Why Does Not Nanotechnology Go Green? Bioprocess Simulation and Economics for Bacterial-Origin Magnetite Nanoparticles

Nanotechnological developments, including fabrication and use of magnetic nanomaterials, are growing at a fast pace. Magnetic nanoparticles are exciting tools for use in healthcare, biological sensors, and environmental remediation. Due to better control over final-product characteristics and cleaner production, biogenic nanomagnets are preferable over synthetic ones for technological use. In this sense, the technical requirements and economic factors for setting up industrial production of magnetotactic bacteria (MTB)-derived nanomagnets were studied in the present work. Magnetite fabrication costs in a single-stage fed-batch and a semicontinuous process were US$ 10,372 and US$ 11,169 per kilogram, respectively. Depending on the variations of the production process, the minimum selling price for biogenic nanomagnets ranged between US$ 21 and US$ 120 per gram. Because these prices are consistently below commercial values for synthetic nanoparticles, we suggest that microbial production is competitive and constitutes an attractive alternative for a greener manufacturing of magnetic nanoparticles nanotools with versatile applicability.

Semi-Continuous Adsorption Processes with Multi-Walled Carbon Nanotubes for the Treatment of Water Contaminated by an Organic Textile Dye

Adsorbent columns, containing different amounts of multi-walled carbon nanotubes (MWCNTs), in a semicontinuous process were studied. The optimal conditions for the discoloration of water contaminated by an azoic organic textile dye were investigated. In particular, as representative of contaminated water, a highly concentrated solution of Reactive Black 5 (RB5) equal to 37 mg/L was utilized. A predetermined volume of dye solution, equal to 100 mL, was subjected to repeated cycles of adsorption until the eluted solution became colorless. This adsorption operation was carried out for different types of columns. Adsorbent performances as a function of characteristics of each column were investigated. For each column, the optimum quantity of MWCNTs, maximum volume of treatable solution, carbon usage rate (CUR), empty bed contact time (EBCT), and adsorption capacity were determined. The permeate was characterized by UV-VIS analysis and TOC analysis, while adsorbent material (MWCNTs) was characterized by thermogravimetric TG-DTA analysis. The column containing 2.5 g of carbon nanotubes was revealed to be the best one for the total amount of Reactive Black 5 adsorbed, i.e., 55 mg/g(MWCNTs) The research has shown the high adsorption efficiency of carbon nanotubes toward RB5 dye, highlighting the degradation of the dye molecule and the stratification, inside the columns, of the adsorbed compound.

Manufacture 4.0 with LabVIEW and Arduino Mega for distributed cooling control of the DeMag 250 Ton machine injection mold

Nowdays the injection plastics processes at insdustrial level have had a great development in the bajio region with the arrival of new enterprise suppliers of the automotive industry that work particuary de injection molding. The plastics injection molding is a semicontinuous process that consists of inject a polymer in the molten state into a mold closed under pressure, throught a small hole called gate, in the mole the material is solidifies, the piece or final part is obtained when the mold is opened and remove the piece molding from the cavity [1]. To monitor and control the temperature changes in the plastics injection cicles permite reduce errors and costs in the process. In this project we propose to apply manufacture 4.0 using the Arduino Mega microcontroller and LabVIEW to monitor part of the process of the injection molding of the DeMag 250 Ton Machine, specifically the coolding system adapting to control the injection molde temperature. The preliminare results show that is apropiate to use the LabVIEW an Arduino Mega combination to generation of innovation project applied to the plastic industry.

Study on Optimization of Coal Truck Flow in Open-Pit Mine

A semicontinuous process system consisting of a single-bucket excavator, truck, crushing station, and belt conveyor is the main coal mining process system of a large-scale hard coal open-pit mine. Through analyzing the coal mining production process, the key issues of coal mining truck flow optimization are obtained. Statistical method of using triangular fuzzy numbers analyzes the key time parameters of coal mining truck flow. Taking one shift, the minimum expected value of number of trucks, as the objective function, the fuzzy expectation of the coal mining semicontinuous process system is established with the constraints of the truck flow continuity at the loading and unloading point, the production capacity of the electric shovel, the production capacity of the crushing station, coal quality, and coal mining production tasks. The truck flow planning model is solved using particle swarm intelligence algorithm. The simulation results show that the result of truck flow planning can effectively reduce truck number, truck dispatching number, transportation costs, and truck queuing. The fuzzy expected truck flow planning model established by the study is suitable for solving the problem of optimizing and matching the production capacity in the process which links electric shovel, truck, and crushing station. It can effectively improve the production efficiency of electric shovel mining, truck transportation, and crushing station.