Nanometer-scale surface chemistry limits the performance of superconducting radio-frequency cavities and quantum circuits. We present an ab initio framework connecting density-functional theory interfacial energetics with strong-coupling Eliashberg theory for capped Nb and Ta surfaces. This approach identifies Au and Au-based alloys (AuPd, AuPt) as effective passivation layers. Our model further predicts that combining a noble-metal capping layer with an appropriate wetting/adhesion layer yields far more robust adhesion than a capping layer alone under realistic conditions, enabling thinner caps and thus addressing a central challenge in superconducting surface passivation.

Experiments on superconducting cavities have found that under large RF fields the quality factor can improve with increasing field amplitude, a so-called “anti-Q slope.” We numerically solve the Bogoliubov-de Gennes equations at a superconducting surface in a parallel magnetic field, finding at large fields there are surface quasiparticle states with energies below the bulk superconducting gap that emerge and disappear as the field cycles. Modifying the standard two-fluid model, we introduce a “three”-fluid model where we partition the normal fluid to consider continuum and surface quasiparticle states separately. We compute dissipation in a semi-classical theory of conductivity, where we provide physical estimates of elastic scattering times of Bogoliubov quasiparticles with point-like impurities having potential strengths informed from complementary ab initio calculations of impurities in bulk niobium. We show, in this simple yet effective framework, how the relative scattering rates of surface and continuum quasiparticle states can play a role in producing an anti-Q slope while demonstrating how this model naturally includes a mechanism for turning the anti-Q slope on and off.

We propose hydrogenated carbon structures as targets with a remarkable sensitivity to dark matter-nucleon interactions, in the mass range between the 1 MeV and 100 MeV. The ejection of a proton following the interaction with a dark matter particle is a quasi-elastic process, with an extremely small energy threshold, and a clear experimental signature. The proposed detectors are simple, technologically ready, and inexpensive. Yet, they can be considerably more sensitive than current experiments. They also allow strong directionality, to be used towards efficient background rejection.

Photoemission is an escape problem, yet first-principles calculations usually trap the electron in a periodic box. We present a parameter-free ab initio framework that removes this artificial boundary by constructing open scattering states for semi-infinite crystal-vacuum interfaces from Wannier Hamiltonians and Green-function embedding. The method gives continuum-normalized time-reversed LEED final states with microscopic quasiparticle attenuation. For Ag(111), it predicts absolute quantum efficiency, vectorial photoemission, and mean transverse energy on the experimental scale.

We establish a first-principles theory of vacuum Wannier functions unifying tight-binding and nearly-free-electron descriptions across solid-vacuum interfaces. Analytic solutions for canonical Wannier functions in arbitrary dimension and disentangled functions in 1D motivate a numerically verified 3D Wannier close-packing principle, enabling dense k-space construction of full Born-series scattering states at interfaces and thus predictive photoemission calculations without semiempirical vacuum potentials. Applications to graphene and h-BN reveal corrections beyond the first-Born approximation.

Surface oxides are associated with two-level systems (TLSs) that degrade the performance of niobium-based superconducting quantum computing devices. To address this, we introduce a predictive framework for selecting metal capping layers that inhibit niobium oxide formation. Using DFT-calculated oxygen interstitial and vacancy energies as thermodynamic descriptors, we train a logistic regression model on a limited set of experimental outcomes to successfully predict the likelihood of oxide formation beneath different capping materials. This approach identifies Zr, Hf, and Ta as effective diffusion barriers. Our analysis further reveals that the oxide formation energy per oxygen atom serves as an excellent standalone descriptor for predicting barrier performance. By combining this new descriptor with lattice mismatch as a secondary criterion to promote structurally coherent interfaces, we identify Zr, Ta, and Sc as especially promising candidates. This closed-loop strategy integrates first-principles theory, machine learning, and limited experimental data to enable rational design of next-generation materials.

The thermodynamic stability of inorganic solids spans a vast compositional space, yet materials scientists have long organized their intuition around a manageable number of materials families. Here we show that this organization has a precise geometric basis. The formation-energy convex hull of all inorganic compounds from the Materials Project, spanning 92-dimensional elemental composition space, is captured to near DFT accuracy by a polyhedron with only seven facets. Each facet corresponds to a family of materials sharing similar chemical potentials. This low-dimensional structure is not merely an economical description of energies: without retraining or structural input, the same framework reproduces trends in DFT-calculated defect energies and elemental spatial correlations in high-entropy nanoparticles. These results reveal that a small number of material families, corresponding to geometric features of composition-energy space, govern bulk stability, defect energetics, and elemental mixing, and provide a unified, interpretable framework for rapid screening across diverse materials systems.

Research linking surface hydrides to Q-disease, and the subsequent development of methods to eliminate surface hydrides, is one of the great successes of SRF cavity R D. We use time-dependent Ginzburg-Landau to extend the theory of hydride dissipation to sub-surface hydrides. Just as surface hydrides cause Q-disease behavior, we show that sub-surface hydrides cause high-field Q-slope (HFQS) behavior. We find that the abrupt onset of HFQS is due to a transition from a vortex-free state to a vortex-penetration state. We show that controlling hydride size and depth through impurity doping can eliminate HFQS.

The increasing availability of high-precision player-tracking data in sports-centimeter-precision positional information of athletes captured dozens of times per second-has the potential to improve the quantification of player abilities and overall team strategies. Working toward achieving this quantification, we adapt density-functional fluctuation theory (DFFT) to infer spatial preferences and player-to-player interactions in National Basketball Association (NBA) basketball. We first demonstrate several foundational results, including the ability of DFFT to predict the location of a player to within 3% of the half-court area roughly half the time, and to provide a team-position-based metric that correlates strongly with play outcomes. Building on these results, we demonstrate that it is possible to improve player positioning and identify player-specific tendencies, such as the consistency with which a player positions himself to help his team collectively defend against 2-point or 3-point shots. Finally, we quantify how particular players attract the opposing team, with and without the ball, constituting the first advanced quantification of 'player gravity' that explicitly deconfounds the influence of teammate positioning.

Common belief is that the large band shifts observed in incommensurate misfit compounds, e.g., (LaSe)1.14(NbSe2)2, are due to interlayer charge transfer. By contrast, our analysis, based on both angle-resolved photoemission spectroscopy (ARPES) measurements and a specialized ab initio framework employing only quantities well defined in incommensurate materials, demonstrates that the large band shifts instead reflect changes in valence band hybridization and interlayer bonding. The strong alignment of our ab initio predictions and ARPES measurements confirms our understanding of the incommensurate electronic structure and charge transfer.

Furthering the understanding of the catalytic mechanisms in the oxygen reduction reaction (ORR) is critical to advancing and enabling fuel cell technology. In this work, we use multimodal operando synchrotron X-ray diffraction (XRD) and resonant elastic X-ray scattering (REXS) to investigate the interplay between the structure and oxidation state of a Co-Mn spinel oxide electrocatalyst, which has previously shown ORR activity that rivals Pt in alkaline fuel cells. During cyclic voltammetry, the electrocatalyst exhibited a reversible and rapid increase in tensile strain at low potentials, suggesting robust structural reversibility and stability of Co-Mn oxide electrocatalysts during normal fuel cell operating conditions. At low potential holds, exploring the limit of structural stability, an irreversible tetragonal-to-cubic phase transition was observed, which may be correlated to reduction in both Co and Mn valence states. Meanwhile, joint density-functional theory (JDFT) calculations provide insight into how reactive adsorbates induce strain in spinel oxide nanoparticles. Through this work, strain and oxidation state changes that are possible sources of degradation during the ORR in Co-Mn oxide electrocatalysts are uncovered, and the unique capabilities of combining structural and chemical characterization of electrocatalysts in multimodal operando X-ray studies are demonstrated.

We propose a fully ab initio approach to predicting thermal attenuation in elastic helium atom scattering amplitudes, validated through strong agreement with experiments on Nb(100) and (3×1)-O/Nb(100) surfaces. Our results reveal the relative contributions from bulk, resonant, and surface phonon modes, as well as from different surface mode polarizations, providing insights into differences between smooth and corrugated surfaces. These findings advance understanding of surface dynamics and electron-phonon coupling, laying groundwork for future studies on surface superconductivity.

The Josephson junction is a crucial element in superconducting devices, and niobium is a promising candidate for the superconducting material due to its large energy gap relative to aluminum. AlO_x has long been regarded as the highest quality oxide tunnel barrier and is often used in niobium-based junctions. Here we propose ZrO_x as an alternative tunnel barrier material for Nb electrodes. We theoretically estimate that zirconium oxide has excellent oxygen retention properties and experimentally verify that there is no significant oxygen diffusion leading to NbO_x formation in the adjacent Nb electrode. We develop a top-down, subtractive fabrication process for Nb/Zr-ZrO_x/Nb Josephson junctions, which enables scalability and large-scale production of superconducting electronics. Using cross sectional scanning transmission electron microscopy, we experimentally find that depending on the Zr thickness, ZrO_x tunnel barriers can be fully crystalline with chemically abrupt interfaces with niobium. Further analysis using electron energy loss spectroscopy reveals that ZrO_x corresponds to tetragonal ZrO_2. Room temperature characterization of fabricated junctions using Simmons' model shows that ZrO_2 exhibits a low tunnel barrier height, which is promising in merged-element transmon applications. Low temperature transport measurements reveal sub-gap structure, while the low-voltage sub-gap resistance remains in the megaohm range.

Cs-Sb compound thin-film photocathodes are an excellent candidate to produce bright electron beams for use in various accelerator applications. Despite the virtues of these photocathodes being known, the mechanics that govern their photoemission are not well-understood. Crystalline and other material properties affect the mean transverse energy (MTE) and quantum efficiency (QE) and, thus, the overall brightness. Electrons photoemitted from these thin-film crystals experience an unexpected energy loss similar to that found in bulk crystals despite their being a significantly shorter transport phase. Deeply understanding the relationship between the crystalline properties and the emitted electron beam’s brightness, as well as this drop in energy, is vital to generating ultra-bright electron beams for advanced accelerator applications. The purpose of this work is to use the Monte Carlo method to simulate photoemission from semiconducting films with electronic band structure parameters supplied by Density Functional Theory (DFT) calculations. This method is used to study all steps of photoemission and to identify the key parameters necessary for optimizing photocathode performance.

We introduce Effective Atom Theory (EAT), a framework that transforms combinatorial materials design into a smooth, gradient-driven optimization within density functional theory (DFT). Atoms are represented as probabilistic mixtures of elements, enabling gradient-based optimizers to converge to a physically realizable material in about 50 energy evaluations – far fewer than combinatorial optimization methods. Applied to Co-Cr-Ni-V oxides for the alkaline oxygen evolution reaction (OER), EAT leads to a final recommended composition of Co0.19Cr0.06V0.31Ni0.44O.

The rare-earth tritellurides have a rich phase diagram that includes charge density waves (CDWs), superconductivity, and magnetic order, offering a platform to study the interplay between these phases on a square-net system. Prior studies have shown that defects can affect the CDW characteristics in these materials, yet coupling between the CDW order and the underlying microstructure has not been studied at the nanoscale. Here we use scanning transmission electron microscopy at cryogenic temperatures to directly visualize the effects of defects on the CDW order and provide a spatially resolved microscopic correlation between the CDW transition and structural defects. We show that in the presence of extended defects, such as dislocations and stacking faults, the weak orthorhombicity of the rare-earth tritellurides is lost and the material becomes pseudotetragonal. Since the orthorhombicity acts as a symmetry breaking field for the CDW transitions in rare-earth tritellurides, the presence of these extended defects modulates the energetics of the CDWs and suppresses the ground-state CDW phase at low temperature.

Precious-metal-free spinel oxide electrocatalysts are promising candidates for catalyzing the oxygen reduction reaction (ORR) in alkaline fuel cells. In this theory-driven study, we use joint density-functional theory in tandem with supporting electrochemical measurements to identify a novel theoretical pathway for the ORR on cubic Co3O4 nanoparticle electrocatalysts. This pathway aligns more closely with experimental results than previous models. The new pathway employs the cracked adsorbates *(OH)(O) and *(OH)(OH), which, through hydrogen bonding, induce spectator surface *H. This results in an onset potential closely matching experimental values, in stark contrast to the traditional ORR pathway, which keeps adsorbates intact and overestimates the onset potential by 0.7 V. Finally, we introduce electrochemical strain spectroscopy (ESS), a groundbreaking strain analysis technique. ESS combines ab initio calculations with experimental measurements to validate proposed reaction pathways and pinpoint rate-limiting steps.

The synthesis of spinel oxide nanocrystals is gaining momentum due to their broad applicability in energy storage and conversion technologies, including supercapacitors, lithium-ion batteries, and electrocatalysis for the oxygen reduction reaction (ORR) and the oxygen evolution reaction (OER). The performance of these spinel nanomaterials depends on their intrinsic physical properties, such as electronic conductivity and the interaction with reaction intermediates, which are, in turn, influenced by particle size and morphology. These dependencies arise from effects such as quantum confinement and surface or lattice strain, highlighting the importance of producing nanocrystals with controlled size and low dispersity for precise property-application correlations. Achieving such control is crucial for tailoring material properties to specific applications. Colloidal synthesis emerges as a promising method, offering the precision to generate small, monodisperse nanocrystals in a scalable manner. The complexity of colloidal synthesis, dictated by factors such as precursor species, ligands, temperature and solvents, makes synthetic optimization of nanocrystals with precise crystallographic phase and composition both time-consuming and labor-intensive. This leads us to integrate machine learning to efficiently explore and optimize this vast parameter space. By leveraging historical data and employing iterative learning, we aim to automate reaction route optimization in colloidal synthesis. This approach not only enhances synthesis efficiency and material performance for energy applications but also enables the tailored development of nanomaterials through data-driven predictions and streamlined processes.

Helium (He) atom scattering (HAS) simultaneously measured the surface electron-phonon coupling (EPC, SEPC) constant (lambda, lambda(S)) and in situ high-temperature atomic-scale surface structure of the unreconstructed, metallic Nb(100) surface. The Nb(100) surface lambda(S) is 0.50 +/- 0.08, and its atomic-scale surface structure is confirmed. The lambda(S) measured for the Nb(100) surface is similar to 1/2 the reported bulk Nb lambda values. The significance of Nb(100)'s diminished EPC was elucidated by estimating relevant superconducting properties from the measured lambda(S), surface Debye temperature, known material parameters, and well-established equations. Density functional theory (DFT) with local averaging agrees well with the HAS data. A critical temperature (T-C) of 1.4-3.6 K, a superheating field (H-sh at 2 K) <= 0.16 T, and a superconducting gap (at 2 K) <= 1.0 meV were estimated from these measurements. These results indicate that the Nb(100) surface has decreased superconducting properties relative to the bulk. This study shows that these effects may also be due to the interface itself even without oxygen. These results contain the first lambda measured for the metallic Nb(100) and any Nb surface. These measurements begin a fundamental understanding of the atomic-scale surface structure's effect on EPC and superconductivity in Nb.