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Spin qubits are considered to be among the most promising candidates for building a quantum processor. Group IV hole spin qubits are particularly interesting owing to their ease of operation and compatibility with Si technology. In addition, Ge offers the option for monolithic superconductor–semiconductor integration. Here, we demonstrate a hole spin qubit operating at fields below 10 mT, the critical field of Al, by exploiting the large out-of-plane hole g -factors in planar Ge and by encoding the qubit into the singlet-triplet states of a double quantum dot. We observe electrically controlled g -factor difference-driven and exchange-driven rotations with tunable frequencies exceeding 100 MHz and dephasing times of 1 μs, which we extend beyond 150 μs using echo techniques. These results demonstrate that Ge hole singlet-triplet qubits are competing with state-of-the-art GaAs and Si singlet-triplet qubits. In addition, their rotation frequencies and coherence are comparable with those of Ge single spin qubits, but singlet-triplet qubits can be operated at much lower fields, emphasizing their potential for on-chip integration with superconducting technologies. A singlet-triplet spin qubit using holes in a Ge quantum well is demonstrated, and can be operated at low magnetic fields of a few millitesla.

Charge noise in the host semiconductor degrades the performance of spin-qubits and poses an obstacle to control large quantum processors. However, it is challenging to engineer the heterogeneous material stack of gate-defined quantum dots to improve charge noise systematically. Here, we address the semiconductor-dielectric interface and the buried quantum well of a 28 Si/SiGe heterostructure and show the connection between charge noise, measured locally in quantum dots, and global disorder in the host semiconductor, measured with macroscopic Hall bars. In 5 nm thick 28 Si quantum wells, we find that improvements in the scattering properties and uniformity of the two-dimensional electron gas over a 100 mm wafer correspond to a significant reduction in charge noise, with a minimum value of 0.29 ± 0.02 μeV/Hz ½ at 1 Hz averaged over several quantum dots. We extrapolate the measured charge noise to simulated dephasing times to CZ -gate fidelities that improve nearly one order of magnitude. These results point to a clean and quiet crystalline environment for integrating long-lived and high-fidelity spin qubits into a larger system. Charge noise degrades the performance of spin qubits hindering scalability. Here the authors engineer the heterogeneous material stack in 28 Si/SiGe gate-defined quantum dots, to improve the scattering properties and to reduce charge noise.

Hybrid semiconductor–superconductor devices hold great promise for realizing topological quantum computing with Majorana zero modes 1 – 5 . However, multiple claims of Majorana detection, based on either tunnelling 6 – 10 or Coulomb blockade (CB) spectroscopy 11 , 12 , remain disputed. Here we devise an experimental protocol that allows us to perform both types of measurement on the same hybrid island by adjusting its charging energy via tunable junctions to the normal leads. This method reduces ambiguities of Majorana detections by checking the consistency between CB spectroscopy and zero-bias peaks in non-blockaded transport. Specifically, we observe junction-dependent, even–odd modulated, single-electron CB peaks in InAs/Al hybrid nanowires without concomitant low-bias peaks in tunnelling spectroscopy. We provide a theoretical interpretation of the experimental observations in terms of low-energy, longitudinally confined island states rather than overlapping Majorana modes. Our results highlight the importance of combined measurements on the same device for the identification of topological Majorana zero modes. Valentini et al. devise a method through which they can perform both tunnelling spectroscopy and Coulomb blockade spectroscopy on the same hybrid nanowire island to reduce ambiguities in the detection of Majorana.

High kinetic inductance superconductors are gaining increasing interest for the realisation of qubits, amplifiers and detectors. Moreover, thanks to their high impedance, quantum buses made of such materials enable large zero-point fluctuations of the voltage, boosting the coupling rates to spin and charge qubits. However, fully exploiting the potential of disordered or granular superconductors is challenging, as their inductance and, therefore, impedance at high values are difficult to control. Here, we report a reproducible fabrication of granular aluminium resonators by developing a wireless ohmmeter, which allows in situ measurements during film deposition and, therefore, control of the kinetic inductance of granular aluminium films. Reproducible fabrication of circuits with impedances (inductances) exceeding 13 k Ω (1 nH per square) is now possible. By integrating a 7.9 k Ω resonator with a germanium double quantum dot, we demonstrate strong charge-photon coupling with a rate of g c /2 π  = 566 ± 2 MHz. This broadly applicable method opens the path for novel qubits and high-fidelity, long-distance two-qubit gates. Recently, disordered or granular superconductors have gained attention for their applications in quantum devices. Here the authors report a reproducible method to fabricate high-impedance granular Al resonators, followed by integration with quantum dot devices, achieving record hole-photon coupling strength.

The co-integration of spin, superconducting, and topological systems is emerging as an exciting pathway for scalable and high-fidelity quantum information technology. High-mobility planar germanium is a front-runner semiconductor for building quantum processors with spin-qubits, but progress with hybrid superconductor-semiconductor devices is hindered by the difficulty in obtaining a superconducting hard gap, that is, a gap free of subgap states. Here, we address this challenge by developing a low-disorder, oxide-free interface between high-mobility planar germanium and a germanosilicide parent superconductor. This superconducting contact is formed by the thermally-activated solid phase reaction between a metal, platinum, and the Ge/SiGe semiconductor heterostructure. Electrical characterization reveals near-unity transparency in Josephson junctions and, importantly, a hard induced superconducting gap in quantum point contacts. Furthermore, we demonstrate phase control of a Josephson junction and study transport in a gated two-dimensional superconductor-semiconductor array towards scalable architectures. These results expand the quantum technology toolbox in germanium and provide new avenues for exploring monolithic superconductor-semiconductor quantum circuits towards scalable quantum information processing. The difficulty in obtaining a superconducting gap free of subgap states has hindered progress with hybrid superconductor-semiconductor devices in germanium. Here, this challenge is addressed by using a germanosilicide parent superconductor to contact high mobility planar germanium, facilitating scalable quantum information processing.

Strain relaxation mechanisms during epitaxial growth of core-shell nanostructures play a key role in determining their morphologies, crystal structure and properties. To unveil those mechanisms, we perform atomic-scale aberration-corrected scanning transmission electron microscopy studies on planar core-shell ZnSe@ZnTe nanowires on α-Al 2 O 3 substrates. The core morphology affects the shell structure involving plane bending and the formation of low-angle polar boundaries. The origin of this phenomenon and its consequences on the electronic band structure are discussed. We further use monochromated valence electron energy-loss spectroscopy to obtain spatially resolved band-gap maps of the heterostructure with sub-nanometer spatial resolution. A decrease in band-gap energy at highly strained core-shell interfacial regions is found, along with a switch from direct to indirect band-gap. These findings represent an advance in the sub-nanometer-scale understanding of the interplay between structure and electronic properties associated with highly mismatched semiconductor heterostructures, especially with those related to the planar growth of heterostructured nanowire networks. Planar growth of nanowire arrays involves interactions between materials that affect the electronic behavior of the effective heterojunction. Here, authors show how core curvature and cross-section morphology affect shell growth, demonstrating how strain at the core-shell interface induces electronic band modulations in ZnSe@ZnTe nanowires.

Materials science has traditionally relied on a combination of experimental techniques and theoretical modeling to discover and develop new materials with desired properties. However, these processes can be time‐consuming, resource‐intensive, and often limited by the complexity of material systems. The advent of artificial intelligence (AI), particularly machine learning, has revolutionized materials science by offering powerful tools to accelerate the discovery, design, and characterization of novel materials. AI not only enhances the predictive modeling of material properties but also streamlines data analysis in techniques like X‐Ray diffraction, Raman spectroscopy, scanning probe microscopy, and electron microscopy. By leveraging large datasets, AI algorithms can identify patterns, reduce noise, and predict material behavior with unprecedented accuracy. In this review, recent advancements in AI applications across various domains of materials science, including spectroscopy, synchrotron studies, scanning probe and electron microscopies, metamaterials, atomistic modeling, molecular design, and drug discovery, are highlighted. It is discussed how AI‐driven methods are reshaping the field, making material discovery more efficient, and paving the way for breakthroughs in material design and real‐time experimental analysis. AI‐driven methods are transforming materials science by accelerating material discovery, design, and analysis, leveraging large datasets to enhance predictive modeling and streamline experimental techniques. This review highlights advancements in AI applications across spectroscopy, microscopy, and molecular design, enabling efficient material development and real‐time experimental breakthroughs.

Strong Metal‐Support Interaction (SMSI) is a key concept in heterogeneous catalysis, but it remains underexplored in the context of photon‐to‐hydrogen conversion, as coupling of metallic nanoparticles with photocatalysts is overlooked and only discussed in terms of Schottky barrier formation. In this study, we provide deep insights into the effect of Au encapsulation with TiO2 overlayer on enhancing photocatalytic hydrogen generation. Our findings reveal that the construction of a SMSI‐like nanostructure induces the formation of oxygen vacancies at the Au‒TiO2 interface which actively facilitate charge carrier separation through interfacial band reconstruction. The presence of defects is evidenced by Electron Paramagnetic Resonance and X‐ray Photoelectron Spectroscopy, unveiling their relationship with photocatalytic activities. Consistent with experimental results, Density Functional Theory (DFT) calculations demonstrate that Au promotes oxygen vacancy formation. These vacancies located at the TiO2 surface significantly enhances H2O and MeOH adsorption during H2 evolution reactions. The SMSI‐like concept was extended to Pt, Pd, and Ag, in which the oxygen vacancy formation energy at the metal‐semiconductor interface varied depending on the metal, as computed by DFT. The results suggest that photocatalytic activity is related to the ease of oxygen vacancy formation, which is influenced by the nature of the metals. In this work, the oxygen vacancy formation is reported at the Au‐TiO2 interface in strong metal‐support interaction (SMSI) photocatalyst. The oxygen vacancies faciliate electron transfer and favor the adsorption of water and methanol at photocatalyst surface, thus enhancing the kinetic of photocatalytic hydrogen generation. The SMSI concept is extended to Pt, Pd, and Ag, in which the formation energy of oxygen vacancies at the metal‐semiconductor interface varied depending on the metal. The results indicate that the ease and the localization of oxygen vacancy formation is a critical factor governing photocatalytic acitivity.

The electrical characterisation of classical and quantum devices is a critical step in the development cycle of heterogeneous material stacks for semiconductor spin qubits. In the case of silicon, properties such as disorder and energy separation of conduction band valleys are commonly investigated individually upon modifications in selected parameters of the material stack. However, this reductionist approach fails to consider the interdependence between different structural and electronic properties at the danger of optimising one metric at the expense of the others. Here, we achieve a significant improvement in both disorder and valley splitting by taking a co-design approach to the material stack. We demonstrate isotopically purified, strained quantum wells with high mobility of 3.14(8) × 10 5  cm 2  V −1  s −1 and low percolation density of 6.9(1) × 10 10  cm −2 . These low disorder quantum wells support quantum dots with low charge noise of 0.9(3) μeV Hz −1/2 and large mean valley splitting energy of 0.24(7) meV, measured in qubit devices. By striking the delicate balance between disorder, charge noise, and valley splitting, these findings provide a benchmark for silicon as a host semiconductor for quantum dot qubits. We foresee the application of these heterostructures in larger, high-performance quantum processors.