This study investigates the anomalous spin and orbital Hall effects in iron ($\mathrm{Fe}$) films with strong in-plane uniaxial anisotropy, highlighting the interactions between spin and orbital currents. Using heterogeneous $\mathrm{YIG}/\mathrm{Fe}$ and $\mathrm{YIG}/\mathrm{Pt}/\mathrm{Fe}$ structures, fabricated by oblique deposition in a magnetic field, spin-pumping ferromagnetic resonance (SP-FMR) measurements were performed. It was observed that the uniaxial anisotropy enables the emergence of spin-to-charge and orbital-to-charge conversion signals in the out-of-plane configuration, where the spin polarization is parallel to the direction of the spin current. Experimental analysis revealed that orbital dynamics, mediated by orbital Hall conductivity, are more prominent in $\mathrm{Fe}$ films due to the low spin-orbit interaction (SOC) and large orbital response. These findings provide fundamental insights for the advancement of orbitronics devices, indicating the potential for controlling orbital and spin currents through magnetic and anisotropic parameters.

Multistable metamaterials, capable of adopting multiple stable configurations, offer versatile control over the shape and mechanical properties of systems. Transition waves (TWs), which propagate spatially through state transitions, provide a promising mechanism for reconfiguring such materials. While TWs in systems with asymmetric energy landscapes propagate stably by transitioning from higher to lower energy states, they require additional energy input to reset the structure, limiting their reusability. This work explores a multistable system with a reconfigurable surface shape, comprising an elastic slender beam coupled to a foundation of bistable elements with a symmetric energy landscape. The symmetric landscape enables TWs with tunable speeds, energy, and propagation distances, which can be controlled by the impact speed on the boundaries. The stop position of the TW forms a static domain wall, separating regions into distinct stable states. Leveraging the relationship between impact speed and propagation distance, we propose a dynamic strategy for reversible surface shape reconfiguration using sequential impulses to generate targeted configurations. An experimental demonstration using buckled double beams as bistable elements confirms the feasibility of this strategy, highlighting its potential for postmanufacturing shape control in multistable systems.

Solid-state defects such as nitrogen-vacancy ($\mathrm{N}$-$V$) centers in diamond have been utilized for NMR sensing at ambient temperatures for samples at the nanoscale and up to the microscale. Similar to standard NMR, $\mathrm{N}$-$V$-sensitivities can be increased using tesla-valued magnetic fields to boost nuclear thermal polarization, while structural parameters, such as chemical shifts, are also enhanced. However, with standard microwave- (MW) based sensing techniques, $\mathrm{N}$-$V$ centers struggle to track fast megahertz Larmor frequencies encountered in high-field scenarios. Previous protocols have addressed this by mapping target NMR parameters to the signal amplitude rather than the frequency, using a mediating radio-frequency field. Although successful, protocol sensitivities are limited by the coherence time ($T_2^{\ast }$) of the NMR signal owing to the presence of stages where the sample magnetization freely evolves. In this work, we propose extending this coherence time, and consequently improving sensitivity, via amplitude encoding with weak nuclear-spin locking instead of free evolution, thereby taking advantage of the longer sample coherence times ($T_{1\rho }$). We demonstrate that this can enhance protocol sensitivities by a factor of $\gtrsim 4$.

We investigate the lattice thermal-transport properties of intercalation compounds $X\mathrm{Nb}{Y}_2$ ($X=\mathrm{Li}$, $\mathrm{Na}$; $Y$ = $\mathrm{S}$, $\mathrm{Se}$) using the unified theory of thermal transport. The calculations reveal that soft optical phonons exhibit strong hybridization with acoustic branches, leading to a non-negligible contribution to the lattice thermal conductivity. Our results suggest that the stereochemically active lone-pair electrons on the chalcogen atoms enhance the anharmonic phonon-phonon interactions, leading to a reduction in the thermal conductivity. The weak coupling of interlayer vibrational modes, particularly along the out-of-plane direction, results in negligible wavelike tunneling phonon transport at room temperature. However, its strong temperature dependence highlights a growing contribution of coherent phonon transport at elevated temperatures. Simultaneously, the intercalation of alkali-metal atoms enhances interlayer interactions, leading to more collective atomic vibrations and promoting particlelike phonon transport. While this transition facilitates more efficient thermal conduction across layers, it partially counteracts the intended suppression of lattice thermal conductivity, thereby compromising thermoelectric optimization in the out-of-plane direction. On the electronic side, a multivalley band structure near the Fermi level enhances the power factor via improved carrier scattering phase space, while the introduction of alkali-metal layers reduces electrical-conductivity anisotropy. These combined effects yield a maximum thermoelectric figure of merit $Z_T\approx 2.9$ at 700 K.

The high-capacity and long-distance transmission of acoustic signals is vital for wireless underwater communications. However, the presence of sound-dense barriers within the transmission path significantly hinders the interaction of acoustic information and energy across different media. In this study, we design an acoustic metalens aiming at facilitating high-capacity communication through dense barriers with enhanced efficiency, leveraging achromatic ultrasound focusing. The metalens is developed by thoroughly considering and utilizing the multiphysical interactions between the metastructure and the surrounding water medium, which substantially amplifies the vibrations of the barrier, thereby creating an effective channel for acoustic signals to traverse. Additionally, the designed metalens is capable of transmitting multifrequency ultrasonic waves while concurrently focusing sound power at the same position, resulting in high-capacity underwater communication characterized by an improved high signal-to-noise ratio and channel isolation. This advanced transmission enhancement technology presents a novel approach for developing efficient underwater communication devices in complex environments, with potential application in underwater acoustic sensing and detection.

The newest and most powerful electronic chips for applications such as artificial intelligence generate so much heat that liquid-based cooling has become indispensable to prevent breakdown from thermal runaway effects. While cooling schemes such as microfluidic networks or liquid immersion are proving effective for now, further progress requires tackling an age-old problem—namely, the intrinsic thermal impedance of the liquid/solid (L/S) interface, quantified either by the thermal boundary resistance or by the thermal slip length. While there are well-known models for estimating bounds on the thermal impedance of a superfluid/metal interface, no analytic models or experimental data are available for normal liquid/solid interfaces. Researchers therefore rely on nonequilibrium molecular dynamics simulations to gain insight into phonon transfer at the L/S interface. Here we explore correlated order and motion within the L/S contact zone in an effort to extract general scaling relations for the thermal slip length in Lennard-Jones (LJ) systems. We focus on the in-plane structure factor and dominant vibrational frequency of the first solid and liquid layer for 180 systems. When scaled by the temperature of the liquid contact layer and characteristic LJ interaction distance, the data collapse onto two power-law equations, one quantifying the reduction in thermal impedance from enhanced in-plane translational order and the other from enhanced frequency matching in the contact zone. More generally, these power-law relations highlight the critical role of surface acoustic phonons, an area of focus that may also prove useful to the development of analytic models as well as instrumentation for testing the relations proposed.

Two-dimensional (2D) materials, with their atomic-scale thickness and high carrier mobility, are promising candidates for replacing silicon channels, offering significant potential for gate lengths below 5 nm. Monolayer $MN$$\mathrm{H}$${}_2$ ($MN$ = $\mathrm{CSi},\mathrm{Si}\mathrm{Si},\mathrm{Si}\mathrm{Ge}$) materials, such as ${\mathrm{CSi}\mathrm{H}}_2$, ${\mathrm{Si}}_2{\mathrm{H}}_2$, and ${\mathrm{Si}\mathrm{Ge}\mathrm{H}}_2$, exhibit suitable band gaps alongside excellent carrier mobility. Their high compatibility with existing silicon-based chip technologies further positions them as suitable channel materials for 2D field-effect transistors (FETs). Using first-principles calculations, we systematically investigate the transport properties of monolayer $MN$$\mathrm{H}$${}_2$ metal-oxide-semiconductor field-effect transistors (MOSFETs) and benchmark their performance against the International Technology Roadmap for Semiconductors (ITRS) 2028 requirements for high-performance (HP) and low-power applications. These MOSFETs achieve peak on-state currents ($I_{\mathrm{ON}}$) of 4157 and 3527 $\text{μ}\mathrm{A}/\text{μ}\mathrm{m}$ for $n$- and $p$-type HP devices, respectively, with notably low delay times $\tau$ and power dissipation (PDP). They maintain compliance with ITRS 2028 standards when scaled to gate lengths as small as 3 nm. When scaled to 5 nm, the subthreshold swing reaches 58 mV/dec, surpassing the Boltzmann thermal limit of 60 mV/dec. Compared to other 2D materials, $MN$$\mathrm{H}$${}_2$ MOSFETs deliver higher $I_{\mathrm{ON}}$, lower $\tau$, and reduced PDP, establishing them as highly promising candidates for next-generation 2D FET applications.

Parametric amplification offers a powerful means to enhance quantum interactions through field squeezing, yet it typically introduces additional noise, which accelerates quantum decoherence, a major obstacle for scalable quantum information processing. The squeezing field is implemented in cavities rather than continuous waveguides, thereby limiting its scalability for applications in quantum simulation. Giant atoms, which couple to waveguides at multiple points, provide a promising route to mitigate dissipation via engineered interference, enabling decoherence-free interactions. We extend the squeezing-amplified interaction to an alternative quantum platform combining giant atoms with traveling-wave parametric waveguides based on ${\chi }^{(2)}$ nonlinearity. By exploiting destructive interference between different coupling points, the interaction between giant atoms is not only significantly enhanced but also becomes immune to squeezed noise. Unlike conventional waveguide quantum electrodynamics without a squeezing pump, the giant emitters exhibit both exchange and pairing interactions, making this platform particularly suitable for simulating many-body quantum physics. More intriguingly, the strengths of these interactions can be smoothly tuned by adjusting the squeezing and coupling parameters. Our architecture thus provides a versatile and scalable platform for quantum simulation of strongly correlated physics and paves the way toward robust quantum control in many-body regimes.

Optical lattice clocks of fermionic strontium offer a versatile platform for probing fundamental physics and developing quantum technologies. The bivalent electronic structure of strontium gives rise to a doubly forbidden atomic transition that is accessible due to hyperfine mixing in fermionic strontium-87, thus resulting in a submillihertz natural linewidth. Currently, the most accurate optical lattice clocks operate on this narrow transition by tightly trapping strontium-87 atoms in a magic optical lattice at 813 nm. Magic wavelengths occur where the Stark shifts of both the ground and excited states are equal, thus eliminating any position- and intensity-dependent broadening of the corresponding transition. Theoretical calculations of the electronic structure of strontium-87 have also predicted another magic wavelength of the clock transition at 497.01(57) nm. In this work, we experimentally measure the magic wavelength to be 497.4364(4) nm. Compared to the 813-nm magic wavelength, 497 nm is closer to the strong 461-nm dipolar transition of strontium, resulting in an order-of-magnitude increase in atomic polarizability and deeper traps with less optical power. The proximity to the 461-nm transition also leads to an enhanced sensitivity of 334(10) Hz/(nm $E_R$) at the magic wavelength.

Metal halide perovskites exhibit a rich interplay between electronic and ionic dynamics, leading to diverse phenomena such as negative capacitance (NC) and resistive switching (RS). Despite their significance in photovoltaic and memristive applications, these effects are often treated independently, with no unified physical explanation. In this work, we demonstrate that NC and RS in halide perovskite devices originate from a shared mechanism: electric field–driven ion migration. Through operando impedance spectroscopy and systematic variation of perovskite dimensionality and interfaces, we identify a quantitative correlation between the onset voltage of RS and the threshold voltage of NC (Pearson correlation coefficient r = 0.91), both governed by ionic relaxation timescales. Interfacial halide accumulation induces dipolar relaxation, yielding volatile switching and NC, whereas bulk ion percolation enables nonvolatile RS through conductive filament formation. A phase diagram constructed from ion concentration and interfacial energetics delineates the transition between these regimes. This unified framework establishes the physical basis for tuning memristor volatility and provides a predictive approach for the design of ionically coupled perovskite systems.

The electrochemical nitrogen reduction reaction (NRR) offers a sustainable, low-energy alternative to the Haber-Bosch process for ammonia synthesis under mild conditions. Experimental studies on $\mathrm{Cu}$ clusters and stepped surfaces have indicated that high-index $\mathrm{Cu}$ facets can significantly enhance catalytic performance. However, systematic first-principles studies remain lacking on $\mathrm{Cu}$ surfaces with high-index facets. Motivated by recent breakthroughs, we conduct a comprehensive first-principles investigation of dozens of experimentally accessible $\mathrm{Cu}$ high-index surfaces. By evaluating the Gibbs free energy of the potential-determining step ($\mathrm{\Delta }{G}_{\mathrm{PDS}}^{\mathrm{NRR}}$), we identify $\mathrm{Cu}$(211), $\mathrm{Cu}$(430), and $\mathrm{Cu}$(511) as the most active. Furthermore, transition-metal doping is explored as a strategy to enhance activity, with several doped surfaces reducing $\mathrm{\Delta }{G}_{\mathrm{PDS}}^{\mathrm{NRR}}$ from 1.5 eV to around 0.3 eV. Considering competition from the hydrogen evolution reaction, $\mathrm{Co}$ and $\mathrm{Re}$-doped $\mathrm{Cu}$(430) surfaces show superior NRR selectivity. Our results offer theoretical insight into $\mathrm{Cu}$ high-index facets and propose a low-cost, efficient NRR catalyst via dopant engineering.

The Toffoli gate is an important universal quantum gate, and will alongside the Clifford gates be available in future fault-tolerant quantum computing hardware. Many quantum algorithms rely on performing arbitrarily small single-qubit rotations for their function, and these rotations may also be used to construct any unitary from a limited (but universal) gate set. How to carry out such rotations is then of significant interest. In this work, we evaluate the performance of a recently proposed single-qubit rotation algorithm using the Clifford plus Toffoli gate set by implementation of a one-shot version on both a real and a simulated quantum computer. We test the algorithm under various simulated noise levels using a per-qubit depolarizing error noise model and examine how the probabilities and process fidelities are affected. We then conduct live runs and find that the results reasonably match the simulated results. We also attempt to model the hardware noise by combining a number of noise models, matching the results to results of the live runs to approximate the hardware noise. Our results suggest that the algorithm will perform well for up to $1\mathrm{\%}$ noise under the noise models we chose. We further posit the use of our algorithm as a benchmark for quantum processing units, given that it has a low complexity that is easy to fine-tune in small steps. We provide details for how to do this.

Quantum sensors offer exceptional sensitivity to nanoscale magnetic field fluctuations, where nonstationary effects—such as spin diffusion—and non-Markovian dynamics arising from coupling to few environmental degrees of freedom play critical roles. Because fully reconstructing the microscopic structure of realistic spin baths is often infeasible, a practical challenge is to identify the dynamical features that are actually encoded in the sensor’s decoherence signal. Here we demonstrate how quantum sensors can operationally characterize the statistical nature of environmental noise, distinguishing between stationary and nonstationary behaviors, as well as Markovian and non-Markovian dynamics. Using nitrogen-vacancy centers in diamond as a platform, we develop a physical noise model that captures the essential dynamical features of realistic environments relevant to sensor observables—independently of the microscopic bath details— and provides analytical predictions for Ramsey decay across different regimes. These predictions are experimentally validated through controlled noise injection with tunable correlation properties. Our results showcase the capability of quantum sensors to isolate and identify key dynamical properties of complex environments, without requiring full microscopic bath reconstruction. This work clarifies the operational signatures of nonstationarity and non-Markovian behavior at the nanoscale and lays the foundation for strategies that mitigate decoherence while exploiting environmental dynamics for enhanced quantum sensing.

We propose a practical hybrid decoding scheme for the parity-encoding architecture. This architecture was first introduced by N. Sourlas [Phys. Rev. Lett. 94, 070601 (2005)] as a computational technique for tackling hard optimization problems, especially those modeled by spin systems such as the Ising model and spin glasses, and reinvented by W. Lechner, P. Hauke, and P. Zoller [Sci. Adv. 1, e1500838 (2015)] to develop quantum annealing devices. We study the specific model, called the SLHZ model, aiming to achieve a near-term quantum annealing device implemented solely through geometrically local spin interactions. Taking account of the close connection between the SLHZ model and a classical low-density parity-check (LDPC) code, two approaches can be chosen for the decoding: (1) finding the ground state of a spin Hamiltonian derived from the SLHZ model, which can be achieved via stochastic decoders such as a quantum annealer or a classical Monte Carlo sampler; or (2) using deterministic decoding techniques for the classical LDPC code, such as belief propagation and a bit-flip decoder. The proposed hybrid approach combines the two approaches by applying bit-flip decoding to the readout of the stochastic decoder based on the SLHZ model. We present simulations demonstrating that this approach can reveal the latent potential of the SLHZ model, realizing the soft-annealing concept proposed by Sourlas.