资源环境科技发展态势分析平台

Fine-scale satellite data are used to quantify forest harvest rates in 26 European countries, finding an increase in harvested forest area of 49% and an increase in biomass loss of 69% between 2011-2015 and 2016-2018.

The rapid increase in global energy demand and the need to replace carbon dioxide (CO2)-emitting fossil fuels with renewable sources have driven interest in chemical storage of intermittent solar and wind energy(1,2). Particularly attractive is the electrochemical reduction of CO2 to chemical feedstocks, which uses both CO2 and renewable energy(3-8). Copper has been the predominant electrocatalyst for this reaction when aiming for more valuable multi-carbon products(9-16), and process improvements have been particularly notable when targeting ethylene. However, the energy efficiency and productivity (current density) achieved so far still fall below the values required to produce ethylene at cost-competitive prices. Here we describe Cu-Al electrocatalysts, identified using density functional theory calculations in combination with active machine learning, that efficiently reduce CO2 to ethylene with the highest Faradaic efficiency reported so far. This Faradaic efficiency of over 80 per cent (compared to about 66 per cent for pure Cu) is achieved at a current density of 400 milliamperes per square centimetre (at 1.5 volts versus a reversible hydrogen electrode) and a cathodic-side (half-cell) ethylene power conversion efficiency of 55 +/- 2 per cent at 150 milliamperes per square centimetre. We perform computational studies that suggest that the Cu-Al alloys provide multiple sites and surface orientations with near-optimal CO binding for both efficient and selective CO2 reduction(17). Furthermore, in situ X-ray absorption measurements reveal that Cu and Al enable a favourable Cu coordination environment that enhances C-C dimerization. These findings illustrate the value of computation and machine learning in guiding the experimental exploration of multi-metallic systems that go beyond the limitations of conventional single-metal electrocatalysts.

Oppositely charged colloidal particles are assembled in water through an approach that allows electrostatic interactions to be precisely tuned to generate macroscopic single crystals.

From rock salt to nanoparticle superlattices, complex structure can emerge from simple building blocks that attract each other through Coulombic forces(1-4). On the micrometre scale, however, colloids in water defy the intuitively simple idea of forming crystals from oppositely charged partners, instead forming non-equilibrium structures such as clusters and gels(5-7). Although various systems have been engineered to grow binary crystals(8-11), native surface charge in aqueous conditions has not been used to assemble crystalline materials. Here we form ionic colloidal crystals in water through an approach that we refer to as polymer-attenuated Coulombic self-assembly. The key to crystallization is the use of a neutral polymer to keep particles separated by well defined distances, allowing us to tune the attractive overlap of electrical double layers, directing particles to disperse, crystallize or become permanently fixed on demand. The nucleation and growth of macroscopic single crystals is demonstrated by using the Debye screening length to fine-tune assembly. Using a variety of colloidal particles and commercial polymers, ionic colloidal crystals isostructural to caesium chloride, sodium chloride, aluminium diboride and K4C60 are selected according to particle size ratios. Once fixed by simply diluting out solution salts, crystals are pulled out of the water for further manipulation, demonstrating an accurate translation from solution-phase assembly to dried solid structures. In contrast to other assembly approaches, in which particles must be carefully engineered to encode binding information(12-18), polymer-attenuated Coulombic self-assembly enables conventional colloids to be used as model colloidal ions, primed for crystallization.