The pyroelectric response of materials is a promising phenomenon that is used in many applications. Here, we report first-principles lattice dynamics and ab initio molecular dynamics calculations to investigate the mechanisms of the pyroelectric effect in the $Pca{2}_1$ orthorhombic phase of ${\mathrm{Hf}\mathrm{O}}_2$; this is an emerging pyroelectric material with promising technological applications. With first-principles lattice dynamics calculations, we demonstrate a large pyroelectric response that is intrinsic to the pure $Pca{2}_1$ orthorhombic phase. Unlike most conventional ferroelectric pyroelectrics, such large pyroelectricity arises unexpectedly from the secondary effect (induced by the negative longitudinal piezoelectric effect) that has not received due attention. Ab initio molecular dynamics simulations further demonstrate a giant pyroelectric response that is associated with an orthorhombic (polar) to tetragonal (nonpolar) structural phase transition. Upon the incorporation of $\mathrm{Si}$ dopants with increasing dopant concentrations, the phase transition persists, but occurs at reduced temperatures with enhanced pyroelectric responses. The present work highlights the importance of the secondary pyroelectric effect responsible for the pyroelectricity in ${\mathrm{Hf}\mathrm{O}}_2$ and its promising potential for device applications.

Deep-frequency-modulation interferometry combines optical minimalism with multifringe readout. However, precision is key for applications such as optical gradiometers for satellite geodesy or as dimensional sensors for ground-based gravity experiments. We present a single-component interferometer smaller than a cubic inch. Two of these are compared to each other to demonstrate tilt and displacement measurements with a precision of less than 20 $\mathrm{nrad}/\sqrt{\mathrm{Hz}}$ and 1 $\mathrm{pm}/\sqrt{\mathrm{Hz}}$ at frequencies below 1 Hz.

Typical acoustic refractive metasurfaces governed by the generalized Snell law require several types of subwavelength subunits to provide an extra phase gradient along the surface. However, current design strategies have several drawbacks; for instance, the complex subwavelength subunits result in inevitable viscous loss, and ignoring the coupling between adjacent subunits leads to low efficiency in wavefront manipulations, especially for large angles. To overcome these limitations, we propose a metasurface or metagrating composed of only one straight channel and several surface-etched grooves per period. By harnessing the nonlocal coupling between the channel and the grooves, and the evanescent modes inside them, superior feasible acoustic transmission manipulations can be achieved. Nearly perfect acoustic bending with transmission efficiency up to $95\mathrm{\%}$ is obtained in theory and experiments for an extremely large angle of ${81}^{\circ }$. Our results extend the realm of acoustic metasurfaces and offer alternative opportunities for the development of highly efficient acoustic devices for wavefront manipulations.

Plasmonic metamaterials can be used to enhance midinfrared sensors and detectors for immunosensing applications. The major challenge with them is to integrate these technologies in low-cost, compact, and promising platforms. As an emerging technique, we utilize toroidal resonant plasmonic metamaterials to develop an ultrasensitive label-free analytical platform for the detection of specific antibiotics in the midinfrared spectra. Taking advantage of the unique sensitivity of robustly squeezed electromagnetic fields in the toroidal plasmonic meta-atoms, we demonstrate that our proposed approach based on toroidal metastructures provides recognition of extremely-low-weight (approximately 0.6 KDa) biological targets at attomolar densities. We envisage that this understanding extends the capabilities of plasmonic metamaterials to analyze the presence of specific biological molecules and organisms with ultrahigh precision.

Ferroelectric tunnel barriers in between two ferromagnetic electrodes (multiferroic tunnel junctions, or MFTJs) hold great promise for future microelectronic devices. Here, we utilize ${\mathrm{Hf}}_{0.5}{\mathrm{Zr}}_{0.5}{\mathrm{O}}_2$ (HZO) tunnel barriers with an ultralow thickness of only 2 nm, epitaxially grown on ${\mathrm{La}}_{0.7}{\mathrm{Sr}}_{0.3}{\mathrm{Mn}\mathrm{O}}_3$ ferromagnetic bottom electrodes and with cobalt top electrodes. Both tunneling electroresistance and tunneling magnetoresistance effects are observed, demonstrating four nonvolatile resistance states in HZO-based junctions. The large band gap and excellent homogeneity of the HZO tunnel barriers enable a high yield of working devices, as well as devices with sizes of tens of micrometers. This allows working with fixed electrodes, as opposed to the use of scanning probes, bringing MFTJs closer to applications.

Within the paradigm of metamaterials and metasurfaces, the electromagnetic properties of composite materials can be engineered by shaping or modulating their constituents, the so-called meta-atoms. Synthesis and analysis of complex-shaped meta-atoms with general polarization properties is a challenging task. In this paper, we demonstrate that the most general dipolar response of any small object can be conceptually decomposed into a set of basic fundamental polarization phenomena, which enables immediate all-direction characterization of the electromagnetic properties of arbitrary linear materials and metamaterials. The proposed platform for modular characterization is tested on several examples of bianisotropic and nonreciprocal meta-atoms. As a demonstration of the potential of this modular analysis, we use it to design a single-layer metasurface of vanishing thickness with unitary circular dichroism. The analysis approach developed in this paper is supported by a ready-to-use computational code and can be further extended to meta-atoms engineered for other types of wave interactions, such as in acoustics and mechanics.

The study of Weyl points in electronic systems has inspired much recent research in classical systems such as photonic and acoustic lattices. Here we show how Weyl physics can also inspire the design of novel elastic structures. We construct a single-phase three-dimensional structure, an analog of the $AA$-stacked honeycomb lattice, and predict the existence of Weyl points with opposite topological charges ($\pm 1$), elastic Fermi arcs, and the associated gapless topologically protected surface states. We apply full-scale numerical simulations on the elastic three-dimensional structure and present a clear visualization of topological surface states that are directional and robust. Such designed lattices can pave the way for novel vibration control and energy harvesting on structures that are ubiquitous in many engineering applications.

We design an all-carbon membrane for the filtration and desalination of water. A unique layered assembly of carbon nanostructures including graphite oxide (GO), buckypaper consisting of carbon nanotubes, and a strong carbon fabric provides high mechanical strength and thermal stability, resilience to harsh chemical cleaning agents, and electrical conductivity, thus addressing major shortcomings of commercial reverse osmosis membranes. We use ab initio density-functional-theory calculations to obtain atomic-level insight into the permeation of water molecules in between GO layers and across in-layer vacancy defects. Our calculations elucidate the reason for selective rejection of solvated ${\mathrm{Na}}^{+}$ ions in an optimized GO membrane that is structurally stabilized in a sandwich arrangement in between layers of buckypaper, which are protected on both sides by strong carbon fabric layers.

The recent demonstration of neuromorphic computing with spin-torque nano-oscillators has opened a path to energy efficient data processing. The success of this demonstration hinged on the intrinsic short-term memory of the oscillators. We extend the memory of the spin-torque nano-oscillators through time-delayed feedback. We leverage this extrinsic memory to increase the efficiency of solving pattern recognition tasks that require memory to discriminate different inputs. The large tunability of these nonlinear oscillators allows us to control and optimize the delayed-feedback memory using different operating conditions of applied current and magnetic field.

The Shockley and Queisser limit, a well-known efficiency limit for a solar cell, is based on unrealistic physical assumptions and its maximum limit is seriously overestimated. To understand the power loss mechanisms of record efficiency cells, a more rigorous approach is necessary. We establish a formalism that can accurately predict absolute performance limits of solar cells in conventional thin-film form. In particular, a formulation for a strict evaluation of the saturation current in a nonblackbody solar cell is developed by taking the incident angle, light polarization, and texture effects into account. Based on the established method, we estimate the maximum efficiencies of 13 well-studied solar cell materials [$\mathrm{Ga}\mathrm{As}$, $\mathrm{In}\mathrm{P}$, $\mathrm{Cd}\mathrm{Te}$, $a\text{−}\mathrm{Si}:\mathrm{H}$, ${\mathrm{Cu}\mathrm{In}\mathrm{Se}}_2$, ${\mathrm{Cu}\mathrm{Ga}\mathrm{Se}}_2$, ${\mathrm{Cu}\mathrm{In}\mathrm{Ga}\mathrm{Se}}_2$, ${\mathrm{Cu}}_2{\mathrm{Zn}\mathrm{Sn}\mathrm{Se}}_4$, ${\mathrm{Cu}}_2{\mathrm{Zn}\mathrm{Sn}\mathrm{S}}_4$, ${\mathrm{Cu}}_2\mathrm{Zn}\mathrm{Sn}(\mathrm{S},\mathrm{Se}{)}_4$, ${\mathrm{Cu}}_2{\mathrm{Zn}\mathrm{Ge}\mathrm{Se}}_4$, ${\mathrm{CH}}_3{\mathrm{NH}}_3{\mathrm{PbI}}_3$, $\mathrm{HC}({\mathrm{NH}}_2{)}_2{\mathrm{PbI}}_3$] in a 1-µm-thick physical limit. Our calculation shows that over 30% efficiencies can be achieved for absorber layers with sharp absorption edges ($\mathrm{Ga}\mathrm{As}$, $\mathrm{In}\mathrm{P}$, $\mathrm{Cd}\mathrm{Te}$, ${\mathrm{Cu}\mathrm{In}\mathrm{Ga}\mathrm{Se}}_2$, ${\mathrm{Cu}}_2{\mathrm{Zn}\mathrm{Ge}\mathrm{Se}}_4$). Nevertheless, many record efficiency polycrystalline solar cells, including hybrid perovskites, are limited by open-circuit voltage and fill-factor losses. We show that the maximum conversion efficiencies described here present alternative limits that can predict the power generation of real-world solar cells.

We investigate the magnetic proximity effect in a van der Waals heterostructure formed by a monolayer semiconductor stacked on a two-dimensional (2D) ferromagnet, where the lattice mismatch and twisting between the layers typically lead to the formation of a moiré pattern. We find that the magnetic proximity effect arising from the spin-dependent interlayer coupling depends sensitively on the interlayer atomic registry. Consequently, in the moiré pattern, the spatial variation of the atomic registry leads to a lateral modulation of a magnetic proximity field. Such a moiré modulated magnetic proximity effect manifests as a miniband spin splitting that strongly depends on the moiré periodicity, which can be mechanically tuned by a relative twisting and/or strain between the layers. We also show, because of the moiré modulation on the interlayer distance, a perpendicular electric field can be used to control the miniband spin splitting. Our results suggest potential nanodevices where the moiré modulated magnetic proximity effect can lead to unique spin controllability.

All-optical helicity-dependent switching in ferromagnetic $\mathrm{Co}/\mathrm{Pt}$ multilayers is investigated using magneto-optical microscopy and anomalous Hall effect measurements. A state diagram is built by studying the effect of pulse duration, fluence, and spot size. We use numerical solutions of the three-temperature model to explain that the all-optical helicity-dependent switching mechanism relies on the spin bath reaching temperatures close to the Curie point. Further insights into the reversal process are provided by the experimental demonstration of significant helicity-dependent reversal after a single laser pulse that reveals the involvement of direct angular momentum transfer. Moreover, based on the observation that longer pulse durations and larger spot sizes lead to enhanced reversal efficiency, we identify experimental conditions that lead to saturated magnetization reversal after just a few tens of laser pulses.

The frontiers of quantum electronics have been linked to the discovery of new refrigeration methods since the discovery of superconductivity at a temperature of around 4 K, enabled by the liquefaction of helium. Since then, advances in cryogenics have led to discoveries such as the quantum Hall effect and new technologies such as superconducting and semiconductor quantum bits. Presently, nanoelectronic devices typically reach electron temperatures of around 10–100 mK by use of commercially available dilution refrigerators. However, cooling electrons via the encompassing lattice vibrations, or phonons, becomes inefficient at low temperatures. Further progress toward lower temperatures requires new cooling methods for electrons on the nanoscale, such as direct cooling with nuclear spins, which themselves can be brought to microkelvin temperatures by adiabatic demagnetization. Here we introduce indium as a nuclear refrigerant for nanoelectronics and demonstrate that solely on-chip cooling of electrons is possible down to $3.2\pm 0.1\mathrm{mK}$, limited by the heat leak via the electrical connections of the device.

The Hodgkin-Huxley model describes the behavior of the cell membrane in neurons, treating each part of it as an electric circuit element; namely, capacitors, memristors, and voltage sources. We focus on the activation channel of potassium ions, due to its simplicity, while keeping most of the features displayed by the original model. This reduced version is essentially a classical memristor, a resistor whose resistance depends on the history of electric signals that have crossed it, coupled to a voltage source and a capacitor. We consider a quantized Hodgkin-Huxley model based on a quantum-memristor formalism. We compare the behavior of the membrane voltage and the potassium-channel conductance when the circuit is subjected to ac sources, in both the classical realm and the quantum realm. Numerical simulations show an expected adaptation of the considered channel conductance depending on the signal history in all regimes. Remarkably, the computation of higher moments of the voltage shows purely quantum features related to the circuit zero-point energy. Finally, we study the implementation of the Hodgkin-Huxley quantum memristor as an asymmetric rf superconducting quantum-interference device in superconducting circuits. This study may allow the construction of quantum neuron networks inspired by the brain function, as well as the design of neuromorphic quantum architectures for quantum machine learning.

Real-time high-resolution three-dimensional (3D) reconstruction of scenes hidden from the direct field of view is a challenging field of research, with applications in real-life situations related, e.g., to surveillance, self-driving cars, and rescue missions. Most current techniques recover the 3D structure of a non-line-of-sight (NLOS) static scene by detecting the return signal from the hidden object on a scattering observation area. Here, we demonstrate the full color retrieval of the 3D shape of a hidden scene by coupling back-projection imaging algorithms with the high-resolution time-of-flight information provided by a single-pixel camera. By using a high-efficiency single-photon avalanche-diode (SPAD) detector, this technique provides the advantage of imaging with no mechanical scanning parts, with acquisition times down to the subsecond range.

Using point-source atom interferometry (PSI), we characterize the sensitivity of a multiaxis gyroscope based on free-space Raman interrogation of a single source of cold atoms in a glass vacuum cell. The instrument simultaneously measures the acceleration in the direction of the Raman-laser beams and the projection of the rotation vector onto the plane perpendicular to that direction. The sensitivities for the magnitude and direction of the rotation-vector measurement are ${0.033}^{\circ }/\mathrm{s}$ and ${0.27}^{\circ }$ with an averaging time of 1 s, respectively. The fractional acceleration sensitivity $\delta g/g$ is $1.6\times {10}^{-5}/\surd \mathrm{Hz}$. The sensitivity can be increased by increasing the Raman interrogation time, allowing the cold-atom cloud to expand further, correcting the fluctuations in the initial cloud shape, and reducing sources of technical noise. PSI resolves a rotation vector in a plane by measuring a phase gradient. This two-dimensional rotation sensitivity may be specifically important for applications such as tracking the precession of a rotation vector and gyrocompassing.

An electroactive biofilm is a porous layer of bacteria covering an electrode, which plays an important role in bioelectrochemical systems, such as in the microbial fuel cell. We derive a dynamic model of ion transport, biochemical reactions, and electron transport inside such a biofilm. After validating the model against data, we evaluate model output to obtain an understanding of the transport of ions and electrons through a current-producing biofilm. For a system fed with a typical wastewater stream containing organic molecules and producing 5 A ${\mathrm{m}}^{-2}$, our model predicts that transport of the organic molecules is not a limiting factor. However, the pH deep within the biofilm drops significantly, which can inhibit current production of such biofilms. Our results suggest that the electronic conductivity of the biofilm does not limit charge transport significantly, even for a biofilm as thick as 100 $\mu \mathrm{m}$. Our study provides an example of how physics-based modeling helps to understand complex coupled processes in bioelectrochemical systems.

Photon recycling is required for a solar cell to achieve an open-circuit voltage $(V_{\mathrm{OC}})$ and power conversion efficiency (PCE) approaching the Shockley-Queisser theoretical limit. The achievable performance gains from photon recycling in metal halide perovskite solar cells remain uncertain due to high variability in material quality and the nonradiative recombination rate. We quantify the enhancement due to photon recycling for state-of-the-art perovskite ${\mathrm{Cs}}_{0.05}({\mathrm{MA}}_{0.17}{\mathrm{FA}}_{0.83}{)}_{0.95}\mathrm{Pb}({\mathrm{I}}_{0.83}{\mathrm{Br}}_{0.17}{)}_3$ (triple-cation) films and corresponding solar cells. We show that, at the maximum power point (MPP), the absolute PCE can increase up to 2.0% in the radiative limit, primarily due to a 77 mV increase in $(V_{\mathrm{MPP}})$. For this photoactive layer, even with finite nonradiative recombination, benefits from photon recycling can be achieved when nonradiative lifetimes and external light-emitting diode (LED) electroluminescence efficiencies, $Q_e^{\mathrm{LED}}$, exceed 2 µs and 10%, respectively. This analysis quantifies the significance of photon recycling in boosting the real-world performance of perovskite solar cells toward theoretical limits.

We report three-dimensional (3D)-printed acoustic holographic lenses for the formation of ultrasonic fields of complex spatial distribution inside the skull. Using holographic lenses, we experimentally, numerically, and theoretically produce acoustic beams whose spatial distribution matches target structures of the central nervous system. In particular, we produce three types of targets of increasing complexity. First, a set of points are selected at the center of both right and left human hippocampi. Experiments using a skull phantom and 3D-printed acoustic holographic lenses show that the corresponding bifocal lens simultaneously focuses acoustic energy at the target foci, with good agreement between theory and simulations. Second, an arbitrary curve is set as the target inside the skull phantom. Using time-reversal methods, the holographic beam bends following the target path, in a similar way as self-bending beams do in free space. Finally, the right human hippocampus is selected as a target volume. The focus of the corresponding holographic lens overlaps with the target volume in excellent agreement between theory in free media, and experiments and simulations including the skull phantom. The precise control of focused ultrasound into the central nervous system is mainly limited due to the strong phase aberrations produced by refraction and attenuation of the skull. Using the present method, the ultrasonic beam can be focused not only at a single point but overlapping one or various target structures simultaneously using low-cost 3D-printed acoustic holographic lens. The results open alternative paths to spread incoming biomedical ultrasound applications, including blood-brain-barrier opening or neuromodulation.

There have been multiple attempts to demonstrate that quantum annealing and, in particular, quantum annealing on quantum-annealing machines, has the potential to outperform current classical optimization algorithms implemented on CMOS technologies. The benchmarking of these devices has been controversial. Initially, random spin-glass problems were used, however, these were quickly shown to be not well suited to detect any quantum speedup. Subsequently, benchmarking shifted to carefully crafted synthetic problems designed to highlight the quantum nature of the hardware while (often) ensuring that classical optimization techniques do not perform well on them. Even worse, to date a true sign of improved scaling with the number of problem variables remains elusive when compared to classical optimization techniques. Here, we analyze the readiness of quantum-annealing machines for real-world application problems. These are typically not random and have an underlying structure that is hard to capture in synthetic benchmarks, thus posing unexpected challenges for optimization techniques, both classical and quantum alike. We present a comprehensive computational scaling analysis of fault diagnosis in digital circuits, considering architectures beyond D-Wave quantum annealers. We find that the instances generated from real data in multiplier circuits are harder than other representative random spin-glass benchmarks with a comparable number of variables. Although our results show that transverse-field quantum annealing is outperformed by state-of-the-art classical optimization algorithms, these benchmark instances are hard and small in the size of the input, therefore representing the first industrial application ideally suited for testing near-term quantum annealers and other quantum algorithmic strategies for optimization problems.