Single atom Cu-N-C catalysts for the electro-reduction of CO_(2) to CO assessed by rotating ring-disc electrode

The electrochemical CO_(2) reduction reaction(CO_(2)RR) to controllable chemicals is considered as a promising pathway to store intermittent renewable energy. Herein, a set of catalysts based on copper-nitrogendoped carbon xerogel(Cu-N-C) are successfully developed varying the copper amount and the nature of the copper precursor, for the efficient CO_(2)RR. The electrocatalytic performance of Cu-N-C materials is assessed by a rotating ring-disc electrode(RRDE), technique still rarely explored for CO_(2)RR. For comparison, products are also characterized by online gas chromatography in a H-cell. The as-synthesized Cu-NC catalysts are found to be active and highly CO selective at low overpotentials(from -0.6 to -0.8 V vs.RHE) in 0.1 M KHCO_(3), while H_(2) from the competitive water reduction appears at larger overpotentials(-0.9 V vs. RHE). The optimum copper acetate-derived catalyst containing Cu-N_(4) moieties exhibits a CO_(2)-to-CO turnover frequency of 997 h^(-1) at -0.9 V vs. RHE with a H_(2)/CO ratio of 1.8. These results demonstrate that RRDE configuration can be used as a feasible approach for identifying electrolysis products from CO_(2)RR.

Spatiotemporal dynamics of ecosystem fires and biomass burning-induced carbon emissions in China over the past two decades

Fire is a major type of disturbance that has important influences on ecosystem dynamics and carbon cycles.Yet our understanding of ecosystem fires and their carbon cycle consequences is still limited,largely due to the difficulty of large-scale fire monitoring and the complex interactions between fire,vegetation,climate,and anthropogenic factors.Here,using data from satellite-derived fire observations and ecosystem model simulations,we performed a comprehensive investigation of the spatial and temporal dynamics of China’s ecosystem fire disturbances and their carbon emissions over the past two decades(1997–2016).Satellite-derived results showed that on average about 3.47-4.53×10^(4) km^(2) of the land was burned annually during the past two decades,among which annual burned forest area was about 0.81-1.25×10^(4) km^(2),accounting for 0.33-0.51%of the forest area in China.Biomass burning emitted about 23.02 TgC per year.Compared to satellite products,simulations from the Energy Exascale Earth System Land Model(ELM)strongly overestimated China’s burned area and fire-induced carbon emissions.Annual burned area and fire-induced carbon emissions were high for boreal forest in Northeast China’s Daxing’anling region and subtropical dry forest in South Yunnan,as revealed by both the satellite product and the model simulations.Our results suggest that climate and anthropogenic factors play critical roles in controlling the spatial and seasonal distribution of China’s ecosystem fire disturbances.Our findings highlight the importance of multiple complementary approaches in assessing ecosystem fire disturbance and its carbon consequences.Further studies are required to improve the methods of observing and modelling China’s ecosystem fire disturbances,which will provide valuable information for fire management and ecosystem sustainability in an era when both human activities and the natural environment are rapidly changing.

Surface oxidation of Ni-cermet electrodes by CO_(2) and H_(2)O and how to moderate it

The oxidation of porous Ni-yttria-stabilized zirconia(YSZ)and Ni-gadolinia-doped ceria(GDC)ceramicmetal(cermet)electrodes in H_(2)O and CO_(2)atmospheres was studied by near-ambient pressure X-ray photoelectron spectroscopy(NAP-XPS).We show that the oxidation of nickel by the two gases is not similar,as is commonly believed,but it depends on the ceramic type.Nickel is vulnerable to oxidation in H_(2)O but it resists to CO_(2)in Ni-GDC,as compared to the Ni-YSZ electrode.Inspired by this observation we conceptualize and fabricate Ni-YSZ electrodes modified by ceria nanoparticles,which show significantly higher resistance to CO_(2)oxidation as compared with conventional Ni-YSZ electrodes.The preparation of tailormade cermet electrodes with identical bulk/mechanical characteristics but very different surface properties offers a promising fabrication strategy for high-performance and durability solid oxide electrolysis cells for CO_(2)conversion.

Visualization of the electronic phase separation in superconducting K_(x)Fe_(2−y)Se_(2)

Type-II iron-based superconductors(Fe-SCs),the alkali-metal-intercalated iron selenide A_(x)Fe_(2−y)Se_(2)(A=K,Tl,Rb,etc.)with a superconducting transition temperature of 32 K,exhibit unique properties such as high Néel temperature,Fe-vacancies ordering,antiferromagnetically ordered insulating state in the phase diagram,and mesoscopic phase separation in the superconducting materials.In particular,the electronic and structural phase separation in these systems has attracted intensive attention since it provides a platform to unveil the insulating parent phase of type-II Fe-SCs that mimics the Mott parent phase in cuprates.In this work,we use spatial-and angle-resolved photoemission spectroscopy to study the electronic structure of superconducting K_(x)Fe_(2−y)Se_(2).We observe clear electronic phase separation of K_(x)Fe_(2−y)Se_(2) into metallic islands and insulating matrix,showing different K and Fe concentrations.While the metallic islands show strongly dispersive bands near the Fermi level,the insulating phase shows an energy gap up to 700 meV and a nearly flat band around 700 meV below the Fermi energy,consistent with previous experimental and theoretical results on the superconducting K_(1−x)Fe_(2)Se_(2)(122 phase)and Fe-vacancy ordered K_(0.8)Fe_(1.6)Se_(2)(245 phase),respectively.Our results not only provide important insights into the mysterious composition of phase-separated superconducting and insulating phases of K_(x)Fe_(2−y)Se_(2),but also present their intrinsic electronic structures,which will shed light on the comprehension of the unique physics in type-II Fe-SCs.

A convolutional neural network for defect classification in Bragg coherent X-ray diffraction

Coherent diffraction imaging enables the imaging of individual defects,such as dislocations or stacking faults,in materials.These defects and their surrounding elastic strain fields have a critical influence on the macroscopic properties and functionality of materials.However,their identification in Bragg coherent diffraction imaging remains a challenge and requires significant data mining.The ability to identify defects from the diffraction pattern alone would be a significant advantage when targeting specific defect types and accelerates experiment design and execution.Here,we exploit a computational tool based on a three-dimensional(3D)parametric atomistic model and a convolutional neural network to predict dislocations in a crystal from its 3D coherent diffraction pattern.Simulated diffraction patterns from several thousands of relaxed atomistic configurations of nanocrystals are used to train the neural network and to predict the presence or absence of dislocations as well as their type(screw or edge).Our study paves the way for defect-recognition in 3D coherent diffraction patterns for material science.

Connector theory for reusing model results to determine materials properties

The success of Density Functional Theory(DFT)is partly due to that of simple approximations,such as the Local Density Approximation(LDA),which uses results of a model,the homogeneous electron gas,to simulate exchange-correlation effects in real materials.We turn this intuitive approximation into a general and in principle exact theory by introducing the concept of a connector:a prescription how to use results of a model system in order to simulate a given quantity in a real system.In this framework,the LDA can be understood as one particular approximation for a connector that is designed to link the exchange-correlation potentials in the real material to that of the model.Formulating the in principle exact connector equations allows us to go beyond the LDA in a systematic way.Moreover,connector theory is not bound to DFT,and it suggests approximations also for other functionals and other observables.We explain why this very general approach is indeed a convenient starting point for approximations.We illustrate our purposes with simple but pertinent examples.

Competing magnetic states in silicene and germanene 2D ferromagnets

Two-dimension(2D)magnets have recently developed into a class of stoichiometric materials with prospective applications in ultra-compact spintronics and quantum computing.Their functionality is particularly rich when different magnetic orders are competing in the same material.Metalloxenes REX2(RE=Eu,Gd;X=Si,Ge),silicene or germanene—heavy counterparts of graphene—coupled with a layer of rare-earth metals,evolve from three-dimension(3D)antiferromagnets in multilayer structures to 2D ferromagnets in a few monolayers.This evolution,however,does not lead to fully saturated 2D ferromagnetism,pointing at a possibility of coexisting/competing magnetic states.Here,REX2 magnetism is explored with element-selective X-ray magnetic circular dichroism(XMCD).The measurements are carried out for GdSi2,EuSi2,GdGe2,and EuGe2 of different thicknesses down to 1 monolayer employing K absorption edges of Si and Ge as well as M and L edges of the rare-earths.They access the magnetic state in REX2 and determine the seat of magnetism,orbital,and spin contributions to the magnetic moment.High-field measurements probe remnants of the bulk antiferromagnetism in 2D REX2.The results provide a new platform for studies of complex magnetic structures in 2D materials.

Delocalization of dark and bright excitons in flat-band materials and the optical properties of V_(2)O_(5)

The simplest picture of excitons in materials with atomic-like localization of electrons is that of Frenkel excitons,where electrons and holes stay close together,which is associated with a large binding energy.Here,using the example of the layered oxide V_(2)O_(5),we show how localized charge-transfer excitations combine to form excitons that also have a huge binding energy but,at the same time,a large electron-hole distance,and we explain this seemingly contradictory finding.The anisotropy of the exciton delocalization is determined by the local anisotropy of the structure,whereas the exciton extends orthogonally to the chains formed by the crystal structure.Moreover,we show that the bright exciton goes together with a dark exciton of even larger binding energy and more pronounced anisotropy.These findings are obtained by combining first principles many-body perturbation theory calculations,ellipsometry experiments,and tight binding modelling,leading to very good agreement and a consistent picture.Our explanation is general and can be extended to other materials.