Majorana-like Coulomb spectroscopy in the absence of zero-bias peaks.

Hybrid semiconductor-superconductor devices hold great promise for realizing topological quantum computing with Majorana zero modes1-5. However, multiple claims of Majorana detection, based on either tunnelling6-10 or Coulomb blockade (CB) spectroscopy11,12, 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.

Is Soft Carbon a More Suitable Match for SiOx in Li-Ion Battery Anodes?

Silicon oxide (SiOx ), inheriting the high-capacity characteristic of silicon-based materials but possessing superior cycling stability, is a promising anode material for next-generation Li-ion batteries. SiOx is typically applied in combination with graphite (Gr), but the limited cycling durability of the SiOx /Gr composites curtails large-scale applications. In this work, this limited durability is demonstrated in part related to the presence of a bidirectional diffusion at the SiOx /Gr interface, which is driven by their intrinsic working potential differences and the concentration gradients. When Li on the Li-rich surface of SiOx is captured by Gr, the SiOx surface shrinks, hindering further lithiation. The use of soft carbon (SC) instead of Gr can prevent such instability is further demonstrated. The higher working potential of SC avoids bidirectional diffusion and surface compression thus allowing further lithiation. In this scenario, the evolution of the Li concentration gradient in SiOx conforms to its spontaneous lithiation process, benefiting the electrochemical performance. These results highlight the focus on the working potential of carbon as a strategy for rational optimization of SiOx /C composites toward improved battery performance.

A singlet-triplet hole spin qubit in planar Ge.

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.

Ballistic InSb Nanowires and Networks via Metal-Sown Selective Area Growth.

Selective area growth is a promising technique to realize semiconductor-superconductor hybrid nanowire networks, potentially hosting topologically protected Majorana-based qubits. In some cases, however, such as the molecular beam epitaxy of InSb on InP or GaAs substrates, nucleation and selective growth conditions do not necessarily overlap. To overcome this challenge, we propose a metal-sown selective area growth (MS SAG) technique, which allows decoupling selective deposition and nucleation growth conditions by temporarily isolating these stages. It consists of three steps: (i) selective deposition of In droplets only inside the mask openings at relatively high temperatures favoring selectivity, (ii) nucleation of InSb under Sb flux from In droplets, which act as a reservoir of group III adatoms, done at relatively low temperatures, favoring nucleation of InSb, and (iii) homoepitaxy of InSb on top of the formed nucleation layer under a simultaneous supply of In and Sb fluxes at conditions favoring selectivity and high crystal quality. We demonstrate that complex InSb nanowire networks of high crystal and electrical quality can be achieved this way. We extract mobility values of 10 000-25 000 cm2 V-1 s-1 consistently from field-effect and Hall mobility measurements across single nanowire segments as well as wires with junctions. Moreover, we demonstrate ballistic transport in a 440 nm long channel in a single nanowire under a magnetic field below 1 T. We also extract a phase-coherent length of ∼8 µm at 50 mK in mesoscopic rings.

Enhanced Oxygen Evolution and Zinc-Air Battery Performance via Electronic Spin Modulation in Heterostructured Catalysts.

Beyond optimizing electronic energy levels, the modulation of the electronic spin configuration is an effective strategy, often overlooked, to boost activity and selectivity in a range of catalytic reactions, including the oxygen evolution reaction (OER). This electronic spin modulation is frequently accomplished using external magnetic fields, which makes it impractical for real applications. Herein, spin modulation is achieved by engineering Ni/MnFe2O4 heterojunctions, whose surface is reconstructed into NiOOH/MnFeOOH during the OER. NiOOH/MnFeOOH shows a high spin state of Ni, which regulates the OH- and O2 adsorption energy and enables spin alignment of oxygen intermediates. As a result, NiOOH/MnFeOOH electrocatalysts provide excellent OER performance with an overpotential of 261 mV at 10 mA cm-2. Besides, rechargeable zinc-air batteries based on Ni/MnFe2O4 show a high open circuit potential of 1.56 V and excellent stability for more than 1000 cycles. This outstanding performance is rationalized using density functional theory calculations, which show that the optimal spin state of both Ni active sites and oxygen intermediates facilitates spin-selected charge transport, optimizes the reaction kinetics, and decreases the energy barrier to the evolution of oxygen. This study provides valuable insight into spin polarization modulation by heterojunctions enabling the design of next-generation OER catalysts with boosted performance.

Enhanced Electrochemical Hydrogenation of Benzaldehyde to Benzyl Alcohol on Pd@Ni-MOF by Modifying the Adsorption Configuration.

Electrocatalytic hydrogenation (ECH) approaches under ambient temperature and pressure offer significant potential advantages over thermal hydrogenation processes but require highly active and efficient hydrogenation electrocatalysts. The performance of such hydrogenation electrocatalysts strongly depends not only on the active phase but also on the architecture and surface chemistry of the support material. Herein, Pd nanoparticles supported on a nickel metal-organic framework (MOF), Ni-MOF-74, are prepared, and their activity toward the ECH of benzaldehyde (BZH) in a 3 M acetate (pH 5.2) aqueous electrolyte is explored. An outstanding ECH rate up to 283 µmol cm-2 h-1 with a Faradaic efficiency (FE) of 76% is reached. Besides, higher FEs of up to 96% are achieved using a step-function voltage. Materials Studio and density functional theory calculations show these outstanding performances to be associated with the Ni-MOF support that promotes H-bond formation, facilitates water desorption, and induces favorable tilted BZH adsorption on the surface of the Pd nanoparticles. In this configuration, BZH is bonded to the Pd surface by the carbonyl group rather than through the aromatic ring, thus reducing the energy barriers of the elemental reaction steps and increasing the overall reaction efficiency.

Cobalt-Iron Oxyhydroxide Obtained from the Metal Phosphide: A Highly Effective Electrocatalyst for the Oxygen Evolution Reaction at High Current Densities.

The development of high current density anodes for the oxygen evolution reaction (OER) is fundamental to manufacturing practical and reliable electrochemical cells. In this work, we have developed a bimetallic electrocatalyst based on cobalt-iron oxyhydroxide that shows outstanding performance for water oxidation. Such a catalyst is obtained from cobalt-iron phosphide nanorods that serve as sacrificial structures for the formation of a bimetallic oxyhydroxide through phosphorous loss concomitantly to oxygen/hydroxide incorporation. CoFeP nanorods are synthesized using a scalable method using triphenyl phosphite as a phosphorous precursor. They are deposited without the use of binders on nickel foam to enable fast electron transport, a highly effective surface area, and a high density of active sites. The morphological and chemical transformation of the CoFeP nanoparticles is analyzed and compared with the monometallic cobalt phosphide in alkaline media and under anodic potentials. The resulting bimetallic electrode presents a Tafel slope as low as 42 mV dec-1 and low overpotentials for OER. For the first time, an anion exchange membrane electrolysis device with an integrated CoFeP-based anode was tested at a high current density of 1 A cm-2, demonstrating excellent stability and Faradaic efficiency near 100%. This work opens up a way for using metal phosphide-based anodes for practical fuel electrosynthesis devices.

Reducing charge noise in quantum dots by using thin silicon quantum wells.

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 28Si/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 28Si 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/Hz½ 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.

Machine learning in electron microscopy for advanced nanocharacterization: current developments, available tools and future outlook.

In the last few years, electron microscopy has experienced a new methodological paradigm aimed to fix the bottlenecks and overcome the challenges of its analytical workflow. Machine learning and artificial intelligence are answering this call providing powerful resources towards automation, exploration, and development. In this review, we evaluate the state-of-the-art of machine learning applied to electron microscopy (and obliquely, to materials and nano-sciences). We start from the traditional imaging techniques to reach the newest higher-dimensionality ones, also covering the recent advances in spectroscopy and tomography. Additionally, the present review provides a practical guide for microscopists, and in general for material scientists, but not necessarily advanced machine learning practitioners, to straightforwardly apply the offered set of tools to their own research. To conclude, we explore the state-of-the-art of other disciplines with a broader experience in applying artificial intelligence methods to their research (e.g., high-energy physics, astronomy, Earth sciences, and even robotics, videogames, or marketing and finances), in order to narrow down the incoming future of electron microscopy, its challenges and outlook.

Sub-nanometer mapping of strain-induced band structure variations in planar nanowire core-shell heterostructures.

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-Al2O3 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.