Brain-computer interfaces are moving beyond simple device control toward more dexterous robotic assistance. A new review highlights how noninvasive neural decoding, deep learning, and shared autonomy are helping robotic devices better interpret user intent, reduce control burden, and support future assistive technologies for people with motor impairments and the general population.

A Chinese Medical Journal study reveals Rhein, a rhubarb-derived compound, protects against severe acute pancreatitis-associated intestinal injury by activating peroxisome proliferator-activated receptor γ (PPARγ) to suppress NOD-like receptor thermal protein domain associated protein 3 (NLRP3) inflammasome and reprogram macrophage polarization from pro-inflammatory M1 to anti-inflammatory M2 phenotype. Rhein restored intestinal barrier integrity and reduced endotoxemia—effects abolished by PPARγ inhibition. This identifies the PPARγ/NLRP3/macrophage axis as a promising therapeutic target for SAP complications.

 Researchers have developed a microwave‑assisted hydrothermal method for growing dense, uniform NaA zeolite coatings on silicon carbide (SiC) foams. The strong microwave absorption of SiC induces localized overheating, directing crystal growth onto the support surface while suppressing unwanted nucleation in the solution. A silica sol pretreatment effectively addresses support dissolution and enables rapid construction of a dense zeolite layer, achieving a mass variation of 1.11 after only five cycles. The resulting coating exhibits excellent adhesion, with a minimal mass loss of 0.62 % under rigorous ultrasonic and solvent‑flushing tests. In aldehyde‑ketone condensation reactions, the structured catalyst maintains a high yield (>90 %) over three cycles, offering a promising route to reduce raw material consumption.

Researchers have provided the first quantitative characterization of coalescence between a sessile droplet (attached to a fiber) and a pendant droplet (suspended in the continuous phase) – an asymmetric configuration prevalent in industrial fiber coalescers for oily wastewater treatment. Using high‑speed imaging and a Mask R‑CNN deep‑learning model, the study identified three distinct stages. The liquid bridge expansion (Stage I) is governed by capillary pressure difference, insensitive to droplet size ratio. In the oscillation decay stage (Stage II), fiber adhesion rapidly dissipates energy. Crucially, increasing the sessile‑to‑pendant radius ratio to 1.5 significantly reduces the size of secondary droplets generated during neck rupture, offering a direct strategy to improve separation efficiency.

Fiber coalescers are widely used to separate oil from water in petrochemical and other industries. Their performance depends on how dispersed oil droplets merge on fiber surfaces. Most previous studies focused on symmetric coalescence of two sessile droplets sitting on a fiber. In real industrial conditions, however, a more common event is the interaction between a sessile droplet already attached to a fiber and a pendant droplet suspended in the flowing continuous phase. This asymmetric configuration introduces gravity orientation and different kinematic freedom, yet it has remained largely unexplored.

In a study published in ENGINEERING Chemical Engineering, researchers from East China University of Science and Technology used a highspeed camera at 20,000 frames per second and trained a Mask RCNN neural network to automatically segment droplet boundaries and extract morphological parameters with high precision (mean relative error for liquid bridge width only 1.12 %). They systematically investigated coalescence for sessiletopendant radius ratios of 1, 1.25, and 1.5, with water droplets in isooctane under conditions where inertia dominates over viscosity.

The coalescence process comprises three stages. In Stage I (liquid bridge formation), upon contact a liquid bridge expands. The bridge width grows in proportion to the square root of time, confirming the classical capillaryinertial scaling. The driving capillary pressure difference is nearly independent of the droplet size ratio, showing that the initial dynamics are locally controlled by curvature rather than global dimensions.

Stage II (oscillation decay) shows unique behavior. In contrast to symmetric sessilesessile systems where periodic oscillations persist over many cycles, the pendantsessile configuration exhibits rapid energy dissipation because the fiber strongly suppresses oscillations through contact line damping. The amplitude of the capillary wave on the pendant droplet side increases with the size ratio. Neck rupture at the needle tip and fiber junction causes abrupt energy loss, eliminating distinct periodicity and leading to quick equilibrium.

Stage III (stable morphology formation) involves secondary droplet generation from pinchoff of neck filaments. The upper neck (needle side) evolves through hourglass, conical, and dropletformation stages, producing multiple secondary droplets. The lower neck (fiber side) is suppressed by fiber adhesion, generating only a single tiny droplet. Increasing the radius ratio to 1.5 systematically reduces secondary droplet sizes and completely eliminates fiberside breakup.

These findings provide direct guidance for controlling polydisperse droplet emissions in industrial fiber coalescers, enhancing oilwater separation efficiency.

Researchers propose a groundbreaking theoretical concept—equivalent potential—that bridges quantum mechanics with fluid behavior under microwave irradiation and interfacial confinement. This unified framework explains how microwave fields and solid surfaces jointly reshape fluid molecular arrangements, leading to ordered or disordered cluster structures. The work provides a fundamental principle for designing external-field-enhanced chemical processes, from CO₂ capture to catalytic conversion, and opens a pathway toward rational regulation of fluid structures at the nanoscale.

Solid‑state hydrogen storage offers high density and safety, but material development is slow. A comprehensive review highlights how machine learning (ML) and big data are accelerating discovery. The Digital Hydrogen‑S platform integrates over 3000 materials and 254,000 structured records, including multimodal data (PCT curves, kinetic data, synthesis metadata). Analysis shows that nearly no alloy meets US DOE targets for capacity, temperature, and pressure. ML models now predict storage capacity, formation enthalpy, and pressure‑composition‑temperature curves with high accuracy. Neural network potentials (NNPs) provide near‑first‑principles insight into hydrogen adsorption, dissociation, and diffusion. Future priorities include open‑access multimodal databases, inverse design, and generalized NNPs for complete absorption‑desorption cycles.

A stretchable, self-healing semiconductor has been developed using hierarchical hydrogen bonds—like mixing Velcro with a zipper. Unlike single-strength bonds, these multi-level bonds work together to balance rigidity and flexibility. It achieves 150% stretchability, 90% electrical healing, and record mobility of 1.01 cm² V⁻¹ s⁻¹ under 150% strain. This solves the trade-off between charge transport, stretchability, and healing ability, paving the way for future stretchable electronics.

Researchers from the group of Prof. Jia Shuang at Peking University and the group of Prof. Xu Gang at Huazhong University of Science and Technology have recently collaborated to investigate the heavy-fermion ferromagnet CeCrGe₃. They observed giant anomalous Hall and anomalous Nernst effects and revealed that these remarkable responses originate from Kondo-driven topological flat bands. The results were published under the title “Giant Anomalous Hall and Nernst Effects in a Heavy Fermion Ferromagnet” in Science Bulletin.