Zobrazeno 1 - 10
of 246
pro vyhledávání: '"F. Calegari"'
Autor:
D. Mayer, F. Lever, D. Picconi, J. Metje, S. Alisauskas, F. Calegari, S. Düsterer, C. Ehlert, R. Feifel, M. Niebuhr, B. Manschwetus, M. Kuhlmann, T. Mazza, M. S. Robinson, R. J. Squibb, A. Trabattoni, M. Wallner, P. Saalfrank, T. J. A. Wolf, M. Gühr
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-9 (2022)
Imaging the charge flow in photoexcited molecules would provide key information on photophysical and photochemical processes. Here the authors demonstrate tracking in real time after photoexcitation the change in charge density at a specific site of
Externí odkaz:
https://doaj.org/article/5c32a671c326466eaf927fda5b542105
Autor:
Berrens, Margaret L., Andrade, Marcos F. Calegari, Fourkas, John T., Pham, Tuan Anh, Donadio, Davide
Understanding the molecular-level structure and dynamics of ice surfaces is crucial for deciphering several chemical, physical, and atmospheric processes. Vibrational sum-frequency generation (SFG) spectroscopy is the most prominent tool for probing
Externí odkaz:
http://arxiv.org/abs/2410.19980
Autor:
D. Mayer, F. Lever, D. Picconi, J. Metje, S. Alisauskas, F. Calegari, S. Düsterer, C. Ehlert, R. Feifel, M. Niebuhr, B. Manschwetus, M. Kuhlmann, T. Mazza, M. S. Robinson, R. J. Squibb, A. Trabattoni, M. Wallner, P. Saalfrank, T. J. A. Wolf, M. Gühr
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-3 (2022)
Externí odkaz:
https://doaj.org/article/3a574a66caab423e86d95b6140cc6544
Autor:
D. Faccialà, M. Devetta, S. Beauvarlet, N. Besley, F. Calegari, C. Callegari, D. Catone, E. Cinquanta, A. G. Ciriolo, L. Colaizzi, M. Coreno, G. Crippa, G. De Ninno, M. Di Fraia, M. Galli, G. A. Garcia, Y. Mairesse, M. Negro, O. Plekan, P. Prasannan Geetha, K. C. Prince, A. Pusala, S. Stagira, S. Turchini, K. Ueda, D. You, N. Zema, V. Blanchet, L. Nahon, I. Powis, C. Vozzi
Publikováno v:
Physical Review X, Vol 13, Iss 1, p 011044 (2023)
Chirality is widespread in nature, playing a fundamental role in biochemical processes and in the origin of life itself. The observation of dynamics in chiral molecules is crucial for the understanding and control of the chiral activity of photoexcit
Externí odkaz:
https://doaj.org/article/08607be60e024b88bf8837847833d35b
Autor:
Berrens, Margaret, Kundu, Arpan, Andrade, Marcos F. Calegari, Pham, Tuan Anh, Galli, Giulia, Donadio, Davide
The electronic properties and optical response of ice and water are intricately shaped by their molecular structure, including the quantum mechanical nature of hydrogen atoms. In spite of numerous studies appeared over decades, a comprehensive unders
Externí odkaz:
http://arxiv.org/abs/2405.06207
Autor:
Ko, Hsin-Yu, Andrade, Marcos F. Calegari, Sparrow, Zachary M., Zhang, Ju-an, DiStasio Jr, Robert A.
High-throughput DFT calculations are key to screening existing/novel materials, sampling potential energy surfaces, and generating quantum mechanical data for machine learning. By including a fraction of exact exchange (EXX), hybrid functionals reduc
Externí odkaz:
http://arxiv.org/abs/2208.06097
Publikováno v:
Journal of Agricultural Engineering, Vol 44, Iss 2s (2013)
Agrochemical distribution accuracy is critical for an effective intervention with a significant impact both on production costs and on the environment. Here we present the results obtained on processingtomato crops using a sprayer boom with and witho
Externí odkaz:
https://doaj.org/article/6cc9d898221647ac80966bbc6e940a7b
Autor:
A. Trabattoni, M. Klinker, J. González-Vázquez, C. Liu, G. Sansone, R. Linguerri, M. Hochlaf, J. Klei, M. J. J. Vrakking, F. Martín, M. Nisoli, F. Calegari
Publikováno v:
Physical Review X, Vol 5, Iss 4, p 041053 (2015)
Studying the interaction of molecular nitrogen with extreme ultraviolet (XUV) radiation is of prime importance to understand radiation-induced processes occurring in Earth’s upper atmosphere. In particular, photoinduced dissociation dynamics involv
Externí odkaz:
https://doaj.org/article/340c61b08381498597cb3f3bb9d03f5a
We introduce a scheme based on machine learning and deep neural networks to model the environmental dependence of the electronic polarizability in insulating materials. Application to liquid water shows that training the network with a relatively sma
Externí odkaz:
http://arxiv.org/abs/2004.07369
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