Fe Single-Atom Catalyst for Cost-Effective yet Highly Efficient Heterogeneous Fenton Catalysis

Shi, Bofang; Li, Hang; Fu, Xiaojie; Zhao, Chengcheng; Li, Mingtao; Liu, Maochang; Yan, Wei; Yang, Honghui

doi:10.1021/acsami.2c15232

Cited by 17 publications

(7 citation statements)

References 74 publications

(114 reference statements)

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“…The maximum phenol degradation rate in SACs reaches 0.158 min –1 when the synthesis conditions are Fe addition of 4 wt %, a calcination time of 3 h, a calcination heating rate of 0.6 °C/min, a calcination temperature of 680 °C, N addition of 18%, Fe addition of 4%, a pyrolysis heating rate of 0.7 °C/min, a pyrolysis time of 2 h, and a pyrolysis temperature of 240 °C, which substantially surpasses the highest k in the original data set. More importantly, such a high k value of an ML-guided SAC is higher than most other reported state-of-the-art Fe-based Fenton-like catalysts (Figure a and Table S3), − which verifies the effectiveness of the trained ML model.…”

Section: Resultsmentioning

confidence: 57%

Machine-Learning-Assisted Optimization of a Single-Atom Coordination Environment for Accelerated Fenton Catalysis

Zhang

et al. 2023

ACS Nano

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Machine learning (ML) algorithms will be enablers in revolutionizing traditional methods of materials optimization. Here, we broaden the use of ML to assist the construction of Fenton-like single-atom catalysts (SACs) by developing a methodology including model building, training, and prediction. Our approach can efficiently extract synthesis parameters that exert a substantial influence on Fenton activity and accurately predict the phenol degradation rate k of SACs with a mean error of ±0.018 min −1 . The extended synthesis window with accelerated learning enables the realization that the heating temperatures during SAC synthesis significantly influence the Fe−N coordination number, which ultimately dictates their performance. Through ML-guided optimization, a highly efficient SAC dominated by Fe−N 5 sites with exceptional Fenton activity (k = 0.158 min −1 ) is identified. Our work provides an example for ML-assisted optimization of single-atom coordination environments and illuminates the feasibility of ML in accelerating the development of high-performance catalysts.

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Section: Resultsmentioning

confidence: 57%

Machine-Learning-Assisted Optimization of a Single-Atom Coordination Environment for Accelerated Fenton Catalysis

Zhang

et al. 2023

ACS Nano

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“…Figure B describes the ESR spectra of the formation of DMPO/ • OH species in Cu@MIL-88B Fenton-like system at 5 min. A four-fold unique peak signal with an intensity ratio of 1:2:2:1 was detected, indicating the presence of • OH in the reaction system and the • OH signal peak intensity of 0.4Cu@MIL-88B is the highest.…”

Section: Resultsmentioning

confidence: 99%

Effects and Mechanisms of Cu Species in Fe-MOFs on Fenton-Like Catalytic Activity and Stability

Song

Han

Wang

et al. 2023

ACS Appl. Mater. Interfaces

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Fe-based MOFs (Fe-MOFs) are deemed promising Fenton-like catalysts due to their well-developed pores and accessible active sites. However, their inferior catalytic activity, iron leaching, and low H2O2 utilization always hinder their application as Fe-based MOF catalysts. In this work, we manipulated the structure of Fe-oxo nodes in MIL-88B(Fe) via a CuI species substitution method, affording a mixed-valence (Cu-incorporated Fe-MOFs) with highly improved Fenton-like performance. It is found that the CuI serves as a shuttle to promote transfer between FeII/FeIII, inducing the formation of a larger amount of stable FeII sites, which was proven by experimental and DFT calculation results. A linear relationship was observed for the Fenton-like performance and the amount of CuI species for the catalysts. The corresponding value of the •OH formation is 2.17 eV for Cu-incorporated MIL-88B(Fe), which is significantly lower than that of MIL-88B(Fe) (2.69 eV). Meanwhile, the enriched CuI species suppress Fe species leaching during the catalytic reaction. The Fe-ion leakage of 0.4Cu@MIL-88B is very tiny (0.01–0.03 mg/L), significantly less than that of MIL-88B (2.00–3.02 mg/L). At the same time, H2O2 utilization for 0.4Cu@ MIL-88B(Fe) is 88%, which is almost 4.4 times that of pure MIL-88B(Fe). This work provides insights into the rational design of Fe-MOFs as promising Fenton-like catalysts for wastewater treatment.

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“…A literature report by Shi et al 58 suggested that the −N� site of the PAni (EB) polymer is energetically more favorable for coordination with a Fe atom compared to the −NH− site. Based on this finding, binary composites of PAni and TMs were formed by decorating the first-row TMs on the −N� site, as depicted in Figure 1b.…”

Section: The Journal Of Physical Chemistry Amentioning

confidence: 99%

DFT Study on the Spin States of Polyaniline–3d Transition-Metal (Sc–Zn) Composites and Their Sensing Application to Detect Chemical Warfare Agents

Garg,

Singla,

Goel

2024

J. Phys. Chem. A

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Organic–inorganic composite materials, combining polymers with transition metal (TM) atoms based on PAni and 3d TMs, have been designed and investigated in various spin states by performing density functional calculations. These designed composites were analyzed for their stability in different spin states as well as for their calculated electronic properties, including binding energies, frontier molecular orbitals, and dipole moments. Additionally, 3D isosurfaces and 2D scattered plots of reduced density gradient as a function of (sign λ2)ρ provide insights into the noncovalent interactions between the composite units. The most stable Mn@PAni composite has been assessed as a sensing material for chemical warfare blood agents (HCN, NCCl, NCBr, NCCN, and AsH3) using density functional-based calculations. The reduced band gap and significant red/blue shift in the UV–vis spectra obtained through TDDFT calculations underline the selectivity and efficiency of the Mn@PAni composite toward different analytes.

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Fe Single-Atom Catalyst for Cost-Effective yet Highly Efficient Heterogeneous Fenton Catalysis

Cited by 17 publications

References 74 publications

Machine-Learning-Assisted Optimization of a Single-Atom Coordination Environment for Accelerated Fenton Catalysis

Machine-Learning-Assisted Optimization of a Single-Atom Coordination Environment for Accelerated Fenton Catalysis

Effects and Mechanisms of Cu Species in Fe-MOFs on Fenton-Like Catalytic Activity and Stability

DFT Study on the Spin States of Polyaniline–3d Transition-Metal (Sc–Zn) Composites and Their Sensing Application to Detect Chemical Warfare Agents

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