Papers

The crystal lattice governs the emergent electronic, magnetic, and optical properties of quantum materials, making structural tuning through strain, pressure, or chemical substitution a key approach for discovering and controlling novel quantum phases. Beyond static modifications, driving specific lattice modes with ultrafast stimuli offers a dynamic route for tailoring material properties out of equilibrium. However, achieving dynamic coherent control of the nonequilibrium phases via resonant excitation of lattice coherences remains largely unexplored. Such manipulation enables non-volatile, on demand amplification and suppression of order parameters on femtosecond timescales, necessary for next generation optoelectronic ultrafast computation. In this study, we demonstrate coherent phononic control of a newly discovered, light-induced metastable magnetization in the van der Waals antiferromagnet FePS3. By using a sequence of terahertz (THz) pulses, we modulate the magnetization amplitude at the frequencies of phonon coherences, whose infrared-active nature and symmetries are further revealed by polarization- and field-strength-dependent measurements. Furthermore, our two-dimensional THz spectroscopy, in tandem with first-principles numerical simulations, shows that these phonons nonlinearly displace a Raman active phonon, which induces the metastable net magnetization. These findings not only clarify the microscopic mechanism underlying the metastable state in FePS3 but also establish vibrational coherences in solids as a powerful tool for ultrafast quantum phase control, enabling manipulation of material functionalities far from equilibrium.

A comprehensive analysis is presented for the diffusivity of oxygen defects and oxygen self-diffusion in ThO$-2$. The migration energy and diffusivity of oxygen defects with nominal charges have been investigated using density functional theory and phonon simulations. The pathway for the lowest migration energy barrier of oxygen vacancies was found to be along the $\langle 100 \rangle$ direction. Neutral and non-neutral oxygen interstitials exhibited direct (interstitial) and indirect (interstitialcy) migration, respectively. The vacancy migration barrier was found to be lowest for the highest charge, while for interstitials, it is lowest when the charge is lowest. The attempt frequencies of defects were calculated using the Eyring and Vineyard theories. These frequencies displayed a similar dependence on the defect charge as the activation barriers. The charge-averaged diffusivity of vacancies and interstitials were also computed. Across all temperatures, the average vacancy diffusivity was found to be greater than that of interstitial, indicating that oxygen vacancies are more mobile than interstitials. Oxygen self- and chemical diffusion coefficients were analyzed by combining the defect diffusivities with the concentrations computed using an equilibrium defect thermodynamics. The self-diffusion coefficient of oxygen was found to rise with temperatures and lower oxygen pressures. The contributions of various defects to self-diffusion of oxygen were subsequently examined. In the normal to high oxygen pressure range, at all temperatures, it is found that interstitials contribute most to oxygen diffusion in ThO2. At low oxygen pressures, vacancies with highest charge state were found to dominate oxygen diffusion. The chemical diffusion coefficient of oxygen was further computed, which was found to increase with temperature and decrease with hypo-stoichiometry in ThO2 to a plateau value.

A regular lattice of magnetic skyrmions is the ground state of thin ferromagnetic films with Dzyaloshinskii-Moriya interaction in a relatively wide range of external magnetic fields. It was previously theoretically shown that upon the increase of magnetic field a topological transition in the magnon spectrum of such skyrmion crystal (SkX) may occur. Non-uniform magnetic field may lead to localized magnon states emerging at the interface between two half-planes of SkX. Using semiclassical quantization and the stereographic projection approach, we study such appearing edge states both in a full band structure calculation and in simplified effective model. The latter effective model described by extended Dirac equation is applicable to two relevant magnon bands near $\Gamma$ point. We show that both the chirality of emerging edge states and the degree of its localization at the interface is controlled by magnetic field profile. We demonstrate that the localization length may be as small as a few inter-skyrmion distances.

Rare earth doping is an effective way to convert chemically stable oxides into multifunctional materials with coupled electronic, optical, and magnetic properties. We present first principles calculations of pristine and Tm3+ doped Ca2SnO4 to understand how localized 4f states change the structural, electronic, magnetic, and optical behavior of the host. Pristine Ca2SnO4 is a mechanically stable, wide band gap insulator with mostly ionic covalent bonding and diamagnetic character. Replacing Ca2+ with Tm3+ introduces several key changes: (i) localized Tm 4f states create intermediate levels inside the wide gap, reducing the optical band gap; (ii) exchange and spin orbit interactions generate strong local magnetic moments and spin asymmetry near the conduction band; (iii) electron localization function analysis shows enhanced covalency and electron pockets that stabilize luminescent centers; and (iv) the optical response shows visible range absorption, refractive index features, and low energy plasmon peaks while maintaining high energy dielectric stability. These effects make Tm doped Ca2SnO4 a mechanically robust, optically tunable, and magnetically active oxide phosphor suitable for red emission, intermediate band photovoltaics, and spin photon coupling. More broadly, our results show how targeted rare earth substitution can enable multifunctionality in wide gap stannates and guide the design of next generation spintronic photonic oxides.

We report a three-stage synthesis of a hybrid metal-carbon 2D material, in which cobalt atoms are covalently embedded in the graphene-like carbon (GLC) matrix. The resulting material (CoGLC) exhibits a distinctive XRD pattern indicative of the ordered arrangement of cobalt atoms in the layers. Furthermore, we demonstrate the fabrication of surfactant-free conductive inks from CoGLC via electrochemical exfoliation, making it a promising candidate for applications in in flexible electronics, spintronics or electrocatalysis.

While it is well known that cavitation occurs in liquids under tension, no universally accepted criterion for its onset in transient pressure fields exists. We propose a precise definition of the critical tension for cavitation in transient pressure fields that bridges the gap between quasi-static and dynamic regimes, identifying cavitation as the transition of the bubble radius to a dynamically unstable state. This threshold depends on the instantaneous state of the gas-liquid system and, when combined with an appropriate set of dimensionless parameters, yields a self-similar description of cavitation onset. Phase maps for different liquids reveal a minimum tension required for the onset of cavitation, determined by the duration of the tension event and the initial bubble size, whereby the well-known Blake threshold is the lower bound for cavitation across all conditions.

We investigate the impact of random bond disorder on quantum skyrmions using a spin-half quantum Heisenberg model on the square lattice with Dzyaloshinskii-Moriya interaction, Heisenberg anisotropy, and boundary-pinned magnetic field. Utilizing the neural network quantum state technique, we explore the influence of disorder on spin textures, topological properties, and quantum entanglement. We show that the disorder reduces the stability of quantum skyrmions, ultimately causing them to collapse at high disorder strengths. In addition, our results reveal two key insights. First, the presence of disorder, rather than simply degrading skyrmion order, significantly enhances local quantum entanglement, as evidenced by the rise in second Rényi entropy. Second, our calculations show that the topological entanglement entropy calculated using the second Rényi entropy remains negligible across all the disorder strengths. This suggests long-range entanglement is absent and the skyrmion phase is not detectable using this specific probe. Overall, our work provides new insights into how disorder constructively influences quantum materials.

We propose an extended kinematics of nominally elastic continuum solids allowing one to describe their mechanical interaction with micro-scale loading devices. The main new ingredient is the concept of a micro-displacement tensor which extends the conventional description of the deforming elastic solids in terms of macroscopic displacement vectors. We show that micro-displacement tensors are particularly useful in dealing with active incompatibility acquisition and its subsequent passive relaxation. We use the proposed approach to describe the energetics of surface deposition while accounting for the presence of micro-mechanical controls.To illustrate the effectiveness of the new conceptual scheme we present two case studies: crystallization from a melt resulting in pre-stress, and winding of a coil with controlled pre-stretch.

This paper presents the temperature dependence of the static spin susceptibility at $q = (pi, pi)$ and $q = (pi, 0)$ in a Mott-proximate cuprate model with an antinodal pseudogap – a model system for high-temperature superconducting (HTSC) cuprates. The results show the spin susceptibility onset temperature tracks the critical temperature ($T_c$) of HTSCs with a comparable scale across the electron filling factor. Also, as the electron filling decreases and the chemical potential approaches the antinodal van Hove region, the spin susceptibility at $q=(pi, pi)$ and $(pi, 0)$, corresponding to diagonal and axial particle-hole scattering channels, respectively, grows markedly. It suggests that the emergence of cuprate superconductivity correlates with a suppression of low-energy antinodal spin response and associated particle-hole excitations, which would otherwise dephase $d$-wave pairing, commonly attributed to spin fluctuations. In this context, the pseudogap partially suppresses antinodal spectral weight near $omega = 0$, thereby reducing the low-$omega$ particle-hole phase space.

The non-equilibrium Green's function method combined with density functional theory (NEGF-DFT) provides a rigorous framework for simulating nanoscale electronic transport, but its computational cost scales steeply with system size. Recent artificial intelligence (AI) approaches have sought to accelerate such simulations, yet most rely on conventional machine learning, lack atomic resolution, struggle to extrapolate to larger systems, and cannot predict multiple properties simultaneously. Here we introduce DeepQT, a deep-learning framework that integrates graph neural networks with transformer architectures to enable multi-property predictions of electronic structure and transport without manual feature engineering. By learning key intermediate quantities of NEGF-DFT, the equilibrium Hamiltonian and the non-equilibrium total potential difference, DeepQT reconstructs Hamiltonians under both equilibrium and bias conditions, yielding accurate transport predictions. Leveraging the principle of electronic nearsightedness, DeepQT generalizes from small training systems to much larger ones with high fidelity. Benchmarks on graphene, MoS2, and silicon diodes with varied defects and dopants show that DeepQT achieves first-principles accuracy while reducing computational cost by orders of magnitude. This scalable, transferable framework advances AI-assisted quantum transport, offering a powerful tool for next-generation nanoelectronic device design.

The primary requirement for achieving spin-selective electron transfer in a nanojunction possessing a magnetic system with zero net magnetization is to break the symmetry between the up and down spin sub-Hamiltonians. Circumventing the available approaches, in the present work, we put forward a new mechanism for symmetry breaking by introducing a bias drop along the functional element. To demonstrate this, we consider a clean magnetic chain with antiparallel alignment of neighboring magnetic moments. The junction is modeled within a tight-binding framework, and spin-dependent transmission probabilities are evaluated using wave-guide theory. The corresponding current components are obtained through the Landauer-Büttiker formalism. Selective spin currents, exhibiting a high degree of spin polarization, are obtained over a wide bias region. Moreover, the bias-dependent transmission profile exhibits negative differential resistance (NDR), another important aspect of our study. We examine the results under three different potential profiles, one linear and two non-linear, and in each case, we observe a favorable response. This work may offer a new route for designing efficient spintronic devices based on bias-controlled magnetic systems with vanishing net magnetization.

We theoretically investigate the transient spectral function during the photoinduced melting of charge order in a correlated electron system, to unravel the dynamical processes triggered by different initial excitations. We employ a one-dimensional interacting spinless fermion model introducing a pulsed laser light, and perform a comparative study by the Hartree-Fock approximation and by the exact diagonalization method to numerically solve the time-dependent Schrödinger equation. We find characteristic behavior in the transient spectral function, whose features strongly depend on the pump light frequency $\omega_p$. When $\omega_p$ is resonant with the collective phase mode of frequency $\Omega_c\simeq \Delta_{\rm CO}/2$, where $\Delta_{\rm CO}$ is the charge gap, the transient spectral function exhibits a photoinduced in-gap weight which triggers large responses. With increasing the laser intensity, the development of in-gap weight directly turns into the collapse of the gap. This charge-order destabilization process is in sharp contrast to the case of $\omega_p>\Delta_{\rm CO}$, where the photoirradiation induces interband electron-hole excitations giving rise to a shrinkage of the gap. The impact of quantum fluctuations and spatial inhomogeneity on the photoinduced dynamics is also discussed.

We propose the realization of a spin-2 Floquet spinor Bose-Einstein condensate via Floquet engineering of the quadratic Zeeman energy. In the Floquet system, the coupling strengths of all angular-momentum-conserving spin-flip processes are renormalized by driving-parameter-dependent Bessel functions. Such Floquet-engineered interactions significantly enriches possible ground states in homogeneous gases. The resulting phase diagrams, which map the distributions of these possible ground states, are presented in the space of the driving parameters.

Time-reversal symmetry-breaking (TRSB) superconductivity has been reported in a growing number of materials. In some cases, TRSB arises naturally from chiral superconductivity, but in many low-symmetry systems this explanation is not viable. In these latter cases, TRSB is often attributed to phase frustration among multiple superconducting gaps on different Fermi surfaces. Yet, the microscopic conditions enabling such frustration remain poorly understood. Here, inspired by the TRSB reported in the superconducting state of iron-based materials, we demonstrate that a minimal two-orbital model can support a TRSB superconducting state via phase frustration. We identify the key microscopic parameters that stabilize TRSB in d-electron systems with orthorhombic symmetry and provide a framework to systematically enlarge the region of parameter space within which TRSB is expected in materials with other electronic content and crystalline symmetries. Our results offer a simple and experimentally relevant route to understand and control TRSB in multiorbital superconductors.

Exact characterization of phase transitions requires sufficient configurational sampling, necessitating efficient and accurate potential energy surfaces. Molecular force fields with computational efficiency and physical interpretability are desirable but challenging to refine for complex interactions. To address this, we propose a force field refinement strategy with phase diagrams as top-down optimization targets based on automatic differentiation. Using gas-liquid co-existence as a paradigm, we employ an enhanced sampling technique and design a differentiable loss function to evaluate force fields' depiction of phase diagrams. The refined force fields produce gas-liquid phase diagrams matching well with targets for two modeling systems, which confirms our approach as an effective automated force field development framework for phase transition studies.

The MnBi$_2$Te$_4$ material family has emerged as a key platform for exploring magnetic topological phases, most notably exemplified by the experimental realization of the axion insulator state. While spin dynamics are known to significantly influence the axion state, a profound understanding of their interplay remains elusive. In this work, we employ an antiferromagnetic spin-chain model to demonstrate that an external magnetic field induces extrinsic perpendicular magnetic anisotropy. We find that an in-plane field stabilizes the antiferromagnetic order, whereas an out-of-plane field destabilizes it and triggers spin-flop transitions. Remarkably, near the surface spin-flop transition in even-layer MnBi$_2$Te$_4$ films, the axion insulator state undergoes a sharp switching behavior accompanied by distinct magnetoelectric responses. Furthermore, we propose that this switchable axionic magnetoelectric effect can be utilized to convert alternating magnetic field signals into measurable square-wave magneto-optical outputs, thereby realizing an axionic analog of a zero-crossing detector. Our findings could open a pathway toward potential applications of axion insulators in next-generation spintronic devices.

Multiferroics, which combine ferroelectric and magnetic order, offer a transformative platform for next-generation electronic devices. However, the intrinsic competition between the mechanisms driving ferroelectricity and magnetism in single-phase materials severely limits their performance, typically resulting in weak magnetoelectric coupling at room temperature. Here, we propose a solution to this long-standing challenge through the novel concept of fractional quantum multiferroics (FQMF), where strong magnetoelectric coupling is naturally realized by coupling fractional quantum ferroelectricity (FQFE) with altermagnetism (AM). Symmetry analysis shows that reversing the FQFE polarization necessarily inverts the AM spin splitting under parity-time ($\mathcal{PT}$) or time-reversal ($\mathcal{T}\tau$) operations. A minimal tight-binding model reproduces this effect, demonstrating electrically driven spin control without rotating the Néel vector. First-principles calculations further identify a broad family of candidate materials in two and three dimensions including bulk MnTe, Cr$_2$S$_3$, Mn$_4$Bi$_3$NO$_{15}$ and two-dimensional AB$_2$ bilayers such as MnX$_2$ (X=Cl, Br, I), CoCl$_2$, CoBr$_2$, and FeI$_2$. Notably, MnTe exhibits a high Néel temperature ($\sim$300 K) and a large electrically switchable spin splitting ($\sim$0.8 eV), demonstrating room-temperature magnetoelectric performance that surpasses that of conventional multiferroics. To further showcase the technological potential, we propose an electric-field-controlled FQMF tunnel junction based on MnTe that achieves tunneling magnetoresistance exceeding 300%. This work establishes FQMF as a distinct and promising route to achieving room-temperature strong magnetoelectric coupling, opening a new avenue for voltage-controlled spintronics.

In our previous work [Phys. Rev. E 104, 014124 (2021)], we developed a method for analyzing classical liquids using the functional renormalization group (FRG) without relying on a hard-core reference system. In this paper, we extend this method to three-dimensional liquids. We describe an efficient approach for performing the spatial integrals that appear in the renormalization group equations, which is essential for realizing numerical calculations in three dimensions. As a demonstration, we present its application to the Lennard-Jones liquids. Through calculations of thermodynamic quantities, we find that FRG preserves thermodynamic consistency (TC) better than traditional integral-equation methods such as the hypernetted-chain, Percus-Yevick, and Kovalenko-Hirata closures. Taking the molecular dynamics results as a benchmark, we also show that FRG can achieve an accuracy comparable to that of integral-equation methods that incorporate TC, such as the Rogers-Young closure. We further assess the accuracy of the pair distribution function and examine whether our method remains applicable below the critical temperature. Our results demonstrate that FRG provides a new method for describing classical liquids with accuracy comparable to modern liquid theories.

Multi-principal element alloys (MPEAs) exhibit exceptional properties but face significant challenges in developing accurate machine-learning potentials (MLPs) due to their vast compositional and configurational complexity. Here, we introduce an efficient small-cell sampling (SCS) method, which allows for generating diverse and representative training datasets for MPEAs using only small-cell structures with just one and two elements, thereby bypassing the computational overhead of iterative active learning cycles and large-cell density functional theory calculations. The efficacy of the method is carefully validated through principal component analysis, extrapolation grades evaluation, and root-mean-square errors and physical properties assessment on the TiZrHfCuNi system. Further demonstrations on TiZrVMo, CoCrFeMnNi, and AlTiZrNbHfTa systems accurately reproduce complex phenomena including phase transitions, chemical orderings, and thermodynamic properties. This work establishes an efficient one-shot protocol for constructing high-quality training datasets across multiple elements, laying a solid foundation for developing universal MLPs for MPEAs.

Many efforts have been made to explore systems that show significant deviations from predictions related to the standard statistical mechanics. The present work introduces a unified formalism that connects divergences, generalized free energies, generalized Fokker-Planck equations, and H-theorem. This framework is applied here in a range of scenarios, illustrating both established and novel results. In many cases, the approach begins with a free energy functional that explicitly includes a potential energy term, leading to a direct relation between this energy and the stationary solution. Conversely, when a divergence is used as free energy, the associated Fokker-Planck-like equation lacks any explicit dependence on the potential energy, depending instead on the stationary solution. To restore a potential-based interpretation, an additional relation between the stationary solution and the potential energy must be imposed. This duality underlines the flexibility of the formalism and its capacity to adapt to systems where the potential energy is unknown or unnecessary.

We consider tensor factorizations based on sparse measurements of the components of relatively high rank tensors. The measurements are designed in a way that the underlying graph of interactions is a random graph. The setup will be useful in cases where a substantial amount of data is missing, as in completion of relatively high rank matrices for recommendation systems heavily used in social network services. In order to obtain theoretical insights on the setup, we consider statistical inference of the tensor factorization in a high dimensional limit, which we call as dense limit, where the graphs are large and dense but not fully connected. We build message-passing algorithms and test them in a Bayes optimal teacher-student setting in some specific cases. We also develop a replica theory to examine the performance of statistical inference in the dense limit based on a cumulant expansion. The latter approach allows one to avoid blind usage of Gaussian ansatz which fails in some fully connected systems.

Proposing new ways to organize carbon in 2D nanomaterials has been a relevant strategy in the search for systems with targeted properties for different applications. One focus is the study of fully sp$^2$ non-graphitic networks, with successfully synthesized examples. Hybrid sp-sp$^2$ systems of the graphyne family are a related approach, and many systems have the honeycomb lattice as a base model. However, other examples have been inspired by other lattices as the recently proposed r$\gamma$GY sheet, which features a semiconducting behavior with highly localized quasi-1D states. Here, we investigate how to tune r$\gamma$GY properties by folding this sheet into nanotube forms. We elucidate mechanisms that determine their electronic structure by means of density functional theory calculations, as well as we identify the interplay involving chirality, diameter, and the emergence of dispersive/localized frontier states on gap modulation through simple extrapolated methods.

Rare earth oxide-phosphates (REOPs) form a largely unexplored family of refractory lanthanides and yttrium compounds with general formula RExOy(PO4)z. They are of interest for applications ranging from thermal barrier coatings to catalysts and magnetic materials. At least four REOPs phases were experimentally identified with RE/P ratios from 7:3 to 6:1, however the structures were solved only for 3:1 phases (RE3O3(PO4)). In this work we report the structure for the 7:3 phases (RE7O6(PO4)3) derived by ab initio analysis of models based on previously reported oxide-vanadate analogues. The most stable structures for all 7:3 REOPs were found to be isotypic, adopting monoclinic symmetry with space group P21/c. The structures were validated by comparison of their powder X-ray diffraction patterns to those of synthesized La, Pr, Nd, Sm, Eu, Gd and Tb 7:3 phases (Rietveld refinement for all except Tb). Ab initio analysis of thermodynamic stability showed that all 7:3 REOPs are unstable at 0 K toward decomposition to REPO4 and RE3PO7 or RE2O3. The entropy contribution stabilizes RE7O6(PO4)3 phases for light rare earth elements above 1000 K, however, starting with Dy, computationally predicted stabilization temperature is higher than estimated melting points of RE7O6(PO4)3, which is consistent with observed synthesis pattern.

Semiconductor magic-size clusters (MSCs) are atomically precise nanoparticles exhibiting unique size-dependent properties, but their ultrasmall dimensions hinder structural characterization, limiting our understanding of their formation and stability. A few MSC structures have been fully resolved, revealing either bulk-like zincblende-type structures or a range of non-bulk-like motifs. Here we use a computational model to investigate the relationship between cluster size and atomic structure in zincblende-forming II-VI and III-V semiconductors. Firstly, we find that all non-bulk-like MSCs in these systems exhibit the same distorted icosahedral motif that is intrinsically chiral. Secondly, we reproduce these MSC geometries in small-cluster self-assembly simulations and discover that their chirality emerges from the geometric frustration and symmetry breaking in arranging tetrahedral bonding environments into an icosahedral topology. Overall, this work reproduces experimentally reported motifs without system-specific parameterization, establishes the structural origin of chirality in MSCs, and provides design principles for predicting new cluster geometries.

Surface-induced liquid crystalline phase transitions evoke fundamental interest and can provide deeper insight into the nature of low-dimensional phases. Board-like conjugated polymers are of particular interest because they exhibit novel sanidic liquid crystalline mesophases that have not been widely studied. Furthermore, films of these polymers often exhibit preferential molecular orientation near the free surface, suggesting that the surface influences the ordering process. However, the underlying mechanism of this surface-induced ordering remains unclear. Here, we use surface-sensitive grazing-incidence X-ray scattering to monitor the formation and disappearance of positional order in situ in thin films of two board-like conjugated polymers representative of two classes: polythiophenes and polydiketopyrrolopyrroles. The results show that the free surface induces the formation of a highly oriented, sanidic disordered mesophase at the surface of both conjugated polymers, thus marking the emergence of positional order. This ordering process continues upon cooling and involves multiple transitions into more ordered liquid crystalline mesophases, both at the surface and in the bulk. The positional smectic-like order parameter exhibits continuous temperature dependence near the transition, signifying that the breaking of translational symmetry by the surface occurs continuously. Theoretical analysis allows us to accurately describe the temperature-dependent order parameter when critical behavior is considered.

Quantum thermometry leveraging quantum sensors is investigated with an emphasis on fundamental precision bounds derived from quantum estimation theory. The proposed sensing platform consists of two dissimilar qubits coupled via capacitor, which induce quantum oscillations in the presence of a thermal environment. Thermal equilibrium states are modeled using the Gibbs distribution. The precision limits are assessed through the Quantum Fisher Information (QFI) and the Hilbert-Schmidt Speed (HSS), serving as stringent criteria for sensor sensitivity. Systematic analysis of the dependence of QFI and HSS on tunable parameters -such as qubit energies and coupling strengths- provides optimization pathways for maximizing temperature sensitivity. Furthermore, we explore two distinct quantum thermometry paradigms: (I) local temperature estimation directly performed by Alice, who possesses the quantum sensor interfacing with the thermal bath, and (II) remote temperature estimation conducted by Bob, facilitated via quantum teleportation. In the latter scenario, temperature information encoded in the qubit state is transmitted through a single-qubit quantum thermal teleportation protocol. Our findings indicate that direct measurement yields superior sensitivity compared to remote estimation, primarily due to the inherent advantage of direct sensor-environment interaction. The analysis reveals that increasing Josephson energies diminishes sensor sensitivity, whereas augmenting the mutual coupling strength between the qubits enhances it.

Wetting phenomena are relevant in several technological applications, particularly those involving hydrophobic or hydrophilic surfaces. Many substrates support multiple wetting states depending on surface conditions or droplet history, a behavior known as metastability. This feature is crucial both for its theoretical complexity and for its relevance in practical applications that rely on controlling metastable states. While several experimental and computational techniques have been developed to study metastability, they tend to be complex or computationally expensive. In this work, we introduce an alternative approach based on concepts from active matter physics. We investigate the wetting behavior of a droplet placed on a pillared surface using a 3-state Cellular Potts model with a polarity term that mimics a self-propelled droplet. Applying this model to a pillared substrate with known metastable wetting states, we demonstrate that increasing activity enables the droplet to traverse free energy barriers, explore consecutive metastable states, and eventually suppress metastability entirely. Our results show that activity reduces the disparity between dry and wet states and provides a reliable framework for identifying and quantifying metastability through contact angle measurements.

Generation of photocurrent via photon drag effect enables very fast light detection with response time limited by momentum relaxation. At the same time, photon drag in bulk uniform samples is small by the virtue of small photon momentum. We show that the edge of metal gate placed above a two-dimensional electron system (2DES) provides highly non-uniform electromagnetic field that enhances the drag effect. We study the drag photovoltage using an exact solution of diffraction problem for 2DES with semi-infinite metal gate. We show that the only non-trivial dimensionless parameters governing the drag responsivity are the 2DES conductivity scaled by the free-space impedance {\eta} and gate-2DES separation scaled by the incident wavelength d/{\lambda}0. For radiation with electric field polarized orthogonal to the gate edge, the responsivity is maximized for inductive 2d conductivity with Im{\eta} ~ 1 and Re{\eta} << 1, and becomes very small for the capacitive 2d conductivity. The electromagnetic ponderomotive force pushes the charge carriers under the gate at arbitrary 2d conductivity, and the force direction is opposite to that at metal-2DES lateral contact. These patterns are explained by the dominant role of gated 2d plasmons in the formation of PDE photovoltage.

We perform numerically exact determinant quantum Monte Carlo simulations of the Hubbard model and analyze pairing tendencies by evaluating correlation functions at the imaginary-time midpoint ($\tau=\beta/2$), which suppresses high-frequency weight and emphasizes low-energy physics. Using this diagnostic, we identify clear finite-temperature signatures of underlying $d$-wave superconductivity for electron doping, while finding no clear indication upon cooling for hole doping. Our analysis enables direct comparison with ground-state DMRG, revealing consistent real-space pairing patterns. These results provide a practical route to bridge the gap between finite-temperature and ground-state numerically exact simulations of the Hubbard model despite the fermion sign problem.

We introduce UnIPH, an equivariant graph neural network designed to jointly predict both interatomic potentials and tight-binding (TB) Hamiltonians for an atomic structure. UnIPH is trained using density functional theory (DFT) calculations followed by Wannier projection to predict energies and forces as node-level targets and Wannier-projected TB Hamiltonians as edge-level targets. This enables physically consistent modeling of coupled mechanical-electronic responses with near-DFT-level accuracy. After separately training two UnIPH models on DFT data for bilayer graphene and monolayer MoS2, respectively, we find that these models capture key deformation-electronic effects: in twisted bilayer graphene, the trained UnIPH reveals how interlayer spacing, in-plane strain, and out-of-plane corrugation drive isolated flat-band formation, and further shows that modulating substrate interaction strength can generate flat bands even away from the magic angle (approximately 1.1 degrees). For monolayer MoS2, UnIPH accurately reproduces phonon dispersions and strain-dependent band-gap evolution, and further predicts how a non-uniform substrate creates localized strain pockets that spatially modulate the conduction- and valence-band edges.