arXiv subjects

Davide Bidoggia

Publications and source records attributed to Davide Bidoggia.

3 recordsLinked to original sources

arXiv2026

Defects, Corrugation and Temperature Govern Rarefied-Air Drag on Graphene Coatings

In rarefied atmospheric environments, where continuum fluid dynamics breaks down, aerodynamic drag is governed by gas-surface momentum exchange, making surface structure and chemistry key design knobs. Using molecular dynamics simulations, we show that coating the $α$-Al2O3(0001) surface with graphene markedly reduces the tangential momentum accommodation coefficient (TMAC) of N2, shifting scattering toward more specular reflection and thereby lowering drag; we further benchmark this response against graphite. The reduction strengthens up to 900 K. While structural defects can increase TMAC via defect-induced corrugation and local atomic and electronic rearrangements, graphene retains its performance at experimentally relevant defect densities.

cond-mat.mtrl-sci↗

arXiv2026

AiiDA-TrainsPot: Towards automated training of neural-network interatomic potentials

Crafting neural-network interatomic potentials (NNIPs) remains a complex task, demanding specialized expertise in both machine learning and electronic-structure calculations. Here, we introduce AiiDA-TrainsPot, an automated, open-source, and user-friendly workflow that streamlines the creation of accurate NNIPs by orchestrating density-functional-theory calculations, data augmentation strategies, and classical molecular dynamics. Our active-learning strategy leverages on-the-fly calibration of committee disagreement against ab initio reference errors to ensure reliable uncertainty estimates. We use electronic-structure descriptors and dimensionality reduction to analyze the efficiency of this calibrated criterion, and show that it minimizes both false positives and false negatives when deciding what to compute from first principles. AiiDA-TrainsPot has a modular design that supports multiple NNIP backends, enabling both the training of NNIPs from scratch and the fine-tuning of foundation models. We demonstrate its capabilities through automated training campaigns targeting pristine and defective carbon allotropes, including amorphous carbon, as well as structural phase transitions in monolayer $\mathrm{W_xMo_{1-x}Te_2}$ alloys.

physics.comp-ph↗

arXiv2023

Ultrafast all-optical manipulation of the charge-density-wave in VTe$_{2}$

The charge-density wave (CDW) phase in the layered transition-metal dichalcogenide VTe$_{2}$ is strongly coupled to the band inversion involving vanadium and tellurium orbitals. In particular, this coupling leads to a selective disappearance of the Dirac-type states that characterize the normal phase, when the CDW phase sets in. Here, by means of broadband time-resolved optical spectroscopy (TR-OS), we investigate the ultrafast reflectivity changes caused by collective and single particle excitations in the CDW ground state of VTe$_{2}$. Remarkably, our measurements show the presence of two collective (amplitude) modes of the CDW ground state. By applying a double-pulse excitation scheme, we show the possibility to manipulate these modes, demonstrating a more efficient way to control and perturb the CDW phase in VTe$_{2}$.

cond-mat.str-el↗