Design of a Graphene Nitrene Two-Dimensional Catalyst Heterostructure Providing a Well-Defined Site Accommodating 1 to 3 Metals, with Application to CO₂ Reduction Electrocatalysis for the 2 Metal Case

Recently, the reduction of CO₂ to fuels has been the subject of numerous studies, but the selectivity and activity remain inadequate. Progress has been made on single-site two-dimensional catalysts based on graphene coupled to a metal and nitrogen for the CO₂ reduction reaction (CO₂RR); however, the product is usually CO, and the metal–N environment remains ambiguous. We report a novel two-dimensional graphene nitrene heterostructure (grafiN₆) providing well-defined active sites (N₆) that can bind one to three metals for the CO₂RR. We find that homobimetallic FeFe–grafiN₆ could reduce CO₂ to CH₄ at −0.61 V and to CH₃CH₂OH at −0.68 V versus reversible hydrogen electrode, with high product selectivity. Moreover, the heteronuclear FeCu–grafiN₆ system may be significantly less affected by hydrogen evolution reaction, while maintaining a low limiting potential (−0.68 V) for C1 and C2 mechanisms. Binding metals to one N₆ site but not the other could promote efficient electron transport facilitating some reaction steps. This framework for single or multiple metal sites might also provide unique catalytic sites for other catalytic processes

Predicted Optimal Bifunctional Electrocatalysts for the Hydrogen Evolution Reaction and the Oxygen Evolution Reaction Using Chalcogenide Heterostructures Based on Machine Learning Analysis of in Silico Quantum Mechanics Based High Throughput Screening

Two-dimensional van der Waals heterostructure materials, particularly transition metal dichalcogenides (TMDC), have proved to be excellent photoabsorbers for solar radiation, but performance for such electrocatalysis processes as water splitting to form H₂ and O₂ is not adequate. We propose that dramatically improved performance may be achieved by combining two independent TMDC while optimizing such descriptors as rotational angle, bond length, distance between layers, and the ratio of the bandgaps of two component materials. In this paper we apply the least absolute shrinkage and selection operator (LASSO) process of artificial intelligence incorporating these descriptors together with quantum mechanics (density functional theory) to predict novel structures with predicted superior performance. Our predicted best system is MoTe₂/WTe₂ with a rotation of 300°, which is predicted to have an overpotential of 0.03 V for HER and 0.17 V for OER, dramatically improved over current electrocatalysts for water splitting

Advances and challenges in shale oil development: A critical review

    Different from the conventional oil reservoirs, the primary storage space of shale is micro/nano pore networks. Moreover, the multiscale and multi-minerals characteristics of shale also attract increasing attentions from researchers. In this work, the advances and challenges in the development of shale oil are summarized from following aspects: phase behavior, flow mechanisms, reservoir numerical simulation and production optimization. The phase behavior of fluids confined in shale nanopores are discussed on the basis of theoretical calculations, experiments, and molecular simulations. The fluid transport mechanisms through shale matrix are analyzed in terms of molecular dynamics, pore scale simulations, and experimental studies. The methods employed in fracture propagation simulation and production optimization of shale oil are also introduced. Clarifying the problems of current research and the need for future studies are conducive to promoting the scientific and effective development of shale oil resources.Cited as: Feng, Q., Xu, S., Xing, X., Zhang, W., Wang, S. Advances and challenges in shale oil development: A critical review. Advances in Geo-Energy Research, 2020, 4(4), 406-418, doi: 10.46690/ager.2020.04.0

High-Throughput Screening of Transition Metal Single-Atom Catalysts for Nitrogen Reduction Reaction

The discovery of metals as catalytic centers for nitrogen reduction reactions has stimulated great enthusiasm for single-atom catalysts. However, the poor activity and low selectivity of available SACs are far away from the industrial requirement. Through the high throughout first principles calculations, the doping engineering can effectively regulate the NRR performance of b-Sb monolayer. Especially, the origin of activated N2 is revealed from the perspective of the electronic structure of the active center. Among the 24 transition metal dopants, Re@Sb and Tc@Sb showed the best NRR catalytic performance with a low limiting potential. The Re@Sb and Tc@Sb also could significantly inhibit HER and achieve a high theoretical Faradaic efficiency of 100%. Our findings not only accelerate discovery of catalysts for ammonia synthesis but also contribute to further elucidate the structure-performance correlations

Predicted Optimal Bifunctional Electrocatalysts for the Hydrogen Evolution Reaction and the Oxygen Evolution Reaction Using Chalcogenide Heterostructures Based on Machine Learning Analysis of in Silico Quantum Mechanics Based High Throughput Screening

Two-dimensional van der Waals heterostructure materials, particularly transition metal dichalcogenides (TMDC), have proved to be excellent photoabsorbers for solar radiation, but performance for such electrocatalysis processes as water splitting to form H₂ and O₂ is not adequate. We propose that dramatically improved performance may be achieved by combining two independent TMDC while optimizing such descriptors as rotational angle, bond length, distance between layers, and the ratio of the bandgaps of two component materials. In this paper we apply the least absolute shrinkage and selection operator (LASSO) process of artificial intelligence incorporating these descriptors together with quantum mechanics (density functional theory) to predict novel structures with predicted superior performance. Our predicted best system is MoTe₂/WTe₂ with a rotation of 300°, which is predicted to have an overpotential of 0.03 V for HER and 0.17 V for OER, dramatically improved over current electrocatalysts for water splitting

Anti-inflammatory Effects of α7-nicotinic ACh Receptors are Exerted Through Interactions with Adenylyl Cyclase-6

Background and purpose Alpha 7 nicotinic acetylcholine receptors (CHRNA7) suppress inflammation through diverse pathways in immune cells, so is potentially involved in a number of inflammatory diseases. However, the detailed mechanisms underlying CHRNA7’s anti‐inflammatory effects remain elusive. Experimental approach The anti‐inflammatory effects of CHRNA7 agonists in both murine macrophages (RAW 264.7) and bone marrow‐derived macrophages (BMDM) stimulated with LPS were examined. The role of adenylyl cyclase 6 (AC6) in Toll‐like Receptor 4 (TLR4) degradation was explored via overexpression and knockdown. A mouse model of chronic obstructive pulmonary disease was used to confirm key findings. Results Anti‐inflammatory effects of CHRNA7 were largely dependent on AC6 activation, as knockdown of AC6 considerably abnegated the effects of CHRNA7 agonists while AC6 overexpression promoted them. We found that CHRNA7 and AC6 are co‐localized in lipid rafts of macrophages and directly interact. Activation of AC6 led to the promotion of TLR4 degradation. Administration of CHRNA7 agonist PNU‐282987 attenuated pathological and inflammatory end points in a mouse model of chronic obstructive pulmonary disease (COPD). Conclusion and implications CHRNA7 inhibits inflammation through activating AC6 and promoting degradation of TLR4. The use of CHRNA7 agonists may represent a novel therapeutic approach for treating COPD and likely other inflammatory diseases

Structural and Functional Insights into an Archaeal Lipid Synthase

The UbiA superfamily of intramembrane prenyltransferases catalyzes an isoprenyl transfer reaction in the biosynthesis of lipophilic compounds involved in cellular physiological processes. Digeranylgeranylglyceryl phosphate (DGGGP) synthase (DGGGPase) generates unique membrane core lipids for the formation of the ether bond between the glycerol moiety and the alkyl chains in archaea and has been confirmed to be a member of the UbiA superfamily. Here, the crystal structure is reported to exhibit nine transmembrane helices along with a large lateral opening covered by a cytosolic cap domain and a unique substrate-binding central cavity. Notably, the lipid-bound states of this enzyme demonstrate that the putative substrate-binding pocket is occupied by the lipidic molecules used for crystallization, indicating the binding mode of hydrophobic substrates. Collectively, these structural and functional studies provide not only an understanding of lipid biosynthesis by substrate-specific lipid-modifying enzymes but also insights into the mechanisms of lipid membrane remodeling and adaptation