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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$_3$.