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Catalysis

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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...

Tackling a textbook example of multistep enzyme catalysis with deep learning-driven design.

Molecular cell
Enzyme design has struggled to emulate the complexity and catalytic proficiency of natural enzymes. Lauko et al. show that with the help of deep learning, the design of serine hydrolases that rival nature's ingenuity is possible.

DLTKcat: deep learning-based prediction of temperature-dependent enzyme turnover rates.

Briefings in bioinformatics
The enzyme turnover rate, ${k}_{cat}$, quantifies enzyme kinetics by indicating the maximum efficiency of enzyme catalysis. Despite its importance, ${k}_{cat}$ values remain scarce in databases for most organisms, primarily because of the cost of exp...

Data-driven enzyme engineering to identify function-enhancing enzymes.

Protein engineering, design & selection : PEDS
Identifying function-enhancing enzyme variants is a 'holy grail' challenge in protein science because it will allow researchers to expand the biocatalytic toolbox for late-stage functionalization of drug-like molecules, environmental degradation of p...

Leveraging Machine Learning for Enantioselective Catalysis: From Dream to Reality.

Chimia
Catalyst optimization for enantioselective transformations has traditionally relied on empirical evaluation of catalyst properties. Although this approach has been successful in the past it is intrinsically limited and inefficient. To address this pr...

An 88-milligram insect-scale autonomous crawling robot driven by a catalytic artificial muscle.

Science robotics
The creation of autonomous subgram microrobots capable of complex behaviors remains a grand challenge in robotics largely due to the lack of microactuators with high work densities and capable of using power sources with specific energies comparable ...

Kinetic study of dye removal using TiO supported on polyethylene terephthalate by advanced oxidation processes through neural networks.

Water science and technology : a journal of the International Association on Water Pollution Research
This work investigated the efficiency of polyethylene terephthalate (PET) as support material for TiO films in the photocatalytic degradation of red Bordeaux and yellow tartrazine dyes. The optimum operating conditions were determined by a factorial ...

An integrated design and fabrication strategy for entirely soft, autonomous robots.

Nature
Soft robots possess many attributes that are difficult, if not impossible, to achieve with conventional robots composed of rigid materials. Yet, despite recent advances, soft robots must still be tethered to hard robotic control systems and power sou...

Application of artificial neural networks for prediction of photocatalytic reactor.

Water environment research : a research publication of the Water Environment Federation
In this paper, forecasting of kinetic constant and efficiency of photocatalytic process of TiO2 nano powder immobilized on light expanded clay aggregates (LECA) was investigated. Synthetic phenolic wastewater, which is toxic and not easily biodegrada...