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Defect creation in metal–organic frameworks (MOFs) is a promising approach to optimize the performance of MOFs for a wide range of potential applications. Because of its excellent stability, large surface area, and pore size, MOF-808 (Zr), an essential member of the family of MOFs, has received increasing attention. Consequently, the development of defective MOF-808-Zr has become a hot topic of research. Here, we synthesized and investigated the oxidative catalytic characteristics of nonprecious metal-doped MOF-808-Zr nanoparticles. X-ray diffraction was combined with analytical and spectroscopic techniques to investigate the characteristics of the MOF material (MOF-808-ZrM, where M = Mn, V, Ce, and Ti). Toluene oxidation in the presence of oxygen was used as a model reaction to investigate its catalytic capabilities. Various tests, including in situ DRIFT, confirmed that the incorporation of exotic metals into MOF-808-Zr nanoparticles increased surface oxygen vacancies and surface imperfections, thereby enhancing the catalytic activity. This article proposes a method to improve the performance of toluene-oxidizing catalysts by doping 808-MOFs with transition metals. [ABSTRACT FROM AUTHOR]

Hydrogen (H2) is an environmentally-safe power source and its demands is continuously growing worldwide. The most important approach for its generation is water–gas shift (WGS) reaction through various catalysts. This work investigates feasibility of neural network method named Multilayer Perceptron Neural Network (MLP-NN) to estimate CO conversion in WGS reactions based on different active phase compositions and various supports. The approach considers the intrinsic parameters of the catalyst to estimate reaction performance. This research investigates the most influential variables by conducting a sensitivity analysis study on the predictions of the implemented method. The results of the modeling study revealed that the MLP-NN method can accurately approximate the experimental CO conversion values. The sensitivity analysis study revealed temperature and H2 feed concentration are the most crucial parameters on the reaction performance. The reliability of neural network methods is proved such as the MLP-NN to accurately estimate the CO conversion values in WGS reaction. [ABSTRACT FROM AUTHOR]

Hydrogen (H 2) is known as an environmentally friendly and crucial source of energy and recently demands for this compound has increased globally. One of the main ways of production of this compound is the Water-Gas Shift (WGS) reaction which utilizes various catalysts based on the operating conditions of the process. This work presents the performance of a soft computing method named PSO-RBF to estimate carbon monoxide (CO) conversion in WGS reactions. In addition, decision tree analysis was also performed to extract the associated rules which provides the highest performance for the reaction (higher conversion of CO). Different active phase compositions and support types of catalysts were utilized for development of the PSO-RBF model. The developed model accounts for the intrinsic catalyst parameters for estimation of the reaction performance by including features such as surface area, calcination time and temperature. In addition, sensitivity analysis of the model predictions was also examined to identify useful patterns. The results showed that the PSO-RBF model can accurately predict the actual CO conversion data with overall R2, AARD%, and RMSE values of 0.9977, 3.93, and 0.0159, respectively. It was also observed that the decision tree model can successfully extract the rules and trends from the experimental data. The outcomes of the sensitivity analysis study revealed that the most influential parameters for the process are temperature and H 2 composition in the feed stream. This work shows the capability of soft computing methods such as the PSO-RBF and decision tree approaches for estimating better catalysts and process conditions for this crucial reaction in the environmental field. • A PSO-RBF method for hydrogen production prediction for the Water-Gas Shift reaction was proposed. • Sensitivity analysis was performed to investigate the changes in conversion of CO. • Decision tree analysis was performed to find best catalyst/reaction conditions. • The approach exhibits accurate results for different catalysts and operating conditions during the process. • The temperature and the H 2 content of the feed stream are the most significant parameters. [ABSTRACT FROM AUTHOR]

It has previously been shown that an Ag/CZA catalyst can simultaneously remove NOx and soot from an oxygen-rich exhaust gas at low temperatures, by utilising the N2O generated preferentially during incomplete NOx reduction. Here, we examine the effect of reformulating the catalyst to include potassium, which is a known promoter of soot combustion. On including 2 wt% K, NOx-reduction occurs both in the absence and presence of soot, but the N2O formed does not play a part in the oxidation of soot. At higher K loadings (5, 10 and 15 wt%), NOx reduction is almost completely disabled, and only contributes to the activity of the catalyst containing 5 wt% K when tested in the presence of soot. At a loading of 20 wt% K, the potassium phase segregates, leaving NO and NH3 adsorption sites exposed. In the absence of soot, this catalyst can remove NOx by reduction on the Ag/CZA component and through nitration of the potassium phase. Although the presence of potassium lowers the onset temperature for soot oxidation to within the range of NOx reduction over Ag/CZA, the mobile K species prevents the desirable C+N2O reaction. [ABSTRACT FROM AUTHOR]

Substituted cyclohexenones are well-known building blocks for the synthesis of numerous natural products and bioactive compounds. Despite their widespread use, they are prepared under conditions that are not compatible with the principles of green chemistry. Here the synthesis of substituted cyclohexenones was revisited using a tandem annulation-decarboxylation strategy, in an eco-friendly process without compromising on efficiency. To meet this challenge, environmental catalysts, named ecocatalysts®, which derived from biomass wastes were used. Under microwave activation, ecocatalysis assisted by statistical tools led to excellent yields, as well as remarkable green metrics for the whole synthetic process, which both exceeded those previously reported. The reaction was scaled-up allowing the recycling assessment of the best ecocatalysts®. The reaction was also extended to other substrates. The catalytically active species within the best ecocatalyst® was identified through extensive characterisation by MP-AES, XRPD, SEM, XPS and solid-state NMR, allowing to depict a mechanism confirmed by DFT calculations. [Display omitted] • Ecocatalysts® were easily prepared from plant or food biomass wastes. • Cyclohexenones were prepared one-pot with ecocatalysts® in good to excellent yields. • Green metrics of the process exceeded those previously reported from literature. • The active species within ecocatalysts® were identified by extensive characterisation. • DFT calculations supported the reaction mechanism with identified active species. [ABSTRACT FROM AUTHOR]

Due to the great limitation of glass forming ability, precisely controlling the chemical compositions of metallic glasses (MGs) still dramatically inhibits their widespread applications in wastewater remediation. Here, heterostructured catalysts were exploited by rapid annealing of Fe-based MGs and subsequent ball milling (BM) as advanced alternatives for amorphous counterparts in Fenton-like process. It was found that the surface characteristics tailored by ball milling enable more chemically active sites due to its enlarged specific surface area, surface defects and nanosized amorphous oxide layer that significantly enhance surface-catalyzed reaction in Fenton-like process. On the other hand, high-temperature annealing induced grain growth and electrochemical potential difference induced effect of galvanic cells in multiple crystalline phases (e.g. α-Fe (Si), Fe 2 B and Fe 3 Si) further provide an important contribution to high efficiency of electron transfer in heterostructured catalysts. Since the multiphase heterostructure is easily formed by a high-temperature annealing of MGs/amorphous-crystalline composite alloys, this work aims to provide an advanced alternative of MG catalyst without the elemental limitation of glass forming ability for wastewater remediation. [ABSTRACT FROM AUTHOR]

Bimetallic Cu-Al-BTC MOFs with various Cu/Al ratios were successfully synthesized via a hydrothermal method and applied for CO-SCR. It is found that the catalytic efficiency increased significantly with Cu:Al ratio from 1:1 to 6:1. 6Cu1Al-BTC catalyst exhibits the highest catalytic activity, which achieves nearly 100% NO conversion in the temperature range from 325 °C to 400°C. All bimetallic Cu-Al-BTC catalysts showed higher catalytic activity than pure Cu-BTC and Al-BTC materials. The feasibility of bimetallic Cu-Al-BTC MOFs as a novel deNOx catalyst was evaluated in this work. [ABSTRACT FROM AUTHOR]

Bimetallic Cu-Al-BTC MOFs with various Cu/Al ratios were successfully synthesized via a hydrothermal method and applied for CO-SCR. It is found that the catalytic efficiency increased significantly with Cu:Al ratio from 1:1 to 6:1. 6Cu1Al-BTC catalyst exhibits the highest catalytic activity, which achieves nearly 100% NO conversion in the temperature range from 325 °C to 400 °C. All bimetallic Cu-Al-BTC catalysts showed higher catalytic activity than pure Cu-BTC and Al-BTC materials. The feasibility of bimetallic Cu-Al-BTC MOFs as a novel deNOx catalyst was evaluated in this work. [ABSTRACT FROM AUTHOR]

Iron nanoparticles encapsulated within boron and nitrogen co-doped carbon nanoshell (B/N-C@Fe) were synthesized through a novel and green pyrolysis process using melamine, boric acid, and ferric nitrate as the precursors. The surface morphology, structure, and composition of the B/N-C@Fe materials were thoroughly investigated. The materials were employed as novel catalysts for the activation of potassium monopersulfate triple salt (PMS) for the degradation of levofloxacin (LFX). Linear sweep voltammograms and quenching experiments were used to identify the mechanisms of PMS activation and LFX oxidation by B/N-C@Fe, where SO 4 − as well as HO were proved to be the main radicals for the reaction processes. This study also discussed how the fluvic acid and inorganic anions in the aqueous solutions affected the degradation of LFX and use this method to simulate the degradation in the real wastewater. The synthesized materials showed a high efficiency (85.5% of LFX was degraded), outstanding stability, and excellent reusability (77.7% of LFX was degraded in the 5th run) in the Fenton-like reaction of LFX. In view of these advantages, B/N-C@Fe have great potentials as novel strategic materials for environmental catalysis. Unlabelled Image • Iron nanomaterials were encapsulated in boron/nitrogen co-doped carbon nanoshell. • The B/N-C@Fe4 700 catalysts were synthesized through a green pyrolysis process. • The role of anions in advanced oxidation processes of PPCPs was emphasized. • The B/N-C@Fe4 700 catalysts exhibited an excellent stability and reusability. • The catalysts showed better reusability than N-doped graphene and carbon nanotubes. [ABSTRACT FROM AUTHOR]

Abstract Hydrogen (H 2) is considered a clean valuable energy source and its worldwide demand has increased in recent years. The Water-Gas Shift (WGS) Reaction is one of the major routes for hydrogen production and uses different catalysts depending on the operating process conditions. A catalyst is usually composed of an active phase and a support for its dispersion. There are currently an increasing number of researches on catalytic field focusing on transition metals nanoparticles supported on different compounds. In order to predict optimal catalyst compositions for the WGS reaction, Artificial Neural Networks (ANNs) were used to build a model from the literature catalytic data. A three-layer feedforward neural network was employed with active phase composition and support type as some of the input variables, and Carbon Monoxide (CO) conversion as output variable. The insertion of properties such as surface area, calcination temperature and time allowed predicting the reaction performance based on intrinsic catalyst variables not commonly used in phenomenological kinetic models. Also, unlike previous studies, a detailed sensitivity analysis was carried out to observe useful trends. An important outcome of this work is the proposition of ceria-supported catalysts for the WGS reaction that present larger surface areas, with Ru, Ni or Cu as active phases conducted at moderate temperatures (≈300 °C) and with reasonable space velocities (2000–6000 h−1). In addition, it was possible to predict the most relevant variables for the process: the temperature and the surface area. Thus, the results show the power of ANNs for predicting better catalysts and conditions for this important process in the environmental field. Graphical abstract Image 1 Highlights • An ANN model for catalyst selection for the Water-Gas Shift reaction was developed. • Changes in CO conversion were investigated by performing a sensitivity analysis. • The model can predict better catalysts and operating conditions for the process. • The temperature and the surface area are the most significant variables. [ABSTRACT FROM AUTHOR]

An iterative approach between machine learning (ML) and laboratory experiments was developed to accelerate the design and synthesis of environmental catalysts (ECs) using selective catalytic reduction (SCR) of nitrogen oxides (NO x ) as an example. The main steps in the approach include training a ML model using the relevant data collected from the literature, screening candidate catalysts from the trained model, experimentally synthesizing and characterizing the candidates, updating the ML model by incorporating the new experimental results, and screening promising catalysts again with the updated model. This process is iterated with a goal to obtain an optimized catalyst. Using the iterative approach in this study, a novel SCR NO x catalyst with low cost, high activity, and a wide range of application temperatures was found and successfully synthesized after four iterations. The approach is general enough that it can be readily extended for screening and optimizing the design of other environmental catalysts and has strong implications for the discovery of other environmental materials.

[Display omitted] • E-waste is a severe risk to environmental security and human health. • Gold in E-waste can be reused to save natural resources and the environment. • Porous structures-based materials can selectively adsorb gold ions from E-waste. • Future prospects for novel porous structure-introduced platforms were discussed for gold recycling. In recent years, electronic waste (E-waste) has emerged as a severe risk to worldwide environmental security and human health because it contains many hazardous chemicals of heavy metals, plastics, flame retardants, etc. Notably, gold – one of the noblest metals – consisted of E-waste that can be reused not only to save natural resources but also to curtail the harsh effect on the environment of mineral exploitation and engineering new products in the future. Highly porous material platforms made up of either metal ions or organic ligand-linked clusters have gained attention owing to specific properties including high surface area, tunable pore sizes, and the ability to selectively adsorb gold ions. This review discusses the recent advances and progress of porous structure-based materials for the recent application in recycling gold from E-waste. Moreover, the current difficulties and future advancements of novel and unique porous structure-introduced platforms in recycling gold derived from E-waste are also discussed by exhibiting reusability, high selectivity, stability, and easiness in handling. [ABSTRACT FROM AUTHOR]

CeO2-TiO2/FA catalysts with the selective catalytic reduction (SCR), using industrial solid waste-Fly Ash (FA) as the supporter was prepared by sol-gel and insuccation methods. Ammonia was used as reducing gas to detect the catalytic performance of as-prepared catalyst. Surface structure and catalytic properties of the catalyst were characterized by using BET, XRD, SEM and denitrification tests, respectively. It was confirmed that the loading of CeO2and TiO2on FA supporter led to the increased the specific surface area of catalysts, which resulted in the enhanced catalytic performance toward removing NOx. The NOx conversion over this catalyst can reach 95.3%. [ABSTRACT FROM PUBLISHER]

A series of highly active state-of-the-art catalysts have been synthesized by depositing high loadings of transition metal oxides (MnO 2 , Co 3 O 4 , NiO, CuO and Fe x O y ) onto nitrogen-doped carbon nanotubes (CNTs) for bi-functional catalysis in alkaline media. The metal oxides have been dispersed onto functionalized CNTs by an improved impregnation method. This novel, synthetic approach allows for both the preparation of functionalized nitrogen-doped CNTs as well as the even dispersion of metal oxides onto the walls of the CNTs. The catalysts have been characterized by Brunauer–Emmett–Teller (BET), scanning electron microscopy (SEM), transition electron microscopy (TEM), X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) methods. Catalytic activity has been measured using a Rotating Disc Electrode (RDE) experiment. The resulting catalysts are stable in alkaline media under experimental conditions and have high bi-functional electrocatalytic activity—both for the oxygen reduction reactions (ORR) and oxygen evolution reactions (OER). From this series of catalysts, the most active catalyst for ORR is the 50 wt% MnO 2 /CNT catalyst with a half-wave potential of 0.84 V at the current density of −2.1 mA cm −2 and an onset at 0.98 V versus RHE. The most active for OER is the 50 wt% NiO/CNT catalyst with an onset potential at 1.45 V versus RHE. [ABSTRACT FROM AUTHOR]

Abstract: Catalytic processes developed and commercialized in Japan during 1994–2009 are reviewed and classified into 6 industrial areas: petroleum and energy, bulk chemicals, polymers, fine chemicals, auto exhaust catalysts, and environmental catalysts. They have contributed to overcome a rise in oil price as well as to promote Green Sustainable Chemistry. While these technologies made significant contributions to respond to social issues or commercial demands, continuous efforts for development of these processes greatly promoted the catalytic science and technologies including catalytic materials, concepts, mechanism and surface science of catalysis. [ABSTRACT FROM AUTHOR]

The key role of electron microscopy in understanding and creating advanced catalyst materials and processes in selective alkane oxidation, environmental control, and alternative energy sources is reviewed. In many technological processes, catalysts are increasingly nanoscale heterogeneous materials. With growing regulatory guidelines requiring efficient and environmentally compatible catalytic processes, it is crucial to have a fundamental understanding of the catalyst nanostructure and modes of operation under reaction conditions to design novel catalysts and processes. The review highlights the pioneering development and applications of atomic resolution in situ-environmental transmission electron microscopy (ETEM) for probing dynamic catalysis directly at the atomic level, high-resolution electron microscopy, and analytical spectroscopic methods in the development of alkane catalyzation, environmental protection, and new energy sources. [ABSTRACT FROM AUTHOR]

[Display omitted] • Ceramic nanofibers are active supports for catalysts in soot oxidation. • Bundles of CeO 2 hollow nanofibers were obtained by electrospinning. • CeO 2 microfibers and ZrO 2 nanorods were prepared by hydrothermal synthesis. • ZrO 2 favored higher Co 3 O 4 spreading as compared with CeO 2. • The best Co/shaped-fiber catalysts burned soot at T M = 360 °C. Two series of shaped catalysts were obtained, one of them from CeO 2 and the other one from ZrO 2 , to which cobalt was added. On the one hand, ceria fibers prepared by electrospinning exhibited greater catalytic activity for soot combustion, under loose contact and in the presence of NO, than those made by hydrothermal synthesis. The deposition of low loads of cobalt (2 wt.%) resulted in a positive effect for soot combustion (maximum soot combustion rate, T M = 360 °C), whereas higher loadings (12 wt.%) did not result in a further improvement. On the other hand, cobalt catalysts supported on zirconia nanorods were prepared by hydrothermal synthesis. In comparison with the ceria catalysts, zirconia showed a better catalytic activity when the cobalt load increased from 2 to 12 wt.%, due to a better dispersion of cobalt on ZrO 2. This is in line with STEM and EDX results that indicated the presence of smaller aggregates of cobalt on the zirconia surface. Among the ZrO 2 catalysts studied, Co(12%)-ZrO 2 presented the best catalytic activity (T M = 360 °C), obtained under loose contact conditions and in the presence of NO. The activity of the catalysts was thoroughly correlated with the characterization of the samples by XRD, SEM, EDX, STEM, LRS and XPS. [ABSTRACT FROM AUTHOR]