63 citations · 80 across the 9 of their papers we have counts for
6 papers · 1 filter
Hierarchical universal open structure dataset for atomistic modeling
Sofiia Chorna, Cesare Malosso, Jonathan Schmidt +1
Atomic-scale simulations have been transformed by machine-learning models that predict the properties of atomistic structures with the accuracy of quantum calculations, but at a sm…
Transferable machine learning of excited-state dynamics with extremal pooling
Cesare Malosso, Wei Bin How, Gonzalo Díaz Mirón +2
Photochemical processes govern phenomena ranging from solar energy conversion and atmospheric chemistry to vision and photosynthesis. Accurate simulation of these processes require…
Beyond the Virial Expansion: Microscopic Origins of Partial Molar Volumes in LiCl Solutions
Chun-Ting Lin, Diganta Dasgupta, Tinglu Yang +6
Although electrolyte density measurements have been reported for over a century, employing them to obtain accurate partial molar volume (PMV) profiles as a function of salt concent…
Comparing the latent features of universal machine-learning interatomic potentials
Sofiia Chorna, Davide Tisi, Cesare Malosso +3
The past few years have seen the development of ``universal'' machine-learning interatomic potentials (uMLIPs) capable of approximating the ground-state potential energy surface ac…
The Photochemical Birth of the Hydrated Electron in Liquid Water
Gonzalo Díaz Mirón, Cesare Malosso, Solana Di Pino +4
The photophysics and photochemistry associated with irradiating UV light in liquid water is central to numerous physical, chemical and biological processes. One of the key events i…
Aqueous Solution Chemistry In Silico and the Role of Data Driven Approaches
Debarshi Banerjee, Khatereh Azizi, Colin K. Egan +14
The use of computer simulations to study the properties of aqueous systems is, today more than ever, an active area of research. In this context, during the last decade there has b…