arXiv subjects

Xinguo Ren

Publications and source records attributed to Xinguo Ren.

At least 19 recordsLinked to original sources

arXiv2026

Screening phonon-mediated superconductors from static orbital Hamiltonians

The first-principles search for superconductors is severely limited by the high cost of electron-phonon coupling (EPC) calculations. Here we develop a low-cost, physically transparent framework that identifies strong-EPC materials directly from static orbital-based Hamiltonians without explicit phonon perturbation calculations. Verification using density functional perturbation theory (DFPT) for representative superconductors shows that the framework captures semi-quantitatively the EPC scale at substantially lower computational cost. Applied to more than 36,000 compounds in the MattKeyBond database, it identifies 34 dynamically stable superconducting candidates with calculated $T_c > 10$ K after DFPT verification. These candidates reveal two distinct routes to relatively high-$T_c$ superconductivity: a metallized covalent $\sigma$-bond route that is more favorable for achieving high-$T_c$ superconductors, and a Fermi-level density-of-states accumulation route that can enhance $T_c$ but usually to a more limited extent.

cond-mat.supr-con↗

arXiv2026

Iterative minimization in reduced density matrix functional theory for periodic systems

Reduced density matrix functional theory (RDMFT) offers a route beyond Kohn-Sham density functional theory for strongly correlated systems, yet practical calculations for periodic solids are still out of reach. We formulate RDMFT for extended systems in a basis-independent way and present a planewave implementation using iterative minimization for periodic solids, evaluating nonlocal exchange-correlation functionals through the existing adaptive compressed exchange machinery. Natural occupations are optimized under N-representability constraints with a spectral projected gradient (SPG) method or an first-order explicit-by-implicit (EBI) map, while natural orbitals are updated by Riemannian optimization on the complex Stiefel manifolds. Benchmarks on typical systems of \ce{H2}, silicon, and sodium with the Hartree-Fock functional show that SPG reproduces converged hybrid references, whereas EBI can stall when occupations approach $0$ or $1$. With the power and M\"uller functionals, SPG yields lower energies and more stable convergence than EBI. Applications to fractionally charged \ce{LiH}, dissociating \ce{H2} and \ce{N2} molecules, and equation of state of silicon show that the algorithm presented in this implementation is reliable and robust.

cond-mat.str-el↗

arXiv2026

Efficient Bethe-Salpeter Equation Calculations Based on Numerical Atomic Orbitals and Norm-Conserving Pseudopotentials: Dual-${\boldsymbol k}$-Mesh Strategy

We present an efficient implementation of the Bethe--Salpeter equation (BSE) based on numerical atomic orbitals (NAOs) and norm-conserving pseudopotentials within the ABACUS+LibRPA framework. By exploiting the localized resolution-of-identity (LRI) technique, the screened Coulomb interaction is cast into a real-space, unit-cell-indexed form $W_{\mu\nu}(\boldsymbol R)$ that is inherently short-ranged and well localized. This spatial locality enables an efficient Fourier interpolation of the BSE kernel from the coarse $\boldsymbol k$-mesh used in the preceding $GW$ calculation to an arbitrarily dense $\boldsymbol k$-mesh on which the BSE Hamiltonian is assembled and diagonalized, thereby giving rise naturally to a dual-$\boldsymbol k$-mesh workflow. Building on this scheme, we systematically examine the convergence of the absorption spectra with respect to the NAO basis set, the auxiliary basis set, and the $\boldsymbol k$-point sampling. Benchmark calculations for both molecular and periodic systems collectively validate the accuracy of the present implementation and establish the dual-$\boldsymbol k$-mesh strategy as a practical and reliable approach for $GW$+BSE calculations.

cond-mat.mtrl-sci↗

arXiv2026

Termination-Dependent Surface States and Magnetic Fingerprints of Chiral Helimagnet Cr1/3TaS2

Chiral helimagnets based on intercalated transition-metal dichalcogenides, characterized by nano-scale spin ordering, provide a powerful route to engineer chiral spin textures (e.g. the topologically protected magnetic solitons) and emergent electronic functionality at reduced dimensions, where surface and interface states often dominate device operation. However, despite growing interest, direct experimental studies of termination-dependent surface electronic structures and their temperature-driven magnetic evolution remain largely unexplored, hindering a microscopic understanding of the electronic states that is crucial for the development of low-dimensional spintronic devices. Here, for the first time, taking Cr1/3TaS2 as a representative example, we systematically investigate the termination-dependent surface electronic states of the chiral helimagnets and uncover their distinct temperature evolution across the magnetic transition (TC~142K) by combining high-resolution ARPES with a micro-focused beam and surface-state-resolved first-principles calculations. The TaS2-terminated surface hosts folded monolayer-like TaS2 bands under the $\sqrt3\times\sqrt3$ superlattice potential and a shallow triangular electron pocket at the superlattice $\bar K$ point arising from Cr-Ta orbital hybridization. In contrast, the Cr-terminated surface exhibits reconstructed hole pockets with pronounced magnetic band splitting. This splitting disappears above TC and closely follows the chiral helimagnetic order parameter, providing a direct spectroscopic fingerprint of chiral helimagnetic order. In addition, multiple ultranarrow Cr-d-derived surface flat bands are resolved. These findings establish Cr1/3TaS2 as a model system in which surface electronic states are strongly coupled to chiral magnetism, opening new opportunities for chiral spintronic and valleytronic micro/nanodevices.

cond-mat.mtrl-sci↗

arXiv2026

$G^0W^0$ implementation based on the pseudopotential and numerical-atomic-orbital basis-set framework: Algorithms and benchmarks

The $GW$ method delivers substantially improved accuracy in electronic band structure calculations over conventional Kohn-Sham density functional theory (KS-DFT) by explicitly incorporating the electron self-energy effect beyond mean-field approximations. Despite many existing implementations, a periodic $GW$ implementation within the framework of numerical atomic orbitals (NAO) combined with the pseudopotential (PP) scheme has not been reported. This is urgently needed given the increasing popularity of the NAO-PP framework in KS-DFT calculations and its importance for the development of machine-learning electronic-structure approaches. In this work, we present an efficient NAO-PP-based $G^0W^0$ computational framework by interfacing the first-principles software package ABACUS with LibRPA -- a library for performing low-scaling random-phase approximation and $GW$ calculations based on NAOs. Our approach employs the localized resolution of identity (LRI) technique with a novel compression scheme, significantly improving both computational efficiency and numerical stability. In addition, an analytic treatment of the small-q limit of the microscopic dielectric function reduces the need for dense q-point sampling. Furthermore, we propose a practical strategy to select a suitable KS-DFT pseudopotential prior to $G^0W^0$ calculations by examining the frequency-dependent macroscopic dielectric function. Systematic benchmarks validate the effectiveness of our compression scheme and real-space tensor filtering strategies, demonstrating both high accuracy and significant computational efficiency gains. Comparisons with established $G^0W^0$ implementations show excellent agreement in band structures and band gaps, confirming ABACUS+LibRPA as a reliable and efficient platform for large-scale $G^0W^0$ simulations.

cond-mat.mtrl-sci↗

arXiv2026

Low-scaling \textit{GW} calculations of quasi-particle energies for extended systems within the numerical atomic orbital framework

The many-body perturbation theory within the $GW$ approximation is a widely used method for describing the electronic band structures in real materials. Its application to large-scale systems is, however, impeded by its high computational cost. The rate-limiting steps in a typical $GW$ implementation are the evaluation of the polarization function under the random phase approximation (RPA) and the evaluation of the $GW$ self-energy, both of which have a canonical $O(N^4)$ scaling with $N$ being the system size. The conventional space-time algorithm within the plane-wave basis sets reduces the scaling from $O(N^4)$ to $O(N^3)$, albeit with a large prefactor and increased memory cost. Here, we present a space-time algorithm within the numerical atomic orbital (NAO) basis-set framework, for which the evaluation of the polarization function and self-energy is formally reduced to $O(N^2)$ or better with respect to system size. This is achieved by computing these quantities in real space, where low-scaling algorithms can be formulated by leveraging the localized resolution of identity (LRI) technique. The resulting NAO-based, LRI-enhanced space-time $GW$ algorithm has been implemented in the LibRPA library interfaced with the FHI-aims code package. Benchmark calculations for crystalline solids show that the low-scaling implementation yields quasi-particle energies in close agreement with the conventional $O(N^4)$ k-space formalism previously implemented in FHI-aims. For the systems studied here, the observed overall scaling is substantially reduced relative to the canonical approach, and the low-scaling implementation becomes advantageous already for systems containing fewer than 100 atoms.

cond-mat.mtrl-sci↗

arXiv2026

Bridging Crystal Structure and Material Properties via Bond-Centric Descriptors

Although chemical bonding is the fundamental mechanistic bridge connecting atomic structure to macroscopic material properties, current data-driven materials science largely treats it as an implicit "black box". Existing machine learning (ML) models rely predominantly on geometric coordinates, forcing them to implicitly relearn complex quantum mechanics from scratch. This lack of intermediate physical features limits model interpretability and generalizability, particularly when training data is scarce. To solve this problem, we introduce MattKeyBond, a bond-centric materials database that explicitly maps the local electronic landscape and bonding interactions of materials. Building on this, we propose Bonding Attractivity (BA), a novel element-specific descriptor that quantifies the intrinsic capability of atoms to form covalent networks. By providing pre-calculated, energy-dimensional bonding descriptors, MattKeyBond transforms the implicit "black box" into physically interpretable features. This strategy relieves ML models from the burden of deducing physical laws from pure geometry, enabling accurate predictions even with limited data and seamlessly integrating electronic structure theory into modern AI workflows.

cond-mat.mtrl-sci↗

arXiv2026

All-electron Quasiparticle Self-consistent GW for Molecules and Periodic Systems within the Numerical Atomic Orbital Framework

We report an all-electron implementation of the quasiparticle self-consistent GW (QSGW) method for molecular and periodic systems within the framework of numerical atomic orbitals (NAOs), as implemented in the LibRPA software package. Our implementation is based on the space-time formalism, combined with the localized resolution-of-identity approximation to treat two-electron quantities. We found that analytical continuation of the self-energy matrix, in combination with the ``Mode B" QSGW scheme, can yield stable self-consistent quasiparticle energy spectra. Systematic benchmark calculations on molecules and crystalline solids (including typical semiconductors and wide-gap insulators) demonstrate that our NAO-based QSGW scheme yields molecular ionization potentials and quasiparticle band gaps for periodic solids that are consistent with reference results from established implementations. Our work opens the way for large-scale QSGW calculations, taking advantage of the NAO-based low-scaling algorithm previously developed for the G0W0 method.

cond-mat.mtrl-sci↗

arXiv2025

Real-time time-dependent density functional theory simulations with range-separated hybrid functionals for periodic systems

Real-time time-dependent density functional theory (RT-TDDFT) is a powerful approach for investigating various ultrafast phenomena in materials. However, most existing RT-TDDFT studies rely on adiabatic local or semi-local approximations, which suffer from several shortcomings, including the inability to accurately capture excitonic effects in periodic systems. Combining RT-TDDFT with range-separated hybrid (RSH) functionals has emerged as an effective strategy to overcome these limitations. The RT-TDDFT-RSH implementation for periodic systems requires careful treatment of the Coulomb singularity and choosing proper gauges for the incorporation of external fields. We benchmark two schemes for treating the Coulomb singularity - the truncated Coulomb potential and the auxiliary-function correction - and find that the latter shows better convergence behavior and numerical stability for long-range corrected hybrid functions. Additionally, we assess the impact of gauge choice in simulations using numerical atomic orbitals and show that the recently proposed hybrid gauge incorporating position-dependent phases provides a more accurate description of excitonic absorption than the conventional velocity gauge. Our implementation significantly improves the accuracy of RT-TDDFT-RSH for modeling ultrafast excitonic dynamics in periodic systems.

cond-mat.mtrl-sci↗

arXiv2025

Influence of Exchange-Correlation Functionals and Neural Network Architectures on Li$^+$-Ion Conductivity in Solid-State Electrolyte from Molecular Dynamics Simulations with Machine-Learning Force Fields

With the rapid advancement of machine learning techniques for materials simulations, machine-learned force fields (MLFFs) have become a powerful tool that complements first-principles calculations by enabling high-accuracy molecular dynamics simulations over extended timescales. Typically, MLFFs are trained on data generated from density functional theory (DFT) using a specific exchange-correlation (XC) functional, with the goal of reproducing DFT-level properties. However, the uncertainties in MLFF-based simulations--arising from variations in both MLFF model architectures and the choice of XC functionals--remain insufficiently understood. In this work, we construct MLFF models of different architectures trained on DFT data from both semilocal and hybrid functionals to describe Li$^+$ diffusion in the solid-state electrolyte Li$_6$PS$_5$Cl. We systematically investigate how different XC functionals influence the Li$^+$ diffusion coefficient. To reduce statistical uncertainty, the mean squared displacements are averaged over 300 independent molecular dynamics (MD) trajectories of 70 ps each, yielding statistical variations below $1\%$. This enables a clear assessment of the respective influences of the functional and the MLFF model. Due to its tendency to underestimate band gaps and migration barriers, the semilocal functional predicts consistently higher Li$^+$ diffusion coefficients, compared to the hybrid functional. Furthermore, comparisons among various neural network methods reveal that the differences in predicted diffusion coefficients arising from different network architectures are of the same order of magnitude as those caused by different functionals, indicating that the choice of the network model itself substantially influences the MLFF predictions. This observation calls from an urgent need for standardized protocols to minimize model-dependent biases in MLFF-based MD.

cond-mat.mtrl-sci↗

arXiv2025

Self-Consistent Random Phase Approximation from Projective Truncation Approximation Formalism

We derive the self-consistent random phase approximations (sc-RPA) from the projective truncation approximation (PTA) for the equation of motion of two-time Green's function. The obtained sc-RPA applies to arbitrary temperature and recovers the Rowe's formalism at zero temperature. The PTA formalism not only rationalize Rowe's formula, but also provides a general framework to extend sc-RPA. We implement the sc-RPA calculation for the one-dimensional spinless fermion model in the parameter regime of disordered ground state, with the N-representability constraints enforced. The obtained ground state energy, correlation function, and density spectral function agree well with existing results. The features of the Luttinger liquid ground state and the continuum/bound state in the spectral function are well captured. We discuss several issues concerning the approximations made in RPAs, difficulties of RPA for symmetric state, and the static component problem of PTA.

cond-mat.str-el↗

arXiv2025

A finite-element Delta-Sternheimer approach for computing accurate all-electron RPA correlation energies of polyatomic molecules

Attaining a reliable complete basis set (CBS) limit remains a significant challenge in ab initio correlated electronic-structure calculations. Building on our previous work for atoms and diatomic molecules, we present a finite-element (FE) Delta Sternheimer approach for numerically accurate random phase approximation (RPA) calculations applicable to general molecules. This approach seamlessly integrates atomic orbital basis sets with FE grids, enabling an arbitrary precision representation of first order wavefunctions. As a result, the density response function and RPA correlation energies can be computed with fully controlled numerical precision. The Delta Sternheimer approach thus provides direct access to RPA correlation energies at the CBS limit, eliminating reliance on conventional extrapolation schemes. We apply this approach to two problems: The energy hierarchy of 20 water-dimer configurations and the atomization energies of 50 molecules from the G2 set. For the water dimer, we examine the basis set dependence of the isomer energy ordering. For the G2 set, we investigate the residual numerical uncertainty in the conventional extrapolated CBS limit, both with and without correction for basis-set superposition error (BSSE).

cond-mat.mtrl-sci↗

arXiv2025

Analytical gradients of random-phase approximation plus corrections from renormalized single excitations

The random-phase approximation (RPA) formulated within the adiabatic connection fluctuation-dissipation framework is a powerful approach to compute the ground-state energies and properties of molecules and materials. Its overall underbinding behavior can be effectively mitigated by a simple correction term, called renormalized single excitation (rSE) correction. Analytical gradient calculations of the RPA energy have become increasingly available, enabling structural relaxations and even molecular dynamics at the RPA level. However, such calculations at the RPA+rSE level have not been reported, due to the lack of the rSE analytical gradient. Here, we present the first formulation and implementation of the analytical gradients of the rSE energy with respect to the nuclear coordinates within an atomic-orbital basis set framework, which allows us to assess the performance of RPA+rSE in determining the molecular geometries and energetics. It is found that the slight overestimation behavior of RPA for small covalently bonded molecules is strengthened by rSE, while such behavior for molecules bonded with purely dispersion interactions is corrected. We further applied the approach to the water clusters, and found that the energy difference between the low-energy isomers of water hexamers is almost unchanged when going from RPA to RPA+rSE geometries. For the bigger WATER27 test set, using the RPA+rSE geometries instead of the RPA ones leads to a slight reduction of the mean absolute error of RPA+rSE from 0.91 kcal/mol to 0.70 kcal/mol, at the complete basis set.

physics.chem-ph↗

arXiv2025

Gas-solid Reaction Dynamics on Li$_6$PS$_5$Cl Surfaces: A Case Study of the Influence of CO$_2$ and CO$_2$/O$_2$ Atmospheres Using AIMD and MLFF Simulations

In recent years, rapid progress has been made in solid-state lithium batteries. Among various technologies, coating the surface of electrodes or electrolytes has proven to be an effective method to enhance interfacial stability and improve battery cycling performance. Recent experimental studies showed that gas-solid reactions offer a convenient approach to form modified coating layers on the solid electrolyte. Here, we performed computational simulations to investigate this surface reaction process. Specifically, we simulated the gas-solid reactions of Li$_6$PS$_5$Cl(LPSC) solid-state electrolytes in pure CO$_2$ and in mixed CO$_2$/O$_2$ atmospheres using ab-initio molecular dynamics (AIMD) and machine-learning force fields (MLFF)-accelerated molecular dynamics (MD) approaches. In the former case, LPSC surfaces primarily form Li$_2$CO$_2$S because it is difficult to dissociate another oxygen atom from the second CO$_2$ molecule. While in CO$_2$/O$_2$ mixed atmosphere, O$_2$ molecules preferentially adsorb onto LPSC, which supplies oxygen sites for subsequent CO$_2$ adsorption to form carbonate -CO$_3$ units. This reaction pathway ultimately generates an interfacial product dominated by Li$_2$CO$_3$. These coatings exhibit distinct electronic and ionic conductivity characteristics, allowing the possibility to control coating compositions and configurations by adjusting the gas-solid reactions. Key criteria for applying this strategy are extracted from the current research.

physics.chem-ph↗

arXiv2025

Applying Space-Group Symmetry to Speed up Hybrid-Functional Calculations within the Framework of Numerical Atomic Orbitals

Building upon the efficient implementation of hybrid density functionals (HDFs) for large-scale periodic systems within the framework of numerical atomic orbital bases using the localized resolution of identity (RI) technique, we have developed an algorithm that exploits the space group symmetry in key operation steps of HDF calculations, leading to further improvements in two ways. First, the reduction of $\mathbf{k}$-points in the Brillouin zone can reduce the number of Kohn-Sham equations to be solved. This necessitates the correct implementation of the rotation relation between the density matrices of equivalent $\mathbf{k}$-points within the representation of atomic orbitals. Second, the reduction of the real-space sector can accelerate the construction of the exact-exchange part of the Hamiltonian in real space. We have implemented this algorithm in the ABACUS software interfaced with LibRI, and tested its performance for several types of crystal systems with different symmetries. The expected speed-up is achieved in both aspects: the time of solving the Kohn-Sham equations decreases in proportion with the reduction of $\mathbf{k}$-points, while the construction of the Hamiltonian in real space is sped up by several times, with the degree of acceleration depending on the size and symmetry of the system.

physics.comp-ph↗

arXiv2025

ABACUS: An Electronic Structure Analysis Package for the AI Era

ABACUS (Atomic-orbital Based Ab-initio Computation at USTC) is an open-source software for first-principles electronic structure calculations and molecular dynamics simulations. It mainly features density functional theory (DFT) and molecular dynamics functions and is compatible with both plane-wave basis sets and numerical atomic orbital basis sets. ABACUS serves as a platform that facilitates the integration of various electronic structure methods, such as Kohn-Sham DFT, stochastic DFT, orbital-free DFT, and real-time time-dependent DFT, etc. In addition, with the aid of high-performance computing, ABACUS is designed to perform efficiently and provide massive amounts of first-principles data for generating general-purpose machine learning potentials, such as DPA models. Furthermore, ABACUS serves as an electronic structure platform that interfaces with several AI-assisted algorithms and packages, such as DeePKS-kit, DeePMD, DP-GEN, DeepH, DeePTB, HamGNN, etc.

cond-mat.mtrl-sci↗

arXiv2024

Direct minimization on the complex Stiefel manifold in Kohn-Sham density functional theory for finite and extended systems

Direct minimization method on the complex Stiefel manifold in Kohn-Sham density functional theory is formulated to treat both finite and extended systems in a unified manner. This formulation is well-suited for scenarios where straightforward iterative diagonalization becomes challenging, especially when the Aufbau principle is not applicable. We present the theoretical foundation and numerical implementation of the Riemannian conjugate gradient (RCG) within a localized non-orthogonal basis set. Riemannian Broyden-Fletcher-Goldfarb-Shanno (RBFGS) method is tentatively implemented. Extensive testing compares the performance of the proposed methods and highlights that the quasi-Newton method is more efficient. However, for extended systems, the computational time required grows rapidly with respect to the number of $\mathbf{k}$-points.

physics.comp-ph↗

arXiv2024

Neural Canonical Transformations for Quantum Anharmonic Solids of Lithium

Lithium is a typical quantum solid, characterized by cubic structures at ambient pressure. As the pressure increases, it forms more complex structures and undergoes a metal-to-semiconductor transformation, complicating theoretical and experimental analyses. We employ the neural canonical transformation approach, an \textit{ab initio} variational method based on probabilistic generative models, to investigate the quantum anharmonic effects in lithium solids at finite temperatures. This approach combines a normalizing flow for phonon excited-state wave functions with a probabilistic model for the occupation of energy levels, optimized jointly to minimize the free energy. Our results indicate that quantum anharmonicity lowers the \textit{bcc}-\textit{fcc} transition temperature compared to classical molecular dynamics predictions. At high pressures, the predicted fractional coordinates of lithium atoms in the \textit{cI16} structure show good quantitative agreement with experimental observations. Finally, contrary to previous beliefs, we find that the poor metallic \textit{oC88} structure is stabilized by the potential energy surface obtained via high-accuracy electronic structure calculations, rather than thermal or quantum nuclear effects.

cond-mat.mtrl-sci↗