Browse Articles

Geometrically driven reversible solid-liquid phase transition at the atomic scale

Atomic-resolution observation of the liquid-solid phase transition within a geometrically confined nanocluster provides fundamental insights into heterogeneous nucleation mechanisms. In this work, using in situ transmission electron microscopy, we directly control and observe a single critical-sized bismuth nanocluster within a tunable nanoscale gap, driving it through a reversible cycle from quasi-amorphous nanodisc, to crystalline nanowire, to liquid nanodroplet. The cluster’s aspect ratio, rather than its volume, is the primary descriptor governing these phase transitions, determined by the interplay between intrinsic surface anisotropy and interfacial energetics. Confinement also imposes texture, forcing the nanowire to adopt a preferred 2 1 ¯ 1 ¯ 0 orientation that is absent in unconfined nanoparticles. These results provide the mechanistic foundation for geometry-driven phase and orientation selection, which enables the rational design of nanomaterials through engineered confinement.

Time to Stop? Rethinking the Duration of Maintenance Treatment in Multiple Myeloma

Erratum for the Research Article “Elastic ice microfibers”

Lead Lines in Severe Lead Poisoning

Preferred synthesis of armchair transition metal dichalcogenide nanotubes

Nanotubes represent an important class of crystalline materials but controlling their structures, particularly chiralities, remains a fundamental challenge. In this work, we report a strategy for synthesizing transition-metal dichalcogenide nanotubes with preferred armchair chirality. tin disulfide, molybdenum disulfide, and tungsten disulfide nanotubes are formed with high yield and structural purity inside boron nitride nanotube channels. Atomic-resolution imaging, electron diffraction, and circular dichroism reveal an armchair preference up to 83%. Density functional theory rules out structural stability as the origin of this preference but confirms that zigzag nanoribbons are energetically more stable. Machine learning potential molecular dynamics simulate that zigzag nanoribbons roll up to form armchair nanotubes, a process that is subsequently observed by in situ transmission electron microscope. This work may inspire the achievement of on-demand synthesis of various nanotubes with specific chiralities.

Seeking universal malaria-vaccine targets

Reprogramming synthesis

General-purpose artificial intelligence agents are at work in the materials chemistry laboratory

Seabed mining requires timely governance

Spain’s largest research body confronts its dark past

Spanish National Research Council has published the stories of some 500 staff purged under Francisco Franco’s dictatorship

Systems-level design of a multi-epitope immunotherapeutic vaccine targeting EBV-associated oncogenesis

Abstract Epstein–Barr virus (EBV) is an oncogenic herpesvirus associated with multiple lymphoid and epithelial malignancies. Despite extensive investigation of EBV vaccine strategies, effective therapeutic approaches capable of targeting established EBV-associated cancers remain limited. In this study, we developed an integrated immunoinformatics and structure-guided framework for the design and prioritization of therapeutic multi-epitope vaccine candidates targeting both structural glycoproteins (gp350, gB, gH/gL, and gp42) and latency-associated proteins (EBNA1, LMP1, LMP2, and BZLF1). Sixteen multi-epitope vaccine constructs were generated and evaluated through sequence validation, structural refinement, reverse vaccinology assessment, immune-response simulation, receptor interaction analysis, molecular dynamics simulations, and expression-readiness profiling. The prioritized epitope repertoire achieved projected global population coverage exceeding 98% for both MHC class I and II pathways. Structural refinement improved model quality across vaccine constructs, while immunological and safety assessments supported favorable predicted antigenicity, non-allergenic potential, non-toxicity, and developability properties. Immune simulations predicted coordinated innate, humoral, and cellular responses, with several constructs demonstrating strong predicted immunogenic profiles. Molecular docking and molecular dynamics analyses further supported predicted structural compatibility and interaction stability with immune-associated receptors under simulated conditions. Integrated multi-parameter evaluation identified Constructs 4, 7, 10, 8, and 12 as the most promising candidates, with Construct 4 exhibiting the most balanced profile across immunological, structural, safety, and expression-related properties. Collectively, this study provides a comprehensive computational framework for therapeutic EBV vaccine development and identifies prioritized vaccine candidates for experimental validation. The proposed strategy offers a scalable approach for accelerating the development of multi-epitope vaccines targeting persistent viral infections and virus-associated malignancies.

Thrust prediction for hybrid rocket motors with aerodynamic throats based on radial basis function neural networks

TFIDD: Adaptive dynamics for fast model-agnostic drift detection

A surrogate-assisted framework for the subject-specific scalable design of compliant prosthetic wrists

Evaluating the effects of soil and water conservation measures on soil moisture regimes and crop performance in Jammu’s rainfed agroecosystems

Isomeric multi-hydrogen-bonding enables blue perovskite LEDs

Interleaved premotor rTMS does not affect motor sequence learning

Abstract Acquiring new motor skills is a vital component of lifelong learning and underpins everyday activities. Performance improvements through training evolve from an initially fragile state to one that becomes increasingly resistant to disruption, a process known as motor consolidation. Recent research has indicated that learning takes place even during brief periods of rest – termed micro-offline learning. In healthy young individuals, such intervals may represent the primary source of performance enhancements during training sessions. Other studies have identified both the primary motor cortex (M1) and the premotor cortex (PMC) as pivotal neural structures for motor consolidation. Specifically, it has been demonstrated that 10 Hz interleaved repetitive transcranial magnetic stimulation (i-rTMS) to M1 during rest intervals between active motor training blocks can enhance post-training offline consolidation without influencing performance during training. Here, we examined whether 10 Hz i-rTMS to the PMC produces similar effects. Contrary to our expectations, our results suggest that premotor i-rTMS does not affect online or offline learning, at both microscopic and macroscopic temporal scales. We also measured corticospinal excitability before and after training, but no detectable effects of training or i-rTMS were observed. Taken together, these findings provide no evidence for an effect of i-rTMS of the PMC on online or offline motor sequence learning. We speculate that consolidation during offline processing in short rest periods between active training phases may not necessarily require involvement of the premotor cortex.

Dendrite initiation and deflection in biaxially stressed solid electrolytes

Product appearance sensory evaluation model using Qualia Theory and AHP for Chaozhou woodcarving crafts

BASG-Net: a background-aware spatial gating network for cervical cell segmentation in pap smear images

Missense but mis-spliced: germline TP53 variant c.671A > C (p.E224A) and the path from uncertainty to pathogenicity