AIMC Topic: Catalysis

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Bifunctional composite from spent "Cyprus coffee" for tetracycline removal and phenol degradation: Solar-Fenton process and artificial neural network.

International journal of biological macromolecules
Removals of tetracycline and photocatalytic degradation of phenol by Fe3O4/coffee residue (MCC) were investigated. Brunauer-Emmett-Teller (BET), vibrating sample magnetometer (VSM) and Boehm titration were employed to characterize MCC. Artificial neu...

Degradation and mineralization of phenol compounds with goethite catalyst and mineralization prediction using artificial intelligence.

PloS one
The efficiency of phenol degradation via Fenton reaction using mixture of heterogeneous goethite catalyst with homogeneous ferrous ion was analyzed as a function of three independent variables, initial concentration of phenol (60 to 100 mg /L), weigh...

Expert system for predicting reaction conditions: the Michael reaction case.

Journal of chemical information and modeling
A generic chemical transformation may often be achieved under various synthetic conditions. However, for any specific reagents, only one or a few among the reported synthetic protocols may be successful. For example, Michael β-addition reactions may ...

Ultrasound assisted biodiesel production from sesame (Sesamum indicum L.) oil using barium hydroxide as a heterogeneous catalyst: Comparative assessment of prediction abilities between response surface methodology (RSM) and artificial neural network (ANN).

Ultrasonics sonochemistry
The present study estimates the prediction capability of response surface methodology (RSM) and artificial neural network (ANN) models for biodiesel synthesis from sesame (Sesamum indicum L.) oil under ultrasonication (20 kHz and 1.2 kW) using barium...

Artificial intelligence-driven revolution in nanozyme design: from serendipity to rational engineering.

Materials horizons
Nanozymes are a class of nanomaterials that possess catalytic functions similar to those of natural enzymes. Due to their tunable catalytic activity and unique nanoscale properties, these materials exhibit significant potential for applications in bi...

Engineering catalytically promiscuous enzymes to serve new functions.

Biotechnology advances
Catalytic promiscuity in enzymes refers to their ability to catalyze multiple chemically distinct reactions in addition to their native activity. The increasing discovery of additional enzymes exhibiting catalytic promiscuity has underscored the sign...

Applied Machine Learning for Prediction of Energy-Efficient CO Desorption on Solid Acid Catalysts.

Environmental science & technology
The development of solid acid catalysts (SACs) for energy-efficient CO desorption and amine regeneration is critical to carbon capture commercialization. To avoid the time-consuming and ineffective screening process, a predictive model correlating th...

Machine Learning-Assisted Discovery of Bimetallic Oxides for Highly Efficient Catalytic Ozonation.

Environmental science & technology
Catalytic ozonation stands out as an effective process in the advanced treatment of industrial wastewater, where heterogeneous catalysts play a pivotal role. Here, by screening 1603 bimetallic oxides via machine learning (ML), a pioneering ZnCuO was ...

Machine Learning-Driven Prediction of Electrochemical Promotion in the Reverse Water Gas Shift Reaction.

Journal of chemical information and modeling
Electrochemical promotion of catalysis (EPOC) provides an effective and versatile strategy to enhance catalytic activity, selectivity, and stability in the reverse water-gas shift (RWGS) reaction, facilitating efficient CO hydrogenation to syngas und...

Bioinspired rational design of nanozymes.

Materials horizons
Nanozymes, an emerging class of artificial enzymes, have attracted increasing attention for their potential in environmental monitoring, industrial catalysis, food safety, and biomedicine. To date, more than 1500 nanomaterials have been identified wi...