资源环境科技发展态势分析平台

Enhanced silicate rock weathering (ERW), deployable with croplands, has potential use for atmospheric carbon dioxide (CO2) removal (CDR), which is now necessary to mitigate anthropogenic climate change(1). ERW also has possible co-benefits for improved food and soil security, and reduced ocean acidification(2-4). Here we use an integrated performance modelling approach to make an initial techno-economic assessment for 2050, quantifying how CDR potential and costs vary among nations in relation to business-as-usual energy policies and policies consistent with limiting future warming to 2 degrees Celsius(5). China, India, the USA and Brazil have great potential to help achieve average global CDR goals of 0.5 to 2gigatonnes of carbon dioxide (CO2) per year with extraction costs of approximately US$80-180 per tonne of CO2. These goals and costs are robust, regardless of future energy policies. Deployment within existing croplands offers opportunities to align agriculture and climate policy. However, success will depend upon overcoming political and social inertia to develop regulatory and incentive frameworks. We discuss the challenges and opportunities of ERW deployment, including the potential for excess industrial silicate materials (basalt mine overburden, concrete, and iron and steel slag) to obviate the need for new mining, as well as uncertainties in soil weathering rates and land-ocean transfer of weathered products.

Transparent piezoelectrics are highly desirable for numerous hybrid ultrasound-optical devices ranging from photoacoustic imaging transducers to transparent actuators for haptic applications(1-7). However, it is challenging to achieve high piezoelectricity and perfect transparency simultaneously because most high-performance piezoelectrics are ferroelectrics that contain high-density light-scattering domain walls. Here, through a combination of phase-field simulations and experiments, we demonstrate a relatively simple method of using an alternating-current electric field to engineer the domain structures of originally opaque rhombohedral Pb(Mg1/3Nb2/3)O-3-PbTiO3 (PMN-PT) crystals to simultaneously generate near-perfect transparency, an ultrahigh piezoelectric coefficient d(33) (greater than 2,100 picocoulombs per newton), an excellent electromechanical coupling factor k(33) (about 94 per cent) and a large electro-optical coefficient gamma(33) (approximately 220 picometres per volt), which is far beyond the performance of the commonly used transparent ferroelectric crystal LiNbO3. We find that increasing the domain size leads to a higher d(33) value for the [001]-oriented rhombohedral PMN-PT crystals, challenging the conventional wisdom that decreasing the domain size always results in higher piezoelectricity(8-10). This work presents a paradigm for achieving high transparency and piezoelectricity by ferroelectric domain engineering, and we expect the transparent ferroelectric crystals reported here to provide a route to a wide range of hybrid device applications, such as medical imaging, self-energy-harvesting touch screens and invisible robotic devices.

Applying a bias correction to a state-of-the-art dataset covering non-alpine regions of the Northern Hemisphere and to three other datasets yields a more constrained quantification of snow mass in March from 1980 to 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.