Accelerating Discovery of WX2-Based Gas Sensors (X = S, Se, and Te) for C4F7N Decomposed Species via Density Functional Theory and Machine Learning.

Cui H, Pu Y, Wu H, Zhang Y, Zhang X, Hu J

Open source

DOI
10.1021/acssensors.6c01416
Published
2026 Jul 24
Container
ACS sensors
Publisher
Not recorded
Open access
unknown

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BibTeX

@article{allodium:10.1021/acssensors.6c01416,
  title = {Accelerating Discovery of WX2-Based Gas Sensors (X = S, Se, and Te) for C4F7N Decomposed Species via Density Functional Theory and Machine Learning.},
  author = {Cui H and Pu Y and Wu H and Zhang Y and Zhang X and Hu J},
  year = {2026},
  journal = {ACS sensors},
  doi = {10.1021/acssensors.6c01416},
  url = {https://doi.org/10.1021/acssensors.6c01416}
}

RIS

TY  - JOUR
TI  - Accelerating Discovery of WX2-Based Gas Sensors (X = S, Se, and Te) for C4F7N Decomposed Species via Density Functional Theory and Machine Learning.
AU  - Cui H
AU  - Pu Y
AU  - Wu H
AU  - Zhang Y
AU  - Zhang X
AU  - Hu J
PY  - 2026
JO  - ACS sensors
DO  - 10.1021/acssensors.6c01416
UR  - https://doi.org/10.1021/acssensors.6c01416
ER  -

APA

H, C., Y, P., H, W., Y, Z., X, Z., & J, H. (2026). Accelerating Discovery of WX2-Based Gas Sensors (X = S, Se, and Te) for C4F7N Decomposed Species via Density Functional Theory and Machine Learning.. ACS sensors. https://doi.org/10.1021/acssensors.6c01416

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