Design and synthesis of iron-nickel oxide/nickel oxide at carbon sphere for effective electrochemical detection of hazardous pesticide fenitrothion

Journal of environmental chemical engineering, Год журнала: 2025, Номер unknown, С. 115621 - 115621

Опубликована: Янв. 1, 2025

Язык: Английский

Novel Estimation of Nanofiber Diameter from SEM Images Using Deep Feature Embeddings and Machine Learning Models

Advanced Theory and Simulations, Год журнала: 2025, Номер unknown

Опубликована: Апрель 17, 2025

Abstract Accurate nanofiber diameter estimation is crucial for optimizing their functionality in materials science. Traditional measurement methods from Scanning Electron Microscopy (SEM) images are often labor‐intensive and subjective. This study proposes a machine learning‐based approach using deep feature embeddings to predict average diameters directly SEM images. Eight learning models—Linear Regression (LR), k‐Nearest Neighbors (kNN), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), Neural Network (NN), Gradient Boosting (GB), AdaBoost—are evaluated 5‐fold 10‐fold cross‐validation. Performance assessed via Mean Squared Error (MSE), Root (RMSE), Absolute (MAE), Percentage (MAPE), R 2 . The kNN model consistently outperformed others across three datasets: smooth nanofibers, beaded combined set. It achieves the lowest error metrics highest (0.950) while demonstrating strong generalization morphologies. among first integrate with direct prediction, providing reliable alternative traditional methods.

Язык: Английский

Efficient As(V) removal by NiFe-LDHs and NiFe2O4 in situ growth on 3D porous carbon foam fabricated from waste melamine–formaldehyde foam

Desalination and Water Treatment, Год журнала: 2024, Номер 320, С. 100876 - 100876

Опубликована: Окт. 1, 2024

Язык: Английский