Radiative cooling is a passive cooling technology that offers great promises to reduce space cooling cost, combat the urban island effect, and alleviate the global warming. To achieve passive daytime ...radiative cooling, current state-of-the-art solutions often utilize complicated multilayer structures or a reflective metal layer, limiting their applications in many fields. Attempts have been made to achieve passive daytime radiative cooling with single-layer paints, but they often require a thick coating or show partial daytime cooling. In this work, we experimentally demonstrate remarkable full-daytime subambient cooling performance with both BaSO4 nanoparticle films and BaSO4 nanocomposite paints. BaSO4 has a high electron band gap for low solar absorptance and phonon resonance at 9 μm for high sky window emissivity. With an appropriate particle size and a broad particle size distribution, the BaSO4 nanoparticle film reaches an ultrahigh solar reflectance of 97.6% and a high sky window emissivity of 0.96. During field tests, the BaSO4 film stays more than 4.5 °C below ambient temperature or achieves an average cooling power of 117 W/m2. The BaSO4-acrylic paint is developed with a 60% volume concentration to enhance the reliability in outdoor applications, achieving a solar reflectance of 98.1% and a sky window emissivity of 0.95. Field tests indicate similar cooling performance to the BaSO4 films. Overall, our BaSO4-acrylic paint shows a standard figure of merit of 0.77, which is among the highest of radiative cooling solutions while providing great reliability, convenient paint form, ease of use, and compatibility with the commercial paint fabrication process.
The outbreak of the COVID-19 pandemic shows the increasing importance of determining the factors of the public perceptions of personal and societal risks. These perceptions can shape people's ...behaviors, which, in turn, alter the spread of a pandemic on the community level. However, previous research on risk communication was inconsistent, and little is known about the impact of timely warning messages on stakeholders' perceptions of public health emergencies. To address this theoretical gap, this study analyzes the survey data (N = 538) from Singapore to explore the main effect of information timeliness on the respondents' stakeholder perceptions. This effect is moderated by normative factors, including attention and threat perceptions. We find that the more timely the government updates the risk information, the more trustworthy the stakeholders appear in respondents' opinions. Such an effect is weakened when the pre-decision attention or the threat perception interacts with the predictor independently. However, this effect on stakeholder perceptions becomes stronger if both moderators interact with the information timeliness. That is, an appropriate combination of the information released by the government can effectively enhance the image of the stakeholders during the pandemic.
The deployment of urban air mobility in built-out metropolitan regions is constrained by infrastructure opportunities, land use, and airspace zoning designations. Meanwhile, the availability and ...spatial distribution of infrastructure opportunities influence the travel demand that can be potentially captured by UAM services. The purpose of this study is to provide an initial assessment of the infrastructure opportunities of UAM in southern California with different mixes of spatial constraints, such as noise levels, school buffer zones, and airspace zones. The corresponding travel demand that can be potentially captured under each scenario is estimated with a home–workplace trip table. The results of the analyses indicate that supply-side infrastructure opportunities, such as heliports and elevated parking structures, are widely available to accommodate the regional deployment of UAM services. However, current spatial constraints can significantly limit the scope of vertiport location choices. Furthermore, the low-income population, blue-collar workers, and young people live farther away from supply-side opportunities than the general population. Moreover, this study proposes a network of UAM based on the top home-based and workplace-based stations for long-distance trips.
Over the past few decades, with the development of science and technology, the field of biomedicine has rapidly developed, especially with respect to biomedical materials. Low toxicity and good ...biocompatibility have always been key targets in the development and application of biomedical materials. As a degradable and environmentally friendly polymer, polylactic acid, also known as polylactide, is favored by researchers and has been used as a commercial material in various studies. Lactic acid, as a synthetic raw material of polylactic acid, can only be obtained by sugar fermentation. Good biocompatibility and biodegradability have led it to be approved by the U.S. Food and Drug Administration (FDA) as a biomedical material. Polylactic acid has good physical properties, and its modification can optimize its properties to a certain extent. Polylactic acid blocks and blends play significant roles in drug delivery, implants, and tissue engineering to great effect. This article describes the synthesis of polylactic acid (PLA) and its raw materials, physical properties, degradation, modification, and applications in the field of biomedicine. It aims to contribute to the important knowledge and development of PLA in biomedical applications.
Recent advances in thermally localized solar evaporation hold significant promise for vapor generation, seawater desalination, wastewater treatment, and medical sterilization. However, salt ...accumulation is one of the key bottlenecks for reliable adoption. Here, we demonstrate highly efficient (>80% solar-to-vapor conversion efficiency) and salt rejecting (20 weight % salinity) solar evaporation by engineering the fluidic flow in a wick-free confined water layer. With mechanistic modeling and experimental characterization of salt transport, we show that natural convection can be triggered in the confined water. More notably, there exists a regime enabling simultaneous thermal localization and salt rejection, i.e., natural convection significantly accelerates salt rejection while inducing negligible additional heat loss. Furthermore, we show the broad applicability by integrating this confined water layer with a recently developed contactless solar evaporator and report an improved efficiency. This work elucidates the fundamentals of salt transport and offers a low-cost strategy for high-performance solar evaporation.
Geological evidence shows that the Asian inland environment experienced enhanced aridity from the Early to the Late Eocene. This enhanced Eocene aridity in the Asian inland was related to combined ...impacts from global cooling, topographic uplift and land–sea reorganization. However, the primary cause of the enhanced Eocene aridity in this region is still under debate and varies between global cooling and early Tibetan Plateau uplift. To distinguish between the importance of these factors, we evaluate the climatic impacts of these factors from a modeling point of view. Consistent with geological evidence, our simulations support the observed enhanced Eocene aridity in the Asian inland. Both global cooling (induced by atmospheric CO2 decrease) and topographic uplift contributed to intensified Asian inland aridity, while land–sea redistribution did not. The uplift of the central Tibetan Plateau during the early stage of the India–Asia collision is emphasized more to be responsible for the long-term Asian inland aridification during the Eocene, playing at least an equally important role as the global cooling induced by decrease in atmospheric CO2.
•Climate simulations support the observed enhanced Eocene aridity in the Asian inland.•Both the early uplift of Tibetan Plateau and the global cooling played important roles in the enhanced aridity.•The early uplift of Tibetan Plateau contributed to the long-term Asian inland aridification during the Eocene.
•The scattering and absorption properties are studies as a function of nanoparticle size.•At a given concentration, hierarchical nanoparticle sizes enhance solar reflection.•The findings can ...significantly improve radiative cooling and cut the cost.
A key requirement for achieving passive radiative cooling for an ideal emitter, in the sky window (8–13 µm), during daytime is a total solar reflection >85%, and every 1% above this threshold results in ∼10 W/m2 gain in cooling power. One promising, inexpensive, and scalable solution for achieving high total solar reflectance is a dielectric nanoparticle-polymer composite coating. Past works have widely used a single particle size. However, it is challenging to achieve solar reflectance significantly above 85%. Here, recognizing the broadband nature of the solar irradiation, we propose and test a new concept of enhancing solar reflection at a given particle volume concentration by using hierarchical particle sizes, which we hypothesize to scatter each band of the solar spectrum i.e. VIS, NIR, and UV effectively. The hypothesis is tested using a TiO2 nanoparticle-acrylic system. Using the Mie Theory, the scattering and absorption efficiencies and asymmetric parameter of nanoparticles with different sizes and combinations are calculated, then the Monte Carlo Method is used to solve the Radiative Transfer Equation. When validating our computational model to in-house experimental results it is found that a nanoparticle size distribution of d = 104 ± 37 nm creates an overall better fit to the experimental data and increases the total solar reflection when compared to the single size model of d = 104 nm. We then purposely design hierarchical combinations of particle sizes in the broader range of 50 nm to 800 nm, and we have achieved an overall total solar reflection of ≈91%, which is higher than the ≈78% and ≈88% for 100 nm and 400 nm single particle sizes, respectively. The results confirm our hypothesis that hierarchical particle sizes can scatter over a broad spectrum more effectively rather than any single particle size. Moreover, our findings could also cut the manufacturing cost since no precise control of particle size is necessary.
•Early-age interaction between the GO and cement hydrates was revealed.•Ca2+ cations can be captured by the GO at the very beginning of mixing.•GO accelerates the cement dissolution into aqueous ...solution.•GO can restrict the drying shrinkage by densifying matrix and self-curing effect.
The remarkable properties of graphene oxide (GO) make it as an ideal candidate for developing high performance cementitious composites. In this study, it is the first time to investigate the early-age physical adsorption and chemical interactions between the GO and cement hydrates, which have a great influence on the hydration development, microstructures and drying shrinkage of the GO modified cement paste. The experimental results indicated that the addition of GO led to the decreased fluidity of cement paste, resulting from the rapid interaction between the GO and divalent metal cations released from cement hydrates, characterized by Ultraviolet-visible spectroscopy and X-ray photoelectron spectroscopy. It was found that 0.08wt% GO improved the cement hydration rate/heat by accelerating the cement dissolution, providing nucleation site and regulating the microstructure of cement hydrates. The GO covered cement hydrates at the hydration of 10min was characterized by scanning electron microscopy. Moreover, the addition of GO restricted the 28-day drying shrinkage of cement paste due to the more compacted microstructures and self-curing effect at the early age. In conclusion, the research finding gives a thorough understanding on early-age interaction mechanism when the GO is immediately mixed with cement particles, and provides a valuable guidance to the sustainable design of GO modified cementitious materials for construction use.
•Support vector machine is employed to identify the flow patterns in packed beds.•Features of different flow patterns are extracted based on different pressure signals.•Feature extraction is ...conducted by the PDF, PSD and WES methods respectively.•Three SVM models are trained and their identification ability is compared.•Identification rate of typical flow patterns is up to 96.08%.
Rapid and accurate identification of two-phase flow patterns in porous media is of great significance to the chemical industry, petroleum and nuclear engineering, etc. Based on the different pressure signals of gas-liquid two-phase flow in a porous bed, the present work proposes an intelligent recognition method to identify the two-phase flow patterns in porous media by the technologies of feature extraction and support vector machine (SVM). The analysis techniques, including time domain (PDF), frequency domain (PSD) and time-frequency domain (Wavelet), are employed to extract and summarize the corresponding characteristics of differential pressure signals of flow patterns. The intelligent recognition models are developed to identify the two-phase flow patterns in porous media by SVM. The models are trained respectively based on the characteristics of time domain + frequency domain (TF-SVM model), time domain + wavelet (TW-SVM model) and frequency domain + wavelet (FW-SVM model). The overall identification accuracy of the optimal model (TW-SVM model) reaches 96.08%.
Abstract
Biophysical models contain a large number of parameters, while the spiking characteristics of neurons are related to a few key parameters. For thalamic neurons, relay reliability is an ...important characteristic that affects Parkinson's state. This paper proposes a method to fit key parameters of the model based on the spiking characteristics of neurons, and improves the traditional particle swarm optimization algorithm. That is, a nonlinear concave function and a Logistic chaotic mapping are combined to adjust the inertia weight of particles to avoid the particle falling into a local optimum in the search process or appearing premature convergence. In this paper, three parameters that play an important role in Parkinson's state of the thalamic cell model are selected and fitted by the improved particle swarm optimization algorithm. Using the fitted parameters to reconstruct the neuron model can predict the spiking trajectories well, which verifies the effectiveness of the fitting method. By comparing the fitting results with other particle swarm optimization algorithms, it is shown that the proposed particle swarm optimization algorithm can better avoid local optima and converge to the optimal values quickly.
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