As novel photocatalysts, covalent organic frameworks (COFs) have potential for water purification. Insufficient exciton dissociation and low charge mobility in COFs yet restricted their photocatalytic activity. Excitonic dissociation and charge transfer in COFs could be optimized via regulating the donor–acceptor (D–A) interactions through adjusting the number of donor units within COFs, yet relevant research is lacking. By integrating the 1,2,4-triazole or bis-1,2,4-triazole unit with quinone, we fabricated COF-DT (with a single donor unit) and COF-DBT (with double donor units) via a facile sonochemical method and used to decontaminate emerging contaminants. Due to the stronger D–A interactions than COF-DT, the exciton binding energy was lower for COF-DBT, facilitating the intermolecular charge transfer process. The degradation kinetics of tetracycline (model contaminant) by COF-DBT (k = (12.21 ± 1.29) × 10–2 min–1) was higher than that by COF-DT (k = (5.11 ± 0.59) × 10–2 min–1) under visible-light irradiation. COF-DBT could efficiently photodegrade tetracycline under complex water chemistry conditions and four real water samples. Moreover, six other emerging contaminants, both Gram-negative and Gram-positive strains, could also be effectively eliminated by COF-DBT. High tetracycline degradation performance achieved in a continuous-flow system and in five reused cycles in both laboratory and outdoor experiments with sunlight irradiation showed the stability and the potential for the practical application of COF-DBT.
With the developing technologies of artificial intelligence and the Internet of Things, intelligent IoT (iIoT) is prevailing currently. Design and implementation of integrated IoT nodes with continuous perception capability are indispensable to realize various smart terminal devices, which would also be vital to reduce the power consumption, improve the real-time performance, and enhance the security/privacy of the IoT system. In this paper, we present the architecture of “Sensing with Computing” and its chip design for smart sensing applications, which would support multi-modal perception signal processing with multi-dimension extension ability. Specially, we explore the analog/mixed-signal circuit designs and algorithm-hardware co-design methodologies for perception signal processing, and we also study the multi-modal integration of novel sensors and their interface technologies. Additionally, some multi-modal smart sensing systems with “Sensing + Computing in Memory” mixed-signal chips would be fabricated, which would support typical always-on smart sensing tasks.
Halogenated pharmaceuticals exhibit high toxicity if released to natural environment, and dehalogenation is a key process for their degradation. In this study, a reductive and directional dehalogenation technique, heterogenous formic acid (HCOOH) catalytic activation system, was proposed for diclofenac (DCF) dechlorination and detoxification. A functional material of Pd nanocluster decorated graphitic carbon nitride (Pd/g-C3N4) was developed for HCOOH activation. Although the optimized material (Pd1/g-C3N4) showed lower HCOOH decomposition rate (k1 = 0.287 ± 0.017 min−1) than the pristine Pd particles (k1 = 0.401 ± 0.031 min−1), it processed higher DCF degradation efficiency (97.9% within 30 min) than Pd particles. The enhancement mechanism was revealed by both experiments and theoretical calculations. Firstly, the six-fold cavities of g-C3N4 acted as anchor sites, which offered strong coordination environment for Pd nanoclusters. Secondly, the strong coordination environment of Pd led to upshifted d-band center of Pd 4d with enhanced bonding state, and then promoted HCOOH adsorption on Pd/g-C3N4, thus facilitating HCOOH decomposition through formate pathway rather than carboxyl pathway. Thirdly, Pd/g-C3N4 ensured HCOOH selectively decomposed as dehydrogenation reaction, which generated more H* (adsorbed H on Pd) than the dehydration reaction. The H* was proved to be the dominant reductive species for DCF hydrodechlorination. Moreover, the toxicities of DCF dechlorination products were greatly reduced.
Events are not isolated but rather linked to one another in various dimensions. In language processing, various sources of information—including real-world knowledge, (representations of) current linguistic input and non-linguistic visual context—help establish causal connections between events. In this review, we discuss causal inference in relation to events and event knowledge as one aspect of world knowledge, and their representations in language comprehension. To evaluate the mechanism and time course of causal inference, we gather insights from studies on (1) implicit causality/consequentiality as a specific form of causal inference regarding the protagonists of cause/consequence events, and (2) the processing of causal relations. We highlight the importance of methodology in measuring causal inference, compare the results from different research methods, and emphasize the contribution of the visual-world paradigm to achieve a better understanding of causal inference. We recommend that further investigations of causal inference consider temporally sensitive measures and more detailed contexts.
A series of C-doped Bi3O4X (X = Cl, Br, I) photocatalysts with layer-stacked structure was synthesized using glucose as carbon source, and the carbon doping and halogen species on harvesting broader solar spectrum and promoting charge carrier separation were systematically investigated. For pyrene photolysis, the photodegradation rate of pristine materials followed the order of Bi3O4I > Bi3O4Br > Bi3O4Cl, which was attributed to the difference in electronegativity of the halogen elements. The doped carbon boosted photocatalytic performance and the optimal C/Bi3O4I achieved 100% pyrene removal within 20 min, which primarily benefited from the dramatic improvement of the internal electric field (IEF). The improved IEF further increased the separation and transfer efficiency of photogenerated charge carriers. XRD and XPS characterizations confirmed that the doped carbon implanted into the lattice of [X] layers, and mainly affected the X np states. The X np orbitals contributed to the valence band (VB) of Bi3O4X, thus the local occupied states induced by doped carbon formed above VB and significantly decreased the VB potential. Meanwhile, the doped carbon narrowed the band gap and greatly improved visible light utilization. The O2−, h+ and OH were identified as dominant active species for pyrene degradation, and the generation rate of O2− and OH was further measured by the probe technique. Moreover, the photodegradation pathways of pyrene were proposed and the ecotoxicity of intermediates was assessed. This study reveals the effect of halogen species on photocatalytic activity and provides guidance for enhancing IEF by doping inorganic element.
A novel carbon quantum dots decorated C-doped α-Bi2O3 photocatalyst (CBO/CQDs) was synthesized by solvothermal method. The synergistic effect of adsorption and photocatalysis highly improved contaminants removal efficiencies. The ceftriaxone sodium degradation rate constant (k) of CBO/CQDs was 11.4 and 3.2 times that of pure α-Bi2O3 and C-doped α-Bi2O3, respectively. The interstitial carbon doping generated localized states above the valence band, which enhanced the utilization of visible light and facilitated the separation of photogenerated electrons and holes; the loading of CQDs improved the charge carrier separation and extended the visible light response; the reduced particle size of CBO/CQDs accelerated the migration of photogenerated carriers. The •O2− and h+ were identified as the dominant reactive species in ceftriaxone sodium degradation, and the key role of •O2− was further investigated by NBT transformation experiments. The Fukui index was applied to ascertain the molecular bonds of ceftriaxone sodium susceptible to radical attack, and intermediates analysis was conducted to explore the possible degradation pathways. The toxicity evaluation revealed that some degradation intermediates possessed high toxicity, thus the contaminants require sufficient mineralization to ensure safe discharge. The present study makes new insights into synchronous carbon dopping and CQDs decoration on modification of α-Bi2O3, which provides references for future studies.
Numerical resolution for 6-D Wigner dynamics under the Coulomb potential is faced with the combined challenges of high dimensionality, nonlocality, oscillation, and singularity. In particular, the extremely huge memory storage of 6-D grids hinders the usage of all existing deterministic numerical schemes, which is well known as the curse of dimensionality. To surmount these difficulties, we propose a massively parallel solver, termed the characteristic-spectral-mixed (CHASM) scheme, by fully exploiting two distinct features of the Wigner equation: locality of spatial advection and nonlocality of quantum interaction. Our scheme utilizes the local cubic B-spline basis to interpolate the local spatial advection. The key is to use a perfectly matched boundary condition to give a closure of spline coefficients, so that distributed pieces can recover the global one as accurately as possible owing to the rapid decay of wavelet basis in the dual space, and communication costs are significantly reduced. To resolve the nonlocal pseudodifferential operator with a singular symbol, CHASM further adopts the truncated kernel method to attain a highly efficient approximation. Several typical experiments including the quantum harmonic oscillator and the 1s state of hydrogen demonstrate the accuracy and efficiency of CHASM. Nonequilibrium electron-proton couplings are also clearly displayed and illuminate the uncertainty principle and quantum tunneling in phase space. Finally, the scalability of CHASM up to 16000 cores is presented.
Abstract Forests provide a huge carbon pool, a substantial portion of which is stored in above-ground biomass (AGB). Deciduous broadleaf forests in China are an essential component of global deciduous broadleaf forests, yet the impacts of climate and forest attributes on their AGB are not well understood. Using a comprehensive forest inventory database from 772 plots distributed across temperate and subtropical deciduous broadleaf forests in China (23.51°?42.53°N and 104.24°?128.27°E), we applied variance partitioning analysis, model selection analysis and structural equation models to explore how climate and forest attributes (species diversity, community-level functional traits and stand structures) affect AGB in different climatic forests (semi-arid forests, semi-humid forests and humid forests). Community-level functional traits and stand structures together explained a great portion of the variance in AGB. The effect of community-level functional traits was greater than that of stand structures in semi-arid forests and semi-humid forests, but smaller in humid forests. Further analyses showed that community-level maximum tree height, stem density and tree size inequality were important explanatory variables. Although climate and species diversity had minor effects, the direct positive effect of mean annual precipitation (MAP) was still important, especially in semi-arid forests. Synthesis. Community-level functional traits but not species diversity were key drivers of AGB, indicating that tree species diversity loss may not impair AGB substantially in deciduous broadleaf forests in China. Moreover, stand structures also had strong effects on AGB in both semi-arid forests and humid forests, highlighting the importance of structural complexity. In addition, MAP had a direct positive effect on AGB in semi-arid forests and semi-humid forests, and a future increase in drought might potentially reduce carbon storage in these forests.
Global climate change has led to the decline of species and functional diversity in ecosystems, changing community composition and ecosystem functions. However, we still know little about how species with different resource-use strategies (different types of resource usage and plant growth of plants as indicated by the spectrum of plant economic traits, including acquisitive resource-use strategy and conservative resource-use strategy) would change in response to climate change, and how the changes in the diversity of species with different resource-use strategies may influence community-level productivity. Here, using long-term (1982–2017) observatory data in a temperate grassland in Inner Mongolia, we investigated how climate change had affected the species richness (SR) and functional richness (FRic) for the whole community and for species with different resource-use strategies. Specifically, based on data for four traits representing leaf economics spectrum (leaf carbon concentration, leaf nitrogen concentration, leaf phosphorus concentration, and specific leaf area), we divided 81 plant species appearing in the grassland community into three plant functional types representing resource-acquisitive, medium, and resource-conservative species. We then analyzed the changes in community-level productivity in response to the decline of SR and FRic at the community level and for different resource-use strategies. We found that community-level SR and FRic decreased with drying climate, which was largely driven by the decline of diversity for resource-acquisitive species. However, community-level productivity remained stable because resource-conservative species dominating this grassland were barely affected by climate change. Our study revealed distinctive responses of species with different resource-use strategies to climate change and provided a new approach based on species functional traits for predicting the magnitude and direction of climate change effects on ecosystem functions.
Flowering phenology of plants, which is important for reproductive growth, has been shown to be influenced by climate change. Understanding how flowering phenology responds to climate change and exploring the variation of this response across plant groups can help predict structural and functional changes in plant communities in response to ongoing climate change. Here, we used long-term collections of 33 flowering plant species from the Gongga Mountains (Mt. Gongga hereafter), a biodiversity hotspot, to investigate how plant flowering phenology changed over the past 70 years in response to climate change. We found that mean flowering times in Mt. Gongga were delayed in all vegetation types and elevations over the last 70 years. Furthermore, flowering time was delayed more in lowlands than at high elevations. Interestingly, we observed that spring-flowering plants show earlier flowering times whereas summer/autumn plants show delayed flowering times. Non-synchronous flowering phenology across species was mainly driven by changes in temperature and precipitation. We also found that the flowering phenology of 78.8% plant species was delayed in response to warming temperatures. Our findings also indicate that the magnitude and direction of variation in plant flowering times vary significantly among species along elevation gradients. Shifts in flowering time might cause trophic mismatches with co-occurring and related species, affecting both forest ecosystem structure and function.
The commercialization of academic patents is a basic means for universities to promote economic growth and upgrade the industrial innovation of enterprises. However, among developing countries, the commercialization rate of university patents is generally low. This study utilizes data from 65 universities which are directly under the Ministry of Education of China to analyze the influencing factors and mechanisms of academic patent commercialization. The findings show that the proportion of associate professors, the size of service staff transforming research and development achievement, and the proportion of basic research funding in universities are positively correlated with the commercialization rate of university patents. In addition, these factors indirectly affect the commercialization of university patents by affecting neighboring universities; that is, there are spatial spillover effects in the commercialization of university patents between neighboring universities. These empirical results indicate that universities can promote the commercialization of university patents by optimizing the structure of faculty, developing the R&D achievement transformation service staff team, and strengthening investment in basic research.
Because of land privatisation and marketisation in rural areas, community-based adaptation to climate change may face new challenges. A field survey conducted on the Qinghai–Tibetan Plateau (QTP) shows that herders with a grassland collective management system (CMS) suffer higher livestock mortality than those with an individual management system (IMS) during the same extreme climatic events, in contrast to previous research findings. This study seeks to explain this contrast. The results show that although local herders have begun to rely on market-related adaptation strategies to cope with climate change, IMS herders are more inclined to rent-in grassland, while CMS herders are more inclined to purchase fodder. The high-cost grassland renting-in strategy reduces livestock mortality and total household economic loss more effectively than purchasing fodder during snow disasters. An important reason for this is that IMS strengthens market concepts and promotes interaction between herders and external markets, especially the grassland rental market, while CMS continues past grazing traditions and maintains traditional social relationships and collective concepts within the community. CMS herders fail to rent-in grassland due to psychological free-riding incentives and scale mismatch. In the face of repeated climatic disasters, however, CMS herders have also begun to overcome various obstacles to entering the grassland rental market through self-organization and are gradually forming a new pathway of adaptation to climate change.
The poor colloidal stability of magnetite nanoparticles (MNPs) limits their mobility and application, so various organic coatings (OCs) were applied to MNPs. Here, a comparative study on the colloidal stability of MNPs coated with acetic (HAc) and polyacrylic acids (PAA) was conducted under varied pH (5.0–9.0) in the presence of different concentrations of cations and anions, as well as humic acid (HA). Comparing the effects of various cations and anions, the stability of both HAc/PAA-MNPs followed the order: Na+ > Ca2+and PO43− > SO42− > Cl−, which could be explained by their adsorption behaviors onto HAc/PAA-MNPs and the resulting surface charge changes. Under all conditions even with more anion adsorption onto HAc-MNPs (0.14–22.56 mg/g) than onto PAA-MNPs (0.04–18.34 mg/g), PAA-MNPs were more negatively charged than HAc-MNPs, as PAA has a lower pHIEP (2.6 ± 0.1) than that of HAc (3.7 ± 0.1). Neither the HAc nor PAA coatings were displaced by phosphate even at considerably high phosphate concentration. Compared with HAc-MNPs, the stability of PAA-MNPs was greatly improved under all studied conditions, which could be due to both stronger electrostatic and additional steric repulsion forces among PAA-MNPs. Besides, under all conditions, Derjaguin-Landau-Verwey-Overbeek (DLVO) explained well the aggregation kinetic of HAc-MNPs; while extended DLVO (EDLVO) successfully predict that of PAA-MNPs, indicating steric forces among PAA-MNPs. The aggregation of HAc/PAA-MNPs was all inhibited in varied electrolyte solutions by HA (2 mg C/L) addition. This study suggested that carboxyl coatings with higher molecular weights and pKa values could stabilize MNPs better due to stronger electrostatic and additional steric repulsion. However, in the presence of HA, these two forces were mainly controlled by adsorbed HA instead of the organic pre-coatings on MNPs.
A compilation of new advances made in the research field of laboratory reaction kinetics in China's Key Development Project for Air Pollution Formation Mechanism and Control Technologies was presented. These advances are grouped into six broad, interrelated categories, including volatile organic compound (VOC) oxidation, secondary organic aerosol (SOA) formation, new particle formation (NPF) and gas-particle partitioning, ozone chemistry, model parameters, and secondary inorganic aerosol (SIA) formation, highlighting the laboratory work done by Chinese researchers. For smog chamber applications, the current knowledge gained from laboratory studies is reviewed, with emphasis on summarizing the oxidation mechanisms of long-chain alkanes, aromatics, alkenes, aldehydes/ketones in the atmosphere, SOA formation from anthropogenic emission sources, and oxidation of aromatics, isoprene, and limonene, as well as SIA formation. For flow tube applications, atmospheric oxidation mechanisms of toluene and methacrolein, SOA formation from limonene oxidation by ozone, gas-particle partitioning of peroxides, and sulfuric acid-water (H2SO4-H2O) binary nucleation, methanesulfonic acid-water (MSA-H2O) binary nucleation, and sulfuric acid-ammonia-water (H2SO4-NH3-H2O) ternary nucleation are discussed.