Browse Articles

Resilience and charge-dependent fibrillation of functional amyloid: Interactions of Pseudomonas biofilm-associated FapB and FapC amyloids

Structural basis of the bifunctionality of Marinobacter salinexigens ZYF650T glucosylglycerol phosphorylase in glucosylglycerol catabolism

ID3 promotes erythroid differentiation and is repressed by a TAL1–PRMT6 complex

A coplanar electrode operating mode for piezoelectric energy harvesting and self-powered sensing

Piezoelectric semiconductors have emerged as a prominent area of research in recent years due to their unique combination of piezoelectric and semiconductor properties. In this Letter, we propose a piezoelectric device structure featuring coplanar electrodes positioned above the piezoelectric layer. We have conducted a detailed theoretical analysis of the piezoelectric properties of this piezoelectric device. By utilizing a coplanar electrode piezoelectric mode, pressure applied to one electrode generates a potential difference between the two electrodes. Notably, the piezoelectric performance of the device can be adjusted by modifying its structure. Numerical simulations and experimental results indicate that the piezoelectric performance reaches an optimal value when the distance between the electrodes is equal to one-half of the electrode length. Additionally, we have developed a method to enhance the piezoelectric voltage output capability of the device under low load resistance conditions. Specifically, by introducing charge carriers into the piezoelectric layer from the doped silicon substrate, the device's resistance is reduced due to the Schottky contact. The piezoelectric operating mode proposed in this paper facilitates energy harvesting and self-powered sensing, distinguishing it from the d31 and d33 operational modes associated with traditional sandwich device structures, thereby allowing for more versatile device configurations.

Human α10 nicotinic acetylcholine receptor subunits assemble to form functional receptors

Unconventional in-plane field-like spin–orbit torques induced by rare-earth Dy interface in Py/Dy/Pt tri-layers

Spin transport across an interface in energy-efficient spintronic devices, especially for spin–orbit torque applications, has sparked interest in the spintronics community. Here, we employ a rare-earth metal spacer Dy to modify the interface of a Py-based heterostructure, with the aim of modulating the spin dynamics of the system and thereby controlling the spin–orbit torques. As the thickness of Dy increases, it is found that the saturation magnetization of Py/Dy decreases and eventually reaches a plateau, suggesting the induced magnetic moment of Dy that aligns opposite to the Fe and Ni moments. Such a self-assembled antiferromagnetic interface can be destroyed by the insertion of a Cu layer between Py and Dy. Utilizing this interface effect, an additional spin dissipation is observed by enhancement of spin dynamic damping, which has achieved a high spin mixing conductance at the interface of Py/Dy according to spin pumping theory. Utilizing the Py/Dy interface, an unconventional in-plane field-like torque spin–orbit torque (SOT) in a Py/Dy/Pt structure is achieved, while the field-like SOT efficiency experiences a notable enhancement in the Py/Dy/Pt system. By optimizing the interface between the Dy layer and Pt, it is possible to further enhance the performance and efficiency of the devices, thereby promoting the development of spintronic devices. This discovery has significant implications for the future design of low-power spintronic devices.

DNMT3b-mediated CpA methylation facilitates REST binding and gene silencing and exacerbates hippocampal demyelination in diabetic mice

Resonant inter-mode second harmonic generation by backward spin waves in YIG nano-waveguides

We experimentally study the nonlinear generation of the second harmonic by backward volume spin waves propagating in microscopic magnonic waveguides fabricated from a low-loss magnetic insulator with a thickness of several tens of nanometers. We show that highly efficient resonant second harmonic generation is possible in the inter-mode regime at microwave powers of the order of 10−4 W. In contrast to previously observed second harmonic generation processes, the generation by backward waves is characterized by the nonlinearly generated waves propagating opposite to the initial waves and can be realized at zero bias magnetic field.

The viral serpin SPI-1 directly inhibits the host cell serine protease FAM111A

Vertical Al2O3/GaN MOS capacitors with PEALD-GaO<i>x</i> interlayer passivation

In this Letter, we report high-quality vertical GaN metal–oxide–semiconductor (MOS) capacitors with sulfur passivation and a plasma-enhanced atomic layer deposition -grown GaOx interlayer, exhibiting a low interface trap density (Dit) of ∼8 × 1010 cm−2 eV−1 and a low frequency-dependent flatband voltage shift [ΔVFB (f)] of ∼20 mV (from 1 kHz to 1 MHz). The introduction of the GaOx interlayer effectively suppresses the leakage current (from ∼10−3 to ∼10−6 A/cm2 under 10 V positive bias) and passivates nitrogen/oxygen-related vacancies and dangling bonds. The demonstrated controllable and low-destructive passivation technique provides the insights and methodologies for the fabrication of high-performance GaN MOS structure-based devices.

A physicochemical rationale for the varied catalytic efficiency in RNase J paralogues

Anomalous shot noise in a bad metal β-tantalum

We investigate the electronic shot noise produced by nanowires of β-Ta, an archetypal “bad” metal with resistivity near the Ioffe–Regel localization limit. The Fano factor characterizing the shot noise exhibits a strong dependence on temperature and is suppressed compared to the expectations for quasiparticle diffusion, but hopping transport is ruled out by the analysis of scaling with the nanowire length. These anomalous behaviors closely resemble those of strange metal nanowires, suggesting that β-Ta may host a correlated electron liquid. This material provides an accessible platform for exploring exotic electronic states of matter.

Protein kinase a suppresses antiproliferative effect of interferon-α in hepatocellular carcinoma by activation of protein tyrosine phosphatase SHP2

Complementary logic-in-memory inverters integrating n-channel and p-channel ferroelectric organic transistors

The emerging logic-in-memory (LIM) technology is a promising strategy to overcome the von Neumann bottleneck in modern computers. For LIM circuits, the complementary structure is desirable for low-power consumption. To date, there have been rare reports on the n-channel organic thin-film transistor nonvolatile memories (OTFT-NVMs), which is indispensable for building the complementary LIM circuits. In this Letter, we demonstrate a route to achieve the low-voltage operatable n-channel OTFT-NVMs, by blade-coating an ultrathin tetratetracontane buffer layer on the oxygen plasma treated ferroelectric terpolymer insulator with a low coercive field. The n-channel OTFT-NVMs exhibit good performances, with a high electron mobility over 0.1 cm2/V s, highly reliable endurance over 1000 cycles, and highly stable retention over 10 000 s. The mechanism for improving device performances is discussed. Moreover, the mechanism and the route for improving performances are also suitable for p-channel OTFT-NVMs. Furthermore, the LIM architecture-based complementary organic inverters are constructed by integrating the n-channel and p-channel OTFT-NVMs, which can well perform logic and memory operations at the low voltage of 10 V. The work laid the foundation for the development of the LIM circuits.

Differences in structure, dynamics, and zinc coordination between isoforms of human ubiquitin ligase UBE3A

A deep convolutional neural network for diffuse correlation tomography

Near-infrared diffuse correlation tomography (DCT) is an emerging technology for tomographic imaging of blood flow index (BFI) in biological tissues through quantifying the light electric field temporal autocorrelation function. With the conventional approaches, proper reconstruction of BFI images is a challenging task from the limited DCT signals due to the severe imbalance between the optical measurements and the voxels to be reconstructed. In this study, we proposed a complete deep learning solution for DCT, including a dataset containing massive prior information for network training, a long short-term memory neural network for DCT signal denoising, as well as a deep convolutional neural network for mapping the DCT signals into the tomographic BFI images. The proposed deep learning solution was comprehensively validated through both computer simulations and phantom experiments, demonstrating its strong superiority over the conventional approach for precise and robustness reconstructions of the target BFI anomalies, with much better performance in reducing errors (i.e., the mean absolute error was reduced by 26.1 times) and preserving fine structure (i.e., the structure similarity index measure was increased by 12.8 times). The proper establishment of a deep learning strategy enables future exploration of the microvasculature blood flow mechanism on pathological tissues even from the limited DCT signals.

The NADH-dependent flavin reductase ThdF follows an ordered sequential mechanism though crystal structures reveal two FAD molecules in the active site

Enhanced thermoelectric performance in AgSbTe2 with extremely low thermal conductivity via grain boundary defects

A delicate balance between high electrical conductivity and ultra-low glass-like thermal conductivity is critical for enhancing thermoelectric performance. Here, by introducing grain boundary trapping states into the AgSbTe2 matrix, the thermally activated release of carriers at elevated temperatures enhances electrical conductivity, while the increased barrier potential induces an energy filtering effect that sustains a high Seebeck coefficient. This synergistic optimization of electrical conductivity and Seebeck coefficient significantly enhances the power factor. Additionally, numerous point defects and a higher density of grain boundaries further enhance phonon scattering, resulting in a 33% reduction in glass-like thermal conductivity compared to the pristine sample. With enhanced power factor and reduced lattice thermal conductivity, Fe-doped AgSbTe2 achieves a remarkable peak zT of 1.8 at 623 K and an impressive zTavg of 1.4 over the temperature range of 323–623 K, showcasing its leading performance in the field. By selecting proper contact layer materials with matched thermal expansion coefficients, low interfacial resistivity was achieved, enabling a single-leg thermoelectric device with ∼10% efficiency under a 323 K temperature difference.

Lipid droplet targeting of the lipase coactivator ABHD5 and the fatty liver disease-causing variant PNPLA3 I148M is required to promote liver steatosis

Improved spectral filtering of broadband diffractive neural network by loss function engineering

We engineer the loss function by removing the conventional physics-based energy constraint during the training of broadband diffractive neural networks (DNNs) to enhance their spectral filtering capabilities of supercontinuum light. Simulations show that compared to DNNs trained with conventional loss function, the suppression of out-of-band spectral intensities can be improved by three orders of magnitude, resulting in an extinction coefficient of 10−6. Additionally, the spectral resolution can be enhanced by over 50% with a 6.6% improvement of energy efficiency. These findings are corroborated by experiments conducted with a two-layer DNN. The proposed method holds promise for enhancing the performance of broadband DNNs across various applications, including spectral reconstruction, spectrum classification, and color image processing, among others.