Room-Temperature Ferromagnetism in Epitaxial Bilayer FeSb/SrTiO3(001) Terminated with a Kagome Lattice.

Two-dimensional (2D) magnets exhibit unique physical properties for potential applications in spintronics. To date, most 2D ferromagnets are obtained by mechanical exfoliation of bulk materials with van der Waals interlayer interactions, and the synthesis of single- or few-layer 2D ferromagnets with strong interlayer coupling remains experimentally challenging. Here, we report the epitaxial growth of 2D non-van der Waals ferromagnetic bilayer FeSb on SrTiO3(001) substrates stabilized by strong coupling to the substrate, which exhibits in-plane magnetic anisotropy and a Curie temperature above 390 K. In situ low-temperature scanning tunneling microscopy/spectroscopy and density-functional theory calculations further reveal that an Fe Kagome layer terminates the bilayer FeSb. Our results open a new avenue for further exploring emergent quantum phenomena from the interplay of ferromagnetism and topology for application in spintronics.

Efficient Full-Frequency GW Calculations Using a Lanczos Method.

The GW approximation is widely used for reliable and accurate modeling of single-particle excitations. It also serves as a starting point for many theoretical methods, such as its use in the Bethe-Salpeter equation (BSE) and dynamical mean-field theory. However, full-frequency GW calculations for large systems with hundreds of atoms remain computationally challenging, even after years of efforts to reduce the prefactor and improve scaling. We propose a method that reformulates the correlation part of the GW self-energy as a resolvent of a Hermitian matrix, which can be efficiently and accurately computed using the standard Lanczos method. This method enables full-frequency GW calculations of material systems with a few hundred atoms on a single computing workstation. We further demonstrate the efficiency of the method by calculating the defect-state energies of silicon quantum dots with diameters up to 4 nm and nearly 2,000 silicon atoms using only 20 computational nodes.

Predicting Binding Energies and Electronic Properties of Boron Nitride Fullerenes Using a Graph Convolutional Network.

As isoelectronic counterparts of carbon fullerenes, medium-sized boron nitride clusters also prefer cage structures composed of even-sized polygons. As the cluster size increases, the number of cage isomers grows rapidly, and determining the ground state structure requires a tremendous amount of DFT calculations. Herein, we develop a graph convolutional network (GCN) that can describe the energy of a (BN)n cage by its topology connection. We define a vertex feature vector on a dual polyhedron by the permutation of the neighbor vertices' degree and aggregate the information on vertices by two graph convolutional layers to learn the local feature of the dual polyhedron. The GCN is trained on (BN)28 and subsequently tested on (BN)23 and (BN)24 data sets, which satisfactorily reproduce the order of isomer energies from DFT calculations. We further employ the trained GCN to predict the ground state structures within the size range of n = 25-32, which agree well with DFT results. Using the same GCN framework, we also successfully trained the highest-occupied or lowest-unoccupied orbital energies of (BN)28 isomers. The present graph convolutional network establishes a direct mapping between the topological connection and the energetic or electronic properties of a cage-like cluster or molecule.

Two-dimensional fullerene-based monolayer materials assembled by C80 and Sc3N@C80.

Construction of two-dimensional (2D) materials using fullerenes as building blocks has attracted particular attention, primarily due to their ability to integrate desired functionalities into devices. However, realization of stable 2D phases of polymerized fullerenes remains a big challenge. Here, we propose two stable 2D monolayer phases with covalently bridged C80 cages, namely α-C80-2D and ß-C80-2D, which are semiconductors with strong absorption in the long wave range and appreciable carrier mobility, respectively. The high stability originates from the bond energy released by the [2+2] cycloaddition polymerization of C80 is greater than the deformation energy of a cage. Starting from α-C80-2D, endohedral incorporation of the Sc3N molecule into each C80 cage leads to 2D semiconductors of α-Sc3N@C80-2D and α'-Sc3N@C80-2D, which possess exceptional stability and diverse physical properties, including unique electronic band structures, strong optical absorption in the visible (VIS) to near-infrared (NIR) regime, and anisotropic optical characteristics. Remarkably, a temperature-induced order-disorder transition in the α-Sc3N@C80-2D phase has been observed at elevated temperatures above 600 K. These findings expand the family of 2D carbon materials and provide useful clue for the potential applications of fullerene-assembled monolayer networks.

Effect of fission defects on tensile strength of U3Si2 Σ5(210) grain boundary from first-principles calculations.

U3Si2 is regarded as a promising accident tolerant fuel (ATF) to replace the commercial fuel UO2; however, grain boundary (GB) embrittlement of U3Si2 caused by irradiation-induced defect segregation remains to be clarified. In this work, the U3Si2 Σ5(210) symmetrically tilted GB is taken as a representative to elucidate the individual effect of xenon (Xe) and vacancy on the tensile strength and failure of GBs using first-principles calculations. Compared with the predicted segregation energies of defects at the most energetically favourable positions of GBs, Si vacancy (VSi) has a much stronger preference to segregate to GBs than that of Xe substitution on the Si sublattice (XeSi). Moreover, the strengthening/embrittlement potency of GBs with single vacancy/Xe is evaluated using the first-principles-based uniaxial tensile test. Although both VSi and XeSi yield a weakening effect on the strength of the U3Si2 Σ5(210) GB, such defective GBs exhibit significantly stronger interface strengths compared to the corresponding defects segregated to the UO2 Σ3(111) GB. The underlying mechanism of strength change of U3Si2 GBs is discussed in terms of charge analysis. Our results can provide a fundamental understanding of the mechanical behavior of irradiated GBs from an atomic perspective.

Luminescence properties of endohedrally doped group-IV clusters.

Endohedrally doped clusters form a large category of cage clusters, with unique structures, diverse elemental compositions, and highly tunable electronic structures and physisochemical properties. They have been widely achieved in laboratory and may serve as functional building blocks for assembling new supermolecular structures and devices. In this paper, for the first time, we disclosed the luminescence properties of endohedrally doped group-IV clusters by time-dependent density functional theory calculations. A total of 64 cage clusters have been explored in terms of stability, emission wavelength, and the energy difference between the first excited singlet and triplet states. The key geometric and electronic factors governing the photophysical properties of these cage clusters were unveiled, to provide crucial insights for crafting atomically precise nanoclusters for optical and optoelectronic applications.

p-block germanenes as a promising electrocatalysts for the oxygen reduction reaction.

The oxygen reduction reaction (ORR), a pivotal process in hydrogen fuel cells crucial for enhancing fuel cell performance through suitable catalysts, remains a challenging aspect of development. This study explores the catalytic potential of germanene on Al (111), taking advantage of the successful preparation of stable reconstructed germanene layers on Al (111) and the excellent catalytic performance exhibited by germanium-based nanomaterials. Through first-principles calculations, we demonstrate that the O2 molecule can be effectively activated on both freestanding and supported germanene nanosheets, featuring kinetic barriers of 0.40 and 0.04 eV, respectively. The presence of the Al substrate not only significantly enhances the stability of the reconstructed germanene but also preserves its exceptional ORR catalytic performance. These theoretical findings offer crucial insights into the substrate-mediated modulation of germanene stability and catalytic efficiency, paving the way for the design of stable and efficient ORR catalysts for future applications.

Tin-oxo nanoclusters for extreme ultraviolet photoresists: Effects of ligands, counterions, and doping.

The extreme ultraviolet (EUV) nanolithography technology is the keystone for developing the next-generation chips. As conventional chemically amplified resists are approaching the resolution limit, metal-containing photoresists, especially tin-oxo clusters, seize the opportunity to embrace this challenge owing to their small sizes, precise atomic structures, and strong EUV absorption. However, atomistic insights into the mechanism for regulating their photolithographic behavior are lacking. Herein, we systematically explored the effects of ligands, counterions, and endohedral doping on the photophysical properties of tin-oxo cage clusters by first-principles calculations combined with molecular dynamics simulations. Photoresists assembled by allyl-protected clusters with small-size OH- or Cl- counterions have a high absorption coefficient at the EUV wavelength of 13.5 nm and a low energy cost for ligand detachment and superior stability to ensure high sensitivity and strong etch resistance, respectively. The photoresist performance can further be improved by endohedral doping of the metal-oxo nanocage with Ag+ and Cd2+ ions, which exhibit superatomic characteristics and are likely to be synthesized in laboratory. These theoretical results provide useful guidance for modification of metal-oxo clusters for high-resolution EUV photolithography.

Identification and validation of biomarkers related to lipid metabolism in osteoarthritis based on machine learning algorithms.

BACKGROUND: Osteoarthritis and lipid metabolism are strongly associated, although the precise targets and regulatory mechanisms are unknown. METHODS: Osteoarthritis gene expression profiles were acquired from the GEO database, while lipid metabolism-related genes (LMRGs) were sourced from the MigSB database. An intersection was conducted between these datasets to extract gene expression for subsequent differential analysis. Following this, functional analyses were performed on the differentially expressed genes (DEGs). Subsequently, machine learning was applied to identify hub genes associated with lipid metabolism in osteoarthritis. Immune-infiltration analysis was performed using CIBERSORT, and external datasets were employed to validate the expression of these hub genes. RESULTS: Nine DEGs associated with lipid metabolism in osteoarthritis were identified. UGCG and ESYT1, which are hub genes involved in lipid metabolism in osteoarthritis, were identified through the utilization of three machine learning algorithms. Analysis of the validation dataset revealed downregulation of UGCG in the experimental group compared to the normal group and upregulation of ESYT1 in the experimental group compared to the normal group. CONCLUSIONS: UGCG and ESYT1 were considered as hub LMRGs in the development of osteoarthritis, which were regarded as candidate diagnostic markers. The effects are worth expected in the early diagnosis and treatment of osteoarthritis.

Recognition and localization of asymmetric spectra in FBG sensing networks.

We propose a deep learning demodulation method based on a long short-term memory (LSTM) neural network for fiber Bragg grating (FBG) sensing networks. Interestingly, we find that both low demodulation error and distorted spectrum recognition are realized using the proposed LSTM-based method. Compared with conventional demodulation methods, including Gaussian-fitting, convolutional neural network, and the gated recurrent unit, the proposed method improves the demodulation accuracy being close to 1 pm and achieves a demodulation time of 0.1s for 128-FBG sensors. Furthermore, our approach can realize 100% accuracy of distorted spectra recognition and complete the location of spectra with spectrally encoded FBG sensors.

High-performance gas sensor with symmetry-protected quasi-bound states in the continuum.

A high-performance optical sensor with a vertical cavity structure comprising high-contrast gratings (HCGs) and a distributed Bragg reflector was designed. The structure has two peaks with different mechanisms, among which the first peak is formed by breaking the symmetry of the structure and coupling between the incident wave and the symmetric protection mode. The joint action of the HCG resonance and Fabry-Perot resonance formed a second peak. Moreover, changing the structural parameters, such as the grating width, period, and cavity length, can tune the spectral reflection dips. The sensitivity of the designed structure was as high as 674 nm/RIU, and the corresponding figure of merit was approximately 34741. The presented gas sensor provides a method for applying a vertical cavity structure to the sensing domain.

Self-healing FBG sensor network fault-detection based on a multi-class SVM algorithm.

We propose a three-layer ring architecture with enhanced reconfigurable capabilities for fiber Bragg grating (FBG) sensor networks. The proposed network is capable of self-healing when three fiber links fail. In addition to self-healing, soft faults in the FBG sensors can be detected using a multi-classification support vector machine (multi-class SVM) algorithm. The detection accuracy reached 99%. Additionally, we used an artificial neural network (ANN) reliability estimation model to estimate the reliability of the FBG self-healing network. The results show that the ANN reliability analysis model can accurately estimate the reliability of the architecture at a reasonable cost.

The s-p Nonhybrid Nature Causes Adaptive Superatomic States of Bismuth Clusters.

We report a joint experimental and theoretical study on the stability and reactivity of Bin + (n=5-33) clusters. The alternating odd-even effect on the reaction rates of Bin + clusters with NO is observed, and Bi7 + finds the most inertness. First-principles calculation results reveal that the lowest energy structures of Bi6-9 + exhibit quasi-spherical geometry pertaining to the jellium shell model; however, the Bin + (n≥10) clusters adopt assembly structures. The prominent stability of Bi7 + is associated with its highly symmetric structure and superatomic states with a magic number of 34e closed shell. For the first time, we demonstrate that the unique s-p nonhybrid feature in bismuth rationalizes the stability of Bi6-9 + clusters within the jellium model, by filling the 6s electrons into the superatomic orbitals (forming "s-band"). Interestingly, the stability of 18e "s-band" coincides with the compact structure for Bin + at n≤9 but assembly structures for n≥10, showing an accommodation of the s electrons to the geometric structure. The atomic p-orbitals also allow to form superatomic orbitals at higher energy levels, contributing to the preferable structures of tridentate binding units. We illustrate the s-p nonhybrid nature accommodates the structure and superatomic states of bismuth clusters.

Core-Packing-Related Vibrational Properties of Thiol-Protected Gold Nanoclusters and Their Excited-State Behavior.

Thiolate-protected gold nanoclusters, with unique nuclearity- and structure-dependent properties, have been extensively used in energy conversion and catalysis; however, the mystery between kernel structures and properties remains to be revealed. Here, the influence of core packing on the electronic structure, vibrational properties, and excited-state dynamics of four gold nanoclusters with various kernel structures is explored using density functional theory combined with time-domain nonadiabatic molecular dynamics simulations. We elucidate the correlation between the geometrical structure and excited-state dynamics of gold nanoclusters. The distinct carrier lifetimes of the four nanoclusters are attributed to various electron-phonon couplings arising from the different vibrational properties caused by core packing. We have identified specific phonon modes that participate in the electron-hole recombination dynamics, which are related to the gold core of nanoclusters. This study paints a physical picture from the geometric configuration, electronic structure, vibrational properties, and carrier lifetime of these nanoclusters, thereby facilitating their potential application in optoelectronic materials.

Robust electronic properties of monolayer BeO against molecule adsorption.

The stability of two-dimensional (2D) materials upon exposure to ambient conditions is significant for their applications. In this paper, the air stability of the BeO monolayer with and without vacancy defects is carefully studied via DFT calculations. Our results suggest high structural and electronic stability of BeO monolayers upon exposure to O2, N2, CO2 and H2O even with Be vacancies. O vacancies are not favorable in free-standing BeO monolayers and can be easily healed by H2O or CO2 adsorption. Due to the high stability, large band gap and atomic flat surface, BeO monolayers are expected to be an ideal encapsulation material for 2D electronic devices.

Understanding xenon and vacancy behavior in UO2, UN and U3Si2: a comparative DFT+U study.

Extensive attention has been paid to accident tolerant fuels (ATFs), such as uranium mononitride (UN) and uranium sesquisilicide (U3Si2), which are regarded as potential candidates to replace uranium dioxide (UO2) in light-water reactors (LWRs). However, the thermodynamic behavior of fission gas atoms in these fuels that can quantitatively affect the burnup characteristics of ATFs needs to be explored. To this end, systematic density functional calculations on the energetic properties of xenon (Xe)-vacancy complexes in UO2, UN and U3Si2 are performed with the GGA+U approach as well as the corrected chemical potential. The stabilities of Xe-vacancy clusters, including interstitial trap site (IS), mono-, bi- and tri-atomic vacancies, are thoroughly assessed. The formation energies of vacancy complexes indicate that they are more likely to form vacancy cluster defects and their complexes with Xe in UO2 and to generate mono-atomic vacancy and Xe-vacancy complexes in both UN and U3Si2. Xe can be strictly confined by the trap sites in UO2 and UN, and yet in U3Si2, it prefers to move to the centre of a large free volume trap site. The strong solubility of Xe in U3Si2 indicates the excellent storage capacity of fission gas products in the matrix. Overall, this work provides comprehensive insights into the origins of the interplay between Xe and vacancies as well as the thermodynamic behavior of defects in uranium-based fuels.

Solar driven CO2 hydrogenation to HCOOH on (TiO2)n (n = 1-6) atomic clusters.

Artificial photosynthesis is a crucial reaction that addresses energy and environmental challenges by converting CO2 into fuels and value-added chemicals. However, efficient catalytic activity using earth-abundant materials can be challenging due to intrinsic limitations. Herein, we explore neutral (TiO2)n (n = 1-6) atomic clusters for CO2 hydrogenation via comprehensive ab initio calculations combined with time-dependent functional theory. Our results show that these (TiO2)n clusters exhibit outstanding thermodynamic stabilities and decent surficial activities for CO2 activation and H2 dissociation, both of which possess kinetic barriers down to 0-0.74 eV. We establish a relationship between the binding strength of *CO2 species and electron characterization for these (TiO2)n clusters. These clusters, which have a wide energy gap between the highest occupied molecular orbital (HOMO) and the lowest unoccpied molecular orbital (LUMO) that allows them to harvest the solar light in the ultraviolet regime, enabling efficient catalysis for driving the catalysis of CO2 conversion. They provide exclusive reaction channels and high selectivity for yielding HCOOH products via the carboxyl mechanism, involving the kinetic barrier of the limiting step of 0.74-1.25 eV. We also investigated the substrate effect on supported (TiO2)n clusters, with non-metallic substrates featuring inert surfaces serving as suitable options for anchoring (TiO2)n clusters while preserving their intrinsic activity and selectivity. These computational results have significant implications not only for meeting energy demands but also for mitigating carbon emissions by utilizing CO2 as an alternative feedstock rather than considering it solely as a greenhouse gas.

Single atom alloy clusters Agn-1X- (X = Cu, Au; n = 7-20) reacting with O2: Symmetry-adapted orbital model.

Single atom alloy AgCu catalysts have attracted great attention, since doping the single Cu atom introduces narrow free-atom-like Cu 3d states in the electronic structure. These peculiar electronic states can reduce the activation energies in some reactions and offer valuable guidelines for improving catalytic performance. However, the geometric tuning effect of single Cu atoms in Ag catalysts and the structure-activity relationship of AgCu catalysts remain unclear. Here, we prepared well-resolved pristine Agn - as well as single atom alloy Agn-1Cu- and Agn-1Au- (n = 7-20) clusters and investigated their reactivity with O2. We found that replacing an Ag atom in Agn - (n = 15-18) with a Cu atom significantly increases the reactivity with O2, while replacement of an Ag with an Au atom has negligible effects. The adsorption of O2 on Agn - or Agn-1Cu- clusters follows the single electron transfer mechanism, in which the cluster activity is dependent on two descriptors, the energy level of α-HOMO (strong correlation) and the α-HOMO-LUMO gap (weak correlation). Our calculation demonstrated that the cluster arrangements caused by single Cu atom alloying would affect the above activity descriptors and, therefore, regulates clusters' chemical activity. In addition, the observed reactivity of clusters in the representative sizes with n = 17-19 can also be interpreted using the symmetry-adapted orbital model. Our work provides meaningful information to understand the chemical activities of related single-atom-alloy catalysts.

Mechanisms in the Catalytic Reduction of N2O by CO over the M13@Cu42 Clusters of Aromatic-like Inorganic and Metal Compounds.

Metal aromatic substances play a unique and important role in both experimental and theoretical aspects, and they have made tremendous progress in the past few decades. The new aromaticity system has posed a significant challenge and expansion to the concept of aromaticity. From this perspective, based on spin-polarized density functional theory (DFT) calculations, we systematically investigated the doping effects on the reduction reactions of N2O catalyzed by CO for M13@Cu42 (M = Cu, Co, Ni, Zn, Ru, Rh, Pd, Pt) core-shell clusters from aromatic-like inorganic and metal compounds. It was found that compared with the pure Cu55 cluster, the strong M-Cu bonds provide more structural stability for M13@Cu42 clusters. Electrons that transferred from the M13@Cu42 to N2O promoted the activation and dissociation of the N-O bond. Two possible reaction modes of co-adsorption (L-H) and stepwise adsorption (E-R) mechanisms over M13@Cu42 clusters were thoroughly discovered. The results showed that the exothermic phenomenon was accompanied with the decomposition process of N2O via L-H mechanisms for all of the considered M13@Cu42 clusters and via E-R mechanisms for most of the M13@Cu42 clusters. Furthermore, the rate-limiting step of the whole reactions for the M13@Cu42 clusters were examined as the CO oxidation process. Our numerical calculations suggested that the Ni13@Cu42 cluster and Co13@Cu42 clusters exhibited superior potential in the reduction reactions of N2O by CO; especially, Ni13@Cu42 clusters are highly active, with very low free energy barriers of 9.68 kcal/mol under the L-H mechanism. This work demonstrates that the transition metal core encapsulated M13@Cu42 clusters can present superior catalytic activities towards N2O reduction by CO.

Ambient Preparation of Benzoxazine-based Phenolic Resins Enables Long-term Sustainable Photosynthesis of Hydrogen Peroxide.

Rational design of polymer structures at the molecular level promotes the iteration of high-performance photocatalyst for sustainable photocatalytic hydrogen peroxide (H2 O2 ) production from oxygen and water, which also lays the basis for revealing the reaction mechanism. Here we report a benzoxazine-based m-aminophenol-formaldehyde resin (APFac) polymerized at ambient conditions, exhibiting superior H2 O2 yield and long-term stability to most polymeric photocatalysts. Benzoxazine structure was identified as the crucial photocatalytic active segment in APFac. Favorable adsorption of oxygen/intermediates on benzoxazine structure and commendable product selectivity accelerated the reaction kinetically in stepwise single-electron oxygen reduction reaction. The proposed benzoxazine-based phenolic resin provides the possibility of production in batches and industrial application, and sheds light on the de novo design and analysis of metal-free polymeric photocatalysts.