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• Microreactor benefited greatly the azidation as a key step for zidovudine synthesis. • Azidation system was simplified with the use of less chemicals and enhanced safety. • Microreactor reached a 360-fold increase in the azidation rate than batch reactor. • A complete kinetic model was established and accorded with the reaction mechanism. • Validation experiments show accuracy of kinetic model and its potential application. Zidovudine, i.e., AZT, is an indispensable anti-AIDS drug for highly active antiretroviral therapy. The azidation step is of the most vital importance in the synthetic route of zidovudine. Herein we report the use of microreactors in combination with the simplified azidation system instead of conventional batch reactors, with reducing the usage of solvent and hazardous chemicals, avoiding risk of explosion and increasing process efficiency. First, effects of various parameters such as volumetric flow rate, microreactor diameter, reactant concentration, reaction temperature and residence time on the azidation process were systematically studied. Compared with the batch reactor, the continuous-flow microreactor could achieve comparable AZT-C yield (i.e., 89%) at much shorter time (10 min) under the condition optimized by experimental parameter screening. The reaction rate of the azidation in the microreactor was 360 times faster than that in the batch reactor. Then, the reaction order of each reactant, pre-exponential factors and activation energy values for both the main and side reactions were determined. On the basis of the kinetic study, the reaction mechanism of the azidation from AZT-B to AZT-C was proved for the first time. Finally, we designed a series of validation experiments to show the accuracy of the obtained reaction kinetics, with the indication of its use for the further process optimization and scale-up. [ABSTRACT FROM AUTHOR]

For K-distributed sea clutter, a constant false alarm rate (CFAR) is crucial as a desired property for automatic target detection in an unknown and non-stationary background. In multiple-target scenarios, the target masking effect reduces the detection performance of CFAR detectors evidently. A machine learning based processor, associating the artificial neural network (ANN) and a clustering algorithm of density-based spatial clustering of applications with noise (DBSCAN), namely, DBSCAN-CFAR, is proposed herein to address this issue. ANN is trained with a symmetrical structure to estimate the shape parameter of background clutter, whereas DBSCAN is devoted to excluding interference targets and sea spikes as outliers in the leading and lagging windows that are symmetrical about the cell under test (CUT). Simulation results verified that the ANN-based method provides the optimal parameter estimation results in the range of 0.1 to 30, which facilitates the control of actual false alarm probability. The effectiveness and robustness of DBSCAN-CFAR are also confirmed by the comparisons of conventional CFAR processors in different clutter conditions, comprised of varying target numbers, shape parameters, and false alarm probabilities. Although the proposed ANN-based DBSCAN-CFAR processor incurs more elapsed time, it achieves superior CFAR performance without a prior knowledge on the number and distribution of interference targets. [ABSTRACT FROM AUTHOR]

• Side reaction in the DTG-7 demethylation process was analyzed for the first time. • Reaction kinetic model of the DTG-7 demethylation process was developed. • An operating window was established for process optimization. • High selectivity and DTG yield were achieved by precise operation control. Demethylation of DTG-7 (i.e., an intermediate of an anti-HIV medication dolutegravir (DTG)) is the final step in the DTG synthesis, but its reaction network and kinetic investigations have not been reported yet. In this work, we established the reaction kinetic model of this system based on experimental data from microreactors, according with the demethylation mechanism of the complex ion formation and transformation examined by density functional theory (DFT) calculation. Due to limited solubility of the intermediate product (i.e., organolithium), various parameters were screened to reach a high DTG yield of 98.5 % at a residence time of 12 min without microreactor clogging. Detailed kinetic investigation of DTG-7 demethylation and ring-opening side reaction revealed that precise control over the temperature and residence time in the cascade microreactor system facilitated high selectivity and DTG yield with short residence times. Finally, an operating window was established for process optimization based on the kinetic model. [ABSTRACT FROM AUTHOR]