The intraflagellar transport cycle
Related Articles
Demand-side strategies enable rapid and deep cuts in buildings and transport emissions to 2050
Decarbonization of energy-using sectors is essential for tackling climate change. We use an ensemble of global integrated assessment models to assess CO2 emissions reduction potentials in buildings and transport, accounting for system interactions. We focus on three intervention strategies with distinct emphases: reducing or changing activity, improving technological efficiency and electrifying energy end use. We find that these strategies can reduce emissions by 51–85% in buildings and 37–91% in transport by 2050 relative to a current policies scenario (ranges indicate model variability). Electrification has the largest potential for direct emissions reductions in both sectors. Interactions between the policies and measures that comprise the three strategies have a modest overall effect on mitigation potentials. However, combining different strategies is strongly beneficial from an energy system perspective as lower electricity demand reduces the need for costly supply-side investments and infrastructure.
Solution-processable 2D materials for monolithic 3D memory-sensing-computing platforms: opportunities and challenges
Solution-processable 2D materials (2DMs) are gaining attention for applications in logic, memory, and sensing devices. This review surveys recent advancements in memristors, transistors, and sensors using 2DMs, focusing on their charge transport mechanisms and integration into silicon CMOS platforms. We highlight key challenges posed by the material’s nanosheet morphology and defect dynamics and discuss future potential for monolithic 3D integration with CMOS technology.
Solution-processable polymer membranes with hydrophilic subnanometre pores for sustainable lithium extraction
Membrane-based separation processes hold great promise for sustainable extraction of lithium from brines for the rapidly expanding electric vehicle industry and renewable energy storage. However, it remains challenging to develop high-selectivity membranes that can be upscaled for industrial processes. Here we report solution-processable polymer membranes with subnanometre pores with excellent ion separation selectivity in electrodialysis processes for lithium extraction. Polymers of intrinsic microporosity incorporated with hydrophilic functional groups enable fast transport of monovalent alkali cations (Li+, Na+ and K+) while rejecting relatively larger divalent ions such as Mg2+. The polymer of intrinsic microporosity membranes surpasses the performance of most existing membrane materials. Furthermore, the membranes were scaled up and integrated into an electrodialysis stack, demonstrating excellent selectivity in simulated salt-lake brines. This work will inspire the development of selective membranes for a wide range of sustainable separation processes critical for resource recovery and a global circular economy.
Effect of hydrogen leakage on the life cycle climate impacts of hydrogen supply chains
Hydrogen is of interest for decarbonizing hard-to-abate sectors because it does not produce carbon dioxide when combusted. However, hydrogen has indirect warming effects. Here we conducted a life cycle assessment of electrolysis and steam methane reforming to assess their emissions while considering hydrogen’s indirect warming effects. We find that the primary factors influencing life cycle climate impacts are the production method and related feedstock emissions rather than the hydrogen leakage and indirect warming potential. A comparison between fossil fuel-based and hydrogen-based steel production and heavy-duty transportation showed a reduction in emissions of 800 to more than 1400 kg carbon dioxide equivalent per tonne of steel and 0.1 to 0.17 kg carbon dioxide equivalent per tonne-km of cargo. While any hydrogen production pathway reduces greenhouse gas emissions for steel, this is not the case for heavy-duty transportation. Therefore, we recommend a sector-specific approach in prioritizing application areas for hydrogen.
Prediction of thermal conductivity in CALF-20 with first-principles accuracy via machine learning interatomic potentials
Understanding the thermal transport properties of CALF-20, a recent addition to the metal-organic framework family, is crucial for its effective utilization in greenhouse gas capture. Here, we report the thermal transport study of CALF-20 using artificial neural network-based machine learning potentials. We use the Green-Kubo approach based on equilibrium molecular dynamics, with a heat-flux renormalization technique, to determine the thermal conductivity (κ) of CALF-20. We predict that the anisotropic thermal transport in CALF-20, with κ below 1 Wm−1K−1 at 300 K, is ideal for thermoelectric applications. Our analysis reveals a weak temperature dependence (κ ~ 1/T0.56) and near invariance with pressure in κ value of CALF-20, which stands out from the typical trend observed in crystalline materials. The outcome of the study, leveraging advanced computational techniques for predictive modeling, offers valuable insights into more suitable applications of CALF-20 with tailored thermal properties.
Responses