrumental in the interpretation of STM topographies of atomic-thick materials and in the development of 2D material for (opto)electronic and various quantum applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Electronic structure of van der Waals ferromagnet CrI 3 from self-consistent vertex corrected GW approaches

Electronic structure of the layered van der Waals ferromagnet CrI 3 is studied with self consistent diagrammatic approaches beyond the GW approximation. Considerable improvement in the calculated band gap as compared to the non-self-consistent G0W0 results has been found. Certain spectral features in the valence bands discovered recently by the angle resolved photoemission spectroscopy, are reproduced better when we use full frequency dependent self energy. Density functional theory and the quasiparticle self-consistent GW method which are based on the frequency-independent self energy are unable to resolve these features. The non-locality effects in the diagrams beyond the GW approximation are large for both polarizability and self energy. This finding can potentially have an impact on the development of methods like the GW+DMFT (dynamical mean field theory).

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Development of a multiphase equation of state for gallium with experiments and ab initio free-energy calculations

Here, we present a five-phase equation of state (EOS) for elemental gallium (Ga) that is developed using both experimental data and new theoretical predictions. Four experimentally observed solid phases (Ga-I, Ga-II, Ga-III, and Ga-IV) and one liquid phase are included. To improve our understanding of the thermal behavior of Ga and its phase boundaries under compression, we have performed ab initio density functional theory (DFT) free-energy calculations for the Ga-III and liquid phases, which enables us to determine the melt temperature to be 2214 ± 100 K at 110 GPa, extending significantly beyond the existing experimental melt data, which are limited to 25 GPa. In order to best describe the electron-thermal contribution, which dominates the liquid free energy at high temperatures, we have carried out averaged-atom-in-jellium DFT calculations to cover the entire temperature and density range of the EOS. The resulting multiphase Ga EOS is able to accurately reproduce a diverse variety of data, including known phase boundaries, the principal Hugoniot, low-pressure liquid isobars, and diamond-anvil-cell isotherm measurements at high pressures. It agrees more closely with key experimentally measured properties than other Ga EOS models targeted for high-pressure applications.

Wu, Christine J. [Lawrence Livermore National Labo↗
DOE OSTI2023

DeePKS-kit: A package for developing machine learning-based chemically accurate energy and density functional models

We introduce DeePKS-kit, an open-source software package for developing machine learning based energy and density functional models. DeePKS-kit is interfaced with PyTorch, an open-source machine learning library, and PySCF, an ab initio computational chemistry program that provides simple and customized tools for developing quantum chemistry codes. It supports the DeePHF and DeePKS methods. In addition to explaining the details in the methodology and the software, we also provide an example of developing a chemically accurate model for water clusters.

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

Final Report (October 2024): University of Tennessee, Knoxville (UTK) contribution to: FusMatML: Machine Learning Atomistic Modeling for Fusion Materials Collaborative Project led by Dr. Aidan Thompson, Sandia National Laboratory

The rapid growth of the field of Machine Learning Inter-Atomic Potentials (MLIAP) has lead to a profusion of methods, all of which have some similarity to each other, but each also restricted to particular design choices, often arrived at in a rather ad hoc fashion. Beyond anecdotal evidence, and some benchmarking studies on specific problems, little progress has been made in developing design principles for MLIAPs. The goal of this project is to use machine learning, data science, and uncertainty quantification methods to optimize the design choices for MLIAP.

Density functional theory, Helium and Hydrogen↗
DOE OSTI2023

Spatiotemporal measurements of striations in a glow discharge’s positive column using laser-collisional induced fluorescence

Here we have observed the behavior of striations caused by ionization waves propagating in low-pressure helium DC discharges using the non-invasive laser-collision induced fluorescence (LCIF) diagnostic. To achieve this, we developed an analytic fit of collisional radiative model (CRM) predictions to interpret the LCIF data and recover quantitative two-dimensional spatial maps of the electron density, n e , and the ratios of LCIF emission states that can be correlated with T e with the use of accurate distribution functions at localized positions within striated helium discharges at 500 mTorr, 750 mTorr, and 1 Torr. To our knowledge, these are the first spatiotemporal, laser-based, experimental measurements of n e in DC striations. The n e and 447:588 ratio distributions align closely with striation theory. Constriction of the positive column appears to occur with decreased gas pressure, as shown by the radial n e distribution. We identify a transition from a slow ionization wave to a fast ionization wave between 750 mTorr and 1 Torr. These experiments validate our analytic fit of n e , allowing the implementation of an LCIF diagnostic in helium without the need to develop a CRM.

42 ENGINEERING↗
DOE OSTI2021

Cesium-Coated Halide Perovskites as a Photocathode Material: Modeling Insights

Photocathodes emit electrons when illuminated, a process utilized across many technologies. Cutting-edge applications require a set of operating conditions that are not met with current photocathode materials. Meanwhile, halide perovskites have been studied extensively and have shown a lot of promise for a wide variety of optoelectronic applications. Well-documented halide perovskite properties such as inexpensive growth techniques, improved carrier mobility, low trap density, and tunable direct band gaps make them promising candidates for next-generation photocathode materials. In this study, we use density functional theory to explore the possible application of pure inorganic perovskites (CsPbBr 3 and CsPbI 3 ) as photocathodes. It is determined that the addition of a Cs coating improved the performance by lowering the work function anywhere between 1.5 and 3 eV depending on the material, crystal surface, and surface coverage. A phenomenological model, modified from that developed by Gyftopoulos and Levine, is used to predict the reduction in work function with Cs coverage. The results of this work aim to guide the further experimental development of Cs-coated halide perovskites for photocathode materials.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2022

CO 2 Chemisorption Behavior in Conjugated Carbanion-Derived Ionic Liquids via Carboxylic Acid Formation

Superbase-derived task-specific ionic liquids (STSILs) represent one of the most attractive and extensively studied systems in carbon capture via chemisorption, in which the obtained CO 2 uptake capacity has a strong relationship with the basicity of the anions. High energy input in desorption and side reactions caused by the strong basicity of the anions are still unsolved issues. The development of other customized STSILs leveraging an alternative driving force to achieve efficient CO 2 chemisorption/desorption is highly desirable yet challenging. Here, in this work, carbanion-derived STSILs were developed for efficient CO 2 chemisorption via a carboxylic acid formation pathway. The STSIL with the deprotonated malononitrile molecule ([MN]) as the anion exhibited much higher CO 2 uptake capacity than the one derived from 2-methylmalononitrile ([MMN]). Notably, this trend was opposite to their basicity ([MN] < [MMN]). Detailed characterization of the products, supported by density functional theory simulations of spectra and calculations of the reaction energetics, demonstrated that carboxylic acid was formed upon reacting with CO 2 via proton transfer in [MN]-derived STSILs but not in the case of [MMN] due to lack of an α-H. The preference of the carboxylic acid product over carboxylate formation was driven by the extended conjugation among the central sp 2 carbon, the as-formed carboxylic acid, and the two nitrile groups. The achievements made in this work provide an alternative design principle of STSILs by leveraging the extended conjugation in the CO 2 -integrated product.

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

An open database of computed bulk ternary transition metal dichalcogenides

Abstract We present a dataset of structural relaxations of bulk ternary transition metal dichalcogenides (TMDs) computed via plane-wave density functional theory (DFT). We examined combinations of up to two chalcogenides with seven transition metals from groups 4–6 in octahedral (1T) or trigonal prismatic (2H) coordination. The full dataset consists of 672 unique stoichiometries, with a total of 50,337 individual configurations generated during structural relaxation. Our motivations for building this dataset are (1) to develop a training set for the generation of machine and deep learning models and (2) to obtain structural minima over a range of stoichiometries to support future electronic analyses. We provide the dataset as individual VASP xml files as well as all configurations encountered during relaxations collated into an ASE database with the corresponding total energy and atomic forces. In this report, we discuss the dataset in more detail and highlight interesting structural and electronic features of the relaxed structures.

36 MATERIALS SCIENCE↗