Outer mitochondrial membrane fusion is mediated by the mitofusin paralogs Mfn1 and Mfn2. Nucleotide-driven self-assembly and conformational changes are required for regulated membrane fusion activity, but the allosteric mechanisms remain enigmatic due to incomplete structural information. In this study, we investigate the GTP-coupled conformational dynamics of Mfn1 using time-resolved transition metal ion fluorescence resonance energy transfer (tmFRET). Using the minimal Mfn1 construct with the GTPase domain and helical bundle 1 (HB1) connected by Hinge 2, we engineered FRET pairs by incorporating a fluorescent noncanonical amino acid donor and a metal ion acceptor. For each state of the catalytic cycle, we measured tmFRET with fluorescence lifetimes and determined distance distributions, which can capture complex structural heterogeneity. Our distance measurements for the GDP-bound state matched predictions from the atomic resolution structure, establishing that the same open state, with GTPase and HB1 domains far apart, exists in solution. Our data reveal that the transition state is not a single closed state with HB1 stably contacting the GTPase domain. Rather, the distance distributions indicate that the presence of GDP + Pi results in an equilibrium between the open and closed states. We also captured the GTP-bound and nucleotide-free states of Mfn1. GTP binding favors the open state, and the conformation of the apo state is distinct from any nucleotide-bound state. Together, these findings redefine our understanding of GTP-driven conformational dynamics in Mfn1, demonstrating an unexpected conformational reversal in a single catalytic cycle and a heterogeneous transition state ensemble with implications for the mechanism and regulation of mitochondrial membrane fusion.

Atomic structures of a Lu-segregated grain boundary (GB) in α-Al2O3 are identified using hybrid Monte Carlo and molecular dynamics (MCMD) simulations based on a neural-network potential (NNP) trained on density-functional-theory (DFT) data, in combination with scanning transmission electron microscopy (STEM). The NNP accurately reproduces the relationship between the potential energy and atomic structures. This enables us to screen candidate atomic structures by performing many structural relaxations and long time-scale MD simulations, prior to final DFT validation, significantly reducing computational cost. The NNP predicts that multiple Lu configurations are energetically favorable, with variations in the occupied site and segregation level. The Lu atomic configurations observed in the experimental STEM images are fully explained by the present calculations, allowing for quantitative analyses of the atomic and electronic structures. The present NNP approach opens the way for a deeper understanding of impurity-segregated GBs at the atomic level.

First-principles prediction of two-dimensional GaO/ZnO heterostructure: Atomic structure and electronic properties

GATv2-TransDTI: A graph and sequence hybrid model for fine-grained drug-target interaction prediction.

The m = 2 member of the monophosphate tungsten bronze family had been thought to be the only one without an electronic instability at low temperature. In this paper, we report the discovery of a charge density wave phase in this compound, with a transition temperature of 290 K and an incommensurate modulation vector q = 0.245b* + ξc*, which reaches a lock-in with a commensurate vector at 130 K. The presence of this new phase is confirmed by diffraction and resistivity measurements. Pre-transitional dynamics are investigated using diffuse and inelastic X-ray scattering, revealing a clear Kohn anomaly. We analyze both structural and electronic contributions to the phase transition, providing a comprehensive picture of the mechanism driving this newly identified instability.

Engineering chaperone/usher pathway pili for surface display: Structural constraints, design principles, and biotechnological potential.

The organic cation choline is essential for eukaryotic metabolism. Recently, the feline leukemia virus subgroup C receptor-related (FLVCR, SLC49) family was demonstrated as central for basal choline transport, questioning the role of the choline transporter-like (CTL, SLC44) family in this capacity. Here, we use Xenopus laevis oocytes to confirm that FLVCR1 (SLC49A1) and FLVCR2 (SLC49A2) proteins are choline transporters. CTL1 (SLC44A1) does not transport choline under the same conditions, supported by other CTL proteins, Arabidopsis thaliana CherI and Saccharomyces cerevisiae PNS1, which also display no choline transport activity. We present the atomic structures of FLVCR2, CTL1, and PNS1. The 3.4 Å cryo-EM structure of FLVCR2 has choline in the binding pocket. The 3.3 Å cryo-EM structure of CTL1 and the 2.7 Å crystal structure of PNS1 reveal an unusual protein fold, weakly related to the mitochondrial carrier family (SLC25). The unusual fold appears incompatible with transmembrane transport and implies a different and, so far, unknown function for CTL proteins. Our results support FLVCR proteins as choline transporters and suggest a nontransport role for CTL proteins.

In this study, we investigated the room-temperature wafer bonding of indium phosphide (InP) and thermally oxidized Si (SiO 2 ). The bond strength of InP/SiO 2 wafers via surface-activated direct bonding and room-temperature quasi-direct bonding using an activated Si atomic layer were compared, and the bonding using an activated Si atomic layer resulted in a tenfold increase in bond strength. The surface morphology and atomic structure of the bonding interface were characterized to confirm that the bond strength was enhanced because the InP surface with an activated atomic Si layer maintained low roughness, and a strong direct bond between the activated Si atoms was obtained simultaneously. Subsequently, the state of In and P diffusion at the bonding interface was verified. The observation of the debonded surfaces showed that although In and P diffuses into the activated Si atom layer, the amount is negligible, and the bonding interface consists almost entirely of strong Si-Si bonds. Using this room temperature quasi-direct bonding method, the heterogenous InP-on-insulator wafer bonded at room temperature is suitable for fabricating optical and electronics devices and could be integrated with other exciting material platforms. • The fabrication of heterogeneous InP-on-insulator (InPOI) wafers was demonstrated using a surface-activated, room-temperature quasi-direct wafer bonding method. • The tensile strength of the bonded InPOI wafers at room temperature exceeded 29 MPa, indicating that the InP/SiO 2 bonding interface achieves sufficient bond strength. • Void-free atomic contact formation at the InP/SiO 2 bonding interface was confirmed. • Detailed investigations of the bonding interface and debonded surfaces clarified the formation of a strong InP/SiO 2 bonding interface.

Amorphous/crystalline interfaces that combine structural distortion with local charge redistribution remain poorly understood, mainly owing to limited access to atomically well-defined single-crystalline components and correlative probes of interfacial fields. Herein, we construct atomically resolvable single-crystalline/amorphous heterointerfaces by synthesizing a library of transition metal oxytellurides and map the projected electric field and strain by combining scanning transmission electron microscopy (STEM) with four-dimensional STEM (4D-STEM). In RuTe1.93O0.97, 4D-STEM reveals a locally enhanced electrostatic field whose direction reorients at the interface. Charge density maps show electron accumulation in the amorphous region and depletion in the single-crystalline region, suggesting directional electron transfer. Nanometer-scale tensile and compressive strain localized around the heterointerface is identified. Electronic structure calculations indicate enhanced Ru 4d delocalization near the Fermi level, facilitating electron-driven reactions. This work spatially correlates atomic structure with built-in electric fields and lattice strain at disordered-ordered interfaces, providing a general route to elucidating structure-activity relationships.

The origin of superconductivity in oxide interfaces and its relation to ferroelectricity remains an open question. At LaAlO3/SrTiO3 interfaces, quantum confinement and inversion symmetry breaking create a two-dimensional electron gas near a ferroelectric quantum critical point, yet direct evidence linking phonon dynamics to electron pairing has been lacking. Here we directly probe lattice vibrations and atomic structure at LaAlO3/SrTiO3 interfaces across the superconducting phase diagram using vibrational spectroscopy with momentum selectivity in a scanning transmission electron microscope. We find that superconductivity across the doping series correlates with inversion symmetry breaking and the appearance of high-frequency localized phonons. These tunable, polar vibrations-confined near the interface-exhibit strong electron-phonon coupling and evolve systematically with carrier density. Our findings establish a link between lattice instability, superconductivity and strong electron-phonon coupling mediated by tunable localized phonons, providing new insights into possible microscopic pairing pathways in quantum paraelectric systems.

A gated integrating laser-combined scanning tunneling microscope has been developed for high-fidelity investigation of photophysical processes at the atomic scale. This instrument integrates a low-repetition-rate, high-pulse-energy laser with a synchronized gated-integration scheme, enabling selective extraction of the laser-induced tunneling current. To demonstrate its performance, atomically resolved topography and surface photovoltage mapping were simultaneously obtained on the Si(111)-(7 × 7) surface. The surface photovoltage distribution is found to be strongly correlated with the underlying atomic structure. In addition, a highly localized enhancement of the laser-induced tunneling current is observed at a specific single-atom defect site. Detailed analysis, supported by local density of states measurements, reveals that this defect possesses an unusually high density of deep valence-band states. This distinctive electronic structure likely promotes Auger recombination between photogenerated holes accumulated under positive sample bias and electrons tunneling from the tip, thereby giving rise to the observed increase in the local tunneling current.

This study employs molecular dynamics (MD) simulations to investigate the effects of temperature (600, 650, and 700 K) and annealing time (0-32 ps) on the atomic structure of copper nanorods. The embedded atom method (EAM) potential is used to model interatomic interactions under NPT conditions. Structural evolution is characterized using radial distribution function (RDF), coordination number, common neighbor analysis (CNA), and total energy. Results reveal that increasing temperature induces structural disorder, with a gradual transformation from a highly ordered Face-Centered Cubic (FCC) lattice to a partially amorphous state. Conversely, prolonged annealing promotes atomic rearrangement and recrystallization, stabilizing the structure. At 650 K and ~28 ps, the system achieves optimal stability with the lowest energy and highest FCC fraction. These findings provide atomistic insights into thermal treatment optimization of copper-based materials and contribute to the understanding of thermally induced structural evolution in metallic systems.

Understanding the atomic structure, speciation, and reactivity of surface sites is critical for establishing structure-activity relationships in heterogeneous catalysis. A longstanding objective in this field is the simultaneous identification of Brønsted acid sites (BASs) and the quantification of their acidity. Although BASs often govern the overall reactivity of catalysts and specific support effects such as bifunctionality, achieving this objective has remained a grand challenge. In this work, we selectively tag reactive surface functionalities on materials, such as -OH groups spanning a wide range of acidity, using an organosilver(I) compound that incorporates 109Ag and 31P reporter nuclei at natural abundance. This 31P-109Ag surface tag, which can be visualized by transmission electron microscopy (TEM) when applicable, provides dual NMR probes, enabling a high-resolution characterization of BASs by solid-state nuclear magnetic resonance (SSNMR) spectroscopy. Leveraging Dynamic Nuclear Polarization Surface Enhanced NMR spectroscopy (DNP-SENS), 2D 31P-{109Ag} J-correlated NMR spectroscopy enables the detection and resolution of different surface functionalities (e.g., reactive -OH and -NH groups) and their speciation (e.g., terminal O vs bridging O sites) across various levels of surface complexity. Rationalizing the complementary NMR signatures of 31P-109Ag tags using Density Functional Theory (DFT) calculations and constructing a 2D map enables the precise evaluation of surface acidity across diverse sites and materials. The simultaneous identification of surface structures and quantitative assessment of their properties or reactivities advance the molecular-level understanding of the surface sites and chemistry in functional materials, paving the way for rational design, in heterogeneous catalysis.

Atomistic structure prediction requires search algorithms capable of locating global and local minima on high-dimensional, multimodal potential energy surfaces. Traditional algorithms tend to become less effective as the dimensionality of the search space increases. In this work, we introduce an adaptive diffusion framework that reinterprets the neural-network-based denoising process as an evolutionary search mechanism for structure optimization. The framework incorporates two key optimization mechanisms. First, geometric constraints provide physics-informed guidance during sampling. Second, a memetic approach combines the global diverse sampling capabilities of diffusion models with local gradient-based relaxation. Unlike heuristic evolutionary algorithms, which rely on predefined analytical update rules for comparatively simple search distributions, neural-network-based denoising learns the underlying structure of the search space directly from the full accumulated history of sampled configurations, enabling the representation of highly complex distributions. We benchmark the algorithm using Lennard-Jones and gold clusters, demonstrating its ability to locate the global minimum and an ensemble of low-energy local minima within a single evolutionary run. The results indicate that the algorithm remains effective on high-dimensional potential energy surfaces, maintaining both population diversity and search efficiency throughout the optimization.

Layered nickelates host a variety of correlated electronic phenomena that can be tuned through doping, strain, and dimensionality. Here, we explore anion engineering as an alternative tuning knob to modify the properties of layered nickelate thin films. First, we synthesize epitaxial thin films of the n = 1 Ruddlesden-Popper nickelate, La2NiO4. We then achieve transformation to crystalline La2NiO3F2 thin films through redox-neutral, topochemical fluorination. X-ray diffraction and electron microscopy confirm the atomic structure and crystallinity of La2NiO4 and La2NiO3F2. X-ray absorption spectroscopy further confirms a NiO4F2 coordination environment and Ni2+ oxidation state following fluorination, while electronic transport measurements reveal semiconducting behavior across a range of compressive strain states (ϵ = -1.9% to -5.8%). High dynamic range reciprocal space mapping reveals nanoscale periodicity that emerges upon fluorination, and computational analysis indicates that La2NiO3F2 is susceptible to transverse structural distortions. Overall, we illustrate topochemical fluorination and anion engineering as a tuning knob to modify the chemical and electronic properties of complex oxide thin films.

IrO2 is a benchmark oxygen evolution reaction (OER) electrocatalyst, and recent studies have revealed that its OER activity can be markedly improved by the coexistence of multiple crystallographic phases. Hence, elucidating the influence of crystal phase and surface structure on OER activity is crucial for the rational design of catalysts with improved performance and reduced overpotential. In this study, first-principles calculations were performed to accurately simulate the overpotential of iridium dioxide catalysts and to clarify the surface electronic-structure factors governing the overpotential. The activity of IrO2 electrocatalysts depends on the surface index and space group. Using three density functional methods (PBE, RPBE, and optPBE-vdw), we compared the activity of stable IrO2 surfaces across the P42/mnm (tetragonal), C2/m (monoclinic), and Pbcn (orthorhombic) phases. The catalytic activity followed the order C2/m > Pbcn > P42/mnm. We explain the differences in catalytic performance among the three space groups in terms of free energy changes induced by variations in the surface-layer atomic structure. Accordingly, projected Crystal Orbital Hamilton Population analysis was employed to investigate how O-Ir-O angle variations modulate the bonding interactions of HO*, O*, and HOO* groups. The O-Ir-O angle acts as a key geometric descriptor that directly reflects the adsorption strength of these groups on the IrO2 surface. This structure-bonding interaction relationship offers valuable guidance for the rational design of highly active IrO2 OER catalysts via crystal symmetry control.

Blue phosphorene (BlueP), a two-dimensional phosphorus allotrope with a buckled honeycomb lattice, has attracted significant interest for its semiconducting properties that extend beyond graphene. Yet, its growth on Au(111) remains debated, with structural phases highly discussed due to the possible incorporation of substrate adatoms into the phosphorus adlayer. Here, we present a general methodology combining noncontact atomic force microscopy (nc-AFM) and force spectroscopy to unambiguously discriminate between competing structural models of BlueP/Au(111) obtained by density functional theory (DFT). Each phosphorus phase is resolved at the atomic scale by nc-AFM imaging, while site-dependent force spectroscopy probes local atomic corrugations within the structure. Comparison with probe-particle simulations using DFT coordinates reveals that all structural phases on Au(111) consist of an assembly of BlueP9 or BlueP16 units stabilized by Au adatoms. These findings not only solve the long-standing debate over the phosphorus-Au(111) interface but also provide an experimental strategy for identifying atomic structures of epitaxial Xenes.

The electrochemical two-electron oxygen reduction reaction (2e- ORR) offers a sustainable route for the on-site production of hydrogen peroxide (H2O2), yet developing cost-effective and high-performance catalysts remains highly challenging. In this study, porous biochar (BC) was first derived from corncob powder via KOH activation, followed by loading of uniformly dispersed cobalt nanoparticles through impregnation and carbothermal reduction methods to yield catalysts denoted as Co/BC-X (with X representing the Co : C molar ratio). The characterization of the catalysts by various analytical methods confirmed the formation of uniformly dispersed cobalt nanoparticles anchored on porous biochar with abundant oxygen-containing functional groups (OFGs), significantly enhancing the electrocatalytic production of H2O2. Density functional theory (DFT) calculations suggested the modulation of the electronic structure of the carbon atoms through synergy between Co nanoparticles and OFGs, optimizing the adsorption free energy of the OOH* intermediate closer to the theoretical optimal value and steering the ORR predominantly along the 2e- pathway. Among catalysts, the optimized Co/BC-3.3 catalyst achieved outstanding electrocatalytic performance toward H2O2 production with high H2O2 selectivity (∼96%), an electron transfer number of ∼2.06 at 0.45 V vs. RHE, a low Tafel slope of 72.42 mV dec-1 and excellent stability. In an H-type cell, the H2O2 production rate reached 1602 mmol gcat-1 h-1 using Co/BC-3.3, highlighting the effectiveness of the proposed strategy for sustainable and cost-effective conversion of biomass waste into high-performance electrocatalysts, along with providing fundamental insights into tuning the electronic structure of carbon-based materials for efficient on-site H2O2 electrosynthesis.

Fe-based amorphous alloys have attracted increasing attention as potential current-collector materials because of their unique atomic structure and corrosion resistance. In this work, Fe78Si13B9amorphous-alloy ribbons were employed as current collectors to investigate the influence of annealing treatment on the electrochemical behavior of Li||current collector half-cells. differential scanning calorimetry and x-ray diffraction analyses indicated that partial crystallization occurred after annealing at 480 °C, while the degree of crystallization further increased after annealing at 580 °C. Scanning electron microscopy (SEM) observations revealed obvious changes in surface morphology and crystallization features after annealing treatment. Electrochemical measurements showed that the Fe78Si13B9alloy annealed at 580 °C demonstrated improved cycling stability and smaller polarization evolution compared with untreated alloy and Cu foil under the present testing conditions. The sample maintained a Coulombic efficiency of approximately 97% after 150 cycles at 1.0 mA cm-2. In addition, electrochemical impedance spectroscopy and SEM observations of Li deposition morphology suggested lower interfacial impedance and comparatively denser Li deposition morphology after annealing treatment. This work provides insight into the relationship between annealing-induced structural evolution and Li deposition behavior of Fe-based amorphous-alloy current collectors.

Determining the atomic structure of amorphous materials remains a fundamental challenge in condensed-matter physics and materials science. Unlike crystalline solids, disordered systems lack long-range periodicity, which makes conventional diffraction analysis insufficient for resolving the three-dimensional atomic arrangements. Existing reverse Monte Carlo (RMC) approaches rely on stochastic sampling, limiting both computational efficiency and the ability to enforce chemically realistic local environments. Here we present TorchDisorder, a PyTorch-based framework that replaces stochastic moves with gradient-based optimization via automatic differentiation, built on three tightly integrated components: GPU-accelerated neighbor list construction via torch-sim, augmented Lagrangian constrained optimization via the Cooper library, and a differentiable structure factor engine that propagates gradients through the full Faber-Ziman weighted Fourier transform. Coordination constraints for tetrahedral, octahedral, and other geometries are specified via JSON configuration files generated automatically from crystalline precursors and require no manual parameter tuning. We apply TorchDisorder to three glass systems relevant to energy technology, namely, silica (SiO2), germania (GeO2), and lithium thiophosphate (Li2S-P2S5) solid electrolytes, and obtain structural models in quantitative agreement with experimental scattering data (R2 ≥ 0.955) within 5000 gradient steps using a single diffraction data set per system, outperforming stochastic RMC in both convergence speed and constraint satisfaction.