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A central challenge in quantum networking is transferring quantum states between different physical modalities, such as between flying photonic qubits and stationary quantum memories. One implementation entails using spin–photon interfaces that combine solid-state spin qubits, such as color centers in diamond, with photonic nanostructures. However, while high-fidelity spin–photon interactions have been demonstrated on isolated devices, building practical quantum repeaters requires scaling to large numbers of interfaces yet to be realized. Here, we demonstrate integration of nanophotonic cavities containing tin-vacancy (SnV) centers in a photonic integrated circuit (PIC). Out of a six-channel quantum microchiplet (QMC), we find four coupled SnV-cavity devices with an average Purcell factor of ∼7. Based on system analyses and numerical simulations, we find with near-term improvements this multiplexed architecture can enable high-fidelity quantum state transfer, paving the way toward building large-scale quantum repeaters.

 

We demonstrate heterogeneous integration of solid-state nanophotonic cavities into a scalable photonic platform as an efficient optical interface for quantum memories based on diamond color centers.

 

Soft materials are usually defined as materials made of mesoscopic entities, often self-organised, sensitive to thermal fluctuations and to weak perturbations. Archetypal examples are colloids, polymers, amphiphiles, liquid crystals, foams. The importance of soft materials in everyday commodity products, as well as in technological applications, is enormous, and controlling or improving their properties is the focus of many efforts. From a fundamental perspective, the possibility of manipulating soft material properties, by tuning interactions between constituents and by applying external perturbations, gives rise to an almost unlimited variety in physical properties. Together with the relative ease to observe and characterise them, this renders soft matter systems powerful model systems to investigate statistical physics phenomena, many of them relevant as well to hard condensed matter systems. Understanding the emerging properties from mesoscale constituents still poses enormous challenges, which have stimulated a wealth of new experimental approaches, including the synthesis of new systems with, e.g. tailored self-assembling properties, or novel experimental techniques in imaging, scattering or rheology. Theoretical and numerical methods, and coarse-grained models, have become central to predict physical properties of soft materials, while computational approaches that also use machine learning tools are playing a progressively major role in many investigations. This Roadmap intends to give a broad overview of recent and possible future activities in the field of soft materials, with experts covering various developments and challenges in material synthesis and characterisation, instrumental, simulation and theoretical methods as well as general concepts. 

We present an efficient microwave and optical interface for quantum memories at 1.3 K based on tin-vacancy color centers in diamond and scalable integrated photonics.

 

Highly efficient air electrodes are a key component of reversible fuel cells for energy storage and conversion; however, the development of efficient electrodes that are stable against water vapor remains a grand challenge. Here we report an air–electrode, composed of double perovskite material PrBa 0.8 Ca 0.2 Co 2 O 5+δ (PBCC) backbone coated with nanoparticles (NPs) of BaCoO 3−δ (BCO), that exhibits remarkable electrocatalytic activity for oxygen reduction reaction (ORR) while maintaining excellent tolerance to water vapor. When tested in a symmetrical cell exposed to wet air with 3 vol% H 2 O at 750 °C, the electrode shows an area specific resistance of ∼0.03 Ω cm 2 in an extended period of time. The performance enhancement is attributed mainly to the electrocatalytic activity of the BCO NPs dispersed on the surface of the porous PBCC electrode. Moreover, in situ Raman spectroscopy is used to probe reaction intermediates ( e.g. , oxygen species) on electrode surfaces, as the electrochemical properties of the electrodes are characterized under the same conditions. The direct correlation between surface chemistry and electrochemical behavior of an electrode is vital to gaining insight into the mechanisms of the electrocatalytic processes in fuel cells and electrolysers. 

Co$$_{3}$$${}_3$Sn$$_{2}$$${}_2$S$$_{2}$$${}_2$is a ferromagnetic Weyl semimetal that has been the subject of intense scientific interest due to its large anomalous Hall effect. We show that the coupling of this material’s topological properties to its magnetic texture leads to a strongly exchange biased anomalous Hall effect. We argue that this is likely caused by the coexistence of ferromagnetism and geometric frustration intrinsic to the kagome network of magnetic ions, giving rise to spin-glass behavior and an exchange bias.

 

This work probes the slurry architecture of a high silicon content electrode slurry with and without low molecular weight polymeric dispersants as a function of shear rate to mimic electrode casting conditions for poly(acrylic acid) (PAA) and lithium neutralized poly(acrylic acid) (LiPAA) based electrodes. Rheology coupled ultra‐small angle neutron scattering (rheo‐USANS) was used to examine the aggregation and agglomeration behavior of each slurry as well as the overall shape of the aggregates. The addition of dispersant has opposing effects on slurries made with PAA or LiPAA binder. With a dispersant, there are fewer aggregates and agglomerates in the PAA based silicon slurries, while LiPAA based silicon slurries become orders of magnitude more aggregated and agglomerated at all shear rates. The reorganization of the PAA and LiPAA binder in the presence of dispersant leads to a more homogeneous slurry and a more heterogeneous slurry, respectively. This reorganization ripples through to the cast electrode architecture and is reflected in the electrochemical cycling of these electrodes.