Upconversion (UC) based luminescent materials have promising applications in noncontact temperature sensors. How to improve the sensitivity is one main object at present. This work presented several ...strategies for optical temperature sensing based on UC spectra of the Y2WO6:Yb3+-Er3+/Ho3+/Tm3+ phosphors. The improvement for the relative (S R) and absolute (S A) sensitivities were discussed by using a fluorescence intensity ratio technique. It includes thermally coupled levels (TCLs) and non-TCLs. It was proposed that a piecewise expression could be employed to achieve high S A value for TCLs. However, improving the S R value is limited for TCLs. With regard to the non-TCLs, S R and S A are not restricted, but not easy to be improved synchronously. On the other hand, the morphology and UC spectra of the samples were also studied. The above investigation could be instructive to develop new luminescent materials with high sensitivity.
Functionalized Fe-TCNQ monolayers serve as high-performance bifunctional ORR/OER catalysts.
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•A low limiting overpotential of 0.33 V for Fe-TCNQ is predicted toward ORR.•The catalytic ...performance of Ni-TCNQs monolayer is identified as the highest for OER.•By grafting ligands and applying strain, the adsorption strengths can be optimized.•Fe-TCNQ-Cl is predicted as high-activity bifunctional ORR/OER catalysts.
The identification of catalytically active and stable bifunctional electrocatalysts for the oxygen reduction and evolution reaction (ORR/OER) would revolutionize rechargeable metal-air batteries and regenerative fuel cell technologies. In this study, we use density functional theory (DFT) calculations to systemically investigate 2D transition metal based tetracyanoquinodimethane (TM–TCNQ, TM = Cr-Cu, Ru-Ag, Pt, Ir) monolayers with single TM atoms catalysts (SACs) distributed periodically with high density. We calculate a lower limiting overpotential of ηlim = 0.33 V for Fe-TCNQ yielding a higher expected activity than that of Pt metal (0.48 V) for the ORR under acidic conditions. The catalytic performance of Fe-TCNQ for OER is, however, surpassed by Ni-TCNQs (ηlim = 0.46 V), which is identified as the highest among the candidates. By applying grafting axial ligands and external strain, the adsorption strength of reaction intermediates on TM reactive sites can be further optimized and enhances the activities of Mn-, Fe- and Ni-TCNQs for the ORR or the OER. Here, Fe-TCNQ-Cl (ηlim = 0.27/0.55 V), followed by Fe-TCNQ-CO (ηlim = 0.67/0.43 V), are predicted as novel, high-performance bifunctional ORR/OER catalysts with comparable limiting overpotentials to those of the best commercially used electrocatalysts, Pt (ORR: ηlim = 0.48 V) and RuO2 (OER: ηlim = 0.42 V). In addition, the recently synthesized Fe-TCNQ possess excellent conductivity with fast electron transfer during the catalytic reactions. These results show 2D TM-TCNQ monolayers are durable, low-cost, and efficient catalysts for the ORR and the OER in metal-air batteries and fuel cells.
The N-doped Sr2.985Mg1-ySi2O8:0.005Eu2+,0.01Dy3+,yMn2+ (0 ≤ y ≤ 0.15) phosphors were designed to obtain long-persistent phosphors for white LEDs. All the samples were determined to be single-phase by ...XRD analysis. The particles show smooth surface with the help of the H3BO3 flux. The energy-dispersive X-ray spectrum indicates the existence of N element. Various Eu2+ emission centers have been gained and verified by the photoluminescence spectra and long-persistent emission spectra, and a red-shift of the Eu2+ emission was observed in the N-doped samples due to the nephelauxetic effect. In Eu2+-Mn2+ co-activated phosphors, tunable emission has been realized and an efficient energy transfer from Eu2+ to Mn2+ was found, which could belong to the dipole-dipole interaction mechanism. The optimal afterglow time was obtained in the Sr2.985MgSi2O7.76N0.16:0.005Eu2+,0.01Dy3+ sample, but doping Mn2+ reduces the afterglow time largely. The mechanism for the increase of luminescence intensity and afterglow time with N present was interpreted. The temperature-dependent luminescence was also evaluated.
Because of the electron deficiency, freestanding honeycomb borophene (HB) is predicted to be kinetically unstable. Very recently, the honeycomb phase of two-dimensional boron, nevertheless, has been ...surprisingly synthesized via a molecular beam epitaxy method on Al(111) (Sci. Bull. 2018, 63, 282–286). The mechanism underlying the enhanced stability of the supported HB remains unclear. Here, we comprehensively investigate the structural, energetic, electronic, and lattice dynamic properties of HB supported on Al(111) via ab initio calculations. Our calculations reveal a strong adhesion energy between the HB and the Al(111) substrate ∼1.05 eV/atom, which is significantly stronger than the interaction between graphene and any transition-metal surfaces that have been studied before. The strong interaction can be elucidated by the charge donation/back donation as well as the strong covalent bonding interactions between the HB and the substrate. Such a strong adhesive interaction stabilizes the supported HB, whose kinetic stability is further validated by the direct calculation of phonon dispersion.
We theoretically demonstrate the mechanically mediated electromagnetically induced transparency in a two-mode cavity optomechanical system, where two cavity modes are coupled to a common mechanical ...resonator. When the two cavity modes are driven on their respective red sidebands by two pump beams, a transparency window appears in the probe transmission spectrum due to destructive interference. Under this situation the transmitted probe beam can be delayed as much as 4 μs, which can be easily controlled by the power of the pump beams.
A series of Yb3+-Er3+, Yb3+-Ho3+, and Yb3+-Tm3+ doped Ca2Gd8(SiO4)6O2 (CGS) phosphors were synthesized by solid-state reaction method, and their upconversion (UC) luminescence properties for ...temperature sensing were studied. Upon 980 nm excitation, the green and red emissions of Er3+ were observed, and the optimal Er3+ concentration was determined to be 3 mol%. For the CGS:10%Yb3+,yHo3+ phosphors, three emission peaks in the green, red and near-infrared region appear. It was found that the relative intensities of Ho3+ different emissions change with Ho3+ concentration, which has been explained by the cross-relaxation process. The strongest Tm3+ emission appeared at 790 nm, attributed to the 3H4-3H6 transition. The optimal Tm3+ concentration was determined to be 0.5 mol%. The temperature sensing behavior was evaluated by employing the thermally-coupled or non-thermally coupled levels of Er3+, Ho3+ and Tm3+. The maximum sensitivities obtained are 3.71×10−3 and 1.12 K-1 for CGS:10%Yb3+,3%Er3+, 0.111 K-1 for CGS:10%Yb3+,3%Ho3+ and 3.3×10−4 K−1 for CGS:10%Yb3+,0.5%Tm3+, respectively. The high sensitivities indicate the present phosphors could have potential application in temperature sensing.
•Different strategies for temperature sensing were introduced in the present phosphors.•The present phosphors show smooth particle surface that benefits the UC luminescence.•High sensor sensitivity has been obtained in the CGS:Yb3+-Er3+/Ho3+/Tm3+.•The present phosphors could have potential application in optical temperature sensors.
Depressive disorder (DD) has become one of the most common mental diseases, seriously endangering both the affected person’s psychological and physical health. Nowadays, a DD diagnosis mainly relies ...on the experience of clinical psychiatrists and subjective scales, lacking objective, accurate, practical, and automatic diagnosis technologies. Recently, electroencephalogram (EEG) signals have been widely applied for DD diagnosis, but mainly with high-density EEG, which can severely limit the efficiency of the EEG data acquisition and reduce the practicability of diagnostic techniques. The current study attempts to achieve accurate and practical DD diagnoses based on combining frontal six-channel electroencephalogram (EEG) signals and deep learning models. To this end, 10 min clinical resting-state EEG signals were collected from 41 DD patients and 34 healthy controls (HCs). Two deep learning models, multi-resolution convolutional neural network (MRCNN) combined with long short-term memory (LSTM) (named MRCNN-LSTM) and MRCNN combined with residual squeeze and excitation (RSE) (named MRCNN-RSE), were proposed for DD recognition. The results of this study showed that the higher EEG frequency band obtained the better classification performance for DD diagnosis. The MRCNN-RSE model achieved the highest classification accuracy of 98.48 ± 0.22% with 8–30 Hz EEG signals. These findings indicated that the proposed analytical framework can provide an accurate and practical strategy for DD diagnosis, as well as essential theoretical and technical support for the treatment and efficacy evaluation of DD.
This work suggests a theoretical principle about the oscillation signal decomposition, which is based on the requirement of a pure oscillation component, in which the mean zero is extracted from the ...signal. Using this principle, the validity and robustness of the empirical mode decomposition (EMD) method are first proved mathematically. This work also presents a modified version of EMD by the interpolation solution, which is able to improve the frequency decomposition of the signal. The result shows that it can provide a primary theoretical basis for the development of EMD. The simulation signal verifies the effectiveness of the EMD algorithm. At the same time, compared with the existing denoising algorithm, it has achieved good results in the denoising of rolling bearing fault signals. It contributes to the development and improvement of adaptive signal processing theory in the field of fault diagnosis. It provides practical value research results for the rapid development of adaptive technology in the field of fault diagnosis.
While graphene nanoribbons are prone to twist intrinsically, the effect of local twist on the electromechanical properties remains unexplored. By using the density functional theory in combination ...with the nonequilibrium Green’s function method, we investigate the responses of structural evolution and electrical transport of armchair graphene nanoribbons to local torsion. We show that local twist can alter their transport properties significantly. The current at a given bias can switch on/off or change many times with twist angle, which is related with twist-induced changes in electronic structures of graphene nanoribbons. Our results can provide a valuable guideline for design and implementation of graphene nanoribbons in nanoelectromechanical systems and devices.
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