Fundamental Research最新文献

Single-walled carbon nanotubes (SWCNTs) present excellent electronic and mechanical properties desired in wearable and flexible devices. The preparation of SWCNT films is the first step for fabricating various devices. This work developed a scalable and feasible method to assemble SWCNT thin films on water surfaces based on Marangoni flow induced by surface tension gradient. The films possess a large area of 40 cm × 30 cm (extensible), a tunable thickness of 15∼150 nm, a high transparency of up to 96%, and a decent conductivity. They are ready to be directly transferred to various substrates, including flexible ones. Flexible strain sensors were fabricated with the films on flexible substrates. These sensors worked with high sensitivity and repeatability. By realizing multi-functional human motion sensing, including responding to voices, monitoring artery pulses, and detecting knuckle and muscle actions, the assembled SWCNT films demonstrated the potential for application in smart devices.

The European Commission has proposed a Carbon Border Adjustment Mechanism (CBAM) to reduce carbon leakage and create a level playing field for its domestic products and imported goods. Nevertheless, the effectiveness of the proposal remains unclear, especially when it triggers threats of retaliation from trading partners of the European Union. We apply a Computable General Equilibrium model - Global Trade Analysis Project - to assess the economic and environmental impacts of different CBAM schemes. Here we show that the effectiveness of the CBAM to address carbon leakage risks is rather limited, and the CBAM raises concerns over global welfare costs, Correct to Gross Domestic Product (GDP) losses, and violation of equality principles. Trade retaliation leads to multiplied welfare losses, which would mostly be borne by poor countries. Our results question the carbon leakage reduction effect of a unilateral trade policy and suggest that climate change mitigation still needs to be performed within the framework of international cooperation.

In the global challenge of Coronavirus disease 2019 (COVID-19) pandemic, accurate prediction of daily new cases is crucial for epidemic prevention and socioeconomic planning. In contrast to traditional local, one-dimensional time-series data-based infection models, the study introduces an innovative approach by formulating the short-term prediction problem of new cases in a region as multidimensional, gridded time series for both input and prediction targets. A spatial-temporal depth prediction model for COVID-19 (ConvLSTM) is presented, and further ConvLSTM by integrating historical meteorological factors (Meteor-ConvLSTM) is refined, considering the influence of meteorological factors on the propagation of COVID-19. The correlation between 10 meteorological factors and the dynamic progression of COVID-19 was evaluated, employing spatial analysis techniques (spatial autocorrelation analysis, trend surface analysis, etc.) to describe the spatial and temporal characteristics of the epidemic. Leveraging the original ConvLSTM, an artificial neural network layer is introduced to learn how meteorological factors impact the infection spread, providing a 5-day forecast at a 0.01° × 0.01° pixel resolution. Simulation results using real dataset from the 3.15 outbreak in Shanghai demonstrate the efficacy of Meteor-ConvLSTM, with reduced RMSE of 0.110 and increased R² of 0.125 (original ConvLSTM: RMSE = 0.702, R² = 0.567; Meteor-ConvLSTM: RMSE = 0.592, R² = 0.692), showcasing its utility for investigating the epidemiological characteristics, transmission dynamics, and epidemic development.

The pursuit of compact and integrated devices has stimulated a growing demand for multifunctional sensors with rapid and accurate responses to various physical parameters, either separately or simultaneously. Fluorescent fiber sensors have the advantages of robust stability, light weight, and compact geometry, enabling real-time and noninvasive signal detection by monitoring the fluorescence parameters. Despite substantial progress in fluorescence sensors, achieving multifunctional sensing in a single optical fiber remains challenging. To solve this problem, in this study, we present a bottom-up strategy to design and fabricate thermally drawn multifunctional fiber sensors by incorporating functional nanocrystals with temperature and pressure fluorescence responses into a transparent glass matrix. To generate the desired nanocrystal-in-glass composite (NGC) fiber, the fluorescent activators, incorporated nanocrystals, glassy core materials, and cladding matrix are rationally designed. Utilizing the fluorescence intensity ratio technique, a self-calibrated fiber sensor is demonstrated, with a bi-functional response to temperature and pressure. For temperature sensing, the NGC fiber exhibits temperature-dependent near-infrared emission at temperatures up to 573 K with a maximum absolute sensitivity of 0.019 K⁻¹. A pressure-dependent upconversion emission is also realized in the visible spectral region, with a linear slope of -0.065. The successful demonstration of multifunctional NGC fiber sensors provides an efficient pathway for new paradigms of multifunctional sensors as well as a versatile strategy for future hybrid fibers with novel combinations of magnetic, optical, and mechanical properties.

Corona virus disease 2019 (COVID-19) has exerted a profound adverse impact on human health. Studies have demonstrated that aerosol transmission is one of the major transmission routes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Pathogenic microorganisms such as SARS-CoV-2 can survive in the air and cause widespread infection among people. Early monitoring of pathogenic microorganism transmission in the atmosphere and accurate epidemic prediction are the frontier guarantee for preventing large-scale epidemic outbreaks. Monitoring of pathogenic microorganisms in the air, especially in densely populated areas, may raise the possibility to detect viruses before people are widely infected and contain the epidemic at an earlier stage. The multi-scale coupled accurate epidemic prediction system can provide support for governments to analyze the epidemic situation, allocate health resources, and formulate epidemic response policies. This review first elaborates on the effects of the atmospheric environment on pathogenic microorganism transmission, which lays a theoretical foundation for the monitoring and prediction of epidemic development. Secondly, the monitoring technique development and the necessity of monitoring pathogenic microorganisms in the atmosphere are summarized and emphasized. Subsequently, this review introduces the major epidemic prediction methods and highlights the significance to realize a multi-scale coupled epidemic prediction system by strengthening the multidisciplinary cooperation of epidemiology, atmospheric sciences, environmental sciences, sociology, demography, etc. By summarizing the achievements and challenges in monitoring and prediction of pathogenic microorganism transmission in the atmosphere, this review proposes suggestions for epidemic response, namely, the establishment of an integrated monitoring and prediction platform for pathogenic microorganism transmission in the atmosphere.

The environmental stability of infectious viruses in the laboratory setting is crucial to the transmission potential of human respiratory viruses. Different experimental techniques or conditions used in studies over the past decades have led to diverse understandings and predictions for the stability of viral infectivity in the atmospheric environment. In this paper, we review the current knowledge on the effect of simulated atmospheric conditions on the infectivity of respiratory viruses, mainly focusing on influenza viruses and coronaviruses, including severe acute respiratory syndrome coronavirus 2 and Middle East respiratory syndrome coronavirus. First, we summarize the impact of the experimental conditions on viral stability; these involve the methods of viral aerosol generation, storage during aging and collection, the virus types and strains, the suspension matrixes, the initial inoculum volumes and concentrations, and the drying process. Second, we summarize and discuss the detection methods of viral infectivity and their disadvantages. Finally, we integrate the results from the reviewed studies to obtain an overall understanding of the effects of atmospheric environmental conditions on the decay of infectious viruses, especially aerosolized viruses. Overall, this review highlights the knowledge gaps in predicting the ability of viruses to maintain infectivity during airborne transmission.