Zobrazeno 1 - 10
of 1 198
pro vyhledávání: '"Zipoli, A"'
Spectroscopic techniques are essential tools for determining the structure of molecules. Different spectroscopic techniques, such as Nuclear magnetic resonance (NMR), Infrared spectroscopy, and Mass Spectrometry, provide insight into the molecular st
Externí odkaz:
http://arxiv.org/abs/2407.17492
Autor:
Roy, Swagata, Dürholt, Johannes P., Asche, Thomas S., Zipoli, Federico, Gómez-Bombarelli, Rafael
The reactivity of silicates in an aqueous solution is relevant to various chemistries ranging from silicate minerals in geology, to the C-S-H phase in cement, nanoporous zeolite catalysts, or highly porous precipitated silica. While simulations of ch
Externí odkaz:
http://arxiv.org/abs/2307.01705
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-10 (2024)
Abstract The reactivity of silicates in aqueous solution is relevant to various chemistries ranging from silicate minerals in geology, to the C-S-H phase in cement, nanoporous zeolite catalysts, or highly porous precipitated silica. While simulations
Externí odkaz:
https://doaj.org/article/209b5859bf5748e3a70be35b67a6f5ab
Publikováno v:
npj Computational Materials, Vol 10, Iss 1, Pp 1-14 (2024)
Abstract Machine learning algorithms have shown great accuracy in predicting chemical reaction outcomes and retrosyntheses. However, designing synthesis pathways remains challenging for existing machine learning models which are trained for single-st
Externí odkaz:
https://doaj.org/article/645eb6f591f346859cf2e0c92b6a3894
Autor:
Manica, Matteo, Born, Jannis, Cadow, Joris, Christofidellis, Dimitrios, Dave, Ashish, Clarke, Dean, Teukam, Yves Gaetan Nana, Giannone, Giorgio, Hoffman, Samuel C., Buchan, Matthew, Chenthamarakshan, Vijil, Donovan, Timothy, Hsu, Hsiang Han, Zipoli, Federico, Schilter, Oliver, Kishimoto, Akihiro, Hamada, Lisa, Padhi, Inkit, Wehden, Karl, McHugh, Lauren, Khrabrov, Alexy, Das, Payel, Takeda, Seiji, Smith, John R.
Publikováno v:
Nature Partner Journals (npj) Computational Materials 9, 69 (2023)
With the growing availability of data within various scientific domains, generative models hold enormous potential to accelerate scientific discovery. They harness powerful representations learned from datasets to speed up the formulation of novel hy
Externí odkaz:
http://arxiv.org/abs/2207.03928
Autor:
Kahle, Leonid, Zipoli, Federico
Publikováno v:
Phys. Rev. E 105 (2022), 015311
Neural network potentials (NNPs) combine the computational efficiency of classical interatomic potentials with the high accuracy and flexibility of the ab initio methods used to create the training set, but can also result in unphysical predictions w
Externí odkaz:
http://arxiv.org/abs/2108.05748
Autor:
Matteo Manica, Jannis Born, Joris Cadow, Dimitrios Christofidellis, Ashish Dave, Dean Clarke, Yves Gaetan Nana Teukam, Giorgio Giannone, Samuel C. Hoffman, Matthew Buchan, Vijil Chenthamarakshan, Timothy Donovan, Hsiang Han Hsu, Federico Zipoli, Oliver Schilter, Akihiro Kishimoto, Lisa Hamada, Inkit Padhi, Karl Wehden, Lauren McHugh, Alexy Khrabrov, Payel Das, Seiji Takeda, John R. Smith
Publikováno v:
npj Computational Materials, Vol 9, Iss 1, Pp 1-6 (2023)
Abstract With the growing availability of data within various scientific domains, generative models hold enormous potential to accelerate scientific discovery. They harness powerful representations learned from datasets to speed up the formulation of
Externí odkaz:
https://doaj.org/article/d563c21247234f54b23d37c88d05e3d1
Publikováno v:
Arthroscopy Techniques, Vol 13, Iss 1, Pp 102820- (2024)
Tension band repair frequently is used for small rotator cuff tears. This Technical Note describes a variation using a single knotless suture anchor but with a specific lark’s head knot technique to pass the sutures through the tendon that improves
Externí odkaz:
https://doaj.org/article/e5721cc6114c4ccbb71c85f977dd4f4c
Autor:
Antonio Cardinale, Alessandro Castrogiovanni, Theophile Gaudin, Joppe Geluykens, Teodoro Laino, Matteo Manica, Daniel Probst, Philippe Schwaller, Aleksandros Sobczyk, Alessandra Toniato, Alain C. Vaucher, Heiko Wolf, Federico Zipoli
Publikováno v:
CHIMIA, Vol 77, Iss 7/8 (2023)
The RXN for Chemistry project, initiated by IBM Research Europe – Zurich in 2017, aimed to develop a series of digital assets using machine learning techniques to promote the use of data-driven methodologies in synthetic organic chemistry. This res
Externí odkaz:
https://doaj.org/article/a7d5d4b484f54709884821f7a8e58eba
Autor:
Kahle, Leonid, Cheng, Xi, Binninger, Tobias, Lacey, Steven David, Marcolongo, Aris, Zipoli, Federico, Gilardi, Elisa, Villevieille, Claire, Kazzi, Mario El, Marzari, Nicola, Pergolesi, Daniele
Publikováno v:
Solid State Ionics 347, 115226 (2020)
We study the oxo-hexametallate Li$_7$TaO$_6$ with first-principles and classical molecular dynamics simulations, obtaining a low activation barrier for diffusion of $\sim$0.29 eV and a high ionic conductivity of $5.7 \times 10^{-4}$ S cm$^{-1}$ at ro
Externí odkaz:
http://arxiv.org/abs/1910.11079