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Graph neural networks (GNNs) have excelled in predictive modeling for both crystals and molecules, owing to the expressiveness of graph representations. High-entropy alloys (HEAs), however, lack chemical long-range order, limiting the applicability of current graph representations. To overcome this challenge, we propose a representation of HEAs as a collection of local environment (LE) graphs. Based on this representation, we introduce the LESets machine learning model, an accurate, interpretable GNN for HEA property prediction. We demonstrate the accuracy of LESets in modeling the mechanical properties of quaternary HEAs. Through analyses and interpretation, we further extract insights into the modeling and design of HEAs. In a broader sense, LESets extends the potential applicability of GNNs to disordered materials with combinatorial complexity formed by diverse constituents and their flexible configurations.

The discovery of materials that exhibit a metal-insulator transition (MIT) is key to the development of multiple types of novel efficient microelectronic and optoelectronic devices. However, identifying MIT materials is challenging due to a combination of high computational cost of electronic structure calculations needed to understand their mechanism, the mechanisms' complexity, and the labor-intensive experimental validation process. To that end, we use a machine learning classification model to rapidly screen a high-throughput crystal structure database to identify candidate compounds exhibiting thermally-driven MITs. We focus on three candidate oxides, Ca$_2$Fe$_3$O$_8$, CaCo$_2$O$_4$, and CaMn$_2$O$_4$, and identify their MIT mechanism using high-fidelity density functional theory calculations. Then, we provide a probabilistic estimate of which synthesis reactions may lead to their realization. Our approach couples physics-informed machine learning, density functional theory calculations, and machine learning-suggested synthesis to reduce the time to discovery and synthesis of new technologically relevant materials.

The non-relativistic spin-splitting (NRSS) of electronic bands in "altermagnets" has sparked renewed interest in antiferromagnets (AFMs) that have no net magnetization. However, altermagnets with collinear and compensated magnetism are not the only type of NRSS AFMs. In this study, we identify the symmetry conditions and characteristic signatures of a distinct group of NRSS AFMs that go beyond the description of altermagnets. These compounds exhibit a broken spin-degeneracy among the spin-polarized bands at the $\Gamma$ point in the absence of spin-orbit coupling (SOC). We use density functional theory calculations to validate these models in ternary magnetic nitrides, specifically MnXN$_2$ (X = Si, Ge, Sn), and their cation ordered variants. By removing the previous NRSS constraint on $\Gamma$, these compounds may facilitate the generation of spin currents without cancellation arising from the alternating spin polarizations. Our findings expand the scope of NRSS eligible materials., Comment: 7 pages, 3 figures

We develop a percolation model for face centered cubic binary alloys with chemical short-range order (SRO) to account for chemical ordering/clustering that occurs in nominally random solid solutions. We employ a lattice generation scheme that directly utilizes the first nearest neighbor Warren-Cowley SRO parameter to generate the lattice. We quantify the effects of SRO on the first nearest neighbor three-dimensional (3D) site percolation threshold using the large cell Monte Carlo renormalization group method and find that the 3D site percolation threshold is a function of the SRO parameter. We analyze the effects of SRO on the distribution of the total number of distinct clusters in the percolated structures and find that short-ranged clustering promotes the formation of a dominant spanning cluster. Furthermore, we find that the scaling exponents of percolation are independent of SRO. We also examine the effects of SRO on the 2D-3D percolation crossover and find that the thickness of the thin film for percolation crossover is a function of the SRO parameter. We combine these results to develop a percolation crossover model to understand the electrochemical passivation behavior in binary alloys. The percolation crossover model provides a theoretical framework to understand the critical composition of passivating elements for protective oxide formation. With this model, we show that SRO can be used as a processing parameter to improve corrosion resistance., Comment: 9 pages, 7 figures

We use first principles density functional theory calculations to examine the effect of multiple anions on the Peierls distortion in the rutile oxyfluoride TiOF. By using a structure enumeration approach, we obtain the ground state atomic structure for TiOF and identify the driving forces behind the experimentally observed two-dimensional anion ordering along rutile (110) planes. We find that adjacent edge-connected octahedra comprise like atoms with an --O-O/F-F/O-O/F-F-- pattern along the rutile [001] direction. This anion pattern coexists with a Peierls-like distortion leading to the formation of a singlet state between neighboring Ti$^{3+}$ cations. We show that the anion ordering arises from competition between electrostatic interactions, owing to the Ti-F cation-anion pairs, and the tendency of the $d^1$ Ti$^{3+}$ cation to form Ti-Ti dimers, characterized by increased metal-metal bonding. We find that the addition of strong on-site Coulombic interactions to the Ti $d$ manifold suppresses the formation of the singlet state. By increasing the correlation strength, we uncover two first-order phase transitions: first, from a nonmagnetic insulator to a ferromagnetic half-metal, and then second to a ferromagnetic insulator. Last, we show that the electronic configuration of the transition metal cation in rutile oxyfluorides is responsible for the observed anion order, enabling design of ordered heteroanionic materials exhibiting collective phenomena through cation sublattice control., Comment: 7 pages, 6 figures

Recent advances in machine learning (ML) have expedited materials discovery and design. One significant challenge faced in ML for materials is the expansive combinatorial space of potential materials formed by diverse constituents and their flexible configurations. This complexity is particularly evident in molecular mixtures, a frequently explored space for materials such as battery electrolytes. Owing to the complex structures of molecules and the sequence-independent nature of mixtures, conventional ML methods have difficulties in modeling such systems. Here we present MolSets, a specialized ML model for molecular mixtures. Representing individual molecules as graphs and their mixture as a set, MolSets leverages a graph neural network and the deep sets architecture to extract information at the molecule level and aggregate it at the mixture level, thus addressing local complexity while retaining global flexibility. We demonstrate the efficacy of MolSets in predicting the conductivity of lithium battery electrolytes and highlight its benefits in virtual screening of the combinatorial chemical space., Comment: 21 pages, 4 figures, 2+4 tables, working paper

We demonstrate that the absorption of femtosecond x-ray pulses can excite quasi-spherical high-wavevector coherent acoustic phonon wavepackets using an all x-ray pump and probe scattering experiment. The time- and momentum-resolved diffuse scattering signal is consistent with strain pulses induced by the rapid electron cascade dynamics following photoionization at uncorrelated excitation centers. We quantify key parameters of this process, including the localization size of the strain wavepacket and the energy absorption efficiency, which are determined by the photoelectron and Auger electron cascade dynamics, as well as the electron-phonon interaction. In particular, we obtain the localization size of the observed strain wave packet to be 1.5 and 2.5 nm for bulk SrTiO$_3$ and KTaO$_3$ single crystals, even though there are no nanoscale structures or light-intensity patterns that would ordinarily be required to generate acoustic waves of wavelengths much shorter than the penetration depth. Whereas in GaAs and GaP we do not observe a signal above background. The results provide crucial information on x-ray matter interactions, which sheds light on the mechanism of x-ray energy deposition, and the study of high wavevector acoustic phonons and thermal transport at the nanoscale.

Ordered oxygen vacancies (OOVs) in perovskites can exhibit long-range order and may be used to direct materials properties through modifications in electronic structures and broken symmetries. Based on the various vacancy patterns observed in previously known compounds, we explore the ordering principles of OOVs in oxygen-deficient perovskite oxides with $AB\mathrm{O}_{2.5}$ stoichiometry to identify other OOV variants. We performed first-principles calculations to assess the OOV stability on a dataset of 50 OOV structures generated from our bespoke algorithm. The algorithm employs uniform planar vacancy patterns on (111) pseudocubic perovskite layers and the approach proves effective for generating stable OOV patterns with minimal computational loads. We find as expected that the major factors determining the stability of OOV structures include coordination preferences of transition metals and elastic penalties resulting from the assemblies of polyhedra. Cooperative rotational modes of polyhedra within OOV structures reduce elastic instabilities by optimizing the bond valence of $A$- and $B$-cations. This finding explains the observed formation of vacancy channels along low-index crystallographic directions in prototypical OOV phases. The identified ordering principles enable us to devise other stable vacancy patterns with longer periodicity for targeted property design in yet to be synthesized compounds.

From lithium-ion batteries to high-temperature superconductors, oxide materials have been widely used in electronic devices. However, demands of future technologies require materials beyond oxides, as anion chemistries distinct from oxygen can expand the palette of mechanisms and phenomena, to achieve superior functionalities. Examples include nitride-based wide bandgap semiconductors and halide perovskite solar cells, with MAPbBr3 being a representation revolutionizing photovoltaics research. Here, we demonstrate magnetoelectric behaviour in quasi-two-dimensional halides (K,Rb)3Mn2Cl7 through simultaneous thermal control of electric and magnetic polarizations by exploiting a polar-to-antipolar displacive transition. Additionally, our calculations indicate a possible polarization switching path including a strong magnetoelectric coupling, indicating halides can be excellent platforms to design future multiferroic and ferroelectric devices. We expect our findings to broaden the exploration of multiferroics to non-oxide materials and open access to novel mechanisms, beyond conventional electric/magnetic control, for coupling ferroic orders., Comment: 20 pages, 4 figures

MnSiN$_2$ is a transition metal nitride with Mn and Si ions displaying an ordered distribution on the cation sites of a distorted wurtzite-derived structure. The Mn$^{2+}$ ions reside on a 3D diamond-like covalent network with strong superexchange pathways. We simulate its electronic structure and find that the N anions in MnSiN$_2$ act as $\sigma$- and $\pi$-donors, which serve to enhance the N-mediated superexchange, leading to the high N\'{e}el ordering temperature of $T_N$ = 443 K. Polycrystalline samples of MnSiN$_2$ were prepared to reexamine the magnetic structure and resolve previously reported discrepancies. An additional magnetic canting transition is observed at $T_\mathrm{cant}$ = 433 K and the precise canted ground state magnetic structure has been resolved using a combination of DFT calculations and powder neutron diffraction. The calculations favor a $G$-type antiferromagnetic spin order with lowering to $Pc^\prime$. Irreducible representation analysis of the magnetic Bragg peaks supports the lowering of the magnetic symmetry. The computed model includes a 10$^\circ$ rotation of the magnetic spins away from the crystallographic $c$-axis consistent with measured powder neutron diffraction data modeling and a small canting of 0.6$^\circ$., Comment: 9 pages, 6 figures

We present a novel transmon qubit fabrication technique that yields systematic improvements in T$_1$ relaxation times. We fabricate devices using an encapsulation strategy that involves passivating the surface of niobium and thereby preventing the formation of its lossy surface oxide. By maintaining the same superconducting metal and only varying the surface structure, this comparative investigation examining different capping materials, such as tantalum, aluminum, titanium nitride, and gold, and film substrates across different qubit foundries definitively demonstrates the detrimental impact that niobium oxides have on the coherence times of superconducting qubits, compared to native oxides of tantalum, aluminum or titanium nitride. Our surface-encapsulated niobium qubit devices exhibit T$_1$ relaxation times 2 to 5 times longer than baseline niobium qubit devices with native niobium oxides. When capping niobium with tantalum, we obtain median qubit lifetimes above 300 microseconds, with maximum values up to 600 microseconds, that represent the highest lifetimes to date for superconducting qubits prepared on both sapphire and silicon. Our comparative structural and chemical analysis suggests why amorphous niobium oxides may induce higher losses compared to other amorphous oxides. These results are in line with high-accuracy measurements of the niobium oxide loss tangent obtained with ultra-high Q superconducting radiofrequency (SRF) cavities. This new surface encapsulation strategy enables even further reduction of dielectric losses via passivation with ambient-stable materials, while preserving fabrication and scalable manufacturability thanks to the compatibility with silicon processes.

We present electronic structure calculations on layered nickelate oxyfluorides derived from the Ruddlesden-Popper arisotype structure in search of unidentified materials that may host nickelate superconductivity. By performing anion exchange of oxygen with fluorine, we create two heteroanionic La$_2$NiO$_3$F polymorphs and stabilize Ni$^{1+}$ in 4-coordinate and 5-coordinate square planar and square pyramidal geometries, respectively. We further predict chemical reactions with high thermodynamic driving forces to guide their synthesis. These oxyfluorides are weakly correlated antiferromagnetic insulators and their nonmagnetic phases exhibit quasi-2D Fermi surfaces dominated by Ni $d_{x^2-y^2}$ states, which strikingly resemble undoped cuprate superconductors. We discuss how the oxyfluoride anion chemistry promotes Ni-O covalency and single-band character that is more similar to the cuprates than homoanionic infinite-layer nickelates. We use our understanding to propose doping strategies and layered LaSrNiO$_2$F$_2$ and La$_3$Ni$_2$O$_4$F$_3$ nickelate oxyfluorides with tunable electronic and magnetic structures for experimentation., Comment: 8 pages, 4 figures

Molecular color centers, such as $S=1$ Cr($o$-tolyl)$_{4}$, show promise as an adaptable platform for magnetic quantum sensing. Their intrinsically small size, i.e., 1-2 nm, enables them to sense fields at short distances and in various geometries. This feature, in conjunction with tunable optical read-out of spin information, offers the potential for molecular color centers to be a paradigm shifting materials class beyond diamond-NV centers by accessing a distance scale opaque to NVs. This capability could, for example, address ambiguity in the reported magnetic fields arising from two-dimensional magnets by allowing for a single sensing technique to be used over a wider range of distances. Yet, so far, these abilities have only been hypothesized with theoretical validation absent. We show through simulation that Cr($o$-tolyl)$_{4}$ can spatially resolve proximity-exchange versus direct magnetic field effects from monolayer CrI$_{3}$ by quantifying how these interactions impact the excited states of the molecule. At short distances, proximity exchange dominates through molecule-substrate interactions, but at further distances the molecule behaves as a typical magnetic sensor, with magnetostatic effects dominating changes to the energy of the excited state. Our models effectively demonstrate how a molecular color center could be used to measure the magnetic field of a 2D magnet and the role different distance-dependent interactions contribute to the measured field., Comment: 7 pages, 4 figures

Growing materials data and data-driven informatics drastically promote the discovery and design of materials. While there are significant advancements in data-driven models, the quality of data resources is less studied despite its huge impact on model performance. In this work, we focus on data bias arising from uneven coverage of materials families in existing knowledge. Observing different diversities among crystal systems in common materials databases, we propose an information entropy-based metric for measuring this bias. To mitigate the bias, we develop an entropy-targeted active learning (ET-AL) framework, which guides the acquisition of new data to improve the diversity of underrepresented crystal systems. We demonstrate the capability of ET-AL for bias mitigation and the resulting improvement in downstream machine learning models. This approach is broadly applicable to data-driven materials discovery, including autonomous data acquisition and dataset trimming to reduce bias, as well as data-driven informatics in other scientific domains., Comment: 35 pages, 13 figures, under review

Over the past decade, materials that combine broken inversion symmetry with metallic conductivity have gone from a thought experiment to one of the fastest growing research topics. In 2013, the observation of the first uncontested polar transition in a metal, LiOsO$_3$, inspired a surge of theoretical and experimental work on the subject, uncovering a host of materials which combine properties previously thought to be contraindicated [Nat. Mater. \textbf{12}, 1024 (2013)]. As is often the case in a nascent field, the sudden rise in interest has been accompanied by diverse (and sometimes conflicting) terminology. Although ``ferroelectric-like" metals are well-defined in theory, i.e., materials that undergo a symmetry-lowering transition to a polar phase while exhibiting metallic electron transport, real materials find a myriad of ways to push the boundaries of this definition. Here, we review and explore the burgeoning polar metal frontier from the perspectives of theory, simulation, and experiment while introducing a unified taxonomy. The framework allows one to describe, identify, and classify polar metals; we also use it to discuss some of the fundamental tensions between theory and models of reality inherent in the terms ``ferroelectric" and ``metals.'' In addition, we highlight shortcomings of electrostatic doping simulations in modeling different subclasses of polar metals, noting how the assumptions of this approach depart from experiment. We include a survey of known materials that combine polar symmetry with metallic conductivity, classified according to the mechanisms used to harmonize those two orders and their resulting properties. We conclude by describing opportunities for the discovery of novel polar metals by utilizing our taxonomy.

Persistent spin textures (PSTs) in solid-state materials arise from a unidirectional spin-orbit field in momentum space and offer a route to deliver long carrier spin lifetimes sought for future quantum microelectronic devices. Nonetheless, few three-dimensional materials are known to host PSTs owing to crystal symmetry and chemical requirements. There are even fewer examples demonstrated experimentally. Here we report that high-quality persistent spin textures can be obtained in the polar point groups containing an odd number of mirror operations. We use representation theory analysis and electronic structure calculations to formulate general discovery principles to identify PSTs hidden in known complex ternary layered and perovskite structures with large electric polarizations. We then show some of these materials exhibit PSTs without requiring any special crystalline symmetries. This finding removes the limitation imposed by mirror-symmetry protected PSTs that has limited compound discovery. Our general design approach enables the pursuit of persistent spin helices in materials exhibiting the $C_{3v}$ crystal class adopted by many quantum materials exhibiting large Rashba coefficients.

The relaxor ferroelectric transition in Cd$_2$Nb$_2$O$_7$ is thought to be described by the unusual condensation of two $\Gamma$-centered phonon modes, $\Gamma_4^-$ and $\Gamma_5^-$. However, their respective roles have proven to be ambiguous, with disagreement between $\textit{ab initio}$ studies, which favor $\Gamma_4^-$ as the primary mode, and global crystal refinements, which point to $\Gamma_5^-$ instead. Here, we resolve this issue by demonstrating from x-ray pair distribution function measurements that locally, $\Gamma_4^-$ dominates, but globally, $\Gamma_5^-$ dominates. This behavior is consistent with the near degeneracy of the energy surfaces associated with these two distortion modes found in our own $\textit{ab initio}$ simulations. Our first-principles calculations also show that these energy surfaces are almost isotropic, providing an explanation for the numerous structural transitions found in Cd$_2$Nb$_2$O$_7$, as well as its relaxor behavior. Our results point to several candidate descriptions of the local structure, some of which demonstrate two-in/two-out behavior for Nb displacements within a given Nb tetrahedron. Although this suggests the possibility of a charge analog of spin ice in Cd$_2$Nb$_2$O$_7$, our results are more consistent with a Heisenberg-like description for dipolar fluctuations rather than an Ising one. We hope this encourages future experimental investigations of the Nb and Cd dipolar fluctuations, along with their associated mode dynamics., Comment: 9 pages, 6 figures, published in Physical Review Research

Magnetism in topological materials creates phases exhibiting quantized transport phenomena with applications in spintronics and quantum information. The emergence of such phases relies on strong interaction between localized spins and itinerant states comprising the topological bands, and the subsequent formation of an exchange gap. However, this interaction has never been measured in any intrinsic magnetic topological material. Using a multimodal approach, this exchange interaction is measured in MnBi2Te4, the first realized intrinsic magnetic topological insulator. Interrogating nonequilibrium spin dynamics, itinerant bands are found to exhibit a strong exchange coupling to localized Mn spins. Momentum-resolved ultrafast electron scattering and magneto-optic measurements reveal that itinerant spins disorder via electron-phonon scattering at picosecond timescales. Localized Mn spins, probed by resonant X-ray scattering, disorder concurrently with itinerant spins, despite being energetically decoupled from the initial excitation. Modeling the results using atomistic simulations, the exchange coupling between localized and itinerant spins is estimated to be >100 times larger than superexchange interactions. This implies an exchange gap of >25 meV should occur in the topological surface states. By directly quantifying local-itinerant exchange coupling, this work validates the materials-by-design strategy of utilizing localized magnetic order to create and manipulate magnetic topological phases, from static to ultrafast timescales.

When creating training data for machine-learned interatomic potentials (MLIPs), it is common to create initial structures and evolve them using molecular dynamics to sample a larger configuration space. We benchmark two other modalities of evolving structures, contour exploration and dimer-method searches against molecular dynamics for their ability to produce diverse and robust training density functional theory data sets for MLIPs. We also discuss the generation of initial structures which are either from known structures or from random structures in detail to further formalize the structure-sourcing processes in the future. The polymorph-rich zirconium-oxygen composition space is used as a rigorous benchmark system for comparing the performance of MLIPs trained on structures generated from these structural evolution methods. Using Behler-Parrinello neural networks as our machine-learned interatomic potential models, we find that contour exploration and the dimer-method searches are generally superior to molecular dynamics in terms of spatial descriptor diversity and statistical accuracy., Comment: 13 pages, 15 figures, 4 tables

We formulate the maximum driving force (MDF) parameter as a descriptor to capture the thermodynamic stability of aqueous surface scale creation over a range of environmental conditions. We use formation free energies, $\Delta_f G$s, sourced from high-throughput density functional theory (DFT) calculations and experimental databases to compute the maximum driving force for a wide variety of materials, including simple oxides, intermetallics, and alloys of varying compositions. We show how to use the MDF to describe trends in aqueous corrosion of nickel thin films determined from experimental linear-sweep-voltometry data. We also show how to account for subsurface oxidation behavior using depth-dependent effective chemical potentials. We anticipate this approach will increase overall understanding of oxide formation on chemically complex multielement alloys, where competing oxide phases can form during transient aqueous corrosion., Comment: 7 pages, 3 figures

We use an x-ray free-electron laser to study the ultrafast lattice dynamics following above band-gap photoexcitation of the incipient ferroelectric potassium-tantalate, \kto. % We use ultrafast near-UV (central wavelength 266\,nm and 50 fs pulse duration) laser light to photoexcite charge carriers across the gap and probe the ultrafast lattice dynamics by recording the x-ray diffuse intensity throughout multiple Brillouin zones using pulses from the Linac Coherent Light Source (LCLS) (central wavelength 1.3\,\AA\, and $< 10$~fs pulse duration). We observe changes in the diffuse intensity that we conclude are associated with a hardening of the soft transverse optical and transverse acoustic phonon branches along $\Gamma$ to $X$ and $\Gamma$ to $M$. Using ground- and excited-state interatomic force constants from density functional theory (DFT) and assuming the phonon populations can be described by a time-dependent temperature, we fit the quasi-equilibrium thermal diffuse intensity to the experimental time-dependent intensity. We obtain the instantaneous lattice temperature and density of photoexcited charge carriers as a function of time delay. The DFT calculations demonstrate that photoexcitation transfers charge from oxygen $2p$ derived $\pi$-bonding orbitals to Ta $5d$ derived antibonding orbitals, further suppressing the ferroelectric instability and increasing the stability of the cubic, paraelectric structure., Comment: 8 pages, 4 figures

Infrared laser systems are vital for applications in spectroscopy, communications, and biomedical devices, where infrared nonlinear optical (NLO) crystals are required for broadband frequency down-conversion. Such crystals need to have high non-resonant NLO coefficients, a large bandgap, low absorption coefficient, phase-matchability among other competing demands, e.g., a larger bandgap leads to smaller NLO coefficients. Here, we report the successful growth of single crystals of $\gamma$-NaAsSe$_2$ that exhibit a giant second harmonic generation (SHG) susceptibility of d$_{11}$=590 pm V$^{-1}$ at 2$\mu$m wavelength; this is ~ eighteen times larger than that of commercial AgGaSe$_2$ while retaining a similar bandgap of ~1.87eV, making it an outstanding candidate for quasi-phase-matched devices utilizing d$_{11}$. In addition, $\gamma$-NaAsSe$_2$ is both Type I and Type II phase-matchable, and has a transparency range up to 16$\mu$m wavelength. Thus $\gamma$-NaAsSe2 is a promising bulk NLO crystal for infrared laser applications., Comment: Main text: 21 pages, 4 figures

We study the consequences of the approximately trigonal ($D_{3d}$) point symmetry of the transition metal (M) site in two-dimensional van der Waals MX$_2$ dihalides and MX$_3$ trihalides. The trigonal symmetry leads to a 2-2-1 orbital splitting of the transition metal $d$ shell, which may be tuned by the interlayer distance, and changes in the ligand-ligand bond lengths. Orbital order coupled to various lower symmetry lattice modes may lift the remaining orbital degeneracies, and we explain how these may support unique electronic states using ZrI$_2$ and CuCl$_2$ as examples, and offer a brief overview of possible electronic configurations in this class of materials. By building and analysing Wannier models adapted to the appropriate symmetry we examine how the interplay among trigonal symmetry, electronic correlation effects, and $p$-$d$ orbital charge transfer leads to insulating, orbitally polarized magnetic and/or orbital-selective Mott states. Our work establishes a rigorous framework to understand, control, and tune the electronic states in low-dimensional correlated halides. Our analysis shows that trigonal symmetry and its breaking is a key feature of the 2D halides that needs to be accounted for in search of novel electronic states in materials ranging from CrI$_3$ to $\alpha$-RuCl$_3$.

Higgs and Goldstone modes, well known in high energy physics, have been realized in a number of condensed matter physics contexts, including superconductivity and magnetism. The Goldstone-Higgs concept is also applicable to and gives rise to new insights on structural phase transitions. Here, we show that the Leggett mode, a collective mode observed in multi-band superconductors, also has an analog in crystallographic phase transitions. Such structural Leggett modes can occur in the phase channel as in the original work of Leggett, \href{https://doi.org/10.1143/PTP.36.901}{Prog.\ Theor.\ Phys.\ \textbf{36}, 901 (1966)}. That is, they are antiphase Goldstone modes (anti-phasons). In addition, a new collective mode can also occur in the amplitude channel, an out-of phase (antiphase) Higgs mode, that should be observable in multi-band superconductors as well. We illustrate the existence and properties of these structural Leggett modes using the example of the pyrochlore relaxor ferroelectric, Cd$_2$Nb$_2$O$_7$., Comment: 7 pages, 2 figures

The emergence of magnetism in quantum materials creates a platform to realize spin-based applications in spintronics, magnetic memory, and quantum information science. A key to unlocking new functionalities in these materials is the discovery of tunable coupling between spins and other microscopic degrees of freedom. We present evidence for interlayer magnetophononic coupling in the layered magnetic topological insulator MnBi2Te4. Employing magneto-Raman spectroscopy, we observe anomalies in phonon scattering intensities across magnetic field-driven phase transitions, despite the absence of discernible static structural changes. This behavior is a consequence of a magnetophononic wave-mixing process that allows for the excitation of zone-boundary phonons that are otherwise 'forbidden' by momentum conservation. Our microscopic model based on density functional theory calculations reveals that this phenomenon can be attributed to phonons modulating the interlayer exchange coupling. Moreover, signatures of magnetophononic coupling are also observed in the time domain through the ultrafast excitation and detection of coherent phonons across magnetic transitions. In light of the intimate connection between magnetism and topology in MnBi2Te4, the magnetophononic coupling represents an important step towards coherent on-demand manipulation of magnetic topological phases.

We introduce a method of exploring potential energy contours in complex dynamical systems based on potentiostatic kinematics wherein the systems are evolved with minimal changes to their potential energy. We construct a simple iterative algorithm for performing potentiostatic kinematics, which uses an estimate curvature to predict new configurations space coordinates on the potential energy contour and a potentiostat term component to correct for errors in prediction. Our methods are then applied to atomic structure models using an interatomic potential for energy and force evaluations as would commonly be invoked in a molecular dynamics simulation. Using several model systems, we assess the stability and accuracy of the method on different hyperparameters in the implementation of the potentiostatic kinematics. Our implementation is open source and available within the Atomic Simulation Environment (ASE) package for atomic simulation., Comment: 8 pages, 7 figures

Band topology of anomalous quantum Hall insulators can be precisely addressed by computing Chern numbers of constituent non-degenerate bands that describe quantized, Abelian Berry flux through two-dimensional Brillouin zone. Can Chern numbers be defined for $SU(2)$ Berry connection of two-fold degenerate bands of materials preserving space-inversion ($\mathcal{P}$) and time-reversal ($\mathcal{T}$) symmetries or combined $\mathcal{PT}$ symmetry, without detailed knowledge of underlying basis? We affirmatively answer this question by employing a non-Abelian generalization of Stokes' theorem and describe a manifestly gauge-invariant method for computing magnitudes of quantized $SU(2)$ Berry flux (spin-Chern number) from eigenvalues of Wilson loops. The power of this method is elucidated by performing $\mathbb{N}$-classification of \emph{ab initio} band structures of three-dimensional, Dirac materials. Our work outlines a unified framework for addressing first-order and higher-order topology of insulators and semimetals, without relying on detailed symmetry data., Comment: 17 pages, 11 figures; substantial revision of computational aspects; new data on ab initio band structure of Dirac materials

Materials property predictions have improved from advances in machine learning algorithms, delivering materials discoveries and novel insights through data-driven models of structure-property relationships. Nearly all available models rely on featurization of materials composition, however, whether the exclusive use of structural knowledge in such models has the capacity to make comparable predictions remains unknown. Here we employ a deep neural network model to decode structure-property relationships in crystalline materials without explicitly considering chemical compositions. The focus is on classification of crystal systems, mechanical elasticity, electronic band gap, and phase stability. Our model utilizes a three-dimensional (3D) momentum space representation of structure from elastic x-ray scattering theory that exhibits rotation and permutation invariance. We perform novel ablation studies to help interpret the model performance by perturbing the physically meaningful input features (i.e., the diffraction patterns) instead of tuning the architecture of the learning model as in conventional ablation methods. We find that the spatial symmetry of the 3D diffraction patterns, which reflects crystalline symmetry operations, is more important than the diffraction intensities contained within for the model to make a successful classification. Our work showcases the potential of using statistical learning models to help understand materials physics, rather than performing predictive and generative tasks as in most materials informatics research. We also argue that learning the crystal structure genome in a chemistry-agnostic manner demonstrates that some crystal structures inherently host high propensities for optimal materials properties, which enables the decoupling of structure and composition for future codesign of multifunctionality., Comment: 14 pages, 6 Figures

Usually the quantum spin Hall states are expected to possess gapless, helical edge modes. Are there clean, non-interacting, quantum spin Hall states without gapless, edge modes? We show the generic, $n$-fold-symmetric, momentum planes of three-dimensional, stable Dirac semi-metals, which are orthogonal to the direction of nodal separation are examples of such generalized quantum spin Hall systems. We demonstrate that the planes lying between two Dirac points and the celebrated Bernevig-Zhang-Hughes model support identical quantized, non-Abelian Berry flux of magnitude $2 \pi$. Consequently, both systems exhibit spin-charge separation in response to electromagnetic, $\pi$-flux vortex. The Dirac points are identified as the unit-strength, monopoles of $SO(5)$ Berry connection, describing topological quantum phase transitions between generalized, quantum spin Hall and trivial insulators. Our work identifies precise bulk invariant and quantized response of Dirac semimetals and shows that many two-dimensional higher-order topological insulators can be understood as generalized quantum spin Hall systems, possessing gapped edge states., Comment: 5 pages, 3 figures; concise presentation of bulk invariant and new results on spin-charge separation in higher-order topological insulators and Dirac semimetals

Anionic ordering is a promising route to engineer physical properties in functional heteroanionic materials. A central challenge in the study of anion-ordered compounds lies in developing robust synthetic strategies to control anion occupation and in understanding the resultant implications for electronic structure. Here, we show that epitaxial strain induces preferential occupation of F and O on the anion sites in perovskite oxyfluoride SrMnO2.5-dFg films grown on different substrates. Under compressive strain, F tends to take the apical-like sites, which was revealed by F and O K-edge linearly polarized x-ray absorption spectroscopy and density functional theory calculations, resulting in an enhanced c-axis expansion. Under tensile strain, F tends to take the equatorial-like sites, enabling the longer Mn-F bonds to lie within the plane. The anion ordered oxyfluoride films exhibit a significant orbital polarization of the 3d electrons, distinct F-site dependence to their valence band density of states, and an enhanced resistivity when F occupies the apical-like anion site compared to the equatorial-like site. By demonstrating a general strategy for inducing anion-site order in oxyfluoride perovskites, this work lays the foundation for future materials design and synthesis efforts that leverage this greater degree of atomic control to realize new polar or quasi-two-dimensional materials.

TaAs and NbAs are two of the earliest identified Weyl semimetals that possess many intriguing optical properties, such as chirality-dependent optical excitations and giant second harmonic generation (SHG). Linear and nonlinear optics have been employed as tools to probe the Weyl physics in these crystals. Here we extend these studies to address two important points: determining the complete anisotropic dielectric response, and to explore if and how they can reveal essential Weyl physics. For the first time, we determine the complete anisotropic dielectric functions of TaAs and NbAs by combining spectroscopic ellipsometry and density functional theory (DFT). Parameterized Lorentz oscillators are reported from 1.2-6 eV (experiment) and 0-6 eV (DFT), and good agreement is shown between them. Both linear and nonlinear optical properties have been reported to reveal Weyl physics. We suggest that strong optical resonances from trivial bands are the likely origin of the large optical second harmonic generation previously reported at these energies. Furthermore, by comparing the contribution of a small k-space centered around the Weyl cones to the total linear dielectric function, we find that these contributions are highly anisotropic and are <25% of the total dielectric function below 0.5 eV; above 1eV, these contributions are negligible. Thus, the study of Weyl physics using optical techniques requires very low energies and even there, a careful assessment is required in distinguishing the much smaller contributions of the Weyl bands from the dominant contributions of the trivial bands and Drude response to the total dielectric function., Comment: 42 pages, 13 figures for the main text

Metal-insulator transition (MIT) compounds are materials that may exhibit insulating or metallic behavior, depending on the physical conditions, and are of immense fundamental interest owing to their potential applications in emerging microelectronics. There is a dearth of thermally-driven MIT materials, however, which makes delineating these compounds from those that are exclusively insulating or metallic challenging. Here we report a material database comprising temperature-controlled MITs (and metals and insulators with similar chemical composition and stoichiometries to the MIT compounds) from high quality experimental literature, built through a combination of materials-domain knowledge and natural language processing. We featurize the dataset using compositional, structural, and energetic descriptors, including two MIT relevant energy scales, an estimated Hubbard interaction and the charge transfer energy, as well as the structure-bond-stress metric referred to as the global-instability index (GII). We then perform supervised classification, constructing three electronic-state classifiers: metal vs non-metal (M), insulator vs non-insulator (I), and MIT vs non-MIT (T). We identify two important descriptors that separate metals, insulators, and MIT materials in a 2D feature space: the average deviation of the covalent radius and the range of the Mendeleev number. We further elaborate on other important features (GII and Ewald energy), and examine how they affect classification of binary vanadium and titanium oxides. We discuss the relationship of these atomic features to the physical interactions underlying MITs in the rare-earth nickelate family. Last, we implement an online version of the classifiers, enabling quick probabilistic class predictions by uploading a crystallographic structure file.

We report a pressure-induced phase transition in the frustrated kagom\'e material jarosite at ~45 GPa, which leads to the disappearance of magnetic order. Using a suite of experimental techniques, we characterize the structural, electronic, and magnetic changes in jarosite through this phase transition. Synchrotron powder X-ray diffraction and Fourier transform infrared spectroscopy experiments, analyzed in aggregate with the results from density functional theory calculations, indicate that the material changes from a R-3m structure to a structure with a R-3c space group. The resulting phase features a rare twisted kagom\'e lattice in which the integrity of the equilateral Fe3+ triangles persists. Based on symmetry arguments we hypothesize that the resulting structural changes alter the magnetic interactions to favor a possible quantum paramagnetic phase at high pressure., Comment: Manuscript and Supplement included

Spin splitting of energy bands can be induced by relativistic spin-orbit interactions in materials without inversion symmetry. Whereas polar space group symmetries permit Rashba (R-1) spin splitting with helical spin textures in momentum space, which could be reversed upon switching a ferroelectric polarization via applied electric fields, the ordinary Dresselhaus effect (D-1A) is ac-tive only in materials exhibiting nonpolar noncentrosymmetric crystal classes with atoms occupy-ing exclusively non-polar lattice sites. Consequently, the spin-momentum locking induced by D-1A is not electric field-switchable. An alternative type of Dresselhaus symmetry, referred to as D-1B, exhibits crystal class constraints similar to D-1A (all dipoles add up to zero), but unlike D-1A, at least one polar site is occupied. We find that this behavior exists in a class of ferri-chiral crys-tals, which in principle could be reversed upon a change in chirality. Focusing on alkali metal chalcogenides, we identify NaCu5S3 in the nonentiamorphic ferri-chiral structure, which exhibits CuS3 chiral units differing in the magnitude of their Cu displacements. We then synthesize NaCu5S3 (space group P6322) and confirm its ferri-chiral structure with power x-ray diffraction. Our electronic structure calculations demonstrate it exhibits D-1B spin splitting as well as a ferri-chiral phase transition, revealing spin splitting interdependent on chirality. Our electronic struc-ture calculations show that a few percent biaxial tensile strain can reduce (or nearly quench) the switching barrier separating the monodomain ferri-chiral P6322 states. We discuss what type of external stimuli might switch the chirality so as to reverse the (non-helical) Dresselhaus D-1B spin texture, offering an alternative to the traditional reversal of the (helical) Rashba spin texture., Comment: 27 pages, 12 figures

There are few known semiconductors exhibiting both strong optical response and large dielectric polarizability. Inorganic materials with large dielectric polarizability tend to be wide-band gap complex oxides. Semiconductors with strong photoresponse to visible and infrared light tend to be weakly polarizable. Interesting exceptions to these trends are halide perovskites and phase-change chalcogenides. Here we introduce complex chalcogenides in the Ba-Zr-S system in perovskite and Ruddlesden-Popper structures as a new family of highly polarizable semiconductors. We report the results of impedance spectroscopy on single crystals that establish BaZrS3 and Ba3Zr2S7 as semiconductors with low-frequency relative dielectric constant (${\epsilon}_0$) in the range 50 - 100, and band gap in the range 1.3 - 1.8 eV. Our electronic structure calculations indicate the enhanced dielectric response in perovskite BaZrS3 versus Ruddlesden-Popper Ba3Zr2S7 is primarily due to enhanced IR mode-effective charges, and variations in phonon frequencies along $\langle 001 \rangle$; differences in the Born effective charges and the lattice stiffness are of secondary importance. This combination of covalent bonding in crystal structures more common to complex oxides results in a sizable Fr\"ohlich coupling constant, which suggests that charge carriers are large polarons., Comment: 22 pages, 5 figures

Electronic materials exhibiting phase transitions between metastable states (e.g., metal-insulator transition materials with abrupt electrical resistivity transformations) are challenging to decode. For these materials, conventional machine learning methods display limited predictive capability due to data scarcity and the absence of features impeding model training. In this article, we demonstrate a discovery strategy based on multi-objective Bayesian optimization to directly circumvent these bottlenecks by utilizing latent variable Gaussian processes combined with high-fidelity electronic structure calculations for validation in the chalcogenide lacunar spinel family. We directly and simultaneously learn phase stability and band gap tunability from chemical composition alone to efficiently discover all superior compositions on the design Pareto front. Previously unidentified electronic transitions also emerge from our featureless adaptive optimization engine. Our methodology readily generalizes to optimization of multiple properties, enabling co-design of complex multifunctional materials, especially where prior data is sparse.

The antiferromagnetic Ruddlesden-Popper ruthenate Ca$_3$Ru$_2$O$_7$ is a model polar metal, combining inversion symmetry breaking with metallic conductivity; however, its low temperature ($T < 48$ K) crystal structure and Fermi surface topology remain ambiguous despite numerous measurements and theoretical studies. Here we perform both first principles calculations with static correlations and angle resolved photoelectron spectroscopy experiments to construct a complete model of Ca$_3$Ru$_2$O$_7$, reconciling inconsistencies among interpretations of electrical transport, thermopower measurements, and momentum- and energy-resolved band dispersions. The solution relies on treating the interplay among Coulomb repulsion, magnetic ordering, spin-orbit interactions, and the RuO$_6$ octahedral degrees-of-freedom on equal footing. For temperatures $30

We perform systematic density functional theory (DFT) calculations to assess the performance of various exchange-correlation potentials $V_{xc}$ in describing the chalcogenide GaM$_4$Q$_8$ lacunar spinels (M=Mo, V, Nb, Ta; Q=S, Se). We examine the dependency of crystal structure (in cubic and rhombohedral symmetries), electronic structure, magnetism, optical conductivity, and lattice dynamics in lacunar spinels at four different levels of $V_{xc}$: the local density approximation (LDA), generalized gradient approximation (GGA), meta-GGA, and hybrid with fractional Fock exchange. We find that LDA significantly underperforms GGA and higher level functionals in predicting lattice constants. LDA also fails to properly describe the magnetism in the family, and for some compositions it does not find the ground state distorted crystal structure. The Perdew-Burke-Ernzerhof (PBE) and PBE revised for solids (PBEsol) GGA functionals perform reasonably well in predicting lattice constants as well as the electronic structures. We find that the GGA with an on-site Coulomb interaction (GGA$+U$) is unnecessary to produce a semiconducting state in the distorted polar $R3m$ phase. Plus Hubbard $U$ values ranging from 1$\sim$2 eV, however, improve the quantitative performance of the GGA functionals. The meta-GGA functional SCAN predicts reasonable lattice constants and electronic structures; it exhibits behavior similar to the GGA$+U$ functionals for small $U$ values. The hybrid functional HSE06 is accurate in predicting the lattice constants, but leads to a band gap of $\approx$1 eV in the rhombohedral phase, which is higher than the experimental estimation of 0.2 eV. Our findings suggest that accurate qualitative and quantitative simulations of the lacunar spinel family with DFT requires careful attention to the nuances of the exchange-correlation functional and considered spin structures., Comment: 16 Pages, 13 Figures, 5 Tables

We showcase the potential of symbolic regression as an analytic method for use in materials research. First, we briefly describe the current state-of-the-art method, genetic programming-based symbolic regression (GPSR), and recent advances in symbolic regression techniques. Next, we discuss industrial applications of symbolic regression and its potential applications in materials science. We then present two GPSR use-cases: formulating a transformation kinetics law and showing the learning scheme discovers the well-known Johnson-Mehl-Avrami-Kolmogorov (JMAK) form, and learning the Landau free energy functional form for the displacive tilt transition in perovskite LaNiO$_3$. Finally, we propose that symbolic regression techniques should be considered by materials scientists as an alternative to other machine-learning-based regression models for learning from data., Comment: 14 pages, 6 figures