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Complex materials, characterized by geometrical or electronic complexities, catalyze the emergence of various intriguing functionalities. At the atomic level, these materials typically feature intricate and competing bond orders associated with d-orbitals, providing a rich test bed for assessing the capabilities of density functional theory (DFT). The Strongly Constrained and Appropriately Normed (SCAN) functional has been shown to outperform traditional density functionals in modeling a diverse range of chemical bonds, marking a significant advancement in DFT. Here, we investigate the effectiveness of SCAN in simulating the electronic properties of displacive ferroelectrics, magnetoelectric multiferroics, and cuprate high-temperature superconductors, which encompass a broad spectrum of bonding characteristics. We demonstrate how SCAN addresses challenging simulations involving (1) anisotropic bonding with geometrical symmetry breaking, (2) bonding hybridization of localized open d-shells, and (3) variable electronic states on the boundary of localization-insulator to itinerant-metal transitions. We also show how the advanced functional captures the complex bonds by analyzing the intricate electron densities, offering an intuitive understanding of SCAN's operational principles. Our insights have practical implications for the computational materials science community, potentially guiding the broader adoption of SCAN in modeling complex functional materials.

Accurate approximation of the exchange-correlation (XC) energy in density functional theory (DFT) calculations is essential for reliably modelling electronic systems. Many such approximations are developed from models of the XC hole; accurate reference XC holes for real electronic systems are crucial for evaluating the accuracy of these models however the availability of reliable reference data is limited to a few systems. In this study, we employ the Lieb optimization with a coupled cluster singles and doubles (CCSD) reference to construct accurate coupling-constant averaged XC holes, resolved into individual exchange and correlation components, for five spherically symmetric atoms: He, Li, Be, N, and Ne. Alongside providing a new set of reference data for the construction and evaluation of model XC holes, we compare our data against the exchange and correlation hole models of the established LDA and PBE density functional approximations. Our analysis confirms the established rationalization for the limitations of LDA and the improvement observed with PBE in terms of the hole depth and its long-range decay, demonstrated in real-space for the series of spherically-symmetric atoms.

The efficacy of large language models (LLMs) is heavily dependent on the quality of the underlying data, particularly within specialized domains. A common challenge when fine-tuning LLMs for domain-specific applications is the potential degradation of the model's generalization capabilities. To address these issues, we propose a two-stage approach for the construction of production prompts designed to yield high-quality data. This method involves the generation of a diverse array of prompts that encompass a broad spectrum of tasks and exhibit a rich variety of expressions. Furthermore, we introduce a cost-effective, multi-dimensional quality assessment framework to ensure the integrity of the generated labeling data. Utilizing a dataset comprised of service provider and customer interactions from the real estate sector, we demonstrate a positive correlation between data quality and model performance. Notably, our findings indicate that the domain-specific proficiency of general LLMs can be enhanced through fine-tuning with data produced via our proposed method, without compromising their overall generalization abilities, even when exclusively domain-specific data is employed for fine-tuning.

In the field of chemical structure recognition, the task of converting molecular images into machine-readable data formats such as SMILES string stands as a significant challenge, primarily due to the varied drawing styles and conventions prevalent in chemical literature. To bridge this gap, we proposed MolNexTR, a novel image-to-graph deep learning model that collaborates to fuse the strengths of ConvNext, a powerful Convolutional Neural Network variant, and Vision-TRansformer. This integration facilitates a more detailed extraction of both local and global features from molecular images. MolNexTR can predict atoms and bonds simultaneously and understand their layout rules. It also excels at flexibly integrating symbolic chemistry principles to discern chirality and decipher abbreviated structures. We further incorporate a series of advanced algorithms, including an improved data augmentation module, an image contamination module, and a post-processing module for getting the final SMILES output. These modules cooperate to enhance the model's robustness to diverse styles of molecular images found in real literature. In our test sets, MolNexTR has demonstrated superior performance, achieving an accuracy rate of 81-97%, marking a significant advancement in the domain of molecular structure recognition.

The widely-used Kohn-Sham implementation of density functional theory (DFT) maps a system of interacting electrons onto an auxiliary non-interacting one and is presumably inaccurate for strongly correlated materials. We present a concrete benchmark for DFT by examining the electronic ground state phase diagram of a strongly interacting chain with uneven, non-integer nuclear charges. The interplay between charge imbalance and Coulomb repulsion yields two competing phases, a band insulator and a Mott insulator. By including infinitesimal lattice distortions, DFT stabilizes the intermediate spontaneously dimerized insulator phase that results from this competition. We assess the phase diagram by mapping the bond length and nuclear charge ratio of the chain to the ionic Hubbard model and performing highly accurate density matrix renormalization group calculations. Our comparative study provides foundational insight into the utility of symmetry-broken DFT as a predictive tool for elucidating phase diagrams with competing orders.

Flat bands coupled with magnetism and topological orders near or at the Fermi level are well known to drive exotic correlation physics and unconventional superconductivity. Here, based on first-principles modeling combined with an in-depth symmetry analysis, we reveal the presence of topological flat bands involving low-energy Ni-$3d_{z^2}$ states in the recently discovered superconductor LaNiO$_{2}$. Our analysis demonstrates that LaNiO$_2$ is an Axion insulator with $\mathbb{Z}_{4} = 2$ and that it supports topological crystalline insulating states protected by the glide mirror symmetries. The topological flat bands in LaNiO$_{2}$ are also shown to host odd-parity superconductivity. Our study indicates that the nickelates would provide an interesting materials platform for exploring the interplay of flat bands, topological states, and superconductivity., Comment: 8, 3 figures, 1 table

The enigmatic mechanism underlying unconventional high-temperature superconductivity, especially the role of lattice dynamics, has remained a subject of debate. Theoretical insights have long been hindered due to the lack of an accurate first-principles description of the lattice dynamics of cuprates. Recently, using the r2SCAN meta-GGA functional, we were able to achieve accurate phonon spectra of an insulating cuprate YBa$_2$Cu$_3$O$_6$, and discover significant magnetoelastic coupling in experimentally interesting Cu-O bond stretching optical modes [Ning et al., Phys. Rev. B 107, 045126 (2023)]. We extend this work by comparing PBE and r2SCAN performances with corrections from the on-site Hubbard U and the D4 van der Waals (vdW) methods, aiming at further understanding on both the materials science side and the density functional side. We demonstrate the importance of vdW and self-interaction corrections for accurate first-principles YBa2 Cu3 O6 lattice dynamics. Since r2SCAN by itself partially accounts for these effects, the good performance of r2SCAN is now more fully explained. In addition, the performances of the Tao-Mo series of meta-GGAs, which are constructed in a different way from SCAN/r2SCAN, are also compared and discussed., Comment: arXiv admin note: text overlap with arXiv:2210.06569

VO2 is renowned for its electric transition from an insulating monoclinic (M1) phase characterized by V-V dimerized structures, to a metallic rutile (R) phase above 340 Kelvin. This transition is accompanied by a magnetic change: the M1 phase exhibits a non-magnetic spin-singlet state, while the R phase exhibits a state with local magnetic moments. Simultaneous simulation of the structural, electric, and magnetic properties of this compound is of fundamental importance, but the M1 phase alone has posed a significant challenge to density functional theory (DFT). In this study, we show none of the commonly used DFT functionals, including those combined with on-site Hubbard U to better treat 3d electrons, can accurately predict the V-V dimer length. The spin-restricted method tends to overestimate the strength of the V-V bonds, resulting in a small V-V bond length. Conversely, the spin-symmetry-breaking method exhibits the opposite trends. Each bond-calculation method underscores one of the two contentious mechanisms, i.e., Peierls or Mott, involved in the metal-insulator transition in VO2. To elucidate the challenges encountered in DFT, we also employ an effective Hamiltonian that integrates one-dimensional magnetic sites, thereby revealing the inherent difficulties linked with the DFT computations., Comment: 14 pages, 6 figures

The recent development of the accurate and efficient semilocal density functionals on the third rung of Jacob's ladder of density functional theory such as the revised regularized strongly constrained and appropriately normed (r2SCAN) density functional could enable the rapid and highly reliable prediction of the elasticity and temperature dependence of thermophysical parameters of refractory elements and their intermetallic compounds using quasi-harmonic approximation (QHA). Here, we present a comparative evaluation of the equilibrium cell volumes, cohesive energy, mechanical moduli, and thermophysical properties (Debye temperature and thermal expansion coefficient) for 22 transition metals using semilocal density functionals, including local density approximation (LDA), the Perdew-Burke-Ernzerhof (PBE) and PBEsol generalized gradient approximations (GGA), and the r2SCAN meta-GGA. PBEsol and r2SCAN deliver the same level of accuracies for structural, mechanical and thermophysical properties. Otherwise, PBE and r2SCAN perform better than LDA and PBEsol for calculating cohesive energies of transition metals. Among the tested density functionals, r2SCAN provides an overall well-balanced performance for reliably computing the cell volumes, cohesive energies, mechanical properties, and thermophysical properties of various 3d, 4d, and 5d transition metals using QHA. Therefore, we recommend that r2SCAN could be employed as a workhorse method to evaluate the thermophysical properties of transition metal compounds and alloys in the high throughput workflows.

Evidence is growing that a second dome of high-$T_\mathrm{c}$ superconductivity can be accessed in the cuprates by increasing the doping beyond the first dome. Here we use \emph{ab initio} methods without invoking any free parameters, such as the Hubbard $U$, to reveal that pressure could turn YBa$_2$Cu$_3$O$_7$ into an ideal candidate for second-dome-superconductivity, displaying the predicted signature of strongly hybridized $d_{x^2-y^2}$ and $d_{z^2}$ orbitals. Notably, pressure is found to induce a phase transition replacing the antiferromagnetic phases with an orbitally-degenerate $d$--$d$ phase. Our study suggests that the origin of the second dome is correlated with the oxygen-hole fraction in the CuO$_2$ planes and the collapse of the pseudogap phase., Comment: 7 pages, 4 figures

We report thermal conductivity and Seebeck effect measurements on Mn(Bi1-xSbx)2Te4 (MBST) with x = 0.26 under applied magnetic fields below 50 K. Our data shows clear indications of the electronic structure transition induced by the antiferromagnetic (AFM) to ferromagnetic (FM) transition driven by applied magnetic field as well as significant positive magnetothermal conductivity in the Weyl semimetal state of MBST. Further, by examining the dependence of magnetothermal conductivity on field orientation for MBST and comparison with the magnetothermal conductivity of MnBi2Te4 we see evidence of a contribution to thermal conductivity due to Weyl fermions in the FM phase of MBST. From the temperature dependence of Seebeck coefficient under magnetic fields for MBST, we also observed features consistent with the Fermi surface evolution from a hole pocket in the paramagnetic state to a Fermi surface with coexistence of electron and hole pockets in the FM state. These findings provide further evidence for the field-driven topological phase transition from an AFM topological insulator to a FM Weyl semimetal., Comment: 10 pages, 3 figures

In density functional theory the exchange-correlation (XC) energy functional can be defined exactly through the coupling-constant ($\lambda$) averaged XC hole $\bar{n}_\text{xc}(\mathbf{r},\mathbf{r}')$, representing the probability depletion of finding an electron at $\mathbf{r}$ due to an electron at $\mathbf{r}$. Accurate knowledge of $\bar{n}_\text{xc}(\mathbf{r},\mathbf{r}')$ has been crucial for developing various XC energy density functional approximations and understanding their performance for real molecules and materials. However, there are very few systems for which accurate XC holes have been calculated, since this requires evaluating the one- and two-particle reduced density matrices for a reference wave function over a range of $\lambda$ whilst the electron density remains fixed at the physical ($\lambda=1$) density. Although the coupled-cluster singles and doubles (CCSD) method can yield exact results for a two-electron system in the complete basis set limit, it cannot capture the electron-electron cusp with commonly used finite basis sets. In this study, focusing on the Hooke's atom as a two-electron model system for which certain analytic solutions are known, we examine the effect of this cusp error on the XC hole calculated using CCSD. The Lieb functional is calculated at a range of coupling constants to determine the $\lambda$-integrated XC hole. Our results indicate that, for the Hooke's atoms, the error introduced by the description of the electron-electron cusp using Gaussian basis sets at the CCSD level is negligible compared to the basis set incompleteness error. The system-, angle- and coupling-constant-averaged XC hole is calculated using the same approach and provides a benchmark against which the Perdew-Burke-Ernzerhof (PBE) and local density approximation (LDA) XC hole models are assessed., Comment: 16 pages, 7 figures

Multi-center transition metal complexes (MCTMs) with magnetically interacting ions have been proposed as components for information processing devices and storage units. For any practical application of MCTMs as magnetic units, it is crucial to characterize their magnetic behavior, and in particular the isotropic magnetic exchange coupling, J, between its magnetic centers. Due to the large size of typical MCTMs, density functional theory (DFT) is the only practical electronic structure method for evaluating the J coupling. Here we assess the accuracy of different density functional approximations for predicting the magnetic couplings of seven di-metal transition metal complexes with known reliable experimental J couplings spanning from ferromagnetic to strong antiferromagnetic. The density functionals considered include global hybrid functionals which mix semilocal density functional approximations and exact exchange with a fixed admixing parameter, six local hybrid functionals where the admixing parameters are extended to be spatially dependent, the SCAN and r$^2$SCAN meta-generalized gradient approximations (GGAs), and two widely used GGAs. We found that global hybrids have a tendency to over-correct the error in magnetic coupling parameters from the Perdew-Burke-Ernzerhof (PBE) GGA, while the performance of local hybrid density functionals is scattered without a clear trend, suggesting that more efforts are needed for the extension from global to local hybrid density functionals for this particular property. The SCAN and r$^2$SCAN meta-GGAs are found to perform as well or better than the global and local hybrids on most tested complexes. We further analyze the charge density redistribution of meta-GGAs as well as global and local hybrid density functionals with respect to that of PBE, in connection to the self-interaction error (SIE) or delocalization error.

Understanding many-electron phenomena with competing near-degenerate electronic states is of fundamental importance to chemistry and condensed matter physics. One of the most significant challenges for exploring such many-electron phenomena is the necessity for large system sizes in order to realize competing states, far beyond those practical for first-principles methods. Here, we show how allowing non-integer nuclear charges expands the space of computationally tractable electron systems that host competing electronic states. The emergence of competing electronic states from non-integer nuclear charges is exemplified in the simple 2-electron H_{2} molecule and used to examine the microscopic structure of doped quasi-1D cuprate chains, showing how non-integer nuclear charges can open a window for first-principles calculations of difficult many-electron phenomena., Comment: 20 pages, 3 figures

Recent advances in two-dimensional (2D) magnetism have heightened interest in layered magnetic materials due to their potential for spintronics. In particular, layered semiconducting antiferromagnets exhibit intriguing low-dimensional semiconducting behavior with both charge and spin as carrier controls. However, synthesis of these compounds is challenging and remains rare. Here, we conducted firstprinciples based high-throughput search to screen potentially stable mixed metal phosphorous trichalcogenides (MM'P2X6, where M and M' are transition metals and X is a chalcogenide) that have a wide range of tunable bandgaps and interesting magnetic properties. Among the potential candidates, we successfully synthesized a stable semiconducting layered magnetic material, CdFeP2Se6, that exhibits a short-range antiferromagnetic order at TN = 21 K with an indirect band gap of 2.23 eV. Our work suggests that highthroughput screening assisted synthesis be an effective method for layered magnetic materials discovery., Comment: 14 pages, 3 figures

The role of lattice dynamics in unconventional high-temperature superconductivity is still vigorously debated. Theoretical insights into this problem have long been prevented by the absence of an accurate first-principles description of the combined electronic, magnetic, and lattice degrees of freedom. Utilizing the recently constructed r$^2$SCAN density functional that stabilizes the antiferromagnetic (AFM) state of the pristine oxide YBa$_2$Cu$_3$O$_6$, we faithfully reproduce the experimental dispersion of key phonon modes. We further find significant magnetoelastic coupling in numerous high energy Cu-O bond stretching optical branches, where the AFM results improve over the soft non-magnetic phonon bands.

The recently discovered infinite-layer nickelates show great promise in helping to disentangle the various cooperative mechanisms responsible for high-temperature superconductivity. However, lack of antiferromagnetic order in the pristine nickelates presents a challenge for connecting the physics of the cuprates and nickelates. Here, by using a quantum many-body Green's function-based approach to treat the electronic and magnetic structures, we unveil the presence of many two- and three-dimensional magnetic stripe instabilities that are shown to persist across the phase diagram of LaNiO$_2$. Our analysis indicates that the magnetic properties of the infinite-layer nickelates are closer to those of the doped cuprates which host inhomogeneous ground states rather than the undoped cuprates. The computed magnon spectrum in LaNiO$_2$ is found to contain an admixture of contributions from localized and itinerant carriers. The theoretically obtained magnon dispersion is in accord with the results of the corresponding RIXS experiments. Our study gives insight into the origin of inhomogeneity in the infinite-layer nickelates and their relationship with the cuprates., Comment: 11 pages, 4 figures

A central aim of materials discovery is an accurate and numerically reliable description of thermodynamic properties, such as the enthalpies of formation and decomposition. The r$^2$SCAN revision of the strongly constrained and appropriately normed (SCAN) meta-generalized gradient approximation (meta-GGA) balances numerical stability with high general accuracy. To assess the r$^2$SCAN description of solid-state thermodynamics, we evaluate the formation and decomposition enthalpies, equilibrium volumes, and fundamental bandgaps of more than 1,000 solids using r$^2$SCAN, SCAN, and PBE, as well as two dispersion-corrected variants, SCAN+rVV10 and r$^2$SCAN+rVV10. We show that r$^2$SCAN achieves accuracy comparable to SCAN and often improves upon SCAN's already excellent accuracy. Whereas SCAN+rVV10 is often observed to worsen the formation enthalpies of SCAN, and makes no substantial correction to SCAN's cell volume predictions, r$^2$SCAN+rVV10 predicts marginally less-accurate formation enthalpies than r$^2$SCAN, and slightly more-accurate cell volumes than r$^2$SCAN. The average absolute errors in predicted formation enthalpies are found to decrease by a factor of 1.5 to 2.5 from the GGA level to the meta-GGA level. Smaller decreases in error are observed for decomposition enthalpies. For formation enthalpies r$^2$SCAN improves over SCAN for intermetallic systems. For a few classes of systems -- transition metals, intermetallics, weakly-bound solids, and enthalpies of decomposition into compounds -- GGAs are comparable to meta-GGAs. In total, r$^2$SCAN and r$^2$SCAN+rVV10 can be recommended as stable, general-purpose meta-GGAs for materials discovery.

Understanding similarities and differences between the cuprate and nickelate superconductors is drawing intense current interest. Competing charge orders have been observed recently in the $undoped$ infinite-layer nickelates in sharp contrast to the $undoped$ cuprates which exhibit robust antiferromagnetic insulating ground states. The microscopic mechanisms driving these differences remain unclear. Here, using in-depth first-principles and many-body theory based modeling, we show that the parent compound of the nickelate family, LaNiO$_2$, hosts a charge density wave (CDW) ground state with the predicted wavevectors in accord with the corresponding experimental findings. The CDW ground state is shown to be connected to a multi-orbital Peierls distortion. Our study points to the key role of electron-phonon coupling effects in the infinite-layer nickelates., Comment: 8 pages, 4 figures

Lieb and Oxford (1981) derived rigorous lower bounds, in the form of local functionals of the electron density, on the indirect part of the Coulomb repulsion energy. The greatest lower bound for a given electron number N depends monotonically upon N, and the N-> infinity limit is a bound for all N. These bounds have been shown to apply to the exact density functionals for the exchange- and exchange-correlation energies that must be approximated for an accurate and computationally efficient description of atoms, molecules, and solids. A tight bound on the exact exchange energy has been derived therefrom for two-electron ground states, and is conjectured to apply to all spin-unpolarized electronic ground states. Some of these and other exact constraints have been used to construct two generations of non-empirical density functionals beyond the local density approximation: the Perdew-Burke-Ernzerhof (PBE) generalized gradient approximation (GGA), and the strongly constrained and appropriately normed (SCAN) meta-GGA., Comment: 16 pages

Weyl electrons are intensely studied due to novel charge transport phenomena such as chiral anomaly, Fermi arcs, and photogalvanic effect. Recent theoretical works suggest that Weyl electrons can also participate in magnetic interactions, and the Weyl-mediated indirect exchange coupling between local moments is proposed as a new mechanism of spiral magnetism that involves chiral electrons. Despite reports of incommensurate and non-collinear magnetic ordering in Weyl semimetals, an actual spiral order has remained hitherto undetected. Here, we present evidence of Weyl-mediated spiral magnetism in SmAlSi from neutron diffraction, transport, and thermodynamic data. We show that the spiral order in SmAlSi results from the nesting between topologically non-trivial Fermi pockets and weak magnetocrystalline anisotropy, unlike related materials (Ce,Pr,Nd)AlSi, where a strong anisotropy prevents the spins from freely rotating. We map the magnetic phase diagram of SmAlSi and reveal an A-phase where topological magnetic excitations may exist. This is corroborated by the observation of a topological Hall effect within the A-phase., Comment: 7 pages, 4 figures

Machine learning techniques have received growing attention as an alternative strategy for developing general-purpose density functional approximations, augmenting the historically successful approach of human designed functionals derived to obey mathematical constraints known for the exact exchange-correlation functional. More recently efforts have been made to reconcile the two techniques, integrating machine learning and exact-constraint satisfaction. We continue this integrated approach, designing a deep neural network that exploits the exact constraint and appropriate norm philosophy to deorbitalize the strongly constrained and appropriately normed SCAN functional. The deep neural network is trained to replicate the SCAN functional from only electron density and local derivative information, avoiding use of the orbital dependent kinetic energy density. The performance and transferability of the machine learned functional are demonstrated for molecular and periodic systems.

SCAN+rVV10 has been demonstrated to be a versatile van der Waals (vdW) density functional that delivers good predictions of both energetic and structural properties for many types of bonding. Recently, the r$^{2}$SCAN functional has been devised as a revised form of SCAN with improved numerical stability. In this work, we refit the rVV10 functional to optimize the r$^{2}$SCAN+rVV10 vdW density functional, and test its performance for molecular interactions and layered materials. Our molecular tests demonstrate that r$^{2}$SCAN+rVV10 outperforms its predecessor SCAN+rVV10 in both efficiency (numerical stability) and accuracy. This good performance is also found in lattice constant predictions. In comparison with benchmark results from higher-level theories or experiments, r$^{2}$SCAN+rVV10 yields excellent interlayer binding energies and phonon dispersions for layered materials.

This paper presents the details of our system designed for the Task 1 of Multimodal Information Based Speech Processing (MISP) Challenge 2021. The purpose of Task 1 is to leverage both audio and video information to improve the environmental robustness of far-field wake word spotting. In the proposed system, firstly, we take advantage of speech enhancement algorithms such as beamforming and weighted prediction error (WPE) to address the multi-microphone conversational audio. Secondly, several data augmentation techniques are applied to simulate a more realistic far-field scenario. For the video information, the provided region of interest (ROI) is used to obtain visual representation. Then the multi-layer CNN is proposed to learn audio and visual representations, and these representations are fed into our two-branch attention-based network which can be employed for fusion, such as transformer and conformed. The focal loss is used to fine-tune the model and improve the performance significantly. Finally, multiple trained models are integrated by casting vote to achieve our final 0.091 score., Comment: Accepted to ICASSP 2022

The SCAN meta-GGA exchange-correlation functional [Phys. Rev. Lett. 115, 036402 (2015)] is constructed as a chemical environment-determined interpolation between two separate energy densities: one describes single orbital electron densities accurately, and another describes slowly-varying densities accurately. To conserve constraints known for the exact exchange-correlation functional, the derivatives of this interpolation vanish in the slowly-varying limit. While theoretically convenient, this choice introduces numerical challenges that degrade the functional's efficiency. We have recently reported a modification to the SCAN functional, termed r$^2$SCAN [J. Phys. Chem. Lett. 11, 8208 (2020)] that introduces two regularizations into SCAN which improve its numerical performance at the expense of not recovering the fourth order term of the slowly-varying density gradient expansion for exchange. Here we show the derivation of a progression of functionals (rSCAN, r++SCAN, r$^2$SCAN, and r$^4$SCAN) with increasing adherence to exact conditions while maintaining a smooth interpolation. The greater smoothness of r$^2$SCAN seems to lead to better general accuracy than the additional exact constraint of SCAN or r$^4$SCAN does.

First principles predictions of lattice dynamics are of vital importance for a broad range of topics in materials science and condensed matter physics. The large-scale nature of lattice dynamics calculations and the desire to design novel materials with distinct properties demands that first principles predictions are accurate, transferable, efficient, and reliable for a wide variety of materials. In this work, we demonstrate that the recently constructed r2SCAN density functional meets this need for general systems by demonstrating phonon dispersions for typical systems with distinct chemical characteristics. The functional's performance opens a door for phonon-mediated materials discovery from first principles calculations.