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Phase equilibria of carbon dioxide (CO2) hydrate in aqueous solutions of N-methyldiethanolamine (MDEA) at four different mass fractions (5, 10, 15, and 25 wt %) in the temperature range of 274.01 to 281.93 K and pressure range of 1.79 to 4.34 MPa were experimentally investigated by adopting an isochoric pressure search method. The reliability and accuracy of our experimental apparatus and method were examined by comparing the measured data with published ones. The enthalpy of CO2hydrate dissociation was calculated by the Clausius–Clapeyron equation. The experimental results showed that MDEA acted as a thermodynamic inhibitor which could suppress the equilibrium line of CO2hydrate to lower temperatures or higher pressures. The thermodynamic inhibition effect was enhanced after increasing the mass fraction. However, it was weaker than the conventional thermodynamic inhibitors of ethylene glycol (EG) and sodium chloride (NaCl). MDEA had synergistic inhibition effects with EG and NaCl, as their mixtures had stronger thermodynamic inhibition performance. The average enthalpies of CO2hydrate dissociation in the presence of MDEA (5 to 25 wt %) were found to be in the range of 67.562 to 80.776 kJ·mol–1, which were very close to that of pure water. The research results have theoretical guidance for the flow assurance of natural gases.

In recent years, low-dimensional organic–inorganic hybrid metal halides (OIHMHs) have shown excellent photophysical properties due to their quantum structure, adjustable energy levels, and energy transfer between inorganic and organic components, which have attracted extensive attention from researchers. Herein, we synthesize a zero-dimensional (0D) OIHMH, Sb3+:(Gua)3InCl6, by introducing Sb3+into (Gua)3InCl6, which undergoes a significant enhancement of the emission peak at 580 nm with the photoluminescence quantum yield (PLQY) boosted from 17.86 to 95.72% when excited at 340 nm. This boost in photoluminescence of the doped sample was studied by combining ultrafast femtosecond transient absorption, temperature-dependent photoluminescence (PL) spectra, and density functional theory (DFT) calculation, revealing the process of self-trapped exciton (STE) recombination to emit light at both Sb and In sites in this 0D structure simultaneously. This material with the lowest dark STE level at the In site for emission in the undoped sample can amazingly yield very strong emission in the doped sample, which has never been observed before. Finally, we tested its application in a photoelectric device. This work not only helps to gain a deeper understanding of the formation of STEs in In-based halides but also plays a certain guiding role in the design of new luminescent materials.

Historical data scarce and varying patterns of new built run-off small hydropower (RSHP) limits precise power generation prediction. Unforeseen hydropower can induce uneconomic power grid operations. To address this issue, a novel transfer learning method enabling integration of public RSHP knowledge is proposed. First, a RSHP data matching algorithm is proposed to pre-filter similar source domain data and produce a RSHP database matching patterns of target RSHP. This algorithm allows us to improve performance of transfer learning model. Next, public prediction knowledge implicated in the RSHP database is learned towards a CNN-BiLSTM hybrid pre-trained network. Then, the pre-trained network is transferred to the target RSHP prediction models by hyper-parameter fine-tuning algorithm, which reduces divergence between the pre-trained network outputs and the target domain data. As a result, accurate new RSHP prediction models can be generated under the challenge of data lack. At the last, the RSHP prediction models are fed back to the fine-tuning algorithm such that generalizability of the models enables life-long self-renewal. The real-world case demonstrates the superiority of the proposed method in terms of accuracy and data utilization. The average prediction error of the proposed method is 16.27% lower than the best traditional alternative.