Cu-N Synergism Regulation to Enhance Anionic Redox Reversibility and Activity of Li- and Mn-Rich Layered Oxides Cathode.

Anionic redox chemistry enables extraordinary capacity for Li- and Mn-rich layered oxides (LMROs) cathodes. Unfortunately, irreversible surface oxygen evolution evokes the pernicious phase transition, structural deterioration, and severe electrode-electrolyte interface side reaction with element dissolution, resulting in fast capacity and voltage fading of LMROs during cycling and hindering its commercialization. Herein, a redox couple strategy is proposed by utilizing copper phthalocyanine (CuPc) to address the irreversibility of anionic redox. The Cu-N synergistic effect of CuPc could not only inhibit surface oxygen evolution by reducing the peroxide ion O2 2- back to lattice oxygen O2-, but also enhance the reaction activity and reversibility of anionic redox in bulk to achieve a higher capacity and cycling stability. Moreover, the CuPc strategy suppresses the interface side reaction and induces the forming of a uniform and robust LiF-rich cathode electrolyte, interphase (CEI) to significantly eliminate transition metal dissolution. As a result, the CuPc-enhanced LMRO cathode shows superb cycling performance with a capacity retention of 95.0% after 500 long-term cycles. This study sheds light on the great effect of N-based redox couple to regulate anionic redox behavior and promote the development of high energy density and high stability LMROs cathode.

Recent Advances in Understanding of the Singlet Oxygen in Energy Storage and Conversion.

Singlet oxygen (term symbol 1Δg, hereafter 1O2), a reactive oxygen species, has recently attracted increasing interest in the field of rechargeable batteries and electrocatalysis and photocatalysis. These sustainable energy conversion and storage technologies are of vital significance to replace fossil fuels and promote carbon neutrality and finally tackle the energy crisis and climate change. Herein, the recent progresses of 1O2 for energy storage and conversion is summarized, including physical and chemical properties, formation mechanisms, detection technologies, side reactions in rechargeable batteries and corresponding inhibition strategies, and applications in electrocatalysis and photocatalysis. The formation mechanisms and inhibition strategies of 1O2 in particular aprotic lithium-oxygen (Li-O2) batteries are highlighted, and the applications of 1O2 in photocatalysis and electrocatalysis is also emphasized. Moreover, the confronting challenges and promising directions of 1O2 in energy conversion and storage systems are discussed.

Unique gap-related SERS behaviors ofp-aminothiophenol molecules absorbed on TiO2surface in periodic TiO2/Ni nanopillar arrays.

We observed a unique interpillar gap-related surface-enhanced Raman scattering (SERS) behavior ofp-aminothiophenol (PATP) molecules from periodic TiO2nanopillar arrays with three gap sizes of 191, 297 and 401 nm, which is completely different from that on Ag and Ni nanopillar arrays. Especially, the gap-size-dependent charge-transfer (CT) resonance enhancement from TiO2/Ni has been indicated through comparisons of variation trend of SERS intensities with inter-pillar gap size between TiO2/Ni and Ag/TiO2/Ni as well as Ni nanoarrays, and been confirmed by spectra of ultraviolet-visible absorption and photoluminescence. Results demonstrate that the CT resonance enhancement is more susceptible to the change of the gap size compared with the surface plasmon resonance (SPR) enhancement in TiO2/Ni nanoarrays. Hence, SPR and CT enhancement showing different variation trend and rate with the gap size that leads to a different relative contribution of CT resonance to the overall SERS enhancement as gap size changes, and consequently results in a unique gap-related SERS behavior for TiO2/Ni nanoarrays. The present study is not only helpful for investigating SERS mechanism for semiconductors but also providing a method to design and optimize periodic metal/semiconductor SERS substrates in a controllable way.

Life's Essential 8 and Risk of Stroke: A Prospective Community-Based Study.

BACKGROUND: Data are lacking regarding cardiovascular health (CVH) with Life's Essential 8 approach and future stroke risk. We sought to elucidate whether the CVH score constructed by the Life's Essential 8 metrics predicted stroke risk in 2 Chinese ongoing cohorts. METHODS: This included 41 043 participants of the Kailuan I study and 27 842 participants of the Kailuan II study who were free of cardiovascular disease or cancer in 2014. CVH score (ranged from 0 to 100) was assessed using the Life's Essential 8 metrics (body mass index, cigarette smoking, diet quality, physical activity, sleep health, lipid, blood glucose, and blood pressure). A composite of incident stroke events (ischemic stroke and hemorrhagic stroke) was identified via review of medical records. The follow-up period was calculated from the finishing date of the 2014 survey to either the date of stroke occurrence, death, loss to follow-up, or the end of follow-up (December 31, 2020). We also examined the longitudinal association between the CVH score and arterial stiffness status, as assessed by brachial-ankle pulse wave velocity, in 25 922 participants free of cardiovascular disease during the follow-up. We performed a meta-analysis to assess the association between CVH, based on the 2010 American Heart Association recommendation, and stroke integrating the results of current study and previous studies. RESULTS: During a median follow-up of 5.65 years (interquartile range, 5.20-6.09), a total of 1750 incident stroke events were identified in the pooled Kailuan study. The pooled hazard ratios were 0.33 (95% CI, 0.20-0.54) for ideal versus poor health category of CVH (Ptrend<0.0001). Higher CVH scores were also associated with lower brachial-ankle pulse wave velocity values at baseline and slower increments of brachial-ankle pulse wave velocity during follow-up (Ptrend≤0.001 for both). Arterial stiffness mediated 9.07% (95% CI, 5.83%-15.0%) of the total association between CVH and incident stroke. The pooled hazard ratio comparing 2 extreme CVH categories for stroke was 0.45 (95% CI, 0.35-0.59) when including 10 published studies and the current study. CONCLUSIONS: The CVH score as assessed by the Life's Essential 8 metrics significantly predicted future stroke risk and arterial stiffness status.

Integrated mRNA and microRNA profiling in lung tissue and blood from human silicosis.

BACKGROUND: The overwhelming majority of subjects in the current silicosis mRNA and microRNA (miRNA) expression profile are of human blood, lung cells or a rat model, which puts limits on the understanding of silicosis pathogenesis and therapy. To address the limitations, our investigation was focused on differentially expressed mRNA and miRNA profiles in lung tissue from silicosis patients to explore potential biomarker for early detection of silicosis. METHODS: A transcriptome study was conducted based on lung tissue from 15 silicosis patients and eight normal people, and blood samples from 404 silicosis patients and 177 normal people. Three early stage silicosis, five advanced silicosis and four normal lung tissues were randomly selected for microarray processing and analyze. The differentially expressed mRNAs were further used to conduct Gene Ontology and pathway analyses. Series test of cluster was performed to explore possible changes in differentially expressed mRNA and miRNA expression patterns during the process of silicosis. The blood samples and remaining lung tissues were used in a quantitative real-time PCR (RT-qPCR) (RT-qPCR). RESULTS: In total, 1417 and 241 differentially expressed mRNAs and miRNAs were identified between lung tissue from silicosis patients and normal people (p < 0.05). However, there was no significant difference in most mRNA or miRNA expression between early stage and advanced stage silicosis lung tissues. RT-qPCR validation results in lung tissues showed expression of four mRNAs (HIF1A, SOCS3, GNAI3 and PTEN) and seven miRNAs was significantly down-regulated compared to those of control group. Nevertheless, PTEN and GNAI3 expression was significantly up-regulated (p < 0.001) in blood samples. The bisulfite sequencing PCR demonstrated that PTEN had significantly decreased the methylation rate in blood samples of silicosis patients. CONCLUSIONS: PTEN might be a potential biomarker for silicosis as a result of low methylation in the blood.

Visualized concentration sensors based on fluorescence indication in a dye-doped polymer microwire.

We demonstrate visualized microwire sensors based on fluorescence indication for detecting the concentrations of the aqueous solutions. The single Rhodamine (RhB) doped polymer microwires (PMWs) which are excited by the waveguiding excitation method are used as the sensory area. According to the fluorescent microimages of the PMWs, stable periodic oscillations could be observed in the RhB-doped PMWs. The fluorescent period which is dependent on the concentration is further analyzed by image processing and information extraction algorithms. Corresponding to a 1.0% change, the period length change of the visualized sensor reaches ∼380 nm, ∼270 nm, and ∼300 nm in NaCl, KCl, and sucrose solutions, respectively. The dection limits of the three solutions are estimated to be around 1.5 × 10-4%. The dye-doped PMW sensors by fluorescence indication and image analysis proposed here realize the direct visualized detection in concentration sensing, making it possible to avoid the challenges of stability and weak signal detection and offer a potentially stable and cost-effective approach for micro/nanofiber sensor application.

Substrate-mediated plasmon hybridization toward high-performance light trapping.

High-performance light trapping in metamaterials and metasurfaces offers prospects for the integration of multifunctional photonic components at subwavelength scales. However, constructing these nanodevices with reduced optical losses remains an open challenge in nanophotonics. Herein, we design and fabricate aluminum-shell-dielectric gratings by integrating low-loss aluminum materials with metal-dielectric-metal designs for high-performance light trapping featuring nearly perfect light absorption with broadband and large angular tuning ranges. The mechanism governing these phenomena is identified as the occurrence of substrate-mediated plasmon hybridization that allows energy trapping and redistribution in engineered substrates. Furthermore, we strive to develop an ultrasensitive nonlinear optical method, namely, plasmon-enhanced second-harmonic generation (PESHG), to quantify the energy transfer from metal to dielectric components. Our studies may provide a mechanism for expanding the potential of aluminum-based systems in practical applications.

Surface Enhancement Effects of Tiny SnO2 Nanoparticle Modification on α-Fe2O3 for Room-Temperature NH3 Sensing.

The development of a gas sensor capable of detecting ammonia with high selectivity and rapid response at room temperature has consistently posed a formidable challenge. To address this issue, the present study utilized a one-step solvothermal method to co-assemble α-Fe2O3 and SnO2 by evenly covering SnO2 nanoparticles on the surface of α-Fe2O3. By controlling the morphology and Fe/Sn mole ratio of the composite, the as-prepared sample exhibits high-performance detection of NH3. At room temperature conditions, a gas sensor composed of α-Fe2O3@3%SnO2 demonstrates a rapid response time of 14 s and a notable sensitivity of 83.9% when detecting 100 ppm ammonia. Experiments and density functional theory (DFT) calculations suggest that the adsorption capacity of α-Fe2O3 to ammonia is enhanced by the surface effect provided by SnO2. Meanwhile, the existence of SnO2 tailors the pore structure and effective surface area of α-Fe2O3, creating multiple channels for the diffusion and adsorption of ammonia molecules. Additionally, an N-N heterostructure is formed between α-Fe2O3 and SnO2, which enhances the potential energy barrier and improves the ammonia sensing performance. Demonstration experiments have proved that the sensor shows significant advantages over commercial sensors in the process of ammonia detection in agricultural facilities. This work provides new insights into the perspectives on ammonia detection at room temperature.

Predicting Atmospheric Particle Phase State Using an Explainable Machine Learning Approach Based on Particle Rebound Measurements.

The particle phase state plays a vital role in the gas-particle partitioning, multiphase reactions, ice nucleation activity, and particle growth in the atmosphere. However, the characterization of the atmospheric phase state remains challenging. Herein, based on measured aerosol chemical composition and ambient relative humidity (RH), a machine learning (ML) model with high accuracy (R2 = 0.952) and robustness (RMSE = 0.078) was developed to predict the particle rebound fraction, f, which is an indicator of the particle phase state. Using this ML model, the f of particles in the urban atmosphere was predicted based on seasonal average aerosol chemical composition and RH. Regardless of seasons, aerosols remain in the liquid state of mid-high latitude cities in the northern hemisphere and in the semisolid state over semiarid regions. In the East Asian megacities, the particles remain in the liquid state in spring and summer and in the semisolid state in other seasons. The effects of nitrate, which is becoming dominant in fine particles in several urban areas, on the particle phase state were evaluated. More nitrate led the particles to remain in the liquid state at an even lower RH. This study proposed a new approach to predict the particle phase state in the atmosphere based on RH and aerosol chemical composition.

Study on detection method of microplastics in farmland soil based on hyperspectral imaging technology.

Microplastics (MPs) in farming soils can have a substantial impact on soil ecology and agricultural productivity, as well as affecting human health and the food chain cycle. As a result, it is vital to study MPs detection technologies that are rapid, efficient, and accurate in agriculture soils. This study investigated the classification and detection of MPs using hyperspectral imaging (HSI) technology and a machine learning methodology. To begin, the hyperspectral data was preprocessed using SG convolution smoothing and Z-score normalization. Second, the feature variables were extracted from the preprocessed spectral data using bootstrapping soft shrinkage, model adaptive space shrinkage, principal component analysis, isometric mapping (Isomap), genetic algorithm, successive projections algorithm (SPA), and uninformative variable elimination. Finally, three support vector machine (SVM), back propagation neural network (BPNN), and one-dimensional convolutional neural network (1D-CNN) models were developed to classify and detect three microplastic polymers: polyethylene, polypropylene, and polyvinyl chloride, as well as their combinations. According to the experimental results, the best approaches based on three models were Isomap-SVM, Isomap-BPNN, and SPA-1D-CNN. Among them, the accuracy, precision, recall and F1_score of Isomap-SVM were 0.9385, 0.9433, 0.9385 and 0.9388, respectively. The accuracy, precision, recall and F1_score of Isomap-BPNN were 0.9414, 0.9427, 0.9414 and 0.9414, respectively, while the accuracy, precision, recall and F1_score of SPA-1D-CNN were 0.9500, 0.9515, 0.9500 and 0.9500, respectively. When their classification accuracy was compared, SPA-1D-CNN had the best classification performance, with a classification accuracy of 0.9500. The findings of this study shown that the SPA-1D-CNN based on HSI technology can efficiently and accurately identify MPs in farmland soils, providing theoretical backing as well as technical means for real-time detection of MPs in farmland soils.

A network system for the prevention and treatment of mushroom poisoning in Chuxiong Autonomous Prefecture, Yunnan Province, China: implementation and assessment.

BACKGROUND: Mushroom poisoning is a major public health issue in China. The integration of medical resources from different institutes of different levels is crucial in reducing the harm of mushroom poisoning. However, few studies have provided comprehensive implementation procedures and postimplementation effectiveness evaluations. To reduce the harm caused by mushroom poisoning, a network system for the prevention and treatment of mushroom poisoning (NSPTMP) was established in Chuxiong, Yunnan Province, a high-risk area for mushroom poisoning. METHODS: The NSPTMP consists of three types of institutions, namely, centers for disease prevention, hospitals, and health administration departments, with each kind of institution comprising prefecture, county/city, town, and village levels. After three years of implementation, the network was evaluated by comparing the indices before and after network implementation using data from the "Foodborne Disease Outbreak Surveillance System" and 17 hospitals in Chuxiong. The indices included the fatalities caused by mushroom poisoning, the composition ratios of different types of mushrooms for both outpatients and inpatients and the hospitalization rates. RESULTS: Compared to the average fatality rate of mushroom poisoning from 2015 to 2017, the average fatality rate from 2018 to 2020 significantly decreased from 0.57 to 0.06% (P < 0.001). Regarding the poisonous genus containing lethal mushrooms, the outpatient and inpatient composition ratios significantly decreased for Amanita (9.36-2.91% and 57.23-17.68%, respectively) and Russula (15.27-8.41%) (P < 0.05). Regarding poisonous mushrooms that caused mild symptoms, the outpatient and inpatient composition ratios significantly increased for Scleroderma (5.13-13.90% and 2.89-18.90%, respectively) and Boletaceae (19.08-31.71%) (P < 0.05), and the hospitalization rates significantly increased for Scleroderma (6.33-18.02%) and Boletaceae (5.65-12.71%) (P < 0.05). CONCLUSIONS: These findings suggest that the NSPTMP effectively reduced the harm caused by mushroom poisoning. In addition to the integration of medical resources, the development of poisonous mushroom identification, hierarchical treatment systems in hospitals, public education, and professional training also played important roles in improving the system's effectiveness. The establishment and evaluation of the NSPTMP in Chuxiong Prefecture can provide valuable insights and serve as a model for other regions facing similar challenges in managing mushroom poisoning.

Remarkable nucleation and growth of ultrafine particles from vehicular exhaust.

High levels of ultrafine particles (UFPs; diameter of less than 50 nm) are frequently produced from new particle formation under urban conditions, with profound implications on human health, weather, and climate. However, the fundamental mechanisms of new particle formation remain elusive, and few experimental studies have realistically replicated the relevant atmospheric conditions. Previous experimental studies simulated oxidation of one compound or a mixture of a few compounds, and extrapolation of the laboratory results to chemically complex air was uncertain. Here, we show striking formation of UFPs in urban air from combining ambient and chamber measurements. By capturing the ambient conditions (i.e., temperature, relative humidity, sunlight, and the types and abundances of chemical species), we elucidate the roles of existing particles, photochemistry, and synergy of multipollutants in new particle formation. Aerosol nucleation in urban air is limited by existing particles but negligibly by nitrogen oxides. Photooxidation of vehicular exhaust yields abundant precursors, and organics, rather than sulfuric acid or base species, dominate formation of UFPs under urban conditions. Recognition of this source of UFPs is essential to assessing their impacts and developing mitigation policies. Our results imply that reduction of primary particles or removal of existing particles without simultaneously limiting organics from automobile emissions is ineffective and can even exacerbate this problem.

Light Intensity Regulates Low-Temperature Adaptability of Tea Plant through ROS Stress and Developmental Programs.

Low-temperature stress limits global tea planting areas and production efficiency. Light is another essential ecological factor that acts in conjunction with temperature in the plant life cycle. However, it is unclear whether the differential light environment affects the low temperature adaptability of tea plant (Camellia sect. Thea). In this study, tea plant materials in three groups of light intensity treatments showed differentiated characteristics for low-temperature adaptability. Strong light (ST, 240 µmol·m-2·s-1) caused the degradation of chlorophyll and a decrease in peroxidase (POD), superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX), and polyphenol oxidase (PPO) activities, as well as an increase in soluble sugar, soluble protein, malondialdehyde (MDA), and relative conductivity in tea leaves. In contrast, antioxidant enzyme activities, chlorophyll content, and relative conductivity were highest in weak light (WT, 15 µmol·m-2·s-1). Damage was observed in both ST and WT materials relative to moderate light intensity (MT, 160 µmol·m-2·s-1) in a frost resistance test. Chlorophyll degradation in strong light was a behavior that prevented photodamage, and the maximum photosynthetic quantum yield of PS II (Fv/Fm) decreased with increasing light intensity. This suggests that the browning that occurs on the leaf surface of ST materials through frost may have been stressed by the previous increase in reactive oxygen species (ROS). Frost intolerance of WT materials is mainly related to delayed tissue development and tenderness holding. Interestingly, transcriptome sequencing revealed that stronger light favors starch biosynthesis, while cellulose biosynthesis is enhanced in weaker light. It showed that light intensity mediated the form of carbon fixation in tea plant, and this was associated with low-temperature adaptability.

Analysis of Intensive Care Unit Nursing Clinical Judgment and Selection of Nursing Diagnosis for Cerebral Hemorrhage.

Few nursing informatics studies focus on selecting nursing diagnoses for critical patients. The absence of data about nursing clinical judgment in the care of patients with cerebral hemorrhage greatly hinders research progress in evidence-based care. A stratified, retrospective study analyzed 115 electronic "intelligent" nursing information system nurse assessments and nursing diagnoses. Data were documented from April 2019 to November 2020 for critically ill patients admitted with cerebral hemorrhage in a 10-bed medical ICU at a 1500-bed tertiary facility, Henan Honliv Hospital, in Henan Province, China. In the selection of nursing diagnoses among nurses of stratified competencies (novice to expert), novice and experienced nurses were found to have significant variances in selecting nursing diagnoses for critically ill patients with cerebral hemorrhage. Novice nurses more frequently selected the Activity Intolerance Risk diagnosis as an initial diagnosis ( P = .025). Experienced nurses selected the Fluid Volume Excess Risk diagnosis more frequently ( P = .003). Consequently, nursing information systems are important in evaluating professional practice. The access to structured, standardized nursing data for the complete nursing process enables nurse managers to comprehensively analyze the nursing care given to patients, the distribution of patient nursing diagnoses, and the status of patient care risks.

[Study of the unique cellular molecular characteristics of moderately intrauterine adhesion based on single-cell RNA sequencing].

OBJECTIVE: To depict the cell landscape and molecular biological characteristics of human intrauterine adhesion (IUA) so as to better understand its immune microenvironment and provide new inspirations for clinical treatment. METHODS: Four patients with IUA who underwent hysteroscopic treatment at Dongguan Maternal and Child Health Care Hospital from February 2022 to April 2022 were selected as the study subjects. Hysteroscopy was used to collect the tissues of IUA, which were graded based on the patient's medical history, menstrual history and status of IUA. Library construction, sequencing, single cell data comparison and gene expression matrix construction were carried out in strict accordance with the single cell RNA sequencing process. Thereafter, the UMAP dimension reduction analysis of cell population and genetic analysis were carried out based on the cell types. RESULTS: A total of 27 511 cell transcripts were obtained from four moderately graded IUA tissue samples and assigned to six cell lineages including T cells, mononuclear phagocytes, epithelial cells, fibroblasts, endothelial cells and erythrocytes. Compared with normal uterine tissue cells, the four samples showed different cell distribution, and the proportions of mononuclear phagocytes and T cells in sample IUA0202204 were significantly increased, suggesting a strong cellular immune response. CONCLUSION: The cell diversity and heterogeneity of moderate IUA tissues have been described. Each cell subgroup has unique molecular characteristics, which may provide new clues for further study of the pathogenesis of IUA and heterogeneity among the patients.

Effects of heterogeneous reaction with NO2 on ice nucleation activities of feldspar and Arizona Test Dust.

Mineral dust is an important type of ice nucleating particles in the troposphere; however, the effects of heterogeneous reactions on ice nucleation (IN) activities of mineral dust remain to be elucidated. A droplet-freezing apparatus (Guangzhou Institute of Geochemistry Ice Nucleation Apparatus, GIGINA) was developed in this work to measure IN activities of atmospheric particles in the immersion freezing mode, and its performance was validated by a series of experimental characterizations. This apparatus was then employed to measure IN activities of feldspar and Arizona Test Dust (ATD) particles before and after heterogeneous reaction with NO2 (10±0.5 ppmv) at 40% relative humidity. The surface coverage of nitrate, θ(NO3-), increased to 3.1±0.2 for feldspar after reaction with NO2 for 6 hr, and meanwhile the active site density per unit surface area (ns) at -20°C was reduced from 92±5 to <1.0 cm-2 by about two orders of magnitude; however, no changes in nitrate content or IN activities were observed for further increase in reaction time (up to 24 hr). Both nitrate content and IN activities changed continuously with reaction time (up to 24 hr) for ATD particles; after reaction with NO2 for 24 hr, θ(NO3-) increased to 1.4±0.1 and ns at -20°C was reduced from 20±4 to 9.7±1.9 cm-2 by a factor of ∼2. Our work suggests that heterogeneous reaction with NO2, an abundant reactive nitrogen species in the troposphere, may significantly reduce IN activities of mineral dust in the immersion freezing mode.

Measurement of atmospheric nanoparticles: Bridging the gap between gas-phase molecules and larger particles.

Atmospheric nanoparticles are crucial components contributing to fine particulate matter (PM2.5), and therefore have significant effects on visibility, climate, and human health. Due to the unique role of atmospheric nanoparticles during the evolution process from gas-phase molecules to larger particles, a number of sophisticated experimental techniques have been developed and employed for online monitoring and characterization of the physical and chemical properties of atmospheric nanoparticles, helping us to better understand the formation and growth of new particles. In this paper, we firstly review these state-of-the-art techniques for investigating the formation and growth of atmospheric nanoparticles (e.g., the gas-phase precursor species, molecular clusters, physicochemical properties, and chemical composition). Secondly, we present findings from recent field studies on the formation and growth of atmospheric nanoparticles, utilizing several advanced techniques. Furthermore, perspectives are proposed for technique development and improvements in measuring atmospheric nanoparticles.

Efficient thermally activated delayed fluorescence organic light-emitting device based on an exciplex.

An exciplex with significant thermally activated delayed fluorescence properties was realized, comprising diphenyl-[3'-(1-phenyl-1H-phenanthro[9,10-d]imidazol-2-yl)-biphenyl-4-yl]-amine as a donor and 2,4,6-tris[3-(diphenylphosphinyl)phenyl]-1,3,5-triazine as an acceptor. A very small energy difference between the singlet and triplet levels and a large rate constant of the reverse intersystem crossing were attained simultaneously, contributing to the efficient upconversion of triplet excitons from the triplet state to the singlet state and thermally activated delayed fluorescence emission. A high-efficiency organic light-emitting device based on the exciplex was fabricated, which exhibited a maximum current efficiency, power efficiency, external quantum efficiency, and exciton utilization efficiency of 23.1 cd/A, 24.2 lm/W, 7.32%, and 54%, respectively. The efficiency roll-off of the exciplex-based device was slight, as illustrated by a large critical current density of 34.1 mA/cm2. This efficiency roll-off was ascribed to triplet-triplet annihilation, as confirmed by the triplet-triplet annihilation model. We proved the high binding energy of the excitons and excellent charge confinement within the exciplex by performing transient electroluminescence measurements.

Anti-reflection metallic anode-enhanced performance of organic solar cells via cross coupling between Fabry-Perot cavity modes and microcavity modes.

An effective anti-reflection metallic anode with the structure of glass/dielectric2 /Ag (D1D2M) is demonstrated both in small-molecule (SM) and conjugated polymer (CP) organic solar cells (OSCs). The anti-reflection mechanism is investigated by the finite-difference time-domain numerical calculation method and the experimental method. By tuning the refractive index and the thickness of the D2 layer, the reflection light is confined in the Fabry-Perot (F-P) cavity modes, which effectively enhances the transmittance of the D1D2M anode in the wavelength range of 420 nm-800 nm. Compared with the conventional glass/Ag (D1M) anode, the experimental transmittance of the D1D2M anode is enhanced by 33.24% at a wavelength of 550 nm. By replacing the D1M anode with the D1D2M anode in the OSCs, the F-P cavity modes cross couple with the microcavity modes in the active layers. As a result, the absorption intensity is obviously increasing in a wide angle range (0≤θ≤85∘) in the wavelength ranges of 475 nm-650 nm and 540 nm-720 nm for the SM and CP OSCs, respectively. The short circuit current density and power conversion efficiency of the SM OSC is increased by 25.07% and 27.23%, respectively.

Haze Air Pollution Health Impacts of Breath-Borne VOCs.

Here, we investigated the use of breath-borne volatile organic compounds (VOCs) for rapid monitoring of air pollution health effects on humans. Forty-seven healthy college students were recruited, and their exhaled breath samples (n = 235) were collected and analyzed for VOCs before, on, and after two separate haze pollution episodes using gas chromatography-ion mobility spectrometry (GC-IMS). Using a paired t-test and machine learning model (Gradient Boosting Machine, GBM), six exhaled VOC species including propanol and isoprene were revealed to differ significantly among pre-, on-, and post-exposure in both haze episodes, while none was found between clean control days. The GBM model was shown capable of differentiating between pre- and on-exposure to haze pollution with a precision of 90-100% for both haze episodes. However, poor performance was detected for the same model between two different clean days. In addition to gender and particular haze occurrence influences, correlation analysis revealed that NH4+, NO3-, acetic acid, mesylate, CO, NO2, PM2.5, and O3 played important roles in the changes in breath-borne VOC fingerprints following haze air pollution exposure. This work has demonstrated direct evidence of human health impacts of haze pollution while identifying potential breath-borne VOC biomarkers such as propanol and isoprene for haze air pollution exposure.