Browse Articles

Modulating water transport in fractured carbon nanotubes: The role of terahertz electric fields and nanotube geometry

The formation of sub-nanometre fracture gaps in single-walled carbon nanotubes (SWCNTs) represents a major limitation to their efficiency in transporting water. Through molecular dynamics simulations, this work demonstrates that the water flux exhibits a threshold response to the fracture gap. In a 1.34 nm SWCNT, fractures smaller than 3 Å exert negligible influence, whereas fracture gaps exceeding this threshold cause a pronounced reduction in flux. Furthermore, in longer nanotubes, the smoother free energy profile in the central region and more stable water-nanotube interactions facilitate the formation of stable single-file water chains, endowing them with enhanced resistance to fracture. Under the influence of a terahertz electric field, the hydrogen bond network between water molecules is disrupted, which leads to substantial flux enhancement but also to increased sensitivity to fracture spacing. These findings provide new theoretical insight into the interplay between structural defects and external stimuli in nanoscale water transport and offer guidance for designing robust, high-performance SWCNT-based nanofluidic systems.

A residual multi-layer perceptron framework for transmission prediction and physical interpretation of terahertz responses in multilayer compound metal–dielectric metasurfaces

Metamaterials have emerged as promising candidates for terahertz applications. Among different structures, metal–dielectric composite periodic arrays have gained significant interest due to their ability to efficiently manipulate electromagnetic wave propagation and enhance transmission in the terahertz range. In this work, we present a deep-learning-driven modeling framework based on a Residual Multi-Layer Perceptron (ResMLP) to predict the transmittance of multilayer metal–dielectric composite periodic annular-aperture arrays. A large-scale dataset comprising geometric parameters and transmittance spectra obtained from full-wave electromagnetic simulations was used to train the ResMLP. The trained model achieves highly accurate predictions of optical responses, with a validation mean squared error of 0.000 166. To further assess reliability, a “closed-loop verification” was performed, in which the predicted geometric parameters were reintroduced into the forward simulator to regenerate the transmittance spectra, yielding high consistency with the target spectra. Compared to full-wave simulation, our approach offers up to 105-fold improvement in computational efficiency without compromising accuracy. This study demonstrates the potential of deep learning in accelerating the design and optimization of multilayer metal–dielectric metasurfaces, thereby facilitating the development of terahertz photonic devices.

On the nature of deep-level defects in <i>β</i> -Ga2O3 epilayers: The impact of isochronal rapid thermal annealing

Deep-level transient spectroscopy (DLTS) and Laplace-DLTS were used to investigate electrically active defects in (010)-oriented β-Ga2O3 epilayers grown via metal-organic chemical vapor deposition and doped with Si during growth. The impact of isochronal rapid thermal annealing in N2 on the electrical characteristics of Pt Schottky barrier diodes and on defect concentrations was examined by annealing at temperatures from 150 to 450 °C with 100 °C increments. Four deep levels were detected, with concentrations in the range of 1013–1014 cm−3 and activation energies of electron emission to the conduction band (ΔEc) of 0.06, 0.40, 0.55, and 0.62 eV. The Ec-0.06 eV trap was no longer observed in DLTS measurements after heating to 400 K, and the Ec-0.62 eV trap was suppressed after annealing at 350 °C. In contrast, the Ec-0.40 eV trap progressively reduced in concentration, while the trap density of the Ec-0.55 eV level increased with each rapid thermal annealing step, suggesting defect redistribution along the [010] direction. The electric field dependence of the electron emission rates indicates acceptor-like behavior for the Ec-0.55 eV state and donor-like behavior for the Ec-0.62 eV state. As both states exhibit activation energies consistent with the commonly reported E1 defect, we propose the following labelling conventions: E1a (Ec-0.55 eV) and E1b (Ec-0.62 eV). The nature and potential origins for each of the observed defects are discussed.

TYK2 mediates neuroinflammation in Alzheimer’s disease brains with TDP-43 pathology

Abstract Neuroinflammation is a pathological feature of neurodegenerative diseases like Alzheimer’s disease and ALS. Cytoplasmic dsRNA (cdsRNA) triggers a type-I interferon response in human neural cells, leading to their death, and is found in neurons of C9ORF72 -ALS patients. Here, we report the spatial coincidence of cdsRNA and pTDP-43 inclusions in human postmortem tissue with Alzheimer’s disease pathology, and upregulated interferon response genes in affected regions. CdsRNA also accumulates in a human TDP-43 G298S iPSC cortical neuronal model. We use cryptic exon detection as a proxy for TDP-43 mislocalization and demonstrate that FDA-approved JAK inhibitors baricitinib and ruxolitinib, which block interferon signaling, show protective effects only in brains with elevated cryptic exon expression. A CRISPR screen reveals TYK2 as a top hit, and TYK2 knockdown and the selective TYK2 inhibitor deucravacitinib rescue cdsRNA-induced toxicity. We find parallel neuroinflammatory mechanisms, dependent on TYK2 - a potential disease-modifying target - for TDP-43-associated Alzheimer’s disease and C9ORF72 -ALS.

Frequency selective surfaces for the future of wireless technologies, trends, and applications

This paper presents a comprehensive review of Frequency Selective Surfaces (FSSs), highlighting their unique electromagnetic capabilities in controlling the transmission, reflection, and absorption of electromagnetic waves as a function of frequency. FSSs are typically composed of periodic arrangements of conductive patches or apertures on a substrate, where structural optimization enables precise manipulation of electromagnetic responses. Due to their versatility, FSSs have found applications in diverse areas such as solar energy harvesting, electromagnetic interference shielding, radar systems, wireless communication, antenna design, and filtering structures. A major focus of this review is on the role of FSSs in millimeter-wave (mm-wave) communication systems and Reconfigurable Intelligent Surfaces (RIS). Within RIS frameworks, FSSs can be dynamically reconfigured by modifying geometry, spacing, or material properties, allowing for advanced functionalities such as beamforming, signal steering, interference mitigation, spectrum management, and frequency-selective channel shaping. Functionally, FSSs act as over-the-air electromagnetic filters, enabling either frequency transmission (transmissive FSS, analogous to passband filters) or rejection (reflective FSS, analogous to stopband filters). Additionally, the integration of FSSs with artificial magnetic conductors enhances antenna performance by minimizing backward radiation while improving gain and efficiency, making them particularly useful in wearable and compact antenna systems. As engineered metamaterials, FSSs also support antenna miniaturization, mutual coupling reduction, and wideband/multi-band operation. Overall, the review underscores the indispensable role of FSSs in next-generation communication systems, particularly in advanced 5G and upcoming 6G technologies, where efficient electromagnetic wave management is critical for high-performance and compact designs.

Increased hailstorms in cities through cell merger mechanism across North America and East Asia

Room temperature ferromagnetism, perpendicular magnetic anisotropy, and sizable anomalous Hall conductivity in self-intercalated bilayer 1T-CrSe2

Two-dimensional (2D) magnetic materials exhibiting room temperature ferromagnetism have garnered significant attention due to their vast potential application and unique properties. The self-intercalated (SI) atom is a useful approach to controlling magnetic, electronic, and transport properties of 2D materials. SI Cr (CrSI) atom could effectively modulate magnetic order, Curie temperature (Tc), magnetic anisotropy properties, anomalous Hall effect (AHE), anomalous Hall conductivity (AHC), and formation energy (εf) of 1T-CrSe2, which are related to the stacking orders and concentration of CrSI atom (x). CrSI atom transforms 1T-CrSe2-BL from a spin-unpolarized metal with interlayer antiferromagnetic order to a spin-polarized metal with ferromagnetic order and presents AHE, independent of the stacking orders and x. The CrSI atom introduces local charge doping and redistribution of charge density and changes super exchange interaction between Cr and Se atoms, leading to a transfer of magnetic orders. We also find SI-1T-CrSe2 show room temperature Tc, and Cr9Se16-AA/AB have Tc of 404 and 284 K, respectively. SI-1T-CrSe2 present AHE and the corresponding sizable AHC change with the stacking orders and x. Moreover, SI-1T-CrSe2 (higher x) intends to perpendicular magnetic anisotropy, and the magnetocrystalline anisotropy (MCA) energies change with the stacking orders and x. The MCA changes as the hybridization interaction between Se-p orbitals changes. Moreover, the εf of SI-1T-CrSe2 is related to the x and chemical potential, and Cr-rich condition is beneficial to the synthesis of SI-1T-CrSe2 with CrSI atom. SI-1T-CrSe2 have good thermodynamic and kinetic stability. This work advances the research on 2D SI magnetic materials and accelerates their wide application in spintronics.

Tropical cyclone rainfall extends inland

Coexistence of quantum spin Hall effect and intrinsic piezoelectricity in I-doped monolayer Bi4Br4

The quantum spin Hall insulator with intrinsic piezoelectric response has attracted much attention due to its potential applications in topological electronic states and piezoelectric electric coupling fields. Motivated by the comparable chemical properties of Br and I, we construct Janus Bi4BrxI4−x (x = 1, 2, 3) monolayers by tuning the I concentration and systematically investigate their electronic, topological, and piezoelectric properties. First-principles calculations demonstrate that all three Janus structures are dynamically stable, wide-bandgap quantum spin Hall insulators, with nontrivial bandgaps of ∼0.26 eV. Density functional perturbation theory calculations confirm that non-centrosymmetric Bi4Br3I1 and Bi4Br1I3 possess significant in-plane piezoelectric effects, with Bi4Br3I1 exhibiting a notably large piezoelectric strain coefficient of |d11| = 7.092 pm/V. Notably, Bi4BrxI4−x (x = 1, 2, 3) structures have already been synthesized and their properties experimentally verified, underscoring their practical feasibility. These findings establish Janus Bi4BrxI4−x (x = 1, 2, 3) monolayers as a promising platform, enabling the coexistence of nontrivial topological states and strong piezoelectricity, paving the way for next-generation multifunctional quantum devices.

Joint control of precipitation and CO2 on global long-term patterns of plant nitrogen availability

Dynamic capacitive analysis and physical modeling on ZnO resistive random access memory (RRAM) for enabling neuromorphic computing

With the increasing demand for large data storage and artificial intelligence, resistive random-access memory (RRAM) thrives as one of the applicable candidates for the next-generation nonvolatile memory, owing to its simple structure, high scalability, high speed, low power, and tunable conductance. Among oxide-based RRAM, ZnO shows unique optical and electrical properties toward the future heterogeneous integration and low power memory-in-computing systems. In this study, we present a ZnO RRAM manufactured under earth gravity and in-space through inkjet printing. Memory devices with various fabrication environments and conditions include methanol ground, methanol flight, ethanol ground, to ethanol flight. The device fabricated under the microgravity shows a significantly reduced forming voltage and improved reliability. To investigate the filamentary formation in the ZnO RRAM, activation energy was extracted from Arrhenius equations on temperature modulations testing schemes for a comprehensive filament modeling. The capacitive models have concluded oxygen migration conduction dominated on this ZnO RRAM. Finally, the devices' conductance was modulated by AC potentiation and depression with an optimized linearity (R2 = 98%) toward a good training accuracy of 90% on the MNIST data set training toward neuromorphic computing.

An international multi-centre study to develop and validate federated learning-based prognostic models for anal cancer

Abstract Precision oncology relies on access to high-quality data for increasingly smaller patient subgroups. The international atomCAT consortium investigates the potential of federated learning to support this, using anal cancer as a rare cancer exemplar. Here, we show that federated multivariable Cox models trained across 14 centres (1428 patients) and externally validated in two additional centres (277 patients) achieve consistent calibration and discrimination during leave-one-centre-out and external validation (c-indices 0.68-0.79). Lower T stage, absence of nodal involvement, smaller tumour volume, female sex, younger age, and mitomycin- or cisplatin-based chemotherapy are associated with improved overall survival. Lower T stage, smaller tumour volume, and female sex are associated with improved locoregional control, while absence of nodal involvement and smaller tumour volume are associated with better freedom from distant metastases. These findings demonstrate that federated learning enables robust, privacy-preserving prognostic modelling for rare cancers using real-world data, supporting international collaboration without data sharing.

Heteroepitaxial integration of α-Ga2O3/p-NiO by mist-CVD for solar-blind UV detection

Solar-blind ultraviolet (SBUV) photodetection is critically demanded in military and civil fields thanks to its near-zero background radiation. Gallium oxide (Ga2O3) emerges as an ideal wide-bandgap semiconductor for SBUV and power devices thanks to its suitable bandgap and compatibility with substrates. Up to now, the lack of stable p-type Ga2O3 has become a bottleneck, restricting its application. Consequently, p–n heterojunction formation is one possible solution, where p-type nickel oxide appears as a promising p-type semiconductor. Here, we employ mist chemical vapor deposition technology to demonstrate epitaxial integration of single-crystal α-Ga2O3/NiO heterojunctions on c-plane sapphire, featuring a distinct interface with an epitaxial relationship of α-Al2O3(0006) || α-Ga2O3(0006) || NiO(111). The as-grown Li+-doped NiO film shows a high hole mobility (88.32 cm2/V s) and low resistivity (0.09 Ω cm) and exhibits a type-II band alignment with α-Ga2O3, consequently enabling efficient carrier separation. The fabricated α-Ga2O3/NiO p–n junction photodetector exhibits rectification effects and self-powered detection capability, achieving high-performance UV detection with a responsivity of 43.86 A/W, detectivity of 1.64 × 1012 Jones, rejection ratio of 177.3, and fast response (17/16 ms). This work demonstrates a low-cost epitaxial approach to realize high-quality α-Ga2O3/NiO p–n heterojunction integration for fast UV detection applications.

Photoinduced radical-mediated atomic dispersion of noble metal nanoparticles

Reservoir computing in a lithium-based magneto-ionic device

In-materio computing exploits the intrinsic physical dynamics of materials to perform complex computations, enabling low-power, real-time data processing by embedding computation directly within physical layers. Here, we demonstrate a voltage-controlled magneto-ionic device that functions as a reservoir computer capable of forecasting chaotic time series. The device consists of a crossbar structure with a Ta/CoFeB/Ta/MgO/Ta bottom electrode and a LiPON/Pt top electrode. A chaotic Mackey–Glass time series is encoded into a voltage signal applied to the device, while 2D Fourier transforms of voltage-dependent magnetic domain patterns form the output. Performance is influenced by the input rate, smoothing of the output, the number of elements in the reservoir state vector, and the training duration. We identify two distinct computational regimes: Short-term prediction is optimized using smoothed, low-dimensional states with minimal training, whereas prediction around the Mackey–Glass delay time benefits from unsmoothed, high-dimensional states and extended training. Reservoir computing metrics reveal that slower input rates are more tolerant to output smoothing, while faster input rates degrade both memory capacity and nonlinear processing. These findings demonstrate the potential of magneto-ionic systems for neuromorphic computing and offer design principles for tuning performance in response to input signal characteristics.

Catalytic enantioselective synthesis of azahelicenes via cascade Pictet-Spengler reaction and dehydrogenative aromatization

Flexoelectric control of polarization in 2D materials

This review article provides an overview of polarization generation and control in two-dimensional (2D) materials through the flexoelectric effect. Polarization can be engineered across multiple length scales, from the atomic to macroscopic level, using surface corrugation, substrate deformation, and atomic force microscopy tip loading. The flexoelectric effect, which arises from the coupling between a strain gradient and polarization, can occur in all dielectric materials, but its influence becomes especially pronounced in 2D systems where large gradients are readily formed. Such coupling enables mechanically tunable functionalities, including charge modulation, photoresponse enhancement, and energy harvesting, offering a practical pathway for polarization control without external bias. In addition, this review addresses confounding effects, such as piezoelectricity, triboelectricity, and surface electrochemistry, and emphasizes that careful experimental design is crucial to accurately identify the intrinsic flexoelectric behavior in 2D materials.

Single-cell and spatial profiling reveal cDC2A-CXCL13+CD8+ T-epithelial cell crosstalk and cytotoxicity through TNFRSF9 in cutaneous and mucosal lichen planus

Broadband reflective elastic mode conversion enabled by a single row of inclined long-slits

Broadband longitudinal-to-transverse mode conversion under normal incidence remains difficult to achieve, especially with structurally simple designs. Numerical simulations show that a single periodic row of inclined long-slits near a free surface enables high-efficiency broadband conversion, where the conversion rate exceeds 0.8 across a normalized-frequency range of 0.27–0.74, corresponding to a 93.1% relative bandwidth. The broadband response originates from two intrinsic deformation modes of the mass blocks between adjacent inclined slits: a rotational mode and a quadrupole mode. The spectral overlap of these two modes sustains a continuous high-efficiency band. The effect is robust against geometric variations, demonstrating that geometric asymmetry alone offers a minimal yet effective route to broadband elastic-wave mode conversion.

Decoding correlated errors in quantum LDPC codes