Sustainable CO2 adsorbents prepared by coating chitosan onto mesoporous silicas for large-scale carbon capture technology

In this article, we report a new sustainable synthesis procedure for manufacturing chitosan/silica CO2 adsorbents. Chitosan is a naturally abundant material and contains amine functionality, which is essential for selective CO2 adsorptions. It is, therefore, ideally suited for manufacturing CO2 adsorbents on a large scale. By coating chitosan onto high-surface-area mesoporous silica supports, including commercial fumed silica (an economical and accessible reagent) and synthetic SBA-15 and MCF silicas, we have prepared a new family of CO2 adsorbents, which have been fully characterised with nitrogen adsorption isotherms, thermogravimetric analysis/differential scanning calorimetry, TEM, FTIR spectroscopy and Raman spectroscopy. These adsorbents have achieved a significant CO2 adsorption capacity of up to 0.98 mmol g−1 at ambient conditions (P=1 atm and T=25 °C). The materials can also be fully regenerated/recycled on demand at temperatures as low as 75 °C with a >85 % retention of the adsorption capacity after 4 cycles, which makes them promising candidates for advanced CO2 capture, storage and utilisation technology

Ultrafast optical ranging using microresonator soliton frequency combs

Light detection and ranging (LIDAR) is critical to many fields in science and industry. Over the last decade, optical frequency combs were shown to offer unique advantages in optical ranging, in particular when it comes to fast distance acquisition with high accuracy. However, current comb-based concepts are not suited for emerging high-volume applications such as drone navigation or autonomous driving. These applications critically rely on LIDAR systems that are not only accurate and fast, but also compact, robust, and amenable to cost-efficient mass-production. Here we show that integrated dissipative Kerr-soliton (DKS) comb sources provide a route to chip-scale LIDAR systems that combine sub-wavelength accuracy and unprecedented acquisition speed with the opportunity to exploit advanced photonic integration concepts for wafer-scale mass production. In our experiments, we use a pair of free-running DKS combs, each providing more than 100 carriers for massively parallel synthetic-wavelength interferometry. We demonstrate dual-comb distance measurements with record-low Allan deviations down to 12 nm at averaging times of 14 $\mu$s as well as ultrafast ranging at unprecedented measurement rates of up to 100 MHz. We prove the viability of our technique by sampling the naturally scattering surface of air-gun projectiles flying at 150 m/s (Mach 0.47). Combining integrated dual-comb LIDAR engines with chip-scale nanophotonic phased arrays, the approach could allow widespread use of compact ultrafast ranging systems in emerging mass applications.Comment: 9 pages, 3 figures, Supplementary information is attached in 'Ancillary files

Optimized unconventional superconductivity in a molecular Jahn-Teller metal

Understanding the relationship between the superconducting, the neighboring insulating, and the normal metallic state above Tc is a major challenge for all unconventional superconductors. The molecular A3C60 fulleride superconductors have a parent antiferromagnetic insulator in common with the atom-based cuprates, but here, the C603– electronic structure controls the geometry and spin state of the structural building unit via the on-molecule Jahn-Teller effect. We identify the Jahn-Teller metal as a fluctuating microscopically heterogeneous coexistence of both localized Jahn-Teller–active and itinerant electrons that connects the insulating and superconducting states of fullerides. The balance between these molecular and extended lattice features of the electrons at the Fermi level gives a dome-shaped variation of Tc with interfulleride separation, demonstrating molecular electronic structure control of superconductivity

Evidence for phase formation in potassium intercalated 1,2;8,9-dibenzopentacene

We have prepared potassium intercalated 1,2;8,9-dibenzopentacene films under vacuum conditions. The evolution of the electronic excitation spectra upon potassium addition as measured using electron energy-loss spectroscopy clearly indicate the formation of particular doped phases with compositions K$_x$dibenzopentacene ($x$ = 1,2,3). Moreover, the stability of these phases as a function of temperature has been explored. Finally, the electronic excitation spectra also give insight into the electronic ground state of the potassium doped 1,2;8,9-dibenzopentacene films.Comment: 6 pages, 5 figures. arXiv admin note: text overlap with arXiv:1201.200

U-DADA:Unsupervised Deep Action Domain Adaptation

The problem of domain adaptation has been extensively studied for object classification task. However, this problem has not been as well studied for recognizing actions. While, object recognition is well understood, the diverse variety of videos in action recognition make the task of addressing domain shift to be more challenging. We address this problem by proposing a new novel adaptation technique that we term as unsupervised deep action domain adaptation (U-DADA). The main concept that we propose is that of explicitly modeling density based adaptation and using them while adapting domains for recognizing actions. We show that these techniques work well both for domain adaptation through adversarial learning to obtain invariant features or explicitly reducing the domain shift between distributions. The method is shown to work well using existing benchmark datasets such as UCF50, UCF101, HMDB51 and Olympic Sports. As a pioneering effort in the area of deep action adaptation, we are presenting several benchmark results and techniques that could serve as baselines to guide future research in this area.</p

Antimicrobial properties of gallium (III)-and iron (III)-loaded polysaccharides affecting the growth of escherichia coli, staphylococcus aureus, and pseudomonas aeruginosa, in vitro

Antimicrobial resistance (AMR) has become a global concern as many bacterial species have developed resistance to commonly prescribed antibiotics, making them ineffective to treatments. One type of antibiotics, gallium(III) compounds, stands out as possible candidates due to their unique “Trojan horse” mechanism to tackle bacterial growth, by substituting iron(III) in the metabolic cycles of bacteria. In this study, we tested three polysaccharides (carboxymethyl cellulose (CMC), alginate, and pectin) as the binding and delivery agent for gallium on three bacteria (Pseudomonas aeruginosa, Escherichia coli, and Staphylococcus aureus) with a potential bioresponsive delivery mode. Two types of analysis on bacterial growth (minimum inhibitory concentrations (MIC) and minimum bactericidal concentrations (MBC)) were carried out while iron(III)-loaded polysaccharide samples were also tested for comparison. The results suggested that gallium showed an improved inhibitory activity on bacterial growth, in particular gallium(III)-loaded carboxymethyl cellulose (Ga-CMC) sample showing an inhibiting effect on growth for all three tested bacteria. At the MIC for all three bacteria, Ga-CMC showed no cytotoxicity effect on human dermal neonatal fibroblasts (HDNF). Therefore, these bioresponsive gallium(III) polysaccharide compounds show significant potential to be developed as the next-generation antibacterial agents with controlled release capability.info:eu-repo/semantics/acceptedVersio

Robust Domain Adaptation Approach for Tweet Classification for Crisis Response

Information posted by people on Twitter during crises can significantly improve crisis response towards reducing human and financial loss. Deep learning algorithms can identify related tweets to reduce information overloaded which prevents humanitarian organizations from using Twitter posts. However, they heavily rely on labeled data which is unavailable for emerging crises. And because each crisis has its own features such as location, occurring time and social media response, current models are known to suffer from generalizing to unseen disaster events when pretrained on past ones. To solve this problem, we propose a domain adaptation approach that makes use of a distant supervision-based framework to label the unlabeled data from emerging crises. Then, pseudo-labeled target data, along with labeled-data from similar past disasters, are used to build the target model. Our results show that our approach can be seen as a general robust method to classify unseen tweets from current events

Nitrides as ammonia synthesis catalysts and as potential nitrogen transfer reagents

In this article, an overview of the application of selected metal nitrides as ammonia synthesis catalysts is presented. The potential development of some systems into nitrogen transfer reagents is also described

Gold-iron oxide (Au/Fe3O4) magnetic nanoparticles as the nanoplatform for binding of bioactive molecules through self-assembly

Nanomedicine plays a crucial role in the development of next-generation therapies. The use of nanoparticles as drug delivery platforms has become a major area of research in nanotechnology. To be effective, these nanoparticles must interact with desired drug molecules and release them at targeted sites. The design of these “nanoplatforms” typically includes a functional core, an organic coating with functional groups for drug binding, and the drugs or bioactive molecules themselves. However, by exploiting the coordination chemistry between organic molecules and transition metal centers, the self-assembly of drugs onto the nanoplatform surfaces can bypass the need for an organic coating, simplifying the materials synthesis process. In this perspective, we use gold-iron oxide nanoplatforms as examples and outline the prospects and challenges of using self-assembly to prepare drug-nanoparticle constructs. Through a case study on the binding of insulin on Au-dotted Fe3O4 nanoparticles, we demonstrate how a self-assembly system can be developed. This method can also be adapted to other combinations of transition metals, with the potential for scaling up. Furthermore, the self-assembly method can also be considered as a greener alternative to traditional methods, reducing the use of chemicals and solvents. In light of the current climate of environmental awareness, this shift towards sustainability in the pharmaceutical industry would be welcomed

Superconductivity at 5 K in potassium doped phenanthrene

Organic materials are believed to be potential superconductor with high transition temperature (TC). Organic superconductors mainly have two families: the quasi-one dimensional (TMTSF)2X and two dimensional (BEDT-TTF)2X (Ref. 1 and 2), in which TMTSF is tetramethyltetraselenafulvalene (C10H12Se4) and BEDT-TTF or "ET" is bis(ethylenedithio)tetrathiafulvalene (C10H8S8). One key feature of the organic superconductors is that they have {\pi}-molecular orbitals, and the {\pi}-electron can delocalize throughout the crystal giving rise to metallic conductivity due to a {\pi}-orbital overlap between adjacent molecules. The introduction of charge into C60 solids and graphites with {\pi}-electron networks by doping to realize superconductivity has been extensively reported3,4. Very recently, superconductivity in alkali-metal doped picene with {\pi}-electron networks was reported5. Here we report the discovery of superconductivity in potassium doped Phenanthrene with TC~5 K. TC increases with increasing pressure, and the pressure of 1 GPa leads to an increase of 20% in TC, suggesting that the potassium doped phenanthrene shows unconventional superconductivity. Both phenanthrene and picene are polycyclic aromatic hydrocarbons, and contain three and five fused benzene rings, respectively. The ribbon of fused benzene rings is part of graphene. Therefore, the discovery of superconductivity in K3Phenanthrene produces a novel broad class of superconductors consisting of fused hydrocarbon benzene rings with {\pi}-electron networks. The fact that TC increases from 5 K for KxPhenanthrene with three benzene rings to 18 K for Kxpicene with five benzene rings suggests that such organic hydrocarbons with long benzene rings is potential superconductor with high TC.Comment: 20 pages, 3 figures, one supplementary information. submitted to Nature Communication