Results 111 to 120 of about 63,084 (306)
We address the inherently weak particle adhesion of conventional air filters by coating a dynamically crosslinked adhesive layer that delivers capillarity‐driven strong adhesion and particle absorption mediated by dynamic bond exchange. The resulting enhancement in particle adhesion enables efficient ultrafast (up to 20 m s−1) and omnidirectional ...
Junyong Park +11 more
wiley +1 more source
Explicit and implicit modeling of nanobubbles in hydrophobic confinement
Water at normal conditions is a fluid thermodynamically close to the liquid-vapor phase coexistence and features a large surface tension. This combination can lead to interesting capillary phenomena on microscopic scales.
Joachim Dzubiella
doaj +1 more source
Implicit Modeling with Procedural Techniques
Implicit modeling eases the design and animation of complex objects; however, it does not solve the problem completely for extremely complex surface design problems and for modeling volumetric phenomena. Procedural techniques are another growing solution
David Ebert, Edward Bedwell
core
Implicit large eddy simulation of ship airwakes [PDF]
Implicit large eddy simulations (ILES) of two different Royal Navy ships have been conducted as part of the UK Ship/Air Interface Frame-work project using a recently developed very high order accuracy numerical method.
Thornber, Ben +2 more
core
This review summarizes the principles and challenges of nonaqueous lithium‐oxygen batteries and recent advances in cathode catalysts, including carbon‐based materials, metals, oxides, sulfides, nitrides, carbides, and redox mediators. It highlights emerging design strategies and artificial intelligence‐driven approaches, emphasizing data‐assisted ...
Yuqing Yao +8 more
wiley +1 more source
We introduce a computational workflow that combines quantum chemical calculations and machine learning techniques to predict the catalytic performance of a wide range of catalysts in the nitrogen reduction reaction (NRR). The analysis of the trained models provides insights into the complex structure–activity relationship in experimental catalytic ...
Leonardo Di Ciano +5 more
wiley +1 more source
The Extrapolation Power of Implicit Models
In this paper, we investigate the extrapolation capabilities of implicit deep learning models in handling unobserved data, where traditional deep neural networks may falter. Implicit models, distinguished by their adaptability in layer depth and incorporation of feedback within their computational graph, are put to the test across various extrapolation
Juliette Decugis +4 more
openaire +2 more sources
Implicit Structural Modeling with Local Meshless Functions
International audienceWe propose an implicit structural modeling method to generate geological models from evidences of horizons and interpreted discontinuity surfaces such as faults and stratigraphic unconformities.
G. Caumon +7 more
core +1 more source
Phase Diagrams Enable Solid‐State Battery Design
Batteries are non‐equilibrium devices with inherent thermodynamic driving forces to react at interfaces, regardless of kinetics or operating conditions. Chemical potential mismatches across interfaces are dissipated via interfacial reactions. In this work, it is illustrated how phase diagrams and chemical potential maps predict degradation pathways but
Nathaniel L. Skeele, Matthias T. Agne
wiley +1 more source
A Survey of Interlayer Interaction Models for Graphene and Other 2D Materials
Van der Waals interactions arising from electronic polarization at atomically close interfaces generate corrugated interlayer energy landscapes that govern normal and tangential tractions. This review presents an overview of quantum, atomistic, analytical, and continuum modeling approaches, highlighting their roles across length scales in capturing ...
Gourav Yadav +2 more
wiley +1 more source

