CFD modelling of a hollow fibre system for CO2 capture by aqueous amine solutions of MEA, DEA and MDEA

YesA mass transfer model was developed for CO2 capture from a binary gas mixture of N2/CO2 in hollow fibre membrane contactors under laminar flow conditions. The axial and radial diffusions through membrane and convection in tube and shell sides with chemical reaction were investigated. COMSOL software was used to numerically solve a system of non-linear equations with boundary conditions by use of the finite element method. Three different amine solutions of monoethanolamine (MEA), diethanolamine (DEA) and n-methyldiethanolamine (MDEA) were chosen as absorbent in lumen to consider the mass transfer rate of CO2 and compare their removal efficiency. The modelling results were compared with experimental data available in the literature and a good agreement was observed. The CFD results revealed that MEA had the best performance for CO2 removal as compared to DEA and MDEA under various operating conditions due to the different CO2 loading factor of absorbents. Furthermore, efficiency of CO2 removal was highly dependent on the absorbent concentration and its flow rate, increasing of the gas flow rate caused a reduction in gas residence time in the shell and consequently declined CO2 mass transfer. The modelling results showed the influence of the absorbent concentration on the CO2 mass transfer has improved due to availability of absorbent reactants at the gas-liquid interface

Investigation of the Growth of Particles Produced in a Laval Nozzle

YesThis study focuses on numerical modeling of condensation of water vapor in a Laval nozzle, using the liquid drop nucleation theory. Influence of nozzle geometry, pressure, and temperature on the average drop size is reported. A computer program written in MATLAB was used used to calculate the nucleation and condensation of water vapor in the nozzle. The simulation results are validated with the available experimental data in the literature for steam condensation. The model reveals that the average drop size is reduced by increasing the divergent angle of the nozzle. The results also confirm that increasing the inlet pressure has a direct effect on the average drop size while temperature rise has an inverse effect on the drop size

Investigation of Effect of Aluminium Oxide Nanoparticles on the Thermal Properties of Water-Based Fluids in a Double Tube Heat Exchanger

yesThe thermal behavior of aluminium oxide-water nanofluid in a double pipe carbon steel heat exchanger was investigated in the present study. The overall heat transfer coefficient, Nusselt, and heat transfer coefficient of nanofluid were compared with the base fluid. The volume fraction of the nanoparticles was 1%. By adding nanoparticles to the fluid, the thermal properties of the base fluid improved significantly. The hot and cold fluid flow was considered counter-current, and the nanofluid was pumped into the inner tube and once into the outer tube, and the flow rate of each fluid was 0.05 kg/s. The convective heat transfer and the overall heat transfer coefficient enhanced 94% and 253% for the hot fluid flow in the outer tube and 308 % and 144% for the hot fluid flow in the inner tube, respectively. The pressure drop calculations also showed that the pressure drop would not change significantly when using nanofluid

Evaluation of the metformin effects on Anti-Müllerian Hormone in women with polycystic ovarian syndrome: A double-blind randomized clinical trial

This is a Letter to the Editor and does not have an abstract

One‐Shot Active Learning for Globally Optimal Battery Electrolyte Conductivity**

Non-aqueous aprotic battery electrolytes need to perform well over a wide range of temperatures in practical applications. Herein we present a one-shot active learning study to find all conductivity optima, confidence bounds, and relating formulation trends in the temperature range from −30 °C to 60 °C. This optimization is enabled by a high-throughput formulation and characterization setup guided by one-shot active learning utilizing robust and heavily regularized polynomial regression. Whilst there is an initially good agreement for intermediate and low temperatures, there is a need for the active learning step to improve the model for high temperatures. Optimized electrolyte formulations likely correspond to the highest physically possible conductivities within this formulation system when compared to literature data. A thorough error propagation analysis yields a fidelity assessment of conductivity measurements and electrolyte formulation

The forgotten girls: the state of evidence for health interventions for pregnant adolescents and their newborns in low-income and middle-income countries

Every year, an estimated 21 million girls aged 15–19 years become pregnant in low-income and middle-income countries (LMICs). Policy responses have focused on reducing the adolescent birth rate whereas efforts to support pregnant adolescents have developed more slowly. We did a systematic review of interventions addressing any health-related outcome for pregnant adolescents and their newborn babies in LMICs and mapped its results to a framework describing high-quality health systems for pregnant adolescents. Although we identified some promising interventions, such as micronutrient supplementation, conditional cash transfers, and well facilitated group care, most studies were at high risk of bias and there were substantial gaps in evidence. These included major gaps in delivery, abortion, and postnatal care, and mental health, violence, and substance misuse-related outcomes. We recommend that the fields of adolescent, maternal, and sexual and reproductive health collaborate to develop more adolescent-inclusive maternal health care and research, and specific interventions for pregnant adolescents. We outline steps to develop high-quality, evidence-based care for the millions of pregnant adolescents and their newborns who currently do not receive this

Analysis of Physiochemical Parameters to Evaluate the Drinking Water Quality in the State of Perak, Malaysia

YesThe drinking water quality was investigated in suspected parts of Perak state, Malaysia, to ensure the continuous supply of clean and safe drinking water for the public health protection. In this regard, a detailed physical and chemical analysis of drinking water samples was carried out in different residential and commercial areas of the state. A number of parameters such as pH, turbidity, conductivity, total suspended solids (TSS), total dissolved solids (TDS), and heavy metals such as Cu, Zn, Mg, Fe, Cd, Pb, Cr, As, Hg, and Sn were analysed for each water sample collected during winter and summer periods. The obtained values of each parameter were compared with the standard values set by the World Health Organization (WHO) and local standards such as National Drinking Water Quality Standard (NDWQS). The values of each parameter were found to be within the safe limits set by the WHO and NDWQS. Overall, the water from all the locations was found to be safe as drinking water. However, it is also important to investigate other potential water contaminations such as chemicals and microbial and radiological materials for a longer period of time, including human body fluids, in order to assess the overall water quality of Perak state

Enabling Modular Autonomous Feedback-Loops in Materials Science through Hierarchical Experimental Laboratory Automation and Orchestration

Materials acceleration platforms (MAPs) operate on the paradigm of integrating combinatorial synthesis, high-throughput characterization, automatic analysis, and machine learning. Within a MAP, one or multiple autonomous feedback loops may aim to optimize materials for certain functional properties or to generate new insights. The scope of a given experiment campaign is defined by the range of experiment and analysis actions that are integrated into the experiment framework. Herein, the authors present a method for integrating many actions within a hierarchical experimental laboratory automation and orchestration (HELAO) framework. They demonstrate the capability of orchestrating distributed research instruments that can incorporate data from experiments, simulations, and databases. HELAO interfaces laboratory hardware and software distributed across several computers and operating systems for executing experiments, data analysis, provenance tracking, and autonomous planning. Parallelization is an effective approach for accelerating knowledge generation provided that multiple instruments can be effectively coordinated, which the authors demonstrate with parallel electrochemistry experiments orchestrated by HELAO. Efficient implementation of autonomous research strategies requires device sharing, asynchronous multithreading, and full integration of data management in experimental orchestration, which to the best of the authors’ knowledge, is demonstrated for the first time herein