The
efficient identification of bacteria is of considerable significance
in clinical diagnosis. Herein, a novel colorimetric sensor array was
developed for the detection and identification of bacteria based on
the specific affinity and electrostatic interaction between Wulff-type
4-mercaptophenylboronic acid (MPBA)-mercaptoethylamine (MA) cofunctionalized
AgNPs (MPBA-MA@AgNPs) and bacteria at various pH. In the neutral and
alkaline conditions, AgNPs tended to be dispersed due to the specific
affinity between cis-diol residues contained in carbohydrate-rich
compositions on the bacterial cell surface and MPBA. Bacterial cells
have different carbohydrate compositions on their surface. The differential
binding affinity of MPBA on the surface of AgNPs to cis-diol residues of various carbohydrates resulted in a different color
change of AgNPs, which could be tuned by pH. On the contrary, AgNPs
tended to be aggregated due to the electrostatic interaction between
positively charged MA and negatively charged bacteria under acidic
conditions. Therefore, using various pH buffer solutions as the sensing
elements and MPBA-MA@AgNPs as the indicator, bacteria could be differentiated
from each other by their own color response patterns. Moreover, the
complex bacteria mixtures could be well discriminated. The method
is simple, efficient, and visual and has a potential application in
pathogen diagnosis.
A three-dimensional (3-D) two-phase Eulerian-Eulerian-based computational fluid dynamics (CFD) simulation method coupled with a porous media model was developed in this study to simulate the air-water two-phase flow in an industrial-scale randomly packed air cooling tower (RPACT). The authors discussed the effects of gas kinetic energy factor, liquid load, packing materials, and packed bed height on the hydrodynamic performances of the gas-liquid counter-current flow in the proposed RPACT. The simulation results show that the pressure drop increases with the gas or liquid load increases. Liquid load influences the pressure drop, liquid holdup, and wall film flow rate sensitively.A smaller liquid load, a middle range of gas kinetic energy factor, a relatively greater porous resistance coefficient of packing material, and a higher packed bed height can achieve a more uniform liquid flow distribution in an RPACT. The optimum operating conditions for the present RPACT are determined as gas kinetic energy factor is from 1.76 to 2.11 [(m/s) (kg/m 3 ) 0.5 ], liquid load is in the range of 32.40-67.73 m 3 /h, and the plastic Cascade ring (filled in the second packing layer) with a height of 10 m. The presented CFD models are useful for engineers to design and optimize the structure and operation conditions of industrial-scale RPACTs.
Summary
For grid‐scale intermittent electricity storage, liquid air energy storage (LAES) is considered to be one of the most promising technologies for storing renewable energy. In this study, a steady‐state process model was developed for an LAES, by combining a Linde liquefaction process and an open Rankine power cycle. To investigate the system performance and achieve global optimization, a single‐factor analysis approach and multifactor genetic algorithm (GA) optimization model were built using MATLAB software. The effects of the charging pressure, storage pressure, discharging pressure, and isentropic efficiency of the compressor/turbine on the LAES performance parameters, such as the inlet temperature of the Joule–Thomson valve, round‐trip efficiency (RTE), liquefaction ratio (LR), and power consumptions in the compressor, cryo‐pump, and turbine, were investigated. Subsequently, the optimal conditions were obtained using the GA optimization method to achieve the optimal performance of the LAES. The results showed that the charging pressure, discharging pressure, and isentropic efficiencies of the compressor and turbine had significant effects on the RTE; an increase in the discharging pressure resulted in an improved expansion power output; the GA optimization could achieve RTE, LR, the system energy storage and recovery exergy efficiencies of 53.33%, 86.96%, 81.00%, and 78.16%; the power consumption in the compressor of GA optimization was 10.02% maximum saving. The proposed optimization method can be used to further explore the global optimization of cryogenic energy storage systems, such as different‐layout LAES systems and different cryogenic liquefaction media energy storage systems.
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