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In order to solve the heat loss and the pollution of gas boilers, a synergistic system consisting of waste heat recovery tower and air humidification tower is proposed. Increasing in moisture content of the air can inhibit the generation of nitrogen oxides and increase the dew point of the flue gas, which is beneficial to the utilization of the waste heat from the flue gas. More heat is absorbed by the humidification water at the fin heat exchanger after the flue gas enters the waste heat recovery tower, which enhances the heat and mass exchange process in the air humidification tower. But the performance of the heat pump was found to show a downward trend, indicating a competitive relationship between nitrogen oxides reduction and waste heat recovery. Under the optimal condition, the experimental system can reduce nitrogen oxides emissions by 62.35%, and the exhaust gas temperature can be reduced to 24.46 °C. The heat pump can recover 6.94% heat while maintaining a minimum nitrogen oxides emission of 39.66 mg/m3. The heat pump makes more heat from the fuel to enter the heating network, which improves the heating efficiency of the boiler system. The system can meet the high-efficiency and clean production requirements of the energy system at the same time.
Urban Photovoltaic (PV) systems can provide large fractions of the residential electric demand at socket parity (i.e., a cost below the household consumer price). This is obtained without necessarily installing electric storage or exploiting tax funded incentives. The benefits of aggregating the electric demand and renewable output of multiple households are known and established; in fact, regulations and pilot energy communities are being implemented worldwide. Financing and managing a shared urban PV system remains an unsolved issue, even when the profitability of the system as a whole is demonstrable. For this reason, an agent-based modelling environment has been developed and is presented in this study. It is assumed that an optimal system (optimized for self-sufficiency) is shared between 48 households in a local grid of a positive energy district. Different scenarios are explored and discussed, each varying in number of owners (agents who own a PV system) and their pricing behaviour. It has been found that a smaller number of investors (i.e., someone refuse to join) provokes an increase of the earnings for the remaining investors (from 8 to 74% of the baseline). Furthermore, the pricing strategy of an agent shows improvement potential without knowledge of the demand of others, and thus it has no privacy violations.
Abstract Zirconia is an inorganic, nonmetallic material with excellent properties. However, the brittleness of the zirconia, resulting from the thermal performance during the heating and cooling process, seriously limits the application of zirconia in the metallurgical, military, and aerospace industries. Al2O3 doped ZrO2 was developed to improve the potential material’s toughness. This paper studied the evolution of the surface functional groups, phase composition, toughening mechanism, and particle morphology of Al2O3 doped ZrO2 during the heating process. Especially microwave heating was selected as the heating method during the experiments to save energy consumption. The results showed that the phase transition temperature was reduced by the microwave sintering technique, which also promoted the transformation between the m-ZrO2 and t-ZrO2, advancing the crystallinity and structural properties of the samples. The specific surface area shows a positive relationship with the microwave heating temperature, while the particle size of the powder decreased with the temperature increase. The optimized sintering effect appears at 1000 °C in the studied roasting temperature range (800 °C–1200 °C) for Al2O3–ZrO2 powders. With the optimized sintering temperature, the void of the granular zirconia material was controlled, and the best micromorphology was obtained. In practical production, the application of microwave sintering and alumina doping is beneficial to saving costs and protecting the environment. Al2O3–ZrO2
Crowding events, which pose tremendous pressure to city management and society safety, are a typical manifestation of anomalous human mobility in metropolitan areas. However, we are still lacking a comprehensive understanding of the anomalous human mobility in crowding events, which is crucial for preventing crowd disasters and developing sustainable cities and societies. In this study, we analyze the individual and collective human mobility patterns in crowding events using the smart card data of six million subway passengers in Shenzhen city. The discovered individual human mobility patterns reveal the underlying mechanism of crowd formation. The discovered collective human mobility patterns can be employed to anticipate crowding events, offering timely information for transportation and crowd management.
High-modulus asphalt mixture (HMAM) is one of the most effective materials to enhance the rutting resistance of asphalt pavement and upgrade pavement sustainability. The objectives of this study are to investigate the modulus properties of different HMAMs and their correlation with the rutting resistance, to propose reasonable modulus evaluation indicators, and to analyze the rutting resistance mechanisms of different materials (hard asphalt, polyethylene, dissolved polyolefin). The effect of three HMAMs and two styrene-butadiene-styrene (SBS) modifiers on asphalt mixtures’ rutting resistance were evaluated by dynamic modulus test and wheel track test, and the results were simulated and further analyzed via ABAQUS. The results indicate that the dynamic modulus of the mixtures showed a gradual increase and decrease with the increase of loading frequency and testing temperature, respectively. The ratio of dynamic modulus in low frequency to that in high frequency correlates well with dynamic stability under high-temperature conditions, and the wider the frequency coverage, the higher the correlation between this ratio and dynamic stability. The rutting resistance of asphalt pavements can be improved by reducing the frequency sensitivity of HMAMs under high temperatures or by increasing the modulus’ absolute value of the pavement structural layer. Therefore, two indicators, the absolute value of the modulus and the ratio of 0.1 Hz dynamic modulus to 25 Hz dynamic modulus at 55 °C, are recommended for the evaluation of rutting resistance of HMAMs. Based on the evaluation indexes proposed in this paper, a comparative analysis of the rutting resistance mechanism of HMAMs prepared with different materials was carried out, and it was concluded that the mixture with high-modulus agents had the best rutting resistance, which is consistent with the test road observations, thus verifying the feasibility of the modulus evaluation indexes recommended in this paper for the evaluation of the rutting resistance of different typesof HMAMs.
Moiré superlattices, the artificial quantum materials, have provided a wide range of possibilities for the exploration of completely new physics and device architectures. In this Review, we focus on the recent progress on emerging moiré photonics and optoelectronics, including but not limited to moiré excitons, trions, and polaritons; resonantly hybridized excitons; reconstructed collective excitations; strong mid- and far-infrared photoresponses; terahertz single-photon detection; and symmetry-breaking optoelectronics. We also discuss the future opportunities and research directions in this field, such as developing advanced techniques to probe the emergent photonics and optoelectronics in an individual moiré supercell; exploring new ferroelectric, magnetic, and multiferroic moiré systems; and using external degrees of freedom to engineer moiré properties for exciting physics and potential technological innovations.
This paper introduced a new ship domain concept and an analytical framework. The ship domain takes the point of the ship’s first evasive maneuver as a basis and correlates it with the navigator-perceived collision risk level. The first evasive maneuver of a ship is detected based on the ship turning point identification and ship intention estimation. The available maneuvering margin (AMM) is utilized as a proxy to measure the perceived collision risk by the navigator. Interpreting the first evasive maneuver in terms of this AMM over a large sample of vessel encounters taken from automatic identification system (AIS) data finally enables an empirical estimation of the size of this ship domain. The method is applied to AIS data in the Northern Baltic Sea, and separate ship domains are constructed for the give-way and stand-on vessels with different maneuverability characteristics. Compared to the existing proximity-based ship domain, this ship domain explicitly incorporates the dynamic nature of the encounter process and the navigator’s evasive maneuvers. Several advantages of this proposed ship domain concept and limitations of the presented modeling approach are discussed. Finally, possible future applications are explained, including waterway safety assessment and navigational decision support systems to reduce ship-ship collision risk.
Abstract The dried ammonium polyvanadate (APV) can be used to produce high-purity Vanadium pentoxide (V2O5) by calcination. Therefore, drying is a necessary process. The advantages of microwave drying are uniform heating, selective heating, high heating efficiency and the operation process is clean and hygienic. This study uses a microwave to dry APV and discusses the effect of the initial mass, microwave power, initial moisture content on the drying efficiency of APV. The results display that the average drying rate is positively correlated with the microwave output power. When the initial mass is 35 g, the average rate is shown as 0.000263%/s. As the initial moisture content and power of APV increases to 25% and 560W, the average drying rate increases to 0.00036231%/s and 0.003125%/s, respectively. At the same time, through the analysis of APV drying kinetics and the fitting of experimental data, it is found that the APV microwave drying process can be precisely described by the Modified Page model. The microwave heating process saves energy and time, directly penetrates the product, and has certain advantages in green metallurgy.
Abstract In this paper, we propose a cooperative model combined the multi-task reverse sparse representation model (MTRSR) and the AdaBoost classifier, which were used to cope with the disturbing of target gradient information caused by motion blur or target serious occlusion, and a descriptive dictionary were used to estimate the weights of each candidates. First, we use the MTRSR model to get the blur kernel which were used to get the blur target template set, meanwhile the confidence of the candidates is also obtained by the reconstruction error. Then we use the HOG features of the target templates to get the descriptive dictionary to calculate the weights of the candidates, and a AdaBoost classifier is used to calculate the confidences of all candidates. Finally, the best target is retrieved by the sum of production of weight value and the two confidences. The experimental data show that the proposed algorithm can fully cope with the target’s information change which were caused by motion blur and target occlusion in the complex scene, and our algorithm can further improve the accuracy and robustness in visual tracking.
Groundwater (GW) quality assessment is an essential issue, especially in arid and semi-arid regions, due to its critical role in obtaining requirements for freshwater. The GALDIT method is widely recognized as a practical approach for assessing GW susceptibility, which considers six key factors, including the occurrence of groundwater (G), hydraulic conductivity of the aquifer (A), elevation of groundwater above sea level (L), distance from the shoreline (D), impact of existing seawater intrusion (I), and thickness of the aquifer (T). The GALDIT method, being an unsupervised model, has a drawback in that it depends on expert opinion for parameter ranking, leading to an increase in uncertainty. To address this uncertainty and evaluate the susceptibility of the aquifers of Urmia lake basin to saltwater intrusion, this study employed the Z-number which is a novel adaptation of Fuzzy Logic (FL). In contrast to classic FL that does not account for data reliability, the Z-number approach considers both constraints and data reliability, making it a more effective method to manage data uncertainty compared to classic fuzzy models. To illustrate this methodology, the GALDIT parameters (inputs) and Electrical Conductivity (EC) values (outputs) were employed to determine the vulnerability of aquifers. Additionally, the GALDIT method was utilized as a benchmark model to evaluate the inherent vulnerability of aquifers, and its outcomes were compared with those of the proposed model. Upon analyzing the results, it was found that the Z-number Based Modeling (ZBM) not only outperformed the GALDIT method but also enhanced the quality of outcomes by 85% and 35% based on Heidke Skill Score (HSS) and Total Accuracy (TA) criteria compared to the classic FL.
Abstract The rigidity of traditional solid-state surface-enhanced Raman spectroscopy (SERS) substrate hampers their application in the curved structure for nonplanar surface test and in-situ detection. Traditionally, the flexible Raman substrates are often prepared by transferring printing of patterned nanoparticles on the flexible materials such as polymer, paper, etc. However, the replicate patterns are often produced by high-cost instruments. In this study, a low-cost and flexible SERS substrate is prepared by using a microcontact printing technology to transfer three-phase-assembled nanoparticles on a polydimethylsiloxane film, which can stabilize the assembled nanoparticles. Combining with the endonuclease Nt.BbvCI assisted amplification method, a SERS biosensor is constructed for microRNA 21 (miRNA 21) assay. This platform presents a wide dynamic range (100 fM ∼1 nM), achieving a fabulous sensitivity with limit of detection of 11.96 fM for miRNA 21. Furthermore, after being bent 90° for 50 times, the Raman intensity of the flexible substrate shows a negligible change. This versatile flexible substrate exhibits considerable potential for SERS analysis, which also opens a new avenue for preparing flexible devices.
Abstract MicroRNAs (miRNAs) are involved in the regulation of gene expression via incomplete base pairing to sequence motifs at the three prime untranslated regions (3′-UTRs) of mRNAs and play critical roles in the etiology of cancers. Single nucleotide polymorphisms (SNPs) in the 3′-UTR miRNA-binding regions may influence the miRNA affinity. However, this biological mechanism in prostate cancer (PCa) remains unclear. Here, a three-stage genome-wide association study of 3′-UTR SNPs (n=33 117) is performed in 5515 Chinese men. Three genome-wide significant variants are discovered at 8p21.2 (rs1567669, rs4872176, and rs4872177), which are all located in a linkage disequilibrium region of the NKX3–1 gene. Phenome-wide association analysis using the FinnGen data reveals a specific association of rs1567669 with PCa over 2,264 disease endpoints. Expression quantitative trait locus analyses based on both Chinese PCa cohort and the GTEx database show that risk alleles of these SNPs are significantly associated with low expression of NKX3–1. Based on the MirSNP database, dual-luciferase reporter assays show that risk alleles of these SNPs downregulate the expression of NKX3–1 via increased miRNA binding. These results indicate that the SNPs at the 3′-UTR of NKX3–1 significantly downregulate NKX3–1 expression by influencing the affinity of miRNA and increase the PCa risk.
Abstract Aberrant telomerase reverse transcriptase (TERT) expression is crucial for tumor survival and cancer cells escaping apoptosis. Multiple TERT-locus variants at 5p15 have been discovered in association with cancer risk, yet the underlying mechanisms and clinical impacts remain unclear. Here, our association studies showed that the TERT promoter variant rs2853669 confers a risk of prostate cancer (PCa) in different ethnic groups. Further functional investigation revealed that the allele-specific binding of MYC and E2F1 at TERT promoter variant rs2853669 associates with elevated level of TERT in PCa. Mechanistically, androgen stimulations promoted the binding of MYC to allele T of rs2853669, thereby activating TERT, whereas hormone deprivations enhanced E2F1 binding at allele C of rs2853669, thus upregulating TERT expression. Notably, E2F1 could cooperate with AR signaling to regulate MYC expression. Clinical data demonstrated synergistic effects of MYC/E2F1/TERT expression or with the TT and CC genotype of rs2853669 on PCa prognosis and severity. Strikingly, single-nucleotide editing assays showed that the CC genotype of rs2853669 obviously promotes epithelial–mesenchymal transition (EMT) and the development of castration-resistant PCa (CRPC), confirmed by unbiased global transcriptome profiling. Our findings thus provided compelling evidence for understanding the roles of noncoding variations coordinated with androgen signaling and oncogenic transcription factors in mis-regulating TERT expression and driving PCa.
Abstract Pain is a significant indicator that shows people are suffering from an unwell experience and its automatic estimation has attracted much interest in recent years. Of late, most estimation methods are designed to capture the dynamic pain information from visual signals while a few physiological-signal based methods can provide extra potential cues to analyze the pain more accurately. However, it is still challenging to capture the physiological data from patients as it requires contact devices and patients’ cooperation. In this paper, we propose to leverage the pseudo physiological information by generating new modal data from the original visual videos and jointly estimating the pain by an end-to-end network. To extract the representations from bi-modal data, we design a spatio-temporal pain estimation network, which employs a dual-branch framework for extracting pain-aware visual and pseudo physiological features separately and fuses the features in a probabilistic way. The inherent vital sign, i.e., heart rate gain (HRG), from pseudo physiological information can be utilized as an auxiliary signal and integrated with the visual pain estimation framework. Moreover, specially-designed 3D convolution filters and attention structures are employed to extract spatio-temporal features for both branches. To use the HRG as an auxiliary way for pain estimation, we propose a probabilistic inference model by jointly considering the visual branch and physiological branch, which makes our model estimate the pain comprehensively. Experiments on two publicly-available datasets show the effectiveness of introducing the pseudo modality, and the proposed method can outperform the state-of-the-art methods.
The COVID-19 pandemic has had a severe impact on humans' lives and and healthcare systems worldwide. How to early, fastly and accurately diagnose infected patients via multimodal learning is now a research focus. The central challenges in this task mainly lie on multi-modal data representation and multi-modal feature fusion. To solve such challenges, we propose a medical knowledge enriched multi-modal sequence to sequence learning model, termed MedSeq2Seq. The key components include two attention mechanisms, viz. intra-modal (Ia) and inter-model (Ie) attentions, and a medical knowledge augmentation mechanism. The former two mechanisms are to learn multi-modal refined representation, while the latter aims to incorporate external medical knowledge into the proposed model. The experimental results show the effectiveness of the proposed MedSeq2Seq framework over state-of-the-art baselines with a significant improvement of 1%-2%.
Abstract Nanostructured ceramic materials doped with stabilizers have superior mechanical, chemical, and electrical properties. In this study, tetragonal zirconia stabilized by 6 mol% MgO and 2 mol% Y2O3 (t-6MgO–2Y2O3–ZrO2) nanopowders with quasi-spherical morphology, uniform particle size, and narrower grain size distributions were prepared by a combination process including two steps: namely co-precipitation and high-energy ball milling. The effect of ball milling time on ZrO2 crystal particles was investigated by characterizations including XRD, Raman, FT-IR, FEESM, BET, and TEM. With the increase of ball milling time, the average grain size of the powder showed a gradual decrease tendency, the particle size distribution changed from wide to narrow, the particle morphology tended to be spherical, and the specific surface area gradually increased. Under the optimized conditions (ball milling for 8 h, calcination temperature of 800 °C, and holding time of 2 h), the highly dispersed spherical nanopowders with a minimum particle size of 18.47 nm and an average particle size of 29.02 nm were obtained. These zirconium oxide nanopowders are suitable for the preparation of inorganic coatings, biomedical materials, catalyst materials, and other types of functional materials.
Abstract Sparse coding has achieved a great success in various image processing studies. However, there is not any benchmark to measure the sparsity of image patch/group because sparse discriminant conditions cannot keep unchanged. This paper analyzes the sparsity of group based on the strategy of the rank minimization. Firstly, an adaptive dictionary for each group is designed. Then, we prove that group-based sparse coding is equivalent to the rank minimization problem, and thus the sparse coefficients of each group are measured by estimating the singular values of each group. Based on that measurement, the weighted Schatten p-norm minimization (WSNM) has been found to be the closest solution to the real singular values of each group. Thus, WSNM can be equivalently transformed into a non-convex lp-norm minimization problem in group-based sparse coding. Experimental results on two applications: image in painting and image compressive sensing (CS) recovery show that the proposed scheme outperforms many state-of-the-art methods.
Abstract Tetragonal zirconia has excellent mechanical properties and biocompatibility, and is widely used in medicine, aviation, ceramics, and other fields. In this study, nano-zirconia (6MgO–2Y2O3–ZrO2) was prepared by co-precipitation method assisted with pressure-less sintering which was used to obtain tetragonal phase zirconia. The zirconia powders were analyzed by XRD, Raman spectroscopy, FT-IR, SEM, and Gaussian mathematical fitting. The outcomes demonstrate that elevated temperature favors the promotion of phase transitions which enhances structural properties and the crystallinity of zirconia, and enables the stable existence of t-ZrO2 at room temperature. The size of the powder gradually decreases, and the particle size distribution becomes narrower with the temperature increases. With the increasing specific surface area, the morphology of nano-oxidation gradually tends to be spherical. In the sintering temperature (350 °C–950 °C), the spherical nano-powders obtained at 950 °C shows the lowest voidage and the best density. In actual production, it can provide a reference for the preparation of high-quality nano-zirconia and broaden the application field of zirconia.
Abstract In the family of inorganic nanomaterials, zirconia is a highly promising functional ceramic with a high refractive index, hardness, and dielectric constant, as well as excellent chemical inertness and thermal stability. These properties are enhanced in nano-zirconia ceramics, because nanopowders have a small particle size, good morphology, and uniform and dispersive distribution. In this study, a co-precipitation process was proposed to synthesise highly dispersed MgO–Y2O3 co-stabilized ZrO2 nanopowders. The effects of different calcination temperatures on the crystallisation degree and particle dispersion of zirconia nanopowders were characterised by X-ray diffraction (XRD), thermogravimetry-differential scanning calorimetry (TG-DSC), Raman spectroscopy, Fourier transform infrared spectroscopy (FTIR), nitrogen adsorption using the Brunauer–Emmett–Teller (BET) theory, transmission electron microscopy (TEM), and field emission scanning electron microscopy (FESEM). The optimum synthesis conditions were obtained as follows: 6 h of high-energy planetary grinding and calcination at 800 °C in an electric furnace. Under these optimum conditions, the average particle size of the prepared powder was 28.7 nm. This process enriches the literature on the controllable preparation of Mg–Y/ZrO2 nanopowders obtained by the co-precipitation method.
I-V-VI2 ternary chalcogenides are gaining attention as earth-abundant, nontoxic, and air-stable absorbers for photovoltaic applications. However, the semiconductors explored thus far have slowly-rising absorption onsets, and their charge-carrier transport is not well understood yet. Herein, we investigate cation-disordered NaBiS2 nanocrystals, which have a steep absorption onset, with absorption coefficients reaching >105 cm−1 just above its pseudo-direct bandgap of 1.4 eV. Surprisingly, we also observe an ultrafast (picosecond-time scale) photoconductivity decay and long-lived charge-carrier population persisting for over one microsecond in NaBiS2 nanocrystals. These unusual features arise because of the localised, non-bonding S p character of the upper valence band, which leads to a high density of electronic states at the band edges, ultrafast localisation of spatially-separated electrons and holes, as well as the slow decay of trapped holes. This work reveals the critical role of cation disorder in these systems on both absorption characteristics and charge-carrier kinetics.
Abstract Precision measurements by the Alpha Magnetic Spectrometer (AMS) on the International Space Station of 3He and 4He fluxes are presented. The measurements are based on 100 million 4He nuclei in the rigidity range from 2.1 to 21 GV and 18 million 3He from 1.9 to 15 GV collected from May 2011 to November 2017. We observed that the 3He and 4He fluxes exhibit nearly identical variations with time. The relative magnitude of the variations decreases with increasing rigidity. The rigidity dependence of the 3He/4He flux ratio is measured for the first time. Below 4 GV, the 3He/4He flux ratio was found to have a significant long-term time dependence. Above 4 GV, the 3He/4He flux ratio was found to be time independent, and its rigidity dependence is well described by a single power law ∝RΔ with Δ=−0.294±0.004. Unexpectedly, this value is in agreement with the B/O and B/C spectral indices at high energies.
Abstract We report the properties of primary cosmic-ray sulfur (S) in the rigidity range 2.15 GV to 3.0 TV based on 0.38 x 106 sulfur nuclei collected by the Alpha Magnetic Spectrometer experiment (AMS). We observed that above 90 GV the rigidity dependence of the S flux is identical to the rigidity dependence of Ne-Mg-Si fluxes, which is different from the rigidity dependence of the He-C-O-Fe fluxes. We found that, similar to N, Na, and Al cosmic rays, over the entire rigidity range, the traditional primary cosmic rays S, Ne, Mg, and C all have sizeable secondary components, and the S, Ne, and Mg fluxes are well described by the weighted sum of the primary silicon flux and the secondary fluorine flux, and the C flux is well described by the weighted sum of the primary oxygen flux and the secondary boron flux. The primary and secondary contributions of the traditional primary cosmic-ray fluxes of C, Ne, Mg, and S (even Z elements) are distinctly different from the primary and secondary contributions of the N, Na, and Al (odd Z elements) fluxes. The abundance ratio at the source for S/Si is 0.167 ± 0.006, for Ne/Si is 0.833 ± 0.025, for Mg/Si is 0.994 ± 0.029, and for C/O is 0.836 ± 0.025. These values are determined independent of cosmic-ray propagation.
Abstract Partially stabilized Y2O3–ZrO2 (Y-PSZ) is often used as a material in the field of oxygen sensors and batteries. However, the presence of a tetragonal phase will seriously reduce the conductivity of Y-PSZ materials. As a sintering aid, Bi2O3 can be used to sinter materials with high oxygen ion conductivity at low temperatures. It is the first choice for the Y-PSZ doped system. A new microwave sintering technique prepared Bi2O3–Y-PSZ powders. The effects of doping amount of Bi2O3 on the microstructure, phase transition, and tetragonal phase content of Y-PSZ during sintering were researched. The results displayed that doping Bi2O3 improved the tetragonal phase content of the ZrO2. The tetragonal phase content of the samples increased from 59.72% to 94.69% after sintering at 750 °C for 1 h. After doping Bi2O3, the aggregation of the samples reduced gradually, and the particles dispersed evenly. The average particle sizes of raw material and samples doped with different amounts of Bi2O3 were 0.0794 μm, 0.0638 μm, 0.0629 μm, 0.0794 μm, 0.1116 μm, respectively. Therefore, in the doping amount (1 mol%-4 mol%), the Bi2O3 doped Y-PSZ system with 2 mol% has the highest tetragonal phase content, the best dispersion, the smallest average particle size, and the most uniform particle distribution.
Cu–Ce0.8La0.1Sm0.1O2-δ and Cu–Ce0.8Nd0.1Sm0.1O2-δ are studied as anode materials for solid oxide fuel cells with methanol as fuel. The oxygen surface exchange and bulk diffusion coefficients of Ce0.8Sm0.2O2-δ both increase with La and Nd doping. The CH3OH temperature-programmed surface reaction results show that the addition of La and Nd accelerates the chemical oxidation of CH3OH. Furthermore, compared with Cu–Ce0.8Sm0.2O2-δ, the anodes with La and Nd show higher resistance to coking in CH3OH atmosphere. The Cu-based cermet anode exhibits a low catalytic activity for the electrochemical oxidation of H2, and a single cell supported by a Ce0.8Sm0.2O2-δ‑carbonate composite electrolyte with Cu–Ce0.8Sm0.2O2-δ anode exhibits a maximum power density of 160 mW cm−2 at 650 °C using dry hydrogen as fuel. However, the maximum power density reaches 550 mW cm−2 when CH3OH is used as fuel, and further increases to 730 and 830 mW cm−2 with the addition of La and Nd in the anode, respectively. The results indicate that with the promotion of the oxygen activity, the Cu-based cermet is a promising anode material for solid oxide fuel cells using CH3OH as fuel.
Abstract We study damping signatures at the Jiangmen Underground Neutrino Observatory (JUNO), a medium-baseline reactor neutrino oscillation experiment. These damping signatures are motivated by various new physics models, including quantum decoherence, nu(3) decay, neutrino absorption, and wave packet decoherence. The phenomenological effects of these models can be characterized by exponential damping factors at the probability level. We assess how well JUNO can constrain these damping parameters and how to disentangle these different damping signatures at JUNO. Compared to current experimental limits, JUNO can significantly improve the limits on tau(3)/m(3) in the nu(3) decay model, the width of the neutrino wave packet sigma(x), and the intrinsic relative dispersion of neutrino momentum sigma(rel).
Abstract We report the observation of new properties of primary cosmic rays, neon (Ne), magnesium (Mg), and silicon (Si), measured in the rigidity range 2.15 GV to 3.0 TV with 1.8×106 Ne, 2.2×106 Mg, and 1.6×106 Si nuclei collected by the Alpha Magnetic Spectrometer experiment on the International Space Station. The Ne and Mg spectra have identical rigidity dependence above 3.65 GV. The three spectra have identical rigidity dependence above 86.5 GV, deviate from a single power law above 200 GV, and harden in an identical way. Unexpectedly, above 86.5 GV the rigidity dependence of primary cosmic rays Ne, Mg, and Si spectra is different from the rigidity dependence of primary cosmic rays He, C, and O. This shows that the Ne, Mg, and Si and He, C, and O are two different classes of primary cosmic rays.
Abstract The Alpha Magnetic Spectrometer (AMS) is a precision particle physics detector on the International Space Station (ISS) conducting a unique, long-duration mission of fundamental physics research in space. The physics objectives include the precise studies of the origin of dark matter, antimatter, and cosmic rays as well as the exploration of new phenomena. Following a 16-year period of construction and testing, and a precursor flight on the Space Shuttle, AMS was installed on the ISS on May 19, 2011. In this report we present results based on 120 billion charged cosmic ray events up to multi-TeV energies. This includes the fluxes of positrons, electrons, antiprotons, protons, and nuclei. These results provide unexpected information, which cannot be explained by the current theoretical models. The accuracy and characteristics of the data, simultaneously from many different types of cosmic rays, provide unique input to the understanding of origins, acceleration, and propagation of cosmic rays.