Neural Network Approach to Study of Langmuir Layers at the Water Surface
A. V. Filimonov, L. A. Valkova, G. A. Ososkov
Abstract
The structure of the layers of a phthalocyanines is studied through a measurement of surface pressure-area isotherms at various initial surface concentrations of the spreaded compound. Layer characteristics are determined from experimental data by replotting the isotherms in accordance with M. Volmer s equation. Neural networks taught on approximations of the isoterms. The method is compared with the traditional least square one. Another task for NN is a forecast of main characteristics of the layers.
Create a lesson
Related papers
When optimized geometries are not optimal: Implications for inverted singlet-triplet gap predictions
Atreyee Majumdar, Elamathi Selvan Samynathan, Raghunathan Ramakrishnan
Open-shell Configuration State Functions as trial states for phaseless auxiliary-field quantum Monte Carlo
Don Danilov, Hugh G. A. Burton, James Shee
Machine Learning the Complete Active-Space Wavefunction Reconstruction
Aniruddha Seal, Bhavnesh Jangid, Helen S. Clifford et al.
Brueckner Orbitals in Local Pair Natural Orbital Coupled-Cluster Theory: DLPNO-BCCD(T) and DLPNO-BCCD(T)Lambda2
Andy Jiang, Tibor Gyori, Elizabeth C. Toth et al.
Exact periodic electrostatics for latent-charge machine-learning potentials
Eslam Ibrahim
Exploiting floating point emulation in tensor contractions in relativistic coupled cluster theory
Maxime Le, Ryan Benazzouk, Jan Brandejs et al.