Abstract
Pd-based catalyst treatment represents an emerging technology that shows promise to remove nitrate and nitrite from drinking water. In this work we use vapor-grown carbon nanofiber (CNF) supports in order to explore the effects of Pd nanoparticle size and interior versus exterior loading on nitrite reduction activity and selectivity (i.e., dinitrogen over ammonia production). Results show that nitrite reduction activity increases by 3.1-fold and selectivity decreases by 8.0-fold, with decreasing Pd nanoparticle size from 1.4 to 9.6 nm. Both activity and selectivity are not significantly influenced by Pd interior versus exterior CNF loading. Consequently, turnover frequencies (TOFs) among all CNF catalysts are similar, suggesting nitrite reduction is not sensitive to Pd location on CNFs nor Pd structure. CNF-based catalysts compare favorably to conventional Pd catalysts (i.e., Pd on activated carbon or alumina) with respect to nitrite reduction activity and selectivity, and they maintain activity over multiple reduction cycles. Hence, our results suggest new insights that an optimum Pd nanoparticle size on CNFs balances faster kinetics with lower ammonia production, that catalysts can be tailored at the nanoscale to improve catalytic performance for nitrite, and that CNFs hold promise as highly effective catalyst supports in drinking water treatment. © 2012 American Chemical Society.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 2847-2855 |
| Number of pages | 9 |
| Journal | Environmental Science & Technology |
| Volume | 46 |
| Issue number | 5 |
| DOIs | |
| State | Published - Feb 16 2012 |
| Externally published | Yes |
Bibliographical note
KAUST Repository Item: Exported on 2020-10-01Acknowledgements: This work was primarily supported by Water CAMPWS, a Science and Technology Center program of the National Science Foundation under agreement number CTS-0120978, and partially by King Abdullah University of Science and Technology. TEM and STEM analysis were carried out in part at the Frederick Seitz Materials Research Laboratory Central Facilities (MRL), University of Illinois. We thank Danielle Gray of the School of Chemical Sciences 3M Materials Science Laboratory and Mauro Sardela of MRL for performing XRD analyses. We thank Scott J. Robinson of the Imaging Technology Group at Beckman Institute, University of Illinois for performing ESEM analyses. We thank Seyed A. Dastgheib of Illinois State Geological Survey for performing CO chemisorption analyses. We thank Rudiger Laufhutte of the School of Chemical Sciences Microanalytical Laboratory for performing ICP-MS analyses. We thank Yigang Sun, Liangcheng Yang, and Jingwei Su of the Department of Agriculture and Biological Engineering for performing aggregate size analyses. We thank Jian Li of the Department of Civil and Environmental Engineering for assisting with the regression method.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.