Jean-Marc von Mentlen

1. PREHAL, Christian, MENTLEN, Jean-Marc von, DRVARIČ TALIAN, Sara, VIŽINTIN, Alen, DOMINKO, Robert, AMENTISCH, Heinz, PORCAR, Lionel, FREUNBERGER, Stefan A., WOOD, Vanessa. On the nanoscale structural evolution of solid discharge products in lithium-sulfur batteries using operando scattering. Nature communications. 2022, vol. 13, str. 1-13, ilustr. ISSN 2041-1723. https://www.nature.com/articles/s41467-022-33931-4, https://www.nature.com/articles/s41467-022-33931-4.pdf, DiRROS - Digitalni repozitorij raziskovalnih organizacij Slovenije, DOI: 10.1038/s41467-022-33931-4. [COBISS.SI-ID 128838403]

2. MENTLEN, Jean-Marc von, SENOL, Ayca, DEMUTH, Thomas, BELZ, Jürgen, VIŽINTIN, Alen, VOLZ, Kerstin, WOOD, Vanessa, PREHAL, Christian. Exploring solid conversion products in lithium-sulfur batteries through cryo-TEM and machine-learning-supported small angle neutron scattering. V: EMC 2024 : abstract book : [European Microscopy Congress 2024 : Copenhagen, Denmark, 25 - 30 August 2024]. [S. l.: s. n.], 2024. Str. 375-376. https://emc2024.eu/onewebmedia/EMC2024_NO_Graphics.pdf. [COBISS.SI-ID 208184067]

3. SENOL, Ayca, MENTLEN, Jean-Marc von, RUTHES, Jean G. A., GARCIA SORIANO, Francisco J., DRVARIČ TALIAN, Sara, PRESSER, Volker, PORCAR, Lionel, VIŽINTIN, Alen, WOOD, Vanessa, PREHAL, Christian. Understanding rate and capacity limitations in Li–S batteries based on solid-state sulfur conversion in confinement. ACS applied materials & interfaces. [Online ed.]. Dec. 11, 2024, vol. 16, iss. 49, str. 67651–67661, ilustr. ISSN 1944-8252. https://pubs.acs.org/doi/10.1021/acsami.4c13183, DiRROS - Digitalni repozitorij raziskovalnih organizacij Slovenije, DOI: 10.1021/acsami.4c13183. [COBISS.SI-ID 223119107]

4. MENTLEN, Jean-Marc von, SENOL, Ayca, DEMUTH, Thomas, BELZ, Jürgen, PLODINEC, Milivoj, DUTTA, Pronoy, VIŽINTIN, Alen, PORCAR, Lionel, VOLZ, Kerstin, WOOD, Vanessa, PREHAL, Christian. Unraveling multiphase conversion pathways in lithium–sulfur batteries through cryo transmission electron microscopy and machine learning-assisted operando neutron scattering. ACS nano. 2025, vol. 19, iss. 17, str. 16626–16638. ISSN 1936-086X. https://doi.org/10.1021/acsnano.5c00536, DiRROS - Digitalni repozitorij raziskovalnih organizacij Slovenije, DOI: 10.1021/acsnano.5c00536. [COBISS.SI-ID 237105667]