Superior electroadhesion force with permittivity-engineered bilayer films using electrostatic simulation and machine learning approaches.

Electroadhesive forces are crucial in various applications, including grasping devices, electro-sticky boards, electrostatic levitation, and climbing robots. However, the design of electroadhesive devices relies on speculative or empirical error approaches. Therefore, we present a theoretical model comprising predictive coplanar electrodes and protective layers for analyzing the electrostatic fields between an object and electroadhesive device.

Sustaining Surface Lithiophilicity of Ultrathin Li-Alloy Coating Layers on Current Collector for Zero-Excess Li-Metal Batteries.

Zero-excess Li-metal batteries (ZE-LMBs) have emerged as the ultimate battery platform, offering an exceptionally high energy density. However, the absence of Li-hosting materials results in uncontrolled dendritic Li deposition on the Cu current collector, leading to chronic loss of Li inventory and severe electrolyte decomposition, limiting its full utilization upon cycling. This study presents the application of ultrathin (≈50 nm) coatings comprising six metallic layers (Cu, Ag, Au, Pt, W, and Fe) on Cu substrates in order to provide insights into the design of Li-depositing current collectors for stable ZE-LMB operation.

Incidence and risk factors of PICC-related thrombosis in breast cancer: a meta-analysis.

Background: The incidence and risk factors of peripherally inserted central catheter-related thrombosis in patients with breast cancer have not been fully elucidated.

Method: Meta-analysis was performed by searching all studies on the incidence of peripherally inserted central catheter-associated thrombosis and risk factors for its formation in breast cancer patients from the establishment of the database to May 2023, including PubMed, Embase, Web of Science, China Knowledge Network, China Biomedical Literature Service System (SinoMed) and Wanfang databases. Then the incidence of peripherally inserted central catheter-related thrombosis and risk factors for its formation were analyzed in breast cancer patients.

Diagnosis of Current Flow Patterns Inside Fault-Simulated Li-Ion Batteries via Non-Invasive, In Operando Magnetic Field Imaging.

With the growing popularity of Li-ion batteries in large-scale applications, building a safer battery has become a common goal of the battery community. Although the small errors inside the cells trigger catastrophic failures, tracing them and distinguishing cell failure modes without knowledge of cell anatomy can be challenging using conventional methods. In this study, a real-time, non-invasive magnetic field imaging (MFI) analysis that can signal the battery current-induced magnetic field and visualize the current flow within Li-ion cells is developed.

The hidden community architecture of human brain networks.

The organizational principles of the community architecture of human brain networks are still mostly unknown. Here, we found that brain networks have a moderate degree of community segregation but are specifically organized to achieve high community overlap while maintaining their segregated community structures. These properties are distinct from other real-world complex networks.

A logical network-based drug-screening platform for Alzheimer's disease representing pathological features of human brain organoids.

Developing effective drugs for Alzheimer's disease (AD), the most common cause of dementia, has been difficult because of complicated pathogenesis. Here, we report an efficient, network-based drug-screening platform developed by integrating mathematical modeling and the pathological features of AD with human iPSC-derived cerebral organoids (iCOs), including CRISPR-Cas9-edited isogenic lines. We use 1300 organoids from 11 participants to build a high-content screening (HCS) system and test blood-brain barrier-permeable FDA-approved drugs.

The Hidden Control Architecture of Complex Brain Networks.

The brain controls various cognitive functions in a robust and efficient way. What is the control architecture of brain networks that enables such robust and optimal control? Is this brain control architecture distinct from that of other complex networks? Here, we developed a framework to delineate a control architecture of a complex network that is compatible with the behavior of the network and applied the framework to structural brain networks and other complex networks. As a result, we revealed that the brain networks have a distributed and overlapping control architecture governed by a small number of control nodes, which may be responsible for the robust and efficient brain functions.