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Light-emitting electrochemical cells (LECs) are promising candidates for fully solution-processed lighting applications because they can comprise a single active-material layer and air-stable electrodes. While their performance is often claimed to be independent of the electrode material selection due to the in-situ formation of electric double layers (EDLs), we demonstrate conceptually and experimentally that this understanding needs to be modified. Specifically, the exciton generation zone is observed to be affected by the electrode work function. We rationalize this finding by proposing that the ion concentration in the injection-facilitating EDLs depends on the offset between the electrode work function and the respective semiconductor orbital, which in turn influences the number of ions available for electrochemical doping and hence shifts the exciton generation zone. Further, we investigate the effects of the electrode selection on exciton losses to surface plasmon polaritons and discuss the impact of cavity effects on the exciton density. We conclude by showing that the measured electrode-dependent LEC luminance transients can be replicated by an optical model that considers these electrode-dependent effects to calculate the attained light outcoupling of the LEC stack. As such, our findings provide rational design criteria considering the electrode materials, the active-material thickness, and its composition in concert to achieve optimum LEC performance.

Flexible photovoltaics with a lightweight and adaptable nature that allows for deployment on curved surfaces and in building facades have always been a goal vigorously pursued by researchers in thin-film solar cell technology. The recent strides made in improving the sunlight-to-electricity conversion efficiency of kesterite Cu$_{2}$ZnSn(S, Se)$_{4}$ (CZTSSe) suggest it to be a perfect candidate. However, making use of rare Mo foil in CZTSSe solar cells causes severe problems in thermal expansion matching, uneven grain growth, and severe problems at the back contact of the devices. Herein, a strategy utilizing single-crystal graphene to modify the back interface of flexible CZTSSe solar cells is proposed. It will be shown that the insertion of graphene at the Mo foil/CZTSSe interface provides strong physical support for the subsequent deposition of the CZTSSe absorber layer, improving the adhesion between the absorber layer and the Mo foil substrate. Additionally, the graphene passivates the rough sites on the surface of the Mo foil, enhancing the chemical homogeneity of the substrate, and resulting in a more crystalline and homogeneous CZTSSe absorber layer on the Mo foil substrate. The detrimental reaction between Mo and CZTSSe has also been eliminated. Through an analysis of the electrical properties, it is found that the introduction of graphene at the back interface promotes the formation of a quasi-ohmic contact at the back contact, decreasing the back contact barrier of the solar cell, and leading to efficient collection of charges at the back interface. This investigation demonstrates that solution-based CZTSSe photovoltaic devices could form the basis of cheap and flexible solar cells.

Generalizing to novel classes unseen during training is a key challenge of few-shot classification. Recent metric-based methods try to address this by local representations. However, they are unable to take full advantage of them due to (i) improper supervision for pretraining the feature extractor, and (ii) lack of adaptability in the metric for handling various possible compositions of local feature sets. In this work, we unleash the power of local representations in improving novel-class generalization. For the feature extractor, we design a novel pretraining paradigm that learns randomly cropped patches by soft labels. It utilizes the class-level diversity of patches while diminishing the impact of their semantic misalignments to hard labels. To align network output with soft labels, we also propose a UniCon KL-Divergence that emphasizes the equal contribution of each base class in describing "non-base" patches. For the metric, we formulate measuring local feature sets as an entropy-regularized optimal transport problem to introduce the ability to handle sets consisting of homogeneous elements. Furthermore, we design a Modulate Module to endow the metric with the necessary adaptability. Our method achieves new state-of-the-art performance on three popular benchmarks. Moreover, it exceeds state-of-the-art transductive and cross-modal methods in the fine-grained scenario.

We investigate the utilization of a single generalized dephasing qubit for sensing a quantum reservoir, where the antisymmetric coupling between the qubit and its reservoir is broken. It is found that in addition to the decay factor encoding channel, the antisymmetric coupling breaking gives rise to another phase factor encoding channel. We introduce an optimal measurement for the generalized dephasing qubit which enables the practical measurement precision to reach the theoretical ultimate precision quantified by the quantum signal-to-noise ratio (QSNR). As an example, the generalized dephasing qubit is employed to estimate the $s$-wave scattering length of an atomic Bose-Einstein condensate. It is found that the phase-induced QSNR caused by the antisymmetric coupling breaking is at least two orders of magnitude higher than the decay-induced QSNR at the millisecond timescale and the optimal relative error can achieve a scaling $\propto 1/t$ with $t$ being the encoding time in long-term encoding. Our work opens a way for supersensitive sensing of quantum reservoirs.

Polarizability is closely related to many fundamental characteristics of molecular systems and plays an indispensable role in simulating the Raman spectra. However, the calculations of polarizability for large systems still suffers from the limitations of processing ability of the quantum mechanical (QM) methods. This work assessed and compared the accuracy of the bond polarizability model (BPM) and a ML-based atomic polarizability model (AlphaML) in predicting polarizability of alkanes and then also investigated the ability of simulating Raman spectra. We found that the AlphaML has appreciable advantages over the BPM in learning the polarizability in the training data set and predicting polarizability of molecules that configurational differently from training structures. In addition, the BPM has inherent disadvantages in predicting polarizability anisotropy due to many factors including large uncertainties of estimating bond anisotropy, omitting of off-diagonal parameters in the construction of the model. As a result, the BPM has larger errors than the AlphaML in the simulation of anisotropic Raman scattering. Finally, we demonstrated that both the BPM and AlphaML suffer from transference to alkanes larger than those used in the training data sets, but the problem for the AlphaML can be circumvented by exploring more proper training structures., Comment: 37 pages, 10 figures

We propose a theoretical scheme for quantum sensing of temperature close to absolute zero in a quasi-one-dimensional Bose-Einstein condensate (BEC). In our scheme, a single-atom impurity qubit is used as a temper-ature sensor. We investigate the sensitivity of the single-atom sensor in estimating the temperature of the BEC. We demonstrate that the sensitivity of the temperature sensor can saturate the quantum Cramer-Rao bound by means of measuring quantum coherence of the probe qubit. We study the temperature sensing performance by the use of quantum signal-to-noise ratio (QSNR). It is indicated that there is an optimal encoding time that the QSNR can reach its maximum in the full-temperature regime. In particular, we find that the QSNR reaches a finite upper bound in the weak coupling regime even when the temperature is close to absolute zero, which implies that the sensing-error-divergence problem is avoided in our scheme. Our work opens a way for quantum sensing of temperature close to absolute zero in the BEC., Comment: 9 pages,9 figures

In this paper, by using a phase-change lattice Boltzmann (LB) model coupled with an electric field model, we numerically investigate the performance and enhancement mechanism of pool boiling of dielectric fluids on pillar-structured surfaces under an electric field. The numerical investigation reveals that applying an electric field causes both positive and negative influences on the pool boiling of dielectric fluids on pillar-structured surfaces. It is found that, under the action of an electric field, the electric force prevents the bubbles nucleated in the channels from crossing the edges of the pillar tops. On the one hand, such an effect results in the bubble coalescence in the channels and blocks the paths of liquid supply for the channels, which leads to the deterioration of pool boiling in the medium-superheat regime. On the other hand, it prevents the coalescence between the bubbles in the channels and those on the pillar tops, which suppresses the formation of a continuous vapor film and therefore delays the occurrence of boiling crisis. Meanwhile, the electric force can promote the departure of the bubbles on the pillar tops. Accordingly, the critical heat flux (CHF) can be improved. Based on the revealed mechanism, wettability-modified regions are applied to the pillar tops for further enhancing the boiling heat transfer. It is shown that the boiling performance on pillar-structured surfaces can be enhanced synergistically with the CHF being increased by imposing an electric field and the maximum heat transfer coefficient being improved by applying mixed wettability to the pillar-structured surfaces., Comment: 29 pages, 16 figures

Quantum key distribution (QKD) provides an information-theoretically secure method to share keys between legitimate users. To achieve large-scale deployment of QKD, it should be easily scalable and cost-effective. The infrastructure construction of quantum access network (QAN) expands network capacity and the integration between QKD and classical optical communications reduces the cost of channel. Here, we present a practical downstream QAN over a 10 Gbit/s Ethernet passive optical network (10G-EPON), which can support up to 64 users. In the full coexistence scheme using the single feeder fiber structure, the co-propagation of QAN and 10G-EPON signals with 9 dB attenuation is achieved over 21 km fiber, and the secure key rate for each of 16 users reaches 1.5 kbps. In the partial coexistence scheme using the dual feeder fiber structure, the combination of QAN and full-power 10G-EPON signals is achieved over 11 km with a network capacity of 64-user. The practical QAN over the 10G-EPON in our work implements an important step towards the achievement of large-scale QKD infrastructure., Comment: 9 pages, 4 figures. Accepted for publication in Optics Express

Quantum key distribution (QKD) enables secure key exchanges between two remote users. The ultimate goal of secure communication is to establish a global quantum network. The existing field tests suggest that quantum networks are feasible. To achieve a practical quantum network, we need to overcome several challenges, including realising versatile topologies for large scales, simple network maintenance, extendable configuration, and robustness to node failures. To this end, we present a field operation of a quantum metropolitan-area network with 46 nodes and show that all these challenges can be overcome with cutting-edge quantum technologies. In particular, we realise different topological structures and continuously run the network for 31 months, by employing standard equipment for network maintenance with an extendable configuration. We realise QKD pairing and key management with a sophisticated key control center. In this implementation, the final keys have been used for secure communication such as real-time voice telephone, text messaging, and file transmission with one-time pad encryption, which can support 11 pairs of users to make audio calls simultaneously. Combined with inter-city quantum backbone and ground-satellite links, our metropolitan implementation paves the way toward a global quantum network., Comment: 14 pages, 5 figures

Quantum key distribution (QKD) provides information theoretically secures key exchange requiring authentication of the classic data processing channel via pre-sharing of symmetric private keys. In previous studies, the lattice-based post-quantum digital signature algorithm Aigis-Sig, combined with public-key infrastructure (PKI) was used to achieve high-efficiency quantum security authentication of QKD, and its advantages in simplifying the MAN network structure and new user entry were demonstrated. This experiment further integrates the PQC algorithm into the commercial QKD system, the Jinan field metropolitan QKD network comprised of 14 user nodes and 5 optical switching nodes. The feasibility, effectiveness and stability of the post-quantum cryptography (PQC) algorithm and advantages of replacing trusted relays with optical switching brought by PQC authentication large-scale metropolitan area QKD network were verified. QKD with PQC authentication has potential in quantum-secure communications, specifically in metropolitan QKD networks., Comment: 11 pages, 3 figures