Literature DB >> 23586344

Characterization of combustion-generated carbonaceous nanoparticles by size-dependent ultraviolet laser photoionization.

Mario Commodo1, Lee Anne Sgro, Patrizia Minutolo, Andrea D'Anna.   

Abstract

Photoelectric charging of particles is a powerful tool for online characterization of submicrometer aerosol particles. Indeed photoionization based techniques have high sensitivity and chemical selectivity. Moreover, they yield information on electronic properties of the material and are sensitive to the state of the surface. In the present study the photoionization charging efficiency, i.e., the ratio between the generated positive ions and the corresponding neutral ones, for different classes of flame-generated carbonaceous nanoparticles was measured. The fifth harmonics of a Nd:YAG laser, 213 nm (5.82 eV), was used as an ionization source for the combustion generated nanoparticles, whereas a differential mobility analyzer (DMA) coupled to a Faraday cup electrometer was used for particle classification and detection. Carbonaceous nanoparticles in the nucleation mode, i.e., sizes ranging from 1 to 10 nm, show a photoionization charging efficiency clearly dependent on the flame conditions. In particular, we observed that the richer the flame is, i.e., the higher the equivalent ratio is, the higher the photon charging efficiency is. We hypothesized that such an increase in the photoionization propensity of the carbonaceous nanoparticles from richer flame condition is associated to the presence within the particles of larger aromatic moieties. The results clearly show that photoionization is a powerful diagnostic tool for the physical-chemical characterization of combustion aerosol, and it may lead to further insights into the soot formation mechanism.

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Year:  2013        PMID: 23586344     DOI: 10.1021/jp401061d

Source DB:  PubMed          Journal:  J Phys Chem A        ISSN: 1089-5639            Impact factor:   2.781


  1 in total

1.  Flame-formed carbon nanoparticles exhibit quantum dot behaviors.

Authors:  Changran Liu; Ajay V Singh; Chiara Saggese; Quanxi Tang; Dongping Chen; Kevin Wan; Marianna Vinciguerra; Mario Commodo; Gianluigi De Falco; Patrizia Minutolo; Andrea D'Anna; Hai Wang
Journal:  Proc Natl Acad Sci U S A       Date:  2019-06-10       Impact factor: 11.205

  1 in total

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