The non-uniform pore size distribution and high flammability of commercial separators pose significant challenges to the safe application of high-energy-density lithium-ion batteries. In this study, a flame-retardant composite separator (P@HLi) with high thermal stability was successfully developed, which not only suppressed lithium dendrite growth but also improved high-temperature cycling performance of batteries and significantly enhanced their thermal safety. Li//Li symmetric batteries equipped with P@HLi-20 separators demonstrated stable cycling for over 600 h at a low polarization potential (approximately 50 mV), effectively reducing the formation of “dead lithium” and lithium dendrites. The LFP//Li and NCM811//Li cells with P@HLi-20 separators delivered initial discharge specific capacities of 142.0 and 167.9 mAh/g, respectively. Notably, the LFP//Li battery with P@HLi-20 separator showed excellent high-temperature cycling performance, maintaining 98.0% capacity retention and a discharge capacity of 131.1 mAh/g after 100 cycles at 1 C at 90 °C. Furthermore, pouch cells assembled with P@HLi-20 separators exhibited reductions of 52.67% in peak heat release rate (PHRR) and 68.42% in total heat release (THR) compared to those using Celgard separators, demonstrating superior thermal safety. These results confirm that the P@HLi separator offers comprehensive improvements in both electrochemical performance and safety characteristics.

A research team has developed a causal deep learning model to personalize corticosteroid therapy for intensive care unit patients with sepsis. Using data from patients across two major databases, the model accurately identified which patients would benefit, not benefit, or be harmed by treatment. Patients with severe metabolic acidosis and circulatory dysfunction showed the greatest survival benefit. This breakthrough could potentially optimize critical care decisions, reduce treatment risks, and improve survival rates in sepsis.

In the study, researchers identified top-performing covalent organic frameworks (COFs) for both adsorption and membrane separation, showing that 3D COFs with small pores excel in adsorption, while 2D COFs with large pores are ideal for membrane separation. The team also uncovered key features governing COFs' separation performance, pointing to more efficient ways to extract helium from natural gas.

Composite polymer electrolytes (CPEs) offer a promising solution for all-solid-state lithium-metal batteries (ASSLMBs). However, conventional nanofillers with Lewis-acid–base surfaces make limited contribution to improving the overall performance of CPEs due to their difficulty in achieving robust electrochemical and mechanical interfaces simultaneously. Here, by regulating the surface charge characteristics of halloysite nanotube (HNT), we propose a concept of lithium-ion dynamic interface (Li⁺-DI) engineering in nano-charged CPE (NCCPE). Results show that the surface charge characteristics of HNTs fundamentally change the Li⁺-DI, and thereof the mechanical and ion-conduction behaviors of the NCCPEs. Particularly, the HNTs with positively charged surface (HNTs⁺) lead to a higher Li⁺ transference number (0.86) than that of HNTs⁻ (0.73), but a lower toughness (102.13 MJ m⁻³ for HNTs⁺ and 159.69 MJ m⁻³ for HNTs⁻). Meanwhile, a strong interface compatibilization effect by Li⁺ is observed for especially the HNTs⁺-involved Li⁺-DI, which improves the toughness by 2000% compared with the control. Moreover, HNTs⁺ are more effective to weaken the Li⁺-solvation strength and facilitate the formation of LiF-rich solid–electrolyte interphase of Li metal compared to HNTs⁻. The resultant Li|NCCPE|LiFePO₄ cell delivers a capacity of 144.9 mAh g⁻¹ after 400 cycles at 0.5 C and a capacity retention of 78.6%. This study provides deep insights into understanding the roles of surface charges of nanofillers in regulating the mechanical and electrochemical interfaces in ASSLMBs.

Abstract

Purpose – Testing several approaches for implied volatility modeling and forecasting.

Design/methodology/approach – Comparative empirical study with four traded options.

Findings – Non-parametric higher-order spline is better than parametric stochastic volatility inspired (SVI) in China.

Research limitations/implications – Our results imply that even though popular on Wall Street, SVI seems not to be utilized by traders and market-makers in China.

Practical implications – Traders may consider higher-order splines as a better method for implied volatility modeling and forecasting.

Originality/value – Propose to model and forecast implied volatility via the fifth-order spline interpolation as a first; initiates studies of the empirical performance of SVI and the fifth-order spline models in implied volatility modeling and forecasting.

Five-axis machining plays a pivotal role in manufacturing complex industrial components. In a recent study, researchers introduced a surface-partitioning and iso-scallop field-based strategy tailored for non-spherical cutting tools. By adaptively dividing machining surfaces and generating smooth tool orientations, the method significantly shortens tool paths, reduces machining time, and improves surface quality. This breakthrough not only enhances industrial productivity but also provides a foundation for integrating intelligent optimization in smart manufacturing.

In the International Journal of Extreme Manufacturing, a team of Chinese researchers review the fast-growing field of Field-assisted Additive Manufacturing (FAM)—a method that combines 3D printing with external fields such as magnetic, acoustic, or electric stimuli to precisely guide materials as they form.