Low-grade waste heat recovery for wastewater treatment using clathrate hydrate based technology

Effectively recycling low-grade waste heat is crucial for advancing decarbonization and achieving net-zero emissions, yet current methodologies are limited by inefficiencies in extracting energy from sources with low exergy. This study introduces an innovative approach leveraging hydrate formation and dissociation to utilize low-grade waste heat in purifying wastewater. By directly heating (low-grade waste heat) liquid R134a, our method induces bubble formation, thereby enhancing hydrate nucleation and growth. Our system demonstrates exceptional energy efficiencies, reaching up to 23.5%, and exhibits a high removal efficiency for wastewater with high concentrations of organic and heavy metal contaminants, including methylene blue (86.4%), Cr3+ (98.0%), Ni2+ (98.3%), Zn2+ (98.0%), and Cu2+ (97.1%). This approach not only offers a sustainable pathway for waste heat utilization but also addresses critical challenges in wastewater treatment. This technology demonstrates substantial potential in both low-grade waste heat recovery and wastewater treatment

Monitoring gas hydrate formation with magnetic resonance imaging in a metallic core holder

Methane hydrate deposits world-wide are promising sources of natural gas. Magnetic Resonance Imaging (MRI) has proven useful in previous studies of hydrate formation. In the present work, methane hydrate formation in a water saturated sand pack was investigated employing an MRI-compatible metallic core holder at low magnetic field with a suite of advanced MRI methods developed at the UNB MRI Centre. The new MRI methods are intended to permit observation and quantification of residual fluids in the pore space as hydrate forms. Hydrate formation occurred in the water-saturated sand at 1500 psi and 4 °C. The core holder has a maximum working pressure of 4000 psi between -28 and 80 °C. The heat-exchange jacket enclosing the core holder enabled very precise control of the sample temperature. A pure phase encode MRI technique, SPRITE, and a bulk T1-T2 MR method provided high quality measurements of pore fluid saturation. Rapid 1D SPRITE MRI measurements time resolved the disappearance of pore water and hence the growth of hydrate in the sand pack. 3D π-EPI images confirmed that the residual water was inhomogeneously distributed along the sand pack. Bulk T1-T2 measurements discriminated residual water from the pore gas during the hydrate formation. A recently published local T1-T2 method helped discriminate bulk gas from the residual fluids in the sample. Hydrate formation commenced within two hours of gas supply. Hydrate formed throughout the sand pack, but maximum hydrate was observed at the interface between the gas pressure head and the sand pack. This irregular pattern of hydrate formation became more uniform over 24 hours. The rate of hydrate formation was greatest in the first two hours of reaction. An SE-SPI T2 map showed the T2 distribution changed considerably in space and time as hydrate formation continued. Changes in the T2 distribution are interpreted as pore level changes in residual water content and environment

Innovative and Responsible Governance of Nanotechnology for Societal Development

The one-pot synthesis of iron-doped carbon quantum dots (Fe-CQDs) for use as both magnetic resonance (MR) and fluorescent (dual-mode) imaging nanoprobes is described. Comprehensive characterizations of the material confirmed the successful doping of the CQDs with Fe(II) ions. The imaging probe has a longitudinal relaxivity of 3.92 mM−1∙s−1 and a low r2/r1 ratio of 1.27, both of which are critical for T1-weighted contrast agents. The maximum emission of Fe-CQDs locates at 450 nm under 375 nm excitation, which also can be applied to fluorescence imaging. Biotoxicity assessment showed good biocompatibility of the Fe-CQDs. The in-vitro experiments with A549 cells indicated that the Fe-CQDs are viable candidates as dual-mode (MR/fluorescence) imaging nanoprobes. For in-vivo experiments, they exhibit high contrast efficiency, thereby improving the positive contrast in T1-weighted MR images. In-vivo time-dependent MRI of major organs showed that the Fe-CQDs undergo fast glomerular filtration and can evade immuno-absorption due to their ultra-small size and excellent biocompatibility. [Figure not available: see fulltext.]

Draft genome sequence of the mulberry tree Morus notabilis

Human utilization of the mulberry–silkworm interaction started at least 5,000 years ago and greatly influenced world history through the Silk Road. Complementing the silkworm genome sequence, here we describe the genome of a mulberry species Morus notabilis. In the 330-Mb genome assembly, we identify 128 Mb of repetitive sequences and 29,338 genes, 60.8% of which are supported by transcriptome sequencing. Mulberry gene sequences appear to evolve ~3 times faster than other Rosales, perhaps facilitating the species’ spread worldwide. The mulberry tree is among a few eudicots but several Rosales that have not preserved genome duplications in more than 100 million years; however, a neopolyploid series found in the mulberry tree and several others suggest that new duplications may confer benefits. Five predicted mulberry miRNAs are found in the haemolymph and silk glands of the silkworm, suggesting interactions at molecular levels in the plant–herbivore relationship. The identification and analyses of mulberry genes involved in diversifying selection, resistance and protease inhibitor expressed in the laticifers will accelerate the improvement of mulberry plants

Robust CFAR Detection for Multiple Targets in K-Distributed Sea Clutter Based on Machine Learning

For K-distributed sea clutter, a constant false alarm rate (CFAR) is crucial as a desired property for automatic target detection in an unknown and non-stationary background. In multiple-target scenarios, the target masking effect reduces the detection performance of CFAR detectors evidently. A machine learning based processor, associating the artificial neural network (ANN) and a clustering algorithm of density-based spatial clustering of applications with noise (DBSCAN), namely, DBSCAN-CFAR, is proposed herein to address this issue. ANN is trained with a symmetrical structure to estimate the shape parameter of background clutter, whereas DBSCAN is devoted to excluding interference targets and sea spikes as outliers in the leading and lagging windows that are symmetrical about the cell under test (CUT). Simulation results verified that the ANN-based method provides the optimal parameter estimation results in the range of 0.1 to 30, which facilitates the control of actual false alarm probability. The effectiveness and robustness of DBSCAN-CFAR are also confirmed by the comparisons of conventional CFAR processors in different clutter conditions, comprised of varying target numbers, shape parameters, and false alarm probabilities. Although the proposed ANN-based DBSCAN-CFAR processor incurs more elapsed time, it achieves superior CFAR performance without a prior knowledge on the number and distribution of interference targets

Rheology of colloidal gas aphrons (MICROFOAMS) made from different surfactants

This paper extends our previous study on microfoam rheology made from non-ionic (Tween 20) surfactants to ionic surfactants. Anionic (sodium dodecyl sulfate) and cationic (cetyl trimethylammonium bromide) surfactants were used to generate microfoams by stirring an aqueous surfactant solution at high speed in a baffled beaker. Pipe flow experiments were performed in cylindrical stainless steel pipe 1.5 mm in diameter under adiabatic and fully developed laminar flow conditions. The porosity, bubble size distribution, Sauter mean radius , surface tension, and pH are reported for each solution. The porosity varied between 0.54 and 0.72 while the Sauter mean radius ranged from 28 to 48 microns. Zero slip velocity was assumed to prevail at the foam-wall interface as previously observed and reported in the literature for stainless steel pipes. Volume equalized method was used to analyze the data obtained from pipe flow viscometer. In all cases, microfoams behave as a shear thinning fluid. The results suggest that the dimensionless wall shear stress is proportional to the capillary number raised to the power m. The average value of the power-law index m was found to be 0.64 +/- 0.04 with 95% confidence interval