Prediction of Combined Sorbent and Catalyst Materials for SE-SMR, Using QSPR and Multitask Learning.

Nkulikiyinka P, Wagland ST, Manovic V, Clough PT

DOI: 10.1021/acs.iecr.2c00971
Published: 2022 Jul 6
Container: Industrial & engineering chemistry research
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1021/acs.iecr.2c00971,
  title = {Prediction of Combined Sorbent and Catalyst Materials for SE-SMR, Using QSPR and Multitask Learning.},
  author = {Nkulikiyinka P and Wagland ST and Manovic V and Clough PT},
  year = {2022},
  journal = {Industrial \& engineering chemistry research},
  doi = {10.1021/acs.iecr.2c00971},
  url = {https://doi.org/10.1021/acs.iecr.2c00971}
}

RIS

TY  - JOUR
TI  - Prediction of Combined Sorbent and Catalyst Materials for SE-SMR, Using QSPR and Multitask Learning.
AU  - Nkulikiyinka P
AU  - Wagland ST
AU  - Manovic V
AU  - Clough PT
PY  - 2022
JO  - Industrial & engineering chemistry research
DO  - 10.1021/acs.iecr.2c00971
UR  - https://doi.org/10.1021/acs.iecr.2c00971
ER  -

APA

P, N., ST, W., V, M., & PT, C. (2022). Prediction of Combined Sorbent and Catalyst Materials for SE-SMR, Using QSPR and Multitask Learning.. Industrial & engineering chemistry research. https://doi.org/10.1021/acs.iecr.2c00971

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pubmed · retrieved 2026-11-10T12:04:53.737Z