Description
A novel approach to chemical bond analysis for excited states has been developed. Using an extended adaptive natural density partitioning method (AdNDP) as implemented in AdNDP 2.0 code, we obtained chemically intuitive bonding patterns for the excited states of H2O, B5+, and C2H4+ molecules. The deformation pathway in the excited states could be easily predicted based on the analysis of the chemical bond pattern. We expect that this new method of chemical bonding analysis would be very helpful for photochemistry, photoelectron spectroscopy, electron spectroscopy and other chemical applications that involved excited states.
Author ORCID Identifier
Alexander I. Boldyrev https://orcid.org/0000-0002-8277-3669
Nikolay Tkachenko https://orcid.org/0000-0002-7296-4293
OCLC
1259528339
Document Type
Dataset
DCMI Type
Dataset
File Format
.zip, .txt, .py, .in, .out, .data, log
Viewing Instructions
Files will need to be unzipped.
Publication Date
6-17-2021
Funder
NSF, Division of Chemistry (CHE)
Publisher
Utah State University
Award Number
NSF, Division of Chemistry (CHE) 1664379
Award Title
Deciphering Delocalized Bonding in Excited States, Solvated Species and Novel 0-, 1-, 2-, and 3-Dimensional Chemical Systems
Methodology
See the README.txt file.
Referenced by
Tkachenko, N. V., & Boldyrev, A. I. (2019). Chemical bonding analysis of excited states using the adaptive natural density partitioning method. Physical Chemistry Chemical Physics, 21(18), 9590–9596. https://doi.org/10.1039/C9CP00379G
Language
eng
Code Lists
N/A
Disciplines
Chemistry
License
This work is licensed under a Creative Commons Attribution 4.0 License.
Identifier
https://doi.org/10.26078/s476-dt02
Recommended Citation
Boldyrev, A. I. (2021). Data from: Chemical bonding analysis of excited states using the adaptive natural density partitioning method. Utah State University. https://doi.org/10.26078/S476-DT02
Checksum
3bcaad2687c0683db26d77d0140b1f1c
Additional Files
README.txt (2 kB)MD5: fc82b6ca54f110c396041a1de21198f6
AdNDP_2.0_manual.pdf (1090 kB)
MD5: f541db271203085fe272ca99cf77c3cf
AdNDP_2.py (37 kB)
MD5: 9cb243694ff82c6c3904b16452c1337d
B5+.zip (2057 kB)
MD5: c20c773b8e7b4ecdef3da82c67a653a2
C2H4+.zip (1805 kB)
MD5: ef02c4116867bb13dd69b84a6bfeafea
CH2I2.zip (9569 kB)
MD5: 0555017e4460402807166fbef89bea91
H2O.zip (602 kB)
MD5: b5b437f9b31229f549d4da4a74c307c5
Supplementary_Information.pdf (115 kB)
MD5: feda9b9cbffbf9c71b9e9fe5f269713d
Comments
Total of 82 files are included, zipped into their original directories.