Papers

AgNbO$_3$ is a lead-free perovskite with considerable potential for energy storage and optoelectronic applications, yet its low-temperature crystal structure has remained controversial. In this Letter, we revisit its low-energy structural landscape using a systematic first-principles structural search based on symmetry-adapted phonon-mode theory. We uncover a previously unreported chiral ferroelectric phase with space group $R3$, which exhibits a large spontaneous polarization and a low polarization switching barrier, enabling polarization reversal under electric fields. Crucially, the structural chirality of this phase is intrinsically locked to the ferroelectric polarization, allowing electrical control of the chiral handedness. Consequently, chiral optical responses–including circular dichroism, circular photogalvanic effect, optical activity, and second-order nonlinear optics–can be reversibly switched by an external electric field. These results not only clarify the complex low-temperature structural behavior of AgNbO$_3$ but also establish a rare purely inorganic platform for electric-field-tunable chirality, opening a pathway toward ultrafast, electrically controlled chiral optoelectronics.

A prominent feature of $d$-wave altermagnets is that spin current is generated by applying temperature gradient, which is known as the spin-Nernst effect. We show in $f$-wave magnets that spin current is generated proportional to the square of the temperature gradient, which we call the nonlinear spin-Seebeck current. It can be used as a spin current diode. In addition, we show in $g$-wave altermagnets that spin current is generated in the third order of the temperature gradient. We also show in $i$-wave altermagnets that spin current is generated perpendicular to the temperature gradient, which is the spin-Nernst current. We have derived analytic formulas for these spin currents. It is interesting that these phenomena occur in the absence of the spin-orbit interaction. On the other hand, we show in $p$-wave magnets that spin current is not generated by temperature gradient.

We formulate a phenomenological effective field theory in which biological intelligence emerges as a macroscopic order parameter sustained by continuous metabolic flux. By modeling cognition as a coarse-grained neural activity field governed by a variational free energy, we derive closed-form expressions for information capacity and structural susceptibility using a Gaussian maximum entropy approximation. The theory predicts a universal algebraic divergence of the susceptibility, $\chi \sim K^{-3/2}$, as the structural stiffness $K$ approaches the instability threshold. The exponent $\gamma = 3/2$ is consistent with the mean-field branching process universality class, thereby providing a theoretical rationale for the observed avalanche size exponent $\tau \approx 3/2$ in cortical dynamics without invoking microscopic equivalence. We identify adult cognition as a metabolically pinned non-equilibrium steady state maintained near the critical regime $\Gamma \equiv K/\alpha \approx 1$ by continuous metabolic regulation, while pathological decline corresponds to a delocalization transition triggered by the violation of structural stability conditions. The framework generates concrete, falsifiable predictions for attention scaling, altered states of consciousness, and transcranial magnetic stimulation responses, each of which can be tested against existing neuroimaging and electrophysiological datasets.

A novel phenomenological framework for an efficient estimation of the thermo-electric properties at room temperature and elevated temperatures of body-centered cubic (BCC) transition metal concentrated alloys is proposed in this work. The methodology is used to predict the electrical resistivity of BCC systems with our predictions showing excellent correlation with experimental data. This framework is further extended to predict the electrical resistivity $\rho$, thermal conductivity $\kappa$ and the specific heat capacity Cp of BCC alloys in the temperature range of 300-1300 K and the results are validated against experimental data. We demonstrate the capabilities of this model by using it to predict the thermo-electric properties of a concentrated W53Ta42V5 alloy which shows a saturation in the electrical resistivity $\rho$ in the temperature range 300K-1300K. This model is then used to predict the properties of another concentrated Nb$_4$0Mo$_4$0Ta$_2$0 alloy in the same temperature regime.

The Berry connection encodes the momentum-space geometry of occupied Bloch states in gapped insulators and plays a central role in topological materials. While gauge-invariant quantities can be evaluated from overlap matrices between neighboring $k$ points, accessing the Berry connection itself as a smooth field requires specifying a continuous gauge over the Brillouin zone. Wannier-based workflows achieve this through projection onto localized orbitals, enabling stable evaluation of geometric quantities and response functions. In this setting, the Berry connection enters directly in Wannier-interpolated calculations of polarization, Berry curvature, and related response functions. In practical implementations, however, the projection-gauge Berry connection is typically constructed from finite-difference overlaps between neighboring $k$ points, discretizing momentum derivatives and introducing errors tied to $k$-mesh spacing and gauge alignment. These effects can become numerically delicate in systems with small band gaps or when evaluating higher-order responses such as the Chern-Simons axion angle. Here, we derive an exact expression for the non-Abelian Berry connection in the projection gauge that is local in crystal momentum. Starting from projected and orthonormalized Bloch-like states, we obtain a closed-form equation expressed entirely in terms of $k$-local quantities. We validate the formulation in one and three dimensions by computing the Berry phase and Chern-Simons axion angle in tight-binding models. The resulting framework provides a stable route to evaluating geometric properties within Wannier interpolation schemes and future first-principles implementations.

Metal additive manufacturing (AM) is increasingly adopted for safety-critical applications across the biomedical, aerospace, and energy sectors. However, many AM alloys exhibit substantially lower fracture toughness and shorter fatigue lives than their wrought counterparts, limiting their structural reliability. The microscale mechanisms governing this deficit remain obscured because the evolution of crack-tip deformation cannot be directly resolved using conventional characteriza-tion techniques. Here, we combine in situ multimodal synchrotron X-ray diffraction with phase-contrast tomography to directly observe the three-dimensional evolution of crack-tip plasticity dur-ing loading. We find that wrought steel develops a localized crack-tip process zone characterized by extensive geometrically necessary dislocation (GND) accumulation, effective stress relaxation, and crack-tip blunting. This plastic zone provides shielding of the crack tip by redistributing defor-mation and reducing the local driving force for crack initiation. In contrast, the AM alloy exhibits suppressed GND evolution, limited crack-tip blunting, and persistent elevated stresses over an ex-tended region ahead of the crack tip, indicating ineffective stress relaxation and premature crack initiation. These findings demonstrate that fracture resistance is governed by the spatial evolution of crack-tip plasticity, providing a mechanistic framework for improving the damage tolerance of AM structural alloys.

The nonstabilizerness of quantum states is a necessary resource for universal quantum computation, yet its characterization is notoriously demanding. Quantifying nonstabilizerness typically requires an exponential number of measurements and a doubly exponential classical post-processing cost to evaluate its standard monotones. In this work, we show that nonstabilizerness is, to a large extent, in the eyes of the beholder: it can be witnessed and quantified using any set of $m$ $n$-qubit Pauli measurements, provided the set contains anti-commuting pairs. We introduce a general framework that projects the stabilizer polytope onto the subspace defined by these observables and provide an algorithm that estimates magic from Pauli expectation values with runtime exponential in the number of measurements $m$ and polynomial in the number of qubits $n$. By relating the problem to a stabilizer-restricted variant of the quantum marginal problem, we also prove that deciding membership in the corresponding reduced stabilizer polytope is NP-hard. In particular, unless $\mathrm{P} = \mathrm{NP}$, no algorithm polynomial in $m$ can solve the problem in full generality, thus establishing fundamental complexity-theoretic limitations. Finally, we employ our framework to compute nonstabilizerness in different Hamiltonian ground states, demonstrating the practical performance of our method in regimes beyond the reach of existing techniques.

We obtain bounds on the Kullback–Leibler divergence to equilibrium for mass-action chemical reaction networks (CRNs) with equilibrium. The associated trajectory-dependent bounds are characterized in terms of the singular values of the stoichiometric matrix, convexity parameters, and time-integrated activities via deformed-exponential-type functions. We further extend these bounds within a generalized gradient flow framework. We highlight the biological relevance of this framework: the resulting bounds apply to quasi-steady-state regimes, where long transients and plateau-like behavior are common and functionally important. We illustrate the framework using a catalytic CRN exhibiting plateaus, where the bounds provide an a posteriori characterization of slow relaxation induced by local convexity and provide a bound-based approach to quantifying relaxation in CRNs.

Cells often divide under mechanical confinement, where surrounding structures restrict shape changes during cytokinesis. Although forces generated during confined division have been measured experimentally, it remains unclear how confinement geometry and mechanics determine the transmitted force. Here we develop a minimal mechanical theory of cell division under confinement. Modeling the cell as an incompressible volume bounded by an interface with effective isotropic tension, we show that confinement restricts the set of mechanically admissible furrow shapes. As the furrow radius decreases, it reaches it reaches a confinement-induced minimum. Beyond this point, further ingression does not alter the interface shape, and both pressure and axial force saturate. We analyze force and pressure in rigid, soft, and strong three-dimensional confinement and demonstrate that a single geometric mechanism underlies these distinct cases. After rescaling force and length by the appropriate geometric scale, cells of different size and surface tension collapse onto a single universal curve. The relevant length scale is the cell size for rigid and soft confinement, and the confinement size in fully enclosing three-dimensional confinement. In soft confinement, environmental stiffness and spindle-generated axial forces determine the operating force and pressure, while the geometric constraint fixes the maximal attainable levels. In summary, our results show that mitotic force transmission and mitotic pressure during cytokinesis are bounded by confinement geometry, with material properties and active forces selecting the operating point within these geometry-imposed limits.

We assess the impact of atomistic substrate lattice relaxation schemes in the primary band gap at charge neutrality and the secondary valence band gap of graphene on hexagonal boron nitride (G/h-BN) as a function of twist angle. For zero twist angle, the primary gap decreases from $\sim 30$~meV in fully relaxed suspended G/h-BN bilayers, to $\sim 9$~meV when the remote h-BN substrate layer is kept rigid, and down to $\sim 3$~meV in completely rigid structures. In the presence of relaxations, the primary gap shows a maximum near $\sim 0.6^{\circ}$ coinciding with energetic stabilization due to alignment between the moiré pattern and the graphene lattice vectors, while the secondary valence band gap drops from $\sim 12$~meV down to zero beyond twist angles of $\sim 1^{\circ}$. A small but finite primary gap on the order of $\sim 1$~meV, with a mass sign favoring electronic occupation of carbon atop boron, persists across twist angles from $0^{\circ}$ to $30^{\circ}$ for all sliding configurations, and switches sign for twist angles between $30^{\circ}$ and $60^{\circ}$.

The atomistic Hubbard interaction U, representing the on-site Coulomb repulsion, serves as a pivotal parameter in theoretical models describing correlated systems, yet its precise experimental determination, especially in moire systems, remains challenging. Scanning Tunneling Microscopy (STM) provides real-space images of the local density of states (LDOS), offering rich data sets that reflect the unique electronic structure of the material. Here, we introduce a systematic methodology for extracting the Hubbard U parameter directly from these LDOS images through the application of machine learning (ML) in the case of twisted bilayer graphene in the flat-band regime. Accurate regression of U is achieved despite the extremely high visual similarity between FT-LDOS images corresponding to different interaction strengths. Subsequent data analysis further suggests a gradual interaction-dependent redistribution of spectral weight, with a possible crossover scale of order U/t ~ 1. To assess robustness beyond idealized simulations, we introduce physically motivated perturbations that emulate experimental STM imperfections and demonstrate that augmentation-based training substantially improves generalization to noisy and symmetry-broken FT-LDOS images.

We investigate analytically and numerically the dynamics of a two-dimensional superflow governed by the Gross-Pitaevskii equation passing over finite-size rectangular obstacles: an impenetrable wall and an impenetrable rectangular well. Extending classical studies of vortex nucleation around smooth obstacles, we focus on the role of sharp corners in determining the onset of vortex nucleation. Using a combination of analytical techniques based on the Schwarz-Christoffel methods for potential flow and on numerical simulations, we show that local velocity amplification near sharp corners crucially controls the critical flow velocity for vortex nucleation. For both wall and well configurations, we identify analytically and theoretically the critical velocities as a function of the obstacle width and its height or depth, finding an excellent agreement between the theory and our numerical simulations. Our results provide a simple framework for understanding superflow stability past finite-size obstacles with sharp features and are directly relevant to experimentally realizable configurations in atomic Bose-Einstein condensates and related superfluid systems.

We demonstrate that stacking topologically trivial layers, under enforced symmetry restrictions, yields emergent topological phases with protected boundary states. Remarkably, the number of layers itself acts as a topological switch, enabling the system to host topological bound states in the continuum (BICs). Analytically, we reveal that an odd-layer configuration not only renders the spectrum gapless but also supports BICs protected by interlayer reflection symmetry. Combined with entanglement-spectrum calculations, this confirms that odd-layer systems indeed support topological BICs. We provide experimental confirmation of these topological states in stacked acoustic lattices. Our findings establish a previously overlooked pathway to topology and demonstrate a readily applicable strategy for realizing exotic states in a wide range of artificial material systems.

A model for the tensorial dielectric permittivity of phospholipid membranes is presented here. The four-nanometer-thick membrane is treated as a composite made up of three dielectric slabs: one for each of the two phospholipid head-group regions, and one for the entire domain spanned by the lipid tails. Equal and opposite bound surface charge densities surround each head-group slab, and account for the membrane dipole potential. Three-slab model parameters are obtained from molecular dynamics simulations, and capture both the zero-field electric potential and the membrane response to applied electric fields. The tail region is well-approximated as having vacuum permittivity, while the head-group region is highly anisotropic due to the configurations of molecular dipoles. For the bilayers studied, the out-of-plane permittivity of the head-group region is 10–15 times that of the vacuum, while the in-plane permittivity is an order of magnitude larger. Membrane responses to applied electric fields up to 30 millivolts per nanometer are found to be in the linear regime. The model overcomes a fundamental limitation of microscopic theories—where the out-of-plane permittivity lacks a meaningful continuum interpretation in the head-group region due to large gradients in the local electric field—by averaging over slab widths, thereby introducing new length scales. Our approach can be extended to characterize general interfacial systems with similar microscopic permittivities.

The directional nature of heat conduction in semiconductor superlattices–marked by significant differences between in-plane and cross-plane pathways–poses substantial challenges for precise thermal property assessment. Conventional frequency-domain thermoreflectance (FDTR) techniques, while proficient at evaluating cross-plane thermal conductivity, suffer from restricted capability in resolving in-plane transport due to inherent phase-delay constraints and inadequate lateral resolution. In this investigation, we establish a non-contact beam-offset FDTR (BO-FDTR) approach that concurrently determines both directional thermal conductivities within layered semiconductor architectures. Our methodology implements spatial separation between excitation and detection beams while utilizing coupled normalized amplitude and phase responses as analytical inputs, thereby improving discrimination between anisotropic thermal parameters. We combine this experimental configuration with a Bayesian optimization scheme incorporating Gaussian Process Regression (BO-GPR) to reduce estimation inaccuracies, attaining measurement uncertainties under 1% to 2% at 95% confidence intervals. This technique demonstrates particular efficacy for intricate multilayer nanostructures, furnishing a structured protocol for superlattice thermal evaluation. Experimental characterization of an AlAs/GaAs superlattice (period thickness 52 nm) delivers thermal conductivity values of 14.7 W m-1 K-1 (cross-plane) and 37.4 W m-1 K-1 (in-plane). Our findings indicate that integrating frequency sweeps with varied beam offset locations yields superior measurement precision, exceeding conventional single-variable methods and confirming thermal assessment validity across both geometric arrangements.

Although numerical simulations of rheological measurements typically focus on homogeneous systems, heterogeneity can profoundly impact material properties. We report on the rheological properties of a suspension of two-dimensional Lennard-Jones particles across the gas/liquid and the gas/solid coexistence lines of the system. We show how the presence of multiple coexisting states has a significant impact on the mechanical properties of these systems when compared with their homogeneous reference counterparts. Our results establish an extended map to navigate a landscape where not only density and temperature, but also phase coexistence, dictate the transition from viscous to elastic-dominated behavior under shear. These results provides a benchmark for future research into heterogeneous fluids where the coexistence of complex dynamic states is frequently observed.

EXAFS spectroscopy is used to study the local environment of lead and selenium atoms in PbTe$_{1-x}$Se$_x$ solid solution. In addition to a bimodal distribution of bond lengths in the first shell, unusually large Debye–Waller factors for the Pb–Pb interatomic distances in the second shell and a substantial deviation of these distances from Vegard's law are observed. Valence force field (VFF) calculations show that these observations are due to the complex structure of the distribution function for Pb–Pb distances. It is found that the number of Se–Se pairs in the second shell surpasses the statistical value, which indicates that chemical factors play an important role in the structure of the solid solution. The contribution of these chemical factors to the enthalpy of mixing of the solid is estimated to be approximately 0.5 kcal/mole, which is comparable to the strain contribution.

Fluid phase equilibrium depends on the external constraints imposed on a system. In a closed system with fixed volume, depending on the average density, a vapor bubble may be stable, metastable, or unstable, with respect to the homogeneous liquid phase. In the case where the bubble is metastable, we study its lifetime, i.e. the average waiting time needed to observe bubble collapse, and the corresponding lifetime of the homogeneous liquid. For the smallest systems, we predict the possibility to observe phase flipping, when the fluid oscillates between states with and without bubble. We provide an example of phase flipping in a simulation of a Lennard-Jones fluid.

The idea that topologically protected quantum states, such as anyons, may be attached to super/semiconductor heterostructures has received enormous attention, but experimental signatures in 1D systems remain elusive. Here we revisit theoretical underpinnings of anyons in 2D fractional quantum Hall (FQH) systems, whose signatures have been experimentally observed by independent groups. Invoking novel theorems about the Hopfion or $\mathbb{C}P^1$-model understood as flux quantization in 2-Cohomotopy, which retrodicts abelian FQH anyon properties in fine detail. Examining this theoretical model further, we find that islands of expelled (surplus) flux enlarge the ground-state monodromy from an abelian group to a (framed spherical) braid group, nonabelian for two or more islands, so that nonabelian anyonic states become topologically admissible; superconducting islands are one candidate realization of such flux expulsion.

Interfaces that couple digital information with physical matter enable computation to be expressed through tangible motion and touch, yet typically rely on embedded actuators, rigid mechanisms, or enclosed environments. Consequently, contactless manipulation and interaction with centimeter-scale tangible elements in open settings remain difficult to achieve. Here, we present PolygonWave, a solid–fluid acoustic interface that enables transport and tangible interaction by coupling airborne ultrasound with liquid-mediated support. The system employs lightweight Janus icons with asymmetric wettability: a superhydrophobic upper surface permits dry touch interaction, while a hydrophilic lower surface couples to a water droplet resting on a superhydrophobic mesh. Focused acoustic fields generated by a 256-element phased array induce lateral forces, enabling programmable motion without mechanical contact. Systematic characterization demonstrates transport of payloads up to 525 mg across variations in icon size, droplet volume, and applied load. Beyond translation, the liquid layer functions as a reconfigurable mechanical element, enabling button-like input with self-recovery and resonance-driven vibro-visual feedback, exhibiting a peak response near 22 Hz for 200 \textmu L droplets. Liquid-mediated acoustic coupling provides a unified mechanism for mechanically expressive, touch-accessible tangible interfaces bridging acoustics, soft matter physics, and physical human–computer interaction.

N-carbophenes are a class of two-dimensional covalent organic frameworks with potential for solid-state gas storage and as 2D topological materials. Previous studies have demonstrated that variations in their bonding, topology, and functionalization enable the tuning of their chemical, electrical, and mechanical properties. Yet, the thermal stability and high-temperature behavior of pristine and functionalized N-carbophenes remain unexplored. Using ReaxFF-based reactive molecular dynamics (RMD) simulations with extensive statistical validation, we performed temperature-ramp MD simulations of pristine and functionalized N-carbophenes. We demonstrate that N-carbophenes remain stable up to temperatures above 1000 K. The phase-change onset temperatures decrease as the N-phenylene chain length increases in pristine N-carbophenes, attributed to increasing antiaromaticity in the central phenylene segments, thereby contributing to the foundational understanding of aromatic versus antiaromatic bonding in 2D carbon networks, a topic of considerable interest in theoretical chemistry. Pristine N-carbophenes exhibit negative area thermal expansion (NATE), whereas functional groups modulate this, leading to either negative or positive expansion. Functional groups remain stably bonded well above the transition temperature. We also show that a temperature-induced phase transition from graphenylene (2-carbophene) to {\gamma}-graphyne is possible. Our results provide upper bounds on N-carbophene stability, clarify the relationships between structure and thermal properties, and identify a new transformation pathway. These results will have applications in tunable band gaps, porous architectures, or chemically accessible sites.

Vanadium-based oxychalcogenide compounds with the inverse Lieb-lattice (ILL) structural pattern have recently been proposed as candidate altermagnets (AM). However, early studies postulated ferromagnetic interlayer coupling, a critical requirement for preserving the bulk AM state. Here we present a systematic survey of the complete AV2Q2O family (A = K, Rb, Cs; Q = S, Se, Te) in terms of their magnetic ordering and interlayer coupling. While intralayer exchange interaction favors AM ordering in a single ILL layer across the entire family, the relatively weak interlayer coupling in most cases favors Kramers-degenerate antiferromagnetic order with a doubled magnetic unit cell. This means that most stoichiometric bulk materials, including the previously proposed candidate KV2Se2O, are not altermagnetic, with CsV2Te2O being the only exception. Using hole doping to simulate alkali vacancies, we show that realistic deviations from stoichiometry do not change the magnetic ground state in these compounds.

Copolymerization is commonly employed to tune polymers' glass formation and improve properties such as ion conductivity and adhesion. Classically, mixing rules such as the Fox equation are employed to explain glass transition temperature (Tg) variations with copolymer composition. However, many copolymers deviate from these mixing rules in a manner that is monomer-sequence sensitive. We perform molecular dynamics simulations to probe the interplay between copolymer sequence, liquid-liquid phase equilibria, and Tg. We find that the direction and sequence-dependence of Tg shift are predicted by the liquid-liquid phase behavior of the comonomers. Systems tending towards Upper Critical Solution Temperature behavior negative Tg deviations, while systems tending towards Lower Critical Solution Temperature behavior exhibit positive Tg deviations. In both cases, this effect is strengthened with increasing alternation - a consequence of bond-induced forced mixing. These results inform strategies for rationally varying copolymer Tg, at fixed composition, via design of polymer chain sequence.

Fluctuation-response relations encode fundamental constraints on non-equilibrium systems. While time-domain static response is bounded by activity and entropy production, finite-frequency thermodynamic bounds for time-dependent perturbations remain largely unexplored. Here, we find a finite-frequency response-duality relation in non-equilibrium Markov jump processes. For state-current observables, the ratio between the spectral responses to kinetic-barrier and entropic-force perturbations is frequency-independent and gives the single-transition entropy production. The response-duality relation provides a method for measuring the single-transition entropy production from spectral response signals. Furthermore, we derive frequency-domain thermodynamic and kinetic inequalities for non-equilibrium systems with time-dependent perturbations around unperturbed steady states. We illustrate our response-duality relation on a quantum dot system. These finite-frequency response relations and inequalities provide a practical route for inferring dissipation from power-spectrum response measurements.

We show that in situ ion irradiation transient grating spectroscopy (I3TGS) can be used to monitor the real-time evolution of vacancy concentration generated by self-ion radiation damage in Cu-based alloys. Surface acoustic wave (SAW) frequencies are shown, using a combination of theory and experiment, to reveal vacancy concentrations and their kinetics in real-time. These results are shown to agree with corresponding kinetic Monte Carlo simulations at similar temperatures and dose rates. These results suggest the utility of TGS as a non-contact, non-destructive tool for real-time defect monitoring.

Local chemical order (LCO) is a key descriptor linking composition, atomic arrangement, and function in high-entropy alloys (HEAs), yet remains difficult to quantify. This Perspective highlights how X-ray absorption spectroscopy (XAS) provides element-specific, quantitative insight into LCO in complex alloys. We outline practical considerations for XAS data collection and fitting, including width of spectra range, multi-temperature analysis, and X-ray absorption edge choice for 5d elements. We then highlight a coordination-number-based framework for LCO analysis and use model HEAs to show how single-atom and near-single-atom motifs naturally emerge as component number increases, bridging HEAs and single-atom alloys. Finally, we identify priorities including standardized protocols, uncertainty quantification, expanded operando and time-resolved XAS, and integration with complementary characterization and modelling.

Despite their apparent diversity, modern machine learning methods can be reduced to a remarkably simple core principle: learning is achieved by continuously optimizing parameters to minimize or maximize a scalar objective function. This paradigm has been extraordinarily successful for well-defined tasks where goals are fixed and evaluation criteria are explicit. However, if artificial systems are to move toward true autonomy-operating over long horizons and across evolving contexts-objectives may become ill-defined, shifting, or entirely absent. In such settings, a fundamental question emerges: in the absence of an explicit objective function, how can a system determine whether its ongoing internal dynamics are productive or pathological? And how should it regulate structural change without external supervision? In this work, we propose a dynamical framework for learning without an explicit objective. Instead of minimizing external error signals, the system evaluates the intrinsic health of its own internal dynamics and regulates structural plasticity accordingly. We introduce a two-timescale architecture that separates fast state evolution from slow structural adaptation, coupled through an internally generated stress variable that accumulates evidence of persistent dynamical dysfunction. Structural modification is then triggered not continuously, but as a state-dependent event. Through a minimal toy model, we demonstrate that this stress-regulated mechanism produces temporally segmented, self-organized learning episodes without reliance on externally defined goals. Our results suggest a possible route toward autonomous learning systems capable of self-assessment and internally regulated structural reorganization.

Lithium and sodium are the only solids that are known to lose crystalline order upon cooling. The seemingly-disordered low-temperature phase shows signatures of various close-packed structures. The lack of order has been attributed to a hidden gauge symmetry that arises when electrons from one layer can hop to a neighbouring layer but not further. It makes all close-packed structures nearly degenerate and leads to “structural frustration”. In this article, we examine whether this symmetry is reflected in transport signatures. Taking advantage of in-plane translational periodicity, we map the bulk Bloch Hamiltonian to an effective one-dimensional chain, with stacking disorder mapping to random phases of the hopping amplitudes. We derive an explicit analytic form for the Green's function of electrons and use it to calculate conductance of a bulk crystal. When hopping in the effective one-dimensional chain is restricted to nearest neighbours, conductance is completely insensitive to phase disorder, which indicates that all close-packed structures exhibit the same conductance. We show that the leading correction that can differentiate between close-packed structures arises from hopping to the next-nearest-neighbour layer, equivalent to second-neighbour hopping in the chain model. This process appears when a pair of next-neighbour layers are aligned in a certain way, e.g., at an hcp-like stacking fault within an fcc background. With this hopping included, conductance becomes sensitive to the precise arrangement of layers. When multiple stacking faults are present, the conductance decreases with increasing system size, as expected from Anderson localization. Our results are applicable to pressurized lithium and sodium, where conductance measurements can identify and characterize stacking faults.

Atomic Layer Deposition (ALD) process development is often hindered by time-consuming and precursor-intensive tuning cycles required to identify saturation conditions. We introduce a physics-informed Bayesian active learning (BAL) framework that autonomously tunes precursor pulse times by integrating a Langmuir adsorption model directly into the Gaussian Process (GP) kernel. A key innovation is a two-stage parameter estimation strategy that decouples noise filtering from physical parameter extraction: the GP first smooths noisy data through standard prediction, then Langmuir parameters are fitted to the noise-filtered GP predictions. This approach effectively separates signal from experimental noise. We evaluate the framework against a standard data-driven GP across four simulated regimes, demonstrating convergence within five iterations, up to fourfold improvement in prediction accuracy, and two to fourfold reduction in precursor usage. Experimental validation using TiO2 deposition via Tetrakisdimethylamido Titanium (TDMAT) and ozone confirms that the physics-informed model accurately identifies saturation times for high-coverage targets ($\geq$95%), with observed deviations at lower saturation levels providing valuable insight into non-ideal desorption behaviors.

Symmetry constraints provide a powerful means to control the dynamics of open quantum systems. However, the set of accessible control parameters is often limited. Here, we show that a tunable phase in the collective light-matter coupling of a cavity QED system induces a phase-dependent strong symmetry of the Liouvillian, enabling dynamical control of the open quantum system evolution. We demonstrate that tuning this phase substantially reduces the critical driving strength for dissipative phase transitions between stationary and non-stationary phases. We illustrate this mechanism in two experimentally relevant cavity QED settings: a two-species ensemble of two-level atoms and a single-species ensemble of three-level atoms. Our results establish phase control as a versatile tool for engineering dissipative phase transitions, with implications for quantum state preparation.