Journal of Catalysis, Journal Year: 2024, Volume and Issue: unknown, P. 115877 - 115877
Published: Nov. 1, 2024
Language: Английский
Journal of Catalysis, Journal Year: 2024, Volume and Issue: unknown, P. 115877 - 115877
Published: Nov. 1, 2024
Language: Английский
Physical Chemistry Chemical Physics, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 1, 2025
Carbon nitride research has reached a promising point in today's endeavours with diverse applications including photocatalysis, energy storage, and sensing due to their unique electronic structural properties. Recent advances machine learning (ML) have opened new avenues for exploring optimizing the potential of these materials. This study presents comprehensive review integration ML techniques carbon an introduction CN classifications recent advancements. We discuss methodologies employed, such as supervised learning, unsupervised reinforcement predicting material properties, synthesis conditions, enhancing performance metrics. Key findings indicate that algorithms can significantly reduce experimental trial-and-error, accelerate discovery processes, provide deeper insights into structure-property relationships nitride. The synergistic effect combining traditional approaches is highlighted, showcasing studies where driven models successfully predicted novel compositions enhanced functional Future directions this field are also proposed, emphasizing need high-quality datasets, advanced models, interdisciplinary collaborations fully realize materials next-generation technologies.
Language: Английский
Citations
1Coordination Chemistry Reviews, Journal Year: 2024, Volume and Issue: 522, P. 216143 - 216143
Published: Sept. 14, 2024
Language: Английский
Citations
6Materials Science in Semiconductor Processing, Journal Year: 2024, Volume and Issue: 186, P. 109051 - 109051
Published: Oct. 30, 2024
Language: Английский
Citations
5Research on Chemical Intermediates, Journal Year: 2025, Volume and Issue: unknown
Published: Jan. 8, 2025
Language: Английский
Citations
0ACS Catalysis, Journal Year: 2025, Volume and Issue: unknown, P. 5155 - 5170
Published: March 12, 2025
Language: Английский
Citations
0The Journal of Physical Chemistry C, Journal Year: 2025, Volume and Issue: unknown
Published: March 13, 2025
Language: Английский
Citations
0International Journal of Hydrogen Energy, Journal Year: 2025, Volume and Issue: 127, P. 521 - 529
Published: April 15, 2025
Language: Английский
Citations
0Computational and Theoretical Chemistry, Journal Year: 2025, Volume and Issue: unknown, P. 115243 - 115243
Published: April 1, 2025
Language: Английский
Citations
0ACS Applied Materials & Interfaces, Journal Year: 2024, Volume and Issue: 16(45), P. 62043 - 62051
Published: Oct. 31, 2024
Designing high-efficiency bifunctional photocatalysts toward photoinduced overall water splitting is one of the most promising and challenging research directions for clean energy generation. By employing static electronic structure calculation nonadiabatic molecular dynamics (NAMD) simulation, we herein established a recently synthesized two-dimensional (2D) aza-fused covalent organic framework (aza-COF) as potential photocatalyst reactions. Our calculated results reveal that overpotentials hydrogen evolution reaction oxygen are only 0.06 0.31 V, respectively, at pH = 4. The photoexcited charge carriers studied through NAMD simulation predicts electron–hole recombination time (25.15 ns), this confirms photogenerated electron hole migrate to active sites occurrence before they recombine. Therefore, our suggest 2D aza-COFs exhibit great metal-free single-material under visible light.
Language: Английский
Citations
3Inorganic Chemistry Communications, Journal Year: 2024, Volume and Issue: 170, P. 113419 - 113419
Published: Nov. 4, 2024
Language: Английский
Citations
2