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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Multipole Expansion of Atomic Electron Density Fluctuation Interactions in the Density-Functional Tight-Binding Method

The accuracy of the density-functional tight-binding (DFTB) method in describing noncovalent interactions is limited due to its reliance on monopole-based spherical charge densities. In this study, we present a multipole-extended second-order DFTB (mDFTB2) method that takes into account atomic dipole and quadrupole interactions. Furthermore, we combine the multipole expansion with the monopole-based third-order contribution, resulting in the mDFTB3 method. To assess the accuracy of mDFTB2 and mDFTB3, we evaluate their performance in describing noncovalent interactions, proton transfer barriers, and dipole moments. Here, our benchmark results show promising improvements even when using the existing electronic parameters optimized for the original DFTB3 model. Both mDFTB2 and mDFTB3 outperform their monopole-based counterparts, DFTB2 and DFTB3, in terms of accuracy. While mDFTB2 and mDFTB3 perform comparably for neutral and positively charged systems, mDFTB3 exhibits superior performance over mDFTB2 when dealing with negatively charged systems and proton transfers. Overall, the incorporation of the multipole expansion significantly enhances the accuracy of the DFTB method in describing noncovalent interactions and proton transfers.

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

Liquid Phase Modeling in Porous Media: Adsorption of Methanol and Ethanol in H-MFI in Condensed Water

Zeolites are used in the chemical and separation industries for their exceptional selectivity, adsorption capacity, regenerability, and stability in gas and liquid phase processing. Here, we developed an explicit solvation method for predicting solvent/condensed phase effects on adsorption free energies in microporous media such as zeolites based on the hybrid quantum mechanical/molecular mechanical free energy perturbation (QM/MM-FEP) technique. Our explicit solvation method for zeolite systems, called eSZS, aims to capture site-specific interactions during the adsorption process at the Brønsted acid sites of H-MFI zeolite while still considering the diverse configuration space of the solvent molecules. This strategy is ideal for chemical reactions or adsorbates that interact with the microporous medium in few distinct adsorbate/transition state configurations, i.e., the harmonic or similar approximations are acceptable for the adsorbate/transition state while such approximations break down for the solvent molecules that require extensive configuration space sampling. In this way, our approach effectively overcomes the limitations of implicit solvation models and classical force field methods for describing solvation effects on chemical reactions within porous materials such as zeolites. Specifically, in this study, we investigated various aspects of our hybrid QM/MM approach, including QM cluster size dependencies in a periodic electrostatically embedded cluster model (PEECM), rules for link atoms at the QM/MM boundary, and functional and basis set considerations for converged and reasonably accurate gas and aqueous phase methanol and ethanol adsorption free energy predictions in H-MFI. For gas phase adsorption of methanol and ethanol in H-MFI at a Brønsted acid site in T12 position, we compute adsorption free energies at 298 K of −0.61 and −0.75 eV, respectively, using a PEECM containing 50 Si and 1 Al atom with ωB97x-D/def2-TZVP level of theory. For solvent effect calculations, we sample the aqueous phase using grand canonical Monte Carlo (GCMC) simulations to (1) obtain a mean field of electrostatic interactions in the reaction system and (2) perform a rigorous free energy perturbation calculation. Similar to the experimentally and computationally observed endergonic solvation effects observed for hydrocarbon adsorption on metal surfaces, we also observe that a condensed aqueous environment destabilizes methanol and ethanol at these acid sites in H-MFI at 298 K. Specifically, the computed solvation free energies of adsorption (ΔΔG solv ) for methanol and ethanol are +0.44 and +0.54 eV, respectively. From this study, it is evident that adsorbates (methanol and ethanol) are competing with water for adsorption space inside the H-MFI zeolite, leading to an endergonic solvation effect. Here, we expect that the endergonic, aqueous solvent effect during adsorption in microporous zeolites is highly tunable by changing the pore size and hydrophobicity of the microporous material as this will affect the water density inside the pore structure.

Adsorption↗
DOE OSTI2024

Infrared Spectrum of the Pyrene Anion in the CH Stretching Region

In this work, we report the infrared spectrum of pyrene anion, measured using messenger tagging with up to three Ar atoms. We assign the spectrum using density functional theory and vibrational perturbation theory. Additionally, we discuss our results in the context of computed and experimental spectra from the literature as well as recent observations from astronomical sources, addressing the question whether PAH anions could contribute to the strong infrared emission bands at 3.29 μm from carbon- rich regions of space.

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

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

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

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Atomic-Scale Behavior of Radiation-Resistant ZnO under High-Energy Electron Bombardment

Understanding the atomic structure and defect characteristics of ZnO thin films is crucial for optimizing their electronic properties and performance in advanced applications. Here, we investigate the atomic structure and defect characteristics of atomic layer deposition (ALD)-grown ZnO thin films by using aberration-corrected scanning transmission electron microscopy (STEM). Atomic-resolution imaging identifies prevalent stacking faults, dipole disorder, and various grain boundary types, which are believed to influence the electronic properties of ZnO. Additionally, real-time electron beam exposure experiments demonstrate structural transformations, including crystal growth and surface rearrangements. These findings provide insights into the growth mechanisms of ALD ZnO under high-energy electron irradiation conditions, an important finding for the use of polycrystalline ZnO wide bandgap semiconductors in space-like conditions. In conclusion, our results underscore the capability of STEM in directly visualizing and quantifying atomic-scale defects and beam-induced transformations in radiation-resistant ZnO.

Defects↗
DOE OSTI2020

Site-dependent reactivity of MoS2 nanoparticles in hydrodesulfurization of thiophene

The catalytically active site for the removal of S from organosulfur compounds in catalytic hydrodesulfurization has been attributed to a generic site at an S-vacancy on the edge of MoS2 particles. However, steric constraints in adsorption and variations in S-coordination means that not all S-vacancy sites should be considered equally active. Here, we use a combination of atom-resolved scanning probe microscopy and density functional theory to reveal how the generation of S-vacancies within MoS2 nanoparticles and the subsequent adsorption of thiophene (C4H4S) depends strongly on the location on the edge of MoS2. Thiophene adsorbs directly at open corner vacancy sites, however, we find that its adsorption at S-vacancy sites away from the MoS2 particle corners leads to an activated and concerted displacement of neighboring edge S. This mechanism allows the reactant to self-generate a double CUS site that reduces steric effects in more constrained sites along the edge.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Extending the low-temperature operation of sodium metal batteries combining linear and cyclic ether-based electrolyte solutions

Nonaqueous sodium-based batteries are ideal candidates for the next generation of electrochemical energy storage devices. However, despite the promising performance at ambient temperature, their low-temperature (e.g., < 0 °C) operation is detrimentally affected by the increase in the electrolyte resistance and solid electrolyte interphase (SEI) instability. Here, to circumvent these issues, we propose specific electrolyte formulations comprising linear and cyclic ether-based solvents and sodium trifluoromethanesulfonate salt that are thermally stable down to –150 °C and enable the formation of a stable SEI at low temperatures. When tested in the Na||Na coin cell configuration, the low-temperature electrolytes enable long-term cycling down to –80 °C. Via ex situ physicochemical (e.g., X-ray photoelectron spectroscopy, cryogenic transmission electron microscopy and atomic force microscopy) electrode measurements and density functional theory calculations, we investigate the mechanisms responsible for efficient low-temperature electrochemical performance. We also report the assembly and testing between –20 °C and –60 °C of full Na||Na 3 V 2 (PO 4 ) 3 coin cells. The cell tested at –40 °C shows an initial discharge capacity of 68 mAh g –1 with a capacity retention of approximately 94% after 100 cycles at 22 mA g –1 .

25 ENERGY STORAGE↗
DOE OSTI2024

Atomic-scale manipulation of polar domain boundaries in monolayer ferroelectric In 2 Se 3

Domain boundaries have been intensively investigated in bulk ferroelectric materials and two-dimensional materials. Many methods such as electrical, mechanical and optical approaches have been utilized to probe and manipulate domain boundaries. So far most research focuses on the initial and final states of domain boundaries before and after manipulation, while the microscopic understanding of the evolution of domain boundaries remains elusive. In this paper, we report controllable manipulation of the domain boundaries in two-dimensional ferroelectric In 2 Se 3 with atomic precision using scanning tunneling microscopy. We show that the movements of the domain boundaries can be driven by the electric field from a scanning tunneling microscope tip and proceed by the collective shifting of atoms at the domain boundaries. Our density functional theory calculations reveal the energy path and evolution of the domain boundary movement. The results provide deep insight into domain boundaries in two-dimensional ferroelectric materials and will inspire inventive applications of these materials.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Machine learned potential for high-throughput phonon calculations of metal—organic frameworks

Metal–organic frameworks (MOFs) are highly porous and versatile materials studied extensively for applications such as carbon capture and water harvesting. However, computing phonon-mediated properties in MOFs, like thermal expansion and mechanical stability, remains challenging due to the large number of atoms per unit cell, making traditional Density Functional Theory (DFT) methods impractical for high-throughput screening. Recent advances in machine learning potentials have led to foundation atomistic models, such as MACE-MP-0, that accurately predict equilibrium structures but struggle with phonon properties of MOFs. In this work, we developed a workflow for computing phonons in MOFs within the quasi-harmonic approximation with a fine-tuned MACE model, MACE-MP-MOF0. The model was trained on a curated dataset of 127 representative and diverse MOFs. The fine-tuned MACE-MP-MOF0 improves the accuracy of phonon density of states and corrects the imaginary phonon modes of MACE-MP-0, enabling high-throughput phonon calculations with state-of-the-art precision. The model successfully predicts thermal expansion and bulk moduli in agreement with DFT and experimental data for several well-known MOFs. These results highlight the potential of MACE-MP-MOF0 in guiding MOF design for applications in energy storage and thermoelectrics.

Elena, Alin Marin↗
DOE OSTI2022

Efficient conversion of low-concentration nitrate sources into ammonia on a Ru-dispersed Cu nanowire electrocatalyst

We report electrochemically converting nitrate ions, a widely distributed nitrogen source in industrial wastewater and polluted groundwater, into ammonia represents a sustainable route for both wastewater treatment and ammonia generation. However, it is currently hindered by low catalytic activities, especially under low nitrate concentrations. Here we report a high-performance Ru-dispersed Cu nanowire catalyst that delivers an industrial-relevant nitrate reduction current of 1 A cm –2 while maintaining a high NH 3 Faradaic efficiency of 93%. More importantly, this high nitrate-reduction catalytic activity enables over a 99% nitrate conversion into ammonia, from an industrial wastewater level of 2,000 ppm to a drinkable water level <50 ppm, while still maintaining an over 90% Faradaic efficiency. Coupling the nitrate reduction effluent stream with an air stripping process, we successfully obtained high purity solid NH 4 Cl and liquid NH 3 solution products, which suggests a practical approach to convert wastewater nitrate into valuable ammonia products. Density functional theory calculations reveal that the highly dispersed Ru atoms provide active nitrate reduction sites and the surrounding Cu sites can suppress the main side reaction, the hydrogen evolution reaction.

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

Atomically dispersed metal–nitrogen–carbon catalysts for fuel cells: advances in catalyst design, electrode performance, and durability improvement

The urgent need to address the high-cost issue of proton-exchange membrane fuel cell (PEMFC) technologies, particularly for transportation applications, drives the development of simultaneously highly active and durable platinum group metal-free (PGM-free) catalysts and electrodes. The past decade has witnessed remarkable progress in exploring PGM-free cathode catalysts for the oxygen reduction reaction (ORR) to overcome sluggish kinetics and catalyst instability in acids. Among others, scientists have identified the newly emerging atomically dispersed transition metal (M: Fe, Co, or/and Mn) and nitrogen co-doped carbon (M–N–C) catalysts as the most promising alternative to PGM catalysts. Here, we provide a comprehensive review of significant breakthroughs, remaining challenges, and perspectives regarding the M–N–C catalysts in terms of catalyst activity, stability, and membrane electrode assembly (MEA) performance. A variety of novel synthetic strategies demonstrated effectiveness in improving intrinsic activity, increasing active site density, and attaining optimal porous structures of catalysts. Rationally designing and engineering the coordination environment of single metal MN x sites and their local structures are crucial for enhancing intrinsic activity. Increasing the site density relies on the innovative strategies of restricting the migration and agglomeration of single metal sites into metallic clusters. Relevant understandings provide the correlations among the nature of active sites, nanostructures, and catalytic activity of M–N–C catalysts at the atomic scale through a combination of experimentation and theory. Current knowledge of the transferring catalytic properties of M–N–C catalysts to MEA performance is limited. Rationally designing morphologic features of M–N–C catalysts play a vital role in boosting electrode performance through exposing more accessible active sites, realizing uniform ionomer distribution, and facilitating mass/proton transports. We outline future research directions concerning the comprehensive evaluation of M–N–C catalysts in MEAs. The most considerable challenge of current M–N–C catalysts is the unsatisfied stability and rapid performance degradation in MEAs. Therefore, we further discuss practical methods and strategies to mitigate catalyst and electrode degradation, which is fundamentally essential to make M–N–C catalysts viable in PEMFC technologies.

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

Bond order predictions using deep neural networks

Machine learning is an extremely powerful tool for the modern theoretical chemist since it provides a method for bypassing costly algorithms for solving the Schrödinger equation. Already, it has proven able to infer molecular and atomic properties such as charges, enthalpies, dipoles, excited state energies, and others. Most of these machine learning algorithms proceed by inferring properties of individual atoms, even breaking down total molecular energy into individual atomic contributions. In this paper, we introduce a modified version of the Hierarchically Interacting Particle Neural Network (HIP-NN) capable of making predictions on the bonds between atoms rather than on the atoms themselves. We train the modified HIP-NN to infer bond orders for a large number of small organic molecules as computed via the Natural Bond Orbital package. We demonstrate that the trained model is extensible to molecules much larger than those in the training set by studying its performance on the COMP6 dataset. This method has applications in cheminformatics and force field parameterization and opens a promising future for machine learning models to predict other quantities that are defined between atoms such as density matrix elements, Hamiltonian parameters, and molecular reactivities.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Machine learning with bond information for local structure optimizations in surface science

Local optimization of adsorption systems inherently involves different scales: within the substrate, within the molecule, and between the molecule and the substrate. In this work, we show how the explicit modeling of different characteristics of the bonds in these systems improves the performance of machine learning methods for optimization. Furthermore, we introduce an anisotropic kernel in the Gaussian process regression framework that guides the search for the local minimum, and we show its overall good performance across different types of atomic systems. The method shows a speed-up of up to a factor of two compared with the fastest standard optimization methods on adsorption systems. Additionally, we show that a limited memory approach is not only beneficial in terms of overall computational resources but can also result in a further reduction of energy and force calculations.

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

Xenon–metal pair formation in UO 2 investigated using DFT + U

A recent experimental study on a spent uranium dioxide (UO 2 ) fuel sample from Belgium Reactor 3 identified a unique pair structure formed by the noble metal phase (NMP) and fission gas [xenon (Xe)] precipitate. However, the fundamental mechanism behind this structure remains unclear. The present study aims to provide an understanding of the interaction between five different metal precipitates [molybdenum (Mo), ruthenium (Ru), palladium (Pd), technetium (Tc), and rhodium (Rh)] and the Xe fission gas atoms in UO 2 , by using density functional theory (DFT) in combination with the Hubbard U correction to compute the formation energies involved. All DFT + U calculations were performed with occupation matrix control to ensure antiferromagnetic ordering of UO 2 . The calculated formation and binding energies of the Xe and solid fission products in the NMP reveal that these metal precipitates form stable pair structures with Xe. Notably, the formation energy of Xe–metal pairs is lower than that of the isolated single defects in all instances, with Pd and Mo showing the most favorable binding energy, likely accounting for the observed pair structure formation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Layer-dependent topological phase in a two-dimensional quasicrystal and approximant

The electronic and topological properties of materials are derived from the interplay between crystalline symmetry and dimensionality. Simultaneously introducing “forbidden” symmetries via quasiperiodic ordering with low dimensionality into a material system promises the emergence of new physical phenomena. Here, we isolate a two-dimensional (2D) chalcogenide quasicrystal and approximant, and investigate their electronic and topological properties. The 2D layers of the materials with a composition close to Ta 1.6 Te, derived from a layered transition metal dichalcogenide, are isolated with standard exfoliation techniques, and investigated with electron diffraction and atomic resolution scanning transmission electron microscopy. Density functional theory calculations and symmetry analysis of the large unit cell crystalline approximant of the quasicrystal, Ta 21 Te 13 , reveal the presence of symmetry-protected nodal crossings in the quasicrystalline and approximant phases, whose presence is tunable by layer number. Our study provides a platform for the exploration of physics in quasicrystalline, low-dimensional materials and the interconnected nature of topology, dimensionality, and symmetry in electronic systems.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Roadmap on data-centric materials science

Science is and always has been based on data, but the terms ‘data-centric’ and the ‘4th paradigm’ of materials research indicate a radical change in how information is retrieved, handled and research is performed. It signifies a transformative shift towards managing vast data collections, digital repositories, and innovative data analytics methods. The integration of artificial intelligence and its subset machine learning, has become pivotal in addressing all these challenges. This Roadmap on Data-Centric Materials Science explores fundamental concepts and methodologies, illustrating diverse applications in electronic-structure theory, soft matter theory, microstructure research, and experimental techniques like photoemission, atom probe tomography, and electron microscopy. While the roadmap delves into specific areas within the broad interdisciplinary field of materials science, the provided examples elucidate key concepts applicable to a wider range of topics. The discussed instances offer insights into addressing the multifaceted challenges encountered in contemporary materials research.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Electron beam analysis induces Cl vacancy defects in a NaCl thin film

This work reports on the electron-induced modification of NaCl thin film grown on Ag(110). We show using low energy electron diffraction that electron beam bombardment leads to desorption and formation of Cl vacancy defects on NaCl surface. The topographic structure of these defects is studied using scanning tunneling microscopy (STM) showing the Cl defects as depressions on the NaCl surface. Most of the observed defects are mono-atomic vacancies and are located on flat NaCl terraces. Auger electron spectroscopy confirms the effect of electron exposure on NaCl thin films showing Cl atoms desorption from the surface. Using density functional theory taken into account the van der Waals dispersion interactions, we confirm the observed experimental STM measurements with STM simulation. Furthermore, comparing the adsorption of defect free NaCl and defective NaCl monolayer on Ag(110) surfaces, we found an increase of the adhesion energy and the charge transfer between the NaCl film and the substrate due to the Cl vacancy. In details, the adhesion energy increases between the NaCl film and the metallic Ag substrate from 30.4 meV Å –2 for the NaCl film without Cl vacancy and from 39.5 meV Å –2 for NaCl film with a single Cl vacancy. The charge transfer from the NaCl film to the Ag substrate is enhanced when the vacancy is created, from 0.63e – to 1.25e – .

Materials Science↗
DOE OSTI2025

Nonlocal chiral anomaly and generalized parton distributions

We discuss the nonlocal generalization of the QCD chiral anomaly along the light cone and derive relations between twist-two, twist-three, and twist-four generalized parton distributions (GPDs) mediated by the anomaly. We further establish the connection to the “anomaly pole” in the GPD E ˜ recently identified in the perturbative calculation of the Compton scattering amplitudes, and demonstrate its cancellation at the GPD level. Our work helps elucidate the previously unexplored connection between GPDs, the chiral anomaly, and the mass generation of the η ′ meson. Published by the American Physical Society 2025

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗