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At least 127 records · Page 7

Correlating Surface Processing of Nb Superconducting RF Cavities with the Evolution of Surface Electronic States

Superconducting-radio frequency (RF) cavities provide an efficient way to accelerate particle beams with extremely high acceleration gradients while generating very small power dissipation. The few nanometers of the surface play a critical role in defining the RF performance of superconducting Nb based cavities. Over the past two decades, several pioneering surface treatment and processing methods have emerged, enabling remarkable improvements in superconducting cavity performance by simultaneously achieving high quality factors with increasing maximum acceleration gradients. These processing approaches include chemical polishing, distinct multi-step thermal treatments under ultra-high vacuum (UHV) conditions over low to high temperature regimes, as well as high-temperature treatments under controlled nitrogen atmospheres. Beyond their macroscopic impact on RF performance, these methods produce distinct surface oxide configurations characterized by different valence states, oxide thicknesses, chemical uniformity, and oxygen concentration profiles extending into the near-surface bulk of niobium. In this work, we are trying to understand how the surface-processing methods and the resulting oxide/oxygen profiles affect the electronic structure of surface and the mechanism of superconductivity. Using a combination of X-ray photoemission and X-ray absorption spectroscopies, we investigate how the valence-band structure and the electronic density of states (DoS) near the Fermi level evolve under different surface treatments. By employing tunable photon energies across multiple elemental absorption edges, we use resonant photoemission to disentangle and identify the elemental contributions to specific valence-band features. Our observations show that different surface-processing methods lead to distinct temperature evolutions of the DoS and valence-band states near the Fermi level. Our results suggest variations in different Nb-O orbital hybridizations in distinct processes and point towards the possibility of different underlying mechanisms of superconductivity governed by surface chemistry and oxide configuration. We also correlate these distinct superconducting mechanisms with RF cavity performance, specifically focusing on measured surface resistance, the nature of the Q-slope, and quench fields observed in superconducting RF measurements. These results will enable us to identify the potential limiting factors and relevant controllable parameters that can be further optimized to improve the performance of superconducting RF cavities.

Tripathi, Malvika [Fermilab] (ORCID:00000001989251↗

Relativistic Exact Two-Component Theory in the Generalized Pseudospectral Representation

We present a formulation and implementation of exact two-component (X2C) relativistic theory in the generalized pseudospectral representation. When combined with the Hartree-Fock-Slater framework, this approach enables efficient and accurate treatments of scalar-relativistic and spin-orbit effects in atomic electronic structures without the computational overhead of four-component methods. Benchmark calculations across light and heavy elements demonstrate that the our X2C scheme yields substantially more accurate relativistic corrections to core-electron binding energies than perturbational Breit-Pauli treatments while converging more rapidly with respect to basis size. The method provides an improved computational framework for modeling ultrafast x-ray-induced processes in heavy-element systems.

Wang, Xubo↗

Quick-and-Easy Validation of Protein–Ligand Binding Models Using Fragment-Based Semiempirical Quantum Chemistry

Electronic structure calculations in enzymes converge very slowly with respect to the size of the model region that is described using quantum mechanics (QM), requiring hundreds of atoms to obtain converged results and exhibiting substantial sensitivity (at least in smaller models) to which amino acids are included in the QM region. As such, there is considerable interest in developing automated procedures to construct a QM model region based on well-defined criteria. However, testing such procedures is burdensome due to the cost of large-scale electronic structure calculations. Here, we show that semiempirical methods can be used as alternatives to density functional theory (DFT) to assess convergence in sequences of models generated by various automated protocols. The cost of these convergence tests is reduced even further by means of a many-body expansion. We use this approach to examine convergence (with respect to model size) of protein–ligand binding energies. Fragment-based semiempirical calculations afford well-converged interaction energies in a tiny fraction of the cost required for DFT calculations. Two-body interactions between the ligand and single-residue amino acid fragments afford a low-cost way to construct a “QM-informed” enzyme model of reduced size, furnishing an automatable active-site model-building procedure. This provides a streamlined, user-friendly approach for constructing ligand binding-site models that needs neither a priori information nor manual adjustments. Extension to model-building for thermochemical calculations should be straightforward.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural, magnetic, optical, dielectric and electronic properties of R 2 NiIrO 6 (R = Pr and Nd): A comprehensive experimental and theoretical investigation

Double perovskites are highly promising materials capable of exhibiting a wide variety of phenomena. In this work, we perform a comprehensive experimental and theoretical study of polycrystalline R 2 NiIrO 6 (R = Pr and Nd) compounds. Both compounds were synthesised using the solid-state reaction method. Rietveld refinement confirmed a monoclinic structure with the P2 1 /n space group for both compounds. The scanning electron images showed the average grain sizes of 0.55 μm for R = Pr and 0.46 μm for R = Nd. Fourier transform infrared ra- diation spectra of the two compounds presented two intense bands at 470 cm -1 and 540 cm -1 . The optical measurements revealed that the band gaps of the compounds were in the visible absorption range. The field- cooled magnetisation - field hysteresis measurements indicated exchange bias properties in the synthesised compounds at low temperatures. Both temperature and frequency variation of dielectric constant and loss tangent measurements were conducted. The frequency-dependent ac conductivity measurements indicated that the conductivity increases with the increase of frequency as well as temperature. The Nd 2 NiIrO 6 compound showed lower ac conductivities compared to its isostructural Pr 2 NiIrO 6 compound. The atomic and electronic structures of Nd 2 NiIrO 6 and Pr 2 NiIrO 6 were explored using the spin-polarised calculations performed within the DFT+U method. Our results suggested that the inclusion of on-site correlations and repulsions for the d-states of atoms was necessary in order to obtain finite band gaps of Nd 2 NiIrO 6 and Pr 2 NiIrO 6 systems.

36 MATERIALS SCIENCE↗

Correlating Nb-SRF Surface Processing with Evolution of Surface Electronic States

The few nanometers of the surface exposed to RF field plays a major role in defining the RF performance of superconducting cavities. Over the past two decades, several pioneering surface treatment and processing methods have emerged, enabling remarkable improvements in cavity performance by simultaneously achieving high Q with increasing Eacc. These processing methods include: thermal treatment under ultra-high vacuum (UHV) conditions across lo¬¬¬¬¬¬¬w-, mid-, and high-temperature ranges and high temperature treatments under controlled N2 atmosphere. These processes also produce distinct surface oxide configurations with different valence states, thicknesses, and uniformity, as well as different oxygen concentration profiles in bulk Nb. In this work, we are trying to understand how do surface-processing methods and the resulting oxide/oxygen profiles affect the electronic structure of surface and the mechanism of superconductivity? With the help of Fermilab’s in-house X-ray photoemission facility and, in collaboration with the synchrotron-based angle-resolved photoemission (ARPES) facility at Argonne National Laboratory, we are investigating how the valence band structure and density of states (DoS) near the Fermi level modify with different surface treatments. Our observations show that different surface-processing methods lead to distinct evolutions of the valence-band states near the Fermi level during the superconducting transition. This behavior suggests variations in Nb-O orbital hybridizations and points towards the possibility of different underlying mechanisms of superconductivity governed by the surface chemistry and oxide configuration. We also correlate these distinct superconducting mechanisms with RF cavity performance, specifically focusing on measured surface resistance, the nature of the Q-slope, and quench fields observed in SRF measurements. These results will enable us to identify the potential limiting factors and relevant controllable parameters that can be further optimized to improve the performance of SRF cavities.

Tripathi, Malvika [Fermilab]↗

Nanoscale Structure and Interfacial Electrochemical Reactivity of Moiré-Engineered Atomic Layers

Here, the electronic properties of atomically thin van der Waals (vdW) materials can be precisely manipulated by vertically stacking them with a controlled offset (for example, a rotational offset─i.e., twist─between the layers, or a small difference in lattice constant) to generate moiré superlattices. In recent years, the application of this “twistronics” concept to interfacial electrochemistry has unveiled unique pathways for tailoring the electrochemical reactivity. Furthermore, this Account provides an overview of our work that leveraged a suite of structural characterization methods, such as interferometric four-dimensional scanning transmission electron microscopy, dark-field transmission electron microscopy, and scanning tunneling microscopy, along with nanoscale electrochemical measurement techniques, namely, scanning electrochemical cell microscopy (SECCM), to uncover and dissect the profound impact of electrode electronic structure, controlled by interlayer twist, on interfacial electron transfer kinetics.

Charge transfer↗

Tailoring the Electronic Structures and Spectral Properties of ZnO with Irradiation Defects Generated Under Intense Electronic Excitation: A Combined Experimental and DFT Approach

Here, the relationship between the composition of the internal defect states, spectral properties, and correlated electronic structures of wurtzite zinc oxide (ZnO) crystals under 645 MeV Xe 35+ irradiation is systematically investigated, employing experimental characterizations combined with first-principle calculations. Based on the ion irradiation-induced thermal expansion and relaxation processes, the high concentration of vacancy/interstitial defects produced from the transient disordered phase in molten track states trigger photoelectric changes, as follows: i) the generation of internal defect states effectively reduces the intrinsic bandgap (3.25 eV → 2.66 eV); ii) a large number of defective active sites inhibits the recombination between electron–hole pairs, causing dark conductance and photoconductance to increase with increasing damage levels until optimal fluence is achieved. Based on the density functional theory (DFT) with the GGA + U (GGA = generalized gradient approximation) method, the defective models associated with the different electronic structures, density of states, formation energy, and the nature of the chemical bonding are established. The narrowing of the bandgap observed experimentally and the enhancement of carrier concentration originating from the internal electron defect states are qualitatively verified, therefore laying the foundation for designing future nanoscale photoelectronic devices and microelectronics applications.

36 MATERIALS SCIENCE↗

Lattice vacancy migration barriers in Fe-Ni alloys, and an indication as to why Ni atoms diffuse slowly: A first-principles study

Lattice vacancy migration barriers in ferromagnetic Fe 𝑥 ⁢Ni 1−𝑥 alloys (0.4 ≤ 𝑥 ≤ 0.6) are accurately quantified within the framework of ab initio electronic structure calculations using the nudged elastic band (NEB) method. Both the atomically disordered (A1) fcc phase, as well as the atomically ordered, tetragonal L⁢1 0 phase—which is under consideration as a material for a rare-earth-free gap magnet for advanced engineering applications—are investigated. Across an ensemble of NEB calculations performed on supercell configurations spanning a range of compositions and containing disordered, partially ordered, and fully ordered structures, we find that Ni-vacancy interchanges encounter significantly higher energetic barriers than do Fe-vacancy interchanges. We contend that this aspect is a key factor in determining the differences in mobility between Fe and Ni atoms in this ferromagnetic alloy. Moreover, we are able to interpret these findings in terms of the ferromagnetic alloy's underlying spin-polarized electronic structure. Specifically, we report a coupling between the size of local lattice distortions and the magnitude of the local electronic spin polarization around vacancies. This causes Fe atoms to relax into lattice vacancies, while Ni atoms remain rigidly fixed to their original lattice positions. These results give atomic-scale insight into the longstanding experimental observation that Ni exhibits remarkably slow atomic diffusion in Fe-Ni alloys.

density functional theory↗

Accelerating Instanton Theory with the Line Integral Nudged Elastic Band Method and Gaussian Process Regression

Quantum tunneling plays a fundamental role in many chemical reactions, particularly proton transfer processes. Ring polymer instanton theory offers a practical framework for computing tunneling rates in complex molecular systems. However, applying the ring polymer instanton method with a potential energy surface generated on-the-fly using electronic structure calculations can be computationally demanding. Here, in this work, we present a new efficient implementation of the ring polymer instanton method by combining the Line Integral Nudged Elastic Band (LI-NEB) approach with Gaussian Process Regression (GPR). We benchmarked this method on prototypical ground-state proton transfer systems, including the benchmark gas-phase hydrogen abstraction reaction H + CH 4 → H 2 + CH 3 , malonaldehyde, and Z-3-amino-propenal (aminopropenal). Our results show that this approach is an order of magnitude faster than traditional instanton algorithms while maintaining excellent agreement with their tunneling rates. This development opens the door to studying proton transfer in larger systems with improved efficiency.

chemical physics↗

Surface Terminations of LaAlO 3 Perovskite Nanoparticles as Viewed by Solid-State Nuclear Magnetic Resonance

Nanocrystal surfaces generally undergo reconstructions that differentiate them from the bulk structures, often in nontrivial ways. Understanding these terminations is critical across diverse fields, from heterogeneous catalysis to the formation of topological states and the synthesis of semiconductor nanomaterials. Determining surface structures is currently an interdisciplinary task, most often involving high-resolution electron microscopy and surface electron diffraction. These methods, however, do not provide a global view of the ensemble of structures present in a sample. Here, we show how surface-sensitive solid-state nuclear magnetic resonance (SSNMR) spectroscopy methods can bridge this gap. In this context, we investigated the surface structure of lanthanum aluminate (LaAlO 3 ) perovskite nanoparticles. Four distinct surface terminations have previously been observed for this material, but their relative abundances were unknown. Using an array of double- and triple-resonance SSNMR methods probing the relative proximities of surface 1 H, 27 Al, 17 O, and 139 La nuclei, we conclude the surface to be majority terminated (80%) by AlO x with substantial (20%) LaO x terminated regions.

Materials↗

Insights into the Properties of MXenes and MXene Analogs from Atomistic Simulation

We review the properties that have been predicted for MXenes and MXene analogs from computational simulation with a focus on structural and electronic properties, energy storage, and ion transport. Methods considered range from quantum mechanical approaches to classical molecular dynamics. We conclude by reviewing current limitations and outstanding questions for simulation and MXene properties that have been little explored to-date.

Muraleedharan, Murali Gopal↗

Developing a new ethylene glycol/H 2 O pretreatment system to achieve efficient enzymatic hydrolysis of sugarcane bagasse cellulose and recover highly active lignin: Countercurrent extraction

Improving pretreatment efficiency is a critical premise in achieving efficient biomass conversion, and obtaining high-performance natural polymers is the guarantee of high-value conversion of biomass. Here, in this study, a new pilot-scale continuous countercurrent pretreatment reaction unit about ethylene glycol-alkali solution was designed for pretreating sugarcane bagasse in order to achieve efficient separation of the three major components of lignocellulose when expanding the scale of pretreatment, reduce lignin deposition on the fiber surface, and obtain highly active lignin and excellent enzymatic hydrolysis efficiency of cellulose. X-ray diffractometer (XRD), X-ray photoelectron spectrometer (XPS), brunauer-emmett-teller (BET) and scanning electron microscope (SEM) methods are used to analyze the structural properties of sugarcane bagasse before and after pretreatment, and high-performance liquid chromatography (HPLC) is used to analyze the monosaccharide components in the enzymatic solution. In addition, the structural properties of the recovered lignin are analyzed by gel permeation chromatography (GPC), 31 P NMR and 2D-HSQC-NMR methods. The results indicate that the system can gain a high cellulose recovery of 92.99% along with a lignin removal of 95.33%, and recovered lignin has low lignin carbohydrate complexes, low condensation, and rich in phenolic hydroxyl groups for 1.95 mmol/g. Meanwhile, the countercurrent pretreatment system can effectively reduce the deposition of lignin on the cellulose surface, which is evidently superior to the non-countercurrent pretreatment and facilitates the efficiency of enzymatic saccharification of substrate, achieving a high glucose yield of 99% as well as a total sugar yield of 91.11%. The method efficiently separates biomass in a green manner, and solid residues are easily hydrolyzed, showing potential for industrial-scale production.

09 BIOMASS FUELS↗

Dynamic mode decomposition of nonequilibrium electron-phonon dynamics: accelerating the first-principles real-time Boltzmann equation

Abstract Nonequilibrium dynamics governed by electron–phonon ( e -ph) interactions plays a key role in electronic devices and spectroscopies and is central to understanding electronic excitations in materials. The real-time Boltzmann transport equation (rt-BTE) with collision processes computed from first principles can describe the coupled dynamics of electrons and atomic vibrations (phonons). Yet, a bottleneck of these simulations is the calculation of e –ph scattering integrals on dense momentum grids at each time step. Here we show a data-driven approach based on dynamic mode decomposition (DMD) that can accelerate the time propagation of the rt-BTE and identify dominant electronic processes. We apply this approach to two case studies, high-field charge transport and ultrafast excited electron relaxation. In both cases, simulating only a short time window of ~10% of the dynamics suffices to predict the dynamics from initial excitation to steady state using DMD extrapolation. Analysis of the momentum-space modes extracted from DMD sheds light on the microscopic mechanisms governing electron relaxation to a steady state or equilibrium. The combination of accuracy and efficiency makes our DMD-based method a valuable tool for investigating ultrafast dynamics in a wide range of materials.

36 MATERIALS SCIENCE↗

Integrated ab initio modelling of atomic ordering and magnetic anisotropy for design of FeNi-based magnets

We describe an integrated modelling approach to accelerate the search for novel, single-phase, multicomponent materials with high magnetocrystalline anisotropy (MCA). For a given system we predict the nature of atomic ordering, its dependence on the magnetic state, and then proceed to describe the consequent MCA, magnetisation, and magnetic critical temperature (Curie temperature). Crucially, within our modelling framework, the same ab initio description of a material’s electronic structure determines all aspects. We demonstrate this holistic method by studying the effects of alloying additions in FeNi, examining systems with the general stoichiometries Fe 4 Ni 3 X and Fe 3 Ni 4 X, for additives including X = Pt, Pd, Al, and Co. The atomic ordering behaviour predicted on adding these elements, fundamental for determining a material’s MCA, is rich and varied. Equiatomic FeNi has been reported to require ferromagnetic order to establish the tetragonal L1 0 order suited for significant MCA. Our results show that when alloying additions are included in this material, annealing in an applied magnetic field and/or below a material’s Curie temperature may also promote tetragonal order, along with an appreciable effect on the predicted hard magnetic properties.

36 MATERIALS SCIENCE↗

Benchmarking universal machine learning interatomic potentials for rapid analysis of inelastic neutron scattering data

The accurate calculation of phonons and vibrational spectra remains a significant challenge, requiring highly precise evaluations of interatomic forces. Traditional methods based on the quantum description of the electronic structure, while widely used, are computationally expensive and demand substantial expertise. Emerging universal machine learning interatomic potentials (uMLIPs) offer a transformative alternative by employing pre-trained neural network surrogates to predict interatomic forces directly from atomic coordinates. This approach dramatically reduces computation time and minimizes the need for technical knowledge. In this paper, we produce a phonon database comprising nearly 5000 inorganic crystals to benchmark the performance of several leading uMLIPs. We further assess these models in real-world applications by using them to analyze experimental inelastic neutron scattering data collected on a variety of materials. Through detailed comparisons, we identify the strengths and limitations of these uMLIPs, providing insights into their accuracy and suitability for fast calculations of phonons and related properties, as well as the potential for real-time interpretation of neutron scattering spectra. Our findings highlight how the rapid advancement of AI in science is revolutionizing experimental research and data analysis.

inelastic neutron scattering↗

Influence of Markovianity and self-consistency on time-resolved spectral functions of driven quantum systems

We present a systematic comparison of the real-time Dyson expansion (RTDE) with established nonequilibrium Green's function (GF) approaches for simulating driven, interacting quantum systems. Focusing on density matrix dynamics, time-off-diagonal GFs, and time-resolved photoemission spectra, we benchmark RTDE against fully self-consistent Kadanoff-Baym equation (KBE) calculations, the generalized Kadanoff-Baym ansatz, and exact diagonalization for small systems using second-order many-body perturbation theory. Using a driven two-band Hubbard model, we show that mean-field single-particle density matrix trajectories provide a reliable baseline for RTDE across a broad range of interaction strengths and excited-carrier populations. Further, RTDE accurately captures correlation effects in the GFs, including long-lived oscillations and revivals that are strongly suppressed by the overdamping inherent to self-consistent KBE schemes. As a consequence, RTDE resolves rich nonequilibrium spectral structure in time-resolved photoemission, such as interaction- and population-dependent quasiparticle splittings and band gap renormalization, which are largely washed out in self-consistent approaches yet are present in exact solutions. Furthermore, our results demonstrate that RTDE bridges the gap between mean-field propagation and full two-time KBE simulations, retaining favorable linear scaling while capturing essential dynamical correlations relevant for ultrafast spectroscopy.

Electronic structure↗

Isostructural electronic transition in MoS 2 probed by solid-state high-harmonic generation spectroscopy

Studying materials under extreme pressure in diamond anvil cells (DACs) is key to discovering emergent states of matter, yet no method currently allows the direct measurement of the electronic structure in this environment. Solid-state high-harmonic generation (sHHG) offers a unique all-optical window into the electronic structure of materials. We demonstrate sHHG spectroscopy inside a DAC by probing 2H-MoS 2 , up to 30 GPa, revealing a pressure-induced crossover of the lowest direct bandgap from the K-point to the Γ-point. This transition manifests as a sharp minimum in harmonic intensity and a 30° rotation of the sHHG polarization anisotropy, despite the absence of a structural phase change. First-principles simulations attribute these features to interference between competing excitation pathways at distinct points in the Brillouin zone. Our results establish sHHG as a sensitive probe of electronic transitions at high pressure, enabling access to quantum phenomena that evade detection by conventional techniques.

Nebgen, Bailey R. [University of California, Berke↗

Data for "Integrated ab initio modelling of atomic order and magnetic anisotropy for rare-earth-free magnet design: effects of alloying additions in L1 0 FeNi."

We describe an integrated modelling approach to accelerate the search for novel, single-phase, multicomponent materials with high magnetocrystalline anisotropy (MCA). For a given system we predict the nature of atomic ordering, its dependence on the magnetic state, and then proceed to describe the consequent MCA, magnetisation, and magnetic critical temperature (Curie temperature). Crucially, within our modelling framework, the same ab initio description of a material’s electronic structure determines all aspects. We demonstrate this holistic method by studying the effects of alloying additions in FeNi, examining systems with the general stoichiometries Fe 4 Ni 3 X and Fe 3 Ni 4 X, for additives including X = Pt, Pd, Al, and Co. The atomic ordering behaviour predicted on adding these elements, fundamental for determining a material’s MCA, is rich and varied. Equiatomic FeNi has been reported to require ferromagnetic order to establish the tetragonal L1 0 order suited for significant MCA. Our results show that when alloying additions are included in this material, annealing in an applied magnetic field and/or below a material’s Curie temperature may also promote tetragonal order, along with an appreciable effect on the predicted hard magnetic properties.

36 MATERIALS SCIENCE↗