Active Learning‐Driven Discovery of Donor‐Acceptor Covalent Triazine Frameworks for High‐Performance Photocatalysts DOI
Mingliang Wu,

Jinxin Sun,

Yu Cui

et al.

Advanced Functional Materials, Journal Year: 2025, Volume and Issue: unknown

Published: May 2, 2025

Abstract Donor‐acceptor (D‐A) structure enables precise tuning of the electronic and optical properties materials, enabling widely applicable in organic semiconductors photocatalysts. However, vast diversity donor acceptor units their combinations pose considerable challenges to experimental development. Here, this study presents a screening strategy that integrates an active learning (AL)‐based multi‐model framework with synthesis validation discover high‐performance D‐A covalent triazine frameworks (CTFs) This combines AL model, trained on data reported D‐A‐CTFs, graph neural networks model establishes relationship between molecular properties. Meanwhile, expert chemical knowledge is incorporated into improve synthesizability stability, resulting 113 identified candidates from database 21807 structures. Experimental confirms 9 out 10 newly synthesized D‐A‐CTFs exhibit predicted photocatalytic performances. Notably, CTF‐[1,1′‐Biphenyl]‐4,4′‐dicarbaldehyde achieved record hydrogen evolution rate 33.29 mmol g −1 h for CTF‐based bulk Further feature engineering analysis reveals carbon nitrogen charges critically determine performance, offering optimization design. paves promising way accelerate discovery effective structured materials.

Language: Английский

FIB-SEM: Emerging Multimodal/Multiscale Characterization Techniques for Advanced Battery Development DOI
Zhao Liu,

Shuang Bai,

Sven Burke

et al.

Chemical Reviews, Journal Year: 2025, Volume and Issue: unknown

Published: May 1, 2025

The advancement of battery technology necessitates a profound understanding the physical, chemical, and electrochemical processes at various scales. Focused Ion Beam-Scanning Electron Microscopy (FIB-SEM) has emerged as an indispensable tool for research, enabling high-resolution imaging multiscale analysis from macroscopic structures to nanoscale features multiple dimensions. This review starts with introducing fundamentals focused beam matter interaction under framework FIB-SEM instrumentation then explores application characterization on rechargeable batteries (lithium-ion beyond), focus cathode anode materials, well solid-state batteries. Analytical techniques such Energy Dispersive X-ray Spectroscopy, Backscatter Diffraction, Secondary Mass Spectrometry are discussed in context their ability provide detailed morphological, crystallographic, chemical insights. also highlights several emerging applications including workflow maintain sample integrity, in-operando characterization, correlative microscopy. integration Artificial Intelligence enhanced data predictive modeling, which significantly improves accuracy efficiency material is discussed. Through comprehensive multimodal analysis, poised advance development high-performance paving way future innovations technology.

Language: Английский

Citations

0
Active Learning‐Driven Discovery of Donor‐Acceptor Covalent Triazine Frameworks for High‐Performance Photocatalysts DOI
Mingliang Wu,

Jinxin Sun,

Yu Cui

et al.

Advanced Functional Materials, Journal Year: 2025, Volume and Issue: unknown

Published: May 2, 2025

Abstract Donor‐acceptor (D‐A) structure enables precise tuning of the electronic and optical properties materials, enabling widely applicable in organic semiconductors photocatalysts. However, vast diversity donor acceptor units their combinations pose considerable challenges to experimental development. Here, this study presents a screening strategy that integrates an active learning (AL)‐based multi‐model framework with synthesis validation discover high‐performance D‐A covalent triazine frameworks (CTFs) This combines AL model, trained on data reported D‐A‐CTFs, graph neural networks model establishes relationship between molecular properties. Meanwhile, expert chemical knowledge is incorporated into improve synthesizability stability, resulting 113 identified candidates from database 21807 structures. Experimental confirms 9 out 10 newly synthesized D‐A‐CTFs exhibit predicted photocatalytic performances. Notably, CTF‐[1,1′‐Biphenyl]‐4,4′‐dicarbaldehyde achieved record hydrogen evolution rate 33.29 mmol g −1 h for CTF‐based bulk Further feature engineering analysis reveals carbon nitrogen charges critically determine performance, offering optimization design. paves promising way accelerate discovery effective structured materials.

Language: Английский

Citations

0