U
Ursula Rothlisberger
Researcher at École Polytechnique Fédérale de Lausanne
Publications - 338
Citations - 24706
Ursula Rothlisberger is an academic researcher from École Polytechnique Fédérale de Lausanne. The author has contributed to research in topics: Density functional theory & Excited state. The author has an hindex of 68, co-authored 322 publications receiving 20418 citations. Previous affiliations of Ursula Rothlisberger include Curtin University & University of Milan.
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Optimization of Effective Atom Centered Potentials for London Dispersion Forces in Density Functional Theory
TL;DR: Without any prior assignment of types and structures of molecular fragments, the corrected generalized gradient approximation density functional theory calculations yield correct equilibrium geometries and dissociation energies of argon-argon, benzene-benzene, graphite-graphite, and argon and benzene complexes.
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Vapor-assisted deposition of highly efficient, stable black-phase FAPbI3 perovskite solar cells.
Haizhou Lu,Yuhang Liu,Paramvir Ahlawat,Aditya Mishra,Wolfgang Tress,Felix Eickemeyer,Yingguo Yang,Fan Fu,Zaiwei Wang,Claudia E. Avalos,Brian Carlsen,Anand Agarwalla,Xin Zhang,Xiaoguo Li,Yiqiang Zhan,Shaik M. Zakeeruddin,Lyndon Emsley,Ursula Rothlisberger,Li-Rong Zheng,Anders Hagfeldt,Michael Grätzel +20 more
TL;DR: A deposition method using methylammonium thiocyanate vapor treatment to convert δ-FAPbI3 to the desired pure α-phase below the thermodynamic phase-transition temperature is shown.
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New Paradigm in Molecular Engineering of Sensitizers for Solar Cell Applications
Takeru Bessho,Eiji Yoneda,Jun-Ho Yum,Matteo Guglielmi,Ivano Tavernelli,Hachiro Imai,Ursula Rothlisberger,Mohammad Khaja Nazeeruddin,Michael Grätzel +8 more
TL;DR: The present findings provide new design criteria for the next generation of ruthenium sensitizers and help foster widespread interest in the engineering of new sensitizer that interact effectively with the I(-)/I(3)(-) redox couple.
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Mixed Quantum Mechanical/Molecular Mechanical Molecular Dynamics Simulations of Biological Systems in Ground and Electronically Excited States
TL;DR: By using feature selection algorithms to identify the most appropriate subset of relevant variables that describe a certain phenomenon, the high-dimensionality of QM/MM data can be reduced and used for further analysis with causal inference algorithms to establish unique cause-effect relationships.
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Trajectory Surface Hopping within Linear Response Time-Dependent Density-Functional Theory
TL;DR: A fewest switches trajectory surface hopping algorithm based on linear response time-dependent density-functional theory and a scheme to calculate nonadiabatic couplings using a multi determinantal approximation of the excited state wave function is introduced.