HKUST Electronic Theses Deep-neural-network approaches to deconvolve distribution functions of relaxation times from electrochemical impedance spectroscopy data
by Quattrocchi Emanuele
THESIS
2023
Ph.D. Mechanical and Aerospace Engineering
1 online resource (xxvi, 174 pages) : illustrations (some color)
Access
Not presently available for public access at author's request
Abstract
*CONFIDENTIAL*
Permanent URL for this record: https://lbezone.hkust.edu.hk/bib/991013160253703412
Post a Comment