Hard carbon (HC) is considered the most promising anode material for sodium-ion batteries (SIBs) due to its high cost-effectiveness and outstanding overall performance. However, the amorphous and intricate microstructure of HC poses significant challenges in elucidating the structure–performance relationship, which has led to persistent misinterpretations regarding the intrinsic characteristics of closed pores. An irrational construction methodology of closed pores inevitably results in diminished plateau capacity, which severely restricts the practical application of HC in high-energy-density scenarios. This review provides a systematic exposition of the conceptual framework and origination mechanisms of closed pores, offering critical insights into their structural characteristics and formation pathways. Subsequently, by correlating lattice parameters with defect configurations, the structure–performance relationships governing desolvation kinetics and sodium storage behavior are rigorously established. Furthermore, pioneering advancements in structural engineering are critically synthesized to establish fundamental design principles for the rational modulation of closed pores in HC. It is imperative to emphasize that adopting a molecular-level perspective, coupled with a synergistic kinetic/thermodynamic approach, is critical for understanding and controlling the transformation process from open pores to closed pores. These innovative perspectives are strategically designed to accelerate the commercialization of HC, thereby catalyzing the sustainable and high-efficiency development of SIBs.

Rechargeable aqueous zinc (Zn)-metal batteries hold great promise for next-generation energy storage systems. However, their practical application is hindered by several challenges, including dendrite formation, corrosion, and the competing hydrogen evolution reaction. To address these issues, we designed and fabricated a composite protective layer for Zn anodes by integrating carbon nanotubes (CNTs) with chitosan through a simple and scalable scraping process. The CNTs ensure uniform electric field distribution due to their high electrical conductivity, while protonated chitosan regulates ion transport and suppresses dendrite formation at the anode interface. The chitosan/CNTs composite layer also facilitates smooth Zn²⁺ deposition, enhancing the stability and reversibility of the Zn anode. As a result, the chitosan/CNTs @ Zn anode demonstrates exceptional cycling stability, achieving over 3000 h of plating/stripping with minimal degradation. When paired with a V₂O₅ cathode, the composite-protected anode significantly improves the cycle stability and energy density of the full cell. Techno-economic analysis confirms that batteries incorporating the chitosan/CNTs protective layer outperform those with bare Zn anodes in terms of energy density and overall performance under optimized conditions. This work provides a scalable and sustainable strategy to overcome the critical challenges of aqueous Zn-metal batteries, paving the way for their practical application in next-generation energy storage systems.

In a pioneering study that explores the hidden carbon reservoirs of coastal ecosystems, researchers are quantifying the carbon stocks of macroalgal beds in the southwestern Atlantic Ocean. The study, titled "Carbon Stocks of Coastal Macroalgal Beds in the SW Atlantic," is led by Prof. Angelo Fraga Bernardino from the Departamento de Oceanografia at Universidade Federal Do Espírito Santo (UFES) in Vitória, Brazil. This research offers valuable insights into the role of macroalgal beds in carbon sequestration, highlighting their importance in marine protected areas.

A team of AI scientists and seismologists has developed a pioneering self-supervised framework, DASFormer, for high-resolution earthquake monitoring. Built on a two-stage, coarse-to-fine architecture, DASFormer is pre-trained on vast amounts of unlabeled Distributed Acoustic Sensing (DAS) data collected from existing fiber-optic cables (e.g., Internet cables). Acting like a “self-taught seismologist”, the model first learns the predictable patterns of background noise and then flags earthquake signals as anomalies that defy its forecasts. This novel approach demonstrates superior performance, outperforming other state-of-the-art models. Its versatility extends to challenging environments such as the seafloor, underscoring its potential for scalable, automated seismic intelligence.

Ultraviolet (UV) phototherapy is a widely used and effective dermatological treatment, yet its application has been limited by UV toxicity and challenges in targeted delivery. Upconversion nanoparticles (UCNPs), a novel photoluminescent nanomaterial capable of converting near-infrared (NIR) light into shorter-wavelength visible or UV light, hold promise for enabling NIR-driven skin phototherapy.