High performance asymmetric supercapacitor based on 3D microsphere-like 1T-MoS2 with high 1T phase content

1T phase molybdenum disulfide (1T-MoS₂) has aroused extensive concern in energy storage devices such as supercapacitors due to its large interlayer spacing, high conductivity and good hydrophilicity. However, it is struggle to synthesize 1T-MoS₂ with stable 1T phase with high content. Herein, Ammonium ion intercalation molybdenum disulfide (A-MoS₂) with high 1T content and stable 3D microsphere structure was successfully synthesized using a facile hydrothermal method. We explained the feasibility of ammonium ion (NH₄⁺) intercalation through density functional theory (DFT) calculations and proved the successful intercalation of NH₄⁺ by XRD and XPS. Through XPS fitting, the 1T phase content is calculated as high as 83.1%. The as-prepared A-MoS₂ presents a stable 3D microsphere structure with the interlayer spacing expanded to 0.93 nm, which provides a wide ion diffusion channel that allows ions to pass through quickly. Moreover, the high 1T content increases the hydrophilicity of MoS₂, thereby improving the wettability of the electrode, which contributes to the interaction between the electrolyte and electrode. In 1 M Na₂SO₄, A-MoS₂ electrode material displays high specific capacitance of 228 F g^?1 at 5 mV s^?1 and retains 127 F g^?1 at 80 mV s^?1, which proves the good rate capability. Furthermore, the assembled α-MnO₂//A-MoS₂ asymmetric supercapacitor (ASC) displayed a wide operating voltage of 2.1 V. The assembled ASC displays a high energy density of 35.8 Wh?kg^?1 at a power density of 525.0 W kg^?1, which indicates excellent energy storage performance.     

Ir(III) and Ru(II) Complexes in Photoredox Catalysis and Photodynamic Therapy: A New Paradigm towards Anticancer Applications

Individually, photoredox catalysis (PC) and photodynamic therapy (PDT) are well-established concepts that have experienced a remarkable resurgence in recent years, leading to significant progress in organic synthesis for PC and clinical approval of anticancer drugs for PDT. But, very recently, new photoredox catalyst systems based on Ir(III) and Ru(II) complexes have garnered significant interest because they can simultaneously be used as PDT agents apart from their demonstrated PC activity. This highlight discusses the unique PC behavior of emerging Ir(III)- and Ru(II)-based systems while also examining their potential PDT activity in cancer treatment.     

Deep reinforcement learning-based cooperative interactions among heterogeneous vehicular networks

Most real-world vehicle nodes can be structured into an interconnected network of vehicles. Through structuring these services and vehicle device interactions into multiple types, such internet of vehicles becomes multidimensional heterogeneous overlay networks. The heterogeneousness of the overlays makes it difficult for the overlay networks to coordinate with each other to improve their performance. Therefore, it poses an interesting but critical challenge to the effective analysis of heterogeneous virtual vehicular networks. A variety of virtual vehicular networks can be easily deployed onto the native network by applying the concept of SDN (Software Defined Networking). These virtual networks reflect their heterogeneousness due to their different performance goals, and they compete for the same physical resources of the underlying network, so that a sub-optimal performance of the virtual networks may be achieved. Therefore, we propose a Deep Reinforcement Learning (DRL) approach to make the virtual networks cooperate with each other through the SDN controller. A cooperative solution based on the asymmetric Nash bargaining is proposed for co-existing virtual networks to improve their performance. Moreover, the Markov Chain model and DRL resolution are introduced to leverage the heterogeneous performance goals of virtual networks. The implementation of the approach is introduced, and simulation results confirm the performance improvement of the latency sensitive, loss-rate sensitive and throughput sensitive heterogeneous vehicular networks using our cooperative solution.     

Evaluation of the degree of rate control via automatic differentiation

The degree of rate control (DRC) quantitatively identifies the kinetically relevant (sometimes known as rate-limiting) steps of a complex reaction network. This concept relies on derivatives which are commonly implemented numerically, for example, with finite differences (FDs). Numerical derivatives are tedious to implement, and can be problematic, and unstable or unreliable. In this study, we demonstrate the use of automatic differentiation (AD) in the evaluation of the DRC. AD libraries are increasingly available through modern machine learning frameworks. Compared with the FDs, AD provides solutions with higher accuracy with lower computational cost. We demonstrate applications in steady-state and transient kinetics. Furthermore, we illustrate a hybrid local-global sensitivity analysis method, the distributed evaluation of local sensitivity analysis, to assess the importance of kinetic parameters over an uncertain space. This method also benefits from AD to obtain high-quality results efficiently.     

Alteration of the Route to Menaquinone towards Isochorismate-Derived Metabolites

Chorismate and isochorismate constitute branch-point intermediates in the biosynthesis of many aromatic metabolites in microorganisms and plants. To obtain unnatural compounds, we modified the route to menaquinone in Escherichia coli. We propose a model for the binding of isochorismate to the active site of MenD ((1R,2S, 5S,6S)-2-succinyl-5-enolpyruvyl-6-hydroxycyclohex-3-ene-1-carboxylate (SEPHCHC) synthase) that explains the outcome of the native reaction with α-ketoglutarate. We have rationally designed variants of MenD for the conversion of several isochorismate analogues. The double-variant Asn117Arg–Leu478Thr preferentially converts (5S,6S)-5,6-dihydroxycyclohexa-1,3-diene-1-carboxylate (2,3-trans-CHD), the hydrolysis product of isochorismate, with a >70-fold higher ratio than that for the wild type. The single-variant Arg107Ile uses (5S,6S)-6-amino-5-hydroxycyclohexa-1,3-diene-1-carboxylate (2,3-trans-CHA) as substrate with >6-fold conversion compared to wild-type MenD. The novel compounds have been made accessible in vivo (up to 5.3 g L⁻¹). Unexpectedly, as the identified residues such as Arg107 are highly conserved (>94 %), some of the designed variations can be found in wild-type SEPHCHC synthases from other bacteria (Arg107Lys, 0.3 %). This raises the question for the possible natural occurrence of as yet unexplored branches of the shikimate pathway.     

Fabrication of BSCF-based mixed ionic-electronic conducting membrane by electrophoretic deposition for oxygen separation application

Ba_0.5Sr_0.5Co_0.8Fe_0.2O_3-δ (BSCF), which exhibits a high mixed oxide ionic-electronic conduction, was used for the fabrication of an oxygen separation membrane. An asymmetric structure, which was a thin and dense BSCF membrane layer supported on a porous BSCF substrate, was fabricated by the electrophoretic deposition method (EPD). Porous BSCF supports were prepared by the uniaxial pressing method using a powder mixture with BSCF and starch as the pore-forming agent (0–50 wt.%). The sintering behaviors of the porous support and the thin layer were separately characterized by dilatometry to determine the co-fired temperature at which cracking did not occur. A crack-free and thin dense membrane layer, which had about a 15 μm thickness and >95% relative density, was obtained after optimizing the processes of EPD and sintering. The dense/porous interface was well-bonded and the oxygen permeation flux was 2.5 ml (STP) min⁻¹ cm^-2 at 850 °C.