Adsorptive removal of dichlorophenoxyacetic acid (2,4-D) using novel nanoparticles based on cationic surfactant-coated titania nanoparticles.

A novel nanomaterial based on cationic surfactant-coated TiO2 nanoparticle (CCTN) was systematically fabricated in this work. Synthesized titania nanoparticles were thoroughly characterized by XRD, FT-IR, HR-TEM, TEM-EDX, SEM with EDX mapping, BET, and ζ potential measurements. The adsorption of cationic surfactant, cetyltrimethylammonium bromide (CTAB), on TiO2 was studied under various pH and ionic strength conditions. Adsorption of CTAB on TiO2 increased with ionic strength increment in the presence of hemimicelle monolayer structure, indicating that nonelectrostatic and electrostatic forces control CTAB uptake. CTAB adsorption isotherms on TiO2 were according to a two-step model. Potential application in pesticide removal of 2,4-dichorophenoxy acetic acid (2,4-D) using CCTN was also studied. Optimum parameters for 2,4-D treatment through adsorption technique were pH 5, adsorption time of 120 min, and CCTN dosage of 10 mg·mL-1. Very low 2,4-D removal efficiency using TiO2 without CTAB coating was found to be approximately 28.5% whereas the removal efficiency was up to about 90% by using CCTN under optimum conditions, and the maximum adsorption capacity of 12.79 mg·g-1 was found. Adsorption isotherms of 2,4-D on CCTN were more suitable with the Langmuir model than Freundlich. Adsorption mechanisms of 2,4-D on CCTN were mainly governed by Columbic attraction based on isotherms and surface charge changes.

Sulfur-DMSO promoted oxidative coupling of active methylhetarenes with amines: access to amides.

The elemental sulfur-DMSO couple was found to efficiently promote the oxidative coupling of active methylhetarenes with amines to yield amides under simple heating conditions. When 2-methylquinoline was used as the methylhetarene component, the formation of the expected 2-quinolinecarboxamides from anilines could be efficiently catalyzed by iron, nickel and cobalt salts. The method displayed good functional group tolerance and was applicable to aromatic, heteroaromatic and aliphatic amines. Other substrates such as phenylacetic acid, dibenzyl disulfide, and benzylamine could act as competent partners in place of methylhetarenes.

CASD-NMR 2: robust and accurate unsupervised analysis of raw NOESY spectra and protein structure determination with UNIO.

UNIO is a comprehensive software suite for protein NMR structure determination that enables full automation of all NMR data analysis steps involved--including signal identification in NMR spectra, sequence-specific backbone and side-chain resonance assignment, NOE assignment and structure calculation. Within the framework of the second round of the community-wide stringent blind NMR structure determination challenge (CASD-NMR 2), we participated in two categories of CASD-NMR 2, namely using either raw NMR spectra or unrefined NOE peak lists as input. A total of 15 resulting NMR structure bundles were submitted for 9 out of 10 blind protein targets. All submitted UNIO structures accurately coincided with the corresponding blind targets as documented by an average backbone root mean-square deviation to the reference proteins of only 1.2 Å. Also, the precision of the UNIO structure bundles was virtually identical to the ensemble of reference structures. By assessing the quality of all UNIO structures submitted to the two categories, we find throughout that only the UNIO-ATNOS/CANDID approach using raw NMR spectra consistently yielded structure bundles of high quality for direct deposition in the Protein Data Bank. In conclusion, the results obtained in CASD-NMR 2 are another vital proof for robust, accurate and unsupervised NMR data analysis by UNIO for real-world applications.