422 citations · 729 across the 17 of their papers we have counts for
17 papers
Quantifying Perovskite Solar Cell Degradation via Machine Learning from Spatially Resolved Multimodal Luminescence Time Series
Giulio Barletta, Simon Ternes, Saif Ali +7
Perovskite solar cells achieve remarkable power conversion efficiencies, yet operational stability remains a major barrier to large-scale deployment. Reliable and rapid assessment…
Screening novel cathode materials from the Energy-GNoME database using MACE machine learning force field and DFT
Nada Alghamdi, Paolo de Angelis, Pietro Asinari +1
The development of new battery materials, particularly novel cathode chemistries, is essential for enabling next generation energy storage technologies. In this work, we employ a m…
Comparing fine-tuning strategies of MACE machine learning force field for modeling Li-ion diffusion in LiF for batteries
Nada Alghamdi, Paolo de Angelis, Pietro Asinari +1
Machine learning force fields (MLFFs) are transforming materials science and engineering by enabling the study of complex phenomena, such as those critical to battery operation. In…
Notes on Quantum Computing for Thermal Science
Pietro Asinari, Nada Alghamdi, Paolo De Angelis +6
This document explores the potential of quantum computing in Thermal Science. Conceived as a living document, it will be continuously updated with experimental findings and insight…
Energy-GNoME: A Living Database of Selected Materials for Energy Applications
Paolo De Angelis, Giovanni Trezza, Giulio Barletta +2
Artificial Intelligence (AI) in materials science is driving significant advancements in the discovery of advanced materials for energy applications. The recent GNoME protocol iden…
Enhancing ReaxFF for Molecular Dynamics Simulations of Lithium-Ion Batteries: An interactive reparameterization protocol
Paolo De Angelis, Roberta Cappabianca, Matteo Fasano +2
Lithium-ion batteries (LIBs) are crucial for the green economy, powering portable electronics, electric vehicles, and renewable energy systems. The solid-electrolyte interphase (SE…
Mesoscopic modeling and experimental validation of thermal and mechanical properties of polypropylene nanocomposites reinforced by graphene-based fillers
Atta Muhammad, Rajat Srivastava, Nikos Koutroumanis +7
The development of nanocomposites relies on structure-property relations, which necessitate multiscale modeling approaches. This study presents a modelling framework that exploits…
The impact of physicochemical features of carbon electrodes on the capacitive performance of supercapacitors: A machine learning approach
Sachit Mishra, Rajat Srivastava, Atta Muhammad +4
Hybrid electric vehicles and portable electronic systems use supercapacitors for energy storage owing to their fast charging discharging rates, long life cycle, and low maintenance…
Single Relaxation Time and Multiple Revised Matrix Lattice Boltzmann Simulations of Forced Isotropic Turbulence
Waleed Abdel Kareem, Pietro Asinari, Sauro Succi +2
The single relaxation time (SRT) and the revised matrix (RM) lattice Boltzmann models are compared for simulations of three dimensional forced isotropic turbulence with resolutions…
Towards Fairness Certification in Artificial Intelligence
Tatiana Tommasi, Silvia Bucci, Barbara Caputo +1
Thanks to the great progress of machine learning in the last years, several Artificial Intelligence (AI) techniques have been increasingly moving from the controlled research labor…
Passive high-yield seawater desalination at below one sun by modular and low-cost distillation
Eliodoro Chiavazzo, Matteo Morciano, Francesca Viglino +2
Although seawater is abundant, desalination is energy-intensive and expensive. Using the sun as an energy source is attractive for desalinating seawater; however, the performance o…
Link-wise Artificial Compressibility Method
Pietro Asinari, Taku Ohwada, Eliodoro Chiavazzo +1
The Artificial Compressibility Method (ACM) for the incompressible Navier-Stokes equations is (link-wise) reformulated (referred to as LW-ACM) by a finite set of discrete direction…
Nonequilibrium steady solutions of the Boltzmann equation
Davide Proment, Miguel Onorato, Pietro Asinari +1
We report a study of the homogeneous isotropic Boltzmann equation for an open system. We seek for nonequilibrium steady solutions in presence of forcing and dissipation. Using the…
Enhancing heat transfer in nanofluids by carbon nanofins
Eliodoro Chiavazzo, Pietro Asinari
Nanofluids are suspensions of nanoparticles and fibers which have recently attracted much attention due to their superior thermal properties. Here, nanofluids are studied in the se…
Fast computation of multi-scale combustion systems
Eliodoro Chiavazzo, Filippo Visconti, Pietro Asinari
In the present work, we illustrate the process of constructing a simplified model for complex multi-scale combustion systems. To this end, reduced models of homogeneous ideal gas m…
Nonlinear Boltzmann equation for the homogeneous isotropic case: Minimal deterministic Matlab program
Pietro Asinari
The homogeneous isotropic Boltzmann equation (HIBE) is a fundamental dynamic model for many applications in thermodynamics, econophysics and sociodynamics. Despite recent hardware…
Factorization symmetry in lattice Boltzmann simulations
Ilya Karlin, Shyam Chikatamarla, Pietro Asinari
A non-perturbative algebraic theory of lattice Boltzmann method is developed based on a symmetry of a product. It involves three steps: (i) Derivation of admissible lattices in one…