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Comprehensive structural/molecular simulations have been undertaken to study the poly(benzimidazoles) (PBI) membrane combined with four different nano-oxide materials (ZnO, Al 2 O 3 , SiO 2 and TiO 2 ) for purification and production of hydrogen from natural gases. Composite membranes were built with different amounts of nano-oxide materials to investigate the influence of nano-oxide content on the PBI membrane performance. Several structural characterizations such as FFV, WAXD and also a thermal one (glass transition temperature) were done to study the structural properties of all simulated membrane cells. Moreover, MSD and adsorption isotherms tasks were used to estimate the diffusivity and solubility of hydrogen molecules through the latter mixed matrix membranes (MMMs), respectively. Permeability and permselectivity of H 2 penetrate molecules were also carefully calculated using the aforementioned penetrating factors (diffusivity and solubility). Results show a significant improvement in structural and transport properties by increasing the nanomaterials content, which could be due to the growth of penetration pathways through the membranes. Furthermore, membranes with SiO 2 yield the best results compared to other three nano-oxide fillers. H 2 gas yields the best results that help the storage and separation of this precious gas from other gas molecules, which present in natural gases. Compared to the previous studies and literature results, the current results are accurate and reliable to describe the structural and transport properties of PBI/nano-oxides composites. [ABSTRACT FROM AUTHOR]

In this communication, structural-transport-properties of polyether block amide (PEBA)-MFI zeolite mixed matrix membranes (MMMs) have been investigated with molecular simulation (MS) and Monte Carlo (MC) technique. The density profile, RDF, FFV and XRD characterization have been calculated to investigate the aforementioned MMMs microstructure and also sorption and diffusion structural dependence of CO 2 –CH 4 and CO 2 –N 2 pairs. Sorption, diffusion, permeability and selectivity of natural gases including CO 2 , CH 4 and N 2 by PEBA polymeric membrane filled with nano-zeolite (MFI type) have been examined to study the influence of MFI nanomaterial and nanomaterial loading content on the performance of the MMMs. By increase of MFI loading from 10 to 20 wt.%, permeability for CO 2 , CH 4 and N 2 increases from 106.5 to 123.6, 4.75–4.74 and 1.28 to1.31, respectively. Structural analysis shows very good behavior for simulated membranes. Moreover, experiments show that simulation results for XRD and diffusivity are in good agreement with experiment results. [ABSTRACT FROM AUTHOR]

Recalcitrant pollutants in water with high resistance to natural degradation such as per/polyfluoroalkyl substances (PFAS) highlight the need for sustainable, cheap, and effective treatment approaches. Although photocatalysis under direct sunlight can be beneficial due to the usage of ambient conditions for the reaction, air as the oxidant, and sunlight as the energy source, identifying sustainable and sunlight photoactive materials and a process that is both scalable and industrially feasible are challenging. Herein, we report the use of ZnO/cellulose nanofiber (CNF) composites for the photodegradation of PFOA and PFOS upon irradiation by sunlight in a continuous flow photoreactor. HPLC/MS/MS and fluoride quantification using the SPADNS method were used to track the degradation of PFAS and by-product formation. Aqueous solutions of three different standard PFAS samples containing 1200 µg/L of PFOA, 800 µg/L PFOS, and a mixture of 900 µg/L of PFOA and 900 µg/L of PFOS, and a wastewater treatment plant sample with 2.5 µg/L of an environmental mixture of PFAS compounds present in urban wastewater were used for the photocatalytic degradation tests. The concentration of these pollutants and their by-products in these samples was reduced to 0.5 µg/L, 0.07 µg/L, 0.15 µg/L, and 0.3 µg/L with an EE/O figure of merit of 0.19, 0.28, 0.43, 0.88 kWh/m3 per order, respectively. It was observed that the standard mixture and the wastewater treatment plant samples were harder to degrade as compared to the standards containing one PFAS compound. Reusing the catalyst for three cycles showed less than 4% reduction in photodegradation over irradiation time. These findings emphasize the importance of location-specific design as the choice of photocatalyst is enabled by the UVA/B solar radiance characteristics present in Australia. [Display omitted] • Sun-flow photocatalytic PFASs degradation was investigated. • photodegradation of real wastewater containing PFASs was studied. • For the photodegradation process, zinc oxide/cellulose nanofiber catalyst was used. • The concentration of pollutants was reduced to below advised limits. [ABSTRACT FROM AUTHOR]

Cellulose nanofibril (CNF) is regarded as one of the world's advanced biomaterials. However, its production consumes high energy, making it unappealing for many applications. The life cycle assessment studies conducted on CNF indicate that a high environmental impact is mainly due to its novel nature and unexplored future directions. This study aims to analyze the cradle to gate life cycle assessment of a CNF film via four flexible production routes (two-spray deposition and two vacuum filtration processes) for small-scale production. The baseline and high impact scenarios for these films were also used to perform a sensitivity analysis. The results indicate that refined, homogenized and vacuum filtered CNF film (2 g) having a basis weight of 100 g/m2 showed the highest embodied energy (0.426 MJ), global warming potential (0.034 kg CO 2 equiv.) and water usage values (1.033 L), while refined and spray deposited film has the least life cycle impacts (0.241 MJ, 0.018 kg CO2 equiv. & 0.264 L). Although, these films showed approximately 15%–20% higher environmental impacts as compared with the conventional plastic films such as polyethylene terephthalate, however, the expected impact could be much lower if "cradle to grave" or "cradle to cradle" cycles are considered instead and the scale of production is increased. [Display omitted] ➢ Life cycle impacts of cellulose nanofibril films are assessed for small scale production ➢ Spray deposition using refined fibres route showed the least life cycle impacts ➢ Important categories influencing the life cycle impacts are evaluated in sensitivity analysis ➢ The viable options to reduce the life cycle impacts of these films are also discussed [ABSTRACT FROM AUTHOR]

This paper numerically investigates a three-dimensional channel's thermal and hydrodynamic performance with a convergent-divergent section. The convergent-divergent part of the channel is exposed to constant heat flux, and the other walls of the channel are insulated. In particular, the effect of using the nanofluid and magnetic field on Nusselt values, coefficient of friction, and entropy have been investigated. To improve Nusselt, pressure drop, and dimensionless entropy production rate, the Taguchi and ANFIS techniques have been utilized to optimize Reynolds, Hartmann numbers, nanofluid volume fraction, and geometric parameters of the channel. The sensitivity analysis results depict that Reynolds, Hartmann dimensionless numbers, and nanofluid volume fraction play more significant roles in improving the thermal and hydrodynamic performance of the channel than geometric parameters. The results show that the increase in the nanofluid volume fraction causes the most significant increase in the Nusselt number. In this case, the pressure drop inside the channel has increased slightly, but in total, the entropy production rate decreases due to irreversibility. Compared to the base case with the Reynolds number of 100, and in the absence of a magnetic field (Hartman 0), increasing the nanofluid volume fraction to 7% causes an 80% increase in the Nusselt number and a 65% decrease in the dimensionless entropy production rate. Similarly, by increasing the Reynolds number to 500 compared to the base case, the Nusselt number increases by 60% and the dimensionless entropy production rate decreases by 60%. Also, increasing the Hartmann number to 10 compared to the base case causes a 30% increase in the dimensionless Nusselt number and a 45% decrease in the dimensionless entropy production rate. • Heat transfer of a three-dimensional channel with a convergent-divergent section was analyzed. • The impacts of efective parameters on Nusselt, pressure drop, and dimensionless entropy production rate was investigated. • The Taguchi algorithm and ANFIS technique were exploited to optimize the thermal and hydrodynamic performance of the channel. [ABSTRACT FROM AUTHOR]

Chromosome analysis is essential for diagnosing genetic disorders. For hematologic malignancies, identification of somatic clonal aberrations by karyotype analysis remains the standard of care, with the advantage to identify global genomic aberrations at a single-cell basis. However, karyotyping is costly and time-consuming because of the largely manual process and the expertise required in identifying and annotating aberrations. Efforts to automate karyotype analysis to date fell short in aberration detection. Using a training set of ∼10k patient specimens and ∼50k karyograms from over 5 years from the Fred Hutchinson Cancer Center, we created a labeled set of images representing individual chromosomes. These individual chromosomes were used to train and assess deep learning models for classifying the 24 human chromosomes and identifying chromosomal aberrations. The top-accuracy models for both chromosome identification and aberration detection task utilized the recently introduced Topological Vision Transformers (TopViTs) with 2-level-block-Toeplitz masking, to incorporate structural inductive bias. On the baseline task of chromosome identification, our transformer-based models outperformed CNN (Inception) models with >99.3% accuracy. When applied to disease aberration detection, these high-performing architectures exhibited accuracies >99% for most aberrations). Notably, we were able to show high-quality performance even in 'few shot' learning scenarios, with limited examples of true aberrations. Incorporating the definition of clonality substantially improved both precision and recall (sensitivity). When applied to 'zero shot' scenarios, the model captured aberrations without training, with perfect precision at >50% recall. Together these results show that modern deep learning models can approach expert-level performance for chromosome aberration [ABSTRACT FROM AUTHOR]

• Spray deposited CMC/NC films are produced with significantly reduced drying time. • CMC/NC films have moisture barrier properties comparable with plastic packaging. • The environmental impact of CMC/NC films was lower than conventional packaging. Nanocellulose (NC) films are considered as a prospective alternative to non-sustainable packaging materials, however, their higher embodied energy and limited moisture barrier properties are regarded as a huge constraint regarding their commercialization. This study aims to produce films with relatively low environmental impact and improved barrier performance. For this purpose, carboxymethyl cellulose (CMC) and NC were combined, and this resulted in multidimensional advantages. The mass production of films could be achieved in only 2 h (requiring at least 24 h under ambient conditions) when dried in an oven at 75 °C with enhanced mechanical properties and without compromising their dimensional stability. The moisture barrier properties of the NC/CMC films were improved up to 92 % compared with the NC films alone and the results achieved are comparable with packaging materials such as polyethylene terephthalate (PET), polycarbonates (PC) etc. Finally, the NC/CMC (1:1) films have low environmental impact compared with PET films. [ABSTRACT FROM AUTHOR]