3D photon counting imaging at 1550 nm with 1.5-GHz sine-wave-gated InGaAs/InP GAPD

We demonstrated a 3D laser imaging system at 1550 nm with a 1.5-GHz sine-wave gated Geiger-mode InGaAs/InP avalanche photodiode (APD). An optical fiber bundle with 100 individual fiber outputs was implemented at the focal plane of the telescope, providing a 2.5-mrad imaging view. The system used single-pixel near-infrared single-photon detector to measure photons at fiber outputs instead of a photon counting array. The 1.5-GHz gated Geiger-mode InGaAs/InP APD with a timing jitter of 290 ps was operated in quasi-continuous mode with detection efficiency of ∼4.3%. We achieved higher than 6-cm surface-to-surface resolution at single-photon level, showing a potential of low-energy and eye-safe laser imaging system for long-distance measurements.     

Screening of drugs of abuse and toxic compounds in human whole blood using online solid‐phase extraction and high‐performance liquid chromatography with time‐of‐flight mass spectrometry

A novel method for the screening of 151 drugs of abuse and toxic compounds in human whole blood has been developed and validated by online solid‐phase extraction with liquid chromatography coupled to time‐of‐flight mass spectrometry. Analytes were extracted and separated by using a fully automated online solid‐phase extraction liquid chromatography system with total chromatographic run time of 26 min. Time‐of‐flight mass spectrometry screening of 151 drugs of abuse and toxic compounds was performed in a full‐scan (m/z 50–800) mode using an MS^E acquisition of molecular ions and fragment ions data at two collision energies (one was 6 eV and another one was in the range of 5–45 eV). The compounds were identified based on retention times and exact mass of molecular ions and fragment ions. The limit of detection ranged from 1 to 100 ng/mL and the recovery of the method ranged from 6.3 to 163.5%. This method is proved to be a valuable screening method allowing fast and specific identification of drugs in human whole blood.     

Development of an enzyme‐linked immunosorbent assay and immunoaffinity chromatography for glycyrrhizic acid using an anti‐glycyrrhizic acid monoclonal antibody

In this work, a new monoclonal antibody specific for glycyrrhizic acid was prepared and characterized. A hybridoma secreting an anti‐glycyrrhizic acid monoclonal antibody was produced by fusing splenocytes from a mouse immunized against a glycyrrhizic acid–bovine serum albumin conjugate with the hypoxanthine–aminopterin–thymidine‐sensitive mouse myeloma cell line (Sp2/0‐Ag14). Subsequently, an indirect, competitive enzyme‐linked immunosorbent assay for glycyrrhizic acid was developed using the monoclonal antibody. In this assay, we detected an effective measuring range of 78.12–2500 ng/mL. Both intra‐assay and inter‐assay repeatability and precision were achieved, with relative standard deviations lower than 10%. In addition, glycyrrhizic acid levels in both formulated Chinese medicines and biological samples were determined with high sensitivity and efficiency. We then successfully developed a reliable immunoaffinity chromatography to separate glycyrrhizic acid completely from its parent medicine. These methods will contribute to further research investigations to better understand the interactions of glycyrrhizic acid with other drugs in the complex system of traditional Chinese medicine.     

Separation of five compounds from leaves of Andrographis paniculata (Burm. f.) Nees by off‐line two‐dimensional high‐speed counter‐current chromatography combined with gradient and recycling elution

An off‐line two‐dimensional high‐speed counter‐current chromatography method combined with gradient and recycling elution mode was established to isolate terpenoids and flavones from the leaves of Andrographis paniculata (Burm. f.) Nees. By using the solvent systems composed of n‐hexane/ethyl acetate/methanol/water with different volume ratios, five compounds including roseooside, 5,4′‐dihydroxyflavonoid‐7‐O‐β‐d ‐pyranglucuronatebutylester, 7,8‐dimethoxy‐2′‐hydroxy‐5‐O‐β‐d ‐glucopyranosyloxyflavon, 14‐deoxyandrographiside, and andrographolide were successfully isolated. Purities of these isolated compounds were all over 95% as determined by high‐performance liquid chromatography. Their structures were identified by UV, mass spectrometry, and ¹H NMR spectroscopy. It has been demonstrated that the combination of off‐line two‐dimensional high‐speed counter‐current chromatography with different elution modes is an efficient technique to isolate compounds from complex natural product extracts.     

Effects of some nucleating agents on the supercooling of erythritol to be applied as phase change material

Nine nucleating agents, calcium pimelate (CaPi), bicyclic [1, 2, 2]heptane di-carboxylate (HPN-68), a commercially obtained aryl amide nucleating agent (TMB-5), calcium salt of hexahydrophthalic acid (HPN-20E), 1,3:2,4-di-p-methylbenzylidene sorbitol (MDBS) and sodium, potassium, magnesium and calcium salt of benzene-1, 3, 5-tricarboxylic acid (Na₃BTC, K₃BTC, Mg₃BTC₂ and Ca₃BTC₂, respectively), were applied to reduce the supercooling of erythritol, and their effects were investigated by cyclic differential scanning calorimetry (DSC). The results revealed that Na₃BTC and K₃BTC could not induce erythritol to crystallize under the experiment condition. MDBS could only make erythritol to crystallize at a temperature slightly higher than that of pure erythritol, and the effect was unstable. Mg₃BTC₂, Ca₃BTC₂ and HPN-68 could induce erythritol to crystallize at relatively high temperature, but the peak temperature of crystallizing (T _{p, cr}) and the phase change enthalpy of crystallizing (Δ_cr H) decreased greatly as the melting–crystallizing cycles increased. HPN-20E-doped erythritol crystallized at a high temperature with the T _{p, cr} of 69.3 °C at the first cycle, but the T _{p, cr} and Δ_cr H varied greatly during the melting–crystallizing cycles. CaPi and TMB-5 could induce erythritol to crystallize at a stable temperature with the T _{p, cr} of about 69 °C and 64 °C, respectively, and with a stable Δ_cr H of about 204 and 185 J g^?1, respectively, in all melting–crystallizing cycles. Hence, CaPi- and TMB-5-doped erythritol could be used as PCMs and applied in thermal energy storage in which the energy was absorbed at a high temperature and released at a lower but stable temperature.     

Thermal properties characterization of two promising phase change material candidates

Solar absorption cooling is a wonderful method to provide cold energy by exploiting solar energy. Phase change materials (PCMs) that store latent thermal energy are indispensible in solar absorption cooling system. It is worthwhile to find new PCMs due to the demanding on the temperature of the stored thermal energy which in turn would power the absorption chiller. In this paper, two compounds: 1-bromo-2-methoxynaphthalene (compound 1) and 2,2′-diphenyl-4,4′-bi(1,3-dioxane)-5,5′-diol (compound 2), were selected as potential PCMs. Their thermal energy storage properties and thermal stability were characterized by differential scanning calorimetry and thermogravimetric analysis. The results showed that both compounds could be applied as good PCMs in solar absorption cooling systems. Compound 1 melted at 356.82 K with the ΔH of 98.81 J g^?1, while compound 2 melted in a broad temperature range with the melting point of 466.26 K and the ΔH of 101.4 J g^?1. Both compounds exhibited good thermal stability. Furthermore, the molar specific heat capacities of these two compounds were measured by temperature-modulated differential scanning calorimetry from 198.15 K to the temperature that they started to decompose, and the thermodynamic functions of [H _T–H _298.15] and [S _T–S _298.15] were calculated based on the specific heat capacities data.     

Self-Optimization of the Active Site of Molybdenum Disulfide by an Irreversible Phase Transition during Photocatalytic Hydrogen Evolution

The metallic 1T-MoS₂ has attracted considerable attention as an effective catalyst for hydrogen evolution reactions (HERs). However, the fundamental mechanism about the catalytic activity of 1T-MoS₂ and the associated phase evolution remain elusive and controversial. Herein, we prepared the most stable 1T-MoS₂ by hydrothermal exfoliation of MoS₂ nanosheets vertically rooted into rigid one-dimensional TiO₂ nanofibers. The 1T-MoS₂ can keep highly stable over one year, presenting an ideal model system for investigating the HER catalytic activities as a function of the phase evolution. Both experimental studies and theoretical calculations suggest that 1T phase can be irreversibly transformed into a more active 1T′ phase as true active sites in photocatalytic HERs, resulting in a “catalytic site self-optimization”. Hydrogen atom adsorption is the major driving force for this phase transition.     

A self‐adaptive intelligence gray prediction model with the optimal fractional order accumulating operator and its application

The self‐adaptive intelligence gray predictive model (SAIGM) has an alterable‐flexible model structure, and it can build a dynamic structure to fit different external environments by adjusting the parameter values of SAIGM. However, the order number of the raw SAIGM model is not optimal, which is an integer. For this, a new SAIGM model with the fractional order accumulating operator (SAIGM_FO) was proposed in this paper. Specifically, the final restored expression of SAIGM_FO was deduced in detail, and the parameter estimation method of SAIGM_FO was studied. After that, the Particle Swarm Optimization algorithm was used to optimize the order number of SAIGM_FO, and some steps were provided. Finally, the SAIGM_FO model was applied to simulate China's electricity consumption from 2001 to 2008 and forecast it during 2009 to 2015, and the mean relative simulation and prediction percentage errors of the new model were only 0.860% and 2.661%, in comparison with the ones obtained from the raw SAIGM model, the GM(1, 1) model with the optimal fractional order accumulating operator and the GM(1, 1) model, which were (1.201%, 5.321%), (1.356%, 3.324%), and (2.013%, 23.944%), respectively. The findings showed both the simulation and the prediction performance of the proposed SAIGM_FO model were the best among the 4 models.