3D Printed Reactors and Kessil Lamp Holders for Flow Photochemistry: Design and System Standardization

A low-cost 3D printed standardized flow-photochemistry setup has been designed and developed for use with a pressure-driven flow system using photochemistry lamps available in most laboratories. In this research, photochemical reactors were 3D printed from polypropylene which facilitated rapid optimization of both reactor geometry and experimental setup of the lamp housing system. To exemplify the rapidity of this approach to optimization, a Kessil LED lamp was used in the bromination of a range of toluenes in the 3D printed reactors in good yields with residence times as low as 27 seconds. The reaction compared favorably with the batch photochemical procedure and was able to be scaled up to a productivity of 75 mmol h-1.

NEXTorch: A Design and Bayesian Optimization Toolkit for Chemical Sciences and Engineering

<div> <div> <div> <p>Automation and optimization of chemical systems require well-inform decisions on what experiments to run to reduce time, materials, and/or computations. Data-driven active learning algorithms have emerged as valuable tools to solve such tasks. Bayesian optimization, a sequential global optimization approach, is a popular active-learning framework. Past studies have demonstrated its efficiency in solving chemistry and engineering problems. We introduce NEXTorch, a library in Python/PyTorch, to facilitate laboratory or computational design using Bayesian optimization. NEXTorch offers fast predictive modeling, flexible optimization loops, visualization capabilities, easy interfacing with legacy software, and multiple types of parameters and data type conversions. It provides GPU acceleration, parallelization, and state-of-the-art Bayesian Optimization algorithms and supports both automated and human-in-the-loop optimization. The comprehensive online documentation introduces Bayesian optimization theory and several examples from catalyst synthesis, reaction condition optimization, parameter estimation, and reactor geometry optimization. NEXTorch is open-source and available on GitHub. </p> </div> </div> </div>

NEXTorch: A Design and Bayesian Optimization Toolkit for Chemical Sciences and Engineering

<div> <div> <div> <p>Automation and optimization of chemical systems require well-inform decisions on what experiments to run to reduce time, materials, and/or computations. Data-driven active learning algorithms have emerged as valuable tools to solve such tasks. Bayesian optimization, a sequential global optimization approach, is a popular active-learning framework. Past studies have demonstrated its efficiency in solving chemistry and engineering problems. We introduce NEXTorch, a library in Python/PyTorch, to facilitate laboratory or computational design using Bayesian optimization. NEXTorch offers fast predictive modeling, flexible optimization loops, visualization capabilities, easy interfacing with legacy software, and multiple types of parameters and data type conversions. It provides GPU acceleration, parallelization, and state-of-the-art Bayesian Optimization algorithms and supports both automated and human-in-the-loop optimization. The comprehensive online documentation introduces Bayesian optimization theory and several examples from catalyst synthesis, reaction condition optimization, parameter estimation, and reactor geometry optimization. NEXTorch is open-source and available on GitHub. </p> </div> </div> </div>

Particle Image Velocimetry Method for Prediction Hydrodynamic Conditions during Leaching Process on the Basis of Sn–NaOH System

In leaching processes controlled by diffusion and convectional transport of mass, the hydrodynamic structure formed in the reactor’s working volume is an additional factor affecting the process. This research work presents results related to hydrodynamic structures developing in batch reactors, different in shape, recorded by means of the particle image velocimetry (PIV) method. The movement of the distilled water and leaching solution was analyzed during investigations. Next, the system hydrodynamics and the process of tin leaching were analyzed. Finally, the leaching is affected by the reactor geometry and the hydrodynamic structure developed in its working volume, especially when a convectional or diffusion mass transport decides the process efficiency.

Simultaneous Synthesis and Nitrogen Doping of Free-Standing Graphene Applying Microwave Plasma

An experimental and theoretical investigation on microwave plasma-based synthesis of free-standing N-graphene, i.e., nitrogen-doped graphene, was further extended using ethanol and nitrogen gas as precursors. The in situ assembly of N-graphene is a single-step method, based on the introduction of N-containing precursor together with carbon precursor in the reactive microwave plasma environment at atmospheric pressure conditions. A previously developed theoretical model was updated to account for the new reactor geometry and the nitrogen precursor employed. The theoretical predictions of the model are in good agreement with all experimental data and assist in deeper understanding of the complicated physical and chemical process in microwave plasma. Optical Emission Spectroscopy was used to detect the emission of plasma-generated ‘‘building units’’ and to determine the gas temperature. The outlet gas was analyzed by Fourier-Transform Infrared Spectroscopy to detect the generated gaseous by-products. The synthesized N-graphene was characterized by Scanning Electron Microscopy, Raman, and X-ray photoelectron spectroscopies.

The Effect of Hydraulic Conditions in Barbotage Reactors on Aeration Efficiency

Barbotage reactors such as airlift reactors (ALR) and bubble column reactors (BCR), due to their two-phase flow systems, were investigated in many research papers. In their basic design variants, they are typically used to lift, mix, and aerate liquids, while, when equipped with additional elements in hybrid variants, their individual properties, i.e., lifting, mixing, and aeration of liquids, can significantly change with the same reactor geometry. The object of this study was to develop a hybrid barbotage reactor in various structural design variants. The structure consisted of a barbotage column of 50 mm in diameter, used to transport a water–air mixture outside the reactor (so-called external loop). The installation was additionally equipped with a nozzle in order to improve mixture aeration and circulation efficiency. The nozzle was mounted at various heights of the column pump segment. Additionally, the reactor was equipped with s moving bed in two variants (20% and 40% reactor capacity) in order to determine its effect on the mixture aeration and circulation conditions. Based on the measurement results, aeration curves were prepared for various structural design and column packing variants of the reactor. Properties of the two-phase mixture were determined for both parts—ALR and BCR. Technological and energy parameters of the aeration process were calculated, and the results obtained for the individual structural design variants were compared. It was found that, for the most advantageous design, in terms of aeration efficiency, the aeration nozzle should be placed in the mid-length of the pump segment of the barbotage column, irrespective of the hybrid reactor packing rate with the moving bed. The reactor packing with the moving bed resulted in a decreased mean water velocity in the reactor. For most analyzed structural design variants, the respective packing with the moving bed had no significant effect on aeration efficiency. Only for one structural design variant did the lack of packing significantly improve oxygen levels by as much as approximately 41%.