Search NASA⌕ Search

SEARCH · Search NASA

Results for “density functional calculation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The Electron Thermal Conductivity of Pu and Zr Substituted $\mathcal{γ}$-U

Uranium alloys are attractive recycled nuclear fuels because of their high thermal conductivity (𝑘) and fissile density. Limited experimental studies of the 𝑘 of U-Pu-Zr alloys in the range of 15 to 20 wt% Pu and 6 to 15 wt% Zr indicate that increasing the content of either Zr or Pu tends to lower 𝑘. However, which element has the greater effect on 𝑘, and the associated mechanisms, remains unclear. Here, in this study, the electron thermal conductivity (𝑘 𝑒 ) of U-Pu-Zr compositions are calculated using density functional theory. The electronic structure is evaluated to understand the effects of plutonium (Pu) and zirconium (Zr) substitution on the 𝑘 𝑒 of 𝛾-U. Alloys of up to 37.5 at. % Pu and 37.5 at. % Zr are examined. Two methods are applied to calculate 𝑘 𝑒 ; we find that the accuracy of each method depends on the electronic and mass similarities between the solute and solvent atoms. Specifically, when the solute atom is similar in electronic structure and mass, the more accurate method is that which employs the electron relaxation time of 𝛾-U, while if the elements are dissimilar, a mixed method that mixes several parameters associated with JNW_S⁢3033426825100132 from each element in the alloy is best. The introduction of all alloying elements decreases 𝑘 𝑒 ; however, in binary compounds, Pu and Zr have different effects. Pu flattens the electronic bands but compensates for this deleterious effect by increasing electron density near the Fermi level. Zr flattens the electronic bands more severely without adding electron density near the Fermi level. Therefore, Zr decreases 𝑘 𝑒 more than Pu in binary compounds. In ternary compounds, the difference between Pu and Zr is minimal due to the phononic change from the large mass change of Zr substitution, even at 12.5 at. %. Thus, we predict that higher loadings of Pu, and potentially other actinides, can be added to U-Pu-Zr compositions for faster recycling of spent fuel without sacrificing 𝑘. We also note that these 𝑘 𝑒 calculation methods can be applied to non-fuel alloys that require 𝑘 𝑒 predictions, such as cladding, heat exchanger, and structural materials.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Unconventional pressure-induced magnetic transitions and mechanical properties in non-magnetic LaFeSi

Here, this work demonstrates that two consecutive magnetic transitions occur in non-magnetic LaFeSi compound under negative hydrostatic pressure (small volume expansion). Electronic structure properties of LaFeSi were calculated using density functional theory (DFT) to understand the origin of these magnetic transitions. Mechanical properties of LaFeSi, especially elastic properties (shear and Young’s modulus, and Poisson’s ratio), were determined by DFT distortion calculations to elucidate lattice anisotropy and stability. The antiferromagnetic transition at –7.52 GPa, predicted in our work for LaFeSi, is consistent with the reported experimentally observed antiferromagnetic ground states in CeMnSi and LaMnSi compounds having similar crystal geometry. This finding of unexpected magnetic ordering predicts that layered non-magnetic materials, like LaFeSi, may become magnetically active with lattice expansion.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Structure, Bonding, and Vibrational Dynamics of a Triamine High Energy Density Material under Pressure

High energy density materials have complex intermolecular interactions which influence their stability and performance. We used a combination of synchrotron X-ray diffraction, synchrotron infrared spectroscopy, and Raman vibrational spectroscopy, supplemented by density functional theory calculations, to probe pressure-induced changes in structure and intermolecular interactions of 1H,4'H-[3,3'-bis(1,2,4-triazole)]-4',5,5'-triamine as a model high energy density material up to 40 GPa. We find that compression of the triamine is accompanied by increased intermolecular interactions that give rise to an interesting evolution of the structure and bonding with pressure. Analysis of the equation of state determined from the X-ray diffraction indicates a change in compression mechanism near 19 GPa consistent with changes in vibrational spectra that provide evidence for a structural rearrangement associated with changes in hydrogen bonding near that pressure. As a result, the overall compressional behavior calculated theoretically agrees with that observed experimentally though differences are found that indicate the need for improved treatment of the intermolecular interactions including hydrogen bonding under pressure.

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

ReaxFF Parameter Set for Boron Clusters and Icosahedral Boron Crystals: Comparison with Density Functional Theory and Machine-Learning Potentials

Icosahedral boron materials, which include regular icosahedra of 12 boron atoms have gained increasing attention due to their potential applications as superhard materials, semiconductors, and energy storage media. However, the synthesis of high quality crystals of these materials has been a major barrier to the development of these applications. To enable computational prediction of synthesis conditions yielding high-quality icosahedral boron crystals, herein we tested and refined a set of ReaxFF parameters for the nucleation and growth of such crystals. We focused on matching the relative energies of small boron clusters obtained by density functional theory since such small clusters and similar motifs are likely present in crystal nuclei and at the interface of growing crystals. Using a training set of B 80 clusters, including a low-energy core–shell structure containing a B 12 icosahedron core and a high-energy single-shell structure produced in preliminary ReaxFF simulations, the ReaxFF parameter set was refined to better reproduce energies calculated by density functional theory (DFT). Among existing ReaxFF parameter sets and the machine-learning interatomic potentials MACE-MP-0, MACE-MP-0b3, MACE-MPA-0, PFP v7.0.0, and SevenNet-MF-ompa, only our new parameter set and PFP v7.0.0 correctly ranked these B 80 clusters. This refinement led to improved agreement with DFT for a test set of 58 clusters consisting of 8–103 boron atoms. Furthermore, our refined parameter set yielded greater local icosahedral structure than the previously existing ReaxFF parameter set for larger scale simulations of crystallization from supercooled liquid boron. Additionally, simulations of solid boron in contact with molten nickel using our refined ReaxFF parameters yielded a boron solubility value that agrees moderately well with experimental expectations, while the previous boron parameters gave a value that was much too low.

boron↗
DOE OSTI2025

Size-dependent attraction of Cu solutes to clusters formed at Ag grain boundaries

We report a size-dependent solute clustering mechanism at grain boundaries in a sputtered ultrafine-grained Ag-Cu alloy, where large Cu clusters form despite weak individual solute-solute interactions. X-ray diffraction confirms limited Cu solubility in the Ag matrix, while scanning transmission electron microscopy reveals Cu clustering at both ordinary GBs and GB junctions. Density functional theory calculations show that 12-atom Cu clusters are energetically preferred, while smaller three-atom clusters are significantly less stable. Additional calculations demonstrate a marked increase in solute-cluster attraction energy with cluster size. As a result, these findings point to a previously unrecognized pathway for grain-boundary solute clustering in immiscible systems, driven by collective solute-cluster interactions, with implications for segregation behavior and stability in nanocrystalline and ultrafine-grained alloys.

Alloys↗
DOE OSTI2025

Computational Investigation of a CO 2 Conversion Strategy via Diels–Alder Reaction in a Carbon Capture Solvent

Molecular-level insights into reactive separations are crucial for the design of new conversion pathways of carbon dioxide (CO 2 ). This work explores a postulated pathway that directs CO 2 to undergo inverse-electron-demand Diels–Alder reactions to produce heterocycles using the CO 2 chemically fixed on water-lean solvent molecules. Density functional theory calculations are applied to evaluate the lowest unoccupied molecular orbital (LUMO) energies of three types of reactants (1,3-butadiene, 1,3-cyclohexadiene, and 1,2,4,5-tetrazine) with various functional substituents. These calculations also provide a data set (5.8k data) for developing a machine learning model to efficiently predict LUMO energies. A computational screening of LUMO energies for an additional 47k diene and tetrazine candidates is performed, and a list of candidates with lowered LUMO energies by electron-withdrawing substituents is provided. These candidates are further examined by their reaction energy barriers computed from the interatomic potential or density functional theory. Two major energy barriers are identified, one for the proton transfer within the water-lean solvent and the other for the CO 2 transfer from the solvent molecule to the reactant candidate (diene or tetrazine). The functional substituents have a more significant impact on the second barrier but a very slight one on the first barrier. This exploratory work demonstrates a new possibility for guiding experimental efforts toward the chemical conversion of fixated CO 2 to value-added compounds.

Chemical reactions↗
DOE OSTI2026

A Robust Methodology to Elucidate Kinetics of Room Temperature Electrochemical Propane Adsorption on Platinum

Electrocatalytic activation of alkanes can further decarbonize chemical manufacturing by leveraging affordable renewable electricity and readily available shale gas reserves in the United States. Earlier works have identified the unique role of Pt in adsorbing and activating alkanes, like propane, at room temperature in acidic, aqueous electrolytes, revealing spontaneous formation of deeply dehydrogenated propane-derived surface species with an intact C 3 - backbone. Although an adsorption mechanism was hypothesized, it has not been explicitly investigated to date, preventing the quantification of kinetic rate parameters. A robust methodology to investigate and benchmark propane adsorption kinetics on Pt is critical for the rational design of electrocatalysts that exhibit higher selectivity toward desired partially oxidized products. Herein, we analyze an oxidative current transience that appears during the adsorption of propane on Pt in aqueous electrochemical conditions and develop a methodology that elucidates the adsorption mechanism and enables quantification of rate parameters such as order dependences and apparent activation barriers. This method yields an expected first-order dependence with respect to propane concentration at low coverage and reveals a second-order dependence with respect to the concentration of surface active sites. Additionally, the apparent activation barrier for propane adsorption was calculated using an Arrhenius analysis of the current transience under temperature control. The experimentally measured activation barrier of 35 kJ mol –1 is in excellent agreement with the theoretical barrier calculated by density functional theory (DFT). The kinetic analysis was extended, via the use of transition state theory, to extract entropy and enthalpy of activation, yielding consistent results with the proposed two-step adsorption mechanism and DFT calculations. These results demonstrate reliable quantification of kinetic parameters for electrocatalytic activation of C–H bonds in alkanes that can be employed for rational catalyst development for a versatile range of electrocatalytic conditions.

alkane activation↗
DOE OSTI2026

MnRhBi3: A Cleavable Antiferromagnetic Metal

This dataset contains DFT input and output files supporting the theoretical modeling in the associated publication (Chem. Mater. 2024, 36, 11306-11316). The calculations characterize MnRhBi3, an orthorhombic (Cmmm) van der Waals-layered intermetallic compound that cleaves easily between neighboring Bi layers. The dataset is organized into three calculation types: (i) Bulk: Structural relaxations of the periodic MnRhBi3 crystal in antiferromagnetic (AFM) and ferromagnetic (FM) configurations, using the vdW-DF-optB86b functional. These provide the equilibrium lattice constants, magnetic energy differences (AFM is 0.5 meV/f.u. lower than FM), and magnetic moments (4.4 µB/Mn, 0.17 µB/Rh, 0.18 µB/Bi) reported in Table 1 of the main text. (ii) Slab: Same magnetic configurations computed with an 18 Ang vacuum layer introduced between Bi layers, used to calculate the cleavage energy Ec = 0.56 J/m2 (AFM) and 0.57 J/m2 (FM), establishing MnRhBi3 as a van der Waals-layered material comparable to graphite, MoS2, and CrI3. (iii) ELF: Single-point calculation on the relaxed bulk AFM geometry with LELF=.TRUE., producing the ELFCAR file used to generate electron localization function isosurfaces and contour maps (Fig. 2, main text) showing Bi lone pairs directed into the van der Waals gaps. All folders contain CONTCAR, INCAR, KPOINTS, OUTCAR, and POSCAR. The ELF/ folder additionally contains ELFCAR. Calculations were performed using VASP 6.3.2 with PBE + vdW-DF-optB86b, PAW potentials, and an energy cutoff of 800 eV.

36 MATERIALS SCIENCE↗
NASA NTRS2021

Machine Learning the COSMO Model for Predicting Thermodynamics of Electrolyte Mixtures

Bottom-up design of electrolyte mixtures for battery systems requires predicting macro thermodynamic properties from molecular constituents. For instance, molten salt electrolyte batteries require conditions far above room temperature to operate. Therefore, discovering mixtures with increasingly lower eutectic melting points is desirable. A model that can approximate chemical activity is a valuable tool to search through the vast compositional design space. Machine learning can predict properties of materials such as vibrational free energies, electronic energy gaps, and thermal conductivities. Moreover, they can learn physical models such as interatomic potentials. The COSMO-SAC model uses theory and empirical parameterization to predict liquid-vapor and liquid-solid properties using first-principles calculations. However, obtaining activity coefficients required for parameterizing the COSMO-SAC model is costly and limited to a select chemical space. In this work, we explored if machine learning methods could improve the COSMO-SAC model and bridge density functional theory calculations to liquid phase thermodynamic properties. Our data-driven approach uses existing databases for sigma-profiles of organic solvents and reconciles their methodological differences via ensemble averaging. First, an optimal machine learning model is constructed for each dataset. Our machine learning algorithms use the sigma-profile as an input feature to predict binary mixtures' activity coefficients using multi-output regression. Each dataset uses different choices of functionals, methods, and basis sets. Therefore, our ensemble model attempts to predict corrected activity coefficients given the combination of all the model outputs. The activity coefficients used for training are generated using the COSMO-SAC model. This approach enables the extraction of meaningful information from the existing datasets to improve the COSMO-SAC model for obtaining thermodynamic properties of electrolyte mixtures. With the liquid phase activities, we can identify electrolyte mixtures that meet desired phase equilibria conditions.

Thermodynamics↗
DOE OSTI2025

Prediction of Solute Segregation at Metal/Oxide Interfaces Using Machine Learning Approaches

The atomic structure and chemistry at metal/oxide interfaces play a crucial role in determining their properties. However, studying semi-coherent metal/oxide interfaces that include misfit dislocations through density functional theory (DFT) is often computationally expensive due to the large number of atoms involved, ranging from hundreds to thousands. In this study, we explore solute segregation behavior at the Fe/Y 2 O 3 interface—an important model interface for cladding applications in nuclear fission reactors—by combining DFT calculations with a machine learning (ML) approach. ML models are trained using DFT-calculated segregation energies (𝐸 𝑆𝑒𝑔 ) to identify the key chemical and geometric factors influencing solute segregation at metal/oxide interfaces, revealing the competition between these features in determining 𝐸 𝑆𝑒𝑔 . Moreover, the segregation behavior at a specific Fe/Y 2 O 3 interface is predicted with high accuracy using ML models trained on data from this interface. Furthermore, it is found that the ML models could also predict solute segregation at a different Fe/Y 2 O 3 interface with a new orientation relationship (OR), at a computational cost of less than 1/45 of that required for similar DFT calculations.

36 - MATERIALS SCIENCE↗
DOE OSTI2025

Spin qubit properties of the boron-vacancy/carbon defect in the two-dimensional hexagonal boron nitride

Spin qubit defects in two-dimensional materials have a number of advantages over those in three-dimensional hosts including simpler technologies for defect creation and control, as well as qubit accessibility. In this work, we select the V B C B defect in the hexagonal boron nitride (hBN) as a possible optically controllable spin qubit and explain its triplet ground state and neutrality. In this defect a boron vacancy is combined with a carbon dopant substituting the closest boron atom to the vacancy. Our density-functional-theory calculations confirmed that the system has dynamically stable spin triplet and singlet ground states. As revealed from our linear response GW calculations, the spin-sensitive electronic states are localized around the three undercoordinated N atoms and make local peaks in the density of electronic states within the bandgap. Using the triplet and singlet ground state energies, as well as the energies of the optically excited states, obtained from solution to the Bethe–Salpeter equation, we construct the spin-polarization cycle, which is found to be favorable for the spin qubit initialization. The calculated zero-field splitting parameters ensure that the splitting energy between the spin projections in the triplet ground state is comparable to that of the known spin qubits. We thus propose the V B C B defect in hBN as a promising spin qubit.

2D BN↗
DOE OSTI2024

Low-temperature etching of silicon oxide and silicon nitride with hydrogen fluoride

Etching of high aspect ratio features into alternating SiO 2 and SiN layers is an enabling technology for the manufacturing of 3D NAND flash memories. In this paper, we study a low-temperature or cryo plasma etch process, which utilizes HF gas together with other gas additives. Compared with a low-temperature process that uses separate fluorine and hydrogen gases, the etching rate of the SiO 2 /SiN stack doubles. Both materials etch faster with this so-called second generation cryo etch process. Pure HF plasma enhances the SiN etching rate, while SiO 2 requires an additional fluorine source such as PF 3 to etch meaningfully. Further, the insertion of H 2 O plasma steps into the second generation cryo etch process boosts the SiN etching rate by a factor of 2.4, while SiO 2 etches only 1.3 times faster. We observe a rate enhancing effect of H 2 O coadsorption in thermal etching experiments of SiN with HF. Ammonium fluorosilicate (AFS) plays a salient role in etching of SiN with HF with and without plasma. AFS appears weakened in the presence of H 2 O. Density functional theory calculations confirm the reduction of the bonding energy when NH 4 F in AFS is replaced by H 2 O.

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

Ghost states and surface structures of the charge density wave kagome metal ScV 6 Sn 6

In this work, we investigate the high-temperature phase of the kagome metal ScV 6 Sn 6 using scanning tunneling microscopy/spectroscopy (STM/S) and density functional theory calculations. STM topographic images of the cleaved sample reveal two distinct surface terminations: flat islands with Sn termination and trenches terminated by kagome layers with Sn as the outermost atomic layer. STS measurements on the Sn-terminated and kagome-terminated surfaces show significant differences, in particular the presence of large density of states near the Fermi level in the former case. Our first-principles calculations reveal that the charge density on the kagome-terminated surface gives rise to “ghost states” which show intensity away from surface atoms, arising due to hybridization of orbitals above the surface. These states can obscure the intrinsic properties of the surface, potentially leading to misattribution of the surface termination. This underscores the need for careful interpretation in STM studies, especially when discerning surface states of localized states. Understanding the surface structure of this versatile quantum material provides essential information for interpreting surface-sensitive experiments, tailoring material properties, engineering interfaces, and controlling stability and reactivity. This knowledge paves the way for further exploration and potential applications of kagome lattice materials in various fields, including quantum computing, topological physics, and advanced electronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Hollow-structured Ni-N-C catalysts for highly selective CO 2 electroreduction

Atomically dispersed single-atom catalysts have emerged as promising non-precious catalyst alternatives to expensive Ag and Au catalysts for electrochemical CO 2 reduction reaction (CO 2 RR). In particular, nickel-nitrogen-carbon (Ni-N-C) catalysts have demonstrated a high faradaic efficiency (FE) toward CO formation at low overpotentials. Nonetheless, the exact nature of Ni active sites under CO 2 RR remains elusive and conventional Ni-N-C catalysts are limited by microporosity and low density of Ni single atoms, hindering performance in CO 2 electrolyzers. Here, we report the synthesis of hollow-structured Ni-N-C ( hs -Ni-N-C) catalysts via a post-synthesis modification (PSM) strategy using partial ligand exchange of 2-methylimidazole with 3-amino-1,2,4-triazole. This approach enables the formation of a hollow structure, resulting in more than a twofold increase in Ni atom density compared to regular Ni-N-C (r-Ni-N-C). In a zero-gap CO 2 electrolyzer, the optimized hs -Ni-N-C allows for achieving an FE CO of 97% at a current density of > 100 mA cm⁻ 2 , while maintaining high CO selectivity with stable performance over 100 h at 2.5 V. hs-Ni-N-C shows a more than sevenfold increase in the CO partial current density relative to r-Ni-N-C resulting from the combined effects of a higher density of Ni single-atom sites, improved kinetics, and lower transport resistance under the operating conditions, as indicated by electrochemical impedance spectra and distribution of relaxation times analysis. Operando high energy-resolution X-ray absorption spectroscopy (XAS) reveals that atop-bonded CO on Ni single sites induces dynamic transformations of the Ni–N coordination environment, leading to a symmetric coordination structure of hs -Ni-N-C. Under CO 2 RR, the catalysts undergo a more pronounced structural change and form a minor fraction of Ni nanoparticles. Density functional theory calculations are consistent with the XAS results and provide molecular insights showing that the interplay between protonation and CO adsorption leads to adsorbate-induced restructuring of the Ni single atom. This work demonstrates the synergistic role of hollow structure and high-density Ni atoms in governing CO 2 RR selectivity and provides mechanistic insights into the structural dynamics of single-atom catalysts under operating conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Predicting phase transitions in PbTi⁢O 3 using zentropy through quasiharmonic phonon calculations

According to x-ray diffraction (XRD) measurements, PbTi⁢O 3 undergoes a phase transition from a tetragonal ferroelectric (FE) phase to a cubic paraelectric phase at 763 K. However, x-ray absorption fine-structure (XAFS) measurements indicate that PbTi⁢O 3 is locally tetragonal even after the phase transition. The difference in these results is because XAFS measurements can probe local features of a structure, while XRD averages over such local features. For both measurements to be consistent, PbTi⁢O 3 is macroscopically cubic but locally tetragonal after the phase transition. Despite this, most models, such as the Landau-Ginsburg-Devonshire theory and effective Hamiltonians, are still unable to explain this phenomenon. Moreover, these methods involve model parameters fitted to experimental or theoretical data and do not consider other tetragonal configurations, such as domain walls, to predict the phase transition. In our previous study, we used our zentropy approach to predict the phase transition by considering the tetragonal FE ground-state configuration and the tetragonal 90° and 180° domain wall configurations with their total energies at 0 K. Here, in this paper, the Helmholtz energies of the three configurations are obtained from density functional theory calculations through energy-volume curves and phonon calculations. The predicted phase transition temperature using the meta-GGA 𝑟 2⁢ SCAN and revised multiplicities of configurations is 716 K, showing good agreement with the experimental value of 763 K.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Tailoring the structural durability and proton conductivity of electrolytes for highly fuel-flexible and reversible ceramic cells

A durable and high ionic conducting electrolyte is critical for achieving fuel-flexible and reversible protonic ceramic cells (PCCs) at reduced temperatures since the developed electrolyte materials are vulnerable to steam, CO 2 , or coking deterioration. Here, we report a fast-conducting electrolyte material BaZr 0.06 Ce 0.7 Y 0.06 Yb 0.06 Hf 0.06 Gd 0.06 O 3−δ (BZCYYbHG), demonstrating excellent durability against CO 2 and H 2 O under the realistic electrolysis operations, and a high conductivity of 0.017 S cm −1 at 550 °C for lowering the PCC operating temperature. Further, density functional theory calculations indicate that the higher configurational entropy of mixing at the B-site cations slightly reduces the hydrogen adsorption energy, suggesting a higher incorporation rate of protons or hydrogen atoms into the electrolyte bulk. Ultimately, single cells with the BZCYYbHG electrolyte deliver peak power densities of 1.39, 1.12, and 0.7 W cm −2 in H 2 , NH 3 , and wet CH 4 at 550 °C with promising durability. In addition, the PCCs achieve a current density of −1.61 A cm −2 at 1.3 V and 550 °C with a high faradaic efficiency of 91.3% at −0.5 A cm −2 , enabling stable operations in steam electrolysis mode under humid air (30% H 2 O), wet air containing CO 2 (up to 10%), and reversible cycling.

25 ENERGY STORAGE↗
DOE OSTI2026

Understanding Inlet Concentration Effects on the Electrocatalytic Conversion of CO 2 to Formic Acid in Gas-Fed Electrolyzers

The electrochemical CO 2 reduction reaction (CO2RR) to produce value-added products remains a developing technology for utilizing waste CO 2 streams. Most device-level CO2RR studies use pure CO 2 gas feeds; however, the effect of dilute CO 2 on the electrolyzer performance is an important consideration for large-scale electrolyzer operation, single-pass conversion, and real-world CO 2 source utilization. This work investigates the effect that the CO 2 concentration has on the performance of formic acid (HCOOH) producing tin oxide (SnO 2 ) and bismuth oxide (Bi 2 O 3 ) catalysts in an electrolyzer device setting. Surprisingly, SnO2 demonstrated an approximately 20% increase in HCOOH selectivity (Faradaic efficiency) when the CO 2 concentration decreased from 100 to 20%. In contrast, Bi 2 O 3 consistently demonstrated high selectivity toward HCOOH across the same CO 2 concentration range. The effects of the CO 2 concentration on selectivity were further investigated with half-cell experiments and in situ Raman spectroscopy, which revealed dynamic changes in the cathodic overpotential and chemical state of the catalyst that depended on the CO 2 concentration. Density functional theory calculations showed how changes in the surface oxidation state of Sn, varying from fully oxidized SnO 2 to metallic Sn(0), affect the thermodynamic barriers of the three main observed products: HCOOH, CO, and H 2 . Our results indicate that dilute CO 2 concentrations required larger cathodic overpotentials to sustain a fixed current density, which, in turn, pushed the Sn-based catalyst toward a more reduced surface that was favorable to HCOOH formation. On the other hand, the Bi-based catalyst remained in a metallic state at CO2RR-relevant potentials and demonstrated a consistent product selectivity regardless of CO 2 concentration. These findings highlight how varying the CO 2 inlet gas concentrations affects the chemical state of catalysts and the resulting performance metrics.

42 ENGINEERING↗
DOE OSTI2024

UOTe: Kondo‐Interacting Topological Antiferromagnet in a Van der Waals Lattice

Since the initial discovery of 2D van der Waals (vdW) materials, significant effort has been made to incorporate the three properties of magnetism, band structure topology, and strong electron correlations—to leverage emergent quantum phenomena and expand their potential applications. However, the discovery of a single vdW material that intrinsically hosts all three ingredients has remained an outstanding challenge. Here, in this work, the discovery of a Kondo-interacting topological antiferromagnet is reported in the vdW 5f electron system UOTe. It has a high antiferromagnetic (AFM) transition temperature of 150 K, with a unique AFM configuration that breaks the combined parity and time reversal (PT) symmetry in an even number of layers while maintaining zero net magnetic moment. This angle-resolved photoemission spectroscopy (ARPES) measurements reveal Dirac bands near the Fermi level, which combined with the theoretical calculations demonstrate UOTe as an AFM Dirac semimetal. Within the AFM order, the presence of the Kondo interaction is observed, as evidenced by the emergence of a 5ƒ flat band near the Fermi level below 100 K and hybridization between the Kondo band and the Dirac band. The density functional theory calculations in its bilayer form predict UOTe as a rare example of a fully-compensated AFM Chern insulator.

36 MATERIALS SCIENCE↗