Deciphering Closed-Pore Formation and Size-Dependent Sodium Cluster Filling Behavior for Nanopore-Confined Derived Hard Carbon Anodes.

The low-voltage plateau capacity (LVPC) of hard carbon (HC) anodes for sodium-ion batteries originates from sodium cluster filling within closed pores, and closed-pore engineering of activated carbon (AC) via nanopore-confined pyrolysis is a feasible strategy to produce HC anodes with high LVPC. However, the formation mechanism of closed pores and their size-dependent effects on sodium cluster filling behavior remain poorly understood. Herein, pitch-confined pyrolysis is utilized within the nanopores of AC to transform its open pores into closed pores, with pitch dose regulating closed-pore size.

Tuning Diffusion Preferences in Silicon-Based Anodes for Enhanced Rapid and Homogeneous Lithiation.

The inherently sluggish lithiation kinetics of silicon (Si), coupled with its severe volume expansion, causes lithiation retardation and thus exacerbates the failure of Si-based anodes. Here, a Li-diffusion-preference tuning strategy for homogeneous lithiation of Si has been proposed to address these issues and successfully validated through both simulation and experiments using commercial photovoltaic silicon waste (Si). In detail, Li preferentially diffuses along grain boundaries (GBs) and then into grains, enabling rapid and homogeneous lithiation throughout the Si particles rather than the conventional outside-to-inside lithiation process that suffers from lithiation retardation.

Mechanisms and implications of epithelial cell plasticity in the bladder.

Cellular plasticity, the ability of cells to reprogramme and alter their fate, has a pivotal role in maintaining homeostasis and facilitating tissue regeneration after injury. The bladder urothelium, a dynamic transitional epithelial layer, displays a highly plastic phenotype that enables its remarkable regenerative capacity in response to wounding. During both development and repair, urothelial cells exhibit considerable plasticity through processes such as dedifferentiation, transdifferentiation and epithelial-to-mesenchymal transition.

Solid-state amorphization to alleviate severe volume expansion in silicon-based anodes.

The anisotropic lithiation-induced expansion of crystalline silicon leads to uneven volume expansion and extreme stress concentration. This issue will be effectively mitigated by employing an isotropic amorphous structure. Here, an isotropic porous amorphous silicon (aSi) was prepared using a simple and safe method, followed by mechanical mixing with graphite to form an aSi/graphite composite (aSG60).

Boosting High-Temperature Durability of Industrial-Scale LiMnFePO Cathode through Niobium Doping.

Renewable energy's growth of renewable energy drives the need for advanced lithium-ion batteries (LIBs). LiMnFePO (LMFP) cathode materials show promise but face challenges like the Jahn-Teller effect and metal dissolution, undermining structural stability and cycling performance, especially under elevated temperatures. This study pioneers the strategic doping of high-valence niobium (Nb) into LMFP to address these limitations.

Deep Rib Fracture Instance Segmentation and Classification From CT on the RibFrac Challenge.

Rib fractures are a common and potentially severe injury that can be challenging and labor-intensive to detect in CT scans. While there have been efforts to address this field, the lack of large-scale annotated datasets and evaluation benchmarks has hindered the development and validation of deep learning algorithms. To address this issue, the RibFrac Challenge was introduced, providing a benchmark dataset of over 5,000 rib fractures from 660 CT scans, with voxel-level instance mask annotations and diagnosis labels for four clinical categories (buckle, nondisplaced, displaced, or segmental).

C to Modulate the Closed Pore Structures of Hard Carbon for High-Performance Sodium-Ion Batteries.

Hard carbon (HC) has emerged as a highly promising anode material for sodium-ion batteries (SIBs) attributed to its characteristic low-potential charge and discharge plateau. Recent studies have shown that the plateau capacity of HC mainly originates from the filling of the nanoscale closed pores by sodium. However, the precise design of the closed pore structure of HC remains a great challenge.

Treatment of cationic red X-GRL in high-salt printing and dyeing wastewater by an electrocatalytic ozonation system: treatment efficiency and degradation mechanism.

High salt concentrations in printing and dyeing wastewaters significantly influence pollutant removal. The function of the electrocatalytic ozonation (MgMn O -GAC/EP) system in removing pollutants from high-salt printing and dyeing wastewater was investigated. Under high NaCl concentration, the HO yield in the electrochemical system was maintained at approximately 53 mg L.

Association of daily step counts and step intensity with mortality among US adults: a cross-sectional study of NHANES 2005-2006.

Background & Aims: We aimed to describe the dose-response relationship between daily step counts and intensity with respect to all-cause mortality among US adults diagnosed with metabolic dysfunction-associated steatotic liver disease (MASLD).

Methods: Using data from the National Health and Nutrition Examination Survey (NHANES) database spanning from 2005 to 2006, a cross-sectional study included 1,108 participants was performed to assess the relationship between daily step counts and step intensity with mortality.

Results: A total of 1,108 participants from the NHANES study were included, with a mean age of 49.

Changes in rheological properties and structure of wheat gluten proteins induced by transglutaminase.

To elucidate the effect of transglutaminase (TG) on the rheological properties of wheat gluten, this study investigates the underlying mechanisms by analyzing changes in gluten structure. The results demonstrated that the TG-treated gluten samples had higher storage modulus (G') and loss modulus (G″) compared to the control, conversely, creep and recovery strains followed an opposite trend. Notably, the most pronounced effects were observed with adding 2 U/g TG for 20-30 min.

Protein aggregation behavior and structural characteristics in a lipoxygenase-linoleic acid-wheat gluten model system.

This study explores the synergistic effects of linoleic acid (LA) oxidation on the aggregation behavior and structural properties of wheat gluten (WG). Using lipoxygenase to induce LA oxidation, it was observed that this process significantly influenced WG's viscoelasticity and structural characteristics. Specifically, LA oxidation enhanced WG's viscoelastic properties while reducing its instantaneous elastic and recovery deformations.

Advancing river flood forecasting with a collaborative integrated modeling method.

River flood forecasting and assessment are crucial for reducing flood risks, as they offer early alerts and allow for proactive actions to safeguard individuals from possible flood-related damage. Effective modeling in this field often multiple interconnected aspects of the hydrologic cycle, such as precipitation, infiltration, runoff, and evaporation, requiring collaboration among hydrology experts. Such collaboration enables experts to handle and manage their specialized processes more effectively, thereby enhancing the efficiency of the development of integrated flood forecasting models.

The Synergetic Effect of Metal-Loaded Electrospun Carbon Fibers for Photothermal Conversion.

With the increasing demand for energy and worsening environmental issues, the application of photothermal materials has been widely explored due to their high energy conversion capabilities and environmental friendliness. In this work, metal-carbon fiber composites were prepared and subjected to photothermal and water evaporation performance tests alongside pure metals and pyrolytic phenolic resin materials. The results show that the addition of metals effectively improved the photothermal efficiency by narrowing the molecular energy gaps of the materials, indicating a strong synergistic enhancement effect between metals and carbon materials.

Quantum Dynamics Studies of the Li + Na ( = 0, = 0) → Na + NaLi Reaction on a New Neural Network Potential Energy Surface.

The ultracold reaction offers a unique opportunity to elucidate the intricate microscopic mechanism of chemical reactions, and the NaLi system serves as a pivotal reaction system in the investigation of ultracold reactions. In this work, a high-precision potential energy surface (PES) of the NaLi system is constructed based on high-level ab initio energy points and the neural network (NN) method, and a proper asymptotic functional form is adopted for the long-range interaction, which is suitable for the study of cold or ultracold collisions. Based on the new NN PES, the dynamics of the Li + Na ( = 0, = 0) → Na + NaLi reaction are studied in the collision energy range of 10 to 80 cm.

URCA: Uncertainty-based region clipping algorithm for semi-supervised medical image segmentation.

Background And Objective: Training convolutional neural networks based on large amount of labeled data has made great progress in the field of image segmentation. However, in medical image segmentation tasks, annotating the data is expensive and time-consuming because pixel-level annotation requires experts in the relevant field. Currently, the combination of consistent regularization and pseudo labeling-based semi-supervised methods has shown good performance in image segmentation.

A neural network potential energy surface of the Li system and quantum dynamics studies for the Li + Li → LiLi + Li reaction.

A high-precision global potential energy surface (PES) of the Li system is constructed based on high-level calculations, and the root-mean-square error is 5.54 cm. The short-range of the PES is fitted by the fundamental invariant neural network (FI-NN) method, while the long-range uses a function with an accurate asymptotic potential energy form, and the two regions are connected by a switching function.

Synthetically Feasible De Novo Molecular Design of Leads Based on a Reinforcement Learning Model: AI-Assisted Discovery of an Anti-IBD Lead Targeting CXCR4.

Artificial intelligence (AI) de novo molecular generation provides leads with novel structures for drug discovery. However, the target affinity and synthesizability of the generated molecules present critical challenges for the successful application of AI technology. Therefore, we developed an advanced reinforcement learning model to bridge the gap between the theory of de novo molecular generation and the practical aspects of drug discovery.

Regulating Bacterial Culture through Tailored Silk Inverse Opal Scaffolds.

Controlling the growth of microbial consortia is of great significance in the biomedical field. Selective bacterial growth is achieved by fabricating silk inverse opal (SIO) scaffolds with varying pore sizes ranging from 0.3 to 4.