A Novel High‐Energy Hybrid Supercapacitor with an Anatase TiO2–Reduced Graphene Oxide Anode and an Activated Carbon Cathode

A hybrid supercapacitor with high energy and power densities is reported. It comprises a composite anode of anatase TiO₂ and reduced graphene oxide and an activated carbon cathode in a non‐aqueous electrolyte. While intercalation compounds can provide high energy typically at the expense of power, the anatase TiO₂ nanoparticles are able to sustain both high energy and power in the hybrid supercapacitor. At a voltage range from 1.0 to 3.0 V, 42 W h kg^?1 of energy is achieved at 800 W kg^?1. Even at a 4‐s charge/discharge rate, an energy density as high as 8.9 W h kg^?1 can be retained. The high energy and power of this hybrid supercapacitor bridges the gap between conventional batteries with high energy and low power and supercapacitors with high power and low energy.     

Quantum Dot Based Heterostructures for Unassisted Photoelectrochemical Hydrogen Generation

TiO₂ hollow nanowires (HNWs) and nanoparticles (NPs) constitute promising architectures for QDs sensitized photoanodes for H₂ generation. We sensitize these structures with CdS/CdSe quantum dots by two different methods (chemical bath deposition, CBD and succesive ionic layer adsorption and reaction, SILAR) and evaluate the performance of these photoelectrodes. Remarkable photocurrents of 4 mA·cm and 8 mA·cm^?2 and hydrogen generation rates of 40 ml·cm^?2·day^?1 and 80 ml·cm^?2·day^?1 have been obtained in a three electrode configuration with sacrificial hole scavengers (Na₂S and Na₂SO₃), for HNWs and NPs respectively, which is confirmed through gas analysis. More importantly, autonomous generation of H₂ (20 ml·cm^?2·day^?1 corresponding to 2 mA·cm^?2 photocurrent) is obtained in a two electrode configuration at short circuit under 100 mW·cm^?2 illumination, clearly showing that these photoanodes can produce hydrogen without the assistance of any external bias. To the best of the authors' knowledge, this is the highest unbiased solar H₂ generation rate reported for these of QDs based heterostructures. Impedance spectroscopy measurements show similar electron density of trap states below the TiO₂ conduction band while the recombination resistance was higher for HNWs, consistently with the much lower surface area compared to NPs. However, the conductivity of both structures is similar, in spite of the one dimensional character of HNWs, which leaves some room for improvement of these nanowired structures. The effect of the QDs deposition method is also evaluated. Both structures show remarkable stability without any appreciable photocurrent loss after 0.5 hour of operation. The findings of this study constitute a relevant step towards the feasibility of hydrogen generation with wide bandgap semiconductors/quantum dots based heterostructures.     

Sandwich‐Type Microporous Carbon Nanosheets for Enhanced Supercapacitor Performance

Sandwich‐type microporous hybrid carbon nanosheets (MHCN) consisting of graphene and microporous carbon layers are fabricated using graphene oxides as shape‐directing agent and the in‐situ formed poly(benzoxazine‐co‐resol) as carbon precursor. The reaction and condensation can be readily completed within 45 min. The obtained MHCN has a high density of accessible micropores that reside in the porous carbon with controlled thickness (e.g., 17 nm), a high surface area of 1293 m² g^?1 and a narrow pore size distribution of ca. 0.8 nm. These features allow an easy access, a rapid diffusion and a high loading of charged ions, which outperform the diffusion rate in bulk carbon and are highly efficient for an increased double‐layer capacitance. Meanwhile, the uniform graphene percolating in the interconnected MHCN forms the bulk conductive networks and their electrical conductivity can be up to 120 S m^?1 at the graphene percolation threshold of 2.0 wt.%. The best‐practice two‐electrode test demonstrates that the MHCN show a gravimetric capacitance of high up to 103 F g^?1 and a good energy density of ca. 22.4 Wh kg^?1 at a high current density of 5 A g^?1. These advanced properties ensure the MHCN a great promise as an electrode material for supercapacitors.     

Combining model structure identification and hybrid modelling for photo-production process predictive simulation and optimisation

Integrating physical knowledge and machine learning is a critical aspect of developing industrially focused digital twins for monitoring, optimisation, and design of microalgal and cyanobacterial photo-production processes. However, identifying the correct model structure to quantify the complex biological mechanism poses a severe challenge for the construction of kinetic models, while the lack of data due to the time-consuming experiments greatly impedes applications of most data-driven models. This study proposes the use of an innovative hybrid modelling approach that consists of a simple kinetic model to govern the overall process dynamic trajectory and a data-driven model to estimate mismatch between the kinetic equations and the real process. An advanced automatic model structure identification strategy is adopted to simultaneously identify the most physically probable kinetic model structure and minimum number of data-driven model parameters that can accurately represent multiple data sets over a broad spectrum of process operating conditions. Through this hybrid modelling and automatic structure identification framework, a highly accurate mathematical model was constructed to simulate and optimise an algal lutein production process. Performance of this hybrid model for long-term predictive modelling, optimisation, and online self-calibration is demonstrated and thoroughly discussed, indicating its significant potential for future industrial application.     

The geometry and genetics of hybridization

When divergent populations form hybrids, hybrid fitness can vary with genome composition, current environmental conditions, and the divergence history of the populations. We develop analytical predictions for hybrid fitness, which incorporate all three factors. The predictions are based on Fisher's geometric model, and apply to a wide range of population genetic parameter regimes and divergence conditions, including allopatry and parapatry, local adaptation, and drift. Results show that hybrid fitness can be decomposed into intrinsic effects of admixture and heterozygosity, and extrinsic effects of the (local) adaptedness of the parental lines. Effect sizes are determined by a handful of geometric distances, which have a simple biological interpretation. These distances also reflect the mode and amount of divergence, such that there is convergence toward a characteristic pattern of intrinsic isolation. We next connect our results to the quantitative genetics of line crosses in variable or patchy environments. This means that the geometrical distances can be estimated from cross data, and provides a simple interpretation of the “composite effects.” Finally, we develop extensions to the model, involving selectively induced disequilibria, and variable phenotypic dominance. The geometry of fitness landscapes provides a unifying framework for understanding speciation, and wider patterns of hybrid fitness.     

When secondary comes first – The importance of non-canonical DNA structures

Secondary structure-forming DNA motifs have achieved infamy because of their association with a variety of human diseases and cancer. The 3rd FASEB summer conference on dynamic DNA structures focused on the mechanisms responsible for the instabilities inherent to repetitive DNA and presented many exciting and novel aspects related to the metabolism of secondary structures. In addition, the meeting encompassed talks and posters on the dynamic structures that are generated during DNA metabolism including nicked DNA, Holliday junctions and RNA:DNA hybrids. New approaches for analysis and sequencing technologies put forth secondary structures and other DNA intermediates as vital regulators of a variety of cellular processes that contribute to evolution, polymorphisms and diseases.     

DNA-damage response in chromatin of ribosomal genes and the surrounding genome

DNA repair events have functional significance especially for genome stability. Although the DNA damage response within the whole genome has been extensively studied, the region-specific characteristics of nuclear sub-compartments such as the nucleolus or fragile sites have not been fully elucidated. Here, we show that the heterochromatin protein HP1 and PML protein recognize spontaneously occurring 53BP1- or γ-H2AX-positive DNA lesions throughout the genome. Moreover, 53BP1 nuclear bodies, which co-localize with PML bodies, also occur within the nucleoli compartments. Irradiation of the human osteosarcoma cell line U2OS with γ-rays increases the degree of co-localization between 53BP1 and PML bodies throughout the genome; however, the 53BP1 protein is less abundant in chromatin of ribosomal genes and fragile sites (FRA3B and FRA16D) in γ-irradiated cells. Most epigenomic marks on ribosomal genes and fragile sites are relatively stable in both non-irradiated and γ-irradiated cells. However, H3K4me2, H3K9me3, H3K27me3 and H3K79me1 were significantly changed in promoter and coding regions of ribosomal genes after exposure of cells to γ-rays. In fragile sites, γ-irradiation induces a decrease in H3K4me3, changes the levels of HP1β, and modifies the levels of H3K9 acetylation, while the level of H3K9me3 was relatively stable. In these studies, we confirm a specific DNA-damage response that differs between the ribosomal genes and fragile sites, which indicates the region-specificity of DNA repair.     

Controllers for imposing continuum-to-molecular boundary conditions in arbitrary fluid flow geometries

We present a new parallelised controller for steering an arbitrary geometric region of a molecular dynamics (MD) simulation towards a desired thermodynamic and hydrodynamic state. We show that the controllers may be applied anywhere in the domain to set accurately an initial MD state, or solely at boundary regions to prescribe non-periodic boundary conditions (PBCs) in MD simulations. The mean molecular structure and velocity autocorrelation function remain unchanged (when sampled a few molecular diameters away from the constrained region) when compared with those distributions measured using PBCs. To demonstrate the capability of our new controllers, we apply them as non-PBCs in parallel to a complex MD mixing nano-channel and in a hybrid MD continuum simulation with a complex coupling region. The controller methodology is easily extendable to polyatomic MD fluids.