Alfredo Serrano Jiménez

(EN)
- Developed high-dimensional neural-network potential energy surfaces (NN PES) to model interaction energies and forces for O and CO coadsorbed on Pd(111) [O+2CO/Pd(111)], using an autonomous active-learning training loop with automated dataset expansion; validated them against reference ab initio data.
- Applied the NN PES to molecular dynamics simulations of femtosecond laser–induced proce

Developed high-dimensional neural-network potential energy surfaces (NN PES) for O and CO coadsorbed on Pd(111) using an autonomous active-learning training loop, and applied them to molecular dynamics simulations of femtosecond laser-induced processes. Simulated two-pulse correlation on CO/Pd(111) to quantify desorption probability as a function of pulse delay.

(EN)
- Developed neural-network potential energy surfaces (NN PES) for carbon monoxide adsorbed on palladium [CO/Pd(111)] at different coverages; validated them against ab initio molecular dynamics reference data.
- Applied these NN PES to large-scale molecular dynamics simulations to study femtosecond laser–induced desorption and gas–surface interactions, including dependence on fluence, coverag

(EN)
- Performed computational research focused on weak-field coherent control in the ultrafast photodissociation of methyl iodide (CH₃I) using pairs of time-delayed laser pulses.
- Developed scientific code in Fortran with MPI-based parallelization to run large-scale simulations and analyze photofragment distributions.
- Executed calculations on HPC clusters, including SLURM job scripting and Li

PhD Thesis URL: https://cfm.ehu.es/view/files/PhD_Thesis_Alfredo_Serrano_Jimenez_definitive_print_version.pdf

Doctoral research in Physics of Nanostructures and Advanced Materials, focusing on neural-network potential energy surfaces and molecular dynamics simulations.

Master's degree in Quantum Science & Technology.

Bachelor's degree in Physics.