Results 141 to 150 of about 747,597 (268)
CFD modeling and sensitivity‐guided design of silicon filament CVD reactors
Abstract Filament‐based chemical vapor deposition (CVD) for silicon (Si) coatings is often treated as an adaptation of planar deposition. But this overlooks fundamental shifts in transport phenomena and reaction kinetics. In filament CVD, the filament acts as a substrate, heat source, and flow disruptor simultaneously. In this work, we ask: What really
G. P. Gakis +8 more
wiley +1 more source
Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation
We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley +1 more source
By modulating the topological structures of two N‐heterocycle‐based covalent organic frameworks, Phen‐TTA with a kgd‐v topology exhibits narrower optical bandgap, lower exciton binding energy, and faster charge‐carrier kinetics compared to O‐TTA with an hcb topology.
Lei Wang +9 more
wiley +2 more sources
Bubbles Acting as Micro End‐Effectors for Dexterous Manipulation and Sensing in Aqueous Environment
Inspired by bubbles, this article proposes a low‐cost method for multifunctional manipulation and sensing using microbubbles in aqueous environments. Bubbles are easily generated in situ, enabling the safe and adaptive handling of microobjects and sensing of microforces and surface textures.
Zichen Xu, Qingsong Xu
wiley +1 more source
This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi +3 more
wiley +1 more source
Driver Behavior Modeling with Subjective Risk‐Driven Inverse Reinforcement Learning
A subjective risk‐driven inverse reinforcement learning framework is proposed to model driver decision‐making. It infers drivers' risk perception and risk tolerance from driving data. A learnable risk threshold is used to regulate decisions, enabling interpretable and human‐like driving behavior decisions.
Yang Liang +6 more
wiley +1 more source
ABSTRACT In epidemiological studies, obsessive‐compulsive disorder (OCD) is robustly associated with increased risk of cardiometabolic disorders, including cardiovascular diseases, type 2 diabetes, and obesity. However, the mechanisms behind these associations are unclear. We conducted genetic correlation analyses to explore shared genetic etiology and
Robyn E. Wootton +217 more
wiley +1 more source
Clinical implementation and evaluation of a patient-specific surface-guided clearance mapping system for collision avoidance and noncoplanar beam planning. [PDF]
Wang S +10 more
europepmc +1 more source
Quantitative proteomics identifies clusterin as a novel biomarker for atherosclerosis
This schematic illustrates the proposed mechanism. In advanced atherosclerotic lesions, upregulated CLU on the cell surface activates low‐density lipoprotein (LDL) receptor‐related protein 1 (LRP1). This interaction triggers the phosphorylation and activation of AKT.
Dengfeng Ding +10 more
wiley +1 more source

