Publications

Shengli Jiang, Nanqi Bao, Alexander D Smith, Shraddha Byndoor, Reid C Van Lehn, Manos Mavrikakis, Nicholas L Abbott, Victor M Zavala (2023). Scalable Extraction of Information from Spatio-Temporal Patterns of Chemoresponsive Liquid Crystals Using Topological Data Analysis. ChemRxiv preprint ChemRxiv:2023-fjcxd-v2.

PDF Cite Code

Shiyi Qin, Shengli Jiang, Jianping Li, Prasanna Balaprakash, Reid C Van Lehn, Victor M Zavala (2022). Capturing molecular interactions in graph neural networks: a case study in multi-component phase equilibrium. Digital Discovery, 2.1 (2023): 138-151.

PDF Cite Code

Fei Long, Shengli Jiang, Adeyinka Gbenga Adekunle, Victor M Zavala, Ezra Bar-Ziv (2022). Online Characterization of Mixed Plastic Waste Using Machine Learning and Mid-Infrared Spectroscopy. ACS Sustainable Chemistry & Engineering 10.48 (2022): 16064-16069.

PDF Cite Code

Shengli Jiang, Shiyi Qin, Joshua L Pulsipher, Victor M Zavala (2022). Convolutional Neural Networks: Basic Concepts and Applications in Manufacturing. arXiv preprint arXiv:2210.07848.

PDF Cite

Nanqi Bao, Shengli Jiang, Alexander D Smith, James J Schauer, Manos Mavrikakis, Reid C Van Lehn, Victor M Zavala, Nicholas L Abbott (2022). Sensing Gas Mixtures by Analyzing the Spatiotemporal Optical Responses of Liquid Crystals Using 3D Convolutional Neural Networks. ACS Sensors 7.9 (2022): 2545-2555.

PDF Cite

Stas Zinchik, Shengli Jiang, Soren Friis, Fei Long, Lasse Hogstedt, Victor M Zavala, Ezra Bar-Ziv (2021). Accurate Characterization of Mixed Plastic Waste Using Machine Learning and Fast Infrared Spectroscopy. ACS Sustainable Chemistry & Engineering 9.42 (2021): 14143-14151.

PDF Cite Code

Shengli Jiang, Xu Zhuo, Medhavi Kamran, Stas Zinchik, Sidike Paheding, Armando G McDonald, Ezra Bar-Ziv, Victor M Zavala (2021). Using ATR-FTIR spectra and convolutional neural networks for characterizing mixed plastic waste. Computers & Chemical Engineering 155 (2021): 107547.

PDF Cite Code

Shengli Jiang, Victor M Zavala (2021). Convolutional neural nets in chemical engineering: Foundations, computations, and applications. AIChE Journal 67.9 (2021): e17282.

PDF Cite Code

Shengli Jiang, Prasanna Balaprakash (2020). Graph neural network architecture search for molecular property prediction. 2020 IEEE International conference on big data (big data). IEEE, 2020.

PDF Cite Code

Shengli Jiang, JungHyun Noh, Chulsoon Park, Alexander D Smith, Nicholas L Abbott, Victor M Zavala (2020). Using machine learning and liquid crystal droplets to identify and quantify endotoxins from different bacterial species. Analyst 146.4 (2021): 1224-1233.

PDF Cite

Alex K Chew, Shengli Jiang, Weiqi Zhang, Victor M Zavala, Reid C Van Lehn (2020). Fast predictions of liquid-phase acid-catalyzed reaction rates using molecular dynamics simulations and convolutional neural networks. Chemical science 11.46 (2020): 12464-12476.

PDF Cite Code

Fei Ji, Li Wang, Jason Yang, Xu Wu, Mingqian Li, Shengli Jiang, Shihong Lin, Zheng Chen (2018). Highly compact, free-standing porous electrodes from polymer-derived nanoporous carbons for efficient electrochemical capacitive deionization. Journal of Materials Chemistry A 7.4 (2019): 1768-1778.

PDF Cite

Fei Ji, Yang Shi, Mingqian Li, Shengli Jiang, Gen Chen, Fang Liu, Zheng Chen (2018). Scalable synthesis of uniform nanosized microporous carbon particles from rigid polymers for rapid ion and molecule adsorption. ACS applied materials & interfaces 10.30 (2018): 25429-25437.

PDF Cite

Yang Shi, Hanmei Tang, Shengli Jiang, Laure V Kayser, Mingqian Li, Fang Liu, Fei Ji, Darren J Lipomi, Shyue Ping Ong, Zheng Chen (2018). Understanding the electrochemical properties of naphthalene diimide: implication for stable and high-rate lithium-ion battery electrodes. Chemistry of Materials 30.10 (2018): 3508-3517.

PDF Cite