Results 211 to 220 of about 421,634 (286)

Mimetic Metrics for the DGSEM. [PDF]

J Sci Comput
Bach D, Rueda-Ramírez A, Kopriva DA, Gassner GJ.   +3 more
europepmc   +1 more source

CFD modeling and sensitivity‐guided design of silicon filament CVD reactors

AIChE Journal, EarlyView.
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, G. Loachamín‐Suntaxi, I. G. Aviziotis, E. D. Koronaki, P. P. Filippatos, G. Chatzigiannakis, S. P. A. Bordas, D. Davazoglou, A. G. Boudouvis   +8 more
wiley   +1 more source

Approximation of Anisotropic Pair Potentials Using Multivariate Interpolation. [PDF]

J Phys Chem B
Fakhraei M, Kieslich CA, Howard MP.
europepmc   +1 more source

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

A new hybrid block collocation method for solving elliptic PDEs. [PDF]

Sci Rep
Rufai MA, Filippone S, Ramos H, Modanese G.   +3 more
europepmc   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source

Parametric action of homomorphic image of modular group and it's application in image encryption. [PDF]

Sci Rep
Rafiq A, Bibi S, Abbasi AZ, Ali TS, Abdullah N, Becheikh N, Ghachem K, Hassen W.   +7 more
europepmc   +1 more source

Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

Advanced Intelligent Discovery, EarlyView.
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi, Kateryna Andriienkova, Tetyana Goldanova, Ezgi Antmen, Thibaut Soubrie, Nihal Engin Vrana   +5 more
wiley   +1 more source

An adaptive hybrid quadrature scheme: Combining Simpson's rule and Gaussian quadrature for enhanced numerical integration. [PDF]

PLoS One
Asgedom AA, Kefela YY.
europepmc   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source