The checkerboard lattice has been proposed to host topological flat bands as a result of destructive interference among its various electronic hopping terms. However, it has proven challenging to realize experimentally due to the difficulty of isolating this structure from any significant out-of-plane bonding while maintaining structural integrity. Here, single crystals of ${\mathrm{Zr}}_2{\mathrm{CuSb}}_3$, a potential candidate for the checkerboard lattice, were synthesized using the solution (self-flux) method, and their structure was confirmed via x-ray diffraction. Electrical-transport measurements indicate metallic behavior with electron-dominated carriers. Angle-resolved photoemission spectroscopy reveals multiple electron pockets and significant $k_z$ broadening due to its large $c$ axis and low dispersion features in $k_z$. Density-functional theory (DFT) calculations further disentangle the contributions from each high-symmetry plane, providing a comprehensive characterization of electronic behavior. The DFT calculations were then used to determine the orbital contributions of the bands and detect the out-of-plane bonding which prevented the flat bands from forming.

Lanthanide fission products can strongly interact with candidate cladding alloys, but their transport properties in refractory metals remain poorly understood. In this work, we investigate the atomic-scale diffusion behavior of La, Ce, Pr, and Nd in body-centered cubic (bcc) molybdenum, a potential candidate for advanced nuclear cladding. Self-consistent mean-field transport modeling is performed to evaluate the fission product transport and vacancy mobility, informed by first-principles and nudged elastic band calculations of vacancy formation energies, migration barriers, and solute-vacancy binding characteristics. Compared with bcc Fe, lanthanide solutes in bcc Mo exhibit slower tracer diffusion due to higher vacancy formation and migration energies. Furthermore, the calculations reveal that the influence of fission products on migration barriers in bcc Mo are not as extensive in range compared to bcc Fe. Among the studied lanthanides, La exhibits the strongest vacancy binding while also being the fastest diffuser in Mo. These findings highlight how refractory bcc alloys can reduce fission product infiltration, offering valuable insight into the development of durable cladding systems for advanced reactors.

Recent advances in low-dimensional materials have revealed that one-dimensional (1D) monatomic chains serve as ideal platforms for exploring exotic quantum phases and emergent phenomena arising from spatial confinement. The synthesis of such structures within well-defined and stable templates represents a key step toward harnessing their unique physical properties. In this study, we utilize the naturally formed, spatially confined channels between self-assembled silicon nanoribbons (SiNRs) on a Si(111) surface as an ideal template for growing highly ordered potassium (K) monatomic chains. Using scanning tunneling microscopy and density functional theory (DFT) calculations, we systematically characterize the confined potassium (K) atoms by high aspect ratio SiNRs and the resulting electronic properties. Our results show that the unique confined space created by the SiNRs reduces the adsorption energy of K atoms by 0.09 eV. This reduction leads to preferential adsorption of K atoms between strands of double- and multistranded SiNRs, where they form a distinct triangular morphology with three neighboring Si atoms. This triangular structure is a result of charge transfer, as confirmed by our DFT calculations. At higher coverage, the K atoms self-assemble into 1D zigzag chain structures along the SiNRs. Notably, the adsorption of K atoms is reversible and can be precisely controlled by a scanning tunneling microscopy tip voltage pulse without causing damage to the SiNRs. Furthermore, the adsorption of K dynamically shifts the position of the Dirac cone relative to the Fermi level, offering an effective means of electronic tuning. This work not only elucidates the formation of artificial 1D K chains within the confined space of SiNRs, but also opens up avenues for the synthesis of atomically precise nanostructures through the use of special confined spaces.

Exciton mobility in two-dimensional semiconductors is a key ingredient in materials-based design of optoelectronic functionalities. Monolayer transition metal dichalcogenides (TMDs) set a good test case, with tightly bound excitons and designable flexibility that offer an ideal platform for realizing strain effects on exciton energy transfer. Here, we present an ab initio study to construct strain-induced exciton energy profiles and model exciton dynamics on top of these potential surfaces. We focus on spatially inhomogeneous strain in monolayer ${\mathrm{WS}}_2$, combining excitonic band structures derived from many-body perturbation theory for a large variety of strain profiles and calculate the change in mobility characteristics using a semiclassical ballistic transport model. We connect a wealth of strain patterns to exciton drift, diffusion, and confinement. Our findings point to strain-induced regimes of superballistic propagation and anomalous diffusion behavior, governed entirely by the strain landscape. Our results provide structure-specific understanding of ballistic strain-tunable exciton behavior, offering design principles for engineering exciton dynamics in two-dimensional materials.

Inorganic antiperovskite nitrides have recently emerged as promising materials for photovoltaic applications, yet their nonradiative recombination dynamics remain largely unexplored. Here, we examine the influence of X-site cation substitution on the nonradiative electron-hole recombination in ${\mathrm{X}}_3\mathrm{NSb}$ $(\mathrm{X}=\mathrm{Ca}, \mathrm{Sr}, \text{and} \mathrm{Ba})$. Ca- and Sr-based compounds adopt a cubic phase, whereas Ba stabilizes in a hexagonal structure, introducing pronounced symmetry-driven effects. To separate symmetry effects from cation chemistry, we also examine the hexagonal polymorph of ${\mathrm{Sr}}_3\mathrm{NSb}$ $\left({\mathrm{Sr}}_3{\mathrm{NSb}}_{\mathrm{hexa}}\right)$. Substituting Ca with Sr narrows the band gap, suppresses octahedral and band-edge fluctuations, reduces nonadiabatic (NA) coupling by $\sim 54\%$, and extends carrier lifetimes by a factor of 2.5. In ${\mathrm{Sr}}_3{\mathrm{NSb}}_{\mathrm{hexa}}$, the combination of larger band gap and enhanced band gap fluctuations—leading to faster dephasing—further slows down recombination by $41\%$. In contrast, in ${\mathrm{Ba}}_3{\mathrm{NSb}}_{\mathrm{hexa}}$, enhanced NA coupling accelerates recombination relative to ${\mathrm{Sr}}_3{\mathrm{NSb}}_{\mathrm{hexa}}$. Overall, recombination lifetimes are dictated by the interplay between band gap, NA coupling strength, and decoherence time, with ${\mathrm{Sr}}_3{\mathrm{NSb}}_{\mathrm{hexa}}$ exhibiting the longest lifetime. These findings highlight the coupled influence of cation chemistry and crystal symmetry in tailoring carrier dynamics for high-performance antiperovskite-based optoelectronics materials.

The Rashba-Edelstein effect (REE), which generates spin accumulation under an applied electric current, quantifies charge-to-spin conversion (CSC) efficiency in noncentrosymmetric systems. However, systematic investigations of REE in two-dimensional (2D) materials remain scarce. To address this gap, we perform a comprehensive symmetry analysis based on the 80 crystallographic layer groups, elucidating the relationship between materials' symmetries and the geometric characteristics of the REE response tensor. Our analysis identifies 13 distinct symmetry classes for the tensor and reveals all potential material candidates. Considering the requirement of strong spin-orbit coupling for a large REE response, we screen the C2DB database and identify 54 promising 2D materials. First-principles calculations demonstrate that the largest REE response coefficients in these materials exceed those reported for other 2D systems by an order of magnitude, indicating exceptionally high CSC efficiency. Focusing on three representative materials, including ${\mathrm{HgI}}_2, {\mathrm{AgTlP}}_2{\mathrm{Se}}_6$, and BrGaTe, we show that their large response coefficients can be well explained by effective $\mathit{k}·\mathit{p}$ models and the characteristic spin textures around high-symmetry points in momentum space. This work provides a systematic framework and identifies high-performance candidates, paving the way for future exploration of REE-driven CSC in 2D materials.

Recently, the real triple point characterized by Euler class in multigap systems, has been proposed beyond the conventional topological phase classifications. Here, we apply the subgroup lattice to study Euler topology and establish an explicit mapping between various undiscovered nodal line configurations (NLCs) evolving from the nontrivial real triple point and specific symmetry-breaking ways. Considering all symmetry-breaking paths from the magnetic point group $m$−$3m1$′ to −1′ with preserved $PT$ symmetry where $P$ and $T$ are inversion and time-reversal symmetries, respectively, 13 types of topological admissible NLCs are identified, with each subgroup exhibiting a one-to-one or one-to-two correspondence to them, which indicates an accurate design for a target nodal structure. In addition, through the analysis on the interplay between point-group symmetry and underlying non-Abelian topology, we promote an understanding on the formation mechanism of NLCs. Based on first-principles calculations, we verify the NLC evolutions in ten candidate phononic materials such as ${\mathrm{RbCaH}}_3$ and CuCl driven by external strain. The provided strain tensors to reach each corresponding subgroup can be a symmetry guidance for experimentally designing nodal line semimetals via strain engineering. Furthermore, we show that the optical conductivity purely induced by the quantum metric can serve as a nontrivial signature of distinct NLCs, and also can be manipulated along symmetry breaking. Our findings reveal the generality of realizing nodal structures characterized by the Euler class from a group-theoretical perspective that are applicable to real triple point materials in other systems.

Ferroelectric materials have attracted significant attention due to their excellent piezoelectric, pyroelectric, and ferroelectric properties. In applications where ferroelectric ceramics are subjected to coupled shock pressure-self-generated electric field environments, their phase structures critically determine device performance and application scope. However, studies on ferroelectric phase transitions under pressure-electric field coupling remain limited, and the lack of phase diagrams under field conditions hinders the development and application of ferroelectrics in complex environments. In this work, we investigate the discharge behavior of $\mathrm{KNb}{\mathrm{O}}_3$ ceramics under coupled shock pressure and self-generated electric field conditions, and reveal the competition between polar and nonpolar phases. By analyzing the relationship between shock-induced electrical responses and phase transitions, the phase evolution under pressure-electric coupling field is clarified. Combined with first-principles density functional theory calculations, a phase diagram of ${\mathrm{KNbO}}_3$ undercoupled pressure and electric fields is constructed. These findings provide crucial insights into phase transition mechanisms under coupled fields and offer valuable guidance for the design and optimization of ferroelectric materials and devices.

The dielectric response of amorphous organic solids at the timescale of atomic motion has broad implications for their photophysics, governing spectroscopic properties and excited-state relaxation, among other phenomena. We present an original approach to the calculation of the vibrational contribution to the frequency-dependent dielectric permittivity. Our methodology, combining molecular dynamics simulations, density functional theory calculations, and linear response theory, is applied to a set of amorphous carbazole-based small-molecule matrices, widely used as host materials in organic light-emitting diodes. Our analysis reveals the crucial role of hindered molecular rotations (librations) in the solid-state matrices of dipolar compounds. These modes manifest in the very-low frequency ($<100{\mathrm{cm}}^{-1}$) region of the dielectric function, accounting for up to one-third of the total vibrational contribution to the static dielectric constant in a dipolar compound like 3,3'-di(carbazol-9-yl)-5-cyano-1,1'-biphenyl. This low-frequency contribution is found to be crucial for determining the variations in the static dielectric constant across various materials.

Graph neural networks have demonstrated notable advantages in modeling structured data for material property prediction. Nevertheless, their deployment in predicting the creep life of nickel-based single-crystal superalloys presents key challenges, as current models often fail to effectively capture the intricate nonlinear and synergistic interactions among multiple alloying elements. To address this, this paper proposes a Deep Learning-based Graph Attention Network v2(DL-GATv2) prediction framework that integrates physical metallurgy knowledge with an enhanced graph neural network. The model constructs an element graph structure and introduces the GATv2 dynamic attention mechanism to accurately capture the dependencies between elements. Simultaneously, it incorporates multidimensional physical metallurgy knowledge, including microstructure, electronic structure, and thermodynamics, to achieve multiscale modeling of the creep behavior of nickel-based single-crystal superalloys. Experimental results show that the model achieves a prediction accuracy of R² = 0.8218, with errors reduced by 24.7% to 38.0%, significantly outperforming existing methods. Ablation experiments and sensitivity analyses confirm the model's effectiveness and stability under complex operating conditions. More importantly, the weight distribution of element aggregation successfully reveals the key strengthening elements and their synergistic mechanisms across different generations of alloys, enabling a physically interpretable prediction of material behavior. This framework overcomes the limitations of traditional black-box models, providing an alternative paradigm for the composition optimization and performance regulation of high-temperature alloys, with both high prediction accuracy and physical interpretability.

We present a comprehensive study of the electronic transport properties and first-principles calculations of ${\mathrm{Ni}}_3{\mathrm{Bi}}_2{\mathrm{Se}}_2$, a parkerite-structured compound, revealing its topological nodal-line semimetal behavior. Shubnikov-de Haas oscillations confirm the presence of Dirac-like fermions, supported by a nontrivial $\pi$-Berry phase, low effective mass ($m^{*}\sim 0.18m_e$), and a high Fermi velocity ($v_{\mathrm{F}}\sim 2.93\times {10}^5{\mathrm{ms}}^{-1}$). Weak-field magnetoconductivity exhibits a characteristic $-\ln$($B$) dependence, indicative of nodal-line features. The longitudinal resistivity fits well with the Bloch-Gruneisen-Mott model, pointing to multiple scattering mechanisms, including electron-phonon and Mott-interband. Hall effect and Boltzmann transport theory analyses suggest coexistence of electron and hole carriers. Density-functional theory calculations show a bulk band inversion between Ni-$d$ and Bi-$p$ orbitals without spin-orbit coupling, and the surface states merge into the bulk around 0.43 eV, further supporting the topologically nontrivial nature of ${\mathrm{Ni}}_3{\mathrm{Bi}}_2{\mathrm{Se}}_2$.

Epitaxially grown multilayers, ${\mathrm{Mn}}_3\mathrm{PtN}/\mathrm{Cu}/{\mathrm{Co}}_{20}{\mathrm{Fe}}_{60}{\mathrm{B}}_{20}$, with a thickness of the Cu spacer layers from 0 to 5 nm, were prepared on (100)-oriented MgO substrates. The multilayer exhibited a pronounced exchange bias field in the absence of a Cu spacer, which became minimal with the introduction of a finite Cu spacer. We measured spin-torque ferromagnetic resonance to estimate the spin-Hall angle (${\theta }_{\mathrm{SH}}$) in the multilayers, emphasizing the role of the Cu spacer layer in the spin current transport across the interface. We found that both ${\theta }_{\mathrm{SH}}$ and the effective Gilbert damping parameter decrease significantly upon the insertion of Cu, suggesting that the spin-orbit torque (SOT) primarily originates from interfaces. A correlation between SOT and exchange bias with the Cu spacer layer indicates the significance of interfacial contributions. These experimental results demonstrate the critical importance of interfacial engineering in antiferromagnetic-based spintronics, revealing an alternative mechanism for generating spin torque in magnetic heterostructures that is essential for controlling magnetization dynamics in energy-efficient spintronics applications.

The ferroelectric phase ($Pca{2}_1$, which is in orthorhombic symmetry) of hafnium dioxide $\left({\mathrm{HfO}}_2\right)$ has gained much attention due to its potential applications in nanoelectronics and advanced memory devices. However, its complex phase behavior under external stimuli, such as pressure and temperature, remains a subject of intense investigation. This study focuses on developing a machine learning-based interatomic potential (MLIP) that is trained with data from density-functional theory (DFT) calculations to simulate phase transitions and mechanical properties of ${\mathrm{HfO}}_2$. The developed MLIP predicts lattice parameters, equations of state, bulk and shear moduli, and elastic constants that closely align with DFT predictions for several phases and at various pressures. Once validated, the MLIP is used to investigate the phase transitions of ferroelectric ${\mathrm{HfO}}_2$ $\left(Pca{2}_1\right)$ under both isobaric and constant stress conditions at elevated temperatures ranging from 200 to 2500 K. We used several complementary methods, including local symmetry identification, radial distribution function, and x-ray diffraction characterization, to identify interesting phase transitions among several competitive hafnia phases predicted from our simulations. The suggested methods uniformly reveal that under pure deviatoric condition, the system favors a transition from the orthorhombic $Pca{2}_1$ phase to a tetragonal ($P{4}_2/nmc$) phase, whereas a zero stress condition drives the system from the $Pca{2}_1$ phase to another orthorhombic $\left(Pbcn\right)$ phase. These findings provide crucial insights into stress and temperature-induced phase behavior of hafnia, guiding future experimental and theoretical studies for optimizing hafnia-based ferroelectric devices.

Flexible polymer transistors are key components in emerging sensor technologies, such as electronic skin for next-generation biomedical prosthetics, and their charge transport mechanisms differ fundamentally from those of conventional inorganic semiconductors. In this work we report the fabrication of an ambipolar polymer field-effect transistor capable of transporting both electrons and holes. The devices are synthesized using a nanoelectrochemical cyclic voltammetry method, which enables the formation of HCl-doped polyaniline nanofibers. These nanofibers introduce Gaussian-distributed tail states within the energy gap, thereby facilitating ambipolar transport. Electrical characterization is carried out through $I_{\mathrm{D}}\text{−}{V}_{\mathrm{D}}$ and $I_{\mathrm{D}}\text{−}{V}_{\mathrm{G}}$ measurements as well as temperature-dependent resistivity and mobility studies from 300 K down to 24 K. Analysis of the temperature-dependent mobilities using the multiple trapping and release and the variable-range hopping (VRH) models reveals that electron transport is predominantly governed by VRH, while hole transport shows weaker agreement with either model. Three device types with different carrier densities provide a useful platform for controlling carrier populations and for investigating dual-carrier transport across distinct temperature regimes. The results demonstrate that the nanofiber morphology, combined with hopping transport, enhances electron-electron interactions and broadens the energy gap through Gaussian tail states. This broadened tail-state band enables efficient ambipolar transport, yielding a high field-effect mobility of approximately $4\mathrm{c}{\mathrm{m}}^2{\mathrm{V}}^{-1}{\mathrm{s}}^{-1}$, representing a significant advancement in conducting polymer transistors.

The electronic density of states (DOS) is key to understanding material behavior, but is computationally expensive to calculate via density functional theory (DFT), especially for complex systems. We propose a self-consistent encoder-decoder neural network that learns bidirectional mappings between local atomic environments and projected DOS (pDOS), trained via dual-loss optimization to enforce physical consistency. Applied to equiatomic HfNbTiZr high-entropy alloys, the model achieves root-mean-square errors of 2.55 meV for the $d$-band center and 0.02 states/(eV atom) for Fermi-level DOS, surpassing direct structure-level predictions. The approach generalizes well to ${\mathrm{SrTiO}}_3$ and vacancy-ordered perovskites, demonstrating broad applicability. By enabling accurate DOS prediction, multi-objective optimization, and potential inverse design, this framework offers a robust pathway for data-driven electronic structure modeling in complex materials.