A Universal Strategy to Enhance Polarization Performance and Anode Reversal Tolerance by Polyaniline‐Coated Carbon Support for Proton Exchange Membrane Fuel Cells DOI Creative Commons
Zheng Li, Yongbiao Mu, Qing Zhang

et al.

Advanced Science, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 1, 2024

Abstract Anode cell reversal typically leads to severe carbon corrosion and catalyst layer collapse, which significantly compromises the durability of proton exchange membrane fuel cells. Herein, three types commercial supports with various structures are facilely coated by polyaniline (PANI) subsequently fabricated into reversal‐tolerant anodes (RTAs). Consequently, optimized PANI‐coated RTAs demonstrate enhanced polarization performance improved tolerance compared their uncoated counterparts, thus confirming universality this coating strategy. Essentially, surface engineering introduced PANI incorporates abundant N‐groups enhances coulombic interactions ionomer side chains, in turn reduces lower exposure, promotes more uniform Pt deposition, ensures better distribution. Accordingly, membrane‐electrode‐assembly containing Pt/PANI/XC‐72R‐1+IrO 2 RTA presents a 100 mV (at 2500 mA cm −2 ) improvement 26‐fold reduction degradation rate counterpart. This work provides universal strategy for developing durable lays groundwork practical fabrication high‐performance, low‐degradation RTA.

Language: Английский

AI in single-atom catalysts: a review of design and applications DOI Open Access

Qijun Yu,

Ninggui Ma,

Chihon Leung

et al.

Journal of Materials Informatics, Journal Year: 2025, Volume and Issue: 5(1)

Published: Feb. 12, 2025

Single-atom catalysts (SACs) have emerged as a research frontier in catalytic materials, distinguished by their unique atom-level dispersion, which significantly enhances activity, selectivity, and stability. SACs demonstrate substantial promise electrocatalysis applications, such fuel cells, CO2 reduction, hydrogen production, due to ability maximize utilization of active sites. However, the development efficient stable involves intricate design screening processes. In this work, artificial intelligence (AI), particularly machine learning (ML) neural networks (NNs), offers powerful tools for accelerating discovery optimization SACs. This review systematically discusses application AI technologies through four key stages: (1) Density functional theory (DFT) ab initio molecular dynamics (AIMD) simulations: DFT AIMD are used investigate mechanisms, with high-throughput applications expanding accessible datasets; (2) Regression models: ML regression models identify features that influence performance, streamlining selection promising materials; (3) NNs: NNs expedite known structural models, facilitating rapid assessment potential; (4) Generative adversarial (GANs): GANs enable prediction novel high-performance tailored specific requirements. work provides comprehensive overview current status insights recommendations future advancements field.

Language: Английский

Citations

2
Triggering nanoconfinement effect in advanced oxidation processes (AOPs) for boosted degradation of organic contaminants: A review DOI
Junsuo Li,

Yongshuo Wang,

Ziqian Wang

et al.

Chemical Engineering Journal, Journal Year: 2024, Volume and Issue: 503, P. 158428 - 158428

Published: Dec. 9, 2024

Language: Английский

Citations

9
Modulating the Coordination Environment of Atomically Dispersed Nickel for Efficient Electrocatalytic CO2 Reduction at Low Overpotentials and Industrial Current Densities DOI
Yichen Sun, Xiaolu Liu,

Jiazheng Tian

et al.

ACS Nano, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 23, 2025

Electrocatalytic CO2-to-CO conversion with a high CO Faradaic efficiency (FECO) at low overpotentials and industrial-level current densities is highly desirable but huge challenge over non-noble metal catalysts. Herein, graphitic N-rich porous carbons supporting atomically dispersed nickel (NiN4–O sites an axial oxygen) were synthesized (denoted as O–Ni–Nx–GC) applied the cathode catalyst in CO2RR flow cell. O–Ni–Nx–GC showed excellent selectivity FECO 92% ranging from 17 to 60 mV, 99% 80 mV. The was ∼100% 200 900 mA·cm–2. Impressively, delivered state-of-the-art of >96% 1 A·cm–2 turnover frequency 81.5 s–1 M KOH electrolyte. offered stability during long-term operation for 140 h 100 mA·cm–2, maintaining > 99%. Mechanism studies revealed that oxygen enhanced electron delocalization, carbon support lowering energy barrier inducing negative shift Ni-3d d-band center, effectively promoting formation *COOH intermediate while weakening adsorption *CO intermediate, thus optimizing catalytic activity/selectivity under practical conditions.

Language: Английский

Citations

1
Machine learning models for easily obtainable descriptors of the electrocatalytic properties of Ag–Pd–Ir nanoalloys toward the formate oxidation reaction DOI
Xiaoqing Liu, Fuyi Chen,

Wanxuan Zhang

et al.

Nanoscale, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

By training the overpotential dataset of Ag–Pd–Ir nanocatalysts using machine learning models, untrained formate oxidation reaction catalyst is predicted K-nearest neighbors model, screening best candidate catalysts.

Language: Английский

Citations

0
Applications of machine learning in surfaces and interfaces DOI Open Access
Shaofeng Xu, Jing‐Yuan Wu, Ying Guo

et al.

Chemical Physics Reviews, Journal Year: 2025, Volume and Issue: 6(1)

Published: March 1, 2025

Surfaces and interfaces play key roles in chemical material science. Understanding physical processes at complex surfaces is a challenging task. Machine learning provides powerful tool to help analyze accelerate simulations. This comprehensive review affords an overview of the applications machine study systems materials. We categorize into following broad categories: solid–solid interface, solid–liquid liquid–liquid surface solid, liquid, three-phase interfaces. High-throughput screening, combined first-principles calculations, force field accelerated molecular dynamics simulations are used rational design such as all-solid-state batteries, solar cells, heterogeneous catalysis. detailed information on for

Language: Английский

Citations

0
First-principles calculations insight into non-noble-metal bifunctional electrocatalysts for zinc–air batteries DOI

W.W. Zhang,

Yue Wang, Yongjun Li

et al.

Applied Energy, Journal Year: 2025, Volume and Issue: 391, P. 125925 - 125925

Published: April 13, 2025

Language: Английский

Citations

0
Machine-learning-assisted Design of Cathode Catalysts for Metal-Sulfur/Oxygen/Carbon Dioxide Batteries DOI
Qi Zhang, Rui Yang,

Zhengran Wang

et al.

Energy storage materials, Journal Year: 2025, Volume and Issue: unknown, P. 104261 - 104261

Published: April 1, 2025

Language: Английский

Citations

0
A Universal Strategy to Enhance Polarization Performance and Anode Reversal Tolerance by Polyaniline‐Coated Carbon Support for Proton Exchange Membrane Fuel Cells DOI Creative Commons
Zheng Li, Yongbiao Mu, Qing Zhang

et al.

Advanced Science, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 1, 2024

Abstract Anode cell reversal typically leads to severe carbon corrosion and catalyst layer collapse, which significantly compromises the durability of proton exchange membrane fuel cells. Herein, three types commercial supports with various structures are facilely coated by polyaniline (PANI) subsequently fabricated into reversal‐tolerant anodes (RTAs). Consequently, optimized PANI‐coated RTAs demonstrate enhanced polarization performance improved tolerance compared their uncoated counterparts, thus confirming universality this coating strategy. Essentially, surface engineering introduced PANI incorporates abundant N‐groups enhances coulombic interactions ionomer side chains, in turn reduces lower exposure, promotes more uniform Pt deposition, ensures better distribution. Accordingly, membrane‐electrode‐assembly containing Pt/PANI/XC‐72R‐1+IrO 2 RTA presents a 100 mV (at 2500 mA cm −2 ) improvement 26‐fold reduction degradation rate counterpart. This work provides universal strategy for developing durable lays groundwork practical fabrication high‐performance, low‐degradation RTA.

Language: Английский

Citations

0