搜索结果：npj quantum materials

Quantum technologies offer ways to solve certain tasks more quickly, efficiently, and with greater precision than their classical counterparts. Yet substantial challenges remain in the construction of sufficiently error-free and scalable quantum platforms needed to unlock any real benefits to society. Acknowledging that this hardware can take vastly different forms, our review here focuses on materials that bear an optically-addressable electron or nuclear spin to embody qubits. Towards helping the reader to spot trends and pick winners, we have surveyed the various families of optically addressable spin qubits and attempted to benchmark and identify the most promising ones in each. We go on to reveal further trends that demonstrate how qubit lifetimes depend on the material's synthesis, the concentration/distribution of its embedded qubits, and the experimental conditions.

The recently discovered kagome materials AV3Sb5 (A = K, Rb, Cs) attract intense research interest in intertwined topology, superconductivity, and charge density waves (CDW). Although the in-plane 2 × 2 CDW is well studied, its out-of-plane structural correlation with the Fermi surface properties is less understood. In this work, we advance the theoretical description of quantum oscillations and investigate the Fermi surface properties in the three-dimensional CDW phase of CsV3Sb5. We derived Fermi-energy-resolved and layer-resolved quantum orbits that agree quantitatively with recent experiments in the fundamental frequency, cyclotron mass, and topology. We reveal a complex Dirac nodal network that would lead to a π Berry phase of a quantum orbit in the spinless case. However, the phase shift of topological quantum orbits is contributed by the orbital moment and Zeeman effect besides the Berry phase in the presence of spin-orbital coupling (SOC). Therefore, we can observe topological quantum orbits with a π phase shift in otherwise trivial orbits without SOC, contrary to common perception. Our work reveals the rich topological nature of kagome materials and paves a path to resolve different topological origins of quantum orbits.

Quantum emitters in transition metal dichalcogenides (TMDs) have recently emerged as a promising platform for generating single photons for optical quantum information processing. In this work, we present an approach for deterministically controlling the polarization of fabricated quantum emitters in a tungsten diselenide (WSe2) monolayer. We employ novel nanopillar geometries with long and sharp tips to induce a controlled directional strain in the monolayer, and we report on fabricated WSe2 emitters producing single photons with a high degree of polarization (99 ± 4%) and high purity (g (2)(0) = 0.030 ± 0.025). Our work paves the way for the deterministic integration of TMD-based quantum emitters for future photonic quantum technologies.

Quantum nuclear effects (QNEs) can significantly alter a material's crystal structure and phonon spectra, impacting properties such as thermal conductivity and superconductivity. However, predicting a priori whether these effects will enhance or suppress superconductivity, or destabilize a structure, remains a grand challenge. Herein, we address this unresolved problem by introducing two possible descriptors, based upon the integrated crystal orbital bonding index (iCOBI) or the bond valence function, to predict the influence of QNEs on a crystal lattice's dynamic stability, phonon spectra and superconducting properties. We find that structures with atoms in symmetric chemical bonding environments exhibit greater resilience to structural perturbations induced by QNEs, while those with atoms in asymmetric bonding environments are more susceptible to structural alterations, resulting in enhanced superconducting critical temperatures.

Universal machine learning interatomic potentials (uMLIPs) have emerged as powerful tools for accelerating atomistic simulations, offering scalable and efficient modeling with accuracy close to quantum calculations. However, their reliability and effectiveness in practical, real-world applications remain an open question. Metal-organic frameworks (MOFs) and related nanoporous materials are highly porous crystals with critical relevance in carbon capture, energy storage, and catalysis applications. Modeling nanoporous materials presents distinct challenges for uMLIPs due to their diverse chemistry, structural complexity, including porosity and coordination bonds, and the absence from existing training datasets. Here, we introduce MOFSimBench, a benchmark for evaluating uMLIPs on key materials modeling tasks for nanoporous materials, including structural optimization, molecular dynamics (MD) stability, bulk property prediction, and host-guest interactions. Evaluating 20 models from various architectures, we find that top-performing uMLIPs consistently outperform classical force fields and fine-tuned machine learning potentials across all tasks, demonstrating their readiness for deployment in nanoporous materials modeling. Our analysis highlights that data quality plays a more critical role than model architecture in determining performance across all evaluated uMLIPs. We release our modular and extensible benchmarking framework at https://github.com/AI4ChemS/mofsim-bench, providing an open resource to guide the adoption for nanoporous materials modeling and further development of uMLIPs.

In materials science, we have been increasing the number of constituent elements in an alloy and compounds to improve their properties. For example, in magnetism and spintronics, ternary alloys, such as NdFeB and CoFeB have been developed and widely used in permanent magnets and memories/sensors, respectively. It has now been considered to be a time to add more elements to further explore their horizon. For such a complicated development, a manual systematic study is no longer practical, leading to the utilisation of machine learning to predict a candidate. These candidates can then be additionally screened by ab initio calculations before experimental confirmation, which can be performed routinely. Additional use of quantum annealing may also broaden the adoptability of machine learning on the materials development. In this perspective, we plan to offer a standardised process for such a development with some requirements for improvement.

Machine-learned interatomic potentials can offer near first-principles accuracy but are computationally expensive, limiting their application to large-scale molecular dynamics simulations. Inspired by quantum mechanics/molecular mechanics methods, we present ML-MIX, a CPU- and GPU-compatible LAMMPS package to accelerate simulations by spatially mixing interatomic potentials of different complexities, allowing deployment of modern MLIPs even under restricted computational budgets. We demonstrate our method for ACE, UF3, SNAP and MACE potential architectures and demonstrate how linear 'cheap' potentials can be distilled from a given 'expensive' potential, allowing close matching in relevant regions of configuration space. The functionality of ML-MIX is demonstrated through tests on point defects in Si, Fe and W-He, in which speedups of up to 11× over ~8000 atoms are demonstrated, without sacrificing accuracy. The scientific potential of ML-MIX is demonstrated via two case studies in W, measuring the mobility of b = 1 2 〈 111 〉 screw dislocations with ACE/ACE mixing and the implantation of He with MACE/SNAP mixing. The latter returns He reflection coefficients which (for the first time) match experimental observations up to an He incident energy of 80 eV-demonstrating the benefits of deploying state-of-the-art models on large, realistic systems.

We developed a general framework for hybrid quantum-classical computing of molecular and periodic embedding approaches based on an orbital space separation of the fragment and environment degrees of freedom. We demonstrate its potential by presenting a specific implementation of periodic range-separated DFT coupled to a quantum circuit ansatz, whereby the variational quantum eigensolver and the quantum equation-of-motion algorithm are used to obtain the low-lying spectrum of the embedded fragment Hamiltonian. The application of this scheme to study localized electronic states in materials is showcased through the accurate prediction of the optical properties of the neutral oxygen vacancy in magnesium oxide (MgO). Despite some discrepancies in the position of the main absorption band, the method demonstrates competitive performance compared to state-of-the-art ab initio approaches, particularly evidenced by the excellent agreement with the experimental photoluminescence emission peak.

Conventional Coulomb engineering, through controlled manipulation of the environment, offers an effective route to tune the correlation properties of atomically thin van der Waals materials via static screening. Here we present tunable dynamical screening as a method for precisely tailoring bosonic modes to optimize many-body properties. We show that "bosonic engineering" of plasmon modes can be used to enhance plasmon-induced superconducting critical temperatures of layered superconductors in metallic environments by up to an order of magnitude, due to the formation of interlayer hybridized plasmon modes with enhanced superconducting pairing strength. We determine optimal properties of the screening environment to maximize critical temperatures. We show how bosonic engineering can aid the search for experimental verification of plasmon mediated superconductivity.

Using first principles techniques, we show that infrared optical response allows us to discriminate between the topological and the trivial phases of 2D quantum spin Hall insulators (QSHI). We showcase germanene and jacutingaite, of recent experimental realization, as prototypical systems where the infrared spectrum is discontinuous across the transition, due to sudden and large discretized jumps of the Born effective charges (up to ~2). Our results, rationalized thanks to the low-energy Kane-Mele model, are robust with respect to dynamical effects, relevant when the electronic energy gap is comparable with the phonon frequency. In the small gap QSHI germanene, due to dynamical effects, the in-plane phonon resonance in the optical conductivity shows a Fano profile with remarkable differences in the intensity and the shape between different phases. Instead, the large-gap QSHI jacutingaite presents several IR-active phonon modes whose spectral intensities drastically change between different phases.

Solid-state single-photon emitters provide a versatile platform for exploring quantum technologies such as optically connected quantum networks. A key challenge is to ensure the optical coherence and spectral stability of the emitters. Here, we introduce a high-bandwidth 'check-probe' scheme to quantitatively measure (laser-induced) spectral diffusion and ionisation rates, as well as homogeneous linewidths. We demonstrate these methods on single V2 centres in commercially available bulk-grown 4H-silicon carbide. Despite observing significant spectral diffusion under laser illumination (≳GHz s-1), the optical transitions are narrow (~35 MHz), and remain stable in the dark (≳1 s). Through Landau-Zener-Stückelberg interferometry, we determine the optical coherence to be near-lifetime limited (T 2 = 16.4(4) ns), hinting at the potential for using bulk-grown materials for developing quantum technologies. These results advance our understanding of spectral diffusion of quantum emitters in semiconductor materials, and may have applications for studying charge dynamics across other platforms.

We show how looped pipeline architectures-which use short-range shuttling of physical qubits to achieve bounded non-local connectivity-can efficiently implement the fault-tolerant non-Clifford gate between 2D surface codes described in (Sci. Adv. 6, eaay4929 (2020)). The shuttling schedule required is only marginally more complex than is required for implementing the standard 2D surface code in this architecture. We compare the resource cost with the cost of magic state distillation and find that, at present, this comparison is heavily in favour of distillation. The high cost of the non-Clifford gate is largely due to the relatively low performance of the just-in-time decoder used in the procedure, which necessitates very large code distances in order to achieve suitably low logical error rates. We argue that, as little attention has been given to the study and optimisation of these decoders, there are potentially significant improvements to be made in this area.

Understanding structural flexibility of metal-organic frameworks (MOFs) via molecular dynamics simulations is crucial to design better MOFs. Density functional theory (DFT) and quantum-chemistry methods provide highly accurate molecular dynamics, but the computational overheads limit their use in long time-dependent simulations. In contrast, classical force fields struggle with the description of coordination bonds. Here we develop a DFT-accurate machine-learning spectral neighbor analysis potentials for two representative MOFs. Their structural and vibrational properties are then studied and tightly compared with available experimental data. Most importantly, we demonstrate an active-learning algorithm, based on mapping the relevant internal coordinates, which drastically reduces the number of training data to be computed at the DFT level. Thus, the workflow presented here appears as an efficient strategy for the study of flexible MOFs with DFT accuracy, but at a fraction of the DFT computational cost.

Correlated materials are known to display qualitatively distinct emergent behaviors at low energy. Conveniently, upon absorbing rapid quantum fluctuations, these rich low-energy behaviors can always be effectively described by dressed particles with fully quantized charge, spin, and orbital structure. Such a powerful and simple description is, however, difficult to access through bare particles used in most many-body computations, especially when fluctuations are strong such as in 4d and 5d compounds. To decipher the dominant quantized structure, we propose an easy-to-implement 'interaction annealing' approach that utilizes suppressed charge fluctuation through enhancing ionic charging energy. We establish its theoretical foundation using an exactly treated two-site Hubbard model as a generic example. We then demonstrate its applications with more affordable density functional calculations to a representative 3d Mott insulator La2CuO4 and a highly fluctuating 5d semi-metal WTe2. In the latter, it reveals an emergent local electronic structure that makes possible an unprecedented explanation of several experimental observations. Finally, we demonstrate the effectiveness of this approach in studying competing local electronic structures in functional materials.

Polytypism in transition metal dichalcogenides (TMDs) introduces an additional degree of freedom for tailoring the electronic properties of layered van der Waals materials. Polytypes with larger unit cells, spanning four or six layers, can be viewed as natural homostructures, since their atomic composition remains identical across the layers. The resultant crystalline environments can potentially give rise to exotic electronic states, earning these materials recent attention. In this study, we examine structural and charge transport properties of metallic and superconducting 4Ha-NbSe2. We find that the compound has a highly disordered stacking of layers, which impedes interlayer coherence, as demonstrated by detailed out-of-plane resistivity measurements, and effectively tunes the bulk system towards an atomically thin limit. The disordered structure largely accounts for the enhanced resistivity anisotropy and superconducting upper critical field, when compared to 2Ha-NbSe2. This phenomenon can be exploited to promote quasi-two-dimensional physics in bulk crystals, and our study also underscores the importance of thorough structural characterization when investigating large-unit-cell polytypes of TMDs.

We introduce a novel material for integrated photonics and investigate aluminum gallium nitride (AlGaN) on aluminum nitride (AlN) templates as a platform for developing reconfigurable and on-chip nonlinear optical devices. AlGaN combines compatibility with standard photonic fabrication technologies and high electro-optic modulation capabilities with low loss over a broad spectral range, from UVC to long-wave infrared, making it a viable material for complex photonic applications. In this work, we design and grow AlGaN/AlN heterostructures and integrate several photonic components. In particular, we fabricate edge couplers, low-loss waveguides, directional couplers, and tunable high-quality factor ring resonators. These devices will enable nonlinear light-matter interaction and quantum functionality. The comprehensive platform we present in this work paves the way for photon-pair generation applications, on-chip quantum frequency conversion, and fast electro-optic modulation for switching and routing classical and quantum light fields.

Optically trapped silica nanoparticles are a promising tool for precise sensing of gravitational or inertial forces and fundamental physics, including tests of quantum mechanics at "large" mass scales. This field, called levitated optomechanics can greatly benefit from an application in weightlessness. In this paper, we demonstrate the feasibility of such setups in a microgravity environment for the first time. Our experiment is operated in the GraviTower Bremen that provides up to 2.5 s of free fall. System performance and first release-recapture experiments, where the particle is no longer trapped, are conducted in microgravity. This demonstration should also be seen in the wider context of preparing space missions on the topic of levitated optomechanics.

We measure and analyze noise-induced energy-fluctuations of spin qubits defined in quantum dots made of isotopically natural silicon. Combining Ramsey, time-correlation of single-shot measurements, and CPMG experiments, we cover the qubit noise power spectrum over a frequency range of nine orders of magnitude without any gaps. We find that the low-frequency noise spectrum is similar across three different devices suggesting that it is dominated by the hyperfine coupling to nuclei. The effects of charge noise are smaller, but not negligible, and are device dependent as confirmed from the noise cross-correlations. We also observe differences to spectra reported in GaAs [Phys. Rev. Lett. 118, 177702 (2017), Phys. Rev. Lett. 101, 236803 (2008)], which we attribute to the presence of the valley degree of freedom in silicon. Finally, we observe T 2 * to increase upon increasing the external magnetic field, which we speculate is due to the increasing field gradient of the micromagnet suppressing nuclear spin diffusion.

Quantum magnonics investigates the quantum-mechanical properties of magnons, such as quantum coherence or entanglement for solid-state quantum information technologies at the nanoscale. The most promising material for quantum magnonics is the ferrimagnetic yttrium iron garnet (YIG), which hosts magnons with the longest lifetimes. YIG films of the highest quality are grown on a paramagnetic gadolinium gallium garnet (GGG) substrate. The literature has reported that ferromagnetic resonance (FMR) frequencies of YIG/GGG decrease at temperatures below 50 K despite the increase in YIG magnetization. We investigated a 97 nm-thick YIG film grown on 500 μm-thick GGG substrate through a series of experiments conducted at temperatures as low as 30 mK, and using both analytical and numerical methods. Our findings suggest that the primary factor contributing to the FMR frequency shift is the stray magnetic field created by the partially magnetized GGG substrate. This stray field is antiparallel to the applied external field and is highly inhomogeneous, reaching up to 40 mT in the center of the sample. At temperatures below 500 mK, the GGG field exhibits a saturation that cannot be described by the standard Brillouin function for a paramagnet. Including the calculated GGG field in the analysis of the FMR frequency versus temperature dependence allowed the determination of the cubic and uniaxial anisotropies. We find that the total crystallographic anisotropy increases more than three times with the decrease in temperature down to 2 K. Our findings enable accurate predictions of the YIG/GGG magnetic systems behavior at low and ultralow millikelvin temperatures, crucial for developing quantum magnonic devices.