Papers

Domain wall memories have undergone several changes over the years for faster shift, read, and write operations; however, fundamental issues persist due to creating pinning sites topographically along the nanowire. The deformity in notches creates non-uniform pinning strength, leading to multiple faults during shift operation. This study proposes a novel approach to address these challenges and gain greater control over domain manipulation for advanced applications in Boolean and non-Boolean paradigms. Utilizing the magnetic topological insulator (MTI) can create pinning sites without potentially faulty topographical notches made through complex lithography. Moreover, applying an external current enables precise control over the pinning potentials at these sites. Micromagnetic simulations validate the effectiveness of MTI-based pinning sites, showcasing their potential for future applications. Our approach introduces an alternative method for creating pinning sites by cross-architecture of ferromagnetic nanowires and MTI nanobars, inducing exchange interaction at their intersection points. This method offers simplicity of fabrication and enables control over the pinning strength by external current.

Charged water drops are more widespread than commonly acknowledged. For example, raindrops typically carry charges of order Q ~ 1 pC, while routine pipetting in the laboratory produces drops with Q ~ 50 pC. Here, we show that such modest charging can spontaneously generate periodic Coulomb fissions for evaporating water drops on lubricated surfaces, with more than 60 successive cycles observed over 30 min. Interestingly, the underlying instability can be quantitatively predicted by two fissility thresholds: one marking the onset of drop elongation and another triggering fission. Each fission culminates with a fine liquid jet that disintegrates into 40-50 microdroplets, expelled within microseconds. The phenomenon spans an extraordinary range of length scales (from millimetres to microns) and time scales (hour to microseconds), with broad potential applications ranging from nanoscale fabrication to electrospray ionization.

MgMn$_6$Sn$_6$ is the itinerant ferromagnet on the kagome lattice with high ordering temperature featuring complex electronic properties due to the nontrivial topological electronic band structure, where the spin-orbit coupling (SOC) plays a crucial role. Here, we report a detailed ferromagnetic resonance (FMR) spectroscopic study of MgMn$_6$Sn$_6$ aimed to elucidate and quantify the intrinsic magnetocrystalline anisotropy that is responsible for the alignment of the Mn magnetic moments in the kagome plane. By analyzing the frequency, magnetic field, and temperature dependences of the FMR modes, we have quantified the magnetocrystalline anisotropy energy density that reaches the value of approximately $ 3.5\cdot 10^6$ erg/cm$^3$ at $T = 3$ K and reduces to about $1\cdot 10^6$ erg/cm$^3$ at $T = 300$ K. The revealed significantly strong magnetic anisotropy suggests a sizable contribution of the orbital magnetic moment to the spin magnetic moment of Mn, supporting the scenario of the essential role of SOC for the nontrivial electronic properties of MgMn$_6$Sn$_6$.

In hydrodynamic descriptions of lipid bilayers, the membrane is often approximated as being impermeable to the surrounding, solute-containing fluid. However, biological and in vitro lipid membranes are influenced by their permeability and the resultant osmotic forces – whose effects remain poorly understood. Here, we study the dynamics of a fluctuating, planar lipid membrane that is ideally selective: fluid can pass through it, while the electrically-neutral solutes cannot. We find that the canonical membrane relaxation mode, in which internal membrane forces are balanced by fluid drag, no longer exists over all wavenumbers. Rather, this mode only exists when it is slower than solute diffusion – corresponding to a finite range of wavenumbers. The well-known equipartition result quantifying the size of membrane undulations due to thermal perturbations is consequently limited in its validity to the aforementioned range. Moreover, this range shrinks as the membrane surface tension is increased, and above a critical tension the membrane mode vanishes. Our findings are relevant when interpreting experimental measurements of membrane fluctuations, especially in vesicles at moderate to high tensions.

This study numerically investigates the thermal sampling properties of QAOA, the Quantum Alternating Operator Ansatz which was generalized from the original Quantum Approximate Optimization Algorithm. Specifically, the ability of QAOA to sample from the Gibbs distribution, equivalently the Boltzmann distribution, defined by a classical Ising model, specifically a fully connected disordered spin glass (Sherrington-Kirkpatrick) model. We focus on two different QAOA mixers; the standard transverse field X mixer, and the Grover mixer. At a QAOA depth of one we examine, for a single full QAOA parameter search space period, the energy landscape, the Shannon entropy landscape of the QAOA probability distribution, and the tradeoff between Boltzmann distribution sampling temperature and error rate (how close to the true Boltzmann distribution is the QAOA distribution). We find that at very high temperatures one-round Grover mixer QAOA can sample from the Boltzmann distribution more accurately than the standard X mixer QAOA at one round. Both X mixer and Grover mixer depth one QAOA can serve as approximate Boltzmann distribution samplers, and how good this approximation is depends heavily on the QAOA angle choice.

Amorphous boron nitride (\textrm{$\alpha$}-BN) is a promising ultrathin barrier for nanoelectronics, yet the atomistic mechanisms governing its chemical stability remain poorly understood. Here, we investigate the structure-property relationship that dictates the oxidation of \textrm{$\alpha$}-BN using a combination of machine-learning molecular dynamics simulations and angle-resolved X-ray photoelectron spectroscopy. The simulations reveal that the film structure, controlled by synthesis conditions, is the critical factor determining oxidation resistance. Dense, chemically ordered networks with a high fraction of B-N bonds effectively resist oxidation by confining it to the surface, whereas porous, defect-rich structures with abundant homonuclear B-B and N-N bonds permit oxygen penetration and undergo extensive bulk degradation. These computational findings are consistent with experimental trends observed in \textrm{$\alpha$}-BN films grown by chemical vapour deposition. XPS analysis shows that a film grown at a higher temperature develops a more ordered structure with a B/N ratio nearer to stoichiometric and exhibits superior resistance to surface oxidation compared to its more defective, lower-temperature counterpart. Together, these results demonstrate that the oxidation resistance of \textrm{$\alpha$}-BN is a tunable property directly linked to its atomic-scale morphology, providing a clear framework for engineering chemically robust dielectric barriers for future nanoelectronic applications.

Unidirectional magnetoresistance (UMR) in metallic bilayers arises from nonlinear spin-charge transport mediated by broken time-reversal and inversion symmetries, yet the role of magnons remains unsettled. We develop a theoretical framework that incorporates coupled electron-magnon dynamics, revealing cross diffusion and spin-angular-momentum transfer between the two subsystems, which renormalize the characteristic electron and magnon spin-diffusion lengths. We show that nonequilibrium magnons, indirectly excited by the electric field, can suppress UMR by absorbing spin angular momentum from conduction electrons. We also analyze the magnetic-field, thickness, and temperature dependencies and identify distinct features that constitute experimental fingerprints of magnonic contributions to UMR in metallic bilayers, providing qualitative to semiquantitative guidance for elucidating the underlying physical mechanisms.

The process of dephasing during wave evolution has traditionally been viewed as an obstacle to localization, leading to diffusion even in strongly disordered Hermitian lattices. In contrast, here we demonstrate how the interplay of dephasing with non-Hermitian defects can be harnessed to engineer wave localization. Specifically, we identify a novel dynamical localization phenomenon characterized by wavefunction accumulation at the lattice's boundary due solely to dephasing, despite globally reciprocal couplings. Furthermore, we study the incoherent skin effect arising from coupling asymmetry, and investigate the interplay between these antagonistic localization mechanisms. By reframing dephasing from a hindrance into a tool, this study overturns established paradigms of wave localization and paves the way for novel approaches to controlling localization phenomena in non-Hermitian physics.

For two-dimensional polycrystals the effective elasticity tensor $C_*$ as a function $C_*(C_0)$ of the elasticity tensor $C_0$ of the constituent crystal is considered. It is shown that this function can be approximated by one with a continued fraction expansion resembling that associated with a class of microstructure known as sequential laminates. These are hierarchical microstructures defined inductively. Rank 0 sequential laminates are simply rotations of the pure crystal. Rank $j$ sequential laminates are obtained by laminating together, on a length scale much larger that the existing microstructure and with interfaces perpendicular to some direction $n_j$, rank $j-1$ sequential laminates with a rotation of the pure crystal. The continued fraction approximation for arbitrary polycrystal microstructures typically takes a more general form than that of sequential laminates, but has some free parameters. It is an open question as to whether these free parameters can always be adjusted so the continued fraction approximation matches exactly that of a sequential laminate. If so, one would have established that the elastic response of two-dimensional polycrystals can always be mimicked by that of sequential laminates. Our analysis carries over to the more general case where the strain is replaced by a field $E(x)$ that is the gradient of a vector potential $u(x)$, i.e. $E=\nabla u$ and the stress is replaced by a matrix valued field $J(x)$ that need not be symmetric but has zero divergence $\nabla\cdot J=0$. The tensor $L(x)$ entering the constitutive relation $J=L E$ is locally a rotation of the tensor $L_0$ of the pure crystal that need not have any special symmetries and has 16 independent tensor elements.

Life relies on a sophisticated metabolic molecular machinery that turns over high-energy molecules to evolve complex macromolecules and assemblies. At the molecular origin of life, such machinery was absent, implying the need for simple yet robust physical mechanisms to harvest energy from the environment and perform chemical work or produce chemical power. However, the mechanisms involved in harvesting energy from a macroscopic cyclic environment to drive chemical processes on the molecular scale remain elusive. In this work, we propose a theory that describes the kinetics of chemical reactions in a system subject to a cyclic reservoir with varying properties. We compare cycles of solvent (wet-dry cycles), with cycles of a component participating in a chemical reaction (reactant cycle). We find that for both wet-dry and reactant cycles, resonance frequencies exist at which the chemical power is maximal. We identify which cycle type is more beneficial in harvesting chemical power for different molecular interactions. Our findings of harvest efficiencies around ten percent suggest that the cyclic environment could have played a key role in catalyzing the metabolic molecular machinery at the molecular origin of life.

We present a comprehensive investigation of the field-dependent critical current density and pinning force, combined with a detailed analysis of the nanostructural defect landscape in single crystal of underdoped PrFeAs(O,F) superconductor. Our study demonstrates that for both in-plane and out-of-plane magnetic field orientations critical current density exhibits a strong pinning regime in intermediate fields across the entire temperature range. The dominant contribution to pinning originates from oxygen-to-fluorine substitutional defects, oxygen vacancies, which all act as point defects via a quasiparticle mean free path fluctuation mechanism. Scanning transmission electron microscope studies did not reveal any volume or surface defect types within the lattice.

We studied single-particle Anderson localization in ensembles of graphs that correspond to chiral and Bogoliubov-de Gennes (BdG) symmetry classes. For a random biregular bipartite graph with chiral symmetry, the density of states was found using the cavity approach. Calculating the fractal dimension shows the effects of disordered zero modes. For Bogoliubov-de Gennes ensembles with an underlying random regular graph (RRG), the density of states was calculated both numerically and analytically. The ensembles BdG-RRG with symmetry-conserving diagonal disorder in the delocalized phase have a smaller fractal dimension compared to the usual RRG.

Magnetic domain walls play a critical role in the nanoscale evolution of magnetic devices. Despite the early efforts, a complete understanding of the micromagnetic evolution of the width and the type of magnetic domain walls has still remained missing. Here, we report a combined analytical and micromagnetic simulation study and establish the scaling of the magnetic domains as a function of the exchange stiffness (A), uniaxial perpendicular magnetic anisotropy (Ku), saturation magnetization (Ms), and Dzyaloshinskii-Moriya interaction (DMI), and shape anisotropy of the magnetic device. We find that the width of both Bloch and Neel walls scales excellently with the analytical prediction. The DMI is found to have little influence on the domain wall width but strongly affect the type of the domain wall. The domain wall has a Bloch configuration at zero DMI and gradually transitions to Neel configuration upon increase of the DMI. The shape anisotropy of the magnetic domain wall also affects the domain wall width. These results have established a comprehensive, conclusive understanding of the magnetic domain walls within spintronics devices.

In liquid pnictogens, quasi-stable structures can be formed near melting temperature. The nature of their stability does not have the unified point of view. In the present work, the task of determining the degree of atomic bonding in these structures is solved using the Crystal Orbital Hamilton Population (COHP) method. The original results of ab-initio simulation of arsenic, antimony and bismuth melts near their melting temperatures are used. It is shown that the features of the electron interaction at the level of $p$-orbitals determine the characteristic bond lengths and angles between atoms. It has been established that the stability of structures decreases according to a power law with an increase in the atomic mass of a chemical element and the number of atoms in the structure. The obtained results clarify the understanding the mechanisms of formation of quasi-stable structures in pnictogen melts from first principles.

The metal-insulator transition (MIT) in correlated oxide systems opens up a new paradigm to trigger the abruption in multiple physical functionalities, enabling the possibility in unlocking exotic quantum states beyond conventional phase diagram. Nevertheless, the critical challenge for practical device implementation lies in achieving the precise control over the MIT behavior of correlated system across a broad temperature range, ensuring the operational adaptability in diverse environments. Herein, correlated vanadium dioxide (VO2) serves as a model system to demonstrate effective modulations on the MIT functionality through bandwidth and band-filling control. Leveraging the lattice mismatching between RuO2 buffer layer and TiO2 substrate, the in-plane tensile strain states in VO2 films can be continuously adjusted by simply altering the thickness of buffer layer, leading to a tunable MIT property over a wide range exceeding 20 K. Beyond that, proton evolution is unveiled to drive the structural transformation of VO2, with a pronounced strain dependence, which is accompanied by hydrogenation-triggered collective carrier delocalization through hydrogen-related band filling in t2g band. The present work establishes an enticing platform for tailoring the MIT properties in correlated electron systems, paving the way for the rational design in exotic electronic phases and physical phenomena.

This study proposes an Artificial Intelligence (AI) driven methodology for predicting a combination of brazed ceramic-metal composite materials. Multiple machine learning (ML) algorithms are compared with the deep learning (DL) model. The developed models are tested using k-fold validation. Nine different input-output feature configurations are evaluated to assess the model performance. The input-output feature comprises material properties, namely, the coefficient of thermal expansion (CTE) and molecular mass of brazed ceramic-metal composite materials obtained from literature and the strength parameter (average Von Mises Stress (VMS)) estimated from Finite Element Method (FEM) simulation for joint assembly structure. A multi-output model, Autoencoder (AE), has also been developed and tested to predict various features. The ML model, namely the polynomial regression (PR), outperforms the other ML/DL models with a Mean square Error (MSE) of 0.01 for the test data. The autoencoder model with a 32-16-32 structure outperforms LR, PR, RF, and ANN with an MSE of 0.04% for the prediction of unseen data. The developed multi-output model accurately predicts all the features (single and multiple), while PR fails to accurately predict multi-output features of low importance. The developed AE model predicts the different material properties with an average error of ~0.16-3.78% with literature-reported values.

Molecular spin qudits offer an attractive platform for quantum memory, combining long coherence times with rich multi-level spin structures. Terbium bis(phthalocyaninato) (TbPc$_2$) exemplifies such systems, with demonstrated quantum control and chemical reproducibility. In hybrid quantum architectures, TbPc$_2$ can act as the primary memory element, with semiconductor qubits providing scalable readout and coupling. Here we present a step toward such a hybrid system: using an industrially manufactured silicon metal-oxide-semiconductor (SiMOS) spin qubit to detect electronic spin transitions of an ensemble of TbPc$_2$ molecules. The readout is based on a compact and robust protocol that applies a microwave pulse while all gate voltages defining the qubit are held at a fixed operating point. This protocol, which combines simultaneous Rapid adiabatic Passage and Spin- Selective tunneling (RPSS), enables high-contrast resonance detection and avoids repeated $\pi$-pulse recalibration common in decoupling schemes. By demonstrating ensemble detection, we establish a foundation for integrating molecular quantum memories with industrial qubit platforms and mark an important step toward single-molecule hybrid quantum technologies.

The use of a Si pixel-based particle tracking scheme in muSR will, among others, allow measurements using a ten-fold increased stopped muons rate and samples ten times smaller than currently possible. Here we present simulation results to assess the effects of magnetic fields on two spectrometer configurations using a two-layered tracking scheme for the incoming and outgoing particles. At a low magnetic field of up to ~50 mT, the tracking and reconstruction accuracy is only minimally influenced. Beyond a magnetic field of ~80 mT the tracking capabilities diminish significantly. Operating a two-layered scheme using small magnetic fields hence does not require adaptations. Only at large magnetic fields, a tracking scheme that makes use of an accurate field map or the use of at least three layers must be employed to achieve reliable particle tracking.

We investigate bond percolation on mediation-driven attachment (MDA) networks under the generalized Achlioptas process, where $M>1$ candidate bonds are sampled and the one that minimizes the resulting cluster size is selected the best-of-$M$ rule. This framework offers a systematic approach to investigate how network topology and choice mechanisms jointly shape percolation behavior. We analyze the effects of the degree exponent $\omega$ and the choice parameter $M$ on the critical point $t_c$ and the critical exponents ($\beta,\alpha,\gamma$), which define universality classes and obey the Rushbrooke inequality $\alpha + 2\beta + \gamma \geq 2$. Using entropy, the order parameter, and their derivatives (representing specific heat and susceptibility respectively), we show that both $t_c$ and the universality class depend only weakly on $\omega$ but strongly on $M$, while the Rushbrooke inequality remains valid throughout. For $M=2$, the order parameter varies continuously without a clear order-disorder transition. By contrast, $M=3$ and $M=4$ display explosive percolation that still corresponds to a continuous phase transition, with $M=4$ producing a significantly sharper and clearer order-disorder transition. This sharpening is traced to an enhanced powder-keg effect at larger $M$, underscoring the entropic origin of explosive percolation.

Hybrid superconductor-semiconductor(SC-SM) nanowires remain one of the foremost platforms for engineering topological superconductivity and Majorana zero modes(MZMs) towards fault-tolerant topological qubits, especially with the rapid development of artificial Kitaev chains. In contrast to the widely used aluminum(Al)-based hybrids, lead(Pb) offers a bulk superconducting gap of ~1.4meV and a critical temperature of ~7.2K, giving rise to a proximity-induced gap that is roughly five times larger than that obtained with Al. Here we present the first three-terminal Pb-hybrid devices and perform nonlocal differential-conductance spectroscopy on this platform. The nonlocal measurement simultaneously resolves a dual-gap feature of the parent Pb gap and the large, hard, gate-tunable induced superconducting gap, distinguished by a switch between electron- and hole-like dissipation processes. Within the induced gap we observe several types of Andreev bound states(ABSs) that undergo singlet-doublet transitions. Moreover, by tuning gate voltages we achieve gate-controlled resonating sign reversals of the nonlocal conductance, identifying three distinct regimes that correspond to different configurations of quantum-dot(QD) resonances(single-resonance, double-resonance, and series-resonance). Finally, the coupling between ABSs and QDs also present and can be modulated from the weak- to strong-coupling limit, indicating the feasibility of realizing the artificial Kitaev chains. Crucially, the robust nonlocal signatures persist up to temperatures(~1K) far above the operating temperature of Al-based devices thanks to the unusually large induced gap, thereby widening the accessible parameter space greatly and underscoring the suitability of Pb-based hybrids for implementing warm temperature artificial Kitaev chains and the topological quantum devices protected by a substantially larger topological gap.

Bose-Einstein condensates of $^{87}\mathrm{Rb}$ atoms with a hyperfine spin of 2 are open quantum systems, where the atoms are lost through two-body inelastic collisions. In this dissipation process, a collision channel with total spin of 4 is forbidden by angular momentum conservation, which results in magnetization of the atoms remaining in the condensate. Here, we investigate the quantum many-body properties of spin-2 bosons that undergo two-body atomic loss. We show that the system finally reaches a steady state, which is a mixture of the states with maximum total spins. In addition, we find that a nonclassical steady state can be obtained by applying and quenching the quadratic Zeeman field.

The magnetic correlations in double perovskites La2Mn2-xNixO6 (x = 0.5, 0.75, 1.0, 1.25 and 1.5) have been systematically investigated across macroscopic, mesoscopic, and microscopic length scales using temperature-dependent bulk DC magnetization, neutron depolarization, and neutron powder diffraction measurements, respectivitly. The magnetic properties evolve from a long-range ferromagnetic (FM) order to a cluster ferromagnetic or spin-glass (FM or SG) behavior as the Ni concentration increases. This evolution is directly linked to changes in the crystal structure, transitioning from pure orthorhombic (x=0.5) to mixed orthorhombic and monoclinic (x=0.75-1.0), and eventually to mixed trigonal and monoclinic symmetries (x=1.25-1.5). Ni substitution enhances the magnetic ordering temperature from 170 K (x=0.5) to 280 K (x=1.0), but this is accompanied by a reduction in both magnetization and ordered magnetic moment. Beyond x=1.0, any long-range magnetic ordering is absent. Additionally, all compositions exhibit a reentrant spin-glass-like phase at low temperatures (below about 50 K). Neutron diffraction analysis confirms that long-range FM order occurs only in the orthorhombic phase, while the monoclinic and trigonal phases lack such magnetic ordering. The temperature-dependent magnetic correlations are closely connected to variations in crystal structural parameters, including lattice constants and unit cell volume. The electrical conductivity behavior, following the variable range hopping (VRH) model, highlights the role of multivalence Mn and Ni ions on the electrical properties. This study elucidates the microscopic mechanisms behind the tunable magnetic and electrical properties of La2Mn2-xNixO6, offering valuable insights for the design of advanced materials for spintronic applications.

Classical computation of electronic properties in large-scale materials remains challenging. Quantum computation has the potential to offer advantages in memory footprint and computational scaling. However, general and practical quantum algorithms for simulating large-scale materials are still lacking. We propose and implement random-state quantum algorithms to calculate electronic-structure properties of real materials. Using a random state circuit with only a few qubits, we employ real-time evolution with first-order Trotter decomposition and Hadamard test to obtain electronic density of states, and we develop a modified quantum phase estimation algorithm to calculate real-space local density of states via direct quantum measurements. Furthermore, we validate these algorithms by numerically computing the density of states and spatial distributions of electronic states in graphene, twisted bilayer graphene quasicrystals, and fractal lattices, covering system sizes from hundreds to thousands of atoms. Our results manifest that the random-state quantum algorithms provide a general and qubit-efficient route to simulating electronic properties of large-scale periodic and aperiodic materials on quantum computers.

Graphdiyne (GDY) is recognized as a compelling candidate for the fabrication of next-generation high-speed low-energy electronic devices due to its inherent p-type semiconductor characteristics. However, the development of GDY for applications in field-effect transistors (FETs), complementary metal-oxide-semiconductor (CMOS), and logic devices remains constrained by the relatively low carrier mobility reported in current experimental studies. Herein, the synthesis of layer-controlled hydrogen-substituted graphdiyne (HsGDY) films directly on silicon substrates under a supercritical CO2 atmosphere is reported, along with the fabrication of these films into HsGDY-based FETs. The transfer-free growth strategy eliminates performance degradation caused by post-synthesis transfer processes. The resulting HsGDY FETs exhibit a remarkable hole mobility of up to 3800 cm2 V-1 s-1 at room-temperature, which is an order of magnitude higher than that of most p-type semiconductors. The synthesis of transfer-free HsGDY wafers provides a new strategy for resolving the carrier mobility mismatch between p-channel and n-channel two-dimensional metal-oxide-semiconductor devices.

Interplay between topology and magnetism induces various exotic quantum phenomena, with magnetic topological insulators (MTIs) serving as a prominent example due to their ability to host the quantum anomalous Hall effect (QAHE). However, the realization of QAHE at higher temperature approaching magnetic-transition-temperature remains a significant challenge, primarily due to the scarcity of suitable material platforms and limited understanding of the intricate relationships between band topology, magnetism, and defects. Here, we report a comprehensive investigation of MnSb2Te4(Sb2Te3)n (n = 0 - 5) single crystals, including the discovery of novel MnSb8Te13 pure phase. Experimental measurements confirm that MnSb8Te13 exhibits ferromagnetism and features topologically nontrivial electronic structures, characterized by a Dirac point located further from the conduction band and a possible larger bulk gap compared to MnBi2Te4(Bi2Te3)n (n = 0 - 3). Moreover, we systematically analyze the relationship between structure, magnetism, topology, and disorder within Mn(Sb, Bi)2Te4((Sb, Bi)2Te3)n family. Present work will shed light on the exploration of potential platforms capable of achieving QAHE near magnetic transition temperature, offering new directions for advancing topological quantum materials.

Feynman path integrals (PIs) have found many uses in approximate quantum dynamics methods for efficiently calculating real-time quantum correlation functions. The PIs typically take the form of discrete imaginary-time slices along a closed path, where the slices form the “beads” of a ring polymer (RP) necklace. Some methods, such as centroid molecular dynamics (CMD), use the RP to generate an effective potential for the dynamics, while others, like RP molecular dynamics (RPMD), directly utilize the RP in real-time dynamics in order to incorporate approximate quantum effects. The standard, discretized bead forms of CMD and RPMD may require a large number of RP beads to obtain accurate results for systems with strong quantum effects and at low temperatures. In Paper I (J. Chem. Phys. 2025, 163, 144123), we introduced the bead-Fourier (BF)-CMD method, where we utilized the inclusion of a Fourier sine series to reduce the number of beads needed to converge the CMD effective potential up to eightfold. In this work, we extend RPMD to incorporate BF-PIs in the form of BF-RPMD. We study several implementations of the BF-RPMD method through the calculation of correlation functions for both linear and nonlinear operators. We found that the effectiveness of this method is sensitive to both the type of system and the form of the operators being studied. Our results show that this method is able to produce results on par with standard RPMD, with at worst a twofold and up to an eightfold reduction in the number of beads by including two to three Fourier components.

Amorphous solid-state electrolytes (SSEs) hold great promise for advancing the application of all-solid-state batteries (ASSBs), owing to their favorable ionic conductivity, structural tunability, and promising electrochemical performance. However, the absence of universal design principles for amorphous SSEs limits their development. By fundamentally re-evaluating the amorphization-forming ability of amorphous SSE systems, this study establishes a nitrogen-driven universal strategy to convert diverse metal chlorides into amorphous xLi3N-MCly (0.3 < 3x < 1.9; M denotes a metal element; 2 < y < 5) SSE. Nitrogen synergistically disrupts crystalline order via distorted coordination polyhedra and N-bridged networks, while dynamic bond reorganization enables rapid Li+ migration, achieving ionic conductivity of 2.02 mS cm-1 for 0.533Li3N-HfCl4 at 25 {\deg}C. Structural-property relationships reveal that high charge density and bridging capability of N3- enhance network disorder, shorten metal coordinating atom distances, and optimize Li+ diffusion pathway connectivity. ASSBs employing 0.533Li3N-HfCl4 retain 81.87% capacity after 2000 cycles at 1000 mA g-1 with high cathode loading (6.24 mg cm-2), demonstrating engineering viability. This work provides a paradigm for rational design of high-performance amorphous SSEs.

Entangled materials offer attractive structural features including tensile strength and large deformations, combined with infinite assembly and disassembly capabilities. How the geometry of individual particles governs entanglement, and in turn translates into macroscopic structural properties, provides a rich landscape in terms of mechanics and offers intriguing possibilities in terms of structural design. Despite this potential, there are major knowledge gaps on the entanglement mechanisms and how they can generate strength. In particular, vibrations are known to have strong effects on entanglement and disentanglement but the exact mechanisms underlying these observations are unknown. In this report we present tensile tests and discrete element method (DEM) simulations on bundles of entangled staple-like particles that capture the combined effects of particle geometry and vibrations on local entanglement, tensile force chains and strength. We show that standard steel staples with $\theta = 90^\circ$ crown-leg angle initially entangle better than $\theta = 20^\circ$ modified staples because of their more "open" geometry. However, as vibrations are applied entanglement increase faster in $\theta = 20^\circ$ bundles, so that they develop strong and stable tensile force chains, producing bundles which are almost ten times stronger than $\theta = 90^\circ$ bundles. Both tensile strength and entanglement density increase with vibrations and also with deformations, up to a steady state value. At that point the rate of entanglement equals the rate of disentanglement, and each of these rates remains relatively high. Finally, we show that vibration can be used as a manipulation strategy to either entangle or disentangle staple-like entangled granular materials, with confinement playing a significant role in determining whether vibration promotes entanglement or disentanglement.

At low temperature T we expect vacuum tunneling processes to occur in superfluid $^{4}$ He films. We distinguish between extrinsic processes, in which single vortices nucleate by tunneling off boundaries in the system, and intrinsic processes, in which vortex/anti-vortex pairs nucleate far from boundaries. It is crucial to incorporate the varying effective mass of the vortex in tunneling calculations. The intrinsic processes are the superfluid analogue of the Schwinger mechanism in quantum field theory; here they appear as a quantum phase transition at T = 0, driven by an external supercurrent. We calculate the tunneling rate for these processes, and describe a means of testing the predictions using a specific vortex counting experiment.

We prove that an effective temperature naturally emerges from the algorithmic structure of a regular universal Turing machine (UTM), without introducing any external physical parameter. In particular, the redundancy growth of the machine's wrapper language induces a Boltzmann–like exponential weighting over program lengths, yielding a canonical ensemble interpretation of algorithmic probability. This establishes a formal bridge between algorithmic information theory and statistical mechanics, in which the adopted UTM determines the intrinsic “algorithmic temperature.” We further show that this temperature approaches its maximal limit under the universal mixture (Solomonoff distribution), and discuss its epistemic meaning as the resolution level of an observer.