Results 11 to 20 of about 15,138 (216)

Breakthrough Solution for Antimicrobial Resistance Detection: Surface‐Enhanced Raman Spectroscopy‐based on Artificial Intelligence

Advanced Materials Interfaces, EarlyView., 2023
This review discusses the use of Surface‐Enhanced Raman Spectroscopy (SERS) combined with Artificial Intelligence (AI) for detecting antimicrobial resistance (AMR). Various SERS studies used with AI techniques, including machine learning and deep learning, are analyzed for their advantages and limitations.
Zakarya Al‐Shaebi, Munevver Akdeniz, Awel Olsido Ahmed, Mine Altunbek, Omer Aydin   +4 more
wiley   +1 more source

Evaluating feature extraction reproducibility across image biomarker standardization initiative‐compliant radiomics platforms using a digital phantom

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Background The aim of this study was to thoroughly analyze the reproducibility of radiomics feature extraction across three Image Biomarker Standardization Initiative (IBSI)‐compliant platforms using a digital phantom for benchmarking. It uncovers high consistency among common features while also pointing out the necessity for standardization ...
Han‐Back Shin, Heesoon Sheen, Jang‐Hoon Oh, Young Eun Choi, Kihoon Sung, Hyun Ju Kim   +5 more
wiley   +1 more source

Data‐driven forecasting of ship motions in waves using machine learning and dynamic mode decomposition

International Journal of Adaptive Control and Signal Processing, EarlyView.
Summary Data‐driven forecasting of ship motions in waves is investigated through feedforward and recurrent neural networks as well as dynamic mode decomposition. The goal is to predict future ship motion variables based on past data collected on the field, using equation‐free approaches.
Matteo Diez, Mauro Gaggero, Andrea Serani   +2 more
wiley   +1 more source

Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics

Advanced Engineering Materials, EarlyView.
Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani, Aditi Singh, Behnam Ashrafi   +2 more
wiley   +1 more source

A Case‐Based Reasoning Approach to Model Manufacturing Constraints for Impact Extrusion

Advanced Engineering Materials, EarlyView.
A hybrid modeling approach is presented that combines constraint‐based process modeling and case‐based reasoning. The model formalizes manufacturing constraints and integrates simulation data to model complex manufacturing processes. The approach supports manufacturability analysis during product design through an adaptive modeling environment.
Kevin Herrmann, Eduard Ortlieb, Hendrik Wester, Paul Christoph Gembarski, Bernd‐Arno Behrens, Roland Lachmayer   +5 more
wiley   +1 more source

Simulation of Inhomogeneous Refractive Index Fields Induced by Hot Tailored Forming Components

Advanced Engineering Materials, EarlyView.
This article presents a simulation model for simulating inhomogeneous refractive index fields (IRIF) in hot‐forged components, accounting for thermal influences and complex geometries. Through this simulation, a priori knowledge about the propagation of the IRIF can be obtained, allowing for the positioning of the component or an optical measurement ...
Pascal Kern, Lennart Hinz, Markus Kästner, Eduard Reithmeier   +3 more
wiley   +1 more source

A Novel Simulation Approach for Damage Evolution during Tailored Forming

Advanced Engineering Materials, EarlyView.
Traditional damage models are struggling to accurately and efficiently simulate large‐scale three‐dimensional models with a great number of degrees of freedoms. A new gradient‐enhanced damage model based on the extended Hamilton principle can significantly reduce the computation time while ensuring mesh‐independence which is suitable to use in tailored
Fangrui Liu, Dustin Roman Jantos, Philipp Junker   +2 more
wiley   +1 more source

On the Rigidity and Mechanical Behavior of Triply Periodic Minimal Surfaces‐Based Lattices: Insights from Extensive Experiments and Simulations

Advanced Engineering Materials, EarlyView.
This study examines the mechanical properties of triply periodic minimal surfaces (TPMS)‐based lattices, analyzing 36 architectures in elastic and plastic regimes. It evaluates the applicability of beam‐based scaling laws to TPMS lattices. Rigidity arises from the alignment of members with the load direction and solid regions preventing rotation.
Lucía Doyle, Humberto Terrones, Carlos González   +2 more
wiley   +1 more source

Laser Additive Manufacturing of Oxide‐Dispersion‐Strengthened Steels: A Simulation‐Based Comparison Between Powder Bed Fusion and Direct Energy Deposition

Advanced Engineering Materials, EarlyView.
Controlling the size and distribution of dispersoids is essential for optimizing the performance of oxide‐dispersion‐strengthened steels. This study focuses on nanoparticle dispersion and agglomeration during laser additive manufacturing of Fe20Cr alloy reinforced with ZrO 2 nanoparticles. Utilizing multiphysics phase‐field simulations and nanoparticle
Somnath Bharech, Yangyiwei Yang, Timileyin David Oyedeji, Prasanth Bondi, Mareen Goßling, Bilal Gökce, Bai‐Xiang Xu   +6 more
wiley   +1 more source

A Simulative Evaluation of Triply Periodic Minimal Surface Structures in the Context of Elastocaloric Applications

Advanced Engineering Materials, EarlyView.
A simulative evaluation of triply periodic minimal surface (TPMS) structures for an elastocaloric application under compressive load is performed. For the evaluation of the structure's performance, surface/volume ratio, generated heat and invested mechanical work are taken into account and are compared to a tube as a reference specimen.
Michael Fries, Paul Motzki, Dirk Bähre, Anne Jung   +3 more
wiley   +1 more source