Progress in prediction of photocatalytic CO2 reduction using machine learning approach: A mini review

Next Materials, Год журнала: 2025, Номер 8, С. 100522 - 100522

Опубликована: Фев. 10, 2025

Язык: Английский

---

Research progress of machine learning in the field of photocatalysis applications

Journal of Industrial and Engineering Chemistry, Год журнала: 2025, Номер unknown

Опубликована: Апрель 1, 2025

Язык: Английский

---

Fabrication of S-scheme 0D/3D CeO2QDs/Bi2MoO6 micro-sphere heterostructures for tetracycline degradation from actual pharmaceutical wastewater

Journal of Environmental Management, Год журнала: 2025, Номер 376, С. 124561 - 124561

Опубликована: Фев. 18, 2025

Язык: Английский

---

A guided review of machine learning in the design and application for pore nanoarchitectonics of carbon materials

Materials Science and Engineering R Reports, Год журнала: 2025, Номер 165, С. 101010 - 101010

Опубликована: Май 3, 2025

Язык: Английский

---

Melanoma Skin Cancer Recognition with a Convolutional Neural Network and Feature Dimensions Reduction with Aquila Optimizer

Diagnostics, Год журнала: 2025, Номер 15(6), С. 761 - 761

Опубликована: Март 18, 2025

Background: Melanoma is a highly aggressive form of skin cancer, necessitating early and accurate detection for effective treatment. This study aims to develop novel classification system melanoma that integrates Convolutional Neural Networks (CNNs) feature extraction the Aquila Optimizer (AO) dimension reduction, improving both computational efficiency accuracy. Methods: The proposed method utilized CNNs extract features from images, while AO was employed reduce dimensionality, enhancing performance model. effectiveness this hybrid approach evaluated on three publicly available datasets: ISIC 2019, ISBI 2016, 2017. Results: For 2019 dataset, model achieved 97.46% sensitivity, 98.89% specificity, 98.42% accuracy, 97.91% precision, 97.68% F1-score, 99.12% AUC-ROC. On 2016 it reached 98.45% 98.24% 97.22% 97.84% 97.62% 98.97% 2017, results were 98.44% 98.86% 97.96% 98.12% 97.88% 99.03% outperforms existing advanced techniques, with 4.2% higher 6.2% improvement in 5.8% increase specificity. Additionally, reduced complexity by up 37.5%. Conclusions: deep learning-Aquila (DL-AO) framework offers efficient detection, making suitable deployment resource-constrained environments such as mobile edge computing platforms. integration DL metaheuristic optimization significantly enhances robustness, detection.

Язык: Английский

---

In₂S₃‐BaTiO₃ S‐Type Heterojunction Photocatalyst for Efficient Antibiotic Degradation and Hydrogen Generation

Small, Год журнала: 2025, Номер unknown

Опубликована: Апрель 24, 2025

Abstract Quinolone antibiotics, particularly moxifloxacin (MOX), are increasingly contaminating aquatic ecosystems, posing significant threats to both the environment and human health. Due its hydrophilicity stability, traditional water treatment methods ineffective in degrading MOX. In this study, a novel S‐type heterojunction photocatalyst, In‐Ba‐10, is introduced which combines barium titanate (BaTiO 3 ) indium sulfide (In 2 S address challenge. The In‐Ba‐10 catalyst demonstrates excellent photocatalytic performance, with hydrogen production rate of 2050 µmol g −1 h MOX degradation constant (k) 0.049 min . Compared BaTiO alone, performance enhanced by 48‐ 49‐fold, respectively. Comprehensive characterization, including Raman spectroscopy, X‐ray photoelectron spectroscopy (XPS), electron microscopy, reveals that effectively promotes charge separation transfer, reduces electron–hole recombination, improves catalytic efficiency. First‐principles calculations further confirm role as reduction site oxidation site. addition high activity, ‐BaTiO shows stability over multiple cycles, making it promising candidate for sustainable wastewater treatment. This study highlights potential photocatalysts environmental remediation energy applications.

Язык: Английский

---

Recent advances in high-performance Cu/SiO2 catalysts for hydrogenation of dimethyl oxalate to ethylene glycol

Chemical Engineering Science, Год журнала: 2025, Номер unknown, С. 121761 - 121761

Опубликована: Май 1, 2025

Язык: Английский

---

Co3+ in cobalt (100)/g-C3N4 facilitating the conversion of superoxide radicals into hydroxyl radicals and improving photocatalysis

Applied Surface Science, Год журнала: 2025, Номер unknown, С. 163536 - 163536

Опубликована: Май 1, 2025

Язык: Английский

---

Artificial Intelligence and Machine Learning for the Optimization of Photocatalytic Performance

Energy 360., Год журнала: 2025, Номер unknown, С. 100027 - 100027

Опубликована: Май 1, 2025

Язык: Английский

---