Electrical switching of Ising-superconducting nonreciprocity for quantum neuronal transistor.

Nonreciprocal quantum transport effect is mainly governed by the symmetry breaking of the material systems and is gaining extensive attention in condensed matter physics. Realizing electrical switching of the polarity of the nonreciprocal transport without external magnetic field is essential to the development of nonreciprocal quantum devices. However, electrical switching of superconducting nonreciprocity remains yet to be achieved. Here, we report the observation of field-free electrical switching of nonreciprocal Ising superconductivity in Fe3GeTe2/NbSe2 van der Waals (vdW) heterostructure. By taking advantage of this electrically switchable superconducting nonreciprocity, we demonstrate a proof-of-concept nonreciprocal quantum neuronal transistor, which allows for implementing the XOR logic gate and faithfully emulating biological functionality of a cortical neuron in the brain. Our work provides a promising pathway to realize field-free and electrically switchable nonreciprocity of quantum transport and demonstrate its potential in exploring neuromorphic quantum devices with both functionality and performance beyond the traditional devices.

Peceleganan Spray for the Treatment of Skin Wound Infections: A Randomized Clinical Trial.

Importance: Peceleganan spray is a novel topical antimicrobial agent targeted for the treatment of skin wound infections. However, its efficacy and safety remain unclear. Objective: To assess the safety and efficacy of peceleganan spray for the treatment of wound infections. Design, Setting, and Participants: This multicenter, open-label, phase 3 randomized clinical trial recruited and followed up 570 adult patients diagnosed with secondary open wound infections from 37 hospitals in China from August 23, 2021, to July 16, 2022. Interventions: Patients were randomized to 2 groups with a 2:1 allocation. One group received treatment with 2% peceleganan spray (n = 381) and the other with 1% silver sulfadiazine (SSD) cream (n = 189). Main Outcomes and Measures: The primary efficacy outcome was the clinical efficacy rate (the number of patients fulfilling the criteria for efficacy of the number of patients receiving the treatment) on the first day following the end of treatment (day 8). The secondary outcomes included the clinical efficacy rate on day 5 and the bacterial clearance rate (cases achieving negative bacteria cultures after treatment of all cases with positive bacteria cultures before treatment) on days 5 and 8. The safety outcomes included patients' vital signs, physical examination results, electrocardiographic findings, blood test results, and adverse reactions. Results: Among the 570 patients randomized to 1 of the 2 groups, 375 (98.4%) in the 2% peceleganan treatment group and 183 (96.8%) in the 1% SSD control group completed the trial (n = 558). Of these, 361 (64.7%) were men, and the mean (SD) age was 48.6 (15.3) years. The demographic characteristics were similar between groups. On day 8, clinical efficacy was achieved by 339 patients (90.4%) in the treatment group and 144 (78.7%) in the control group (P < .001). On day 5, clinical efficacy was achieved by 222 patients (59.2%) in the treatment group and 90 (49.2%) in the control group (P = .03). On day 8, bacterial clearance was achieved by 80 of 334 patients (24.0%) in the treatment group and in 75 of 163 (46.0%) in the control group (P < .001). On day 5, bacterial clearance was achieved by 55 of 334 patients (16.5%) in the treatment group and 50 of 163 (30.7%) in the control group (P < .001). The adverse events related to the application of peceleganan spray and SSD cream were similar. Conclusions and Relevance: This randomized clinical trial found that peceleganan spray is a safe topical antimicrobial agent with a satisfactory clinical efficacy rate for the treatment of skin wound infections, while the effectiveness of bacterial clearance remains uncertain. Trial Registration: Chinese Clinical Trial Registry Identifier: ChiCTR2100047202.

On-device phase engineering.

In situ tailoring of two-dimensional materials' phases under external stimulus facilitates the manipulation of their properties for electronic, quantum and energy applications. However, current methods are mainly limited to the transitions among phases with unchanged chemical stoichiometry. Here we propose on-device phase engineering that allows us to realize various lattice phases with distinct chemical stoichiometries. Using palladium and selenide as a model system, we show that a PdSe2 channel with prepatterned Pd electrodes can be transformed into Pd17Se15 and Pd4Se by thermally tailoring the chemical composition ratio of the channel. Different phase configurations can be obtained by precisely controlling the thickness and spacing of the electrodes. The device can be thus engineered to implement versatile functions in situ, such as exhibiting superconducting behaviour and achieving ultralow-contact resistance, as well as customizing the synthesis of electrocatalysts. The proposed on-device phase engineering approach exhibits a universal mechanism and can be expanded to 29 element combinations between a metal and chalcogen. Our work highlights on-device phase engineering as a promising research approach through which to exploit fundamental properties as well as their applications.

Interfacial magnetic spin Hall effect in van der Waals Fe3GeTe2/MoTe2 heterostructure.

The spin Hall effect (SHE) allows efficient generation of spin polarization or spin current through charge current and plays a crucial role in the development of spintronics. While SHE typically occurs in non-magnetic materials and is time-reversal even, exploring time-reversal-odd (T-odd) SHE, which couples SHE to magnetization in ferromagnetic materials, offers a new charge-spin conversion mechanism with new functionalities. Here, we report the observation of giant T-odd SHE in Fe3GeTe2/MoTe2 van der Waals heterostructure, representing a previously unidentified interfacial magnetic spin Hall effect (interfacial-MSHE). Through rigorous symmetry analysis and theoretical calculations, we attribute the interfacial-MSHE to a symmetry-breaking induced spin current dipole at the vdW interface. Furthermore, we show that this linear effect can be used for implementing multiply-accumulate operations and binary convolutional neural networks with cascaded multi-terminal devices. Our findings uncover an interfacial T-odd charge-spin conversion mechanism with promising potential for energy-efficient in-memory computing.

Cascadable in-memory computing based on symmetric writing and readout.

The building block of in-memory computing with spintronic devices is mainly based on the magnetic tunnel junction with perpendicular interfacial anisotropy (p-MTJ). The resulting asymmetric write and readout operations impose challenges in downscaling and direct cascadability of p-MTJ devices. Here, we propose that a previously unimplemented symmetric write and readout mechanism can be realized in perpendicular-anisotropy spin-orbit (PASO) quantum materials based on Fe3GeTe2 and WTe2. We demonstrate that field-free and deterministic reversal of the perpendicular magnetization can be achieved using unconventional charge-to-z-spin conversion. The resulting magnetic state can be readily probed with its intrinsic inverse process, i.e., z-spin-to-charge conversion. Using the PASO quantum material as a fundamental building block, we implement the functionally complete set of logic-in-memory operations and a more complex nonvolatile half-adder logic function. Our work highlights the potential of PASO quantum materials for the development of scalable energy-efficient and ultrafast spintronic computing.

Distributed LMMSE Estimation for Large-Scale Systems Based on Local Information.

This article studies the distributed linear minimum mean square error (LMMSE) estimation problem for large-scale systems with local information (LSLI). Large-scale systems are composed of numerous subsystems. Each subsystem only transmits information to its neighbors. Thus, only the local information is available to each subsystem. This implies that the information available to different subsystems is different. Using local information to design an LMMSE estimator, the gains of the estimator must satisfy the sparse structure constraint, which makes the estimator design challenging and complicates the boundedness analysis of the estimation error covariance (EEC). In this article, a framework of the distributed LMMSE estimation for LSLI is established. The gains of the LMMSE estimator are effectively constructed by solving linear matrix equations. A gradient descent algorithm is exploited to design the gains of the LMMSE estimator numerically. Sufficient conditions are derived to ensure the boundedness of the EEC. Also, a gradient-based search algorithm is developed to verify whether the sufficient conditions hold or not. Finally, an example is used to illustrate the effectiveness of the proposed results.

Distributed L2-gain control of large-scale systems: A space construction approach.

This note studies the distributed L2-gain control problem for discrete-time large-scale systems. The considered system is transformed equivalently to a high dimensional system. The classical controller design methods are not suitable to be applied directly due to the matrix inversion terms in the transformed system. Using a space construction approach, this paper derives necessary and sufficient stability conditions in the form of linear matrix inequalities for large-scale systems. In addition, under given L2-gain γ, necessary and sufficient conditions are established such that the considered system is asymptotically stable and the prescribed L2-gain is satisfied. Then, these results are used to design distributed controllers for large-scale systems. Based on a matrix construction method, distributed controllers can be constructed via the solutions of a set of linear matrix inequalities to guarantee that the closed-loop system is stable with the given L2-gain. Finally, the advantages of the proposed theoretical results are demonstrated by two examples.

Optimal Decentralized Output-Feedback LQG Control With Random Communication Delay.

This paper is concerned with the optimal decentralized output-feedback control of the large-scale systems. A random information pattern is considered, where the information is transmitted among the subsystems with random communication delays. For the random information pattern, the optimal LQG problems for both global estimation case and local estimation case are studied. It is difficult to derive the optimal controller under random framework, because the gains of the controller must be designed to satisfy the random sparse structure constraints. In this paper, we design the optimal controller by Hadamard product method. For global estimation case, the gains of the controller are obtained by solving linear matrix equation. For local estimation case, an iterative algorithm is exploited to compute the gains. In addition, the value of the cost function achieved by the designed controller is found and shown to monotonically increase with the increase of the delay probability for both global and local estimation cases. Finally, the theoretical results are illustrated by two numerical examples.

Optimal Filtered and Smoothed Estimators for Discrete-Time Linear Systems With Multiple Packet Dropouts Under Markovian Communication Constraints.

This paper concentrates on the linear least mean square (LLMS) filtered and smoothed estimators for networked linear stochastic systems. Multiple packet losses, Markovian communication constraints, and superposed process noise are considered simultaneously. In order to reduce the channel load during communication, at every step, just one transmission node is permitted to send data packets. Hence, a Markovian communication protocol is utilized to arrange the packets of these transmission nodes. Moreover, multiple data packet dropouts occur during transmission due to an imperfect communication channel. Therefore, the global observation information cannot be obtained by the state estimator. The real state of Markov chain is assumed to be unknown to the estimator except the transition probability matrix. By means of the innovation analysis approach and orthogonal projection principle, we design Kalman-like estimators in a recursive form. Finally, through simulation experiments, we verify the effectiveness and superiority of the designed algorithm.

Static output feedback stabilization of networked control systems with a parallel-triggered scheme.

This paper investigates the parallel-triggered static output feedback stabilization problem for linear networked control systems. A new parallel-triggered scheme is proposed by using both the relative error and the absolute error information. The scheme can reduce transmission rate while maintaining the global asymptotical stability. The linear parallel-triggered networked control system is modeled as a time-delay system. By employing Lyapunov stability theory, sufficient conditions are established for the closed-loop system to be globally asymptotically stable in terms of linear matrix inequalities. Moreover, a co-design algorithm is developed to obtain both the optimal trigger parameters and the output feedback controller gain in the sense that the transmission rate is minimized. Finally, two examples are given to illustrate the advantages of the proposed scheme.