Experimental and numerical investigations of scale-up effects on the hydrodynamics of slurry bubble columns

Experiments and simulations were conducted for bubble columns with diameter of 0.2 m(180 mm i.d.), 0.5 m(476 mm i.d.) and 0.8 m(760 mm i.d.) at high superficial gas velocities(0.12–0.62 m·s-1) and high solid concentrations(0–30 vol%). Radial profiles of time-averaged gas holdup, axial liquid velocity, and turbulent kinetic energy were measured by using in-house developed conductivity probes and Pavlov tubes. Effects of column diameter, superficial gas velocity, and solid concentration were investigated in a wide range of operating conditions. Experimental results indicated that the average gas holdup remarkably increases with superficial gas velocity, and the radial profiles of investigated flow properties become steeper at high superficial gas velocities. The axial liquid velocities significantly increase with the growth of the column size, whereas the gas holdup was slightly affected. The presence of solid in bubble columns would inhibit the breakage of bubbles, which results in an increase in bubble rise velocity and a decrease in gas holdup, but time-averaged axial liquid velocities remain almost the same as that of the hollow column. Furthermore, a 2-D axisymmetric k–ε model was used to simulate heterogeneous bubbly flow using commercial code FLUENT 6.2. The lateral lift force and the turbulent diffusion force were introduced for the determination of gas holdup profiles and the effects of solid concentration were considered as the variation of average bubble diameter in the model. Results predicted by the CFD simulation showed good agreement with experimental data.

Inducing human induced pluripotent stem cell differentiation through embryoid bodies:A practical and stable approach

Human induced pluripotent stem cells(hiPSCs)are invaluable resources for producing high-quality differentiated cells in unlimited quantities for both basic research and clinical use.They are particularly useful for studying human disease mechanisms in vitro by making it possible to circumvent the ethical issues of human embryonic stem cell research.However,significant limitations exist when using conventional flat culturing methods especially concerning cell expansion,differentiation efficiency,stability maintenance and multicellular 3D structure establishment,differentiation prediction.Embryoid bodies(EBs),the multicellular aggregates spontaneously generated from iPSCs in the suspension system,might help to address these issues.Due to the unique microenvironment and cell communication in EB structure that a 2D culture system cannot achieve,EBs have been widely applied in hiPSC-derived differentiation and show significant advantages especially in scaling up culturing,differentiation efficiency enhancement,ex vivo simulation,and organoid establishment.EBs can potentially also be used in early prediction of iPSC differentiation capability.To improve the stability and feasibility of EB-mediated differentiation and generate high quality EBs,critical factors including iPSC pluripotency maintenance,generation of uniform morphology using micro-pattern 3D culture systems,proper cellular density inoculation,and EB size control are discussed on the basis of both published data and our own laboratory experiences.Collectively,the production of a large quantity of homogeneous EBs with high quality is important for the stability and feasibility of many PSCs related studies.

Segmented tubular synthesis of monodispersed microsized copper oxalate

Monodispersed microsized copper oxalate particles were prepared in a segmented continuous flow tube reactor, and the effect of the main parameters such as organic additive agent, initial copper ions concentration, residence time, and segmented media on the final products were investigated experimentally. The obtained copper oxalate microsized particles were disc-like in the presence of citrate ligand,which was the shape inducer for the precipitated copper oxalate. Thermodynamic equilibrium diagrams of the Cu(Ⅱ)-oxalate-H_2O,Cu(Ⅱ)-oxalate-citrate-H_2O, and Cu(Ⅱ)-oxalate-EDTA-H_2O solution systems were drawn to estimate the possible copper species under the experimental conditions and to explain the formation mechanisms of copper oxalate particles in the segmented fluidic reactor. Both theoretical and experimental results indicated that the presence of chelating reagents such as citrate and EDTA had distinct effect on the evolution of particle shape. Air and kerosene were tested as media for the fluidic flow segmentation, and the latter was verified to better promote the growth of copper oxalate particles. The present study provides an easy method to prepare monodispersed copper oxalate microsized particles in a continuous scaling-up way, which can be utilized to prepare the precursor material for conductive inks.

Biomass estimation and uncertainty analysis based on CBERS-02 CCD camera data and field measurement

The study site is located in Qianyanzhou experimental station and the surrounding area. Based on CBERS-02 satellite data and field measurement, we not only discussed the relationship between NDVI and biomass of two species of coniferous plantations, namely, Pinus massoniana Lamb and Pinus elliottii Engelm, but also introduced the biomass models based on NDVI. The comparison between measured biomass in Qianyanzhou and biomass derived from CBERS-02 CCD data showed that it is feasible to estimate biomass based on NDVI. But its limitations cannot be ignored. This kind of model depends on the dominant vegetation species. There are some effect factors in estimating biomass based on NDVI. This paper analyzes these factors based on fine-resolution CBERS-02 CCD data and some conclusions are drawn: In Qianyanzhou, the area with good vegetation coverage, the nonlinearity of NDVI has little influence on scaling-up of NDVI. As a result of surface heterogeneity, scaling-up can cause NDVI within each pixel to change. Because scaling-up can cause pixel attribute to change, the applicability of biomass model is one of the sources of error in estimating biomass.

Electrochemistry-stimulated environmental bioremediation:Development of applicable modular electrode and system scale-up

Bioelectrochemical systems(BESs)have been studied extensively during the past decades owing primarily to their versatility and potential in addressing the water-energy-resource nexus.In stark contrast to the significant advancements that have been made in developing innovative processes for pollution control and bioresource/bioenergy recovery,minimal progress has been achieved in demonstrating the feasibility of BESs in scaled-up applications.This lack of scaled-up demonstration could be ascribed to the absence of suitable electrode modules(EMs)engineered for large-scale application.In this study,we report a scalable composite-engineered EM(total volume of 1 m^(3)),fabricated using graphite-coated stainless steel and carbon felt,that allows integrating BESs into mainstream wastewater treatment technologies.The cost-effectiveness and easy scalability of this EM provides a viable and clear path to facilitate the transition between the success of the lab studies and applications of BESs to solve multiple pressing environmental issues at full-scale.

GeoAI for detection of solar photovoltaic installations in the Netherlands

National mapping agencies are responsible for creating and maintaining country wide geospatial datasets that are highly accurate and homogenous.The Netherlands’Cadastre,Land Registry and Mapping Agency,in short,the Kadaster,has created a database of information related to solar installations,using GeoAI.Deep Learning techniques were employed to detect small and medium-scale solar installations on buildings from very highresolution aerial images for the whole of the Netherlands.The impact of data pre-processing and postprocessing are addressed and evaluated.The process was automatized to deal with enormous data and the method was scaled-up nation-wide with the help of cloud solutions.In order to make this information visible,consistent and usable,we built-upon the existing TernausNet;a convolution neural network(CNN)architecture.Model metrics were evaluated after post-processing.The algorithm when used in combination with automated or custom post-processing improves the results.The precision and recall rates of the model for 3 different regions were evaluated and are on average about 0.93 and 0.92 respectively after implementation of post-processing.Use of custom post-processing improves the results by removing the false positives by at least 50%.The final results were compared with the existing national PV register.Overall,the results are not only useful for policy makers to assist them to take the necessary steps in achieving the energy transition goals but also serves as a register for infrastructure planning.