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At least 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Identifying Critical Electrode Metrics for Efficient, Selective CO 2 Electrochemical Conversion

Low-temperature electrochemical CO 2 reduction (CO 2 R) in zero-gap membrane electrode assembly (MEA) reactors presents a scalable route to fuels and carbon utilization. However, performance at industrially relevant current densities hinges on mesoscale catalyst layer integration, particularly at the ionomer|catalyst interface. Here, we demonstrate a generalizable in situ electrochemical impedance spectroscopy (EIS) method. We utilize this technique to decouple electrode-level parameters that are correlated to the overall MEA performance. By performing this ex situ EIS method on CO 2 -to-CO catalyst-coated membranes with systematically varied ionomer-to-catalyst (I:C) ratios, we reveal a pronounced dependence of performance, ion transport resistance, and catalyst utilization on the I:C ratio as well as the electrode conditioning. We demonstrate that an optimal I:C ratio exists at which ion transport resistance is minimized and Faradaic efficiency for CO production is maximized. Beyond the electrodes examined, here we compare ion transport resistance to MEA selectivity/Faradaic efficiency obtained in prior studies, revealing a clear correlation between the two. These results suggest that ion transport resistance within the catalyst layer may be a quantitative predictor of MEA performance which underscores the importance of mesoscale integration in achieving scalable CO 2 R technologies.

08 HYDROGEN↗
DOE OSTI2024

Machine-Learned Force Field Modeling of Metal Organic Frameworks for CO2 Direct Air Capture

To cope with legacy greenhouse gas emissions and to achieve net-zero emissions by 2050, the U.S. Department of Energy (DOE) is funding efforts to develop direct air capture (DAC), a method for removing CO2 directly from air. Metal organic frameworks (MOFs) have been studied as DAC sorbent materials because of their structural and chemical diversity. Thermodynamic calculations using classical force fields are often used to screen MOFs for their performance in separations such as CO2 capture. Machine-learned force fields (MLFFs) can use machine learning to form quantitative relationships between a material’s chemical structure and the forces and energies predicted by more accurate quantum mechanical calculations, such as dispersion-corrected density functional theory (DFT). These descriptions of forces and energies can be used to improve the accuracy of adsorption calculations. In this work, MLFF models were developed for MOFs to achieve DFT-level accuracy for the forces and energies associated with MOF flexibility and CO2 adsorption. These methods were parametrized based on thousands of DFT calculations of CO2 in flexible MOFs and used to predict MOF structural properties as well as CO2 adsorption properties.

Findley, John↗
DOE OSTI2025

Results and lessons learned from accelerating radio frequency modeling using machine learning [slides]

The “advanced tokamak” reactor concept is a leading candidate for a steady state fusion pilot plant. An advanced tokamak (AT) sustains a majority of the required plasma current with effects resulting from maintenance of the peaked pressure at the device center. This current is augmented by auxiliary current drive sources. These auxiliary actuators may consist of neutral particle beams and/or radio frequency (RF) systems such as lower hybrid current drive (LHCD) and high harmonic fast wave (HHFW) current drive using radio and microwaves from antennas. The primary focus of this work is to develop models of RF current profile control suitable for use in integrated modeling frameworks and for real-time control in experiments. Direct physics models of RF current drive can be computationally intensive. In order to achieve predictive times appropriate for the thousands of calls needed in real-time control of experiments and for use in integrated models, we will apply modern machine learning (ML) techniques to accelerate these models and interpolate their results. To generate the fast and accurate models for use in control level algorithms and integrated modeling we need to replace present models with high dimensional interpolation of their results. We will perform additional simulations across a broader parameter range for EAST and other tokamaks in different physics regimes (Alcator C-Mod, DIII-D, WEST, CFETR, ARC, ITER) and combine them into a larger database for training and testing of the ML models. Further testing of the control level models with experimental current profile data from EAST and C-Mod tokamaks will provide additional confirmation of the control level model before integration in a tokamak control system or integrated modeling suite. ML will be used to optimize the selection of training data consisting of RF current driven at different values of density profile, temperature profile, plasma current, and wavenumber. ML will also be used to facilitate classification of current drive from these input data. The output of this effort will be a validated classifier capable of determining the current drive profiles for HHFW CD and LHCD on a mille-second timescale. This will provide a breakthrough capability enabling real-time control of RF driven current profiles in experiments including ITER ICRF and use integrated modeling frameworks requiring thousands of current profile calculations in discharge simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Thermal reactor systems and methods

An exemplary embodiment of the present invention provides a reactor system comprising: a reaction vessel comprising a reactant, a heat transfer fluid and a first reaction product, wherein the heat transfer fluid has a greater density than the first reaction product such that at least a portion of the first reaction product floats on a surface of the heat transfer fluid; a first outlet positioned at a surface level of the first reaction product, the first outlet configured to output a first outlet flow comprising at least a portion of the first reaction product and at least a portion of the heat transfer fluid; wherein the heat transfer fluid is configured to provide thermal energy to the reactant in the reaction vessel to form the first reaction product.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Electronic Trap-State Modulation in Sm-Doped SnO 2 Nanofibers Enables Ultrasensitive Hydrogen Sensing

The demand for sub-ppm hydrogen (H 2 ) sensing is growing across emerging applications such as environmental monitoring, breath-based disease diagnostics, and early-stage battery failure detection. However, achieving reliable ppb-level detection with chemiresistive metal oxide sensors remains challenging. At trace gas concentrations, resistance modulation is often insufficient, particularly in the absence of noble metal catalysts. Here, we report samarium-doped tin dioxide (Sm-SnO 2 ) nanofibers in which electronic trap-state modulation is exploited to enable ultrasensitive hydrogen sensing. The 2 at% Sm-doped SnO 2 nanofibers exhibited markedly enhanced H 2 sensitivity, achieving clear detection down to 25 ppb H 2 at 200 °C, with a theoretical limit of detection of 4.5 ppb, placing this material among the most sensitive noble-metal-free SnO 2 -based H 2 sensors reported to date. Mechanistic investigations through X-ray photoelectron spectroscopy and electron energy loss spectroscopy revealed that Sm 3+ doping introduces deep trap states associated with charge-compensating defect complexes. These states reduce free carrier density, increase baseline resistance, and enable trap-assisted charge release during H 2 exposure, thereby amplifying the sensing response. Trap-state engineering via rare-earth doping, exemplified by Sm-SnO 2 , provides an effective pathway for achieving ppb-level hydrogen detection in noble-metal-free chemiresistive sensors.

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

A three-dimensional laser ray-tracing methodology for radiation-hydrodynamics simulations

We report on a methodology for performing laser ray-tracing in three spatial dimensions for radiation-hydrodynamics simulation codes. Our method, which is an extension of that developed in Haines et al., Comput. Fluids 201, 104478 (2020), utilizes an automatically generated separate mesh for the laser ray-tracing from the radiation-hydrodynamics mesh. This enables the laser mesh to be tailored to minimize ray noise with significantly fewer rays than would be required when the ray-tracing is performed on the radiation-hydrodynamics mesh, primarily by allowing the use of high-aspect-ratio cells that are not suitable for hydrodynamics solvers. For a planar target, we show that our method provides a ≈ 100× reduction in computational expense to achieve a fixed level of ray noise relative to ray-tracing directly on the radiation-hydrodynamics mesh. The relatively low ray requirement also enables efficient computation of cross-beam energy transfer. Each cell in the logically cubic laser mesh is a non-convex dodecahedron with triangular sides, and numerical integration of the ray trajectories and inverse bremsstrahlung is performed by mapping each cell to the unit cube. We will describe our methodology in detail as well as its implementation in the xRAGE radiation-hydrodynamics code, discuss performance, and present the results from applying the methodology to test problems with analytic solutions for laser ray-tracing through a quadratic density gradient with an analytic solution as well as for a laser-driven heat front. In 3D radiation-hydrodynamics simulations of laser-driven experiments performed on the National Ignition Facility, laser ray-tracing with our methodology uses less than 1% of total computational time while introducing acceptably low levels of ray noise.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Chemical and structural evolutions of Li–Mn-rich layered electrodes at different current densities

Although the two active redox centers in Li-rich cathodes, including the anionic and cationic contributions, can enable Li-ion batteries to achieve outstanding specific energy, their behaviors at different current densities have not been clarified. In this report we provide a comparative study of transition metals (TMs) and oxygen redox activities by directly accessing their oxidation states in Li-rich materials operated at very different current rates. Our data reveal that the oxidation of oxygen in the near-surface region is at the same level for electrodes cycled with a wide range of current rates, indicating a reaction gradient of lattice oxygen redox reactions. The oxidation process of lattice oxygen is found to be dynamically compatible with that of the TMs. Combining the results of first principles calculations and complementary experimental findings, we propose a detailed mechanism of structural distortion from octahedral Li to tetrahedral Li and the role of oxygen vacancy in Li + diffusion. It is found that fast delithiation occurring at high current densities can easily cause local structural transformation, leading to a limited Li + diffusion rate and consequently suppressing rate capability.

25 ENERGY STORAGE↗
DOE OSTI2024

QuTree: A tree tensor network package

Here we present QuTree, a C++ library for tree tensor network approaches. QuTree provides class structures for tensors, tensor trees, and related linear algebra functions that facilitate the fast development of tree tensor network approaches such as the multilayer multiconfigurational time-dependent Hartree approach or the density matrix renormalization group approach and its various extensions. We investigate the efficiency of relevant tensor and tensor network operations and show that the overhead for managing the network structure is negligible, even in cases with a million leaves and small tensors. QuTree focuses on providing simple, high-level routines while retaining easy access to the backend to facilitate novel developments. We demonstrate the capabilities of the package by computing the eigenstates of coupled harmonic oscillator Hamiltonians and performing random circuit simulations on a virtual quantum computer.

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

Carbazole-Based Hole Transport Polymer for Methylammonium-Free Tin-Lead Perovskite Solar Cells with Enhanced Efficiency and Stability

As the most commonly used hole transport material (HTM) in tin-lead (Sn-Pb) perovskite solar cells (PSCs), poly(3,4-ethylenedioxythiophene) polystyrenesulfonate (PEDOT:PSS) limits the power conversion efficiency (PCE) and stability of the PSCs due to its acidic characteristics. Herein, an easily synthesized polymer HTM poly[(phenyl)imino[9-(2-ethylhexyl)carbazole]-2,7-diyl] (CzAn) with a shallow highest occupied molecular orbital (HOMO) level of -4.95 eV is used in a p-i-n structure, methylammonium-free, Sn-Pb PSC to replace PEDOT:PSS. Upon optimization using doping and surface engineering, high quality Sn-Pb PSCs could be successfully fabricated, boosting the PCE to 22.6% (stabilized PCE of 21.3%) compared with 21.2% for PEDOT:PSS. The perovskite films prepared on the modified CzAn HTM possess improved crystallinity, reduced trap-state density, and larger carrier mobility resulting in PSCs with greatly improved stability.

carrier mobility↗
DOE OSTI2023

Intermetallic Single-Atom Alloy In–Pd Bimetallene for Neutral Electrosynthesis of Ammonia from Nitrate

Harvesting recyclable ammonia (NH 3 ) from the electrocatalytic reduction of nitrate (NO 3 RR) offers a sustainable strategy to close the ecological nitrogen cycle from nitration contamination in an energy-efficient and environmentally friendly manner. The emerging intermetallic single-atom alloys (ISAAs) are recognized to achieve the highest site density of single atoms by isolating contiguous metalatoms into single sites stabilized by another metal within the intermetallic structure, which holds promise to couple the catalytic benefits from intermetallic nanocrystals and single-atom catalysts for promoting NO 3 RR. Herein, ISAA In-Pd bimetallene, in which the Pd single atoms are isolated by surrounding In atoms, is reported to boost neutral NO 3 RR with a NH 3 Faradaic efficiency(FE) of 87.2%, a yield rate of 28.06 mg h -1 mg Pd -1 , and an exceptional electrocatalytic stability with increased activity/selectivity over 100 h and 20 cycles. The ISAA structure induces substantially diminished overlap of Pdd-orbitals and narrowed p-d hybridization of In-p and Pd-d states around the Fermi level, resulting in a stronger NO 3 - adsorption and a depressed energy barrier of the potential-determining step for NO 3 RR. Finally, further integrating the NO 3 RR catalyst into a Zn-NO 3 - flow battery as the cathode delivers a power density of 12.64 mW cm -2 and a FE of 93.4% for NH 3 production.

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

Fault Tolerant Decoding of QLDPC-GKP Codes with Circuit Level Soft Information

Concatenated bosonic-stabilizer codes have recently gained prominence as promising candidates for achieving low-overhead fault-tolerant quantum computing in the long term. In such systems, analog information obtained from the syndrome measurements of an inner bosonic code is used to inform decoding for an outer code layer consisting of a discrete-variable stabilizer code such as a surface code. The use of Quantum Low-Density Parity Check (QLDPC) codes as an outer code is of particular interest due to the significantly higher encoding rates offered by these code families, leading to a further reduction in overhead for large-scale quantum computing. Recent works have investigated the performance of QLDPC-GKP codes in detail, and the use of analog information from the inner code significantly boosts decoder performance. However, the noise models assumed in these works are typically limited to depolarizing or phenomenological noise. In this paper, we investigate the performance of QLDPC-GKP concatenated codes under circuit-level noise, based on a model introduced by Noh et al. in the context of the surface-GKP code. To demonstrate the performance boost from analog information, we investigate three scenarios: (a) decoding without soft information, (b) decoding with precomputed error probabilities but without real-time soft information, and (c) decoding with real-time soft information obtained from round-to-round decoding of the inner GKP code. Results show minimal improvement between (a) and (b), but a significant boost in (c), indicating that real-time soft information is critical for concatenated decoding under circuit-level noise. We also study the effect of measurement schedules with varying depths and show that using a schedule with minimum depth is essential for obtaining reliable soft information from the inner code.

Borah, Shantom K. [Arizona U. (main)]↗
DOE OSTI2024

Joint inference of multiplicative and additive systematics in galaxy density fluctuations and clustering measurements

Galaxy clustering measurements are a key probe of the matter density field in the Universe. With the era of precision cosmology upon us, surveys rely on precise measurements of the clustering signal for meaningful cosmological analysis. However, the presence of systematic contaminants can bias the observed galaxy number density, and thereby bias the galaxy two-point statistics. As the statistical uncertainties get smaller, correcting for these systematic contaminants becomes increasingly important for unbiased cosmological analysis. We present and validate a new method for understanding and mitigating both additive and multiplicative systematics in galaxy clustering measurements (two-point function) by joint inference of contaminants in the galaxy overdensity field (one-point function) using a maximum-likelihood estimator (MLE). We test this methodology with Kilo-Degree Survey-like mock galaxy catalogues and synthetic systematic template maps. We estimate the cosmological impact of such mitigation by quantifying uncertainties and possible biases in the inferred relationship between the observed and the true galaxy clustering signal. Our method robustly corrects the clustering signal to the sub-percent level and reduces numerous additive and multiplicative systematics from 1.5σ to less than 0.1σ for the scenarios we tested. In addition, we provide an empirical approach to identifying the functional form (additive, multiplicative, or other) by which specific systematics contaminate the galaxy number density. Even though this approach is tested and geared towards systematics contaminating the galaxy number density, the methods can be extended to systematics mitigation for other two-point correlation measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Effect of cell compression on the performance and the structure of proton exchange membrane water electrolyzer (PEMWE) assembly

Here, in the field of water electrolysis, the proton exchange membrane water electrolyzer (PEMWE) is currently the most advanced technology for producing hydrogen without emitting CO 2 . Although PEMWE plants are already in operation, further research is needed to improve cell efficiency and reduce the use of rare materials, such as iridium oxide catalysts for the oxygen evolution reaction (OER). One of the main causes of performance loss in PEMWE is the relatively low electric conductivity of the porous transport layer (PTL) and of the anode catalyst layer, which results in ohmic losses and low catalyst utilization during high current density operation. The objective of this study is to investigate how optimization of the PTL and electrode interface can increase the cell performance. To this end, we tested different cell assemblies using fibrous and sintered PTLs, decreasing membrane thickness, reducing iridium loading, and inserting a microporous layer to increase contact surface area. Electrochemical characterization of each cell configuration was systematically performed at various compression levels as the pressure is a crucial parameter influencing the electrode/PTL contact area. In parallel, X-ray microcomputed tomography (micro-CT) was employed to investigate the effects of cell hydration and compression on the structure of PEMWE components. This study combining electrochemistry and micro-CT imaging presents how optimizing the electrode/PTL contact surface area, minimizes ohmic losses, and enables PEMWE operation with low iridium loading at high current densities.

Catalyst - PTL interface↗
DOE OSTI2022

Multi-objective goal-directed optimization of de novo stable organic radicals for aqueous redox flow batteries

Abstract Advances in the field of goal-directed molecular optimization offer the promise of finding feasible candidates for even the most challenging molecular design applications. One example of a fundamental design challenge is the search for novel stable radical scaffolds for an aqueous redox flow battery that simultaneously satisfy redox requirements at the anode and cathode, as relatively few stable organic radicals are known to exist. To meet this challenge, we develop a new open-source molecular optimization framework based on AlphaZero coupled with a fast, machine-learning-derived surrogate objective trained with nearly 100,000 quantum chemistry simulations. The objective function comprises two graph neural networks: one that predicts adiabatic oxidation and reduction potentials and a second that predicts electron density and local three-dimensional environment, previously shown to be correlated with radical persistence and stability. With no hard-coded knowledge of organic chemistry, the reinforcement learning agent finds molecule candidates that satisfy a precise combination of redox, stability and synthesizability requirements defined at the quantum chemistry level, many of which have reasonable predicted retrosynthetic pathways. The optimized molecules show that alternative stable radical scaffolds may offer a unique profile of stability and redox potentials to enable low-cost symmetric aqueous redox flow batteries.

25 ENERGY STORAGE↗
DOE OSTI2023

A Combined Wave Function and Density Functional Approach for K-Edge X-ray Absorption Near-Edge Spectroscopy: A Case Study of Hydrated First-Row Transition Metal Ions

The prediction of X-ray absorption spectra (XAS) of transition metal complexes has important and broad application areas in chemistry and biology. In this letter, we have investigated the predictive ability of multiconfiguration pair-density functional theory (MC-PDFT) for X-ray absorption spectra by calculating the metal K pre-edge features of aquated 3d transition metal ions in common oxidation states. MC-PDFT results were compared with experimentally measured spectra as well as analyzed against results from restricted active-space second-order perturbation theory (RASPT2) and time-dependent density functional theory (TDDFT). As expected, TDDFT performs well for excited states that can be accurately represented by singly excited configurations but fails for excited states where higher order excitations become important. On the other hand, both RASPT2 and MC-PDFT provide quantitatively accurate results for all excited states irrespective of their character. While core-level spectroscopy with RASPT2 is accurate, it is computationally expensive. Finally, our results show that MC-PDFT performs equally well with significantly lower computational cost and is an encouraging alternate approach for X-ray spectroscopies.

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

Elucidating the Synergic Effect in Nanoscale MoS 2 /TiO 2 Heterointerface for Na‐Ion Storage

Abstract Interface engineering in electrode materials is an attractive strategy for enhancing charge storage, enabling fast kinetics, and improving cycling stability for energy storage systems. Nevertheless, the performance improvement is usually ambiguously ascribed to the “synergetic effect”, the fundamental understanding toward the effect of the interface at molecular level in composite materials remains elusive. In this work, a well‐defined nanoscale MoS 2 /TiO 2 interface is rationally designed by immobilizing TiO 2 nanocrystals on MoS 2 nanosheets. The role of heterostructure interface between TiO 2 and MoS 2 by operando synchrotron X‐ray diffraction (sXRD), solid‐state nuclear magnetic resonance, and density functional theory calculations is investigated. It is found that the existence of a hetero‐interfacial electric field can promote charge transfer kinetics. Based on operando sXRD, it is revealed that the heterostructure follows a solid‐solution reaction mechanism with small volume changes during cycling. As such, the electrode demonstrates ultrafast Na + ions storage of 300 mAh g −1 at 10 A g −1 and excellent reversible capacity of 540 mAh g −1 at 0.2 A g −1 . This work provides significant insights into understanding of heterostructure interface at molecular level, which suggests new strategies for creating unconventional nanocomposite electrode materials for energy storage systems.

25 ENERGY STORAGE↗
DOE OSTI2023

Assessing the Role of Interfacial and Metal Sites in Pt/TiO2-Catalyzed Acetic Acid Hydrodeoxygenation

Thermochemical conversion of biomass to produce drop-in quality biofuels typically involves hydrodeoxygenation (HDO) steps following catalytic fast pyrolysis (CFP) to remove excess oxygen and create a more-stable bio-oil product. HDO reactions are performed by co-feeding the CFP vapor-phase product and H2 gas over a bi-functional catalyst. Noble-metal catalysts supported on reducible metal oxides (e.g., Pt/TiO2) are active and selective toward these HDO reactions. Griffin and co-workers showed that Pt/TiO2 catalysts promote the desired deoxygenation steps for m-cresol HDO while mitigating undesired C-C bond-breaking steps that reduce the overall value/energy density of the biofuel. Such model-compound studies to inform the design of improved catalysts for HDO chemistry are necessary to improve the overall process economics/efficiencies for biofuels production. One important class of bio-derived compounds that has not been studied extensively with respect to HDO chemistry, particularly at the atomic level, is carboxylic acids. Past experimental work indicates that Pt/C and Pt/TiO2 catalysts are selective toward C-C and C-O bond-dissociation products for acetic acid HDO, respectively. To understand the role of Pt/TiO2 active sites in this observed change in selectivity and guide catalyst development, the work in this presentation focuses on modeling the role of Pt-metal and Pt-TiO2-interfacial sites in promoting key C-C bond-breaking, C-O bond-breaking, and (de)hydrogenation steps in acetic acid HDO. Density functional theory (DFT) calculations were performed using the Vienna Ab initio Simulation Package (VASP). The exchange-correlation functional was approximated by the Perdew-Burke-Ernzerhof functional. Dispersion interactions were captured using the D3 method. Projector augmented-wave potentials described electron-ion interactions, and electron wavefunctions were expanded via a planewave basis with an energy cutoff of 500 eV. Activation barriers were calculated using the climbing image nudged elastic band method. Results and Discussion: To discern the role of Pt-metal and Pt-TiO2 interface sites in promoting acetic acid HDO chemistry, Pt(111) slab and anatase TiO2(101)-supported Pt-nanowire (PtNW/OH-TiO2) surface models were constructed, respectively. Because H2 is co-fed in HDO reactions, the anatase support was terminated with OH groups. Interfacial vacancies have been shown to facilitate Ru/TiO2-catalyzed phenol HDO; thus, an interfacial model with an OH vacancy was also considered (PtNW/OHv-TiO2). Pt-TiO2-interface sites stabilize adsorption of all studied acetic acid HDO surface intermediates relative to terrace Pt-metal sites, particularly when an interfacial-OH vacancy is present. Oxygenated species prefer to bind at the OH vacancy through the O atom, suggesting a preference for C-O over C-C bond cleavage at these sites. This hypothesis is supported by net-negative and net-positive average shifts in the reaction energy and activation energy barriers for C-O and C-C bond-breaking steps, respectively, at Pt-TiO2-interface sites relative to Pt-metal sites. Using the calculated energetics, the predicted minimum-energy pathway was determined for each surface. Pt(111) is predicted to follow decarboxylation, producing undesired methane and carbon dioxide. Conversely, PtNW/OH-TiO2 and PtNW/OHv-TiO2 are both predicted to produce desired acetaldehyde and ethane. The interfacial vacancy may also play a key role in facilitating the first C-O bond-breaking step in acetic acid HDO, lowering the barrier by 0.6 eV relative to the defect-free interface model. These results demonstrate the critical role of the Pt-TiO2 interface in the shift in acetic acid HDO selectivity experimentally observed on Pt/C and Pt/TiO2 catalysts. The results herein demonstrate the important role of the Pt-TiO2 interface and interfacial oxygen vacancies in improving the carbon efficiency for HDO reactions in CFP upgrading.

BIOMASS FUELS,INORGANIC, ORGANIC, PHYSICAL, AND AN↗
DOE OSTI2021

Unconventional chiral charge order in kagome superconductor KV 3 Sb 5

Intertwining quantum order and non-trivial topology is at the frontier of condensed matter physics. A charge-density-wave-like order with orbital currents has been proposed for achieving the quantum anomalous Hall effect in topological materials and for the hidden phase in cuprate high-temperature superconductors. However, the experimental realization of such an order is challenging. Here we use high-resolution scanning tunnelling microscopy to discover an unconventional chiral charge order in a kagome material, KV 3 Sb 5 , with both a topological band structure and a superconducting ground state. Through both topography and spectroscopic imaging, we observe a robust 2 × 2 superlattice. Spectroscopically, an energy gap opens at the Fermi level, across which the 2 × 2 charge modulation exhibits an intensity reversal in real space, signalling charge ordering. At the impurity-pinning-free region, the strength of intrinsic charge modulations further exhibits chiral anisotropy with unusual magnetic field response. Therefore theoretical analysis of our experiments suggests a tantalizing unconventional chiral charge density wave in the frustrated kagome lattice, which can not only lead to a large anomalous Hall effect with orbital magnetism, but also be a precursor of unconventional superconductivity.

36 MATERIALS SCIENCE↗