Application of sulfonated nanoporous carbons as acid catalysts for Fischer esterification reactions

Heterogeneous acid catalysts were prepared by sulfonation of nanoporous carbons (NPCs). The NPCs were produced by pyrolysis of resorcinol–formaldehyde nanoporous resins (NPRs). The NPRs were synthesized as wet gels by condensation of resorcinol and formaldehyde in a sol–gel polycondensation using Na2CO3 as catalyst. A cationic polyelectrolyte (poly(diallyl dimethyl ammonium chloride)) was used as pore stabilizer, allowing to dry the gels in air without any special procedures. Five NPRs with different properties were synthesized by varying the monomer to catalyst ratio (Resorcinol/Na2CO3, R/C). The morphological and textural characterizations of the NPCs were performed by scanning electron microscopy and nitrogen adsorption–desorption isotherms. The results indicate that using a molar ratio of R/C = 200, a nanoporous carbon NPC with large surface area (695 m2/g) is obtained. This NPC was sulfonated by reaction with three different sulfonating agents: (i) concentrated sulfuric acid; (ii) fuming sulfuric acid and (iii) chlorosulfonic acid in order to obtain a novel Fischer esterification catalyst. The amount of acid groups attached to the NPC surface was determined by titration using a modified Boehm method. The catalytic activity, for Fischer esterification reaction of different sulfonated NPCs, was compared with sulfonated NPRs, sulfonated commercial porous carbons and polymeric acid catalyst (cationic ion exchange resins, sulfonated fluoropolymers). The modification of NPCs with concentrated sulfuric acid seems to render the materials with more catalytic activity. The best sulfonated material NPC (PC200-H2SO4) shows a high catalytic activity for the esterification of acetic acid (90.8%) and oleic acid (60.6%) with ethanol. The conversion and conversion rate values are better than commercial acid catalysts. The results suggest that sulfonated NPC catalysts are promising materials for the synthesis of biodiesel and related reactions

Case study of intracranial EEG records of patients with focal cortical dysplasia type I and II

In this study we try to find out if it is possible to differentiate type of focal cortical dysplasia by features obtained from intracranial EEG. We compare occurrence and rates of three biomarkers present in epilepsy in patients with focal cortical dysplasia type I and II. Case study is made on long term night records of 6 pediatric patients. Detection of interictal epileptiform discharges and high-frequency oscillations is made by automated algorithms, delta brush are marked visually. Position of lesion and electrodes inside were obtained from MRI. In individual rates were not found difference on significant level. No major significance were found, but as promising seem to be ratio inside to outside rates of high-frequency oscillations and presence of delta brush, which were found only in patients with focal cortical dysplasia type II

Enhanced polysulphide redox reaction using a RuO₂ nanoparticle-decorated mesoporous carbon as functional separator coating for advanced lithium–sulphur batteries

A multi-functional RuO₂ nanoparticle-embedded mesoporous carbon-coated separator is used as an electrocatalytic and adsorbing polysulphide-net to enhance the redox reaction of migrating polysulphides, to improve active material utilization and boost the electrochemical performance of lithium–sulphur batteries

RESEARCH MOTC WITH EXAMPLES: AN INTERACTIVE AID FOR MULTIDIMENSIONAL HYPOTHESIS GENERATION

This paper reports on conceptual development in the areas of database mining, and knowledge discovery in databases (KDD). Our efforts have also led to a prototype implementation, called MOTC, for exploring hypothesis space in large and complex data sets. Our KDD conceptual development rests on two main principles. First, we use the crosstab representation for working with qualitative data. This is by now standard practice in OLAP (on-line analytical processing) applications and we reaffirm it with additional reasons. Second, and innovatively, we use Prediction Analysis as a measure of goodness for hypotheses. Prediction Analysis is an established statistical technique for analysis of associations among qualitative variables. It generalizes and subsumes a large number of other such measures of association, depending upon specific assumptions the user is willing to make. As such, it provides a very useful framework for exploring hypothesis space in a KDD context. The paper illustrates these points with an extensive discussion of MOTC