Publications by authors named "Qinglong Zhou"

Benzothiadiazine-1-oxide scaffolds with -stereogenic centers are prevalent in bioactive and pharmaceutical molecules. Reported works mainly focused on the metal-catalyzed asymmetric C-H amination/cyclization reaction for the synthesis of benzothiadiazine-1-oxides. Here, we reported a chiral phosphoric acid-catalyzed kinetic resolution of sulfoximines, providing chiral benzothiadiazine-1-oxides and recovered chiral sulfoximines with moderate to good enantioselectivities ( factors up to 36.

View Article and Find Full Text PDF

The development of catalytic asymmetric reaction with water as the reactant is challenging due to the reactivity- and stereoselectivity-control issues resulted from the low nucleophilicity and the small size of water. We disclose herein a chiral phosphoric acid (CPA) catalyzed atroposelective ring-opening reaction of biaryl oxazepines with water. A series of biaryl oxazepines undergo the CPA catalyzed asymmetric hydrolysis in a highly enantioselective manner.

View Article and Find Full Text PDF

Sulfilimines are key intermediates to common motifs in medicines and agrochemicals. Typically, this class of compounds are prepared by imidation of thioethers, transition-metal-catalyzed or base-promoted sulfur alkylation and transition-metal-catalyzed sulfur arylation. Here, we report a practical and efficient base-mediated sulfur arylation reaction for the preparation of sulfilimines.

View Article and Find Full Text PDF

Sweet potato vine, the byproduct of sweet potato, has a high nutritional value. Silage is an effective solution for nutrient preservation. This article explored the effects of sweet potato vine silage (SPVS) supplementation on meat quality, antioxidant capacity and immune function in finishing pigs.

View Article and Find Full Text PDF
Article Synopsis
  • The paper focuses on improving pollution control in combined thermal power (CHP) production by predicting emissions directly from the source rather than using post-treatment methods.
  • It introduces a pollution emission prediction method that combines feature engineering and a hybrid deep learning model, which processes data to identify key factors while eliminating unnecessary variables.
  • A case study demonstrates that this method effectively reduces prediction errors, outperforming existing techniques through seasonal analysis of the data collected, achieving a root mean square error of less than one.
View Article and Find Full Text PDF