PARISI MARIA LAURA
Curriculum Vitae
Teaching activities
Completion accademic year: 2026/2027
Course year: 1
Second cycle degree (Laurea Magistrale)
SUSTAINABLE INDUSTRIAL PHARMACEUTICAL BIOTECHNOLOGY
A.Y. 2026/2027
Course year: 1
Second cycle degree (Laurea Magistrale)
SUSTAINABLE INDUSTRIAL PHARMACEUTICAL BIOTECHNOLOGY
A.Y. 2026/2027
Completion accademic year: 2025/2026
Course year: 1
Second cycle degree (Laurea Magistrale)
SUSTAINABLE INDUSTRIAL PHARMACEUTICAL BIOTECHNOLOGY
A.Y. 2025/2026
Course year: 1
Second cycle degree (Laurea Magistrale)
SUSTAINABLE INDUSTRIAL PHARMACEUTICAL BIOTECHNOLOGY
A.Y. 2025/2026
Completion accademic year: 2024/2025
Course year: 1
Second cycle degree (Laurea Magistrale)
SUSTAINABLE INDUSTRIAL PHARMACEUTICAL BIOTECHNOLOGY
A.Y. 2024/2025
Research
Ultime pubblicazioni:
- Zuffi, C., Mongibello, L., Sinicropi, A., Parisi, M.L. (2026). Cradle-to-Grave LCA and Cost Assessment of Next-Generation Low-Temperature District Heating Networks. PROCESSES, 14(1) [10.3390/pr14010008]. - view more
- Kipyator, M.J., Rossi, F., Alberola‐borràs, J., Vidal, R., Parisi, M.L., Sinicropi, A. (2026). Prospective Environmental Impact Assessment of Scaling Up Perovskite/Silicon Tandem Solar Cells to Industrial Applications. CHEMSUSCHEM, 19(8) [10.1002/cssc.202502409]. - view more
- Zurzolo, S., Romagnoli, G., Braconi, D., Signori, G., Ruggirello, M., Truglio, G., et al. (2026). From Waste to Functional Biomicroreactors: Exploration of Wool-Based Stimuli-Triggered Reversible Pickering Emulsions for Transition Metal Catalysis in Water. ACS SUSTAINABLE CHEMISTRY & ENGINEERING, 14(26), 11680-11694 [10.1021/acssuschemeng.6c03185]. - view more
- Avelar, M., Coppola, C., D'Ettorre, A., Ienco, A., Parisi, M.L., Basosi, R., et al. (2025). In Silico Study of a Bacteriorhodopsin/TiO2 Hybrid System at the Molecular Level. JOURNAL OF CHEMICAL THEORY AND COMPUTATION, 21(6), 3231-3245 [10.1021/acs.jctc.4c01370]. - view more
- Coppola, C., Visibelli, A., Parisi, M.L., Santucci, A., Zani, L., Spiga, O., et al. (2025). A combined ML and DFT strategy for the prediction of dye candidates for indoor DSSCs. NPJ COMPUTATIONAL MATERIALS, 11(1) [10.1038/s41524-025-01521-9]. - view more