Novel Eu3+-activated Ca3Ga2Ge4O14 red-emitting phosphors with high quantum efficiency for plant growth lighting and white LEDs.

In recent years, rare-earth-based phosphors for near-ultraviolet (NUV)-triggered white light emitting diodes (w-LEDs) have become a research hotspot. However, it is still not possible to obtain phosphors with high quantum yield, excellent color purity and multiple applications. Hence, a series of novel Eu3+-activated Ca3Ga2Ge4O14 (CGG) red-emitting phosphors with high quantum efficiency, excellent color purity and good thermal stability were prepared by a high-temperature solid-phase method. All the CGG:Eu3+ phosphors emitted dazzling red emission with excitation at 394 nm. The optimal Eu3+ doping concentration of compounds was 12% with an excellent color purity of 97.89%, and the concentration quenching mechanism was investigated as dipole-dipole interactions. Meanwhile, the synthetic samples exhibited good thermal stability with the activation energy of 0.26 eV. Remarkably, the internal quantum yield of the prepared phosphors reaches 94.26%. Furthermore, the emission spectra of the prepared red-LEDs overlap considerably with the absorption spectra of PR and PFR required for plant growth. The w-LED device emits warm white light with a high color rendering index of 91.64 and an appropriate correlated color temperature of 4808 K. These excellent luminescence properties indicate that the prepared CGG:Eu3+ phosphors exhibit extensive potential for applications in plant growth lighting and white LEDs.

Pressure-Induced Remarkable Spectral Red-Shift in Mn2+ -Activated NaY9 (SiO4 )6 O2 Red-Emitting Phosphors for High-Sensitive Optical Manometry.

To settle the low sensitivity of luminescent manometers, the Mn2+ -activated NaY9 (SiO4 )6 O2 red-emitting phosphors with splendid pressure sensing performances are developed. Excited by 408 nm, the resulting products emit bright red emission originating from 4 T1 (4 G) → 6 A1 transition of Mn2+ , in which the optimal concentration of the activator ion is ≈1 mol%. Moreover, the admirable thermal stability of the developed phosphors is studied and confirmed by the temperature-dependent emission spectra, based on which the activation energy is derived to be 0.275 eV. By analyzing the pressure-dependent Raman spectra, the structural stability of the synthesized compounds at extreme conditions is verified. Furthermore, the designed phosphors exhibit remarkable spectral red-shift at elevated pressure. Especially, as pressure increases from 0.75 to 7.16 GPa, the emission band centroid shifts from 617.2 to 663.4 nm, resulting in a high sensitivity (dλ/dP) of 7.00 nm GPa-1 , whereas the full width at half maximum (FWHM) increases from 83.0 to 110.6 nm, leading to the ultra-high sensitivity (dFWHM/dP) of 10.13 nm GPa-1 . These achievements manifest that the designed red-emitting phosphors are appropriate for ultrasensitive optical manometry. More importantly, the developed manometer is a current global leader in sensitivity, when operating in the band-width mode, that is, FWHM.

Rapid nondestructive detection of peanut varieties and peanut mildew based on hyperspectral imaging and stacked machine learning models.

Moldy peanut seeds are damaged by mold, which seriously affects the germination rate of peanut seeds. At the same time, the quality and variety purity of peanut seeds profoundly affect the final yield of peanuts and the economic benefits of farmers. In this study, hyperspectral imaging technology was used to achieve variety classification and mold detection of peanut seeds. In addition, this paper proposed to use median filtering (MF) to preprocess hyperspectral data, use four variable selection methods to obtain characteristic wavelengths, and ensemble learning models (SEL) as a stable classification model. This paper compared the model performance of SEL and extreme gradient boosting algorithm (XGBoost), light gradient boosting algorithm (LightGBM), and type boosting algorithm (CatBoost). The results showed that the MF-LightGBM-SEL model based on hyperspectral data achieves the best performance. Its prediction accuracy on the data training and data testing reach 98.63% and 98.03%, respectively, and the modeling time was only 0.37s, which proved that the potential of the model to be used in practice. The approach of SEL combined with hyperspectral imaging techniques facilitates the development of a real-time detection system. It could perform fast and non-destructive high-precision classification of peanut seed varieties and moldy peanuts, which was of great significance for improving crop yields.

A new phase of solid iodine with different molecular covalent bonds.

There is a great interest in the behavior of diatomic molecular solids under extremely high-pressure conditions that lead to pressure-induced metallization, molecular dissociation, and formation of atomic phase. The consensus has been that the phase-transition sequence that happened in both solid bromine and iodine is from a molecular phase (phase I), to an incommensurate phase (phase V), and then to an atomic phase (phase II), with increasing pressure. However, a puzzle remains unresolved for both solids: pressure-induced X and Y bands were observed in the Raman spectra in the molecular phase at low pressures, even before the onset of phase V. Here, we suggest a phase for solid iodine in such a low-pressure range (designated as phase I') in which two different covalent intramolecular bonds coexist, based on first-principles calculations and later corroborated by x-ray diffraction experiments. The pressure dependence of the X and Y bands and other vibrational frequencies measured experimentally can be explained nicely by combining the vibrational modes of phase I and phase I'. These results help improve our understanding on the pressure-induced molecular dissociation and metallization in diatomic solids and may shed some light on the investigation of similar phenomena in solid H(2).

Efficacy and safety of acupoint injection therapy for allergic rhinitis: A protocol for systematic review and meta-analysis.

BACKGROUND: Allergic rhinitis (AR), characterized by nasal itching, sneezing, and congestion, is a common disorder of nose. In the United States, AR affects 10% to 20% of adults. The negative impact of the high prevalence of AR has caused a great economic burdens worldwide. Modern Western Medicine mainly treats AR with antihistamine drugs, glucocorticoids, allergic immunotherapy (AIT), but it seriously affects patients compliance because of its long course of treatment, high medical costs and side effect. And now, as an important mean of treating AR, acupoint injection has been widely used in clinics, and has achieved significant efficacy. METHODS AND ANALYSIS: The following databases will be searched for relevant information before July 2020: PubMed, Embase, Cochrane Library, Web of Science, and CNKI. MAJOR RESULTS: scores of Rhinitis Quality of Life (RQLQ), Rhinitis Total Symptom Scores (RTSS). Secondary results: levels of antigen-specific serum immunoglobulin E (IgE), total effective rate, adverse event. Data will be collected independently by 2 researchers, and the risk of bias in meta-analysis will be evaluated according to "Cochrane Handbook for Systematic Reviews of Interventions". All data analysis will be conducted using Review Manager V.5.3. and Stata V.12.0. RESULTS: The curative effect and safety of acupoint injection treatment for AR patients will be evaluated systematically. CONCLUSION: The systematic review of this study will summarize the currently published evidence of acupoint injection treatment for AR to further guide its promotion and application. ETHICS AND DISSEMINATION: The private information from individuals will not be published. This systematic review also will not involve endangering participant rights. Ethical approval is not required. The results may be published in a peer-reviewed journal or disseminated in relevant conferences.Open Science Framework (OSF) registration number: https://osf.io/fa9dq.