Results 61 to 70 of about 1,367 (230)

A Crack‐Based One‐Dimensional Microspheres Array Enables Thermal–Mechanical Decoupled Dual‐Functional Sensing

open access: yesAdvanced Science, EarlyView.
Inspired by Nostoc, a crack‐based one‐dimensional microspheres array (COMA) sensor is developed, which stabilizes crack geometry under isotropic expansion, enabling a predictable, monotonic thermal response from which true strain can be accurately extracted. The COMA sensor exhibits high sensitivity at ultralow deformation (gauge factor up to 89) and a
Wanqing Xu   +7 more
wiley   +1 more source

Dielectric‐Confinement‐Induced in‐Plane Photoelectric Anisotropy in Isotropic Quasi‐1D γ‐GaS Nanoribbon

open access: yesAdvanced Science, EarlyView.
We investigate the geometry‐governed optoelectronic anisotropy arising from dielectric confinement in quasi‐1D γ‐GaS nanoribbons with intrinsically isotropic atomic structures. Dielectric mismatch between the nanoribbon and its surroundings leads to a general polarization‐dependent photoresponse during near‐field scattering.
Jiawei Jing   +16 more
wiley   +1 more source

Combined FEM/Meshfree SPH Method for Impact Damage Prediction of Composite Sandwich Panels

open access: yes, 2005
In this work, impact simulations using both meshfree Smoothed Particle Hydrodynamics (SPH) and combined FEM/SPH Method were carried out for a sandwich composite panel with carbon fibre fabric/epoxy face skins and polyetherimide (PEI) foam core.
Aktay, Levent   +2 more
core  

Capacitive versus Faradaic Microelectrodes for Extracellular Stimulation: A Fully Coupled FEM–Hodgkin–Huxley Study of Thresholds and Current Redistribution

open access: yesAdvanced Electronic Materials, EarlyView.
A fully coupled FEM–HH model shows that ideally capacitive microelectrodes can achieve lower charge‐density thresholds than Faradaic contacts under current‐controlled stimulation. The advantage stems from the dynamics of surface current density on capacitive interfaces, which redirects current beneath adherent neurons.
Aleksandar Opančar   +2 more
wiley   +1 more source

Consistency and convergence of SPH approximations

open access: yes, 2009
Includes bibliographical references (leaves 58-59).Includes abstract.This thesis is about a new approach to SPH. Instead of using a single kernel or shape function for approximation of a function and its derivatives, individual shape functions are used ...
Penzhorn, Karl
core  

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

open access: yesAdvanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen   +4 more
wiley   +1 more source

Large-scale adaptive mantle convection simulation

open access: yes
A new generation, parallel adaptive-mesh mantle convection code, Rhea, is described and benchmarked. Rhea targets large-scale mantle convection simulations on parallel computers, and thus has been developed with a strong focus on computational efficiency
Wilcox, Lucas C.   +6 more
core   +1 more source

Meshless methods: theory and application in 3D fracture modelling with level sets [PDF]

open access: yes, 2010
Accurate analysis of fracture is of vital importance yet methods for effetive 3D calculations are currently unsatisfactory. In this thesis, novel numerical techniques are developed which solve many of these problems. This thesis consists two major parts:
ZHUANG, XIAOYING
core  

Reliability Based Topology Optimization of a Linear Piezoelectric Micromotor Using the Cell-Based Smoothed Finite Element Method

open access: yes, 2011
This paper presents integration of reliability analysis with topology optimization design for a linear mircroactuator, including multitude cantilever piezoelectric bimorphs.
Mohammad Reza Razfar   +2 more
core   +1 more source

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

open access: yesAdvanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas   +4 more
wiley   +1 more source

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