Multiferroic Magnon Spin-Torque Based Reconfigurable Logic-In-Memory

Magnons, bosonic quasiparticles carrying angular momentum, can flow through insulators for information transmission with minimal power dissipation. However, it remains challenging to develop a magnon-based logic due to the lack of efficient electrical manipulation of magnon transport. Here we present a magnon logic-in-memory device in a spin-source/multiferroic/ferromagnet structure, where multiferroic magnon modes can be electrically excited and controlled. In this device, magnon information is encoded to ferromagnetic bits by the magnon-mediated spin torque. We show that the ferroelectric polarization can electrically modulate the magnon spin-torque by controlling the non-collinear antiferromagnetic structure in multiferroic bismuth ferrite thin films with coupled antiferromagnetic and ferroelectric orders. By manipulating the two coupled non-volatile state variables (ferroelectric polarization and magnetization), we further demonstrate reconfigurable logic-in-memory operations in a single device. Our findings highlight the potential of multiferroics for controlling magnon information transport and offer a pathway towards room-temperature voltage-controlled, low-power, scalable magnonics for in-memory computing

Fast 3D Reconstruction of UAV Images Based on Neural Radiance Field

Traditional methods for 3D reconstruction of unmanned aerial vehicle (UAV) images often rely on classical multi-view 3D reconstruction techniques. This classical approach involves a sequential process encompassing feature extraction, matching, depth fusion, point cloud integration, and mesh creation. However, these steps, particularly those that feature extraction and matching, are intricate and time-consuming. Furthermore, as the number of steps increases, a corresponding amplification of cumulative error occurs, leading to its continual augmentation. Additionally, these methods typically utilize explicit representation, which can result in issues such as model discontinuity and missing data during the reconstruction process. To effectively address the challenges associated with heightened temporal expenditures, the absence of key elements, and the fragmented models inherent in three-dimensional reconstruction using Unmanned Aerial Vehicle (UAV) imagery, an alternative approach is introduced—the neural radiance field. This novel method leverages neural networks to intricately fit spatial information within the scene, thereby streamlining the reconstruction steps and rectifying model deficiencies. The neural radiance field method employs a fully connected neural network to meticulously model object surfaces and directly generate the 3D object model. This methodology simplifies the intricacies found in conventional 3D reconstruction processes. Implicitly encapsulating scene characteristics, the neural radiance field allows for iterative refinement of neural network parameters via the utilization of volume rendering techniques. Experimental results substantiate the efficacy of this approach, demonstrating its ability to complete scene reconstruction within a mere 5 min timeframe, thereby reducing reconstruction time by 90% while markedly enhancing reconstruction quality

Three-junction tandem photovoltaic cell for a wide temperature range based on a multilayer circular truncated cone metamaterial emitter

To improve the conversion efficiency of thermophotovoltaic devices, we designed a thermophotovoltaic system based on an InAs/InGaAsSb/GaSb three-junction tandem cell. The tandem cell can recover photons in the wavelength range of 200–3650 nm and therefore enhance the output power of the system. To further improve system performance, we designed a multilayer circular truncated cone metamaterial emitter matching the tandem cell. Existing TPV systems based on multi-junction tandem PV cells can achieve conversion efficiencies of 33.3%–41%, while the thermophotovoltaic system coupled with the multilayer circular truncated cone metamaterial can recover more photons of 1.44 mol/(m·s) and achieve a higher conversion efficiency of 52.8% at 1773 K. The thermophotovoltaic system designed here demonstrates an extremely high energy conversion efficiency and has good application prospects

Biomimetic Conversion of Glucose to Organic Acid Facilitated by Metalloporphyrin under Mild Conditions

Biomimetic catalytic conversion of carbohydrates to low-molecular weight (LWM) organic acids was investigated in the presence of sulfonated metalloporphyrins (MTSPP, M = Fe, Mn, Co, Cu), with dioxygen as the oxidant. The results showed that the selectivity of lactic acid reached 70%, starting from glucose with an iron complex of meso-tetra(4-sulfonato-phenyl)porphyrin (TSPPFeCl) as the catalyst at 433 K, and 0.6 MPa of O2 in 0.05 M NaOH aqueous solution. The effects of various metalloporphyrins on the selectivity of oxidative products were also considered. Experimental results show that TSPPFeCl exhibited the highest catalytic performance compared with TSPPMnCl, TSPPCo, and TSPPCu

Iodine(III)-Mediated C–H Alkoxylation of Aniline Derivatives with Alcohols under Metal-Free Conditions

The development of a novel intermolecular oxidative C–H alkoxylation of aniline derivatives is described under metal-free conditions with high reaction rates at ambient temperature. In the presence of an I­(III) oxidant, a range of aldehydes, anilines, and alcohol substrates undergo three-component coupling to produce synthetically useful alkoxyl-substituted <i>N</i>-arylimines. The preliminary mechanism investigations revealed that the transformation proceeds via imines as intermediates

Transition-Metal-Free Oxidative α‑C–H Amination of Ketones via a Radical Mechanism: Mild Synthesis of α‑Amino Ketones

A transition-metal-free direct α-C–H amination of ketones has been developed using commercially available ammonium iodide as the catalyst and sodium percarbonate as the co-oxidant. A wide range of ketone ((hetero)­aromatic or nonaromatic ketones) and amine (primary/secondary amines, anilines, or amides) substrates undergo cross-coupling to generate synthetically useful α-amino ketones. The mechanistic studies indicated that a radical pathway might be involved in the reaction process. The utility of the method is highlighted through a concise one-step synthesis of the pharmaceutical agent amfepramone

PIFA-Mediated Esterification Reaction of Alkynes with Alcohols via Oxidative Cleavage of Carbon Triple Bonds

A metal-free esterification of alkynes via CC triple bond cleavage has been developed. In the presence of phenyl­iodine bis­(tri­fluoro­acetate), a diverse range of alkyne and alcohol substrates undergoes triple bond cleavage to produce carboxylic ester motifs in moderate to good yields. The transformation is proposed to proceed via hydroxy­ethanones and ethane­diones as intermediates on the basis of mechanistic studies and exhibits a broad substrate scope and good functional group tolerance

Depression Prevalence in Postgraduate Students and Its Association With Gait Abnormality

In recent years, an increasing number of university students are found to be at high risk of depression. Through a large scale depression screening, this paper finds that around 6.5% of the university postgraduate students in China experience depression. We then investigate whether the gait patterns of these individuals have already changed as depression is suggested to associate with gait abnormality. Significant differences are found in several spatiotemporal, kinematic and postural gait parameters such as walking speed, stride length, head movement, vertical head posture, arm swing, and body sway, between the depressed and non-depressed groups. Applying these features to classifiers with different machine learning algorithms, we examine whether natural gait analysis may serve as a convenient and objective tool to assist in depression recognition. The results show that when using a random forest classifier, the two groups can be classified automatically with a maximum accuracy of 91.58%. Furthermore, a reasonable accuracy can already be achieved by using parameters from the upper body alone, indicating that upper body postures and movements can effectively contribute to depression analysis